Aerial Insectivorous Birds Linked to Water Quality and Climate in Urbanizing Landscapes

Thesis

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the

Graduate School of The Ohio State University

By

Joseph William Corra

Graduate Program in Environment and Natural Resources

The Ohio State University

2019

Thesis Committee

Dr. S. Mažeika P. Sullivan, Advisor

Dr. Stephen N. Matthews

Dr. Rachel S. Gabor

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Copyrighted by

Joseph William Corra

2019

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Abstract

Aerial insectivorous birds – a guild comprising swallows, nightjars, swifts, and flycatchers – have experienced alarming population declines in eastern North America in recent decades.

Although declines in individual bird species may be linked to other causes, including loss or fragmentation of suitable breeding habitat and habitat degradation in tropical wintering grounds, similar declines across multiple, taxonomically diverse species in the guild indicate that changes in flying prey is likely a common factor. Aerial insectivores breeding in urban areas – comprising 69.4 million acres (3.6% of total) in the contiguous United States and continuing to expand – are affected by multiple environmental changes, including alterations to local climate, habitat structure, and water quality, as well as potential shifts in both terrestrial and emergent aquatic insect prey. Emergent aquatic have recently been shown to provide energetic advantages to aerial insectivorous birds relative to terrestrial insects, yet they are highly sensitive to changes in water quality.

Here, I used the Tree Swallow (Tachycineta bicolor) to investigate potential associations between aerial insectivorous birds and urbanization, local climate, and water quality.

Specifically, I evaluated Tree Swallow reproductive success, body condition, and trophic dynamics at seven river-riparian sites representing urban and natural/protected land use in greater

Columbus, Ohio over four consecutive breeding seasons (2014-2017). Study sites with impervious surface in the watershed >25% were classified as urban. Urban nests were associated with higher fledging success (linear mixed-effects model [LMM]: p = 0.009) and earlier clutch initiation (LMM: p = 0.060). Nestling mass was not related to land use (LMM: p = 0.930) but

ii exhibited high interannual variability (LMM: p = 0.006), as did body condition in adult males

(LMM: p = 0.010), and mercury (Hg) in both adults (LMM: p = 0.080), and nestlings (LMM: p <

0.001). The interaction of year × land use also had a significant influence on nestling Hg (LMM: p < 0.001). I also used an Urban Stream Index (USI) to explore potential relationships between continuous measures of stream urbanization (e.g., nutrient concentrations, riparian canopy cover, water temperature) and swallow reproductive success and body condition and found that the USI was related to greater fledging success (R2 = 0.16, p < 0.001). Multiple characteristics of urban sites appeared to drive patterns between swallow responses and urbanization, including differences in mean and extreme air temperatures and measures of water quality (e.g., water temperature, nutrient concentrations, turbidity). For example, higher mean air temperature was associated with earlier clutch initiation (R2 = 0.06, p = 0.039), while the frequency of extremely cold days was related to diminished fledging success (R2 = 0.14, p = 0.003).

Relative to trophic position, I investigated the relationships between urbanization and Tree

Swallow (Tachycinenta bicolor) reliance on aquatically derived energy (i.e., originating from aquatic primary production) and trophic position. Bayesian mixing models using 13C and 15N isotopes showed that nutritional reliance on both aquatic primary production and aquatic insects had significant interannual variability. Reliance on aquatic insects by nestling swallows exhibited a significant interaction of year × land use (LMM: p < 0.001), suggesting a possible relationship between elevated total N in the water column and aquatic insect consumption. Trophic position of adult swallows was 8.3% higher at urban than at natural/protected sites (LMM: p = 0.020), whereas nestlings exhibited high interannual variability in trophic position (LMM: p < 0.001), but were not related to land use (LMM: p = 0.720). My results for reliance on aquatic insects,

iii aquatically derived energy, and trophic position all revealed a strong random effect of site, suggesting that local-scale water chemistry and land-use/land-cover characteristics may play a prominent role in shaping flying insect assemblages and driving aquatic-terrestrial energetic pathways. Supporting this finding, I also observed strong relationships between the USI and swallow trophic dynamics: USI was related to greater reliance on aquatic insects among both adult and nestling swallows (adults: R2 = 0.10, p = 0.036; nestlings: R2 = 0.23, p < 0.001), greater reliance on aquatically derived energy (adults: R2 = 0.14, p = 0.019; nestlings: R2 = 0.20, p <

0.001), and higher trophic position (adults: R2 = 0.23, p = 0.001; nestlings: R2 = 0.22, p < 0.001).

Overall, despite the loss of environmental quality generally attributed to cities, Tree

Swallows exhibited greater reproductive success in urban settings where aquatic insects were larger, local climate conditions favored egg and nestling survival, and the breeding season was longer. However, the chronic effect of elevated Hg body burdens in urban areas represents a potentially adverse impact for urban-breeding aerial insectivores. For trophic measures, gradients of urbanization appeared to mediate nutritional reliance on aquatic resources and trophic position more strongly than did a coarser, categorical classification of urbanization. Aerial insectivore energetics may have important implications for long-term population trends as related to fitness, migration survival, exposure to contaminants, and reproductive success. However, owing to differences in foraging strategy, nesting strategy, and dietary preferences, the responses of other aerial insectivorous species to urbanization may vary. Determining the composite effects of urbanization on aerial insectivores represents an important research agenda as we continue to address declining aerial insectivore populations.

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Acknowledgments

I would like to thank Kira Edic, Kaitlin Carr, Jenny Sanderson, Kate Gorman, and

Maggie Woodworth for their tireless work with field data collection and lab processing.

In addition, I would like to extend a special thanks to Jeffry Hayes, Reina Tyl, and

Danielle Vent for their role in directing data collection, developing field and lab work protocols, and managing the field teams. Thanks to Lars Meyer for logistical support in the field and in the lab. To Dr. David Manning and Kristen Diesburg – your help with R saved countless hours. To my committee members Dr. Stephen Matthews, Dr. Rachel

Gabor, and especially my advisor Dr. Mažeika Sullivan: I would like to express my gratitude for sharing your time, expertise, and knowledge throughout this process.

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Vita

2014 …………………………………………. B.S., Science, Mathematics, and

Technology, SUNY Empire State College

2016 …………………………………………. Graduate Fellow, School of Environment

and Natural Resources, The Ohio State

University

2018 to present ………………………………. Graduate Research Assistant, School of

Environment and Natural Resources, The

Ohio State University

Fields of Study

Major Field: Environment and Natural Resources

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Table of Contents

Abstract...... ii

Acknowledgments...... v

Vita...... vi

List of Tables...... ix

List of Figures...... xi

Chapter 1. Introduction...... 1

Chapter 2: Urbanization mediates the effects of water quality and climate on

Tree Swallow (Tachycineta bicolor) body condition and reproductive success.... 51

Abstract...... 52

Introduction...... 53

Methods...... 58

Results...... 67

Discussion...... 70

Conclusion...... 77

Chapter 3: Riparian aerial insectivorous bird trophic dynamics linked to urbanization of streams ...... 116

Abstract...... 117

Introduction...... 118

Methods...... 121

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Results...... 129

Discussion...... 131

Conclusion...... 138

Complete References...... 173

Appendix A. Chapter 2: Supplemental Material...... 196

Appendix B. Chapter 3: Supplemental Material...... 225

Appendix C. Permits...... 226

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List of Tables

Table 2.1 Study sites with impervious surface cover (% of total within 500-m on each side of the stream channel) and land-use designation based on impervious surface cover (Urban or Natural/Protected). Study reaches were categorized by adapting the thresholds developed by Schueler (1994): those < 25% impervious surface were categorized as Natural/Protected, and those reaches > 25% impervious surface were designated as Urban...... 103

Table 2.2 Water-chemistry variables for natural/protected vs. urban study sites, including means and standard deviations across the 4 years of the study...... 104

Table 2.3 Eigenvalues and the percent variance captured by the principal components (eigenvalues > 1), along with each principal component’s loadings and the proportion of the variance R2) each variable shared with the PCA axes. Only the first axis (PC1) was used for analyses...... 105

Table 2.4 Results from linear mixed-effects models with fixed (Year, Land Use [urban or protected], and Year × Land Use) and random (site, nestbox, site × nestbox). ** indicates a significant (p < 0.05) effect. * indicates evidence of a trend; i.e., 0.5 ≥ p < 0.10. Marginal R² = variation explained by fixed effects alone, while conditional R² = variation explained by both fixed and random effects...... 106

Table 3.1 Results from linear mixed-effects models with fixed (year, land use [urban or protected], and year × land use) and random (site, nestbox, site × nestbox). ** indicates a significant (p < 0.05) effect. * indicates evidence of a trend; i.e., 0.5 ≥ p < 0.10. Marginal R² = variation explained by fixed effects alone, while conditional R² = variation explained by both fixed and random effects. TP = trophic position. ADE = aquatically derived energy (i.e., nutritional subsidies originating from periphyton)...... 164

Table A.1 Study site coordinates, stream order, land use category (defined by % impervious surface), and % impervious surface coverage...... 197

Table A.2 Invertebrates collected 2014-2017, by year, site, season (early/late), transect (top/bottom), family, 10-day count, and mean mass (total family dry mass / count). Note that samples from both transects were pooled in 2015, so no transect is listed (entries represent totals for each family from both transects)...... 198

Table B.1 Carbon (ẟ13C) and nitrogen (ẟ15N) isotopic signatures for Tree Swallows. 226

Table B.2 Carbon (ẟ13C) and nitrogen (ẟ15N) isotopic signatures for dominant insect families...... 236 ix

Table B.3 Carbon (ẟ13C) and nitrogen (ẟ15N) isotopic signatures for primary production sources (detritus and periphtyton)...... 241

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List of Figures

Figure 1.1 Percent population change among selected avian groups/guilds in Canada, 1970-2010. Source: Environment Canada, 2013...... 2

Figure 1.2 Tree Swallow range. Source: Cornell Lab of Ornithology, 2015...... 5

Figure 1.3 (a) 4-day-old Tree Swallow nestlings. Photo credit: Reina Tyl; (b) Adult male (left) and female (right) Tree Swallows. Photo credit. L. Villablanca...... 6

Figure 1.4 Food-web linkages between aquatic and riparian systems. Solid lines indicate strong pathways, while dashed lines indicate weaker pathways. From Sullivan & Rodewald (2012)...... 8

Figure 1.5 (a) Experimental treatment reaction norms for Tree Swallows for six body condition metrics. Black represents diets low in long-chain omega-3 polyunsaturated fatty acids; gray represents diets low in these fatty acids. From Twining, et al. (2017). 11

Figure 1.6 Female Tree Swallows in both the control and experimental groups (the latter with clipped wings to handicap foraging ability) produced, on average, smaller clutches as the breeding season advanced. From Nooker, Dunn, & Whittingham (2005)...... 20

Figure 1.7 Monthly means for day-to-day temperature variability for two paired North American urban-rural sites. Urban sites had consistently greater variability of the maximum daily temperature, while the reverse was true for rural sites. From Tam, Gough, & Mohsin (2015)...... 22

Figure 1.8 Example of a dual isotope (mean ± 1 SE) plot of 15N and 13C for aquatic and terrestrial food web components in the Scioto River basin (Ohio, USA) for (a) rural and (b) urban river reaches. Four-letter codes represent riparian swallow species. From Alberts, Sullivan, and Kautza (2013)...... 24

Figure 1.9 Map of study sites in the Scioto River system in metropolitan Columbus (OH, USA). Dark green-shaded areas indicate forested land cover. Source: Homer, et al., 2015 and QGIS Dev Team, 2017...... 25

Figure 2.1 Conceptual model showing the hypothesized relationships among urbanization, climate, water quality, flying insects, and aerial insectivorous birds. Local climate and land-use characteristics are expected to exert both direct effects (e.g., habitat availability) and indirect effects (via impact on invertebrate assemblages) on bird condition and reproductive success...... 107

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Figure 2.2 Study sites and land cover in the greater Columbus, Ohio area. Source: Homer, et al., 2015 and QGIS Dev Team, 2017...... 108

Figure 2.3 Annual means from 2014-2017 by land use (i.e., protected or urban) for local climate variables across the breeding season (30 April-28 June): (a) air temperature °C, (b) humidity (%), (c) no. of days of extreme cold, and (d) number of days of extreme heat. Error bars indicate +/- 1 SE...... 109

Figure 2.4 Annual means from 2014-2017 by land use (i.e., natural or urban) for flying insect (a) family richness, (b) abundance (i.e., capture rate of individuals / m2 10-day-1, and (c) median body size (mg, dry mass). Emergent aquatic insects (left) and terrestrial insects (right) are shown separately. Error bars indicate +/- 1 SE...... 110

Figure 2.5 Annual means from 2014-2017 by land use (i.e., protected or urban) for reproductive response: (a) clutch size (no. eggs) (LMM: p = 0.710), (b) clutch initiation date (Julian date, calendar days) (LMM: p = 0.060) (c) no. successfully fledged (LMM: p = 0.009), and (d) nestling mass (g) (LMM: p = 0.150). Error bars indicate +/- 1 SE. ... 111

Figure 2.6 Relationships between the number of successfully fledged nestlings and (a) the Urban Stream Index (R2 = .16, F = 5.30, p < 0.001) and (b) the number of days of extreme cold between 30 April-28 June (R2 = .14, F = 4.31, p = 0.003). For the regression lines, red = 2014, green = 2015, blue = 2016, and purple = 2017...... 112

Figure 2.7 Relationships between (a) nestling mass (g) and the number of days of extreme heat between 30 April-28 June (R2 = 0.15 , F = 4.36, p < 0.003); and (b) clutch initiation date (Julian date, no. calendar days) and mean air temperature (°C) between 30 April and 29 May (R2 = 0.06 , F = 2.62, p = 0.039). For the regression lines, red = 2014, green = 2015, blue = 2016, and purple = 2017...... 113

Figure 2.8 Annual means from 2014-2017 by land use (i.e., protected or urban) for individual body condition: (a) Scaled Mass Index (g) for with females (F) (LMM: p = 0.680) and males (M) (LMM: p = 0.650), (b) blood mercury (Hg) concentration (ppb) for adults (LMM: p = 0.420) and nestlings (LMM: p = 0.920), and (c) blood glucose concentration (mg/dL) for adults and nestlings (LMM: p = 0.310). Error bars are +/- 1 SE. Note that there are only three years of data for blood mercury concentration (2014- 2016) and one year for glucose (2017). Glucose levels for adults were not tested due to small sample size, but their results are included for reference...... 114

Figure 2.9 Relationship between blood Hg concentration (ppb) in adult Tree Swallows and the Urban Stream Index (R2 = 0.53, F = 9.212, p < 0.001). For the regression lines, red = 2014, green = 2015, and blue = 2016. Hg was log10-transformed; however, the figure above shows the raw values...... 115

Figure 3.1 Tree Swallow study sites in urban and natural/protected areas in the greater Columbus, Ohio area. Source: Homer, et al., 2015 and QGIS Dev Team, 2017...... 165 xii

Figure 3.2 Annual means from 2015-2017 by land use (i.e., natural/protected or urban) for Tree Swallow trophic position of: (a) adults (LMM: p = 0.020) and (b) nestlings at ~13 days (LMM: p = 0.430). Error bars indicate +/- 1 SE. Different letters A, B indicate significant pairwise differences...... 166

Figure 3.3 Annual means from 2015-2017 by land use (i.e., natural/protected or urban) for Tree Swallow nutritional reliance on aquatically derived energy (e.g., originating from algae/periphyton) for (a) adults (LMM: p = 0.490) and (b) nestlings at ~13 days (LMM: p = 0.570). Error bars indicate +/- 1 SE. Different letters A, B indicate significant pairwise differences...... 167

Figure 3.4 Relationships between the Urban Stream Index (USI) for study sites and Tree Swallow trophic position for (a) 2015, (b) 2016, and (c) 2017. Separate multiple regression models with year as a categorical variable were developed for adults (R2 = 0.23, F = 6.04, p = 0.001) and nestlings (R2 = 0.22, F = 24.75, p < 0.001). For the regression lines, gold = adult swallows and green = nestlings at ~13 days...... 168

Figure 3.5 Relationships between Urban Stream Index and Tree Swallow nutritional reliance on emergent aquatic insects (vs. terrestrial flying insects) for (a) 2014, (b) 2015, and (c) 2016, and (d) 2017. Separate multiple regression models with year as a categorical variable were developed for adults (R2 = 0.10, F = 2.77, p = 0.036) and nestlings (R2 = 0.23, F = 23.40, p < 0.001). For the regression lines, pink = adult swallows and blue = nestlings at ~13 days...... 169

Figure 3.6 Composition of emergent aquatic and terrestrial flying insects (by percentage) in Tree Swallows diets across all study sites, 2014-2017. Sites are organized according to their Urban Stream Index (USI), with the lowest (i.e., least urbanized) on the left, and highest on the right. Note that positions of each plot are laterally equidistant from one another for display purposes, and do not necessarily reflect the magnitude of the USI. Blue = emergent aquatic insects, brown = terrestrial insects. Results for adult swallows are shown on the left side of each plot, nestlings on the right...... 170

Figure 3.7 Tree Swallow nutritional reliance on aquatically derived energy (e.g., originating from algae/periphyton) across all study sites, 2015-2017. Sites are organized according to their Urban Stream Index (USI), with the lowest (i.e., least urbanized) on the left, and highest on the right. Note that positions of each plot are laterally equidistant from one another for display purposes, and do not necessarily reflect the magnitude of the USI. Results for adult swallows are shown on the left side of each plot, nestlings on the right...... 171

Figure 3.8 Relationships between Tree Swallow nutritional reliance on emergent aquatic insects and reliance on aquatically derived energy (e.g., originating from algae/periphyton) for (a) early-season insects, (b) late-season insects. Separate linear regression models were developed for early-season insects and adult swallows (R2 = 0.01, F = 0.76, p = 0.390) early-season insects and nestlings (R2 = 0.01, F = 3.87, p = 0.050), xiii late-season insects and adult swallows (R2 = 0.01, F = 1.03, p = 0.318), and late-season insects and nestlings (R2 = 0.01, F = 3.41, p = 0.066). For the regression lines, pink = adult swallows and blue = nestlings at ~13 days...... 172

Figure B.1 Annual means from 2014-2017 by land use (i.e., natural/protected or urban) and period (May or July) for Tree Swallow nutritional reliance on emergent aquatic insects (vs. terrestrial flying insects). Flying insects prey are represented by the two most numerically abundant aquatic and terrestrial families in each season per study site. (a) Early season insects consumed by adults (LMM: p = 0.380), (b) early season insects consumed by nestlings at ~13 days (LMM: p = 0.310), (c) late season insects consumed by adults (LMM: p = 0.770), (d) late season insects consumed by nestling at ~13 days (LMM: p = 0.640). Error bars indicate +/- 1 SE. Different letters A, B indicate significant pairwise differences...... 245

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Chapter 1. Introduction

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Aerial insectivorous birds – a guild comprising swallows, nightjars, swifts, and flycatchers – have experienced alarming population declines in eastern North America in recent decades (Environment Canada, 2012; Nebel et al., 2010) (Figure 1.1). Although the cause of these population declines is not yet fully understood, they are likely anthropogenic in origin.

Possible environmental attributes connected to the decline of aerial insectivorous bird populations include the availability and quality of flying insect prey populations which, in turn, are shaped by environmental conditions (Nebel et al., 2010). Although declines in individual bird species may be linked to other causes, including loss or fragmentation of suitable breeding habitat (MacHunter et al., 2006) and degradation or loss of habitat in tropical wintering grounds

(Fraser et al., 2012), similar declines across multiple, taxonomically diverse species in the guild indicate that changes in insect prey are likely a common factor.

Figure 1.1 Percentage population change among selected avian groups/guilds in Canada, 1970-2010. Source: Environment Canada, 2013.

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Riparian zones can be hotspots of aerial insectivorous bird diversity (Naiman & Decamps, 1997).

Although aerial insectivorous birds are terrestrial organisms, they are often highly dependent on aquatic ecosystems (Uesugi & Murakami, 2007). Therefore, changes in the condition of streams, rivers, lakes, and wetlands might be expected to influence many facets of aerial insectivorous bird ecology, including nutrition and energetics (e.g., Kautza & Sullivan, 2016), nearshore and riparian habitat conditions (Naiman & Decamps, 1997), health (Smits & Fernie, 2013), and reproductive success (McCarty & Secord, 1999). In particular, predator-prey relationships between birds and aquatic insects may be shaped by changes in chemical water quality, vegetation structure and cover, and environmental contaminants (Alberts, Sullivan, & Kautza,

2013).

Additional lines of evidence suggest that urbanization of the landscape may contribute to aerial insectivorous bird population declines (Nebel et al., 2010; Schlesinger, Manley, &

Holyoak, 2008). Urban encroachment in the riparian zone is associated with profound changes in avian community composition, population density (Blair, 1996; Miller et al., 2003; Rodewald &

Bakermans, 2006), and reproductive success (Rodewald, Kearns, & Shustack, 2013). These changes have been linked to the consequences of urban land use change, such as the removal of riparian vegetation (Lussier et al., 2006), habitat fragmentation and altered vegetation structure

(Crooks, Suarez, & Bolger, 2004), and the increased presence of invasive biota (Rottenborn,

1999). Further, intensification of urbanization is associated with decreased invertebrate density and species richness (Macivor & Lundholm, 2011; Urban et al., 2006) and this relative paucity of available prey may be implicated in reduced reproductive success observed among aerial insectivores breeding in urban areas (Teglhøj, 2017). Environmental contaminants can also have

3 a considerable impact on wild bird populations. Mercury, for instance, has been related to diminished reproductive success, even at relatively low blood concentrations (Rowse, Rodewald,

& Sullivan, 2014), and urbanization of watersheds is associated with increased mercury concentrations in stream sediment (Chalmers et al., 2014; Lutz et al., 2009).

Finally, the effects of climate change may be exerting quantitatively important effects on avian reproductive success and survival (Both et al., 2010; Hussell, 2003). Long-term data on

Tree Swallows (Tachycineta bicolor) in Canada revealed a negative impact on fledging success and brood size associated with both increased air temperatures and higher rainfall during the breeding season (McArthur et al., 2017). Changes in climate and local weather conditions may also exacerbate the effects of other environmental variables. For instance, evidence suggests an interactive effect between increased air temperatures and the aforementioned reproductive impacts associated with mercury exposure (Hallinger & Cristol, 2011). Considered together, the complex relationships between climate, water quality, and land use change demand a broad perspective to address their impacts on aerial insectivorous birds.

Background

Tree Swallow – a model aerial insectivore

The Tree Swallow is a secondary cavity-nesting passerine associated with riparian areas

(Rendell & Robertson, 1989). The species is migratory, wintering along the Gulf Coast, in

Mexico, the Caribbean, and Central America before returning north in the early spring (Butler,

1988; Robertson, Stutchbury, & Cohen, 2011). The Tree Swallow’s breeding range extends coast to coast through most of North America, from Alaska to northernmost California in the west, and

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Newfoundland south to northern Georgia in the east (Robertson, Stutchbury, & Cohen, 2011)

(Figure 1.2).

Figure 1.2 Tree Swallow range. Source: Cornell Lab of Ornithology, 2015.

Tree Swallows are primarily aerial insectivores, catching flying insects on the wing.

Although adult Tree Swallows can supplement their diets with vegetable matter such as bayberries during winter or early spring migration (Piland & Winkler, 2015), adults and young are dependent on flying insects during the breeding season (Mengelkoch, Niemi, & Regal, 2004;

Nooker, Dunn, & Whittingham, 2005). Both male and female parents (Fig. 1.3a) forage for flying insects to feed nestlings (Fig. 1.3b), with increased rates of feeding as nestlings age

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(Leffelaar & Robertson, 1986). Adult swallows provision nestlings frequently throughout the day, delivering a bolus of captured insects to nestlings on each return trip to the nest (McCarty,

2002). Tree Swallows prey on a wide variety of invertebrates, primarily flies, true bugs, and dragonflies and damselflies, but also many mayflies, caddisflies, beetles, wasps, stoneflies, other flying insects and occasionally spiders and other nonflying terrestrial invertebrates (Beck,

Hopkins, & Jackson, 2014; Mengelkoch, Niemi, & Regal, 2004; Quinney & Ankney, 1985).

When foraging, invertebrate body size may be a more important factor in prey selection than (Hespenheide, 1971), as swallows preferentially select larger-bodied prey (McCarty &

Winkler, 1999a). Nevertheless, small-bodied insects (<10mm in length) still often constitute the larger proportion of their diets (Quinney & Ankney, 1985).

Figure 1.3 (a) Adult male (left) and female (right) Tree Swallows. Photo credit. L. Villablanca. (b) 4-day-old Tree Swallow nestlings. Photo credit: Reina Tyl.

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Tree Swallows are cavity nesters, and reproduction may therefore be site-limited by the number of available cavities (Stutchbury & Robertson, 1985). Clutch initiation varies depending on latitude. In Ohio, laying usually commences in May, though the timing of reproduction has been linked to air temperature, food abundance, intraspecific competition, and geography (Dunn

& Winkler, 1999; Nooker, Dunn, & Whittingham, 2005). A mated pair of Tree Swallows will typically have a single brood in a season, though two broods are not uncommon in the southern parts of their range (Monroe et al., 2008). Female swallows lay one egg per day, with a typical clutch size of 5 or 6 eggs (Rendell & Robertson, 1993); however, clutch size varies and increased food availability has been linked to larger clutch size (Hussell & Quinney, 1987). Hatching occurs 14-16 days after laying, and nestlings fledge 18-21 days after hatch (Hussell & Quinney,

1987). Ambient temperature and food availability have been associated with nestling growth rates and nestling mass (McCarty & Winkler, 1999b). Lifespan is about three years, on average, though individuals may live up to eight years (Butler, 1988).

Energetic linkages between aquatic and terrestrial ecosystems

Many riparian terrestrial consumers, including Tree Swallows and other aerial insectivores, are nutritionally linked to aquatic ecosystems via their dietary reliance on adult, emergent aquatic insects (Figure 1.4). Cross-system subsidies are a key component of the relationship between streams and the adjacent riparian zones (Baxter, Fausch, & Saunders, 2005;

Power & Dietrich, 2002). The food webs of streams and riparian areas are connected via the transfer of nutrients, prey, and detritus (Polis, Anderson, & Holt, 1997). Fluxes of emergent aquatic insects constitute a critical resource subsidy to adjacent terrestrial food webs, including

7 insectivorous avian consumers (Nakano & Murakami, 2001). In the other direction, allochthonous subsidies (i.e., those originating outside the stream system), such as leaf litter and terrestrial invertebrates (Nakano & Murakami, 2001; Wallace et al., 1997) provide important resource inputs to the recipient aquatic systems (Richardson & Sato, 2015).

Figure 1.4 Food-web linkages between aquatic and riparian systems. Solid lines

indicate strong pathways, while dashed lines indicate weaker pathways. From The importance of insect prey to avian consumers is evidenced by the latter’s Sullivan & Rodewald (2012).

distribution, and evidence strongly suggests that insect prey availability can shape the spatial distribution of insectivorous birds. In fact, distributions of insects have been found to exert substantial influence over the distribution of many terrestrial-consumer taxa (Burdon & Harding,

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2008; Kautza & Sullivan, 2016b; Muehlbauer et al., 2014). Prey availability has emerged as a strong predictor of avian insectivore distribution, with fluctuations in avian abundance tracking emergent aquatic insect abundance within season for some species (Murakami & Nakano, 2002;

Razeng & Watson, 2015).

Even insectivorous birds nesting in areas spatially distant from riparian zones may rely on aquatic systems for food. Uesugi and Murakami (Uesugi & Murakami, 2007) found that emergent aquatic insects can constitute an important food source for insectivorous upland forest birds as well, which congregate and forage in riparian areas in the early spring prior to bud break. Insect abundance, including that of terrestrial insect taxa, may be more strongly associated with riparian vegetation rather than upland vegetation in forested landscapes, driving many bird species to forage near streams (Hagar et al., 2012). Evidence suggests that insectivorous birds will alter the geographic scope of their foraging habits to take advantage of seasonal fluctuations in prey subsidies from both aquatic and terrestrial sources (Uesugi & Murakami, 2007). This effect is especially pronounced among many terrestrial consumers that move toward aquatic zones to take advantage of insect subsidies during peak emergence (Baxter, Fausch, & Saunders,

2005). For instance, seasonal changes in insect emergence have been linked to local densities of insectivorous birds across different habitat types (Gray, 1993). Insectivorous bird abundance also may be strongly influenced by insect assemblage composition and distribution (Hagar et al.,

2012; Hussell & Quinney, 1987).

Among aquatic insects, the orders Ephemeroptera (mayflies), Plecoptera (stoneflies), and

Trichoptera (caddisflies) (collectively referred to as EPT) are generally more sensitive to changes in water quality and therefore the richness and relative abundance of these taxa are commonly

9 used as indicators of stream condition (Compin & Céréghino, 2003; Lenat, 1988). The relatively large-bodied EPT taxa insects are typically associated with less-disturbed streams and serve as an important food source to many aerial insectivores, including Tree Swallows (Hussell &

Quinney, 1987; McCarty & Winkler, 1999a). Research on the prey preferences of other guilds of insectivorous birds has produced similar findings. In temperate forests, gleaners and ground foragers were observed to prefer prey taxa with higher body fat and micronutrient content than low-frequency prey taxa (Razeng & Watson, 2015). Similarly, Heinrich, Whiles, and Roy observed that the abundance of larger-bodied insect taxa was correlated with avian abundance and species richness (2014). Experimental evidence also suggests that aquatic insects confer an energetic advantage over terrestrial insects. In a study that underscores that importance of aquatic insects for insectivorous birds, Twining et al. (2016) showed that Tree Swallow nestlings exhibited faster growth rates and better body condition when provisioned with aquatic insects rich in long-chain omega-3 polyunsaturated fatty acids. Twining et al. (2018) (Fig. 1.5a) further demonstrated that the availability of high-quality aquatic insect prey (Fig. 1.5b) was related to increased fledging success among Tree Swallows.

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Figure 1.5 (a) Experimental treatment reaction norms for Tree Swallows for six body condition metrics. Black represents diets low in long-chain omega-3 polyunsaturated fatty acids; gray represents diets low in these fatty acids. From Twining, et al. (2017). (b) Magnified contents of a single Tree Swallow bolus collected in June 2017 in Columbus, OH (USA). Insects in bolus comprise 23 caddiesflies (Family Hydropsychidae) and 2 long-legged flies (Family Dolichopodidae, not shown).

Just as aerial insectivorous birds are influenced by distributions of emergent insect prey, the composition and distribution of aquatic insect assemblages can be shaped by their environment. For instance, stream discharge, morphology, and other stream characteristics regulate aquatic insect production and, consequently, are strongly connected to the distribution of

11 a variety of insectivorous birds (Gray, 1993). Water chemistry can also strongly impact aquatic insects (Allan & Flecker, 1993; Johnson et al., 2013). Human alteration and management of the landscape can have profound and far-reaching effects on both terrestrial and aquatic ecosystems.

Anthropogenic change to watersheds, including deforestation, agricultural use, impoundments, stream channelization, and the introduction of invasive organisms can have strong effects on populations of both riparian birds and their insect prey (Fausch, Baxter, & Murakami, 2010;

Kautza & Sullivan, 2015; Rioux-Paquette et al., 2014). In a study in the Scioto River system of

Ohio, Kautza and Sullivan (2015) found that higher densities larger-bodied taxa were associated with rural river reaches compared to river reaches in developed landscapes. Strasevicius et al.

(2013) found that emergent aquatic insect subsidies to adjacent forests were reduced by a full order of magnitude along river reaches in Sweden modified for hydropower production.

Availability of insect prey is associated with egg quality (Ardia, Wasson, & Winkler,

2006), nestling survival and body condition (Quinney et al., 1986), brood size and body mass

(Teglhøj, 2017), nestling immune response (Lifjeld, Dunn, & Whittingham, 2002), and oxidative damage in adult individuals (Stanton, Lark, & Morrissey, 2017) among various aerial insectivorous bird species. Overall, evidence suggests aerial insectivores suffer from the diminished abundance and quality of their insect prey. For example, Poulin, Levebre and Paz

(2010) demonstrated a link between the suppression of flying invertebrates via pesticide applications and reduced clutch sizes and fledging success in European House Martins (Delichon urbicum).

Reductions in emergent aquatic insect prey subsidies are reflected in the reproductive success of avian consumers. Research on insectivorous Pied Flycatchers (Ficedula hypoleuca)

12 has shown that reduced aquatic insect subsidies are linked to lower hatchling survival rates

(Strasevicius et al., 2013). The quality of prey is important as well. As songbird fledgling mass has been strongly linked to post-fledging avoidance of predation (Naef-Daenzer & Grüebler,

2016), the diminished condition of smaller swallows could impair their odds of survival.

Environmental variability

Land-use and land-cover change

As rivers and streams are inexorably connected to their surrounding landscapes, the character of those landscapes in instrumental in determining the conditions of the lotic systems that flow through them (Allan, 2004). Consequently, shifts in land use and land cover can have significant impacts on both insectivorous birds and their invertebrate prey. Reduced taxonomic diversity of birds and invertebrates is associated with the built environments of urban areas

(McKinney, 2002). Diversity of invertebrates in urbanized landscapes may be significantly reduced due to habitat loss and fragmentation, pollution of soil and water, and the proliferation of introduced exotic organisms (McIntyre, 2000). Linked aquatic-riparian ecosystems are affected by land use change in multiple ways, as changes in upstream riparian zones can have sizeable impacts on aquatic systems downstream by altering flow regimes, stormwater discharge, and sediment loads (Booth & Jackson, 1998). Engineering of stream channels to accommodate development usually results in reduced channel complexity and a concomitant homogenization of in-stream habitat (Walsh et al., 2005), with negative impacts on emergent insect density

(Iwata, Nakano, & Murakami, 2003). In contrast, less-developed riparian zones are typically characterized by substantial differences in the taxonomic composition of aquatic insect

13 assemblages, with more sensitive taxa more strongly represented. For example, evidence indicates that lower densities of residential land use are associated with increases in

Ephemeroptera (Freeman & Schorr, 2004; Lussier et al., 2008).

Deforestation is associated with many kinds of land-use changes and may substantially alter aquatic insect assemblages in both urban and rural stream reaches. Besides providing energy inputs, terrestrial leaf debris provides habitat for many aquatic insects, enhancing in- stream invertebrate diversity (Compson et al., 2013). Larger materials from trees, like large wood, also provide nutrients and habitat to aquatic biota, and the magnitude and composition of these inputs can be altered by landscape changes (Richardson & Sato, 2015). Alteration or removal of riparian vegetation may influence birds’ spatial foraging patterns; for instance, Tree

Swallows living in urban riparian areas may be more reliant on aquatic subsidies for food, compared to their rural counterparts (Alberts, Sullivan, & Kautza, 2013).

Among land-use changes, urbanization may produce the most pervasive and long-lasting impacts (Ren et al., 2003). Commercial, industrial, and residential land use has been associated with nutrient pollution, increased sediment loads, and the loss of sensitive benthic insect taxa from streams (Klein, 1980). Erosion and deposition of sediment increase substantially in urban stream reaches due to the presence of impervious surfaces, increased flow, and higher localized stream gradients (Meyer, Paul, & Taulbee, 2005; Walsh et al., 2005). Channelized streams in developed landscapes, subject to increased runoff, are often characterized by a more homogenous in-stream morphology and altered substrate size (Arnold, Boison, & Patton, 1982;

Grable & Harden, 2006). Impaired streams in more developed areas were found to exhibit features of Urban Stream Syndrome; i.e., elevated levels of nutrients and toxic contaminants,

14 altered flow regimes with a flashier hydrograph, wider channels, higher water temperatures, fewer sensitive aquatic taxa, and simplified stream morphology (Vietz, Walsh, & Fletcher, 2015;

Walsh et al., 2005). Nitrogen and phosphorus enrichment is typically higher in streams in developed landscapes (Paul & Meyer, 2001; Tromboni & Dodds, 2017). Eutrophication is associated with increased algal biomass, with negative impacts on aquatic systems including elevated pH, reduced light penetration, and depletion of dissolved oxygen (Chislock et al., 2013).

Together, these changes have well-documented harmful consequences for aquatic biota and ecosystem function (Dodds & Smith, 2016; Smith, Tilman, & Nekola, 1998). Other adverse effects on aquatic systems associated with urbanized land use changes associated include increased salinity, reduced dissolved oxygen content, increased sedimentation, and elevated levels of coliform bacteria (Peters, 2009). Although stream restoration projects have become increasingly popular endeavors in recent decades, the long-term impacts of urbanization have proved challenging to reverse (Kondolf, 1995). Even restored urban streams may exhibit diminished aquatic invertebrate richness, underscoring the pervasive character the urban environment’s influence at the watershed scale (Violin et al., 2011).

Habitat loss and impairment strongly influence aquatic invertebrate communities and often lead to substantial declines in species richness of benthic macroinvertebrates on a gradient toward the urban center (McKinney, 2002; Walsh et al., 2001). Overall aquatic insect diversity has been shown to be negatively associated land development in the watershed, particularly the increased land coverage by impervious surfaces (Gage, Spivak, & Paradise, 2004). In such environments, the diversity of aquatic insect assemblages is diminished and the relatively small- bodied, tolerant Chironomidae (midges) are frequently the dominant insect family (Heinrich,

15

Whiles, & Roy, 2014). In contrast, insects of the EPT taxa are often sensitive to poor water quality and are suppressed by the poor stream conditions brought on by urbanization (Roy et al.,

2003).

Environmental contaminants

Environmental contaminants in aquatic systems can affect survival and reproductive success of both aquatic and terrestrial organisms, as linked aquatic-terrestrial food webs can facilitate the bioaccumulation and transfer of trace contaminants to terrestrial consumers. PCBs, for example, are readily transferred by aquatic insects to terrestrial consumers with associated negative impacts on the individual health and reproductive success of songbirds (McCarty &

Secord, 1999; Walters, Fritz, & Otter, 2008) including Tree Swallows (Custer et al., 2003).

Similar effects on Tree Swallow populations have been shown for other contaminants found in aquatic systems, including selenium (Ohlendorf et al., 1988), various contaminants associated with mine tailings (Gentes et al., 2006) and wastewater effluent (Dods et al., 2005), including pharmaceuticals (Richmond et al., 2018).

Among the environmental contaminants found in aquatic systems, mercury is one of the most pervasive and hazardous, and consequently one of the best-studied (Morel, Kraepiel, &

Amyot, 1998). Concentrations of environmental mercury are relatively high in eastern North

America (Driscoll et al., 2007). Elevated levels of mercury in the environment are a byproduct of human activities, particularly combustion of fossil fuels, which release mercury into the atmosphere (Pirrone et al., 2010). Because mercury is both persistent and mobile in the atmosphere, it can be distributed far beyond its point sources (Li & Cai, 2013). As a pollutant,

16 mercury can be hazardous to organisms in its inorganic form, but it becomes a far more potent neurotoxin when converted by microbial processes to organic methylmercury (Boening, 2000;

Munthe et al., 2007). Methylmercury biomagnifies in food webs, with the greatest impact on consumers at the highest trophic levels (Driscoll et al., 2007).

A number of studies have shown a relationship between blood-mercury levels and impaired reproduction in various aquatic and marine birds, including reduced hatchability, lower chick survival rates, and lower chick weights (Burger & Gochfeld, 1997; Fimreite, 1974). Long- term exposure to dietary methylmercury in passerine birds is associated with reduced fledging success (Varian-Ramos, Swaddle, & Cristol, 2014). Similar responses to elevated blood- mercury levels have been observed in insectivorous passerines that nest in riparian habitats, including Tree Swallows (Brasso & Cristol, 2008) and Carolina Wrens (Jackson et al., 2011).

Hallinger and Cristol (Hallinger & Cristol, 2011) demonstrated that elevated levels of blood mercury in adult Tree Swallows were associated with diminished hatching and fledging success.

At higher concentrations, elevated mercury levels can impair immune system response in adult

Tree Swallows (Hawley, Hallinger, & Cristol, 2009). The negative impact of methylmercury may manifest at concentrations too low to produce health impacts in adult birds. For instance, a study of Acadian flycatchers by Rowse, Rodewald, and Sullivan (2014) revealed a strong relationship between elevated blood mercury levels and lower reproductive success, even when mercury concentrations were below the threshold of a predicted negative health response.

The transfer of mercury from aquatic systems to terrestrial consumers can be strongly mediated by aquatic insects (Cristol et al., 2008; Powell, 1983, Sullivan & Rodewald 2012), which suggests that biomagnification of mercury will be high in insectivorous birds, due to their

17 trophic position (Evers et al., 2005). Differences in environment and life history of aerial insectivores play a role in exposure to mercury. Prey selection plays an important role in the transfer of contaminants, suggesting that biomagnification will vary across species of insectivorous birds (Beck, Hopkins, & Jackson, 2014). In addition, land-use and land-cover changes may play a regulatory role in the flux of these contaminants from aquatic systems to terrestrial consumers. Aquatic systems in areas experiencing elevated deposition of inorganic mercury will not necessarily exhibit higher concentrations of methylmercury in aquatic organisms (Chalmers et al., 2014). Lastly, land-use changes can alter the relationship between aquatic systems and terrestrial consumers by altering insect food assemblages and influencing the spatial extent of avian foraging efforts (Alberts, Sullivan, & Kautza, 2013).

Climate change

Climate change has the potential to exert substantial impacts on bird populations and their phenology, including the timing of breeding and migration, reproductive success, and the ranges of individual species (Crick, 2004; McCarty, 2001). In Ohio, 55% of bird species are projected to be climate threatened or climate endangered (i.e., in danger of losing more than 50% of their current range by 2080 or 2050, respectively) if present warming trends continue (Langham et al.,

2014). Climate change may impact aerial insectivorous birds through both direct and indirect means. Warming climates are likely driving phenological changes in Tree Swallows (Winkler,

Dunn, & McCulloch, 2002). Specifically, emerging evidence shows that increasing spring temperatures are related to earlier clutch initiation dates (Bourret et al., 2015; Hussell, 2003); in

18 fact, long-term data from 1959-1991 show a 9-day advance in Tree Swallow clutch initiation

(Dunn & Winkler, 1999).

Experimental treatments suggest that Tree Swallows commence breeding based on immediate food availability, rather than aligning breeding to take advantage of peak food availability for hatchlings (Nooker, Dunn, & Whittingham, 2005), highlighting the influence of early-spring insect emergence as a driver of clutch initiation. Climate change is predicted to exert a similar influence on emergent aquatic flying insects, with potentially adverse effects on birds from the temporal decoupling of hatching and food availability (Visser et al., 1998). Both climate change and encroaching urbanization tend to warm streamwater temperature (Nelson &

Palmer, 2007). Streamwater temperatures have shown a strong correlation with changes in air temperature (Pilgrim, Fang, & Stefan, 1999), with substantial impacts projected for aquatic invertebrates (Durance & Ormerod, 2007). Rising temperatures throughout the year may have an impact on aquatic insect populations, as water temperature serves as a critical cue for insect emergence (Learner & Potter, 1974). Warmer winter temperatures are associated with earlier emergence (Nebeker, 1971). Experimental evidence has shown that changes in water temperature can influence both the timing of aquatic insect emergence (Harper & Peckarsky,

2006; Nordlie & Arthur, 1981) and the composition of emergent insect assemblages in streams

(Jonsson et al., 2015). Extended periods of warm temperatures may spur early incubation of eggs as well, possibly advancing hatch dates in Tree Swallows and promoting asynchronous hatching

(Ardia, Cooper, & Dhondt, 2006). Owing to the importance of aquatic insect emergence for breeding swallows, it is possible that shifts to the timing of clutch initiation, hatching, and fledging may become increasingly asynchronous with aquatic insect emergence, limiting Tree

19

Swallows from fully exploiting a critical food source (Thomas et al., 2001). Experimental treatments conducted by Nooker, Dunn, and Whittingham (2005) (Fig. 1.6) provided evidence to support such links among insect emergence, clutch initiation, and Tree Swallow reproductive success: earlier clutch initiation was related to insect abundance and, in turn, larger clutches and heavier nestlings.

Figure 1.6 Female Tree Swallows in both the control and experimental groups (the latter with clipped wings to handicap foraging ability) produced, on average, smaller clutches as the breeding season advanced. From Nooker, Dunn, & Whittingham (2005).

Apart from the direct impact of climate on the abundance of composition of insect prey assemblages, a changing climate may have other detrimental effects on insectivorous bird populations. Meteorological conditions may affect the foraging success of birds in complex ways, via impacts on the foraging capabilities of adult birds, or by altering flying insect activity.

For instance, bird broods hatched early may succumb to cold snaps, either from direct thermal

20 stress or due to a paralysis of the flying insect food supply (Winkler, Luo, & Rakhimberdiev,

2013) as the ability of insects to fly is suppressed by low temperatures (Taylor, 1963). Similarly, unusually warm weather may limit nestling growth. Pipoly et. al (2013) showed a negative relationship between periods of extreme heat and body condition in House Sparrows (Passer domesticus), another cavity-nesting songbird. Precipitation during the breeding season may also play a role, as sustained high rainfall has been associated with diminished reproductive success in Tree Swallows, either due to the suppression of foraging by adult birds or, more directly, by increased mortality of nestlings due to nest saturation (McArthur et al., 2017).

Conversely, increasing temperatures may also have a beneficial impact on aerial insectivorous birds under certain conditions. Experimental treatments by Perez et al. (2008) observed that Tree Swallow nestlings in artificially-heated nests exhibited better body condition, likely due to increased provisioning activity by adult females. The work of Pipoly et al. (2013) also demonstrated that, despite the unfavorable consequences of extreme heat on nestling body condition, overall higher mean temperatures during the breeding season were associated with increased nestling body mass. Similarly, McCarty and Winkler (1999b) revealed that the positive effect of temperature was strongly evident in the growth of Tree Swallow nestlings.

Global climate change is not the only driver behind variation in climate conditions.

Urbanization also has dramatic local impacts on temperature variability, particularly in large cities, where mean temperatures may be several degrees higher than in adjacent rural areas (Oke,

1982). Built environments with extensive impervious surfaces are characterized by diminished evapotranspiration and limited shade due to reduced vegetation, lower surface albedo, reflective vertical surfaces, suspended airborne particulate matter, and anthropogenic heat sources, all of

21 which contribute to the urban heat island effect (Oke, 1982; US EPA, 2008). Notably, among the

60 largest cities in the United States, Columbus was identified as the 8th most intense of its urban heat island from 2004-2014 (Kenward et al., 2014). Patterns of daily temperature variation differ as well. Tam, Gough, and Mohsin (2015) (Fig. 1.7) observed that urban areas had greater day-to- day temperature variability than surrounding rural areas, driven by greater variability in maximum daily temperatures and, in contrast, more stable minimum temperatures. Conversely, rural sites had greater heat loss and therefore greater temperature variability at night. The differences in temperature regimes illustrate the outsized role played by urbanization of the landscape.

Figure 1.7 Monthly means for day-to-day temperature variability for two paired North American urban-rural sites. Urban sites had consistently greater variability of the maximum daily temperature, while the reverse was true for rural sites. From Tam, Gough, & Mohsin (2015).

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Food webs and stable isotope analysis

The nature of food webs can reveal the relationships between terrestrial secondary consumers (e.g. aerial insectivorous birds), their diets, and trophically linked aquatic-riparian ecosystems (e.g., Collier, Bury, & Gibbs, 2002; Kautza & Sullivan, 2016b). Analysis of stable isotopes is a key tool to ascertain these pathways (Layman et al., 2012; Peterson & Fry, 1987).

Isotopes of carbon (12C and 13C) and nitrogen (14N and 15N) are commonly used in such analyses

(Post, 2002). These stable (i.e., not radioactive) isotopes occur naturally and each pair is identical in terms of most chemical reactions; however, they can be differentiated by their nuclear masses, an attribute which allows the ratio of isotopes to be measured (Fry, 2006).

Enrichment of 15N relative to 14N occurs in consumers with increases in trophic level (Minagawa

& Wada, 1984). In contrast, ratios of carbon isotopes are more stable as carbon moves through food webs (Post, 2002), and they reflect the photosynthetic pathways of primary production

(Rounick & Winterbourn, 1986). By examining the ratios of these isotopes, the dietary contributions of terrestrial and aquatic sources – as well as of terrestrial vs. aquatic insects – to aerial insectivorous birds can be estimated (e.g., Kautza & Sullivan, 2016), as can trophic position and food chain-length (e.g., Kautza & Sullivan, 2016a; Post, Pace, & Hairston, 2002) .

In broad strokes, ratios of 15N in tissues is useful for estimating a consumer’s trophic position

(Cabana & Rasmussen, 1996; Minagawa & Wada, 1984), while 13C ratios yield information about dietary sources (Bearhop et al., 1999, 2002; Caquet, 2006; DeNiro & Epstein, 1978;

Harvey & Kitchell, 2000) (Fig. 1.8).

23

Figure 1.8 Example of a dual isotope (mean ± 1 SE) plot of 15N and 13C for aquatic and terrestrial food web components in the Scioto River basin (Ohio, USA) for (a) rural and (b) urban river reaches. Four-letter codes represent riparian swallow species. From Alberts, Sullivan, and Kautza (2013).

Study system

My study area consists of seven river-riparian sites on an urban-forested gradient in the

Scioto River system (Ohio, USA). The Scioto River watershed drains 16868-km2 as it flows south into the Ohio River (Ohio Environmental Protection Agency, 2014). The central portion of the Scioto River catchment lies within the Columbus Metropolitan Area. The study sites are 24 located on the Scioto, a 6th-order river, plus two major tributaries, the Olentangy River and Big

Darby Creek (Fig. 1.9). The regional landscape is composed overwhelmingly of developed

(45%) or cultivated (40%) lands, with forests comprising only 6% of the total land cover (Ohio

Environmental Protection Agency, 2014).

Figure 1.9 Map of study sites in the Scioto River system in metropolitan Columbus (OH, USA). Red circles indicate the urban study sites. Dark green- shaded areas indicate forested land cover. Source: Homer, et al., 2015 and QGIS Dev Team, 2017.

Objectives

The overarching objective of this research was to quantify the relationships between urbanization, water quality, climate, and aerial insectivores across an urban-rural landscape gradient in central Ohio’s Scioto River basin. This research builds on several years of data

25

collected by Dr. Sullivan’s Stream and River Ecology (STRIVE) Lab in the greater Columbus,

Ohio area since 2011. I addressed this objective through the following specific goals:

1. Investigate linkages among landscape urbanization, local climate, water quality, and reproductive

success and body condition of Tree Swallows.

a. Quantify land-use and land-cover (LULC) at the local (e.g., 500-m buffer) and landscape

(e.g., catchment draining to each study site) scale at seven river reaches in and around

Columbus, Ohio.

b. Assess chemical water-quality conditions (e.g., turbidity, pH, contaminants) at study

reaches.

c. Assess composition, abundance, and availability of aquatic and terrestrial insect

assemblages at study reaches.

d. Monitor air temperature and humidity at Tree Swallow nest boxes.

e. Evaluate potential relationships between Tree Swallow reproductive metrics and

temperature and humidity throughout the breeding season.

f. Relate landscape urbanization and water quality directly and indirectly (via emergent

insects) to Tree Swallow reproductive success (e.g., clutch initiation date, clutch size,

nestling mass, fledging success) and body-condition/health metrics (e.g., mass,

contaminant loads).

2. Investigate influence of urbanization on trophic dynamics of Tree Swallows.

a. Assess composition, abundance, and availability of aquatic and terrestrial insect prey

assemblages at study reaches.

26

b. Quantify isotopic signature of insect prey as well as aquatic and terrestrial primary

producers at study reaches.

c. Investigate, via stable isotope analysis, proportions of Tree Swallow energetic sources

derived from pathways originating from aquatic primary production relative to terrestrial

primary production across the study reaches.

d. Evaluate, via stable isotope analysis, Tree Swallow trophic position across the study

reaches.

The Tree Swallow (Tachycineta bicolor) serves as an ideal model North American aerial insectivore for this study. Tree Swallows are common in the eastern United States, easily observed, and readily make use of artificial nest boxes (Robertson, Stutchbury, & Cohen, 2011).

The latter characteristic offers a great benefit for field research, as investigators can limit external perturbations (e.g., predation, interspecific competition, and nest parasitism) and capture both juveniles and adults. Tree Swallows are also useful models for the effects of environmental contamination, particularly in aquatic systems, since they commonly feed on emergent aquatic insects (Jones, 2003). I anticipate that my investigation of the linkages among climate, water quality, and aerial insectivores will help to reveal the causes of aerial insectivore population declines, and thereby inform conservation and wildlife management efforts in Ohio and throughout North America.

27

References

Adams, T. S., & Sterner, R. W. C. N.-289. (2000). The effects of dietary nitrogen on trophic level 15N enrichment. Limnology and Oceanography, 45(3), 601–607.

Alberts, J. M., Sullivan, S. M. P., & Kautza, A. (2013). Riparian swallows as integrators of landscape change in a multiuse river system: Implications for aquatic-to-terrestrial transfers of contaminants. Science of the Total Environment, 463–464, 42–50. https://doi.org/10.1016/j.scitotenv.2013.05.065

Allan, J. D. (2004). Influence of land use and landscape setting on the ecological status of rivers. Limnetica, 23(3–4), 187–198. https://doi.org/10.1146/annurev.ecolsys.35.120202.110122

Allan, J. D., Erickson, D. L., & Fay, J. (1997). The influence of catchment land use on stream integrity across multiple spatial scales. Freshwater Biology, 37(1), 149–161.

Allan, J. D., & Flecker, A. S. (1993). Biodiversity conservation in running waters. BioScience, 43(1), 32–43.

Anderson, C., & Cabana, G. (2007). Estimating the trophic position of aquatic consumers in river food webs using stable nitrogen isotopes. Journal of the North American Benthological Society, 26(2), 273–285. https://doi.org/10.1899/0887- 3593(2007)26[273:ETTPOA]2.0.CO;2

Andrew, S. C., Hurley, L. L., Mariette, M. M., & Griffith, S. C. (2017). Higher temperatures during development reduce body size in the zebra finch in the laboratory and in the wild. Journal of Evolutionary Biology, 30(12), 2156–2164. https://doi.org/10.1111/jeb.13181

Ardia, D. R. (2013). The effects of nestbox thermal environment on fledging success and haematocrit in Tree Swallows. Avian Biology Research, 6(2), 99–103. https://doi.org/10.3184/175815513X13609528031394

Ardia, D. R., Cooper, C. B., & Dhondt, A. (2006). Warm temperatures lead to early onset of incubation, shorter incubation periods and greater hatching asynchrony in Tree Swallows Tachycineta bicolor at the extremes of their range. Journal of Avian Biology, 37(2), 137– 142.

Ardia, D. R., Wasson, M. F., & Winkler, D. W. (2006). Individual quality and food availability determine yolk and egg mass and egg composition in tree swallows Tachycineta bicolor. Journal of Avian Biology, 37(3), 252–260.

Arnold, C. L., Boison, P. J., & Patton, P. C. (1982). Sawmill Brook: an example of rapid geomorphic change related to urbanization. The Journal of Geology, 90(2), 155–166.

Arnold, C. L., & Gibbon, C. J. (1996). Impervious surface coverage: The emergence of a key

28

environmental indicator. Journal of the American Planning Association, 62(2), 243–258.

Aubin, A., Bourassa, J. P., & Pellisier, M. (1973). An effective emergence trap for the capture of mosquitoes. Mosquito News, 33(2), 251–252.

Bartoń, K. (2018). MuMIn. Retrieved from https://cran.r-project.org/package=MuMIn

Baxter, C. V, Fausch, K. D., & Saunders, W. C. (2005). Tangled webs: Reciprocal flows of invertebrate prey link streams and riparian zones. Freshwater Biology, 50(2), 201–220. https://doi.org/10.1111/j.1365-2427.2004.01328.x

Bearhop, S., Thompson, D. R., Waldron, S., Russell, I. C., Alexander, G., & Furness, R. W. (1999). Stable isotopes indicate the extent of freshwater feeding by cormorants Phalacrocorax carbo shot at inland fisheries in England. Journal of Applied Ecology, 36(1), 75–84. https://doi.org/10.1046/j.1365-2664.1999.00378.x

Bearhop, S., Waldron, S., Votier, S. C., & Furness, R. W. (2002). Factors That influence assimilation rates and fractionation of nitrogen and carbon stable isotopes in avian blood and feathers. Physiological and Biochemical Zoology, 75(5), 451–458.

Beck, M. L., Hopkins, W. A., & Jackson, B. P. (2014). Variation in riparian consumer diet composition and differential bioaccumulation by prey influence the risk of exposure to elements from a recently remediated fly ash spill. Environmental Toxicology and Chemistry, 33(11), 2595–2608. https://doi.org/10.1002/etc.2719

Becker, M. E., & Weisberg, P. J. (2015). Synergistic effects of spring temperatures and land cover on nest survival of urban birds. The Condor, 117(1), 18–30. https://doi.org/10.1650/CONDOR-14-1.1

Benke, A., Wallace, J., & Harrison, J. (2001). Food web quantification using secondary production analysis: predaceous …. Freshwater …, 329–346. https://doi.org/10.1046/j.1365-2427.2001.00680.x

Bennett, P. M., & Hobson, K. A. (2009). Trophic structure of a boreal forest community revealed by stable isotope (d13C, d15N) analyses. Entomological Science, 12(1), 17–24. https://doi.org/10.1111/j.1479-8298.2009.00308.x

Blair, R. B. (1996). Land use and avian species diversity along an urban gradient. Ecological Applications, 6(2), 506–519.

Boening, D. W. (2000). Ecological effects, transport, and fate of mercury: a general review. Chemosphere, 40(12), 1335–1351.

Bohning-Gaese, K., Taper, M. L., & Brown, J. H. (1993). Are declines in North American insectivorous songbirds due to Causes on the breeding range? Conservation Biology, 7(1), 76–86. Retrieved from http://www.jstor.org/stable/2386644%0Ahttp://about.jstor.org/terms 29

Booth, D. B., & Jackson, C. R. (1998). Urbanization of aquatic systems: degradation thresholds, stormwater detection, and the limits of mitigation. Journal of the American Water Resources Association, 33(5), 1077–1090.

Both, C., Van Turnhout, C. A. M., Bijlsma, R. G., Siepel, H., Van Strien, A. J., & Foppen, R. P. B. (2010). Avian population consequences of climate change are most severe for long- distance migrants in seasonal habitats. Proceedings of the Royal Society B-Biological Sciences, 277(1685), 1259–1266. https://doi.org/10.1098/rspb.2009.1525

Bourret, A., Bélisle, M., Pelletier, F., & Garant, D. (2015). Multidimensional environmental influences on timing of breeding in a tree swallow population facing climate change. Evolutionary Applications, 8(10), 933–944. https://doi.org/10.1111/eva.12315

Brasso, R. L., & Cristol, D. A. (2008). Effects of mercury exposure on the reproductive success of Tree Swallows (Tachycineta bicolor). Ecotoxicology, 17(2), 133–141. https://doi.org/10.1007/s10646-007-0163-z

Brigham, R. M. (1989). Roost and nest sites of Common Nighthawks: are gravel roofs important? The Condor, 91, 122–124.

Brown, L. R., Cuffney, T. F., Coles, J. F., Fitzpatrick, F., McMahon, G., Steuer, J., … May, J. T. (2009). Urban streams across the USA: lessons learned from studies in 9 metropolitan areas. Journal of the North American Benthological Society, 28(4), 1051–1069. https://doi.org/10.1899/08-153.1

Burdon, F. J., & Harding, J. S. (2008). The linkage between riparian predators and aquatic insects across a stream-resource spectrum. Freshwater Biology, 53(2), 330–346. https://doi.org/10.1111/j.1365-2427.2007.01897.x

Burger, J., & Gochfeld, M. (1997). Risk, mercury levels, and birds: relating adverse laboratory effects to field biomonitoring. Environmental Research, 172(2), 160–172.

Butler, R. W. (1988). Population dynamics and migration routes of Tree Swallows, Tachycineta bicolor, in North America. Journal of Field Ornithology, 59(4), 395–402.

Cabana, G., & Rasmussen, J. (1996). Comparison of aquatic food chains using nitrogen isotopes. Proceedings of the National Academy of Sciences of the United States of America, 93(20), 10844–10847.

Caquet, T. (2006). Use of carbon and nitrogen stable isotope ratios to assess the effects of environmental contaminants on aquatic food webs. Environmental Pollution, 141(1), 54–59. https://doi.org/10.1016/j.envpol.2005.08.029

Caut, S., Angulo, E., & Courchamp, F. (2008). Caution on isotopic model use for analyses of consumer diet. Canadian Journal of Zoology, 86(5), 438–445. https://doi.org/10.1139/Z08-

30

012

Caut, S., Angulo, E., & Courchamp, F. (2009). Variation in discrimination factors (Δ15N and Δ13C): The effect of diet isotopic values and applications for diet reconstruction. Journal of Applied Ecology, 46(2), 443–453. https://doi.org/10.1111/j.1365-2664.2009.01620.x

Chalmers, A. T., Krabbenhoft, D. P., Metre, P. C. Van, & Nilles, M. A. (2014). Effects of urbanization on mercury deposition and accumulation in New England. Environmental Pollution, 192, 104–112. https://doi.org/10.1016/j.envpol.2014.05.003

Chamberlain, D., Hatchwell, B., & Gaston, K. J. (2009). Avian productivity in urban landscapes: a review and meta-analysis. Ibis, 151(1), 1–18. https://doi.org/10.1111/j.1474- 919X.2008.00899.x

Chislock, M. F., Doster, E., Zitomer, R. A., & Wilson, A. E. (2013). Eutrophication: causes, consequences, and controls in aquatic ecosystems. Nature Education Knowledge, 4(4), 10. Retrieved from http://www.wilsonlab.com/publications/2013_NE_Chislock_et_al.pdf

Collier, K. J., Bury, S., & Gibbs, M. (2002). A stable isotope study of linkages between stream and terrestrial food webs through spider predation. Freshwater Biology, 47(9), 1651–1659. https://doi.org/10.1046/j.1365-2427.2002.00903.x

Compin, A., & Céréghino, R. (2003). Sensitivity of aquatic insect species richness to disturbance in the Adour–Garonne stream system (France). Ecological Indicators, 3(2), 135–142. https://doi.org/10.1016/S1470-160X(03)00016-5

Compson, Z. G., Adams, K. J., Edwards, J. A., Maestas, J. M., Whitham, T. G., & Marks, J. C. (2013). Leaf litter quality affects aquatic insect emergence: contrasting patterns from two foundation trees. Oecologia, 173(2), 507–519. https://doi.org/10.1007/s00442-013-2643-6

Cox, A. R., Robertson, R. J., Fedy, B. C., Rendell, W. B., & Bonier, F. (2018). Demographic drivers of local population decline in Tree Swallows (Tachycineta bicolor). The Condor, 120(4), 842–851. https://doi.org/10.1650/CONDOR-18-42.1

Crick, H. Q. P. (2004). The impact of climate change on birds. Ibis, 146(Suppl. 1), 48–56.

Cristol, D., Brasso, R., Monroe, A., Condon, R., Fovargue, A., Friedman, S., … White, A. (2008). The movement of aquatic mercury through terrestrial food webs. Science, 320(5874), 335.

Crooks, K. R., Suarez, A. V., & Bolger, D. T. (2004). Avian assemblages along a gradient of urbanization in a highly fragmented landscape. Biological Conservation, 115(3), 451–462. https://doi.org/10.1016/S0006-3207(03)00162-9

Cummins, K. W., & Klug, M. J. (1979). Feeding ecology of stream invertebrates. Annual Review of Ecology and Systematics, 10(1), 147–172. 31

https://doi.org/10.1146/annurev.es.10.110179.001051

Cunningham, S. J., Martin, R. O., Hojem, C. L., & Hockey, P. A. R. (2013). Temperatures in excess of critical thresholds threaten nestling growth and survival in A rapidly-warming arid savanna: a study of Common Fiscals. PLoS ONE, 8(9), 1–10. https://doi.org/10.1371/journal.pone.0074613

Custer, C. M., Custer, T. W., Dummer, P. M., Munney, K. L., Midwest, U., Sciences, E., … Office, F. (2003). Exposure and effects of chemical contaminants on Tree Swallows nesting along the Housatonic River, Berkshire County, Massachusetts, USA, 1998 – 2000. Environmental Toxicology and Chemistry, 22(7), 1605–1621.

DeNiro, M. J., & Epstein, S. (1978). Influence of diet on the distribution of nitrogen isotopes in . Geochimica et Cosmochimica Acta, 42(3), 495–506. https://doi.org/10.1016/0016- 7037(81)90244-1

Dodds, W. K., & Smith, V. H. (2016). Nitrogen, phosphorus, and eutrophication in streams. Inland Waters, 6(2), 155–164. https://doi.org/10.5268/IW-6.2.909

Dods, P. L., Birmingham, E. M., Williams, T. D., Ikonomou, M. G., Bennie, D. T., & Elliott, J. E. (2005). Reproductive success and contaminants in tree swallows (Tachycineta bicolor) breeding at a wastewater treatment plant. Environmental Toxicology and Chemistry, 24(12), 3106–3112. https://doi.org/10.1897/04-547R.1

Driscoll, C. T., Han, Y., Chen, C. Y., Evers, D. C., Lambert, K. F., Holsen, T. M., … Munson, R. K. (2007). Mercury contamination in forest and freshwater ecosystems in the Northeastern United States. BioScience, 57(1), 17–28.

Dunn, P., & Hannon, S. J. (1992). Effects of food abundance and male parental care on reproductive success and monogamy in Tree Swallows. The Auk, 109(3), 488–499.

Dunn, P. O., & Winkler, D. W. (1999). Climate change has affected the breeding date of tree swallows throughout North America. Proceedings of the Royal Society B-Biological Sciences, 266(1437), 2487–2490.

Durance, I., & Ormerod, S. J. (2007). Climate change effects on upland stream macroinvertebrates over a 25-year period. Global Change Biology, 13(5), 942–957. https://doi.org/10.1111/j.1365-2486.2007.01340.x

Eeva, T., Veistola, S., & Lehikoinen, E. (2000). Timing of breeding in subarctic passerines in relation to food availability. Canadian Journal of Zoology, 78(1), 67–78. https://doi.org/10.1139/cjz-78-1-67

English, P. A., Green, D. J., & Nocera, J. J. (2018). Stable isotopes from museum specimens may provide evidence of long-term change in the trophic ecology of a migratory aerial

32

insectivore. Frontiers in Ecology and Evolution, 6(February), 14. https://doi.org/10.3389/FEVO.2018.00014

Environment Canada. (2007). Chimney swift (Chaetura pelagica) COSEWIC assessment and status report. Ottawa.

Environment Canada. (2012). The State of Canada’s Birds. Ottawa.

Evers, D. C., Burgess, N. M., Champoux, L., Hoskins, B., Major, A., Goodale, W. M., … Daigle, T. (2005). Patterns and interpretation of mercury exposure in freshwater avian communities in northeastern North America. Ecotoxicology, 14(1–2), 193–221.

Fausch, K. D., Baxter, C. V., & Murakami, M. (2010). Multiple stressors in north temperate streams: lessons from linked forest-stream ecosystems in northern Japan. Freshwater Biology, 55(SUPPL. 1), 120–134. https://doi.org/10.1111/j.1365-2427.2009.02378.x

Fimreite, N. (1974). Mercury contamination of aquatic birds in Northwestern Ontario. The Journal of Wildlife Management, 38(1), 120–131.

Finlay, J. C. (2001). Stable carbon isotope ratios of river biota: implications for energy flow in lotic food webs. Ecology, 82(4), 1052–1064.

Fraser, K. C., Stutchbury, B. J. M., Silverio, C., Kramer, P. M., Barrow, J., Newstead, D., … Tautin, J. (2012). Continent-wide tracking to determine migratory connectivity and tropical habitat associations of a declining aerial insectivore. Proceedings of the Royal Society B- Biological Sciences, 279(1749), 4901–4906. https://doi.org/10.1098/rspb.2012.2207

Freeman, P. L., & Schorr, M. S. (2004). Influence of watershed urbanization on fine sediment and macroinvertebrate assemblage characteristics in Tennessee ridge and valley streams. Journal of Freshwater Ecology, 19(3), 353–362. https://doi.org/10.1080/02705060.2004.9664908

Fry, B. (2006). Stable isotope ecology. Stable isotope ecology. New York: Springer Science+Business Media. https://doi.org/10.1016/j.dsr2.2015.11.009

Gage, M. S., Spivak, A., & Paradise, C. J. (2004). Effects of land use and disturbance on benthic insects in headwater streams drainging small watersheds. Southeastern Naturalist, 3(2), 345–358.

Gentes, M., Waldner, C., Papp, Z., & Smits, J. E. G. (2006). Effects of oil sands tailings compounds and harsh weather on mortality rates, growth and detoxification efforts in nestling Tree Swallows (Tachycineta bicolor). Environmental Pollution, 142(1), 24–33. https://doi.org/10.1016/j.envpol.2005.09.013

Gerald, M., & Tebaldi, C. (2004). More intense, more frequent, and longer-lasting heat waves in the 21st Century. Science, 305(August), 994–997. https://doi.org/10.1126/science.1098704 33

Ghilain, A., & Bélisle, M. (2008). Breeding success of Tree Swallows along a gradient of agricultural intensification. Ecological Applications, 18(5), 1140–1154. https://doi.org/10.1890/07-1107.1

Golondrinas de las Americas. (2011). Nest box design.

Grable, J. L., & Harden, C. P. (2006). Geomorphic response of an Appalachian Valley and Ridge stream to urbanization. Earth Surface Processes and Landforms, 31(13), 1707–1720. https://doi.org/10.1002/esp

Gray, L. J. (1993). Response of insectivorous birds to emerging aquatic insects in riparian habitats of a tallgrass prairie stream. American Midland Naturalist, 129(2), 288–300.

Gurtz, M. E., & Wallace, J. B. (1984). Substrate-mediated response of stream invertebrates to disturbance. Ecology, 65(5), 1556–1569.

Hagar, J. C., Li, J., Sobota, J., & Jenkins, S. (2012). Arthropod prey for riparian associated birds in headwater forests of the Oregon Coast Range. Forest Ecology and Management, 285, 213–226. https://doi.org/10.1016/j.foreco.2012.08.026

Hallinger, K. K., & Cristol, D. A. (2011). The role of weather in mediating the effect of mercury exposure on reproductive success in Tree Swallows. Ecotoxicology, 20(6), 1368–1377. https://doi.org/10.1007/s10646-011-0694-1

Harper, M. P. H., & Peckarsky, B. L. (2006). Emergence cues of a mayfly in a high-altitude stream ecosystem: potential response to climate change. Ecological Applications, 16(2), 612–621.

Harris, D. J. (2009). Clinical tests. Handbook of Avian Medicine (Second Edi). Elsevier Limited. Retrieved from http://dx.doi.org/

Harris, G. P., & Baxter, G. (1996). Interannual variability in phytoplankton biomass and species composition in a subtropical reservoir. Freshwater Biology, 35(3), 545–560. https://doi.org/10.1111/j.1365-2427.1996.tb01768.x

Harvey, C. J., & Kitchell, J. F. (2000). A stable isotope evaluation of the structure and spatial heterogeneity of a Lake Superior food web. Canadian Journal of Fisheries and Aquatic Sciences, 57(7), 1395–1403.

Hawkins, C. P., Hogue, J. N., Decker, L. M., & Feminella, J. W. (1997). Channel morphology, water temperature, and assemblage structure of stream insects. Journal of the North American Benthological Society, 16(4), 728–749.

Hawley, D. M., Hallinger, K. K., & Cristol, D. A. (2009). Compromised immune competence in free-living tree swallows exposed to mercury. Ecotoxicology, 18(5), 499–503. https://doi.org/10.1007/s10646-009-0307-4 34

Heinrich, K. K., Whiles, M. R., & Roy, C. (2014). Cascading ecological responses to an in- stream restoration project in a midwestern river. Restoration Ecology, 22(1), 72–80. https://doi.org/10.1111/rec.12026

Helms, B. S., Schoonover, J. E., & Feminella, J. W. (2009). Seasonal variability of landuse impacts on macroinvertebrate assemblages in streams of western Georgia, USA. Journal of the North American Benthological Society, 28(4), 991–1006. https://doi.org/10.1899/08- 162.1

Hendrickx, F., Maelfait, J., Wingerden, W. Van, Schweiger, O., Speelmans, M., Aviron, S., … Bugter, R. (2007). How landscape structure, land‐use intensity and habitat diversity affect components of total arthropod diversity in agricultural landscapes. Journal of Applied Ecology, 44(2), 340–351.

Hespenheide, H. A. (1971). Food preference and the extent of overlap in some insectivorous birds, with special reference to the Tyrannidae. Ibis, 113(1), 59–72. https://doi.org/10.1111/j.1474-919X.1971.tb05123.x

Hession, W. C., Pizzuto, J. E., Johnson, T. E., & Horwitz, R. J. (2003). Influence of bank vegetation on channel morphology in rural and urban watersheds. Geology, 31(2), 147–150. https://doi.org/10.1130/0091-7613(2003)031<0147:IOBVOC>2.0.CO;2

Homer, C. G., Dewitz, J. A., Yang, L., Jin, S., Danielson, P., Xian, G., … Megown, K. (2015). Completion of the 2011 National Land Cover Database for the conterminous United States- representing a decade of land cover change information. Photogrammetric Engineering and Remote Sensing, 81(5), 345–354.

Hughes, L. (2000). Biological consequences of global warming: is the signal already apparent? Trends in Ecology & Evolution, 15(2), 56–61. https://doi.org/10.1016/S0169- 5347(99)01764-4

Hussell, D. (2003). Climate change, spring temperatures, and timing of breeding of Tree Swallows (Tachycineta bicolor) in southern Ontario. The Auk, 120(3), 607–618.

Hussell, D., & Quinney, T. E. (1987). Food abundance and clutch size of Tree Swallows Tachycineta bicolor. Ibis, 129(1), 243–258. https://doi.org/10.1111/fwb.12476

Iwata, T., Nakano, S., & Murakami, M. (2003). Stream meanders increase insectivorous bird abundance in riparian deciduous forests. Ecography, 26(September 2002), 325–337. https://doi.org/10.1034/j.1600-0587.2003.03355.x

Jackson, A. K., Evers, D. C., Etterson, M. A., Condon, A. M., Sarah, B., Detweiler, J., … Thryothorus, D. (2011). Mercury exposure affects the reproductive success of a free-living terrestrial songbird, the Carolina Wren (Thryothorus ludovicianus). The Auk, 128(4), 759– 769. 35

Jackson, J. K., & Fisher, S. G. (1986). Secondary production, emergence, and export of aquatic insects of a Sonoran Desert stream. Ecology, 67(3), 629–638.

Johnson, N. F., & Triplehorn, C. A. (2005). c (7th ed.). Boston: Brooks/Cole.

Johnson, R. C., Jin, H., Carreiro, M. M., & Jack, J. D. (2013). Macroinvertebrate community structure, secondary production and trophic-level dynamics in urban streams affected by non-point-source pollution. Freshwater Biology, 58(5), 843–857. https://doi.org/10.1111/fwb.12090

Jones, J. (2003). Tree swallows (Tachycineta bicolor): A new model organism? The Auk, 120(3), 591–599.

Jonsson, M., Hedström, P., Stenroth, K., Hotchkiss, E. R., Vasconcelos, F. R., Karlsson, J., & Byström, P. (2015). Climate change modifies the size structure of assemblages of emerging aquatic insects. Freshwater Biology, 60(1), 78–88. https://doi.org/10.1111/fwb.12468

Jonsson, M., Strasevicius, D., & Malmqvist, B. (2012). Influences of river regulation and environmental variables on upland bird assemblages in northern Sweden. Ecological Research, 27(5), 945–954. https://doi.org/10.1007/s11284-012-0974-0

Karagicheva, J., Liebers, M., Rakhimberdiev, E., Hallinger, K. K., Saveliev, A., & Winkler, D. W. (2016). Differences in size between first and replacement clutches match the seasonal decline in single clutches in Tree Swallows Tachycineta bicolor. Ibis, 158(3), 607–613.

Kautza, A., & Sullivan, S. M. P. (2015). Shifts in reciprocal river-riparian arthropod fluxes along an urban-rural landscape gradient. Freshwater Biology, 60(10), 2156–2168. https://doi.org/10.1111/fwb.12642

Kautza, A., & Sullivan, S. M. P. (2016a). Anthropogenic and natural determinants of fish food- chain length in a midsize river system. Freshwater Science, 35(3), 895–908. https://doi.org/10.1086/685932

Kautza, A., & Sullivan, S. M. P. (2016b). The energetic contributions of aquatic primary producers to terrestrial food webs in a mid-size river system. Ecology, 97(3), 694–705. https://doi.org/10.1890/15-1095.1

Kenward, A., Yawitz, D., Sanford, T., & Wang, R. (2014). Summer in the city: Hot and getting hotter. Princeton.

Klein, R. D. (1980). Urbanization and stream quality impairment. Water Resources Bulletin, 15(4), 948–963.

Kondolf, G. M. (1995). Five elements for effective evaluation of stream restoration. Restoration Ecology. https://doi.org/10.1111/j.1526-100X.1995.tb00086.x

36

Kuznetsova, A., Brockhoff, P. B., Haubo, R., & Christensen, B. (2017). lmerTest. Retrieved from https://github.com/runehaubo/lmerTestR

Labocha, M. K., & Hayes, J. P. (2012). Morphometric indices of body condition in birds: a review. Journal of Ornithology, 153(1), 1–22. https://doi.org/10.1007/s10336-011-0706-1

Langham, G., Schuetz, J., Soykan, C., Wilsey, C., Auer, T., LeBaron, G., … Distler, T. (2014). Audubon’s Birds and Climate Change Report. New York.

Layman, C. A., Araujo, M. S., Boucek, R., Hammerschlag-Peyer, C. M., Harrison, E., Jud, Z. R., … Bearhop, S. (2012). Applying stable isotopes to examine food-web structure: An overview of analytical tools. Biological Reviews, 87(3), 545–562. https://doi.org/10.1111/j.1469-185X.2011.00208.x

Learner, M. A., & Potter, D. W. B. (1974). The seasonal periodicity of emergence of insects from two Ponds in Hertfordshire, England, with special reference to the Chironomidae (Diptera: Nematocera). Hydrobiologia, 44(4), 495–510.

Leffelaar, D., & Robertson, R. J. (1986). Equality of feeding roles and the maintenance of monogamy in Tree Swallows. Behavioral Ecology and Sociobiology, 18(3), 199–206.

Lenat, D. R. (1988). Water quality assessment of streams using a qualitative collection method for benthic macroinvertebrates. Journal of the North American Benthological Society, 7(3), 222–233. https://doi.org/10.2307/1467422

Lenat, D. R., & Crawford, J. K. (1994). Effect of land use on water quality and aquatic biota of three North Carolina Piedmont streams. Hydrobiologia, 294(3), 185–199. https://doi.org/10.3923/ijb.2012.181.191

Li, Y., & Cai, Y. (2013). Progress in the study of mercury methylation and demethylation in aquatic environments. Chinese Science Bulletin, 58(2), 177–185.

Lifjeld, J. T., Dunn, P. O., & Whittingham, L. A. (2002). Short-term fluctuations in cellular immunity of tree swallows feeding nestlings. Oecologia, 130(2), 185–190. https://doi.org/10.1007/s004420100798

Lill, A. (2011). Sources of variation in blood glucose concentrations of free-living birds. Avian Biology Research, 4(2), 78–87. https://doi.org/10.3184/175815511X13073729328092

Lussier, S. M., da Silva, S. N., Charpentier, M., Heltshe, J. F., Cormier, S. M., Klemm, D. J., … Jayaraman, S. (2008). The influence of suburban land use on habitat and biotic integrity of coastal Rhode Island streams. Environmental Monitoring and Assessment, 139(1–3), 119– 136. https://doi.org/10.1007/s10661-007-9820-1

Lussier, S. M., Enser, R. W., Dasilva, S. N., & Charpentier, M. (2006). Effects of habitat disturbance from residential development on breeding bird communities in riparian 37

corridors. Environmental Management, 38(3), 504–521. https://doi.org/10.1007/s00267- 005-0088-3

Lutz, M. A., Brigham, M. E., Krabbenhoft, D. P., Aiken, G. R., & Orem, W. H. (2009). methylmercury production and bed sediment-pore water partitioning. Environmental Science & Technology, 43(8), 2726–2732.

MacHunter, J., Wright, W., Loyn, R., & Rayment, P. (2006). Bird declines over 22 years in forest remnants in southeastern Australia: Evidence of faunal relaxation? Canadian Journal of Forest Research, 36(11), 2756–2768. https://doi.org/10.1139/x06-159

Macivor, J. S., & Lundholm, J. (2011). Insect species composition and diversity on intensive green roofs and adjacent level-ground habitats. Urban Ecosystems, 14(2), 225–241. https://doi.org/10.1007/s11252-010-0149-0

Marczak, L. B., Sakamaki, T., Turvey, S. L., Deguise, I., Wood, S. L. R., & Richardson, J. S. J. S. (2010). Are forested buffers an effecive conservation strategy for riparian fauna? An assessment using meta-analysis. Ecological Applications, 20(1), 126–134. https://doi.org/10.1890/08-2064.1

McArthur, S. L., McKellar, A. E., Flood, N. J., & Reudink, M. W. (2017). Local weather and regional climate influence breeding dynamics of Mountain Bluebirds (Sialia currucoides) and Tree Swallows (Tachycineta bicolor): a 35-year study. Canadian Journal of Zoology, 95(4), 271–277.

McCarty, J. P. (1997). Aquatic community characteristics influence the foraging patterns of Tree Swallows. The Condor, 99(1), 210–213. https://doi.org/10.2307/1370241

McCarty, J. P. (2001). Review: ecological consequences of recent climate change. Conservation Biology, 15(2), 320–331.

McCarty, J. P. (2002). The number of visits to the nest by parents is an accurate measure of food delivered to nestlings in Tree Swallows. Journal of Field Ornithology, 73(1), 9–14.

McCarty, J. P., & Secord, A. L. (1999). Reproductive ecology of Tree Swallows (Tachycineta bicolor) with high levels of polychlorinated biphenyl contamination. Environmental Toxicology and Chemistry, 18(7), 1433. https://doi.org/10.1897/1551- 5028(1999)018<1433:REOTST>2.3.CO;2

McCarty, J. P., & Winkler, D. W. (1999a). Foraging ecology and diet selectivity of Tree Swallows feeding nestlings. The Condor, 101(2), 246–254. Retrieved from http://www.jstor.org/stable/pdf/1369987.pdf

McCarty, J. P., & Winkler, D. W. (1999b). Relative importance of environmental variables in determining the growth of nestling Tree Swallows Tachycineta bicolor. Ibis, 141(2), 286–

38

296.

McIntyre, N. E. (2000). Ecology of urban : a review and a call to action. Annals of the Entomological Society of America, 93(4), 825–835. https://doi.org/10.1603/0013- 8746(2000)093[0825:EOUAAR]2.0.CO;2

McKinney, M. (2002). Urbanization, biodiversity, and conservation. BioScience, 52(10), 883– 890.

Mengelkoch, J. M., Niemi, G. J., & Regal, R. R. (2004). Diet of the nestling Tree Swallow. The Condor, 106(2), 423–429.

Merrill, D., & Leatherby, L. (2018). Here’s how America uses its land. Retrieved from https://www.bloomberg.com/graphics/2018-us-land-use/

Merritt, R. W., Cummins, K. . W., & Berg, M. B. (2008). An Introduction to the Aquatic Insects of North America (4th ed.). Dubuque: Kendall Hunt.

Meybeck, M. (1998). Man and river interface: multiple impacts on water and particulates chemistry illustrated in the Seine river basin. Hydrobiologia, 373, 1–20. https://doi.org/10.1023/A:1017067506832

Meyer, J. L., Paul, M. J., & Taulbee, W. K. (2005). Stream ecosystem function in urbanizing landscapes. Journal of the American Benthological Society, 24(3), 602–612.

Michel, N. L., Smith, A. C., Clark, R. G., Morrissey, C. A., & Hobson, K. A. (2016). Differences in spatial synchrony and interspecific concordance inform guild-level population trends for aerial insectivorous birds. Ecography, 39(8), 774–786. https://doi.org/10.1111/ecog.01798

Miller, J. R., Wiens, J. A., Hobbs, N. T., & Theobald, D. M. (2003). Effects of human settlement on bird communities in lowland riparian areas of Colorado (USA). Ecological Applications, 13(4), 1041–1059.

Minagawa, M., & Wada, E. (1984). Stepwise enrichment of 15N along food chains: Further evidence and the relation between 15N and age. Geochimica et Cosmochimica Acta, 48(5), 1135–1140. https://doi.org/10.1016/0016-7037(84)90204-7

Minshall, G. W. (1978). Autotropy in Stream Ecosystems. BioScience, 28(12), 767–771. https://doi.org/10.2307/1307250

Monroe, A. P., Hallinger, K. K., Brasso, R. L., & Cristol, D. A. (2008). Occurrence and implications of double brooding in a southern population of Tree Swallows. The Condor, 110(2), 382–386. https://doi.org/10.1525/cond.2008.8341

Moore, J. W., & Semmens, B. X. (2008). Incorporating uncertainty and prior information into stable isotope mixing models. Ecology Letters, 11(5), 470–480. 39

https://doi.org/10.1111/j.1461-0248.2008.01163.x

Morel, F. M. M., Kraepiel, A. M. L., & Amyot, M. (1998). The chemical cycle and bioaccumulation of mercury. Annual Review of Ecology and Systematics, 29(1), 543–566. https://doi.org/10.1146/annurev.ecolsys.29.1.543

Morse, C. C., Huryn, A. D., & Cronan, C. (2003). Impervious surface area as a predictor of the effects of urbanization on stream insect communities in Maine, USA. Environmental Monitoring and Assessment, 89(1), 95–127.

Muehlbauer, J. D., Collins, S. F., Doyle, M. W., & Tockner, K. (2014). How wide is a stream? Spatial extent of the potential “stream signature” in terrestrial food webs using meta- analysis. Ecology, 95(1), 44–55.

Muldal, A., Gibbs, H. L., & Robertson, R. J. (1985). Preferred nest spacing of an obligate cavity- nesting bird, the Tree Swallow. The Condor, 87(3), 356–363. Retrieved from http://www.jstor.org/stable/pdf/1367216.pdf

Munthe, J., Bodaly, R. A. D., Branfireun, B. A., Driscoll, C. T., Cynthia, C., Harris, R., … Harris, R. (2007). Recovery of mercury-contaminated fisheries. AMBIO: A Journal of the Human Environment, 36(1), 33–44.

Murakami, M., & Nakano, S. (2002). Indirect effect of aquatic insect emergence on a terrestrial insect population through bird predation. Ecology Letters, 5(3), 333–337. https://doi.org/10.1046/j.1461-0248.2002.00321.x

Naef-Daenzer, B., & Grüebler, M. U. (2016). Post-fledging survival of altricial birds: ecological determinants and adaptation. Journal of Field Ornithology, 87(3), 227–250. https://doi.org/10.1111/jofo.12157

Naiman, R. J., & Decamps, H. (1997). The ecology of interfaces: Riparian zones. Annual Review of Ecology, Evolution, and Systematics, 28(102), 621–658. https://doi.org/10.1146/annurev.ecolsys.28.1.621

Naiman, R. J., Decamps, H., & Pollock, M. (1993). The role of riparian corridors in maintaining regional biodiversity. Ecological Application, 3(2), 209–212. https://doi.org/10.2307/1941822

Nakano, S., & Murakami, M. (2001). Reciprocal subsidies: dynamic interdependence between terrestrial and aquatic food webs. Proceedings of the National Academy of Sciences of the United States of America, 98(1), 166–170.

Nancy B. Grimm, Sheibley, R. W., Crenshaw, C. L., Dahm, C. N., Roach, W. J., & Zeglin, L. H. (2005). N retention and transformation in urban streams. Journal of the North American Benthological Society, 24(3), 626–642.

40

Nebeker, A. V. (1971). Effect of high winter water temperatures on adult emergence of aquatic insects. Water Research, 5(9), 777–783. https://doi.org/10.1016/0043-1354(71)90100-X

Nebel, S., Mills, A., Mccracken, J. D., & Taylor, P. D. (2010). Declines of aerial insectivores in North America follow a geographic gradient. Avian Conservation & Ecology, 5(2), 1. https://doi.org/10.5751/ACE-00391-050201

Nelson, K. C., & Palmer, M. A. (2007). Stream temperature surges under urbanization and climate change: data, models, and responses. Journal of the American Water Resources Association, 43(2), 440–452.

Newhouse, M. J., Marra, P. P., & Johnson, L. S. (2008). Reproductive success of House Wrens in suburban and rural landscapes. The Wilson Journal of Ornithology, 120(1), 99–104. https://doi.org/10.1676/06-156.1

Nooker, J. K., Dunn, P. O., & Whittingham, L. a. (2005). Effects of food abundance, weather, and female condition on reproduction in Tree Swallows (Tachycineta bicolor). The Auk, 122(4), 1225–1238. https://doi.org/10.1642/0004- 8038(2005)122{[}1225:EOFAWA]2.0.CO;2

Nordlie, K. J., & Arthur, J. W. (1981). Effect of elevated water temperature on insect emergence in outdoor experimental channels. Environmental Pollution, 25(1), 53–65.

Norris, A. R., Aitken, K. E. H., Martin, K., & Pokorny, S. (2018). Nest boxes increase reproductive output for Tree Swallows in a forest grassland matrix in central British Columbia. Plos One, 13(10), e0204226. https://doi.org/10.1371/journal.pone.0204226

Ohio Environmental Protection Agency. (2014). Scioto River watershed. Retrieved from http://www.epa.ohio.gov/dsw/tmdl/sciotoriver.aspx#122556530-implementation

Ohlendorf, H. M., Kilness, A. W., Simmons, J. L., Richard, K., Hoffman, D. J., Moore, J. F., … Dakota, S. (1988). Selenium toxicosis in wild aquatic birds. Journal of Toxicology and Environmental Health, 24(1), 67–92. https://doi.org/10.1080/15287398809531141

Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108(455), 1–24. https://doi.org/10.1002/qj.49710845502

Parnell, A. C., Inger, R., Bearhop, S., & Jackson, A. L. (2010). Source partitioning using stable isotopes: Coping with too much variation. PLoS ONE, 5(3), e9672. https://doi.org/10.1371/journal.pone.0009672

Parnell, A., & Jackson, A. (2013). SIAR. Retrieved from https://cran.r-project.org/package=siar

Parnell, A., & Jackson, A. (2015). Package ‘ siar ’ documentation. https://doi.org/10.1080/07351690701310649

41

Paul, M. J., & Meyer, J. L. (2001). Streams in the urban landscape. Annual Review of Ecology and Systematics, 32, 333–365. https://doi.org/10.1146/annurev.ecolsys.32.081501.114040

Peig, J., & Green, A. J. (2017). New perspectives for estimating body condition from mass/length data: The scaled mass index as an alternative method. Oikos, 118(12), 1883– 1891.

Perez, J. H., Ardia, D. R., Chad, E. K., & Clotfelter, E. D. (2008). Experimental heating reveals nest temperature affects nestling condition in tree swallows (Tachycineta bicolor). Biology Letters, 4(5), 468–471. https://doi.org/10.1098/rsbl.2008.0266

Peters, N. E. (2009). Effects of urbanization on stream water quality in the city of Atlanta, Georgia, USA. Hydrological Processes, 23(20), 2860–2878. https://doi.org/10.1002/hyp

Peterson, B. J., & Fry, B. (1987). Stable isotopes in ecosystem studies. Annual Review of Ecology and Systematics, 18(1), 293–320. https://doi.org/10.1146/annurev.es.18.110187.001453

Piland, N. C., & Winkler, D. W. (2015). Tree Swallow frugivory in winter. Southeastern Naturalist, 14(1), 123–137.

Pilgrim, J. M., Fang, X., & Stefan, H. G. (1999). Stream temperature correlations with air temperatures in Minnesota: implications for climate warming. Journal of the American Water Resources Association, 34(5), 1109–1121.

Pipoly, I., Bókony, V., Seress, G., Szabó, K., & Liker, A. (2013). Effects of extreme weather on reproductive success in a temperate-breeding songbird. PLoS ONE, 8(11), 1–11. https://doi.org/10.1371/journal.pone.0080033

Pirrone, N., Cinnirella, S., Feng, X., Finkelman, R. B., Friedli, H. R., Leaner, J., … Mukherjee, A. B. (2010). Global mercury emissions to the atmosphere from anthropogenic and natural sources. Atmospheric Chemistry and Physics, 10(13), 5951–5964. https://doi.org/10.5194/acp-10-5951-2010

Polis, G. A., Anderson, W. B., & Holt, R. D. (1997). Toward an integration of landscape and food web ecology: The dynamics of spatially subsidized food webs. Annual Review of Ecology and Systematics, 28, 289–316.

Post, D. M. (2002). Using stable isotopes to estimate trophic position: models, methos, and assumptions. Ecology, 83(3), 703–718. https://doi.org/Doi 10.2307/3071875

Post, D. M., Pace, M. L., & Hairston, N. G. (2000). Ecosystem size determines food chain-length in lakes. Nature, 405(6790), 1047–1049.

Poulin, B., Lefebvre, G., & Paz, L. (2010). Red flag for green spray: adverse trophic effects of Bti on breeding birds. Journal of Applied Ecology, 47(4), 884–889. 42

https://doi.org/10.1111/j.1365-2664.2010.01821.x

Powell, G. V. N. (1983). Industrial effluents as a source of mercury contamination in terrestrial riparian vertebrates. Environmental Pollution Series B, Chemical and Physical, 5(1), 51–57.

Power, M. E., & Dietrich, W. E. (2002). Food webs in river networks. Ecological Research, 17(4), 451–471.

QGIS Development Team. (2017). QGIS Geographic Information System. Open Source Geospatial Foundation Project.

Quinney, T. E., & Ankney, C. D. (1985). Prey size selection by Tree Swallows. The Auk, 102(2), 245–250.

Quinney, T. E., Hussell, D. J. T., Ankney, C. D., & Rowan, P. (1986). Sources of variation in the growth of Tree Swallows. The Auk, 103(April), 389–400.

R Core Team. (2018). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Retrieved from https://www.r-project.org

Ramírez, A., De Jesús-Crespo, R., Martinó-Cardona, D. M., Martínez-Rivera, N., & Burgos- Caraballo, S. (2009). Urban streams in Puerto Rico: what can we learn from the tropics? Journal of the North American Benthological Society, 28(4), 1070–1079. https://doi.org/10.1899/08-165.1

Rau, G. H., Sweeney, R. E., Kaplan, I. R., Mearns, A. J., & Young, D. R. (1981). Differences in animal 13C, 15N and D abundance between a polluted and an unpolluted coastal site: Likely indicators of sewage uptake by a marine food web. Estuarine, Coastal and Shelf Science, 13(6), 701–707. https://doi.org/10.1016/S0302-3524(81)80051-5

Razeng, E., & Watson, D. M. (2015). Nutritional composition of the preferred prey of insectivorous birds: popularity reflects quality. Journal of Avian Biology, 46(1), 89–96. https://doi.org/10.1111/jav.00475

Reavie, E. D., Jicha, T. M., Angradi, T. R., Bolgrien, D. W., & Hill, B. H. (2010). Algal assemblages for large river monitoring: Comparison among biovolume, absolute and relative abundance metrics. Ecological Indicators, 10(2), 167–177. https://doi.org/10.1016/j.ecolind.2009.04.009

Ren, W., Zhong, Y., Meligrana, J., Anderson, B., Watt, W. E., Chen, J., & Leung, H. (2003). Urbanization, land use, and water quality in Shanghai 1947 – 1996. Environment International, 29(5), 649–659. https://doi.org/10.1016/S0160-4120(03)00051-5

Rencher, A. C. (1995). Methods of multivariate analysis. New York: John Wiley and Sons, Inc.

Rendell, W. B., & Robertson, R. J. (1989). Nest-site characteristics, reproductive success and 43

cavity avilaiblity for Tree Swallows breeding in natural cavities. The Condor, 91(4), 875– 885.

Rendell, W. B., & Robertson, R. J. (1993). Cavity size, clutch‐size and the breeding ecology of Tree Swallows Tachycineta bicolor. Ibis, 135(3), 305–310. https://doi.org/10.1111/j.1474- 919X.1993.tb02848.x

Richardson, J. S., & Sato, T. (2015). Resource subsidy flows across freshwater-terrestrial boundaries and influence on processes linking adjacent ecosystems. Ecohydrology, 8(3), 406–415. https://doi.org/10.1002/eco.1488

Richmond, E. K., Rosi, E. J., Walters, D. M., Fick, J., Hamilton, S. K., Brodin, T., … Grace, M. R. (2018). A diverse suite of pharmaceuticals contaminates stream and riparian food webs. Nature Communications, 9(1), 4491. https://doi.org/10.1038/s41467-018-06822-w

Rioux-Paquette, S., Pelletier, F., Garant, D., & Bélisle, M. (2014). Severe recent decrease of adult body mass in a declining insectivorous bird population. Proceedings of the Royal Society B: Biological Sciences, 281(1786). https://doi.org/10.1098/rspb.2014.0649

Robertson, R. J., Stutchbury, B. J., & Cohen, R. R. (2011). Tree Swallow. Retrieved March 1, 2017, from https://birdsna.org/Species-Account/bna/species/011/articles/introduction

Rodewald, A. D., & Bakermans, M. H. (2006). What is the appropriate paradigm for riparian forest conservation? Biological Conservation, 128(2), 193–200. https://doi.org/10.1016/j.biocon.2005.09.041

Rodewald, A. D., Kearns, L. J., & Shustack, D. P. (2013). Consequences of urbanizing landscapes to reproductive performance of birds in remnant forests. Biological Conservation, 160, 32–39. https://doi.org/10.1016/j.biocon.2012.12.034

Rodrigues, L., Train, S., Bovo-Scomparin, V., Jati, S., Borsalli, C., & Marengoni, E. (2009). Interannual variability of phytoplankton in the main rivers of the Upper Paraná River floodplain, Brazil: influence of upstream reservoirs. Brazilian Journal of Biology, 69(2), 501–516. https://doi.org/10.1590/S1519-69842009000300006

Rodríguez, S., & Barba, E. (2016). Nestling growth is impaired by heat stress: an experimental study in a mediterranean Great Tit population. Zoological Studies, 55(40), 1–13. https://doi.org/10.6620/ZS.2016.55-40

Roth, N. E., Allan, J. D., & Erickson, D. L. (1996). Landscape influences on stream biotic integrity assessed at multiple spatial scales. Landscape Ecology, 11(3), 141–156. https://doi.org/10.1007/BF02447513

Rottenborn, S. C. (1999). Predicting the impacts of urbanization on riparian bird communities. Biological Conservation, 88(3), 289–299. https://doi.org/10.1016/S0006-3207(98)00128-1

44

Rounick, J. S., & Winterbourn, M. J. (1986). Stable carbon isotopes and carbon flow in ecosystems. BioScience, 36(3), 171–177. https://doi.org/10.2307/1310304

Rowse, L. M., Rodewald, A. D., & Sullivan, S. M. P. (2014). Pathways and consequences of contaminant flux to Acadian flycatchers (Empidonax virescens) in urbanizing landscapes of Ohio, USA. Science of the Total Environment, 485–486(1), 461–467. https://doi.org/10.1016/j.scitotenv.2014.03.095

Roy, A. H., Rosemond, A. D., Paul, M. J., Leigh, D. S., & Wallace, J. B. (2003). Stream macroinvertebrate response to catchment urbanisation (Georgia, U.S.A.). Freshwater Biology, 48(2), 329–346.

RStudio Team. (2016). RStudio: Integrated Development Environment for R. Boston: RStudio, Inc. Retrieved from http://www.rstudio.com/

Rubin, D. B. (1988). Using the SIR algorithm to simulate posterior distributions. Bayesian Statistics 3: Proceedings ofthe Third Valencia International Meeting, June 1–5, 1987. Oxford.

Schaffers, A. P., Raemakers, I. P., Sýkora, K. V, & ter Braak, C. J. F. (2008). Arthropod assemblages are best predicted by plant species composition. Ecology, 89(3), 782–794. https://doi.org/10.1890/07-0361.1

Schindler, D. W. (1978). Factors regulating phytoplankton production and standing crop in the world’s freshwaters. Limnology and Oceanography, 23(3), 478–486. https://doi.org/10.4319/lo.1978.23.3.0478

Schlesinger, M. D., Manley, P. N., & Holyoak, M. (2008). Distinguishing stressors acting on land bird communities in an urbanizing environment. Ecology, 89(8), 2302–2314. https://doi.org/10.1890/07-0256.1

Schneider, S. C., & Miller, J. R. (2014). Response of avian communities to invasive vegetation in urban forest fragments. The Condor, 116(3), 459–471. https://doi.org/10.1650/CONDOR-13-009R1.1

Schueler, T. R. (1994). The importance of imperviousness. Watershed Protection Techniques, 1(3), 100–111.

Seto, K. C., Guneralp, B., & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences, 109(40), 16083–16088. https://doi.org/10.1073/pnas.1211658109

Shlosberg, A., Rumbeiha, W. K., Lublin, A., & Kannan, K. (2011). A database of avian blood spot examinations for exposure of wild birds to environmental toxicants: The DABSE biomonitoring project. Journal of Environmental Monitoring, 13(6), 1547–1558.

45

https://doi.org/10.1039/c0em00754d

Singmann, H., Bolker, B., Westfall, J., & Aust, F. (2018). afex. Retrieved from https://github.com/singmann/afex

Smith, A. C., Hudson, M.-A. R., Downes, C. M., & Francis, C. M. (2015). Change points in the population trends of aerial-insectivorous birds in North America: synchronized in time across species and regions. PLoS ONE, 10(7), 1–23. https://doi.org/10.1371/journal.pone.0130768

Smith, V. H., Tilman, G. D., & Nekola, J. C. (1998). Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environmental Pollution, 100(1– 3), 179–196. https://doi.org/10.1016/S0269-7491(99)00091-3

Smits, J. E. G., & Fernie, K. J. (2013). Avian wildlife as sentinels of ecosystem health. Comparative Immunology, Microbiology and Infectious Diseases, 36(3), 333–342. https://doi.org/10.1016/j.cimid.2012.11.007

Sponseller, R. A., Benfield, E. F., & Valett, H. M. (2001). Relationships between land use, spatial scale and stream macroinvertebrate communities. Acta Psychiatrica Scandinavica, 46(10), 1409–1424. https://doi.org/10.1111/j.1600-0447.1963.tb07839.x

Stanton, R. S., Lark, R. G. C. O. G. C., & Morrissey, C. A. M. (2017). Intensive agriculture and insect prey availability influence oxidative status and return rates of an aerial insectivore. Ecosphere, 8(3), e01746. https://doi.org/10.1002/ecs2.1746

Stenroth, K., Polvi, L. E., Fältström, E., Jonsson, M., & Science, E. (2015). Land-use effects on terrestrial consumers through changed size structure of aquatic insects. Freshwater Biology, 60(1), 136–149. https://doi.org/10.1111/fwb.12476

Steuer, J. J., Bales, J. D., Giddings, E. M. P., Steuer, J. J., & Giddings, E. M. P. (2009). Relationship of stream ecological conditions to simulated hydraulic metrics across a gradient of basin urbanization Published by : The University of Chicago Press on behalf of the Society for Freshwater Science Relationship of stream ecological conditions, 28(4), 955–976. https://doi.org/10.1899/08-157.1

Stewart, P. M., Butcher, J. T., & Swinford, T. O. (2000). Land use, habitat, and water quality effects on macroinvertebrate communities in three watersheds of a lake Michigan associated marsh system. Aquatic Ecosystem Health and Management, 3(1), 179–189. https://doi.org/10.1080/14634980008656999

Stone, B., Hess, J. J., & Frumkin, H. (2010). Urban form and extreme heat events: Are sprawling cities more vulnerable to climate change than compact cities? Environmental Health Perspectives, 118(10), 1425–1428. https://doi.org/10.1289/ehp.0901879

46

Strasevicius, D., Jonsson, M., Nyholm, N. E. I., & Malmqvist, B. (2013). Reduced breeding success of Pied Flycatchers Ficedula hypoleuca along regulated rivers. Ibis, 155(2), 348– 356. https://doi.org/10.1111/ibi.12024

Strayer, D. L., Beighley, R. E., Thompson, L. C., Brooks, S., Nilsson, C., Pinay, G., & Naiman, R. J. (2003). Effects of land cover on stream ecosystems: Roles of empirical models and scaling issues. Ecosystems, 6(5), 407–423. https://doi.org/10.1007/s10021-002-0170-0

Stutchbury, B. J., & Robertson, R. J. (1985). Floating populations of female Tree Swallows. The Auk, 102(3), 651–654.

Sullivan, S. M. P., Boaz, L. E., & Hossler, K. (2016). Fluvial geomorphology and aquatic-to- terrrestrial Hg export are weekly coupled in small urban streams of Columbus, Ohio. Water Resources Research, 52(4), 2822–2839. https://doi.org/10.1002/2014WR015716

Sullivan, S. M. P., Hossler, K., & Cianfrani, C. M. (2015). Ecosystem structure emerges as a strong determinant of food-chain length in linked stream–riparian ecosystems. Ecosystems, 18(8), 1356–1372. https://doi.org/10.1007/s10021-015-9904-7

Sullivan, S. M. P., Manning, D. W. P., & Davis, R. P. (2018). Do the ecological impacts of dam removal extend across the aquatic–terrestrial boundary? Ecosphere, 9(4), 1–19. https://doi.org/10.1002/ecs2.2180

Sullivan, S. M. P., & Rodewald, A. D. (2012). In a state of flux: The energetic pathways that move contaminants from aquatic to terrestrial environments. Environmental Toxicology and Chemistry, 31(6), 1175–1183. https://doi.org/10.1002/etc.1842

Sullivan, S. M. P., & Vierling, K. T. (2012). Exploring the influences of multiscale environmental factors on the American dipper Cinclus mexicanus. Ecography, 35(7), 624– 636. https://doi.org/10.1111/j.1600-0587.2011.07071.x

Sullivan, S. M. P., Watzin, M. C., & Hession, W. C. (2006). Differences in the reproductive ecology of belted kingfishers (Ceryle alcyon) across streams with varying geomorphology and habitat quality. Waterbirds, 29(3), 258–270. https://doi.org/Doi 10.1675/1524- 4695(2006)29[258:Ditreo]2.0.Co;2

Tam, B. Y., Gough, W. A., & Mohsin, T. (2015). The impact of urbanization and the urban heat island effect on day to day temperature variation. Urban Climate, 12, 1–10. https://doi.org/10.1016/j.uclim.2014.12.004

Taylor, L. R. (1963). Analysis of the effect of temperature on insects in flight. Journal of Animal Ecology, 32(1), 99–117.

Teglhøj, P. G. (2017). A comparative study of insect abundance and reproductive success of barn swallows Hirundo rustica in two urban habitats. Journal of Avian Biology, 48(6), 846–853.

47

https://doi.org/10.1111/jav.01086

Thomas, D. W., Blondel, J., Perret, P., Lambrechts, M. M., & Speakman, J. R. (2001). Energetic and fitness costs of mismatching resource supply and demand in seasonally breeding birds. Science, 291(5513), 2598–2601.

Thorp, J. H., & Delong, M. D. (1994). The riverine productivity model: An heuristic view of carbon sources and organic processing in large river ecosystems. Oikos, 70(2), 305–308.

Townes, H. (1972). A light-weight Malaise trap. Entomological News, 83, 239–247.

Townsend, A. K., Sillett, T. S., Lany, N. K., Kaiser, S. A., Rodenhouse, N. L., Webster, M. S., & Holmes, R. T. (2013). Warm springs, early lay dates, and double brooding in a North American migratory songbird, the Black-throated Blue Warbler. PLoS ONE, 8(4), e59467. https://doi.org/10.1371/journal.pone.0059467

Tromboni, F., & Dodds, W. K. (2017). Relationships between land use and stream nutrient concentrations in a Highly urbanized tropical region of Brazil: thresholds and riparian zones. Environmental Management, 60(1), 30–40. https://doi.org/10.1007/s00267-017- 0858-8

Twining, C. W., Brenna, J. T., Lawrence, P., Shipley, J. R., Tollefson, T. N., Winkler, D. W., … Winkler, D. W. (2016). Omega-3 long-chain polyunsaturated fatty acids support aerial insectivore performance more than food quantity. Proceedings of the National Academy of Sciences of the United States of America, 113(46), 10920–10925. https://doi.org/10.1073/pnas.1616962113

Twining, C. W., Shipley, J. R., & Winkler, D. W. (2018). Aquatic insects rich in omega-3 fatty acids drive breeding success in a widespread bird. Ecology Letters, 12(21), 1812–1820. https://doi.org/10.1111/ele.13156

U.S. Census Bureau. (2010). TIGER/Line shapefile, 2010, 2010 state, Ohio, 2010 census block state-based. Washington: U.S. Census Bureau.

U.S. Geological Survey. (2014a). NLCD 2011 percent developed imperviousness (2011 edition, amended 2014) - National Geospatial Data Asset (NGDA) land use land cover. Sioux Falls: U.S. Geological Survey.

U.S. Geological Survey. (2014b). NLCD2011 USFS percent tree canopy (cartographic version). Sioux Falls: U.S. Geological Survey.

U.S. Geological Survey. (2018). Bird Banding Laboratory. Retrieved from https://www.usgs.gov/centers/pwrc/science/bird-banding-laboratory

Uesugi, A., & Murakami, M. (2007). Do seasonally fluctuating aquatic subsidies influence the distribution pattern of birds between riparian and upland forests? Ecological Research, 48

22(2), 274–281. https://doi.org/10.1007/s11284-006-0028-6

Urban, M. C., Skelly, D. K., Burchsted, D., Price, W., & Lowry, S. (2006). Stream communities across a rural–urban landscape gradient. Diversity and Distributions, 12(4), 337–350. https://doi.org/10.1111/j.1366-9516.2005.00226.x

US EPA. (2008). Reducing urban heat islands: compendium of strategies urban heat island basics. Retrieved from http://www.epa.gov/hiri/resources/compendium.htm

Vander Zanden, M. J., & Rasmussen, J. B. (2001). Variation in 15N and 13C trophic fractionation: Implications for aquatic food web studies. Limnology and Oceanography, 46(8), 2061–2066. https://doi.org/10.4319/lo.2001.46.8.2061

Vannote, R. L., Minshall, G. W., Cummins, K. W., Sedell, J. R., & Cushing, C. E. (1980). The river continuum concept. Canadian Journal Fishery and Aquatic Sciences, 37(1), 130–137.

Varian-Ramos, C. W., Swaddle, J. P., & Cristol, D. A. (2014). Mercury reduces avian reproductive success and imposes selection : an experimental study with adult- or lifetime- exposure in Zebra Finch. PLoS ONE, 9(4), e95674. https://doi.org/10.1371/journal.pone.0095674

Vietz, G. J., Walsh, C. J., & Fletcher, T. D. (2015). Urban hydrogeomorphology and the urban stream syndrome: treating the symptoms and causes of geomorphic change. Progress in Physical Geography, 40(3), 480–492. https://doi.org/10.1177/0309133315605048

Violin, C. R., Cada, P., Sudduth, E. B., Hassett, B. A., Penrose, D. L., & Bernhardt, E. S. (2011). Effects of urbanization and urban stream restoration on the physical and biological structure of stream ecosystems. Ecological Applications, 21(6), 1932–1949. https://doi.org/10.1890/10-1551.1

Visser, A. M. E., Noordwijk, A. J. Van, Tinbergen, J. M., Lessells, C. M., Visser, M. E., Noordwijk, A. J. Van, … Lessells, C. M. (1998). Warmer springs lead to mistimed reproduction in Great Tits (Parus major). Proceedings of the Royal Society B-Biological Sciences, 265(1408), 1867–1870.

Wahl, C. M., Neils, A., & Hooper, D. (2013). Impacts of land use at the catchment scale constrain the habitat benefits of stream riparian buffers. Freshwater Biology, 58(11), 2310– 2324. https://doi.org/10.1111/fwb.12211

Wallace, J. B., Eggert, S. L., Meyer, J. L., & Webster, J. R. (1997). Multiple trophic levels of a forest stream linked to terrestrial litter inputs. Science, 277(5322), 102–104. https://doi.org/10.1126/science.277.5322.102

Walsh, C. J., Roy, A. H., Feminella, J. W., Cottingham, P. D., Groffman, P. M., & Morgan, R. P. (2005). The urban stream syndrome: current knowledge and the search for a cure. Journal

49

of the North American Benthological Society, 24(3), 706–723.

Walsh, C. J., Sharpe, A. K., Breen, P. F., & Sonneman, J. A. (2001). Effects of urbanization on streams of the Melbourne region, Victoria, Australia. I. Benthic macroinvertebrate communities. Freshwater Biology, 46(4), 535–551.

Walsh, C. J., Waller, K. A., Gehling, J., & Mac Nally, R. (2007). Riverine invertebrate assemblages are degraded more by catchment urbanisation than by riparian deforestation. Freshwater Biology, 52(3), 574–587. https://doi.org/10.1111/j.1365-2427.2006.01706.x

Walters, D. M., Fritz, K. M., & Otter, R. R. (2008). The dark side of subsidies: adult stream insects export organic contaminants to riparian predators. Ecological Applications, 18(8), 1835–1841.

Wang, L., Robertson, D. M., & Garrison, P. J. (2007). Linkages between nutrients and assemblages of macroinvertebrates and fish in wadeable streams: Implication to nutrient criteria development. Environmental Management, 39(2), 194–212. https://doi.org/10.1007/s00267-006-0135-8

Wenger, S. J., Roy, A. H., Jackson, C. R., Bernhardt, E. S., Carter, T. L., Filoso, S., … Walsh, C. J. (2009). Twenty-six key research questions in urban stream ecology: an assessment of the state of the science. Journal of the North American Benthological Society, 28(4), 1080– 1098. https://doi.org/10.1899/08-186.1

Whitaker, D. M., Carroll, A. L., & Montevecchi, W. A. (2000). Elevated numbers of flying insects and insectivorous birds in riparian buffer strips. Canadian Journal of Zoology, 78(5), 740–747. https://doi.org/10.1139/z99-254

Winkler, D. W., & Allen, P. E. (1996). The seasonal decline in Tree Swallow clutch size: physiological constraint or strategic adjustment? Ecology, 77(3), 922–932.

Winkler, D. W., Dunn, P. O., & Mcculloch, C. E. (2002). Predicting the effects of climate change on avian life-history traits. Proceedings of the National Academy of Sciences of the United States of America, 99(21), 13595–13599.

Winkler, D. W., Luo, M. K., & Rakhimberdiev, E. (2013). Temperature effects on food supply and chick mortality in tree swallows (Tachycineta bicolor). Oecologia, 173(1), 129–138. https://doi.org/10.1007/s00442-013-2605-z

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Chapter 2. Urbanization mediates the effects of water quality and climate on Tree Swallow (Tachycineta bicolor) body condition and reproductive success

Authors: Joseph W. Corra and S. Mažeika P. Sullivan

51

Abstract

Aerial insectivorous birds – swifts, swallows, flycatchers, and nightjars – have experienced alarming population declines in eastern North America. Meanwhile, urbanization continues to increase rapidly, with urban land use comprising 69.4 million acres (3.6% of total) in the contiguous United States as of 2018. Multiple environmental changes are associated with urbanization, including alterations to local climate, changes in habitat structure, and potential shifts in both terrestrial and emergent aquatic flying insects on which aerial insectivorous birds depend. In particular, emergent aquatic insects have recently been shown to provide energetic advantages to aerial insectivorous birds as compared to terrestrial insects, yet are highly sensitive to losses in water quality. Here, we investigated the linkages between urbanization, water quality, and Tree Swallow (Tachycineta bicolor) reproductive success and body condition at seven river-riparian sites representing urban and natural/protected land use in Columbus, Ohio over four consecutive springs (2014-2017). Urban nests were associated with higher fledging success and earlier laying dates. Nestling mass was not related to land use, but exhibited high interannual variability, as did body condition in adult males and Hg in both adult birds and nestlings. The interaction of year × land use also had a significant influence on Hg in nestlings, suggesting that contaminant transfers to nestlings at urban sites are related to shifts in the composition of insect prey assemblages. Multiple characteristics of urban sites appeared to drive these patterns including differences in mean and extreme air temperatures, and measures of water quality (e.g., water temperature, nutrient concentrations, turbidity). Overall, despite the loss of environmental quality generally attributed to cities, Tree Swallows exhibited greater reproductive success in urban settings where aquatic insects were larger, climate more amenable

52 to egg and nestling survival, and the breeding season longer. However, chronic effects of elevated Hg body burdens in urban areas may disadvantage individuals in other ways. Further, characteristics of urban landscapes that benefit Tree Swallows may not advantage other aerial insectivorous birds owing to differences in life-history and foraging strategies. These findings implicate urbanization, local climate, and water quality as important considerations in the conservation of riparian aerial insectivorous birds.

53

Introduction

Aerial insectivorous birds – a guild comprising swallows, nightjars, swifts, and flycatchers – have experienced alarming population declines in North America, with population losses outpacing declines observed in any other avian group (Environment Canada, 2012; Nebel et al., 2010). Population trends among species in the guild exhibit spatial and temporal variation, but there is broad evidence for intensified declines for most species beginning in the 1980s (A.

C. Smith et al., 2015). Population declines in individual bird species are likely in response to a complex set of conditions, including loss of suitable breeding habitat (MacHunter et al., 2006), predation (Bohning-Gaese, Taper, & Brown, 1993), and environmental degradation or habitat loss on wintering grounds (Fraser et al., 2012; Michel et al., 2016) and migration stopover sites

(Rioux-Paquette et al., 2014). However, comparable declines observed across multiple, taxonomically-diverse species in the guild implicate changes in the availability and quality of flying insect prey (Nebel et al., 2010).

Riparian zones are often hotspots of aerial insectivorous bird diversity (Naiman,

Decamps, & Pollock, 1993), where condition of aquatic-riparian ecosystems can influence many aspects of aerial insectivorous bird ecology, including individual health (Smits & Fernie, 2013) and reproductive success (McCarty & Secord, 1999; Sullivan, Watzin, & Hession, 2006). In particular, aquatic insects that emerge from the water as winged adults (i.e., emergent aquatic insects) provide a critical nutritional subsidy to many riparian aerial insectivorous birds (Jackson

& Fisher, 1986; Nakano & Murakami, 2001). For instance, Kautza and Sullivan (2016b) showed that 41% of riparian swallows’ energy was derived from aquatic primary production via emergent insects. For terrestrial consumers including birds, aquatic insects may provide

54 energetic advantages over terrestrial insects; Twining et al. (2016) experimentally showed that

Tree Swallow (Tachycineta bicolor) nestlings fed a diet high in long-chain omega-3 polyunsaturated fatty acids – found in greater concentrations in aquatic insects – exhibited faster growth rates and better body condition than nestlings fed non-enriched diets.

Anthropogenic landscape changes in a watershed, such as urbanization, can have strong impacts on aquatic ecosystems (Allan, 2004; Meyer, Paul, & Taulbee, 2005; Roth, Allan, &

Erickson, 1996). Urban land cover accounted for 69.4 million acres of land (3.6% of total) in the contiguous United States as of 2018, an increase of 470% since 1945 (Merrill & Leatherby,

2018). Further, urban land use is expected to triple worldwide between 2000 and 2030, outpacing human population growth (Seto, Guneralp, & Hutyra, 2012). Urban encroachment into riparian zones is associated with marked changes in avian community composition, distribution, and reproductive success (Blair, 1996; Rodewald & Bakermans, 2006; Rodewald, Kearns, &

Shustack, 2013), commonly associated with the removal of riparian vegetation (Lussier et al.,

2006), habitat fragmentation and altered vegetation structure (Crooks, Suarez, & Bolger, 2004), and the increased presence of invasive biota (Rottenborn, 1999). The Urban Stream Syndrome

(Meyer, Paul, & Taulbee, 2005) synthesizes the collective impacts of urbanization on streams flowing through urbanized catchments including channelization of streams, increased runoff, homogenized stream geomorphology, flashier hydrographs, elevated concentrations of nutrients and contaminants, and fragmentation of in-stream habitat (Vietz, Walsh, & Fletcher, 2015;

Walsh et al., 2005). These alterations commonly lead to reduced diversity of aquatic insects

(Gage, Spivak, & Paradise, 2004; Urban et al., 2006), with potential implications for aerial insectivorous birds (Stenroth et al., 2015; Twining et al., 2016). For example, Alberts, Sullivan,

55 and Kautza (2013) found that riparian swallows breeding in urban habitats were more dependent on emergent insects and fed at higher trophic levels than rural swallows, thereby increasing their exposure to aquatic contaminants. Stenroth et al. (2015) demonstrated that agricultural development in riparian corridors was related to smaller average body size in flying insect assemblages, which in turn were related to the distribution of insectivorous birds in riparian habitats, which were associated with forested streams and large-bodied insects.

Climatic conditions may also influence avian populations and phenology, including the timing of breeding and migration, reproductive success, and the ranges of individual species

(McCarty, 2001). For instance, 55% of Ohio’s bird species are projected to be climate-threatened or climate-endangered (i.e., in danger of losing more than 50% of their current range by 2080 or

2050, respectively) if present warming trends continue (Langham et al., 2014). Climate change is predicted to exert a similar influence on the phenology and range of flying insects (Hughes,

2000), with potentially adverse effects on insectivorous birds (Visser et al., 1998). Altered temperature regimes may influence birds directly (Becker & Weisberg, 2015; Pipoly et al., 2013) or indirectly via changes to invertebrate assemblages (Jonsson et al., 2015) and insect activity

(Nooker, Dunn, & Whittingham, 2005). At local scales, the urban heat-island effect is a chief driver of localized climate variability, as urban environments typically experience elevated temperatures owing to reduced vegetation cover, diminished evapotranspiration, lower surface albedo, numerous reflective vertical surfaces, higher concentrations of suspended airborne particulate matter, and the presence of anthropogenic heat sources (Oke, 1982; US EPA, 2008).

At the regional scale, climate conditions may have an additional impact on aerial insectivores at the population level. For instance, climate change may facilitate multiple broods per season, a

56 phenomenon which has been observed with increased frequency at the southern end of the Tree

Swallow’s breeding range (Monroe et al., 2008).

Considered together, the complex relationships among climate, water quality, and urbanization demand a broad perspective to adequately address their impacts on aerial insectivorous birds. Here, we investigated the potential impact of these factors on reproductive success and individual body condition of Tree Swallows over four years at a suite of urban and protected (i.e., forested or other natural vegetation) riparian study sites in and around Columbus,

Ohio, USA. We hypothesized that water quality would mediate the effects of urbanization via changes in nutritional subsidies to Tree Swallows (i.e., the availability and composition of invertebrate prey assemblages) (Fig. 2.1). Specifically, we predicted that increased landscape urbanization would be related to impaired water quality and reduced diversity (McKinney, 2002;

Walsh et al., 2005) and quality (Roy et al., 2003) of both aquatic and terrestrial insects, resulting in lower reproductive success and body condition in Tree Swallows. We also anticipated that emergent aquatic insects would serve to transfer contaminants from aquatic ecosystems to Tree

Swallows (Walters, Fritz, & Otter, 2008), with potential implications for swallow survival and reproduction (Rowse, Rodewald, & Sullivan, 2014; Sullivan & Rodewald, 2012). In particular, we predicted that mercury (Hg) blood concentrations would be elevated in urbanized landscapes in both adult and nestling swallows (Driscoll et al., 2007). Further, we predicted that higher spring temperatures at urban sites would be related to earlier clutch initiation (Dunn & Winkler,

1999; Hussell, 2003) and that greater variability in air temperatures (i.e., greater extremes) would be negatively associated with fledging success, clutch size, and nestling mass owing to both direct effects on individual condition (e.g., increased stress) and indirect effects via prey

57 availability (Andrew et al., 2017; Ardia, Cooper, & Dhondt, 2006; Winkler, Luo, &

Rakhimberdiev, 2013).

Methods and Analyses

Study area and experimental design

The Tree Swallow was selected as the model aerial insectivore as this species readily makes use of artificial nest boxes, limiting external perturbations (e.g., predation, interspecific competition, and nest parasitism) and enabling capture of both juveniles and adults (Jones,

2003). At the outset of breeding season in late March each year (2014-2017), nest boxes were deployed at seven riparian study sites distributed across urban and natural/protected land cover in the Scioto River system (Ohio, USA) (Table 2.1, Fig. 2.2). The Scioto River watershed drains

16,868 km2 as it flows south into the Ohio River (Ohio Environmental Protection Agency, 2014).

The middle Scioto River catchment lies within the Columbus Metropolitan Area. Our study sites were located on the Scioto River mainstem (6th order), as well as on two major tributaries, the

Olentangy River (5th order) and Big Darby Creek (4th order). The middle Scioto River basin is composed of developed (45%) and cultivated (40%) lands, with forests comprising only 6% of the total land cover (Ohio Environmental Protection Agency, 2014). Each study site consisted of a 500-m river reach and the adjacent riparian zone, extending 500-m from each bank perpendicular to the river channel. This spatial extent was selected because (1) Tree Swallows generally forage within 500 m of their nest boxes (Dunn & Hannon, 2016; Quinney & Ankney,

1985) and (2) 500 m is considered sufficient to capture the influence of land use and land cover on stream water chemistry at the local scale (Strayer et al., 2003). Nest boxes were constructed

58 according to Golondrinas de las Américas (2011), with identical interior dimensions (12.7-cm ×

12.7-cm × 27.9-cm) to control for possible differences in clutch size due to cavity size (Rendell

& Robertson, 1993). Nest boxes were mounted on a combination of steel rebar and electrical conduit to deter predators; predator guards constructed from PVC pipe were installed at sites where predation was observed or suspected although such instances were very rare. Five to six nest boxes were deployed at each study site, spaced at moderate distance from one another (~20 m) to avoid territorial overlap (Muldal, Gibbs, & Robertson, 1985). All nest boxes were monitored at 2-3 day intervals from shortly before to the end of the breeding season each year.

Nestlings were monitored and accessed via the swinging side-door of the nestbox, while adult birds were captured using the nestbox’s ‘wig-wag’ (i.e., trapdoor at the entrance hole) which can be closed from a distance with a length of monofilament fishing line, thus trapping the adult bird inside and facilitating capture via the side-door (Golondrinas de las Américas, 2011). All captured birds were banded in accordance with North American Bird Banding Program’s banding protocols (U.S. Geological Survey, 2018).

Land use and land cover

Using Quantum GIS (QGIS Development Team, 2017), the percentage of forested or wetland land cover and developed land cover with impervious surfaces at each stream reach were quantified. Land-cover data were obtained using the 2011 National Land Cover Database, which classifies land cover for the continental United States at a 30-m spatial resolution (Homer et al.,

2015). A 500-m buffer was delineated on each side of the stream channel as described above.

Land-cover percentage for each land-cover class (forest, developed, et al) was then calculated for

59 each delineated buffer. Additional GIS layers were added to calculate the percent impervious surface (U.S. Geological Survey, 2014a), percentage canopy cover (U.S. Geological Survey,

2014b), and mean human population density (U.S. Census Bureau, 2010).

Tree Swallow reproductive success and body condition

Nestboxes were observed 2-3 times per week to determine if and when breeding pairs of

Tree Swallows established nests. Tree Swallow reproductive success was measured using several metrics: clutch initiation date (Julian date, no. calendar days), clutch size (no. eggs), no. of eggs successfully hatched, no. of nestlings successfully fledged, and mean nestling weight (mg). The latter measure, nestling mass, is considered an important metric of reproductive success – songbird fledgling mass has been strongly linked to post-fledging avoidance of predation (Naef-

Daenzer & Grüebler, 2016), so the diminished condition of smaller swallows may impair their odds of post-fledging survival. Tree Swallow females lay one egg per day (Hussell & Quinney,

1987; Nooker, Dunn, & Whittingham, 2005); clutch initiation date was determined based on this rate (e.g., observing a nest with two eggs indicated that laying began the day prior). To measure growth rates, each brood was weighed at four, seven, and ten days using an OHAUS Scout Pro

SP601 portable balance (Parsippany, New Jersey, USA). Any disturbance of nesting or laying, such as predation or destruction of eggs by competing cavity-nesters (typically the House

Sparrow [Passer domesticus] or the House Wren [Troglodytes aedon]) was recorded, though such events were very infrequent. Furthermore, nesting material deposited by House Sparrows or

House Wrens was removed in an effort to discourage competition. Tree Swallows occasionally produce second clutches if their first broods fledge sufficiently early (Monroe et al., 2008).

60

However, second clutches as well as replacement clutches (i.e., those laid when the first clutch is destroyed or fails to hatch) are often smaller than the first (Karagicheva et al., 2016), as are late- season clutches of any sort (Winkler & Allen, 1996) so these clutches were identified and not considered in our analyses. Clutches that were destroyed or reduced due to factors outside of the scope of this project (e.g., predation, interspecific competition, flooding) were also identified and such clutches were excluded from subsequent analyses. Similarly, if such factors were implicated in nestling deaths, the affected broods were excluded from subsequent analyses.

Morphological and individual health measurements were performed on all captured swallows. We weighed all adults and measured tarsus length (mm) using handheld calipers.

These measurements, in conjunction with body mass measurements, may be used to estimate individual body fat and general condition (Labocha & Hayes, 2012). Scaled mass index (SMI) was used as an estimate of body fat percentage in passerine birds and served as the primary metric of individual body condition for adult birds. SMI was calculated using the method developed by Peig and Green (2017) as follows:

푏푆푀퐴 퐿0 푀̂푖 = 푀푖 [ ] , 퐿푖 where Mi is the body mass of the individual bird, and Li is the appropriate linear body measurement (in the case of passerine birds, tarsus length). L0 is the mean linear body measurement of the study sample, and bSMA is the scaling exponent determined by dividing the slope from an ordinary least squares regression by the Pearson’s correlation coefficient. Due to sex differences in morphology and mass, male and female swallows were modeled separately in subsequent analysis. Nestling birds were weighed at ~13 days, but morphological measurements were not taken; consequently, SMI was not calculated for nestlings. 61

Blood samples were drawn from the jugular vein of adults and nestlings (e.g., Sullivan &

Vierling, 2012) on day 13 after hatching. Concentrations of Hg were estimated from these blood samples by applying a small amount of blood was applied to a dried blood spot (DBS) card, considered a suitable method for measuring contaminant concentrations in wild birds (Shlosberg et al., 2011). DBS cards were sent to Michigan State University’s Diagnostic Center for

Population and Animal Health (Lansing, MI, USA) to determine concentrations of Hg, measured in parts per billion (ppb). Blood plasma glucose was also estimated from blood samples, as blood glucose levels are a commonly used indicator of avian body condition. For instance, hyperglycemia or hypoglycemia in birds may indicate septicemia or stress, respectively (Harris,

2009; Lill, 2011). A droplet of blood was collected on a plastic cuvette and placed inside a

HemoCue Glucose 201 Analyzer (Brea, CA, USA) glucose meter for analysis. Since we could safely draw only a limited quantity of blood from any individual bird, 2-3 replicates of each of the above measurements were made per brood.

Climate, chemical water quality, and nutrients

Climate variables included temperature and humidity measurements, collected using deployable ThermocronTM and HygrochronTM Ibutton (Baulkham Hills, NSW, AU) passive temperature and humidity sensors, respectively, installed inside the nest boxes. One temperature sensor was installed inside each nest box at each study site. In addition, one humidity sensor was installed per site. All sensors were set to record temperature and/or humidity at 6-hour intervals to obtain a daily average. These data were downloaded from the sensors at close of each field season.

62

A suite of chemical water-quality variables was measured at each study site twice per year (mid-late May and mid-late July). Water samples were collected at the thalweg and both stream edges at upstream, middle, and downstream sections of each reach, for a total of nine

250-mg water samples per site. These samples were then sent to The Ohio State University’s

Service Testing and Research Laboratory (Wooster, OH, USA) for analysis of total phosphorus

(mg L-1), total nitrogen (mg L-1), phosphate (mg L-1), nitrate (mg L-1), ammonia (mg L-1), total dissolved solids (mg L-1), and mercury (Hg; ppt). At the same nine locations per site, water temperature, pH, conductivity, and dissolved oxygen content were also measured using a handheld Hach sensION+ Portable Meter (Loveland, CO, USA). In addition, water samples were collected in 60-mg plastic bottles in the stream thalweg at the upstream, middle, and downstream of each reach (three samples total per reach) and analyzed in a Hach 2100N Turbidimeter

(Loveland, CO, USA) to measure the Nephelometric Turbidity Units (NTUs) of each sample. All water-chemistry data was collected in the early season (mid-late May) and again in the late season (mid-late July), yearly.

For temperature and humidity data, means were calculated for each nest box. Since temperature and humidity varied by nest box within each study site (e.g., owing to the presence of shading vegetation near some boxes), a reach-wide temperature mean was also calculated for each reach and year. Separate means were calculated for 30-d periods: one for the earlier part of the breeding season from 30 April to 29 May (inclusive), and one for the latter part of the season,

30 May to 29 June (inclusive). Most clutch initiations were expected to fall within the designated early 30-d period from late April through May, while most nestling growth and fledging was expected to occur within the 30-d period from late May through June.

63

Extreme temperatures were evaluated by counting the number of days during the May-

June breeding season in which the temperature passed a designated limit, following methodology developed by Pipoly et al. (2013). Extreme heat days were those in which the highest recorded daily temperature exceeded the 90th percentile of all high temperatures measured for the time period (May-June) in all next boxes across all 4 years of data. Similarly, extreme cold days were those in which the lowest recorded daily temperature fell below the 10th percentile of all low temperatures in the same timeframe.

Aquatic and terrestrial insects

Tree Swallow food resources, in the form of flying insect prey, were sampled for 10 d in mid-late May and again for 10 d in mid-late July at each of the study sites, aligning with climatic and water-chemistry measurements. For emergent aquatic insects, two floating, 1-m2 pyramid- style emergent traps (Kautza & Sullivan, 2015) were deployed at each study site (upstream and downstream sections) for two 10-d periods. Likewise, two cloth mesh 1-m × 1-m × 0.6-m

Malaise traps (MegaView Science Co., Taichung, Taiwan; Townes, 1972) were deployed in nearshore vegetation at upstream and downstream locations at each site, suspended from trees at a height of 1-m for two 10-d periods per breeding season. Any insects from families of aquatic origin (e.g., Chironomidae) were excluded so that only terrestrial families of flying insects were considered from Malaise traps. All invertebrates collected from boluses and traps were stored in

70% ethanol solution before being enumerated and identified to family using Johnson and

Triplehorn (2005) and Merritt, Cummins, and Berg (2008). Insects were dried in a 60°C oven and weighed by family, reach, and collection period. Insect capture rate (i.e., no. of insects m-2

64

10 d-1), family richness, and average body size (g, dry mass) were calculated. Due to the presence of a few very large insects in some of the samples (in some instances, 2-3 orders of magnitude larger than the typical insect), median insect body size (i.e., dry mass) was used for subsequent analysis.

Statistical analyses

All statistical analyses were performed using the R statistical package version 3.4.4 (R

Core Team, 2018) and the R Studio package version 1.1.453 (RStudio Team, 2016). Reach-wide means were calculated for each water-quality/nutrient parameter for each year and collection period (e.g., May or July). Principal component analysis (PCA) was then run on the water- chemistry/nutrient data and LULC data. We retained axes with eigenvalues >1 (Rencher, 1995), from which we selected PC1 to represent an Urban Stream Index (USI) similar to Alberts et al.

(2013) (see Results for details), which was used as a predictor variable in subsequent linear regressions (see below).

We used linear-mixed effects models (LMMs) as our main statistical tool in order to test for the potential effects of urbanization on Tree Swallow reproductive responses and measures of individual body condition. The following variables were modeled: clutch initiation date, clutch size, no. successfully fledged, nestling mass, male SMI, female SMI, adult Hg blood concentration, nestling Hg blood concentration, and nestling blood glucose. For individual body condition models, it was necessary to log10-transform the response variables to meet assumptions of normality. Year, urbanization (i.e., a categorical variable indicating the site’s land use: urban or natural/protected) and an urbanization × year interaction term were included as fixed effects,

65 with study site included as a random effect. Nestbox nested within study site was also included a random effect in the models in which nestling responses were included. The model for blood glucose did not include the year or urbanization-year interaction as fixed effects, since there was only one year (2017) of data available. Hg blood concentration data were available for the years

2014-2016 only. LMMs were developed using lmerTest version 3.0 (Kuznetsova et al., 2017) in

R. LmerTest was used to evaluate random and fixed effects from the models, including the coefficients and p-values for fixed effects. The overall effect of each variable (i.e., the sum-to- zero contrast) was also assessed via p-values and F-statistics calculated with the afex package version 0.22-1 (Singmann et al., 2018), which employs the Kenward-Roger approximation for degrees-of-freedom values. R2 values, both marginal (fixed effects) and conditional (fixed + random effects), were determined for each model with the MuMIn package (Bartoń, 2018), which calculates a pseudo-R2 for mixed-effects models. In addition, we explored potential mechanisms (i.e., USI as well as individual measures of water chemistry, nutrient concentrations, air temperature, flying insect prey) driving Tree Swallow reproductive success and body condition with post-hoc multiple regression. Multiple regression models incorporated year as a categorical variable, as many of our predictor variables (particularly the measures of local climate) had considerable interannual variability.

An alpha level of α ≤ 0.05 was used as the threshold of statistical significance, while α ≤

0.10 was employed as evidence of a trend. Note that the afex package reports p-values to only two decimal places, except in cases where p < 0.01.

66

Results

Physicochemical and climatic variability between urban and natural/protected sites

We observed variability in water-chemistry and nutrient concentrations between urban and natural/protected sites (Table 2.2). Concentrations of many nutrients and contaminants were higher, on average, at the urban sites. Hg concentrations, for example, were ~1.8x greater at urban sites than at natural/protected sites. Mean turbidity of the water column at urban sites was

~30% lower than their natural/protected counterparts, while water temperature at urban sites was

0.9 °C higher than at natural/protected sites.

Principal component analysis was performed using three land-use/land-cover variables and nine water-chemistry and nutrient variables (Table 2.3). PC1 – with an eigenvalue of 7.48 and accounting for 62.3% of the variance among the selected variables – served as our USI. This axis was primarily influenced by human population density, total nitrogen, Hg, canopy cover, nitrate, impervious surface, dissolved oxygen, and water temperature. The results of the USI closely correspond with the urban/natural dichotomy established by classifying sites based on impervious surface coverage (Table 2.1), with some variability given the inclusion of other urban characteristics (e.g., “Mussel” USI was driven mostly by human population density and water- quality chemistry conditions).

We observed sizeable and consistent differences in air temperature between urban and natural/protected reaches (Fig. 2.3). On average, urban reaches were warmer than protected reaches through the breeding season from 30 Apr – 28 Jun. This disparity was similar in both the early period from 30 Apr – 29 May (urban: 18.9 °C; protected: 17.1 °C) (Fig. 2.3a) and the late period from 30 May – 28 June. (urban: 24.0 °C; protected: 22.5 °C) (Fig. 2.3b). Moreover,

67 urban reaches experienced fewer days of extreme cold (Fig. 2.3c) and more days of extreme heat

(Fig. 2.3d). Urban sites experienced an average of five days of extreme cold and 11 days of extreme heat between 30 Apr – 28 June, compared to nine days of extreme cold and seven days of extreme heat at natural/protected sites.

Invertebrate prey assemblages between urban and natural/protected reaches

Our measures of flying insect family richness, abundance, and average body size revealed variability between the urban and natural/protected sites and across the four years of the study

(Fig. 2.4). For emergent aquatic insects, there was little distinction in family richness (Fig. 2.4a) or abundance (Fig. 2.4b; estimated via rate-of-capture) between urban and natural/protected sites.

However, median emergent aquatic insect body size was over 4x larger at urban reaches over the course of the study (Fig. 2.4c). For terrestrial flying insects, the opposite held true: median insect body size at the natural/protected sites was over twice that of urban reaches (Fig. 2.4c). The natural/protected sites also exhibited higher terrestrial insect family richness and abundance.

Tree Swallow reproductive success

We used linear mixed models (LMMs) to evaluate differences in reproductive response variables by land use and over time. We observed little variability in clutch size, either across years (LMM: p = 0.440; Table 2.4, Fig. 2.5a) or between urban and protected sites (LMM: p =

0.710), with some evidence of an interaction effect for year × land use (LMM: p = 0.090); nests at urban sites produced about one less egg in 2015 than in the previous year (LMM: p = 0.045).

There was also a trend toward earlier clutch initiation at urban sites (LMM: p = 0.060; Table 2.4,

68

Fig. 2.5b). Land use was a significant factor for number of successfully fledged young, which was significantly higher at the urban nesting sites than at protected sites (LMM: p = 0.009; Table

2.4, Fig. 2.5c), with urban nests yielding, on average, ~1.5 > fledglings each year than their protected counterparts. Nestling mass at ~13 d was significantly different by year (LMM: p =

0.006; Table 2.4, Fig. 2.5d); average nestling mass ranged from 22.5 g in 2014 to 19.2 g in 2015

(p = 0.001), and from 21.9 g in 2016 (p = 0.594) to 20.4 g in 2017 (p = 0.037). In addition, urban nests produced the highest average nestling mass in 2015 (LMM: p = 0.038; Fig. 2.5d). Site, included as a random effect in our models, emerged as an influential factor for nestling mass only, where the inclusion of random effects increased the R2 from 0.13 to 0.35.

We investigated, via regression models, some possible mechanisms driving variability in reproductive responses. For no. fledged, the USI was positively related to fledging success (p <

0.001; Fig. 2.6a). The no. of days of extreme cold, on the other hand, was negatively associated with fledgling success (p = 0.003; Fig. 2.6b). Similarly, nestling mass was negatively related to the no. of extreme heat days during the breeding season (p = 0.003; Fig. 2.7a). Clutch initiation date was also related to temperature, with earlier laying associated with higher average temperatures in the early part of the season (p = 0.039; Fig. 2.7b).

Tree Swallow individual body condition

For several body condition indices, variability was fairly limited. Neither male (LMM: p

= 0.650) nor female (LMM: p = 0.680) SMI varied by land use alone (Table 2.4; Fig. 2.8a).

However, male swallows exhibited significant annual variability (LMM: p = 0.010; Table 2.4), with the highest SMI in 2016 (LMM: p = 0.027; but note that no adult male Tree Swallows were

69 captured in 2015). There was no significant difference in Hg blood concentrations between swallows at urban and protected sites for adults (LMM: p = 0.440) or nestlings (LMM: p =

0.920; Table 2.4, Fig. 2.8b), though the latter had an interaction effect with year (LMM: p <

0.001; Table 2.4), which was related to lower Hg among nestlings at urban sites in 2015 and

2016. Nestlings with the lowest average blood concentrations of Hg were observed in 2016 (p <

0.001), a year that coincided with very low observed Hg concentrations in the water column.

Both adults and nestling Hg concentrations were heavily influenced by site and/or site × nestbox, suggesting that local-scale variability among sites was important. For instance, the USI emerged as a strong predictor of elevated Hg (p = 0.001; Fig. 2.9). For 2017, nestling blood glucose showed no significant differences between site types (LMM: p = 0.31; Table 2.4, Fig. 2.8c), although random effects (site, site × nestbox) were very influential (R2 marginal = 0.05, R2 conditional = 0.41; Table 2.4).

Discussion

Urbanization can have a dramatic impact on avian communities and ecosystem function

(Schlesinger, Manley, & Holyoak, 2008). For instance, meta-analysis by Chamberlain et al.

(2009) of ten species of urban-breeding North American and European passerine birds, though revealing some variability among species, showed a general trend toward smaller clutches, fewer successfully fledged young, earlier clutch initiation dates, and lower nestling mass in among urban breeders. In the Columbus-area study system of our current study, Rodewald et al. (2013) observed that the aerial insectivorous Acadian Flycatcher (Empidonax virescens) exhibited diminished reproductive output from 2001-2011. Given the reliance of riparian swallows and

70 other aerial insectivores on aquatic invertebrate subsidies both in our study system and elsewhere

(Kautza & Sullivan, 2016b; Nakano & Murakami, 2001), we expected that losses in water quality and altered temperature regimes in urban areas would be reflected in urban-breeding Tree

Swallows, both through impaired reproductive success and compromised body condition in both nestlings and adults.

Our results challenged some of our expectations. We observed limited differences in nestling mass or clutch size between urban Tree Swallows and their counterparts nesting in natural areas. There was also little variability in clutch size by land-use, although nestling mass exhibited strong interannual differences: we observed significantly lower mean nestling mass over all study sites in 2015, a result we also observed across the study system in 2017. Of all reproductive responses, nestling mass also had the most variability among sites, suggesting local, site-specific effects such as microclimatic differences (e.g. Fig. 2.7a) may have exerted a greater influence on nestling mass than urbanization alone. Extreme heat, for example, which was more pronounced at our urban sites (Fig. 2.3d), has been related thermal stress, inhibited growth, and even increased mortality in nestling passerine birds of various species (e.g., Andrew et al., 2017;

Cunningham et al., 2013; Rodríguez & Barba, 2016). Water quality, via its influences emergent insects (e.g., body size, Hg contamination) was also implicated as an urban-related factor linked to swallow responses. For example, urbanization in the reach (estimated via the USI) was strongly related blood Hg concentrations in adult Tree Swallows (Fig. 2.9).

In a notable divergence from our hypothesis, the number of successfully fledged young was higher for urban broods than at the natural/protected sites. Although there was a trend toward interannual variability in fledging rates, the effect of urban land use had, by far, the

71 strongest relationship (Table 2.4, Fig. 2.5c). As clutch size did not vary substantially with land use (Table 2.4, Fig. 2.5a), lower nest productivity at natural/protected sites must be attributed to higher mortality of eggs and/or nestlings. Since nests experiencing losses from predation, interspecific competition, floods, and similar events were excluded from our analyses, this mortality is due to starvation, exposure, disease, or other indeterminate causes, some of which can be related to the environmental conditions measured, including local climate and food availability. Fledging success, more than other factors, may play a leading role in driving population growth. Population models developed by Cox et al. (2018), based on 42-year study of a Tree Swallow population in Ontario, Canada, indicated that fledging success and overwinter survival were the two most influential drivers of population change, while clutch size was of limited importance.

Urbanization, as described by the USI, was related to increased fledging success (Fig.

2.6a). Variability in the quantity and quality (Fig. 2.4) of insect prey among sites and land-use types was likely a factor related to the influence of land use on Tree Swallow fledging success.

Previous studies of insectivorous birds including for Barn Swallows (Teglhøj, 2017) and House

Wrens (Newhouse, Marra, & Johnson, 2008) have reported lower nestling mass among birds breeding in developed areas, results which are thought to be related to reduced prey quality or lower prey abundance. However, we found that the median body size of emergent insects was greater at our urban sites relative to the natural/protected sites (Fig. 2.4c). Although terrestrial insect body size was greater at the natural/protected sites, experimental work by Twining et al.

(2016) suggests that the benefit of aquatic insects, which are relatively rich in omega-3 long- chain polyunsaturated fatty acids, may be more important than terrestrial insect prey availability.

72

Other evidence indicates that Tree Swallows selectively catch larger-bodied prey when provisioning nestlings (McCarty & Winkler, 1999a; Quinney & Ankney, 1985), underscoring the importance of prey body size as a determinant of fledging success and post-fledging survival.

Among our four reproductive response metrics, only responses of clutch initiation date conformed to our hypotheses, with urban birds laying eggs significantly earlier than their natural/protected counterparts (Fig. 2.5b). Evidence implicates climate as the likely driver behind the observed differences in clutch initiation. There were considerable differences in both air temperatures means (Fig. 2.3a) and frequency of extreme temperatures (Fig. 2.3c, d) between urban sites and protected sites, implicating the urban heat island effect as the likeliest driver of air temperature variability among sites (Oke, 1982). The early temperature period (30 April – 29

May) captured most of the clutch initiations (91.5%). In our investigation of potential drivers of reproductive response, air temperature during this period emerged at the strongest predictor of clutch initiation date, a finding that was consistent across all years of data (Fig. 2.7b). Urban sites were both markedly warmer and associated with significantly earlier clutch initiation (Fig. 2.5b), strongly suggesting local-scale climate conditions are the mechanism driving these differences.

The availability of insect prey has been identified as a breeding cue in Tree Swallows (Nooker,

Dunn, & Whittingham, 2005), suggesting that temperature-driven insect activity and/or emergence as the link between temperature and clutch initiation (Eeva, Veistola, & Lehikoinen,

2000). Our results echo findings by Hussell (2003), who observed strong and consistent correlations between laying date and local-scale air temperature in early May among Tree

Swallows from 1969-2001. More recently, Bourret et al. (2015) not only revealed similar correlations between regional-scale temperatures and Tree Swallow clutch initiation, but strong

73 evidence that the rise in interannual spring temperature was associated with advances in Tree

Swallow clutch initiation dates from 2004-2013.

Although our results did not show consistent increases in spring air temperature year-to- year 2014-2017, the strong relationship between clutch initiation and early spring temperatures suggest that elevated temperatures may be linked to advanced laying dates among Tree Swallows across our study system. These results are consistent with the analysis of Tree Swallow breeding data from 1959-1991 performed by Dunn and Winkler (1999), which showed advances in laying dates across the breeding range linked to climate change, including a more pronounced rate of change at the southern edge of the range. Air temperature was identified as potentially influential driver of the number fledged. The frequency of extreme cold days was related to fewer fledged young (Fig. 2.6b). Again, the role of land use was prominent – natural/protected sites were associated with more days of extreme cold (Fig. 2.3c). Cold snaps are strongly associated with elevated nestling mortality, as they suppress flying insect activity while increasing Tree Swallow energy demands (Winkler, Luo, & Rakhimberdiev, 2013). Higher spring temperatures have been identified as potentially beneficial for reproductive success among some species of breeding birds (Becker & Weisberg, 2015). The warmer conditions associated with urban heat islands – that is, overall higher temperatures, fewer days of extreme cold, and more stable overnight temperatures (Tam, Gough, & Mohsin, 2015) – may both mitigate the impact of periods of cold weather, while intensifying flying insect activity early in the morning relative to cooler non- urban areas. Tree Swallow nests observed by Ardia (2013) yielded results in line with these expectations, as higher nighttime temperatures in nestboxes were related to higher fledge rates.

The benefit of increased nest temperature on Tree Swallow nestling mass was also evidenced in

74 experimental treatments by Perez et al. (2008). As noted above, however, higher temperature regimes may have negative implications for aerial insectivore body condition and reproductive success. For instance Ardia (2013) found that extreme heat (> 35°C) in Tree Swallow nests was related to both impaired body condition (including reduced mass) and reduced fledging success.

As Ohio lies near the southern end of the Tree Swallow’s breeding range (Robertson, Stutchbury,

& Cohen, 2011), it is likely that extreme heat events will have a greater impact on Ohio Tree

Swallow populations. However, higher spring temperatures may provide an additional benefit to

Tree Swallows by extending the breeding season, a phenomenon which has been linked to greater fecundity in some other passerine species (e.g. Townsend et al., 2013). Monroe et al.

(2008) observed regular double-brooding among a population of Tree Swallows in Virginia, a practice which dramatically increases swallow reproductive output and may have a positive influence on population growth. High-resolution data that capture the effects of temperature across both local and broader spatial scales, including potential impacts on nestling and egg mortality (Ardia, 2013) or nestling growth (Pipoly et al., 2013), will be critical in understanding impacts of both urbanization and climate change on aerial insectivores.

We did not observe our significant variability by land use among individual body condition metrics. Regarding blood concentrations of Hg, variability among sites was far more influential than land use for both adults and nestlings, highlighting the potential importance of local-scale variability (Table 2.4, Fig. 2.8b). We observed similar results among blood glucose levels in nestlings (Fig. 2.8c). In addition, we observed extreme interannual variability among nestlings for blood Hg concentrations (Table 2.4, Fig. 2.8b). In another finding inconsistent with our expectations, urban nests in 2015 and 2016 were associated with reduced blood Hg.

75

Although land use by itself was not identified as a strong predictor of Hg concentrations, the results of our mixed-effects model (Table 2.4) indicate substantial variability among study sites beyond the urban/protected land-use dichotomy. For example, the USI, which reflects a suite of continuous variable of urbanization, strongly predicted Hg blood concentrations in adult swallows, supporting the premise that emergent insects serve as vectors for aquatic contaminants to terrestrial consumers (Walters, Fritz, & Otter, 2008; Sullivan & Rodewald, 2012). The elevated concentrations found in the adult swallows (t = 2.814, p = 0.010) align with previous findings in the same region by Alberts, Sullivan and Kautza (2013), who speculated that higher concentrations among adult swallows may be a due to nestlings’ rapid growth or a consequence of prey selection; the latter would also account for the strong positive relationship between urbanization and Hg in adult Tree Swallows, compared to the negative relationship we observed in nestlings in 2015 and 2016. Further, Tree Swallows tend to forage over open fields or water

(Ghilain & Bélisle, 2008; McCarty & Winkler, 1999a), therefore stream channel width or the distribution of riparian vegetation may cause swallows to prey more or less on aquatic insects, thereby increasing their exposure to Hg (Alberts, Sullivan, & Kautza, 2013). Hg concentrations in both adult and nestling swallows also appeared to track interannual variation in Hg concentrations measured in the water column – for instance, adult swallows across the study system and urban nestlings exhibited significantly lower Hg in 2016 (Table 2.4), a year with the lowest observed Hg concentrations in the river reaches – supporting a link for the transfer of contaminants between the aquatic and terrestrial systems.

Hg has an array of well-documented harmful health impacts on birds (Boening, 2000); among Tree Swallows, weakened immune response has been identified as a major adverse effect

76 of Hg exposure, with potential long-term consequences for fitness (Hawley, Hallinger, & Cristol,

2009). Further, Hg has been linked to impaired reproductive success in Tree Swallows (Brasso

& Cristol, 2008). In fact, the adverse effects of Hg on reproductive response may manifest even when there are the effect on individual health is undetected: in the same Columbus-area study system, Rowse, Rodewald, and Sullivan (2014) reported that Hg concentrations in aerial insectivorous Acadian Flycatchers were related to fewer fledged young, even though there was no observed impact on body condition.

Conclusions

Urban land use has transformed landscapes across North America, with far-reaching and persistent ecological consequences. However, our results indicate that these changes may not prove uniformly harmful to aerial insectivorous birds. On the contrary, some characteristics of the urban environment may advantage aerial insectivores in terms of reproductive success. For instance, in our Columbus-area study system, we observed greater fledging success at urban nests, which may be linked to both greater body size of energetically profitable emergent insects and to microclimatic differences. Temperature regimes in urban areas may mitigate the impact of early spring cold snaps, affording a longer breeding season, and spurring insect activity. If climate change prompts phenological changes in the timing of spring migration as predicted

(Crick, 2004), the risks associated with early nesting could be mitigated by the availability of warmer urban breeding habitats. However, climate shifts may also have unfavorable consequences. Global climate change is expected increase frequency of extreme heat events

(Gerald & Tebaldi, 2004), the impacts of which will be intensified by the urban heat island effect

77

(Stone, Hess, & Frumkin, 2010). Cities like Columbus – home to the 8th-most intense summer urban heat island among the 60 largest U.S. cities (Kenward et al., 2014) – may experience the most intense impact. Nestling mass been identified as a strong indicator of post-fledging survival, itself a key predictor of population growth (Cox et al., 2018). Post-fledging survival was not addressed by our research, but it represents a key line of investigation for understanding of aerial insectivore population declines.

Other hazards associated with urbanization are also evident. Among these, perhaps the most notable in our results are the differences in Hg body burdens. The relationship between Hg in the aquatic environment and bioaccumulation of Hg in Tree Swallows indicates not only a danger from Hg toxicity, but also a vulnerability to the transfer of other contaminants from aquatic systems, such as selenium (Ohlendorf et al., 1988) and PCBs.

It is important to note that Tree Swallows may be unique in their responses to urbanization, and other aerial insectivorous species might fare differently. Foraging strategy, nesting strategy, and dietary preferences may all figure in individual species’ responses to urbanization. For instance, altered vegetation structure and composition in urban habitats may be detrimental to the foraging efforts of salliers like flycatchers (Schneider & Miller, 2014). Cavity- nesters like Tree Swallows may benefit from the proliferation of artificial nestboxes (Norris et al., 2018) and the open-water environments of impounded urban rivers, while nesting sites for otherwise urban-tolerant species, like Chimney Swifts (Environment Canada, 2007) and

Common Nighthawks (Brigham, 1989) have declined due to changes in building construction.

Overall, the joint effects of urbanization, water quality, and climate change on Tree Swallows

78 and other aerial insectivorous birds will be a complex puzzle, yet an important one to solve in order to mitigate continued population losses of this guild.

79

References

Adams, T. S., & Sterner, R. W. C. N.-289. (2000). The effects of dietary nitrogen on trophic level 15N enrichment. Limnology and Oceanography, 45(3), 601–607.

Alberts, J. M., Sullivan, S. M. P., & Kautza, A. (2013). Riparian swallows as integrators of landscape change in a multiuse river system: Implications for aquatic-to-terrestrial transfers of contaminants. Science of the Total Environment, 463–464, 42–50. https://doi.org/10.1016/j.scitotenv.2013.05.065

Allan, J. D. (2004). Influence of land use and landscape setting on the ecological status of rivers. Limnetica, 23(3–4), 187–198. https://doi.org/10.1146/annurev.ecolsys.35.120202.110122

Allan, J. D., Erickson, D. L., & Fay, J. (1997). The influence of catchment land use on stream integrity across multiple spatial scales. Freshwater Biology, 37(1), 149–161.

Allan, J. D., & Flecker, A. S. (1993). Biodiversity conservation in running waters. BioScience, 43(1), 32–43.

Anderson, C., & Cabana, G. (2007). Estimating the trophic position of aquatic consumers in river food webs using stable nitrogen isotopes. Journal of the North American Benthological Society, 26(2), 273–285. https://doi.org/10.1899/0887- 3593(2007)26[273:ETTPOA]2.0.CO;2

Andrew, S. C., Hurley, L. L., Mariette, M. M., & Griffith, S. C. (2017). Higher temperatures during development reduce body size in the zebra finch in the laboratory and in the wild. Journal of Evolutionary Biology, 30(12), 2156–2164. https://doi.org/10.1111/jeb.13181

Ardia, D. R. (2013). The effects of nestbox thermal environment on fledging success and haematocrit in Tree Swallows. Avian Biology Research, 6(2), 99–103. https://doi.org/10.3184/175815513X13609528031394

Ardia, D. R., Cooper, C. B., & Dhondt, A. (2006). Warm temperatures lead to early onset of incubation, shorter incubation periods and greater hatching asynchrony in Tree Swallows Tachycineta bicolor at the extremes of their range. Journal of Avian Biology, 37(2), 137– 142.

Ardia, D. R., Wasson, M. F., & Winkler, D. W. (2006). Individual quality and food availability determine yolk and egg mass and egg composition in tree swallows Tachycineta bicolor. Journal of Avian Biology, 37(3), 252–260.

Arnold, C. L., Boison, P. J., & Patton, P. C. (1982). Sawmill Brook: an example of rapid geomorphic change related to urbanization. The Journal of Geology, 90(2), 155–166.

Arnold, C. L., & Gibbon, C. J. (1996). Impervious surface coverage: The emergence of a key 80

environmental indicator. Journal of the American Planning Association, 62(2), 243–258.

Aubin, A., Bourassa, J. P., & Pellisier, M. (1973). An effective emergence trap for the capture of mosquitoes. Mosquito News, 33(2), 251–252.

Bartoń, K. (2018). MuMIn. Retrieved from https://cran.r-project.org/package=MuMIn

Baxter, C. V, Fausch, K. D., & Saunders, W. C. (2005). Tangled webs: Reciprocal flows of invertebrate prey link streams and riparian zones. Freshwater Biology, 50(2), 201–220. https://doi.org/10.1111/j.1365-2427.2004.01328.x

Bearhop, S., Thompson, D. R., Waldron, S., Russell, I. C., Alexander, G., & Furness, R. W. (1999). Stable isotopes indicate the extent of freshwater feeding by cormorants Phalacrocorax carbo shot at inland fisheries in England. Journal of Applied Ecology, 36(1), 75–84. https://doi.org/10.1046/j.1365-2664.1999.00378.x

Bearhop, S., Waldron, S., Votier, S. C., & Furness, R. W. (2002). Factors That influence assimilation rates and fractionation of nitrogen and carbon stable isotopes in avian blood and feathers. Physiological and Biochemical Zoology, 75(5), 451–458.

Beck, M. L., Hopkins, W. A., & Jackson, B. P. (2014). Variation in riparian consumer diet composition and differential bioaccumulation by prey influence the risk of exposure to elements from a recently remediated fly ash spill. Environmental Toxicology and Chemistry, 33(11), 2595–2608. https://doi.org/10.1002/etc.2719

Becker, M. E., & Weisberg, P. J. (2015). Synergistic effects of spring temperatures and land cover on nest survival of urban birds. The Condor, 117(1), 18–30. https://doi.org/10.1650/CONDOR-14-1.1

Benke, A., Wallace, J., & Harrison, J. (2001). Food web quantification using secondary production analysis: predaceous …. Freshwater …, 329–346. https://doi.org/10.1046/j.1365-2427.2001.00680.x

Bennett, P. M., & Hobson, K. A. (2009). Trophic structure of a boreal forest arthropod community revealed by stable isotope (d13C, d15N) analyses. Entomological Science, 12(1), 17–24. https://doi.org/10.1111/j.1479-8298.2009.00308.x

Blair, R. B. (1996). Land use and avian species diversity along an urban gradient. Ecological Applications, 6(2), 506–519.

Boening, D. W. (2000). Ecological effects, transport, and fate of mercury: a general review. Chemosphere, 40(12), 1335–1351.

Bohning-Gaese, K., Taper, M. L., & Brown, J. H. (1993). Are declines in North American insectivorous songbirds due to Causes on the breeding range? Conservation Biology, 7(1), 76–86. Retrieved from http://www.jstor.org/stable/2386644%0Ahttp://about.jstor.org/terms 81

Booth, D. B., & Jackson, C. R. (1998). Urbanization of aquatic systems: degradation thresholds, stormwater detection, and the limits of mitigation. Journal of the American Water Resources Association, 33(5), 1077–1090.

Both, C., Van Turnhout, C. A. M., Bijlsma, R. G., Siepel, H., Van Strien, A. J., & Foppen, R. P. B. (2010). Avian population consequences of climate change are most severe for long- distance migrants in seasonal habitats. Proceedings of the Royal Society B-Biological Sciences, 277(1685), 1259–1266. https://doi.org/10.1098/rspb.2009.1525

Bourret, A., Bélisle, M., Pelletier, F., & Garant, D. (2015). Multidimensional environmental influences on timing of breeding in a tree swallow population facing climate change. Evolutionary Applications, 8(10), 933–944. https://doi.org/10.1111/eva.12315

Brasso, R. L., & Cristol, D. A. (2008). Effects of mercury exposure on the reproductive success of Tree Swallows (Tachycineta bicolor). Ecotoxicology, 17(2), 133–141. https://doi.org/10.1007/s10646-007-0163-z

Brigham, R. M. (1989). Roost and nest sites of Common Nighthawks: are gravel roofs important? The Condor, 91, 122–124.

Brown, L. R., Cuffney, T. F., Coles, J. F., Fitzpatrick, F., McMahon, G., Steuer, J., … May, J. T. (2009). Urban streams across the USA: lessons learned from studies in 9 metropolitan areas. Journal of the North American Benthological Society, 28(4), 1051–1069. https://doi.org/10.1899/08-153.1

Burdon, F. J., & Harding, J. S. (2008). The linkage between riparian predators and aquatic insects across a stream-resource spectrum. Freshwater Biology, 53(2), 330–346. https://doi.org/10.1111/j.1365-2427.2007.01897.x

Burger, J., & Gochfeld, M. (1997). Risk, mercury levels, and birds: relating adverse laboratory effects to field biomonitoring. Environmental Research, 172(2), 160–172.

Butler, R. W. (1988). Population dynamics and migration routes of Tree Swallows, Tachycineta bicolor, in North America. Journal of Field Ornithology, 59(4), 395–402.

Cabana, G., & Rasmussen, J. (1996). Comparison of aquatic food chains using nitrogen isotopes. Proceedings of the National Academy of Sciences of the United States of America, 93(20), 10844–10847.

Caquet, T. (2006). Use of carbon and nitrogen stable isotope ratios to assess the effects of environmental contaminants on aquatic food webs. Environmental Pollution, 141(1), 54–59. https://doi.org/10.1016/j.envpol.2005.08.029

Caut, S., Angulo, E., & Courchamp, F. (2008). Caution on isotopic model use for analyses of consumer diet. Canadian Journal of Zoology, 86(5), 438–445. https://doi.org/10.1139/Z08-

82

012

Caut, S., Angulo, E., & Courchamp, F. (2009). Variation in discrimination factors (Δ15N and Δ13C): The effect of diet isotopic values and applications for diet reconstruction. Journal of Applied Ecology, 46(2), 443–453. https://doi.org/10.1111/j.1365-2664.2009.01620.x

Chalmers, A. T., Krabbenhoft, D. P., Metre, P. C. Van, & Nilles, M. A. (2014). Effects of urbanization on mercury deposition and accumulation in New England. Environmental Pollution, 192, 104–112. https://doi.org/10.1016/j.envpol.2014.05.003

Chamberlain, D., Hatchwell, B., & Gaston, K. J. (2009). Avian productivity in urban landscapes: a review and meta-analysis. Ibis, 151(1), 1–18. https://doi.org/10.1111/j.1474- 919X.2008.00899.x

Chislock, M. F., Doster, E., Zitomer, R. A., & Wilson, A. E. (2013). Eutrophication: causes, consequences, and controls in aquatic ecosystems. Nature Education Knowledge, 4(4), 10. Retrieved from http://www.wilsonlab.com/publications/2013_NE_Chislock_et_al.pdf

Collier, K. J., Bury, S., & Gibbs, M. (2002). A stable isotope study of linkages between stream and terrestrial food webs through spider predation. Freshwater Biology, 47(9), 1651–1659. https://doi.org/10.1046/j.1365-2427.2002.00903.x

Compin, A., & Céréghino, R. (2003). Sensitivity of aquatic insect species richness to disturbance in the Adour–Garonne stream system (France). Ecological Indicators, 3(2), 135–142. https://doi.org/10.1016/S1470-160X(03)00016-5

Compson, Z. G., Adams, K. J., Edwards, J. A., Maestas, J. M., Whitham, T. G., & Marks, J. C. (2013). Leaf litter quality affects aquatic insect emergence: contrasting patterns from two foundation trees. Oecologia, 173(2), 507–519. https://doi.org/10.1007/s00442-013-2643-6

Cox, A. R., Robertson, R. J., Fedy, B. C., Rendell, W. B., & Bonier, F. (2018). Demographic drivers of local population decline in Tree Swallows (Tachycineta bicolor). The Condor, 120(4), 842–851. https://doi.org/10.1650/CONDOR-18-42.1

Crick, H. Q. P. (2004). The impact of climate change on birds. Ibis, 146(Suppl. 1), 48–56.

Cristol, D., Brasso, R., Monroe, A., Condon, R., Fovargue, A., Friedman, S., … White, A. (2008). The movement of aquatic mercury through terrestrial food webs. Science, 320(5874), 335.

Crooks, K. R., Suarez, A. V., & Bolger, D. T. (2004). Avian assemblages along a gradient of urbanization in a highly fragmented landscape. Biological Conservation, 115(3), 451–462. https://doi.org/10.1016/S0006-3207(03)00162-9

Cummins, K. W., & Klug, M. J. (1979). Feeding ecology of stream invertebrates. Annual Review of Ecology and Systematics, 10(1), 147–172. 83

https://doi.org/10.1146/annurev.es.10.110179.001051

Cunningham, S. J., Martin, R. O., Hojem, C. L., & Hockey, P. A. R. (2013). Temperatures in excess of critical thresholds threaten nestling growth and survival in A rapidly-warming arid savanna: a study of Common Fiscals. PLoS ONE, 8(9), 1–10. https://doi.org/10.1371/journal.pone.0074613

Custer, C. M., Custer, T. W., Dummer, P. M., Munney, K. L., Midwest, U., Sciences, E., … Office, F. (2003). Exposure and effects of chemical contaminants on Tree Swallows nesting along the Housatonic River, Berkshire County, Massachusetts, USA, 1998 – 2000. Environmental Toxicology and Chemistry, 22(7), 1605–1621.

DeNiro, M. J., & Epstein, S. (1978). Influence of diet on the distribution of nitrogen isotopes in animals. Geochimica et Cosmochimica Acta, 42(3), 495–506. https://doi.org/10.1016/0016- 7037(81)90244-1

Dodds, W. K., & Smith, V. H. (2016). Nitrogen, phosphorus, and eutrophication in streams. Inland Waters, 6(2), 155–164. https://doi.org/10.5268/IW-6.2.909

Dods, P. L., Birmingham, E. M., Williams, T. D., Ikonomou, M. G., Bennie, D. T., & Elliott, J. E. (2005). Reproductive success and contaminants in tree swallows (Tachycineta bicolor) breeding at a wastewater treatment plant. Environmental Toxicology and Chemistry, 24(12), 3106–3112. https://doi.org/10.1897/04-547R.1

Driscoll, C. T., Han, Y., Chen, C. Y., Evers, D. C., Lambert, K. F., Holsen, T. M., … Munson, R. K. (2007). Mercury contamination in forest and freshwater ecosystems in the Northeastern United States. BioScience, 57(1), 17–28.

Dunn, P., & Hannon, S. J. (1992). Effects of food abundance and male parental care on reproductive success and monogamy in Tree Swallows. The Auk, 109(3), 488–499.

Dunn, P. O., & Winkler, D. W. (1999). Climate change has affected the breeding date of tree swallows throughout North America. Proceedings of the Royal Society B-Biological Sciences, 266(1437), 2487–2490.

Durance, I., & Ormerod, S. J. (2007). Climate change effects on upland stream macroinvertebrates over a 25-year period. Global Change Biology, 13(5), 942–957. https://doi.org/10.1111/j.1365-2486.2007.01340.x

Eeva, T., Veistola, S., & Lehikoinen, E. (2000). Timing of breeding in subarctic passerines in relation to food availability. Canadian Journal of Zoology, 78(1), 67–78. https://doi.org/10.1139/cjz-78-1-67

English, P. A., Green, D. J., & Nocera, J. J. (2018). Stable isotopes from museum specimens may provide evidence of long-term change in the trophic ecology of a migratory aerial

84

insectivore. Frontiers in Ecology and Evolution, 6(February), 14. https://doi.org/10.3389/FEVO.2018.00014

Environment Canada. (2007). Chimney swift (Chaetura pelagica) COSEWIC assessment and status report. Ottawa.

Environment Canada. (2012). The State of Canada’s Birds. Ottawa.

Evers, D. C., Burgess, N. M., Champoux, L., Hoskins, B., Major, A., Goodale, W. M., … Daigle, T. (2005). Patterns and interpretation of mercury exposure in freshwater avian communities in northeastern North America. Ecotoxicology, 14(1–2), 193–221.

Fausch, K. D., Baxter, C. V., & Murakami, M. (2010). Multiple stressors in north temperate streams: lessons from linked forest-stream ecosystems in northern Japan. Freshwater Biology, 55(SUPPL. 1), 120–134. https://doi.org/10.1111/j.1365-2427.2009.02378.x

Fimreite, N. (1974). Mercury contamination of aquatic birds in Northwestern Ontario. The Journal of Wildlife Management, 38(1), 120–131.

Finlay, J. C. (2001). Stable carbon isotope ratios of river biota: implications for energy flow in lotic food webs. Ecology, 82(4), 1052–1064.

Fraser, K. C., Stutchbury, B. J. M., Silverio, C., Kramer, P. M., Barrow, J., Newstead, D., … Tautin, J. (2012). Continent-wide tracking to determine migratory connectivity and tropical habitat associations of a declining aerial insectivore. Proceedings of the Royal Society B- Biological Sciences, 279(1749), 4901–4906. https://doi.org/10.1098/rspb.2012.2207

Freeman, P. L., & Schorr, M. S. (2004). Influence of watershed urbanization on fine sediment and macroinvertebrate assemblage characteristics in Tennessee ridge and valley streams. Journal of Freshwater Ecology, 19(3), 353–362. https://doi.org/10.1080/02705060.2004.9664908

Fry, B. (2006). Stable isotope ecology. Stable isotope ecology. New York: Springer Science+Business Media. https://doi.org/10.1016/j.dsr2.2015.11.009

Gage, M. S., Spivak, A., & Paradise, C. J. (2004). Effects of land use and disturbance on benthic insects in headwater streams drainging small watersheds. Southeastern Naturalist, 3(2), 345–358.

Gentes, M., Waldner, C., Papp, Z., & Smits, J. E. G. (2006). Effects of oil sands tailings compounds and harsh weather on mortality rates, growth and detoxification efforts in nestling Tree Swallows (Tachycineta bicolor). Environmental Pollution, 142(1), 24–33. https://doi.org/10.1016/j.envpol.2005.09.013

Gerald, M., & Tebaldi, C. (2004). More intense, more frequent, and longer-lasting heat waves in the 21st Century. Science, 305(August), 994–997. https://doi.org/10.1126/science.1098704 85

Ghilain, A., & Bélisle, M. (2008). Breeding success of Tree Swallows along a gradient of agricultural intensification. Ecological Applications, 18(5), 1140–1154. https://doi.org/10.1890/07-1107.1

Golondrinas de las Americas. (2011). Nest box design.

Grable, J. L., & Harden, C. P. (2006). Geomorphic response of an Appalachian Valley and Ridge stream to urbanization. Earth Surface Processes and Landforms, 31(13), 1707–1720. https://doi.org/10.1002/esp

Gray, L. J. (1993). Response of insectivorous birds to emerging aquatic insects in riparian habitats of a tallgrass prairie stream. American Midland Naturalist, 129(2), 288–300.

Gurtz, M. E., & Wallace, J. B. (1984). Substrate-mediated response of stream invertebrates to disturbance. Ecology, 65(5), 1556–1569.

Hagar, J. C., Li, J., Sobota, J., & Jenkins, S. (2012). Arthropod prey for riparian associated birds in headwater forests of the Oregon Coast Range. Forest Ecology and Management, 285, 213–226. https://doi.org/10.1016/j.foreco.2012.08.026

Hallinger, K. K., & Cristol, D. A. (2011). The role of weather in mediating the effect of mercury exposure on reproductive success in Tree Swallows. Ecotoxicology, 20(6), 1368–1377. https://doi.org/10.1007/s10646-011-0694-1

Harper, M. P. H., & Peckarsky, B. L. (2006). Emergence cues of a mayfly in a high-altitude stream ecosystem: potential response to climate change. Ecological Applications, 16(2), 612–621.

Harris, D. J. (2009). Clinical tests. Handbook of Avian Medicine (Second Edi). Elsevier Limited. Retrieved from http://dx.doi.org/

Harris, G. P., & Baxter, G. (1996). Interannual variability in phytoplankton biomass and species composition in a subtropical reservoir. Freshwater Biology, 35(3), 545–560. https://doi.org/10.1111/j.1365-2427.1996.tb01768.x

Harvey, C. J., & Kitchell, J. F. (2000). A stable isotope evaluation of the structure and spatial heterogeneity of a Lake Superior food web. Canadian Journal of Fisheries and Aquatic Sciences, 57(7), 1395–1403.

Hawkins, C. P., Hogue, J. N., Decker, L. M., & Feminella, J. W. (1997). Channel morphology, water temperature, and assemblage structure of stream insects. Journal of the North American Benthological Society, 16(4), 728–749.

Hawley, D. M., Hallinger, K. K., & Cristol, D. A. (2009). Compromised immune competence in free-living tree swallows exposed to mercury. Ecotoxicology, 18(5), 499–503. https://doi.org/10.1007/s10646-009-0307-4 86

Heinrich, K. K., Whiles, M. R., & Roy, C. (2014). Cascading ecological responses to an in- stream restoration project in a midwestern river. Restoration Ecology, 22(1), 72–80. https://doi.org/10.1111/rec.12026

Helms, B. S., Schoonover, J. E., & Feminella, J. W. (2009). Seasonal variability of landuse impacts on macroinvertebrate assemblages in streams of western Georgia, USA. Journal of the North American Benthological Society, 28(4), 991–1006. https://doi.org/10.1899/08- 162.1

Hendrickx, F., Maelfait, J., Wingerden, W. Van, Schweiger, O., Speelmans, M., Aviron, S., … Bugter, R. (2007). How landscape structure, land‐use intensity and habitat diversity affect components of total arthropod diversity in agricultural landscapes. Journal of Applied Ecology, 44(2), 340–351.

Hespenheide, H. A. (1971). Food preference and the extent of overlap in some insectivorous birds, with special reference to the Tyrannidae. Ibis, 113(1), 59–72. https://doi.org/10.1111/j.1474-919X.1971.tb05123.x

Hession, W. C., Pizzuto, J. E., Johnson, T. E., & Horwitz, R. J. (2003). Influence of bank vegetation on channel morphology in rural and urban watersheds. Geology, 31(2), 147–150. https://doi.org/10.1130/0091-7613(2003)031<0147:IOBVOC>2.0.CO;2

Homer, C. G., Dewitz, J. A., Yang, L., Jin, S., Danielson, P., Xian, G., … Megown, K. (2015). Completion of the 2011 National Land Cover Database for the conterminous United States- representing a decade of land cover change information. Photogrammetric Engineering and Remote Sensing, 81(5), 345–354.

Hughes, L. (2000). Biological consequences of global warming: is the signal already apparent? Trends in Ecology & Evolution, 15(2), 56–61. https://doi.org/10.1016/S0169- 5347(99)01764-4

Hussell, D. (2003). Climate change, spring temperatures, and timing of breeding of Tree Swallows (Tachycineta bicolor) in southern Ontario. The Auk, 120(3), 607–618.

Hussell, D., & Quinney, T. E. (1987). Food abundance and clutch size of Tree Swallows Tachycineta bicolor. Ibis, 129(1), 243–258. https://doi.org/10.1111/fwb.12476

Iwata, T., Nakano, S., & Murakami, M. (2003). Stream meanders increase insectivorous bird abundance in riparian deciduous forests. Ecography, 26(September 2002), 325–337. https://doi.org/10.1034/j.1600-0587.2003.03355.x

Jackson, A. K., Evers, D. C., Etterson, M. A., Condon, A. M., Sarah, B., Detweiler, J., … Thryothorus, D. (2011). Mercury exposure affects the reproductive success of a free-living terrestrial songbird, the Carolina Wren (Thryothorus ludovicianus). The Auk, 128(4), 759– 769. 87

Jackson, J. K., & Fisher, S. G. (1986). Secondary production, emergence, and export of aquatic insects of a Sonoran Desert stream. Ecology, 67(3), 629–638.

Johnson, N. F., & Triplehorn, C. A. (2005). c (7th ed.). Boston: Brooks/Cole.

Johnson, R. C., Jin, H., Carreiro, M. M., & Jack, J. D. (2013). Macroinvertebrate community structure, secondary production and trophic-level dynamics in urban streams affected by non-point-source pollution. Freshwater Biology, 58(5), 843–857. https://doi.org/10.1111/fwb.12090

Jones, J. (2003). Tree swallows (Tachycineta bicolor): A new model organism? The Auk, 120(3), 591–599.

Jonsson, M., Hedström, P., Stenroth, K., Hotchkiss, E. R., Vasconcelos, F. R., Karlsson, J., & Byström, P. (2015). Climate change modifies the size structure of assemblages of emerging aquatic insects. Freshwater Biology, 60(1), 78–88. https://doi.org/10.1111/fwb.12468

Jonsson, M., Strasevicius, D., & Malmqvist, B. (2012). Influences of river regulation and environmental variables on upland bird assemblages in northern Sweden. Ecological Research, 27(5), 945–954. https://doi.org/10.1007/s11284-012-0974-0

Karagicheva, J., Liebers, M., Rakhimberdiev, E., Hallinger, K. K., Saveliev, A., & Winkler, D. W. (2016). Differences in size between first and replacement clutches match the seasonal decline in single clutches in Tree Swallows Tachycineta bicolor. Ibis, 158(3), 607–613.

Kautza, A., & Sullivan, S. M. P. (2015). Shifts in reciprocal river-riparian arthropod fluxes along an urban-rural landscape gradient. Freshwater Biology, 60(10), 2156–2168. https://doi.org/10.1111/fwb.12642

Kautza, A., & Sullivan, S. M. P. (2016a). Anthropogenic and natural determinants of fish food- chain length in a midsize river system. Freshwater Science, 35(3), 895–908. https://doi.org/10.1086/685932

Kautza, A., & Sullivan, S. M. P. (2016b). The energetic contributions of aquatic primary producers to terrestrial food webs in a mid-size river system. Ecology, 97(3), 694–705. https://doi.org/10.1890/15-1095.1

Kenward, A., Yawitz, D., Sanford, T., & Wang, R. (2014). Summer in the city: Hot and getting hotter. Princeton.

Klein, R. D. (1980). Urbanization and stream quality impairment. Water Resources Bulletin, 15(4), 948–963.

Kondolf, G. M. (1995). Five elements for effective evaluation of stream restoration. Restoration Ecology. https://doi.org/10.1111/j.1526-100X.1995.tb00086.x

88

Kuznetsova, A., Brockhoff, P. B., Haubo, R., & Christensen, B. (2017). lmerTest. Retrieved from https://github.com/runehaubo/lmerTestR

Labocha, M. K., & Hayes, J. P. (2012). Morphometric indices of body condition in birds: a review. Journal of Ornithology, 153(1), 1–22. https://doi.org/10.1007/s10336-011-0706-1

Langham, G., Schuetz, J., Soykan, C., Wilsey, C., Auer, T., LeBaron, G., … Distler, T. (2014). Audubon’s Birds and Climate Change Report. New York.

Layman, C. A., Araujo, M. S., Boucek, R., Hammerschlag-Peyer, C. M., Harrison, E., Jud, Z. R., … Bearhop, S. (2012). Applying stable isotopes to examine food-web structure: An overview of analytical tools. Biological Reviews, 87(3), 545–562. https://doi.org/10.1111/j.1469-185X.2011.00208.x

Learner, M. A., & Potter, D. W. B. (1974). The seasonal periodicity of emergence of insects from two Ponds in Hertfordshire, England, with special reference to the Chironomidae (Diptera: Nematocera). Hydrobiologia, 44(4), 495–510.

Leffelaar, D., & Robertson, R. J. (1986). Equality of feeding roles and the maintenance of monogamy in Tree Swallows. Behavioral Ecology and Sociobiology, 18(3), 199–206.

Lenat, D. R. (1988). Water quality assessment of streams using a qualitative collection method for benthic macroinvertebrates. Journal of the North American Benthological Society, 7(3), 222–233. https://doi.org/10.2307/1467422

Lenat, D. R., & Crawford, J. K. (1994). Effect of land use on water quality and aquatic biota of three North Carolina Piedmont streams. Hydrobiologia, 294(3), 185–199. https://doi.org/10.3923/ijb.2012.181.191

Li, Y., & Cai, Y. (2013). Progress in the study of mercury methylation and demethylation in aquatic environments. Chinese Science Bulletin, 58(2), 177–185.

Lifjeld, J. T., Dunn, P. O., & Whittingham, L. A. (2002). Short-term fluctuations in cellular immunity of tree swallows feeding nestlings. Oecologia, 130(2), 185–190. https://doi.org/10.1007/s004420100798

Lill, A. (2011). Sources of variation in blood glucose concentrations of free-living birds. Avian Biology Research, 4(2), 78–87. https://doi.org/10.3184/175815511X13073729328092

Lussier, S. M., da Silva, S. N., Charpentier, M., Heltshe, J. F., Cormier, S. M., Klemm, D. J., … Jayaraman, S. (2008). The influence of suburban land use on habitat and biotic integrity of coastal Rhode Island streams. Environmental Monitoring and Assessment, 139(1–3), 119– 136. https://doi.org/10.1007/s10661-007-9820-1

Lussier, S. M., Enser, R. W., Dasilva, S. N., & Charpentier, M. (2006). Effects of habitat disturbance from residential development on breeding bird communities in riparian 89

corridors. Environmental Management, 38(3), 504–521. https://doi.org/10.1007/s00267- 005-0088-3

Lutz, M. A., Brigham, M. E., Krabbenhoft, D. P., Aiken, G. R., & Orem, W. H. (2009). methylmercury production and bed sediment-pore water partitioning. Environmental Science & Technology, 43(8), 2726–2732.

MacHunter, J., Wright, W., Loyn, R., & Rayment, P. (2006). Bird declines over 22 years in forest remnants in southeastern Australia: Evidence of faunal relaxation? Canadian Journal of Forest Research, 36(11), 2756–2768. https://doi.org/10.1139/x06-159

Macivor, J. S., & Lundholm, J. (2011). Insect species composition and diversity on intensive green roofs and adjacent level-ground habitats. Urban Ecosystems, 14(2), 225–241. https://doi.org/10.1007/s11252-010-0149-0

Marczak, L. B., Sakamaki, T., Turvey, S. L., Deguise, I., Wood, S. L. R., & Richardson, J. S. J. S. (2010). Are forested buffers an effecive conservation strategy for riparian fauna? An assessment using meta-analysis. Ecological Applications, 20(1), 126–134. https://doi.org/10.1890/08-2064.1

McArthur, S. L., McKellar, A. E., Flood, N. J., & Reudink, M. W. (2017). Local weather and regional climate influence breeding dynamics of Mountain Bluebirds (Sialia currucoides) and Tree Swallows (Tachycineta bicolor): a 35-year study. Canadian Journal of Zoology, 95(4), 271–277.

McCarty, J. P. (1997). Aquatic community characteristics influence the foraging patterns of Tree Swallows. The Condor, 99(1), 210–213. https://doi.org/10.2307/1370241

McCarty, J. P. (2001). Review: ecological consequences of recent climate change. Conservation Biology, 15(2), 320–331.

McCarty, J. P. (2002). The number of visits to the nest by parents is an accurate measure of food delivered to nestlings in Tree Swallows. Journal of Field Ornithology, 73(1), 9–14.

McCarty, J. P., & Secord, A. L. (1999). Reproductive ecology of Tree Swallows (Tachycineta bicolor) with high levels of polychlorinated biphenyl contamination. Environmental Toxicology and Chemistry, 18(7), 1433. https://doi.org/10.1897/1551- 5028(1999)018<1433:REOTST>2.3.CO;2

McCarty, J. P., & Winkler, D. W. (1999a). Foraging ecology and diet selectivity of Tree Swallows feeding nestlings. The Condor, 101(2), 246–254. Retrieved from http://www.jstor.org/stable/pdf/1369987.pdf

McCarty, J. P., & Winkler, D. W. (1999b). Relative importance of environmental variables in determining the growth of nestling Tree Swallows Tachycineta bicolor. Ibis, 141(2), 286–

90

296.

McIntyre, N. E. (2000). Ecology of urban arthropods: a review and a call to action. Annals of the Entomological Society of America, 93(4), 825–835. https://doi.org/10.1603/0013- 8746(2000)093[0825:EOUAAR]2.0.CO;2

McKinney, M. (2002). Urbanization, biodiversity, and conservation. BioScience, 52(10), 883– 890.

Mengelkoch, J. M., Niemi, G. J., & Regal, R. R. (2004). Diet of the nestling Tree Swallow. The Condor, 106(2), 423–429.

Merrill, D., & Leatherby, L. (2018). Here’s how America uses its land. Retrieved from https://www.bloomberg.com/graphics/2018-us-land-use/

Merritt, R. W., Cummins, K. . W., & Berg, M. B. (2008). An Introduction to the Aquatic Insects of North America (4th ed.). Dubuque: Kendall Hunt.

Meybeck, M. (1998). Man and river interface: multiple impacts on water and particulates chemistry illustrated in the Seine river basin. Hydrobiologia, 373, 1–20. https://doi.org/10.1023/A:1017067506832

Meyer, J. L., Paul, M. J., & Taulbee, W. K. (2005). Stream ecosystem function in urbanizing landscapes. Journal of the American Benthological Society, 24(3), 602–612.

Michel, N. L., Smith, A. C., Clark, R. G., Morrissey, C. A., & Hobson, K. A. (2016). Differences in spatial synchrony and interspecific concordance inform guild-level population trends for aerial insectivorous birds. Ecography, 39(8), 774–786. https://doi.org/10.1111/ecog.01798

Miller, J. R., Wiens, J. A., Hobbs, N. T., & Theobald, D. M. (2003). Effects of human settlement on bird communities in lowland riparian areas of Colorado (USA). Ecological Applications, 13(4), 1041–1059.

Minagawa, M., & Wada, E. (1984). Stepwise enrichment of 15N along food chains: Further evidence and the relation between 15N and animal age. Geochimica et Cosmochimica Acta, 48(5), 1135–1140. https://doi.org/10.1016/0016-7037(84)90204-7

Minshall, G. W. (1978). Autotropy in Stream Ecosystems. BioScience, 28(12), 767–771. https://doi.org/10.2307/1307250

Monroe, A. P., Hallinger, K. K., Brasso, R. L., & Cristol, D. A. (2008). Occurrence and implications of double brooding in a southern population of Tree Swallows. The Condor, 110(2), 382–386. https://doi.org/10.1525/cond.2008.8341

Moore, J. W., & Semmens, B. X. (2008). Incorporating uncertainty and prior information into stable isotope mixing models. Ecology Letters, 11(5), 470–480. 91

https://doi.org/10.1111/j.1461-0248.2008.01163.x

Morel, F. M. M., Kraepiel, A. M. L., & Amyot, M. (1998). The chemical cycle and bioaccumulation of mercury. Annual Review of Ecology and Systematics, 29(1), 543–566. https://doi.org/10.1146/annurev.ecolsys.29.1.543

Morse, C. C., Huryn, A. D., & Cronan, C. (2003). Impervious surface area as a predictor of the effects of urbanization on stream insect communities in Maine, USA. Environmental Monitoring and Assessment, 89(1), 95–127.

Muehlbauer, J. D., Collins, S. F., Doyle, M. W., & Tockner, K. (2014). How wide is a stream? Spatial extent of the potential “stream signature” in terrestrial food webs using meta- analysis. Ecology, 95(1), 44–55.

Muldal, A., Gibbs, H. L., & Robertson, R. J. (1985). Preferred nest spacing of an obligate cavity- nesting bird, the Tree Swallow. The Condor, 87(3), 356–363. Retrieved from http://www.jstor.org/stable/pdf/1367216.pdf

Munthe, J., Bodaly, R. A. D., Branfireun, B. A., Driscoll, C. T., Cynthia, C., Harris, R., … Harris, R. (2007). Recovery of mercury-contaminated fisheries. AMBIO: A Journal of the Human Environment, 36(1), 33–44.

Murakami, M., & Nakano, S. (2002). Indirect effect of aquatic insect emergence on a terrestrial insect population through bird predation. Ecology Letters, 5(3), 333–337. https://doi.org/10.1046/j.1461-0248.2002.00321.x

Naef-Daenzer, B., & Grüebler, M. U. (2016). Post-fledging survival of altricial birds: ecological determinants and adaptation. Journal of Field Ornithology, 87(3), 227–250. https://doi.org/10.1111/jofo.12157

Naiman, R. J., & Decamps, H. (1997). The ecology of interfaces: Riparian zones. Annual Review of Ecology, Evolution, and Systematics, 28(102), 621–658. https://doi.org/10.1146/annurev.ecolsys.28.1.621

Naiman, R. J., Decamps, H., & Pollock, M. (1993). The role of riparian corridors in maintaining regional biodiversity. Ecological Application, 3(2), 209–212. https://doi.org/10.2307/1941822

Nakano, S., & Murakami, M. (2001). Reciprocal subsidies: dynamic interdependence between terrestrial and aquatic food webs. Proceedings of the National Academy of Sciences of the United States of America, 98(1), 166–170.

Nancy B. Grimm, Sheibley, R. W., Crenshaw, C. L., Dahm, C. N., Roach, W. J., & Zeglin, L. H. (2005). N retention and transformation in urban streams. Journal of the North American Benthological Society, 24(3), 626–642.

92

Nebeker, A. V. (1971). Effect of high winter water temperatures on adult emergence of aquatic insects. Water Research, 5(9), 777–783. https://doi.org/10.1016/0043-1354(71)90100-X

Nebel, S., Mills, A., Mccracken, J. D., & Taylor, P. D. (2010). Declines of aerial insectivores in North America follow a geographic gradient. Avian Conservation & Ecology, 5(2), 1. https://doi.org/10.5751/ACE-00391-050201

Nelson, K. C., & Palmer, M. A. (2007). Stream temperature surges under urbanization and climate change: data, models, and responses. Journal of the American Water Resources Association, 43(2), 440–452.

Newhouse, M. J., Marra, P. P., & Johnson, L. S. (2008). Reproductive success of House Wrens in suburban and rural landscapes. The Wilson Journal of Ornithology, 120(1), 99–104. https://doi.org/10.1676/06-156.1

Nooker, J. K., Dunn, P. O., & Whittingham, L. a. (2005). Effects of food abundance, weather, and female condition on reproduction in Tree Swallows (Tachycineta bicolor). The Auk, 122(4), 1225–1238. https://doi.org/10.1642/0004- 8038(2005)122{[}1225:EOFAWA]2.0.CO;2

Nordlie, K. J., & Arthur, J. W. (1981). Effect of elevated water temperature on insect emergence in outdoor experimental channels. Environmental Pollution, 25(1), 53–65.

Norris, A. R., Aitken, K. E. H., Martin, K., & Pokorny, S. (2018). Nest boxes increase reproductive output for Tree Swallows in a forest grassland matrix in central British Columbia. Plos One, 13(10), e0204226. https://doi.org/10.1371/journal.pone.0204226

Ohio Environmental Protection Agency. (2014). Scioto River watershed. Retrieved from http://www.epa.ohio.gov/dsw/tmdl/sciotoriver.aspx#122556530-implementation

Ohlendorf, H. M., Kilness, A. W., Simmons, J. L., Richard, K., Hoffman, D. J., Moore, J. F., … Dakota, S. (1988). Selenium toxicosis in wild aquatic birds. Journal of Toxicology and Environmental Health, 24(1), 67–92. https://doi.org/10.1080/15287398809531141

Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108(455), 1–24. https://doi.org/10.1002/qj.49710845502

Parnell, A. C., Inger, R., Bearhop, S., & Jackson, A. L. (2010). Source partitioning using stable isotopes: Coping with too much variation. PLoS ONE, 5(3), e9672. https://doi.org/10.1371/journal.pone.0009672

Parnell, A., & Jackson, A. (2013). SIAR. Retrieved from https://cran.r-project.org/package=siar

Parnell, A., & Jackson, A. (2015). Package ‘ siar ’ documentation. https://doi.org/10.1080/07351690701310649

93

Paul, M. J., & Meyer, J. L. (2001). Streams in the urban landscape. Annual Review of Ecology and Systematics, 32, 333–365. https://doi.org/10.1146/annurev.ecolsys.32.081501.114040

Peig, J., & Green, A. J. (2017). New perspectives for estimating body condition from mass/length data: The scaled mass index as an alternative method. Oikos, 118(12), 1883– 1891.

Perez, J. H., Ardia, D. R., Chad, E. K., & Clotfelter, E. D. (2008). Experimental heating reveals nest temperature affects nestling condition in tree swallows (Tachycineta bicolor). Biology Letters, 4(5), 468–471. https://doi.org/10.1098/rsbl.2008.0266

Peters, N. E. (2009). Effects of urbanization on stream water quality in the city of Atlanta, Georgia, USA. Hydrological Processes, 23(20), 2860–2878. https://doi.org/10.1002/hyp

Peterson, B. J., & Fry, B. (1987). Stable isotopes in ecosystem studies. Annual Review of Ecology and Systematics, 18(1), 293–320. https://doi.org/10.1146/annurev.es.18.110187.001453

Piland, N. C., & Winkler, D. W. (2015). Tree Swallow frugivory in winter. Southeastern Naturalist, 14(1), 123–137.

Pilgrim, J. M., Fang, X., & Stefan, H. G. (1999). Stream temperature correlations with air temperatures in Minnesota: implications for climate warming. Journal of the American Water Resources Association, 34(5), 1109–1121.

Pipoly, I., Bókony, V., Seress, G., Szabó, K., & Liker, A. (2013). Effects of extreme weather on reproductive success in a temperate-breeding songbird. PLoS ONE, 8(11), 1–11. https://doi.org/10.1371/journal.pone.0080033

Pirrone, N., Cinnirella, S., Feng, X., Finkelman, R. B., Friedli, H. R., Leaner, J., … Mukherjee, A. B. (2010). Global mercury emissions to the atmosphere from anthropogenic and natural sources. Atmospheric Chemistry and Physics, 10(13), 5951–5964. https://doi.org/10.5194/acp-10-5951-2010

Polis, G. A., Anderson, W. B., & Holt, R. D. (1997). Toward an integration of landscape and food web ecology: The dynamics of spatially subsidized food webs. Annual Review of Ecology and Systematics, 28, 289–316.

Post, D. M. (2002). Using stable isotopes to estimate trophic position: models, methos, and assumptions. Ecology, 83(3), 703–718. https://doi.org/Doi 10.2307/3071875

Post, D. M., Pace, M. L., & Hairston, N. G. (2000). Ecosystem size determines food chain-length in lakes. Nature, 405(6790), 1047–1049.

Poulin, B., Lefebvre, G., & Paz, L. (2010). Red flag for green spray: adverse trophic effects of Bti on breeding birds. Journal of Applied Ecology, 47(4), 884–889. 94

https://doi.org/10.1111/j.1365-2664.2010.01821.x

Powell, G. V. N. (1983). Industrial effluents as a source of mercury contamination in terrestrial riparian vertebrates. Environmental Pollution Series B, Chemical and Physical, 5(1), 51–57.

Power, M. E., & Dietrich, W. E. (2002). Food webs in river networks. Ecological Research, 17(4), 451–471.

QGIS Development Team. (2017). QGIS Geographic Information System. Open Source Geospatial Foundation Project.

Quinney, T. E., & Ankney, C. D. (1985). Prey size selection by Tree Swallows. The Auk, 102(2), 245–250.

Quinney, T. E., Hussell, D. J. T., Ankney, C. D., & Rowan, P. (1986). Sources of variation in the growth of Tree Swallows. The Auk, 103(April), 389–400.

R Core Team. (2018). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Retrieved from https://www.r-project.org

Ramírez, A., De Jesús-Crespo, R., Martinó-Cardona, D. M., Martínez-Rivera, N., & Burgos- Caraballo, S. (2009). Urban streams in Puerto Rico: what can we learn from the tropics? Journal of the North American Benthological Society, 28(4), 1070–1079. https://doi.org/10.1899/08-165.1

Rau, G. H., Sweeney, R. E., Kaplan, I. R., Mearns, A. J., & Young, D. R. (1981). Differences in animal 13C, 15N and D abundance between a polluted and an unpolluted coastal site: Likely indicators of sewage uptake by a marine food web. Estuarine, Coastal and Shelf Science, 13(6), 701–707. https://doi.org/10.1016/S0302-3524(81)80051-5

Razeng, E., & Watson, D. M. (2015). Nutritional composition of the preferred prey of insectivorous birds: popularity reflects quality. Journal of Avian Biology, 46(1), 89–96. https://doi.org/10.1111/jav.00475

Reavie, E. D., Jicha, T. M., Angradi, T. R., Bolgrien, D. W., & Hill, B. H. (2010). Algal assemblages for large river monitoring: Comparison among biovolume, absolute and relative abundance metrics. Ecological Indicators, 10(2), 167–177. https://doi.org/10.1016/j.ecolind.2009.04.009

Ren, W., Zhong, Y., Meligrana, J., Anderson, B., Watt, W. E., Chen, J., & Leung, H. (2003). Urbanization, land use, and water quality in Shanghai 1947 – 1996. Environment International, 29(5), 649–659. https://doi.org/10.1016/S0160-4120(03)00051-5

Rencher, A. C. (1995). Methods of multivariate analysis. New York: John Wiley and Sons, Inc.

Rendell, W. B., & Robertson, R. J. (1989). Nest-site characteristics, reproductive success and 95

cavity avilaiblity for Tree Swallows breeding in natural cavities. The Condor, 91(4), 875– 885.

Rendell, W. B., & Robertson, R. J. (1993). Cavity size, clutch‐size and the breeding ecology of Tree Swallows Tachycineta bicolor. Ibis, 135(3), 305–310. https://doi.org/10.1111/j.1474- 919X.1993.tb02848.x

Richardson, J. S., & Sato, T. (2015). Resource subsidy flows across freshwater-terrestrial boundaries and influence on processes linking adjacent ecosystems. Ecohydrology, 8(3), 406–415. https://doi.org/10.1002/eco.1488

Richmond, E. K., Rosi, E. J., Walters, D. M., Fick, J., Hamilton, S. K., Brodin, T., … Grace, M. R. (2018). A diverse suite of pharmaceuticals contaminates stream and riparian food webs. Nature Communications, 9(1), 4491. https://doi.org/10.1038/s41467-018-06822-w

Rioux-Paquette, S., Pelletier, F., Garant, D., & Bélisle, M. (2014). Severe recent decrease of adult body mass in a declining insectivorous bird population. Proceedings of the Royal Society B: Biological Sciences, 281(1786). https://doi.org/10.1098/rspb.2014.0649

Robertson, R. J., Stutchbury, B. J., & Cohen, R. R. (2011). Tree Swallow. Retrieved March 1, 2017, from https://birdsna.org/Species-Account/bna/species/011/articles/introduction

Rodewald, A. D., & Bakermans, M. H. (2006). What is the appropriate paradigm for riparian forest conservation? Biological Conservation, 128(2), 193–200. https://doi.org/10.1016/j.biocon.2005.09.041

Rodewald, A. D., Kearns, L. J., & Shustack, D. P. (2013). Consequences of urbanizing landscapes to reproductive performance of birds in remnant forests. Biological Conservation, 160, 32–39. https://doi.org/10.1016/j.biocon.2012.12.034

Rodrigues, L., Train, S., Bovo-Scomparin, V., Jati, S., Borsalli, C., & Marengoni, E. (2009). Interannual variability of phytoplankton in the main rivers of the Upper Paraná River floodplain, Brazil: influence of upstream reservoirs. Brazilian Journal of Biology, 69(2), 501–516. https://doi.org/10.1590/S1519-69842009000300006

Rodríguez, S., & Barba, E. (2016). Nestling growth is impaired by heat stress: an experimental study in a mediterranean Great Tit population. Zoological Studies, 55(40), 1–13. https://doi.org/10.6620/ZS.2016.55-40

Roth, N. E., Allan, J. D., & Erickson, D. L. (1996). Landscape influences on stream biotic integrity assessed at multiple spatial scales. Landscape Ecology, 11(3), 141–156. https://doi.org/10.1007/BF02447513

Rottenborn, S. C. (1999). Predicting the impacts of urbanization on riparian bird communities. Biological Conservation, 88(3), 289–299. https://doi.org/10.1016/S0006-3207(98)00128-1

96

Rounick, J. S., & Winterbourn, M. J. (1986). Stable carbon isotopes and carbon flow in ecosystems. BioScience, 36(3), 171–177. https://doi.org/10.2307/1310304

Rowse, L. M., Rodewald, A. D., & Sullivan, S. M. P. (2014). Pathways and consequences of contaminant flux to Acadian flycatchers (Empidonax virescens) in urbanizing landscapes of Ohio, USA. Science of the Total Environment, 485–486(1), 461–467. https://doi.org/10.1016/j.scitotenv.2014.03.095

Roy, A. H., Rosemond, A. D., Paul, M. J., Leigh, D. S., & Wallace, J. B. (2003). Stream macroinvertebrate response to catchment urbanisation (Georgia, U.S.A.). Freshwater Biology, 48(2), 329–346.

RStudio Team. (2016). RStudio: Integrated Development Environment for R. Boston: RStudio, Inc. Retrieved from http://www.rstudio.com/

Rubin, D. B. (1988). Using the SIR algorithm to simulate posterior distributions. Bayesian Statistics 3: Proceedings ofthe Third Valencia International Meeting, June 1–5, 1987. Oxford.

Schaffers, A. P., Raemakers, I. P., Sýkora, K. V, & ter Braak, C. J. F. (2008). Arthropod assemblages are best predicted by plant species composition. Ecology, 89(3), 782–794. https://doi.org/10.1890/07-0361.1

Schindler, D. W. (1978). Factors regulating phytoplankton production and standing crop in the world’s freshwaters. Limnology and Oceanography, 23(3), 478–486. https://doi.org/10.4319/lo.1978.23.3.0478

Schlesinger, M. D., Manley, P. N., & Holyoak, M. (2008). Distinguishing stressors acting on land bird communities in an urbanizing environment. Ecology, 89(8), 2302–2314. https://doi.org/10.1890/07-0256.1

Schneider, S. C., & Miller, J. R. (2014). Response of avian communities to invasive vegetation in urban forest fragments. The Condor, 116(3), 459–471. https://doi.org/10.1650/CONDOR-13-009R1.1

Schueler, T. R. (1994). The importance of imperviousness. Watershed Protection Techniques, 1(3), 100–111.

Seto, K. C., Guneralp, B., & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences, 109(40), 16083–16088. https://doi.org/10.1073/pnas.1211658109

Shlosberg, A., Rumbeiha, W. K., Lublin, A., & Kannan, K. (2011). A database of avian blood spot examinations for exposure of wild birds to environmental toxicants: The DABSE biomonitoring project. Journal of Environmental Monitoring, 13(6), 1547–1558.

97

https://doi.org/10.1039/c0em00754d

Singmann, H., Bolker, B., Westfall, J., & Aust, F. (2018). afex. Retrieved from https://github.com/singmann/afex

Smith, A. C., Hudson, M.-A. R., Downes, C. M., & Francis, C. M. (2015). Change points in the population trends of aerial-insectivorous birds in North America: synchronized in time across species and regions. PLoS ONE, 10(7), 1–23. https://doi.org/10.1371/journal.pone.0130768

Smith, V. H., Tilman, G. D., & Nekola, J. C. (1998). Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environmental Pollution, 100(1– 3), 179–196. https://doi.org/10.1016/S0269-7491(99)00091-3

Smits, J. E. G., & Fernie, K. J. (2013). Avian wildlife as sentinels of ecosystem health. Comparative Immunology, Microbiology and Infectious Diseases, 36(3), 333–342. https://doi.org/10.1016/j.cimid.2012.11.007

Sponseller, R. A., Benfield, E. F., & Valett, H. M. (2001). Relationships between land use, spatial scale and stream macroinvertebrate communities. Acta Psychiatrica Scandinavica, 46(10), 1409–1424. https://doi.org/10.1111/j.1600-0447.1963.tb07839.x

Stanton, R. S., Lark, R. G. C. O. G. C., & Morrissey, C. A. M. (2017). Intensive agriculture and insect prey availability influence oxidative status and return rates of an aerial insectivore. Ecosphere, 8(3), e01746. https://doi.org/10.1002/ecs2.1746

Stenroth, K., Polvi, L. E., Fältström, E., Jonsson, M., & Science, E. (2015). Land-use effects on terrestrial consumers through changed size structure of aquatic insects. Freshwater Biology, 60(1), 136–149. https://doi.org/10.1111/fwb.12476

Steuer, J. J., Bales, J. D., Giddings, E. M. P., Steuer, J. J., & Giddings, E. M. P. (2009). Relationship of stream ecological conditions to simulated hydraulic metrics across a gradient of basin urbanization Published by : The University of Chicago Press on behalf of the Society for Freshwater Science Relationship of stream ecological conditions, 28(4), 955–976. https://doi.org/10.1899/08-157.1

Stewart, P. M., Butcher, J. T., & Swinford, T. O. (2000). Land use, habitat, and water quality effects on macroinvertebrate communities in three watersheds of a lake Michigan associated marsh system. Aquatic Ecosystem Health and Management, 3(1), 179–189. https://doi.org/10.1080/14634980008656999

Stone, B., Hess, J. J., & Frumkin, H. (2010). Urban form and extreme heat events: Are sprawling cities more vulnerable to climate change than compact cities? Environmental Health Perspectives, 118(10), 1425–1428. https://doi.org/10.1289/ehp.0901879

98

Strasevicius, D., Jonsson, M., Nyholm, N. E. I., & Malmqvist, B. (2013). Reduced breeding success of Pied Flycatchers Ficedula hypoleuca along regulated rivers. Ibis, 155(2), 348– 356. https://doi.org/10.1111/ibi.12024

Strayer, D. L., Beighley, R. E., Thompson, L. C., Brooks, S., Nilsson, C., Pinay, G., & Naiman, R. J. (2003). Effects of land cover on stream ecosystems: Roles of empirical models and scaling issues. Ecosystems, 6(5), 407–423. https://doi.org/10.1007/s10021-002-0170-0

Stutchbury, B. J., & Robertson, R. J. (1985). Floating populations of female Tree Swallows. The Auk, 102(3), 651–654.

Sullivan, S. M. P., Boaz, L. E., & Hossler, K. (2016). Fluvial geomorphology and aquatic-to- terrrestrial Hg export are weekly coupled in small urban streams of Columbus, Ohio. Water Resources Research, 52(4), 2822–2839. https://doi.org/10.1002/2014WR015716

Sullivan, S. M. P., Hossler, K., & Cianfrani, C. M. (2015). Ecosystem structure emerges as a strong determinant of food-chain length in linked stream–riparian ecosystems. Ecosystems, 18(8), 1356–1372. https://doi.org/10.1007/s10021-015-9904-7

Sullivan, S. M. P., Manning, D. W. P., & Davis, R. P. (2018). Do the ecological impacts of dam removal extend across the aquatic–terrestrial boundary? Ecosphere, 9(4), 1–19. https://doi.org/10.1002/ecs2.2180

Sullivan, S. M. P., & Rodewald, A. D. (2012). In a state of flux: The energetic pathways that move contaminants from aquatic to terrestrial environments. Environmental Toxicology and Chemistry, 31(6), 1175–1183. https://doi.org/10.1002/etc.1842

Sullivan, S. M. P., & Vierling, K. T. (2012). Exploring the influences of multiscale environmental factors on the American dipper Cinclus mexicanus. Ecography, 35(7), 624– 636. https://doi.org/10.1111/j.1600-0587.2011.07071.x

Sullivan, S. M. P., Watzin, M. C., & Hession, W. C. (2006). Differences in the reproductive ecology of belted kingfishers (Ceryle alcyon) across streams with varying geomorphology and habitat quality. Waterbirds, 29(3), 258–270. https://doi.org/Doi 10.1675/1524- 4695(2006)29[258:Ditreo]2.0.Co;2

Tam, B. Y., Gough, W. A., & Mohsin, T. (2015). The impact of urbanization and the urban heat island effect on day to day temperature variation. Urban Climate, 12, 1–10. https://doi.org/10.1016/j.uclim.2014.12.004

Taylor, L. R. (1963). Analysis of the effect of temperature on insects in flight. Journal of Animal Ecology, 32(1), 99–117.

Teglhøj, P. G. (2017). A comparative study of insect abundance and reproductive success of barn swallows Hirundo rustica in two urban habitats. Journal of Avian Biology, 48(6), 846–853.

99

https://doi.org/10.1111/jav.01086

Thomas, D. W., Blondel, J., Perret, P., Lambrechts, M. M., & Speakman, J. R. (2001). Energetic and fitness costs of mismatching resource supply and demand in seasonally breeding birds. Science, 291(5513), 2598–2601.

Thorp, J. H., & Delong, M. D. (1994). The riverine productivity model: An heuristic view of carbon sources and organic processing in large river ecosystems. Oikos, 70(2), 305–308.

Townes, H. (1972). A light-weight Malaise trap. Entomological News, 83, 239–247.

Townsend, A. K., Sillett, T. S., Lany, N. K., Kaiser, S. A., Rodenhouse, N. L., Webster, M. S., & Holmes, R. T. (2013). Warm springs, early lay dates, and double brooding in a North American migratory songbird, the Black-throated Blue Warbler. PLoS ONE, 8(4), e59467. https://doi.org/10.1371/journal.pone.0059467

Tromboni, F., & Dodds, W. K. (2017). Relationships between land use and stream nutrient concentrations in a Highly urbanized tropical region of Brazil: thresholds and riparian zones. Environmental Management, 60(1), 30–40. https://doi.org/10.1007/s00267-017- 0858-8

Twining, C. W., Brenna, J. T., Lawrence, P., Shipley, J. R., Tollefson, T. N., Winkler, D. W., … Winkler, D. W. (2016). Omega-3 long-chain polyunsaturated fatty acids support aerial insectivore performance more than food quantity. Proceedings of the National Academy of Sciences of the United States of America, 113(46), 10920–10925. https://doi.org/10.1073/pnas.1616962113

Twining, C. W., Shipley, J. R., & Winkler, D. W. (2018). Aquatic insects rich in omega-3 fatty acids drive breeding success in a widespread bird. Ecology Letters, 12(21), 1812–1820. https://doi.org/10.1111/ele.13156

U.S. Census Bureau. (2010). TIGER/Line shapefile, 2010, 2010 state, Ohio, 2010 census block state-based. Washington: U.S. Census Bureau.

U.S. Geological Survey. (2014a). NLCD 2011 percent developed imperviousness (2011 edition, amended 2014) - National Geospatial Data Asset (NGDA) land use land cover. Sioux Falls: U.S. Geological Survey.

U.S. Geological Survey. (2014b). NLCD2011 USFS percent tree canopy (cartographic version). Sioux Falls: U.S. Geological Survey.

U.S. Geological Survey. (2018). Bird Banding Laboratory. Retrieved from https://www.usgs.gov/centers/pwrc/science/bird-banding-laboratory

Uesugi, A., & Murakami, M. (2007). Do seasonally fluctuating aquatic subsidies influence the distribution pattern of birds between riparian and upland forests? Ecological Research, 100

22(2), 274–281. https://doi.org/10.1007/s11284-006-0028-6

Urban, M. C., Skelly, D. K., Burchsted, D., Price, W., & Lowry, S. (2006). Stream communities across a rural–urban landscape gradient. Diversity and Distributions, 12(4), 337–350. https://doi.org/10.1111/j.1366-9516.2005.00226.x

US EPA. (2008). Reducing urban heat islands: compendium of strategies urban heat island basics. Retrieved from http://www.epa.gov/hiri/resources/compendium.htm

Vander Zanden, M. J., & Rasmussen, J. B. (2001). Variation in 15N and 13C trophic fractionation: Implications for aquatic food web studies. Limnology and Oceanography, 46(8), 2061–2066. https://doi.org/10.4319/lo.2001.46.8.2061

Vannote, R. L., Minshall, G. W., Cummins, K. W., Sedell, J. R., & Cushing, C. E. (1980). The river continuum concept. Canadian Journal Fishery and Aquatic Sciences, 37(1), 130–137.

Varian-Ramos, C. W., Swaddle, J. P., & Cristol, D. A. (2014). Mercury reduces avian reproductive success and imposes selection : an experimental study with adult- or lifetime- exposure in Zebra Finch. PLoS ONE, 9(4), e95674. https://doi.org/10.1371/journal.pone.0095674

Vietz, G. J., Walsh, C. J., & Fletcher, T. D. (2015). Urban hydrogeomorphology and the urban stream syndrome: treating the symptoms and causes of geomorphic change. Progress in Physical Geography, 40(3), 480–492. https://doi.org/10.1177/0309133315605048

Violin, C. R., Cada, P., Sudduth, E. B., Hassett, B. A., Penrose, D. L., & Bernhardt, E. S. (2011). Effects of urbanization and urban stream restoration on the physical and biological structure of stream ecosystems. Ecological Applications, 21(6), 1932–1949. https://doi.org/10.1890/10-1551.1

Visser, A. M. E., Noordwijk, A. J. Van, Tinbergen, J. M., Lessells, C. M., Visser, M. E., Noordwijk, A. J. Van, … Lessells, C. M. (1998). Warmer springs lead to mistimed reproduction in Great Tits (Parus major). Proceedings of the Royal Society B-Biological Sciences, 265(1408), 1867–1870.

Wahl, C. M., Neils, A., & Hooper, D. (2013). Impacts of land use at the catchment scale constrain the habitat benefits of stream riparian buffers. Freshwater Biology, 58(11), 2310– 2324. https://doi.org/10.1111/fwb.12211

Wallace, J. B., Eggert, S. L., Meyer, J. L., & Webster, J. R. (1997). Multiple trophic levels of a forest stream linked to terrestrial litter inputs. Science, 277(5322), 102–104. https://doi.org/10.1126/science.277.5322.102

Walsh, C. J., Roy, A. H., Feminella, J. W., Cottingham, P. D., Groffman, P. M., & Morgan, R. P. (2005). The urban stream syndrome: current knowledge and the search for a cure. Journal

101

of the North American Benthological Society, 24(3), 706–723.

Walsh, C. J., Sharpe, A. K., Breen, P. F., & Sonneman, J. A. (2001). Effects of urbanization on streams of the Melbourne region, Victoria, Australia. I. Benthic macroinvertebrate communities. Freshwater Biology, 46(4), 535–551.

Walsh, C. J., Waller, K. A., Gehling, J., & Mac Nally, R. (2007). Riverine invertebrate assemblages are degraded more by catchment urbanisation than by riparian deforestation. Freshwater Biology, 52(3), 574–587. https://doi.org/10.1111/j.1365-2427.2006.01706.x

Walters, D. M., Fritz, K. M., & Otter, R. R. (2008). The dark side of subsidies: adult stream insects export organic contaminants to riparian predators. Ecological Applications, 18(8), 1835–1841.

Wang, L., Robertson, D. M., & Garrison, P. J. (2007). Linkages between nutrients and assemblages of macroinvertebrates and fish in wadeable streams: Implication to nutrient criteria development. Environmental Management, 39(2), 194–212. https://doi.org/10.1007/s00267-006-0135-8

Wenger, S. J., Roy, A. H., Jackson, C. R., Bernhardt, E. S., Carter, T. L., Filoso, S., … Walsh, C. J. (2009). Twenty-six key research questions in urban stream ecology: an assessment of the state of the science. Journal of the North American Benthological Society, 28(4), 1080– 1098. https://doi.org/10.1899/08-186.1

Whitaker, D. M., Carroll, A. L., & Montevecchi, W. A. (2000). Elevated numbers of flying insects and insectivorous birds in riparian buffer strips. Canadian Journal of Zoology, 78(5), 740–747. https://doi.org/10.1139/z99-254

Winkler, D. W., & Allen, P. E. (1996). The seasonal decline in Tree Swallow clutch size: physiological constraint or strategic adjustment? Ecology, 77(3), 922–932.

Winkler, D. W., Dunn, P. O., & Mcculloch, C. E. (2002). Predicting the effects of climate change on avian life-history traits. Proceedings of the National Academy of Sciences of the United States of America, 99(21), 13595–13599.

Winkler, D. W., Luo, M. K., & Rakhimberdiev, E. (2013). Temperature effects on food supply and chick mortality in tree swallows (Tachycineta bicolor). Oecologia, 173(1), 129–138. https://doi.org/10.1007/s00442-013-2605-z

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Table 2.1 Study sites with impervious surface cover (% of total within 500-m on each side of the stream channel) and land-use designation based on impervious surface cover (Urban or Natural/Protected). Study reaches were categorized by adapting the thresholds developed by Schueler (1994): those < 25% impervious surface were categorized as natural/protected, and those reaches > 25% impervious surface were designated as urban.

Reach Impervious Surface (%) Land Use Berliner 41.1 Urban Darby 0.0 Natural/Protected Fawcett 48.3 Urban Highbanks 14.2 Natural/Protected Mussel 14.4 Natural/Protected Restoration 64.4 Urban Wetlands 48.5 Urban

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Table 2.2 Water-chemistry variables for natural/protected vs. urban study sites, including means and standard deviations across the 4 years of the study.

Mean Standard Deviation Water-chemistry Natural/ Natural/ Variable Protected Urban Protected Urban Hg (ppt) 0.87 1.57 0.96 1.91 Water Temp. (°C) 23.3 24.2 2.4 2.5

Total P (mg L-1) 0.104 0.111 0.037 0.032 -1 Total N (mg L ) 3.26 0.35 2.01 3.03 -1 PO4 (mg L ) 0.064 0.066 0.033 0.026 -1 NO3 (mg L ) 2.418 3.039 1.409 2.939 -1 NH4 (mg L ) 0.055 0.053 0.093 0.068 Turbidity (NTU) 21.7 15.9 37.6 26.9 Conductivity (µS cm-1) 612 603 255 224 pH 8.63 8.46 0.36 0.07 DO (%) 94.8 90.8 37.7 29.6

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Table 2.3 Eigenvalues and the percent variance captured by the principal components (eigenvalues > 1), along with each principal component’s loadings and the proportion of the variance R2) each variable shared with the PCA axes. Only the first axis (PC1) was used for analyses.

PC1 PC2 Parameter Loading r2 Loading r2 Impervious Surface 0.33 0.79 0.04 0.00

Pop Density 0.35 0.93 -0.14 0.05 Canopy Cover -0.34 0.86 -0.06 0.01 DO -0.31 0.71 0.18 0.09

Water Temp 0.30 0.67 0.24 0.15 NTU -0.24 0.43 0.33 0.29

Total P 0.24 0.43 0.40 0.44

Total N 0.35 0.91 -0.04 0.00 Hg 0.34 0.87 -0.02 0.00

NH4 0.04 0.01 0.52 0.73

NO3 0.33 0.83 -0.16 0.07 PO4 0.07 0.03 0.56 0.85 Eigenvalue 7.476 2.683 % variance 62.3 22.3

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Table 2.4 Results from linear mixed-effects models with fixed (Year, Land Use [urban or protected], and Year × Land Use) and random (site, nestbox, site × nestbox). ** indicates a significant (p < 0.05) effect. * indicates evidence of a trend; i.e., 0.5 ≥ p < 0.10. Marginal R² = variation explained by fixed effects alone, while conditional R² = variation explained by both fixed and random effects.

Linear Mixed Fixed Effects Random Effects Models Year Land Use Year × Land Use Site Site × Nestbox Residuals

df F p df F p df F p variance sd variance sd variance sd Clutch size 92.67 0.91 0.44 5.44 0.15 0.71 92.67 2.23 0.09 0.020 0.142 n/a n/a 0.642 0.801 R 2 marginal: 0.10 R 2 conditional: 0.13

No. fledged 79.84 3.46 0.02** 4.71 17.82 0.009** 79.84 0.36 0.79 0.000 0.000 n/a n/a 1.881 1.372 R 2 marginal: 0.25 R 2 conditional: 0.25

Nestling mass 78.41 4.44 0.006** 5.17 0.01 0.93 78.41 1.81 0.15 1.186 1.089 n/a n/a 3.494 1.869

R 2 marginal: 0.13 R 2 conditional: 0.35

Clutch init. date 98.02 1.17 0.33 5.75 5.75 0.06** 98.02 0.18 0.91 0.978 0.989 n/a n/a 92.988 9.643 R 2 marginal: 0.11 R 2 conditional: 0.12

SMI - male 27.27 5.26 0.01* 13.39 0.21 0.65 27.27 0.3 0.75 0.000 0.000 n/a n/a 0.017 0.130 R 2 marginal: 0.33 R 2 conditional: 0.33

SMI - female 41.15 1.08 0.37 6.79 0.19 0.68 41.15 1.56 0.21 0.000 0.009 n/a n/a 0.013 0.115

R 2 marginal: 0.16 R 2 conditional: 0.16

Hg - adult 14.42 2.72 0.08* 5.47 0.69 0.44 14.49 1.15 0.35 2.279 1.510 n/a n/a 0.967 0.983 R 2 marginal: 0.04 R 2 conditional: 0.72

Hg - nestling 66.03 2544.8 <0.001** 5.01 0.01 0.92 66.03 208.53 <0.001** 2.268 1.506 0.015 0.121 0.034 0.184 R 2 marginal: 0.64 R 2 conditional: 0.99

Glucose - nestling n/a n/a n/a 5.34 1.26 0.31 n/a n/a 0.011 0.104 0.008 0.088 0.030 0.174

R 2 marginal: 0.05 R 2 conditional: 0.41

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Figure 2.10 Conceptual model showing the hypothesized relationships among urbanization, climate, water quality, flying insects, and aerial insectivorous birds. Climate and land-use characteristics are expected to exert both direct effects (e.g., habitat availability) and indirect effects (via impact on invertebrate assemblages) on bird condition and reproductive success.

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Figure 2.11 Study sites and land cover in the greater Columbus, Ohio area. Source: Homer, et al., 2015 and QGIS Dev Team, 2017.

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Figure 2.12 Annual means from 2014-2017 by land use (i.e., protected or urban) for climate variables across the breeding season (30 April-28 June): (a) air temperature °C, (b) humidity (%), (c) no. of days of extreme cold, and (d) number of days of extreme heat. Error bars indicate +/- 1 SE.

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Figure 2.13 Annual means from 2014-2017 by land use (i.e., natural or urban) for flying insect (a) family richness, (b) abundance (i.e., capture rate of individuals / m2 10-day-1, and (c) median body size (mg, dry mass). Emergent aquatic insects (left) and terrestrial insects (right) are shown separately. Error bars indicate +/- 1 SE.

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Figure 2.14 Annual means from 2014-2017 by land use (i.e., protected or urban) for reproductive response: (a) clutch size (no. eggs) (LMM: p = 0.710), (b) clutch initiation date (Julian date, calendar days) (LMM: p = 0.060) (c) no. successfully fledged (LMM: p = 0.009), and (d) nestling mass (g) (LMM: p = 0.150). Error bars indicate +/- 1 SE.

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Figure 2.15 Relationships between the number of successfully fledged nestlings and (a) the Urban Stream Index (R2 = .16, F = 5.30, p < 0.001) and (b) the number of days of extreme cold between 30 April-28 June (R2 = .14, F = 4.31, p = 0.003). For the regression lines, red = 2014, green = 2015, blue = 2016, and purple = 2017.

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Figure 2.16 Relationships between (a) nestling mass (g) and the number of days of extreme heat between 30 April-28 June (R2 = 0.15, F = 4.36, p < 0.003); and (b) clutch initiation date (Julian date, no. calendar days) and mean air temperature (°C) between 30 April and 29 May (R2 = 0.06 , F = 2.62, p = 0.039). For the regression lines, red = 2014, green = 2015, blue = 2016, and purple = 2017.

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Figure 2.17 Annual means from 2014-2017 by land use (i.e., protected or urban) for individual body condition: (a) Scaled Mass Index (g) for with females (F) (LMM: p = 0.680) and males (M) (LMM: p = 0.650), (b) blood mercury (Hg) concentration (ppb) for adults (LMM: p = 0.420) and nestlings (LMM: p = 0.920), and (c) blood glucose concentration (mg/dL) for adults and nestlings (LMM: p = 0.310). Error bars are +/- 1 SE. Note that there are only three years of data for blood mercury concentration (2014- 2016) and one year for glucose (2017). Glucose levels for adults were not tested due to small sample size, but their results are included for reference.

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Figure 2.18 Relationship between blood Hg concentration (ppb) in adult Tree Swallows and the Urban Stream Index (R2 = 0.53, F = 9.212, p < 0.001). For the regression lines, red = 2014, green = 2015, and blue = 2016. Hg was log10-transformed; however, the figure above shows the raw values.

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Chapter 3. Riparian aerial insectivorous bird trophic dynamics linked to urbanization of streams

Authors: Joseph W. Corra and S. Mažeika P. Sullivan

116

Abstract

Serious population declines across species of aerial insectivorous birds have implicated

multiple environmental factors, including the quality and availability of flying insect prey

subsidies. Aquatic insects, many of which emerge from the water as winged adults, are

energetically advantageous to aerial insectivores, and link aerial insectivorous bird trophic

ecology with the condition of aquatic ecosystems. In urban areas, which continue to increase

in the United States and globally, riparian ecosystems have been strongly altered, with

potential consequences for aerial insectivorous birds. We investigated the relationships

between urbanization and Tree Swallow (Tachycinenta bicolor) reliance on aquatically

derived energy (i.e., originating from aquatic primary production) and trophic position at

seven river-riparian study sites in Columbus, Ohio from 2014-2017. Reliance on both aquatic

primary production and aquatic insects exhibited significant interannual variability; for the

latter, the interaction of year × land use suggests a possible relationship between elevated

total N and aquatic insect consumption. Adult trophic position was 8.3% higher at urban

sites, whereas nestling trophic position was not different between urban and natural/protected

sties, although nestlings exhibited high interannual variability in trophic position. The Urban

Stream Index, which captured continuous gradients of stream urbanization was related to

both reliance on aquatically derived energy as well as trophic position, suggesting that local-

scale water chemistry and land-use/land-cover characteristics likely drive aerial insectivorous

bird trophic responses. Overall, our results indicate that gradients of urbanization may

mediate aerial insectivore trophic ecology in multiple ways, with implications for the long-

term of impacts of urbanization on aerial insectivore energetics and population trends. 117

Introduction

Aerial insectivorous birds – a guild comprising swallows, nightjars, swifts and flycatchers – have experienced alarming population declines in eastern North America since the mid-20th century (Environment Canada, 2012), with intensified declines beginning in the 1980s for most species (Smith et al., 2015). Although declines in individual bird species may be linked to many factors, including breeding habitat loss (MacHunter et al., 2006) or degradation of habitat in tropical wintering grounds (Fraser et al., 2012), population losses across this taxonomically diverse guild suggest that changes in the abundance and quality of flying insect prey may be driving these declines (Nebel et al., 2010).

Riparian zones can be hotspots of aerial insectivorous bird diversity; in fact, many North

American aerial insectivorous bird species are riparian breeders (Naiman, Decamps, & Pollock,

1993). The character of land use and land cover in the riparian zone can influence the composition of insect assemblages (Gage, Spivak, & Paradise, 2004; Stenroth et al., 2015; Urban et al., 2006) and in turn,, the composition and distribution of invertebrate prey assemblages may drive these habitat associations among aerial insectivorous birds (Hagar et al., 2012; Hussell &

Quinney, 1987). Riparian zones are also tightly linked to streams via exchanges of nutrients, materials, and energy (Polis, Anderson, & Holt, 1997). In particular, cross-ecosystem prey subsidies of insects that emerge from the water as winged adults fuel riparian food webs (Baxter,

Fausch, & Saunders, 2005; Power & Dietrich, 2002; Sullivan & Rodewald 2012). Fluxes of emergent aquatic insects can constitute a particularly critical resource subsidy to riparian birds relative to distribution (McCarty, 1997; Nakano & Murakami, 2001), reproductive success

(McCarty, 1997; Twining, Shipley, & Winkler, 2018), body condition (Twining et al. 2016), and

118 trophic ecology (Kautza & Sullivan, 2016b; Uesugi & Murakami, 2007). For example, Gray

(1993) found that the density of aerial insectivorous flycatchers was strongly correlated with emergence production of insects in riparian habitats. Similarly, Iwata et al. (2003) observed that increased aquatic insect abundance was related to higher densities of aerial insectivores in forested streams, suggesting that insect emergence provides a key resource to riparian bird communities. The strong relationship between chemical water quality (including nutrient concentrations) and the diversity and abundance of aquatic insects (Lenat & Crawford, 1994;

Stewart, Butcher, & Swinford, 2000) implies riparian aerial insectivorous birds are also tied to water quality (Heinrich, Whiles, & Roy, 2014; McCarty & Winkler, 1999a; Stenroth et al., 2015;

Twining, Shipley, & Winkler, 2018).

Further, considerable evidence suggests that changes associated with human activity and urbanization of the landscape may contribute to aerial insectivorous bird declines (Nebel et al.,

2010; Rodewald, Kearns, & Shustack, 2013). For instance, urbanization in the riparian zone is associated with diminished density and species richness of riparian birds (Miller et al., 2003;

Rodewald, Kearns, & Shustack, 2013; Rottenborn, 1999). In addition, intensification of urbanization is associated with decreased invertebrate density and lower taxonomic richness

(Macivor & Lundholm, 2011; Urban et al., 2006). The relative scarcity of flying insect prey may contribute to declines in reproductive success observed among populations of aerial insectivores breeding in urban areas (e.g., Teglhøj, 2017). Urbanization in riparian areas may thus alter foraging activity in aerial insectivores via changes in both aquatic and terrestrial insect communities. For instance, prior work with riparian swallows in the Scioto River system of central Ohio, USA has shown that riparian swallows at urban sites derive more energy from

119 aquatic primary sources relative to swallows at rural sites (Alberts, Sullivan, & Kautza, 2013;

Kautza & Sullivan, 2016b).

Analysis of naturally-abundant stable isotopes of carbon (13C) and nitrogen (15N) is a powerful tool for investigating trophic relationships and food web structure (Layman et al., 2012;

Peterson & Fry, 1987; Vander Zanden & Rasmussen, 2001, Post, 2002). Enrichment of 15N relative to 14N occurs in consumers with increases in trophic level (Minagawa & Wada, 1984).

In contrast, ratios of carbon isotopes are more stable as carbon moves through food webs (Post,

2002), and they can reflect dietary sources, including sources of primary production (Finlay,

2001; Layman et al., 2012; Rounick & Winterbourn, 1986). By examining the ratios of these isotopes, the dietary contributions of terrestrial and aquatic sources – as well as of terrestrial vs. aquatic insects – to aerial insectivorous birds can be estimated (e.g., Bearhop et al., 1999; Kautza

& Sullivan, 2016b), as can trophic position and food chain-length (Cabana & Rasmussen, 1996;

Post, Pace, & Hairston, 2000; Sullivan, Hossler, & Cianfrani, 2015)

Here, we investigated the influence of urbanization on the trophic dynamics (nutritional subsidies, trophic position) of aerial insectivorous birds in linked aquatic-terrestrial food webs over four years in Columbus, Ohio, USA. The Tree Swallow (Tachycineta bicolor) served as a representative species of the guild. Our overarching hypothesis was that swallow trophic ecology would be strongly linked to urbanization. Specifically, we anticipated that Tree Swallow reliance on aquatic primary production (i.e., energy pathway originating from in-stream periphyton) would be greater at urban reaches than at natural/protected reaches owing to reduced riparian vegetation and consequently reduced canopy typical of urban reaches, and thus greater in-stream primary production cover. Similarly, we predicted that emergent aquatic insects would

120 represent a greater dietary contribution to Tree Swallows than terrestrial flying insects at urban reaches. Alberts, Sullivan, and Kautza (2013) observed a stronger dependence on emergent aquatic insects among urban-breeding swallows compared to those at less-developed reaches, implicating the influence of land cover on swallow foraging behavior as a possible mechanism;

Tree Swallows typically prefer to forage over open areas (Ghilain & Bélisle, 2008; Robertson,

Stutchbury, & Cohen, 2011), such as urbanized and impounded river reaches. Corra and Sullivan

(Chapter 2) also showed a greater abundance of emergent aquatic flying insects at urban reaches

(but no significant differences in the abundance of terrestrial flying insects), as well as a increased body size, conveying strong energetic benefits to Tree Swallows (Twining et al. 2016).

Lastly, we hypothesized that Tree Swallows at urban reaches would also be characterized by a higher relative trophic position than their protected counterparts. Alberts, Sullivan, & Kautza

(2013) observed that urban riparian swallows fed at higher trophic levels relative to swallows at rural reaches. Further, larger areas of open water in urban areas (e.g., impoundments) have been associated with greater dietary reliance on odonates (i.e., dragonflies and damselflies), themselves secondary consumers (e.g., Mengelkoch, Niemi, & Regal, 2004), and Tree Swallows have been observed to selectively prey on these larger-bodied insect taxa (McCarty & Winkler,

1999a; Quinney & Ankney, 1985).

Methods

Study area and experimental design

Our study area consisted of seven riparian sites along an urban-forested gradient in the

Scioto River system (Ohio, USA). The Scioto River watershed drains 16,868-km2 as it flows

121 south into the Ohio River (Ohio Environmental Protection Agency, 2014). The central portion of the Scioto River catchment lies within the Columbus Metropolitan Area (CMA). Our study sites were located on the Scioto mainstem (6th order, two sites), plus two major tributaries, the

Olentangy River (5th order, for sites) and Big Darby Creek (4th order, 1 site) (Fig 1). The regional landscape is composed overwhelmingly of developed (45%) or cultivated (40%) lands, with forests comprising only 6% of the total land cover (Ohio Environmental Protection Agency,

2014).

The North American Tree Swallow (Tachycineta bicolor), which commonly breeds in riparian areas, was selected as a model aerial insectivorous bird species. Tree Swallows are cavity-nesters (and thus amenable to nest boxes) and are relatively tolerant of handling, and are therefore commonly selected for study purposes (Jones, 2003). 500-m study reaches were delineated to conform with the typical Tree Swallow foraging range (Dunn & Hannon, 1992;

Quinney & Ankney, 1985) and adequately capture the influence of land use and land cover at the local scale on stream water chemistry (Strayer et al., 2003). At the outset of Tree Swallow breeding season in late March each year (2014-2017), wood nestboxes (12.7-cm × 12.7-cm ×

27.9-cm) were constructed using guidelines developed by Golondrinas de las Américas (2011).

Five or six nestboxes per study site were mounted on a combination of steel rebar and electrical conduit to deter predators; predator guards constructed from PVC pipe were installed at sites where predation was observed or suspected, although such instances were rare. Nestboxes were spaced at an adequate distance from one another (~20 m) to avoid territorial overlap (Muldal,

Gibbs, & Robertson, 1985). The nestbox’s design facilitates capture and sample collection from nesting birds: the swinging side-door of the nestbox allows access the nestling Tree Swallows,

122 while adult birds were captured using the nestbox’s ‘wig-wag’ (i.e., trapdoor) which can be closed from a distance with a length of monofilament fishing line, thus trapping the adult bird inside and facilitating capture via the side-door (Golondrinas de las Américas, 2011).

Land use and land cover

Quantum GIS (QGIS Development Team, 2017) was used to quantify land cover at our study reaches. Land-cover data were obtained using the 2011 National Land Cover Database, which classifies land cover for the continental United States at a 30-m spatial resolution (Homer et al., 2015). Land-cover percentage for each land-cover class (forest, developed, et al.) was then calculated for each delineated 500-m buffer (as described above). Additional GIS layers were incorporated in order to calculate the percentage of canopy cover (U.S. Geological Survey,

2014b), percent impervious surface (U.S. Geological Survey, 2014a), and mean human population density (U.S. Census Bureau, 2010) at the study reaches.

Field data collection

Beginning in 2015, samples of stream detritus (i.e., coarse benthic organic matter, or

CBOM) and periphyton were collected along three transects running perpendicular at upstream, middle, and downstream sections of each 500-m study site. Detritus samples represented terrestrial primary production and periphyton represented aquatic primary production for subsequent stable isotope analysis. Samples of detritus, and periphyton were collected in both the early (late-May) and late (late-July) breeding season of each year to capture annual and seasonal variability (Post, 2002). Detritus samples were hand-collected from the streambed. Periphyton

123 samples were collected by scrubbing the surface of cobble from each transect following Reavie et al (2010), followed by washing the periphyton into an opaque plastic container using deionized water to remove debris.

Both terrestrial and emergent aquatic flying insects were sampled at each study reach each year. Invertebrate sampling was performed for ten days in both the early season (mid-late

May) and late season (mid-late July) at each of the study reaches. To collect emergent aquatic insects, two floating, 1-m2 pyramid-style emergent traps (Aubin, Bourassa, & Pellisier, 1973) were deployed at each study site (upstream and downstream sections) for 10-day periods (early and late season). Likewise, two cloth mesh 1-m × 1-m × 0.6-m Malaise traps (MegaView

Science Co., Taichung, Taiwan; Townes, 1972) were deployed in nearshore vegetation at the upstream and downstream locations at each site, suspended from trees at a height of 1-m to capture flying insects of both terrestrial and aquatic origin. Any insects from families of aquatic origin (e.g., Chironomidae) were excluded so that only terrestrial families of flying insects were considered from Malaise traps. All invertebrates were subsequently enumerated and identified to family using Johnson and Triplehorn (2005) and Merritt, Cummins, and Berg (2008). From these samples, we selected the two numerically dominant families among the terrestrial and emergent aquatic insects for each site (i.e., four families per reach), per season, per year

(Appendix A. Chapter 2: Supplemental Material) to represent terrestrial and aquatic insect signatures for subsequent stable isotope analysis. In a few instances, one or more numerically dominant insect families had insufficient mass to constitute an isotopic sample. In that event, the next most numerous family was chosen or, failing that, a composite was created from two or more insect families.

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For swallows, a small quantity of blood (enough to yield at least 0.5 mg of material when dried) was drawn from the jugular vein of adults and 13-day-old nestlings, after Sullivan and

Vierling (2012). Blood was collected yearly from at least two nestlings in each brood, as well as from adults when captured.

All samples were dried in a 60° C oven for 48 hours and then pulverized and homogenized, either with a ball-mill grinder (for detritus samples) or a mortar and pestle (for insects, blood, and periphyton samples). Insects were weighed by family, season (i.e., early or late season), and reach (Iwata, Nakano, & Murakami, 2003). Samples were then packed in 4×6 mm tin capsules (Sullivan & Vierling, 2012). Packed samples were submitted for analysis of 13C and 15N stable isotopes by continuous flow isotope ratio mass spectrometry (EA-IRMS) at

Washington State University’s Stable Isotope Core (Pullman, Washington, USA) following

Sullivan et al. (2015).

Dietary/nutritional sources and trophic position

Based on previous research in the study system (Kautza & Sullivan, 2016b, 2016a;

Sullivan, Boaz, & Hossler, 2016), mixed-model approaches were expected to be effective due to discrimination between primary producer basal resources in the Scioto River basin. Thus, we used the SIAR package version 4.2 (Parnell & Jackson, 2013) to fit Bayesian mixing models in R

(R Core Team, 2018). SIAR uses Markov chain Monte Carlo (MCMC) methods to calculate posterior distributions of variables of interest, and fits a model with a Gaussian likelihood and

Dirichlet prior distribution for the probability of the mixture mean to model dietary proportions

(Parnell et al., 2010). Apart from the implementation of a Dirichlet prior distribution (Parnell &

125

Jackson, 2015), the methods used by SIAR are analogous to that employed by MixSIR (Moore &

Semmens, 2008), which uses a Hilborn sampling-importance-resampling (SIR) algorithm to establishes a threshold acceptance value for resampling, facilitating larger model runs (Rubin,

1988). Prior to fitting models, t-tests were conducted on Tree Swallow blood isotope data to detect potential differences in 13C and 15N isotopic signatures between nestlings and adults and to determine if adult and nestling isotopes should be analyzed separately. We found no significant differences in 15N stable isotopic signatures due to Tree Swallow age (t = -0.867, p = 0.388).

However, 13C values were significantly higher among adult Tree Swallows (t = -2.015, p =

0.047), so adult and nestlings were analyzed separately in all our models.

Next, a two-source food-web model using periphyton and detritus as basal resources was employed to estimate nutritional subsidies to Tree Swallows (Finlay, 2001; Kautza & Sullivan,

2016b); i.e., the proportion of C from aquatic sources present in Tree Swallows. Periphyton was selected to represent aquatic primary production, as it was previously identified by Kautza and

Sullivan (2016b) as the largest contributor of aquatically derived energy to riparian swallows in the middle Scioto study system. We combined our early-season and late-season (i.e., May and

July) for both periphyton and detritus isotopic samples for each year of data. We also estimated the dietary contribution of aquatic and terrestrial insects to Tree Swallows by fitting a four- source food-web model using δ 13C and δ 15N signatures from the numerically dominant aquatic and terrestrial insect families at each study site. Separate models were developed for early-season and late-season insect samples.

Following estimates of basal energy sources, we calculated Tree Swallow trophic position (TP) using δ13C or δ15N values (Anderson & Cabana, 2007; Cabana & Rasmussen,

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1996; Sullivan, Manning, & Davis, 2018). We used standard fractionation values (2 ± 0.5%0 for

13 15 δ C, 6 ± 1%0 for δ N) as were applied in Kautza and Sullivan (2016b) for secondary consumers of invertebrates including riparian swallows:

15 15 15 15 훿 푁푝푟푒푑 − (훿 푁푏푎푠푒1 × 훼1 + 훿 푁푏푎푠푒2 × 훼2 + 훿 푁푏푎푠푒3) 푇푃푝푟푒푑 = Δ푛

+ 휌

where α1 = proportion of N acquired from baseline 1 (detritus); α2 = proportion of N acquired from baseline 2 (periphyton); Δn = fractionation rate of N; and ρ = TP of the baseline (TP = 1 for the primary producers used as the baselines). Potential temporal shifts were also an area of interest, so we ran separate models for each year of data (for both nutritional subsidies and trophic position) to investigate interannual variability.

Statistical analysis

Linear mixed-effects models (LMMs) were selected as our primary statistical tool to analyze swallow reliance on aquatically derived energy and emergent aquatic insects, as well as trophic position. LMMs were fitted using R (R Core Team, 2018), the R Studio package version

1.1.453 (RStudio Team, 2016), and lmerTest version 3.0 (Kuznetsova et al., 2017). Year, land use (i.e., a categorical variable indicating the site’s classification as urban or natural/protected) and an urbanization × year interaction were included as fixed effects, with study site included as a random effect. Nestbox nested within study site was included as an additional random effect in

127 the models in which nestling responses were modeled to account for variability within broods.

Three sets of linear mixed-effects models were developed, one for each of our response variables

(trophic position, dietary reliance on aquatic energy, and dietary reliance on aquatic insects) with separate models for adult and nestling Tree Swallows. The overall effect of each variable (i.e., the sum-to-zero contrast) was also assessed via p-values and F-statistics calculated using afex package version 0.22-1 (Singmann et al., 2018) which employs the Kenward-Roger approximation for degrees-of-freedom values. Marginal (variation attributed to fixed effects) and conditional (variation attributed to both fixed and random effects) R2 values were determined for each model with the MuMIn package (Bartoń, 2018), which calculates a pseudo-R2 for mixed- effects models.

In addition, we used multiple regression models to explore potential mechanisms (i.e., measures of water chemistry, nutrient concentrations, air temperature, flying insect prey) driving consumer trophic position and nutrition sources. Specifically, we used the Urban Stream Index

(USI) – developed from previous work in the study system (see Chapter 2), which represents continuous measures of water chemistry and nutrient data, as well as land use/land cover data – as a predictor variable for swallow trophic response variables, in order to capture potential relationships not accounted for by the categorical approach of our LMMs (with land use as urban or protected/natural). Multiple regression models also incorporated year as categorical variable, as many of our predictor variables had considerable interannual variability. Lastly, we used simple regression to test potential relationships between the contribution of aquatic insects to swallow diet and swallow reliance of aquatically derived energy. In all models, α ≤ 0.05 was used as the threshold of statistical significance, while α ≤ 0.10 was considered evidence of a

128 trend. Note that the afex package reports p-values to only two decimal places, except in cases where p < 0.01.

Results

Nutritional Subsidies

For 2015-2017, adult swallows in natural/protected and urban areas obtained about 6% and 12% of their energy from aquatic primary production, respectively (Fig. 3a). However, land use did not emerge as a significant effect (LMM: p = 0.490; Table 1). Instead, there was a strong random effect of site, with the R2 increasing from 0.07 (marginal) to 0.45 (conditional) (Table 1).

Nestling reliance on aquatic primary production was comparable (Fig. 3b), as was the effect of site, with R2 increasing from 0.07 to 0.62 (Table 1). Nestlings also showed strong interannual variability (LMM: p = 0.001; Table 1), with a sharp increase in reliance on aquatic primary production in 2017.

From 2014-2017, adult swallows at natural/protected and urban sites obtained ~22% and

40% of their energy, respectively, from early-season emergent aquatic insects (Fig. 4a); following a similar pattern, nestlings at natural/protected and urban sites derived ~20% and 57% of their energy, respectively, from early-season aquatic-insect sources (Fig. 4b). For late-season insects, adults at natural/protected sites derived slightly more energy (~41%) from aquatic insects relative to urban adults (~36%) (Fig. 4c). Nestlings across land use types obtained about

37% of energy from late-season insects (Fig. 4d). As with aquatic primary production, land use was not implicated as a significant driver (Fig. 4a, 4c; Table 1). Among adults, there was a trend toward interannual change in the reliance on terrestrial vs. aquatic flying insects, for early-season

129 insects only (LMM: p = 0.010; Table 1), with 2014 and 2016 associated with slightly higher consumption of aquatic prey. Nestlings had even more pronounced interannual variability with early-season insect prey subsidies, with the interaction of land use × year positively related to increased consumption of aquatic insect prey in 2016 and 2017 (Table 1). However, there was no notable effect of land use alone (Fig. 4b, 4d; Table 1). As with our other LMMs, the random effect of site was considerable: the R2 increased for adult swallows and early-season insects from

0.15 (marginal) to 0.56 (conditional), and from 0.06 to 0.60 for late-season insects. There were similar results for nestlings, with R2 increasing from 0.23 to 0.69 in the early-season insects model, and 0.04 to 0.56 in the late-season model.

We did not find significant relationships between early-season (p = 0.390, Fig. 3.11a) or late-season insect (p = 0.318, Fig. 3.11b) contribution to adult swallow diet and their reliance on aquatically derived energy or late-season insects and adult swallows (p = 0.318, Fig. 3.11b) (p =

0.390, Fig. 3.11a). However, both early (p = 0.050, Fig. 3.11a) and late-season aquatic insect (p

= 0.066, Fig. 3.11b) contributions to nestling diet trended with their reliance on aquatically derived energy.

Trophic Position

Regarding trophic position, we observed considerable variability by land use for adult swallows, with swallows at urban sites feeding at higher trophic levels than those at the natural/protected sites (LMM: p = 0.020; Table 1, Fig. 2a). Among nestlings, our results did not show variability by land use alone (LMM: p = 0.430, Table 1, Fig. 2b). However, nestling trophic position was 35% and 25% higher in 2016 and 2017, respectively, relative to 2015

130

(LMM: p = <0.001; Table 1). The interaction of land use × year revealed a trend toward higher trophic position and urban sites in 2016 as well (LMM: p = 0.020; Table 1). Site, included as a random effect in our models, accounted for 0.13 additional variation among adult swallows

(Table 1). The random effect of site, however, was far more pronounced (0.79) among nestlings

(Table 1).

Urban Stream Index

We followed our linear-mixed effects models with multiple regression models to investigate the potential drivers of variability in our models. All three swallow response variables – reliance on aquatically-derived energy, reliance on aquatic insects, and trophic position – were positively related to the USI. These relationships were similar for both adults and nestlings. For trophic position, adults (p = 0.001) and nestlings (p < 0.001) both displayed a strong relationship with the USI for 2015-2017 (Fig. 5a-c). In addition, there was a trend toward increasing trophic position each year for both adults and nestlings. The results for dietary reliance on aquatic energy (periphyton) were similar for adults (p = 0.019) and nestlings (p <

0.001) (Fig. 6a-b), though the only interannual increase was observed in nestlings in 2017 (Fig.

6c). Finally, reliance on aquatic insects was comparable for both adult swallows (p < 0.001) for

2014-2017 (Fig. 7a-d). Early-season and late-season insect isotope samples were combined for these regression analyses.

Discussion

131

Although aerial insectivorous birds prey on a mix of flying terrestrial and emergent aquatic insects (Mengelkoch, Niemi, & Regal, 2004), aquatic-insect subsidies may be especially important drivers of population density, health, and reproductive success (Iwata, Nakano, &

Murakami, 2003; Twining et al, 2016; Uesugi & Murakami, 2007). Based on prior work with riparian swallows in the Scioto River ecosystem by Alberts, Sullivan, and Kautza (2013) and

Kautza and Sullivan (2016b), we anticipated that Tree Swallows would exhibit an increased reliance on aquatic insects and energy from aquatic primary production at urban nesting sites, while also feeding at higher trophic levels at urban sites relative to swallows at natural/protected reaches. Overall, we found that swallow trophic position was higher at urban sties, but nutritional subsidies were not different by land use. However, both trophic metrics were positively associated with continuous measures of urbanization as represented by the Urban Stream Index.

These results suggest that urbanization can be a driver of aerial insectivore trophic ecology, with implications for the long-term of impacts of an urbanizing landscape on aerial insectivore energetics and population trends.

Nutritional Subsidies

Our results did not show clear relationships between land use (as categorized by % impervious surface in the riparian area) and Tree Swallow reliance on energetic contributions from periphyton, although interannual differences were observed. Such interannual variation may be related to changes in aquatic primary production associated with fluctuating nutrient inputs (Schindler, 1978), or interannual precipitation and temperature variability that can affect both aquatic insect assemblages (Hawkins et al., 1997) and aquatic primary production (e.g.,

132

Harris & Baxter, 1996; Rodrigues et al., 2009). Elevated concentrations of nutrients are also characteristic of urban streams (Meybeck, 1998; Paul & Meyer, 2001), and the elevated concentrations observed in our study system (particularly for total N) are key metrics of the

Urban Stream Index (Chapter 2). In our study system, nutrient concentrations varied yearly

(Chapter 2), with notably elevated concentrations of total N at urban sites in 2015 but and overall decreasing total P from 2015-2017. Higher concentrations of nutrients in aquatic systems spurs algal growth (Dodds & Smith, 2016), and could potentially alter the balance of aquatic and terrestrial (i.e., detrital) food sources available to aquatic consumers. For instance, in experimental treatments by McCarty (1997), ponds were artificially enriched with nutrients to stimulate insect production which, in turn, drove Tree Swallow foraging efforts. We observed a strong interactive effect for land use × year in 2015 for nestling swallows, suggesting a possible relationship with N enrichment at the urban reaches.

Aquatic primary production may be enhanced or limited by features of both the riparian and aquatic environments, and this is likely to be reflected in the contribution of aquatic primary producer pathways to riparian aerial insectivores. Whereas allocthonous inputs (i.e., leaf litter) typically constitute a greater proportion of energy for low-order streams in forested areas

(Vannote et al., 1980), higher-order streams are often characterized by a smaller share of allocthonous production as in-stream algal productivity increases due to greater light penetration

(Minshall, 1978), accompanied by greater inputs of organic material from upstream sources

(Thorp & Delong, 1994), although these general patterns can be altered in urban streams (Meyer,

Paul, & Taulbee, 2005; Grimm et al., 2005; Paul & Meyer, 2001). This may account for some of the variability in dietary reliance on aquatic primary production we observed relative to the

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Urban Stream Index (Fig. 10). However, the site with the highest reliance on aquatic insects

(“Mussel”) (Fig. 8) was also, paradoxically, the site with the lowest reliance on aquatic primary production (Fig. 10). This apparent discrepancy could be a function of swallow diet: Kautza and

Sullivan (2016b) observed that chironomids in the middle Scioto system transported substantially more energy from phytoplankton than periphyton. We did not measure phytoplankton in our study, which may be important at our study sites on larger river sections.

Thus, our estimates of the contribution of reliance on aquatically derived energy represent the minimum contribution.

The percent of aquatically derived energy provisioned to swallows also can largely hinge on the source of insect prey subsidies; grazing aquatic invertebrates will be strong vectors of aquatic energy, whereas shredding taxa will “recycle” terrestrially-derived energy to swallows and other insectivorous terrestrial consumers. Although we did not observe a difference in the contribution of aquatic insects to swallow diets between urban and natural/protected reaches

(Fig. 3.3), the USI was related to aquatic insect reliance by both nestling and adults (Fig. 7). We also observed interannual variability in the reliance on terrestrial vs. aquatic flying insects for early-season insects. The larvae of Chironomidae, the insect family overwhelmingly numerically dominant in all of our emergent samples, acquire food resources through diverse modes

(Cummins & Klug, 1979). Aquatic insect functional feeding groups differ for various genera, though many are collector-gatherers and grazers (Merritt, Cummins, & Berg, 2008). As mentioned above, isotopic analysis of chironomids collected from the middle Scioto study system by Kautza and Sullivan (2016b) revealed a higher reliance on phytoplankton; however, chironomids were observed to rely on both terrestrial detrital pathways and aquatically-derived

134 energy in varying ratios depending on taxon and location. The taxonomic and functional composition of flying insect assemblages available to swallows therefore, is a strong determinant of energy transfer pathways to swallows from aquatic ecosystems.

Both the strong random effect of “site” in our models of reliance on aquatically derived energy as well as its relationship with USI suggest that categorical classifications of urbanization as described simply by % impervious surface can fail to capture the full range of variability of environmental characteristics associated with urban streams, including water chemistry and land- cover variables besides impervious surface (Meyer, Paul, & Taulbee, 2005; Walsh et al., 2005).

In particular, changes to urban streams that shift community composition of aquatic insects are likely to have consequences for energy budgets of aerial insectivorous bird. Although the extent of impervious surface has been identified as a major driver of reduced invertebrate diversity and abundance, particularly for aquatic invertebrates (Klein, 1980; Morse, Huryn, & Cronan, 2003;

Walsh et al., 2007), other land-cover and water-chemistry/nutrient variables may influence the composition of insect prey subsidies available to aerial insectivores. Among the characteristics to consider are the proximity of natural or semi-natural habitat patches (Hendrickx et al., 2007), species composition of vegetation (Schaffers et al., 2008), extent of agricultural land use in the riparian zone (Allan, Erickson, & Fay, 1997), the presence of forested riparian buffer strips

(Whitaker, Carroll, & Montevecchi, 2000), frequency of stream-channel disturbance (Gurtz &

Wallace, 1984), water temperature (Jonsson, Strasevicius, & Malmqvist, 2012) and aquatic nutrient loads (Wang, Robertson, & Garrison, 2007). A number of these land use and water- chemistry variables are frequently, though not always directly, associated with urbanization and the extent of impervious surface in the riparian area (Arnold & Gibbon, 1996). For instance,

135

Stenroth et al (2015) found that agricultural land use in riparian areas did not change aquatic insect abundance; however, it was related to altered size structure in aquatic insect assemblages relative to forested streams; in the latter, average emergent insect body size was larger than at developed reaches. Further, the influence of landscape development, including impervious surface, may vary depending on scale. For example, Sponsellar et al. (2001) observed that land cover at the sub-corridor (i.e., 200-m) scale had the strongest influence on benthic invertebrate assemblages, while Wahl et al. (2013) identified catchment-scale land use as having the greatest overall influence on stream biota.

Land use and land cover, besides shaping insect prey assemblages, may also influence aerial insectivore foraging behavior. The extent of tree-canopy cover may exert such an influence, as Tree Swallows prefer to forage over open fields or open water (Ghilain & Bélisle,

2008; McCarty & Winkler, 1999b). Therefore the presence of thickly forested riparian buffers, in addition to driving increased abundance of invertebrates (Marczak et al., 2010; Whitaker,

Carroll, & Montevecchi, 2000), may also influence where swallows forage for prey (Alberts,

Sullivan, & Kautza, 2013). Similar land-cover characteristics may have varying implications for other aerial insectivorous species; for instance, salliers like flycatchers forage from perches, so the distribution of trees may shape their foraging range (Schneider & Miller, 2014). Thus, plasticity in foraging strategies likely act in concert with land-use change and flying insect prey to determine shape aerial insectivorous bird reliance on aquatic subsidies.

Trophic position

136

Adult Tree Swallows were associated with higher trophic position at urban sites, but only in 2017 did we see a similar result for nestlings. We did, however, observe strong interannual differences for nestlings, which fed at trophic positions 35% and 25% higher in 2016 and 2017 than in 2015, respectively. Swallow trophic position was also positively associated with our USI, supporting the influence of site as a random effect (i.e., in part representing local environmental variability) in our LMMs. Mengelkoch et al. (2004) observed that the percentage of open water comprising Tree Swallow foraging range was a strong predictor of increased consumption of odonates, themselves predators of other flying insects. Increased predation on secondary consumers like odonates may be a potential driver of the higher trophic position we observed at some sites (Benke, Wallace, & Harrison, 2001; Bennett & Hobson, 2009; Cabana & Rasmussen,

1996). Tree Swallows appear to select for larger-bodied prey when foraging (McCarty &

Winkler, 1999a), and therefore may be feeding at higher trophic levels depending of the composition of insect assemblages in their foraging range. Additional data on Tree Swallow prey in the study system, such as extensive sampling of boluses (e.g., Alberts, Sullivan, &

Kautza, 2013) could reveal more about selective foraging (of insects), water quality, and swallow trophic position.

In addition, elevated N enrichment in water has been related to higher concentrations of

15N in secondary consumer diets and, consequently, greater 15N enrichment in their tissues

(Adams & Sterner, 2000; Rau et al., 1981). Finally, it is important to note that discrimination factors can exhibit high variability in N depending on the consumer and its diet (Caut, Angulo, &

Courchamp, 2009), therefore the fractionation values we employed for secondary consumers, although consistent with commonly used values (Kautza & Sullivan, 2016b; Post, 2002), may

137 under- or overestimate Tree Swallow trophic position if their diet varied greatly from our expectations (Caut, Angulo, & Courchamp, 2008).

Conclusions

Urbanization alters stream ecosystems through both acute and chronic changes that increase peak flows, destabilize stream channels (i.e., altered geomorphology) (Hession et al.,

2003; Walsh et al., 2005; Wenger et al., 2009), lead to elevated toxin levels, increase nutrient concentrations, and change other inputs of mass and energy (Wenger et al., 2009). Biological responses to urbanization have also been widely investigated (Brown et al., 2009; Helms,

Schoonover, & Feminella, 2009; Ramírez et al., 2009; Steuer et al., 2009). Here, we show that the effects of urbanization can extend to riparian wildlife such as aerial insectivores birds that are tightly tied to stream ecosystems.

Factors that may drive insect abundance and the taxonomic composition of insect assemblages and, therefore, the energetic pathways available to swallows, may be related to both aquatic and riparian characteristics not captured by estimates of urbanization based on measures of impervious surface cover alone. The Urban Stream Index, which incorporates a suite of continuous variables related to urban streams (Chapter 2), appeared to more effectively capture this variability, and implies that aerial insectivores respond to gradients of urbanization.

Overall, our findings corroborate and extend those of Alberts, Sullivan, and Kautza

(2013), suggesting that urbanization is related to both greater reliance on aquatically derived energy and higher trophic position among riparian swallows. For urban-breeding aerial insectivorous birds, these links to aquatic systems may have a number of implications. Transfers

138 of energy and nutrients from aquatic systems may also facilitate the transfer of aquatic contaminants (Sullivan & Rodewald, 2012; Walters, Fritz, & Otter, 2008), including selenium

(Beck, Hopkins, & Jackson, 2014), PCBs (McCarty & Secord, 1999), pharmaceuticals

(Richmond et al., 2018), and mercury (Cristol et al., 2008), which entail potential hazards for avian health and reproductive success (Brasso & Cristol, 2008; Hawley, Hallinger, & Cristol,

2009; Ohlendorf et al., 1988; Varian-Ramos, Swaddle, & Cristol, 2014). Even levels below published thresholds of environmental impairment are cause for concern: Rowse, Rodewald, and

Sullivan (2014) found that even relatively low mercury concentrations in adult male aerial insectivorous Acadian Flycatchers were related to reduced reproductive success.

On the other hand, the availability of emergent aquatic insect prey in urban-riparian sites may provide benefits that may help mitigate risks associated with urbanization. Recent evidence suggests that omega-3 long-chain polyunsaturated fatty acids, found in aquatic insects but relatively scarce in terrestrial insects, constitute a key nutritional resource for insectivorous birds

(Twining et al., 2016). Thus, urbanization may confer certain benefits to riparian swallows and other aerial insectivorous birds, including an increased reliance on aquatic resources and feeding at higher trophic position. Further, the availability of high-quality aquatic insect prey has been related to increased Tree Swallow fledging success (Twining, Shipley, & Winkler, 2018) and to

Tree Swallow population growth (Cox et al., 2018), underscoring the energetic advantages conferred by aquatic prey subsidies, particularly owing to long-term declines in the availability of high-quality insect prey for aerial insectivores (English, Green, & Nocera, 2018). As increased insect prey availability has been linked to earlier lay dates among Tree Swallows

(Nooker, Dunn, & Whittingham, 2005), an abundance of emergent aquatic insects may extend

139 the breeding season, with implications for population dynamics (Monroe et al., 2008).

Determining the composite effects of urbanization on aerial insectivores will be an important research and conservation agenda as we continue to address declining aerial insectivore populations.

140

References

Adams, T. S., & Sterner, R. W. C. N.-289. (2000). The effects of dietary nitrogen on trophic level 15N enrichment. Limnology and Oceanography, 45(3), 601–607.

Alberts, J. M., Sullivan, S. M. P., & Kautza, A. (2013). Riparian swallows as integrators of landscape change in a multiuse river system: Implications for aquatic-to-terrestrial transfers of contaminants. Science of the Total Environment, 463–464, 42–50. https://doi.org/10.1016/j.scitotenv.2013.05.065

Allan, J. D. (2004). Influence of land use and landscape setting on the ecological status of rivers. Limnetica, 23(3–4), 187–198. https://doi.org/10.1146/annurev.ecolsys.35.120202.110122

Allan, J. D., Erickson, D. L., & Fay, J. (1997). The influence of catchment land use on stream integrity across multiple spatial scales. Freshwater Biology, 37(1), 149–161.

Allan, J. D., & Flecker, A. S. (1993). Biodiversity conservation in running waters. BioScience, 43(1), 32–43.

Anderson, C., & Cabana, G. (2007). Estimating the trophic position of aquatic consumers in river food webs using stable nitrogen isotopes. Journal of the North American Benthological Society, 26(2), 273–285. https://doi.org/10.1899/0887- 3593(2007)26[273:ETTPOA]2.0.CO;2

Andrew, S. C., Hurley, L. L., Mariette, M. M., & Griffith, S. C. (2017). Higher temperatures during development reduce body size in the zebra finch in the laboratory and in the wild. Journal of Evolutionary Biology, 30(12), 2156–2164. https://doi.org/10.1111/jeb.13181

Ardia, D. R. (2013). The effects of nestbox thermal environment on fledging success and haematocrit in Tree Swallows. Avian Biology Research, 6(2), 99–103. https://doi.org/10.3184/175815513X13609528031394

Ardia, D. R., Cooper, C. B., & Dhondt, A. (2006). Warm temperatures lead to early onset of incubation, shorter incubation periods and greater hatching asynchrony in Tree Swallows Tachycineta bicolor at the extremes of their range. Journal of Avian Biology, 37(2), 137– 142.

Ardia, D. R., Wasson, M. F., & Winkler, D. W. (2006). Individual quality and food availability determine yolk and egg mass and egg composition in tree swallows Tachycineta bicolor. Journal of Avian Biology, 37(3), 252–260.

Arnold, C. L., Boison, P. J., & Patton, P. C. (1982). Sawmill Brook: an example of rapid geomorphic change related to urbanization. The Journal of Geology, 90(2), 155–166.

Arnold, C. L., & Gibbon, C. J. (1996). Impervious surface coverage: The emergence of a key environmental indicator. Journal of the American Planning Association, 62(2), 243–258. 141

Aubin, A., Bourassa, J. P., & Pellisier, M. (1973). An effective emergence trap for the capture of mosquitoes. Mosquito News, 33(2), 251–252.

Bartoń, K. (2018). MuMIn. Retrieved from https://cran.r-project.org/package=MuMIn

Baxter, C. V, Fausch, K. D., & Saunders, W. C. (2005). Tangled webs: Reciprocal flows of invertebrate prey link streams and riparian zones. Freshwater Biology, 50(2), 201–220. https://doi.org/10.1111/j.1365-2427.2004.01328.x

Bearhop, S., Thompson, D. R., Waldron, S., Russell, I. C., Alexander, G., & Furness, R. W. (1999). Stable isotopes indicate the extent of freshwater feeding by cormorants Phalacrocorax carbo shot at inland fisheries in England. Journal of Applied Ecology, 36(1), 75–84. https://doi.org/10.1046/j.1365-2664.1999.00378.x

Bearhop, S., Waldron, S., Votier, S. C., & Furness, R. W. (2002). Factors That influence assimilation rates and fractionation of nitrogen and carbon stable isotopes in avian blood and feathers. Physiological and Biochemical Zoology, 75(5), 451–458.

Beck, M. L., Hopkins, W. A., & Jackson, B. P. (2014). Variation in riparian consumer diet composition and differential bioaccumulation by prey influence the risk of exposure to elements from a recently remediated fly ash spill. Environmental Toxicology and Chemistry, 33(11), 2595–2608. https://doi.org/10.1002/etc.2719

Becker, M. E., & Weisberg, P. J. (2015). Synergistic effects of spring temperatures and land cover on nest survival of urban birds. The Condor, 117(1), 18–30. https://doi.org/10.1650/CONDOR-14-1.1

Benke, A., Wallace, J., & Harrison, J. (2001). Food web quantification using secondary production analysis: predaceous …. Freshwater …, 329–346. https://doi.org/10.1046/j.1365-2427.2001.00680.x

Bennett, P. M., & Hobson, K. A. (2009). Trophic structure of a boreal forest arthropod community revealed by stable isotope (d13C, d15N) analyses. Entomological Science, 12(1), 17–24. https://doi.org/10.1111/j.1479-8298.2009.00308.x

Blair, R. B. (1996). Land use and avian species diversity along an urban gradient. Ecological Applications, 6(2), 506–519.

Boening, D. W. (2000). Ecological effects, transport, and fate of mercury: a general review. Chemosphere, 40(12), 1335–1351.

Bohning-Gaese, K., Taper, M. L., & Brown, J. H. (1993). Are declines in North American insectivorous songbirds due to Causes on the breeding range? Conservation Biology, 7(1), 76–86. Retrieved from http://www.jstor.org/stable/2386644%0Ahttp://about.jstor.org/terms

Booth, D. B., & Jackson, C. R. (1998). Urbanization of aquatic systems: degradation thresholds, 142

stormwater detection, and the limits of mitigation. Journal of the American Water Resources Association, 33(5), 1077–1090.

Both, C., Van Turnhout, C. A. M., Bijlsma, R. G., Siepel, H., Van Strien, A. J., & Foppen, R. P. B. (2010). Avian population consequences of climate change are most severe for long- distance migrants in seasonal habitats. Proceedings of the Royal Society B-Biological Sciences, 277(1685), 1259–1266. https://doi.org/10.1098/rspb.2009.1525

Bourret, A., Bélisle, M., Pelletier, F., & Garant, D. (2015). Multidimensional environmental influences on timing of breeding in a tree swallow population facing climate change. Evolutionary Applications, 8(10), 933–944. https://doi.org/10.1111/eva.12315

Brasso, R. L., & Cristol, D. A. (2008). Effects of mercury exposure on the reproductive success of Tree Swallows (Tachycineta bicolor). Ecotoxicology, 17(2), 133–141. https://doi.org/10.1007/s10646-007-0163-z

Brigham, R. M. (1989). Roost and nest sites of Common Nighthawks: are gravel roofs important? The Condor, 91, 122–124.

Brown, L. R., Cuffney, T. F., Coles, J. F., Fitzpatrick, F., McMahon, G., Steuer, J., … May, J. T. (2009). Urban streams across the USA: lessons learned from studies in 9 metropolitan areas. Journal of the North American Benthological Society, 28(4), 1051–1069. https://doi.org/10.1899/08-153.1

Burdon, F. J., & Harding, J. S. (2008). The linkage between riparian predators and aquatic insects across a stream-resource spectrum. Freshwater Biology, 53(2), 330–346. https://doi.org/10.1111/j.1365-2427.2007.01897.x

Burger, J., & Gochfeld, M. (1997). Risk, mercury levels, and birds: relating adverse laboratory effects to field biomonitoring. Environmental Research, 172(2), 160–172.

Butler, R. W. (1988). Population dynamics and migration routes of Tree Swallows, Tachycineta bicolor, in North America. Journal of Field Ornithology, 59(4), 395–402.

Cabana, G., & Rasmussen, J. (1996). Comparison of aquatic food chains using nitrogen isotopes. Proceedings of the National Academy of Sciences of the United States of America, 93(20), 10844–10847.

Caquet, T. (2006). Use of carbon and nitrogen stable isotope ratios to assess the effects of environmental contaminants on aquatic food webs. Environmental Pollution, 141(1), 54–59. https://doi.org/10.1016/j.envpol.2005.08.029

Caut, S., Angulo, E., & Courchamp, F. (2008). Caution on isotopic model use for analyses of consumer diet. Canadian Journal of Zoology, 86(5), 438–445. https://doi.org/10.1139/Z08- 012

143

Caut, S., Angulo, E., & Courchamp, F. (2009). Variation in discrimination factors (Δ15N and Δ13C): The effect of diet isotopic values and applications for diet reconstruction. Journal of Applied Ecology, 46(2), 443–453. https://doi.org/10.1111/j.1365-2664.2009.01620.x

Chalmers, A. T., Krabbenhoft, D. P., Metre, P. C. Van, & Nilles, M. A. (2014). Effects of urbanization on mercury deposition and accumulation in New England. Environmental Pollution, 192, 104–112. https://doi.org/10.1016/j.envpol.2014.05.003

Chamberlain, D., Hatchwell, B., & Gaston, K. J. (2009). Avian productivity in urban landscapes: a review and meta-analysis. Ibis, 151(1), 1–18. https://doi.org/10.1111/j.1474- 919X.2008.00899.x

Chislock, M. F., Doster, E., Zitomer, R. A., & Wilson, A. E. (2013). Eutrophication: causes, consequences, and controls in aquatic ecosystems. Nature Education Knowledge, 4(4), 10. Retrieved from http://www.wilsonlab.com/publications/2013_NE_Chislock_et_al.pdf

Collier, K. J., Bury, S., & Gibbs, M. (2002). A stable isotope study of linkages between stream and terrestrial food webs through spider predation. Freshwater Biology, 47(9), 1651–1659. https://doi.org/10.1046/j.1365-2427.2002.00903.x

Compin, A., & Céréghino, R. (2003). Sensitivity of aquatic insect species richness to disturbance in the Adour–Garonne stream system (France). Ecological Indicators, 3(2), 135–142. https://doi.org/10.1016/S1470-160X(03)00016-5

Compson, Z. G., Adams, K. J., Edwards, J. A., Maestas, J. M., Whitham, T. G., & Marks, J. C. (2013). Leaf litter quality affects aquatic insect emergence: contrasting patterns from two foundation trees. Oecologia, 173(2), 507–519. https://doi.org/10.1007/s00442-013-2643-6

Cox, A. R., Robertson, R. J., Fedy, B. C., Rendell, W. B., & Bonier, F. (2018). Demographic drivers of local population decline in Tree Swallows (Tachycineta bicolor). The Condor, 120(4), 842–851. https://doi.org/10.1650/CONDOR-18-42.1

Crick, H. Q. P. (2004). The impact of climate change on birds. Ibis, 146(Suppl. 1), 48–56.

Cristol, D., Brasso, R., Monroe, A., Condon, R., Fovargue, A., Friedman, S., … White, A. (2008). The movement of aquatic mercury through terrestrial food webs. Science, 320(5874), 335.

Crooks, K. R., Suarez, A. V., & Bolger, D. T. (2004). Avian assemblages along a gradient of urbanization in a highly fragmented landscape. Biological Conservation, 115(3), 451–462. https://doi.org/10.1016/S0006-3207(03)00162-9

Cummins, K. W., & Klug, M. J. (1979). Feeding ecology of stream invertebrates. Annual Review of Ecology and Systematics, 10(1), 147–172. https://doi.org/10.1146/annurev.es.10.110179.001051

144

Cunningham, S. J., Martin, R. O., Hojem, C. L., & Hockey, P. A. R. (2013). Temperatures in excess of critical thresholds threaten nestling growth and survival in A rapidly-warming arid savanna: a study of Common Fiscals. PLoS ONE, 8(9), 1–10. https://doi.org/10.1371/journal.pone.0074613

Custer, C. M., Custer, T. W., Dummer, P. M., Munney, K. L., Midwest, U., Sciences, E., … Office, F. (2003). Exposure and effects of chemical contaminants on Tree Swallows nesting along the Housatonic River, Berkshire County, Massachusetts, USA, 1998 – 2000. Environmental Toxicology and Chemistry, 22(7), 1605–1621.

DeNiro, M. J., & Epstein, S. (1978). Influence of diet on the distribution of nitrogen isotopes in animals. Geochimica et Cosmochimica Acta, 42(3), 495–506. https://doi.org/10.1016/0016- 7037(81)90244-1

Dodds, W. K., & Smith, V. H. (2016). Nitrogen, phosphorus, and eutrophication in streams. Inland Waters, 6(2), 155–164. https://doi.org/10.5268/IW-6.2.909

Dods, P. L., Birmingham, E. M., Williams, T. D., Ikonomou, M. G., Bennie, D. T., & Elliott, J. E. (2005). Reproductive success and contaminants in tree swallows (Tachycineta bicolor) breeding at a wastewater treatment plant. Environmental Toxicology and Chemistry, 24(12), 3106–3112. https://doi.org/10.1897/04-547R.1

Driscoll, C. T., Han, Y., Chen, C. Y., Evers, D. C., Lambert, K. F., Holsen, T. M., … Munson, R. K. (2007). Mercury contamination in forest and freshwater ecosystems in the Northeastern United States. BioScience, 57(1), 17–28.

Dunn, P., & Hannon, S. J. (1992). Effects of food abundance and male parental care on reproductive success and monogamy in Tree Swallows. The Auk, 109(3), 488–499.

Dunn, P. O., & Winkler, D. W. (1999). Climate change has affected the breeding date of tree swallows throughout North America. Proceedings of the Royal Society B-Biological Sciences, 266(1437), 2487–2490.

Durance, I., & Ormerod, S. J. (2007). Climate change effects on upland stream macroinvertebrates over a 25-year period. Global Change Biology, 13(5), 942–957. https://doi.org/10.1111/j.1365-2486.2007.01340.x

Eeva, T., Veistola, S., & Lehikoinen, E. (2000). Timing of breeding in subarctic passerines in relation to food availability. Canadian Journal of Zoology, 78(1), 67–78. https://doi.org/10.1139/cjz-78-1-67

English, P. A., Green, D. J., & Nocera, J. J. (2018). Stable isotopes from museum specimens may provide evidence of long-term change in the trophic ecology of a migratory aerial insectivore. Frontiers in Ecology and Evolution, 6(February), 14. https://doi.org/10.3389/FEVO.2018.00014 145

Environment Canada. (2007). Chimney swift (Chaetura pelagica) COSEWIC assessment and status report. Ottawa.

Environment Canada. (2012). The State of Canada’s Birds. Ottawa.

Evers, D. C., Burgess, N. M., Champoux, L., Hoskins, B., Major, A., Goodale, W. M., … Daigle, T. (2005). Patterns and interpretation of mercury exposure in freshwater avian communities in northeastern North America. Ecotoxicology, 14(1–2), 193–221.

Fausch, K. D., Baxter, C. V., & Murakami, M. (2010). Multiple stressors in north temperate streams: lessons from linked forest-stream ecosystems in northern Japan. Freshwater Biology, 55(SUPPL. 1), 120–134. https://doi.org/10.1111/j.1365-2427.2009.02378.x

Fimreite, N. (1974). Mercury contamination of aquatic birds in Northwestern Ontario. The Journal of Wildlife Management, 38(1), 120–131.

Finlay, J. C. (2001). Stable carbon isotope ratios of river biota: implications for energy flow in lotic food webs. Ecology, 82(4), 1052–1064.

Fraser, K. C., Stutchbury, B. J. M., Silverio, C., Kramer, P. M., Barrow, J., Newstead, D., … Tautin, J. (2012). Continent-wide tracking to determine migratory connectivity and tropical habitat associations of a declining aerial insectivore. Proceedings of the Royal Society B- Biological Sciences, 279(1749), 4901–4906. https://doi.org/10.1098/rspb.2012.2207

Freeman, P. L., & Schorr, M. S. (2004). Influence of watershed urbanization on fine sediment and macroinvertebrate assemblage characteristics in Tennessee ridge and valley streams. Journal of Freshwater Ecology, 19(3), 353–362. https://doi.org/10.1080/02705060.2004.9664908

Fry, B. (2006). Stable isotope ecology. Stable isotope ecology. New York: Springer Science+Business Media. https://doi.org/10.1016/j.dsr2.2015.11.009

Gage, M. S., Spivak, A., & Paradise, C. J. (2004). Effects of land use and disturbance on benthic insects in headwater streams drainging small watersheds. Southeastern Naturalist, 3(2), 345–358.

Gentes, M., Waldner, C., Papp, Z., & Smits, J. E. G. (2006). Effects of oil sands tailings compounds and harsh weather on mortality rates, growth and detoxification efforts in nestling Tree Swallows (Tachycineta bicolor). Environmental Pollution, 142(1), 24–33. https://doi.org/10.1016/j.envpol.2005.09.013

Gerald, M., & Tebaldi, C. (2004). More intense, more frequent, and longer-lasting heat waves in the 21st Century. Science, 305(August), 994–997. https://doi.org/10.1126/science.1098704

Ghilain, A., & Bélisle, M. (2008). Breeding success of Tree Swallows along a gradient of agricultural intensification. Ecological Applications, 18(5), 1140–1154. 146

https://doi.org/10.1890/07-1107.1

Golondrinas de las Americas. (2011). Nest box design.

Grable, J. L., & Harden, C. P. (2006). Geomorphic response of an Appalachian Valley and Ridge stream to urbanization. Earth Surface Processes and Landforms, 31(13), 1707–1720. https://doi.org/10.1002/esp

Gray, L. J. (1993). Response of insectivorous birds to emerging aquatic insects in riparian habitats of a tallgrass prairie stream. American Midland Naturalist, 129(2), 288–300.

Gurtz, M. E., & Wallace, J. B. (1984). Substrate-mediated response of stream invertebrates to disturbance. Ecology, 65(5), 1556–1569.

Hagar, J. C., Li, J., Sobota, J., & Jenkins, S. (2012). Arthropod prey for riparian associated birds in headwater forests of the Oregon Coast Range. Forest Ecology and Management, 285, 213–226. https://doi.org/10.1016/j.foreco.2012.08.026

Hallinger, K. K., & Cristol, D. A. (2011). The role of weather in mediating the effect of mercury exposure on reproductive success in Tree Swallows. Ecotoxicology, 20(6), 1368–1377. https://doi.org/10.1007/s10646-011-0694-1

Harper, M. P. H., & Peckarsky, B. L. (2006). Emergence cues of a mayfly in a high-altitude stream ecosystem: potential response to climate change. Ecological Applications, 16(2), 612–621.

Harris, D. J. (2009). Clinical tests. Handbook of Avian Medicine (Second Edi). Elsevier Limited. Retrieved from http://dx.doi.org/

Harris, G. P., & Baxter, G. (1996). Interannual variability in phytoplankton biomass and species composition in a subtropical reservoir. Freshwater Biology, 35(3), 545–560. https://doi.org/10.1111/j.1365-2427.1996.tb01768.x

Harvey, C. J., & Kitchell, J. F. (2000). A stable isotope evaluation of the structure and spatial heterogeneity of a Lake Superior food web. Canadian Journal of Fisheries and Aquatic Sciences, 57(7), 1395–1403.

Hawkins, C. P., Hogue, J. N., Decker, L. M., & Feminella, J. W. (1997). Channel morphology, water temperature, and assemblage structure of stream insects. Journal of the North American Benthological Society, 16(4), 728–749.

Hawley, D. M., Hallinger, K. K., & Cristol, D. A. (2009). Compromised immune competence in free-living tree swallows exposed to mercury. Ecotoxicology, 18(5), 499–503. https://doi.org/10.1007/s10646-009-0307-4

Heinrich, K. K., Whiles, M. R., & Roy, C. (2014). Cascading ecological responses to an in- 147

stream restoration project in a midwestern river. Restoration Ecology, 22(1), 72–80. https://doi.org/10.1111/rec.12026

Helms, B. S., Schoonover, J. E., & Feminella, J. W. (2009). Seasonal variability of landuse impacts on macroinvertebrate assemblages in streams of western Georgia, USA. Journal of the North American Benthological Society, 28(4), 991–1006. https://doi.org/10.1899/08- 162.1

Hendrickx, F., Maelfait, J., Wingerden, W. Van, Schweiger, O., Speelmans, M., Aviron, S., … Bugter, R. (2007). How landscape structure, land‐use intensity and habitat diversity affect components of total arthropod diversity in agricultural landscapes. Journal of Applied Ecology, 44(2), 340–351.

Hespenheide, H. A. (1971). Food preference and the extent of overlap in some insectivorous birds, with special reference to the Tyrannidae. Ibis, 113(1), 59–72. https://doi.org/10.1111/j.1474-919X.1971.tb05123.x

Hession, W. C., Pizzuto, J. E., Johnson, T. E., & Horwitz, R. J. (2003). Influence of bank vegetation on channel morphology in rural and urban watersheds. Geology, 31(2), 147–150. https://doi.org/10.1130/0091-7613(2003)031<0147:IOBVOC>2.0.CO;2

Homer, C. G., Dewitz, J. A., Yang, L., Jin, S., Danielson, P., Xian, G., … Megown, K. (2015). Completion of the 2011 National Land Cover Database for the conterminous United States- representing a decade of land cover change information. Photogrammetric Engineering and Remote Sensing, 81(5), 345–354.

Hughes, L. (2000). Biological consequences of global warming: is the signal already apparent? Trends in Ecology & Evolution, 15(2), 56–61. https://doi.org/10.1016/S0169- 5347(99)01764-4

Hussell, D. (2003). Climate change, spring temperatures, and timing of breeding of Tree Swallows (Tachycineta bicolor) in southern Ontario. The Auk, 120(3), 607–618.

Hussell, D., & Quinney, T. E. (1987). Food abundance and clutch size of Tree Swallows Tachycineta bicolor. Ibis, 129(1), 243–258. https://doi.org/10.1111/fwb.12476

Iwata, T., Nakano, S., & Murakami, M. (2003). Stream meanders increase insectivorous bird abundance in riparian deciduous forests. Ecography, 26(September 2002), 325–337. https://doi.org/10.1034/j.1600-0587.2003.03355.x

Jackson, A. K., Evers, D. C., Etterson, M. A., Condon, A. M., Sarah, B., Detweiler, J., … Thryothorus, D. (2011). Mercury exposure affects the reproductive success of a free-living terrestrial songbird, the Carolina Wren (Thryothorus ludovicianus). The Auk, 128(4), 759– 769.

148

Jackson, J. K., & Fisher, S. G. (1986). Secondary production, emergence, and export of aquatic insects of a Sonoran Desert stream. Ecology, 67(3), 629–638.

Johnson, N. F., & Triplehorn, C. A. (2005). c (7th ed.). Boston: Brooks/Cole.

Johnson, R. C., Jin, H., Carreiro, M. M., & Jack, J. D. (2013). Macroinvertebrate community structure, secondary production and trophic-level dynamics in urban streams affected by non-point-source pollution. Freshwater Biology, 58(5), 843–857. https://doi.org/10.1111/fwb.12090

Jones, J. (2003). Tree swallows (Tachycineta bicolor): A new model organism? The Auk, 120(3), 591–599.

Jonsson, M., Hedström, P., Stenroth, K., Hotchkiss, E. R., Vasconcelos, F. R., Karlsson, J., & Byström, P. (2015). Climate change modifies the size structure of assemblages of emerging aquatic insects. Freshwater Biology, 60(1), 78–88. https://doi.org/10.1111/fwb.12468

Jonsson, M., Strasevicius, D., & Malmqvist, B. (2012). Influences of river regulation and environmental variables on upland bird assemblages in northern Sweden. Ecological Research, 27(5), 945–954. https://doi.org/10.1007/s11284-012-0974-0

Karagicheva, J., Liebers, M., Rakhimberdiev, E., Hallinger, K. K., Saveliev, A., & Winkler, D. W. (2016). Differences in size between first and replacement clutches match the seasonal decline in single clutches in Tree Swallows Tachycineta bicolor. Ibis, 158(3), 607–613.

Kautza, A., & Sullivan, S. M. P. (2015). Shifts in reciprocal river-riparian arthropod fluxes along an urban-rural landscape gradient. Freshwater Biology, 60(10), 2156–2168. https://doi.org/10.1111/fwb.12642

Kautza, A., & Sullivan, S. M. P. (2016a). Anthropogenic and natural determinants of fish food- chain length in a midsize river system. Freshwater Science, 35(3), 895–908. https://doi.org/10.1086/685932

Kautza, A., & Sullivan, S. M. P. (2016b). The energetic contributions of aquatic primary producers to terrestrial food webs in a mid-size river system. Ecology, 97(3), 694–705. https://doi.org/10.1890/15-1095.1

Kenward, A., Yawitz, D., Sanford, T., & Wang, R. (2014). Summer in the city: Hot and getting hotter. Princeton.

Klein, R. D. (1980). Urbanization and stream quality impairment. Water Resources Bulletin, 15(4), 948–963.

Kondolf, G. M. (1995). Five elements for effective evaluation of stream restoration. Restoration Ecology. https://doi.org/10.1111/j.1526-100X.1995.tb00086.x

149

Kuznetsova, A., Brockhoff, P. B., Haubo, R., & Christensen, B. (2017). lmerTest. Retrieved from https://github.com/runehaubo/lmerTestR

Labocha, M. K., & Hayes, J. P. (2012). Morphometric indices of body condition in birds: a review. Journal of Ornithology, 153(1), 1–22. https://doi.org/10.1007/s10336-011-0706-1

Langham, G., Schuetz, J., Soykan, C., Wilsey, C., Auer, T., LeBaron, G., … Distler, T. (2014). Audubon’s Birds and Climate Change Report. New York.

Layman, C. A., Araujo, M. S., Boucek, R., Hammerschlag-Peyer, C. M., Harrison, E., Jud, Z. R., … Bearhop, S. (2012). Applying stable isotopes to examine food-web structure: An overview of analytical tools. Biological Reviews, 87(3), 545–562. https://doi.org/10.1111/j.1469-185X.2011.00208.x

Learner, M. A., & Potter, D. W. B. (1974). The seasonal periodicity of emergence of insects from two Ponds in Hertfordshire, England, with special reference to the Chironomidae (Diptera: Nematocera). Hydrobiologia, 44(4), 495–510.

Leffelaar, D., & Robertson, R. J. (1986). Equality of feeding roles and the maintenance of monogamy in Tree Swallows. Behavioral Ecology and Sociobiology, 18(3), 199–206.

Lenat, D. R. (1988). Water quality assessment of streams using a qualitative collection method for benthic macroinvertebrates. Journal of the North American Benthological Society, 7(3), 222–233. https://doi.org/10.2307/1467422

Lenat, D. R., & Crawford, J. K. (1994). Effect of land use on water quality and aquatic biota of three North Carolina Piedmont streams. Hydrobiologia, 294(3), 185–199. https://doi.org/10.3923/ijb.2012.181.191

Li, Y., & Cai, Y. (2013). Progress in the study of mercury methylation and demethylation in aquatic environments. Chinese Science Bulletin, 58(2), 177–185.

Lifjeld, J. T., Dunn, P. O., & Whittingham, L. A. (2002). Short-term fluctuations in cellular immunity of tree swallows feeding nestlings. Oecologia, 130(2), 185–190. https://doi.org/10.1007/s004420100798

Lill, A. (2011). Sources of variation in blood glucose concentrations of free-living birds. Avian Biology Research, 4(2), 78–87. https://doi.org/10.3184/175815511X13073729328092

Lussier, S. M., da Silva, S. N., Charpentier, M., Heltshe, J. F., Cormier, S. M., Klemm, D. J., … Jayaraman, S. (2008). The influence of suburban land use on habitat and biotic integrity of coastal Rhode Island streams. Environmental Monitoring and Assessment, 139(1–3), 119– 136. https://doi.org/10.1007/s10661-007-9820-1

Lussier, S. M., Enser, R. W., Dasilva, S. N., & Charpentier, M. (2006). Effects of habitat disturbance from residential development on breeding bird communities in riparian 150

corridors. Environmental Management, 38(3), 504–521. https://doi.org/10.1007/s00267- 005-0088-3

Lutz, M. A., Brigham, M. E., Krabbenhoft, D. P., Aiken, G. R., & Orem, W. H. (2009). methylmercury production and bed sediment-pore water partitioning. Environmental Science & Technology, 43(8), 2726–2732.

MacHunter, J., Wright, W., Loyn, R., & Rayment, P. (2006). Bird declines over 22 years in forest remnants in southeastern Australia: Evidence of faunal relaxation? Canadian Journal of Forest Research, 36(11), 2756–2768. https://doi.org/10.1139/x06-159

Macivor, J. S., & Lundholm, J. (2011). Insect species composition and diversity on intensive green roofs and adjacent level-ground habitats. Urban Ecosystems, 14(2), 225–241. https://doi.org/10.1007/s11252-010-0149-0

Marczak, L. B., Sakamaki, T., Turvey, S. L., Deguise, I., Wood, S. L. R., & Richardson, J. S. J. S. (2010). Are forested buffers an effecive conservation strategy for riparian fauna? An assessment using meta-analysis. Ecological Applications, 20(1), 126–134. https://doi.org/10.1890/08-2064.1

McArthur, S. L., McKellar, A. E., Flood, N. J., & Reudink, M. W. (2017). Local weather and regional climate influence breeding dynamics of Mountain Bluebirds (Sialia currucoides) and Tree Swallows (Tachycineta bicolor): a 35-year study. Canadian Journal of Zoology, 95(4), 271–277.

McCarty, J. P. (1997). Aquatic community characteristics influence the foraging patterns of Tree Swallows. The Condor, 99(1), 210–213. https://doi.org/10.2307/1370241

McCarty, J. P. (2001). Review: ecological consequences of recent climate change. Conservation Biology, 15(2), 320–331.

McCarty, J. P. (2002). The number of visits to the nest by parents is an accurate measure of food delivered to nestlings in Tree Swallows. Journal of Field Ornithology, 73(1), 9–14.

McCarty, J. P., & Secord, A. L. (1999). Reproductive ecology of Tree Swallows (Tachycineta bicolor) with high levels of polychlorinated biphenyl contamination. Environmental Toxicology and Chemistry, 18(7), 1433. https://doi.org/10.1897/1551- 5028(1999)018<1433:REOTST>2.3.CO;2

McCarty, J. P., & Winkler, D. W. (1999a). Foraging ecology and diet selectivity of Tree Swallows feeding nestlings. The Condor, 101(2), 246–254. Retrieved from http://www.jstor.org/stable/pdf/1369987.pdf

McCarty, J. P., & Winkler, D. W. (1999b). Relative importance of environmental variables in determining the growth of nestling Tree Swallows Tachycineta bicolor. Ibis, 141(2), 286–

151

296.

McIntyre, N. E. (2000). Ecology of urban arthropods: a review and a call to action. Annals of the Entomological Society of America, 93(4), 825–835. https://doi.org/10.1603/0013- 8746(2000)093[0825:EOUAAR]2.0.CO;2

McKinney, M. (2002). Urbanization, biodiversity, and conservation. BioScience, 52(10), 883– 890.

Mengelkoch, J. M., Niemi, G. J., & Regal, R. R. (2004). Diet of the nestling Tree Swallow. The Condor, 106(2), 423–429.

Merrill, D., & Leatherby, L. (2018). Here’s how America uses its land. Retrieved from https://www.bloomberg.com/graphics/2018-us-land-use/

Merritt, R. W., Cummins, K. . W., & Berg, M. B. (2008). An Introduction to the Aquatic Insects of North America (4th ed.). Dubuque: Kendall Hunt.

Meybeck, M. (1998). Man and river interface: multiple impacts on water and particulates chemistry illustrated in the Seine river basin. Hydrobiologia, 373, 1–20. https://doi.org/10.1023/A:1017067506832

Meyer, J. L., Paul, M. J., & Taulbee, W. K. (2005). Stream ecosystem function in urbanizing landscapes. Journal of the American Benthological Society, 24(3), 602–612.

Michel, N. L., Smith, A. C., Clark, R. G., Morrissey, C. A., & Hobson, K. A. (2016). Differences in spatial synchrony and interspecific concordance inform guild-level population trends for aerial insectivorous birds. Ecography, 39(8), 774–786. https://doi.org/10.1111/ecog.01798

Miller, J. R., Wiens, J. A., Hobbs, N. T., & Theobald, D. M. (2003). Effects of human settlement on bird communities in lowland riparian areas of Colorado (USA). Ecological Applications, 13(4), 1041–1059.

Minagawa, M., & Wada, E. (1984). Stepwise enrichment of 15N along food chains: Further evidence and the relation between 15N and animal age. Geochimica et Cosmochimica Acta, 48(5), 1135–1140. https://doi.org/10.1016/0016-7037(84)90204-7

Minshall, G. W. (1978). Autotropy in Stream Ecosystems. BioScience, 28(12), 767–771. https://doi.org/10.2307/1307250

Monroe, A. P., Hallinger, K. K., Brasso, R. L., & Cristol, D. A. (2008). Occurrence and implications of double brooding in a southern population of Tree Swallows. The Condor, 110(2), 382–386. https://doi.org/10.1525/cond.2008.8341

Moore, J. W., & Semmens, B. X. (2008). Incorporating uncertainty and prior information into stable isotope mixing models. Ecology Letters, 11(5), 470–480. 152

https://doi.org/10.1111/j.1461-0248.2008.01163.x

Morel, F. M. M., Kraepiel, A. M. L., & Amyot, M. (1998). The chemical cycle and bioaccumulation of mercury. Annual Review of Ecology and Systematics, 29(1), 543–566. https://doi.org/10.1146/annurev.ecolsys.29.1.543

Morse, C. C., Huryn, A. D., & Cronan, C. (2003). Impervious surface area as a predictor of the effects of urbanization on stream insect communities in Maine, USA. Environmental Monitoring and Assessment, 89(1), 95–127.

Muehlbauer, J. D., Collins, S. F., Doyle, M. W., & Tockner, K. (2014). How wide is a stream? Spatial extent of the potential “stream signature” in terrestrial food webs using meta- analysis. Ecology, 95(1), 44–55.

Muldal, A., Gibbs, H. L., & Robertson, R. J. (1985). Preferred nest spacing of an obligate cavity- nesting bird, the Tree Swallow. The Condor, 87(3), 356–363. Retrieved from http://www.jstor.org/stable/pdf/1367216.pdf

Munthe, J., Bodaly, R. A. D., Branfireun, B. A., Driscoll, C. T., Cynthia, C., Harris, R., … Harris, R. (2007). Recovery of mercury-contaminated fisheries. AMBIO: A Journal of the Human Environment, 36(1), 33–44.

Murakami, M., & Nakano, S. (2002). Indirect effect of aquatic insect emergence on a terrestrial insect population through bird predation. Ecology Letters, 5(3), 333–337. https://doi.org/10.1046/j.1461-0248.2002.00321.x

Naef-Daenzer, B., & Grüebler, M. U. (2016). Post-fledging survival of altricial birds: ecological determinants and adaptation. Journal of Field Ornithology, 87(3), 227–250. https://doi.org/10.1111/jofo.12157

Naiman, R. J., & Decamps, H. (1997). The ecology of interfaces: Riparian zones. Annual Review of Ecology, Evolution, and Systematics, 28(102), 621–658. https://doi.org/10.1146/annurev.ecolsys.28.1.621

Naiman, R. J., Decamps, H., & Pollock, M. (1993). The role of riparian corridors in maintaining regional biodiversity. Ecological Application, 3(2), 209–212. https://doi.org/10.2307/1941822

Nakano, S., & Murakami, M. (2001). Reciprocal subsidies: dynamic interdependence between terrestrial and aquatic food webs. Proceedings of the National Academy of Sciences of the United States of America, 98(1), 166–170.

Nancy B. Grimm, Sheibley, R. W., Crenshaw, C. L., Dahm, C. N., Roach, W. J., & Zeglin, L. H. (2005). N retention and transformation in urban streams. Journal of the North American Benthological Society, 24(3), 626–642.

153

Nebeker, A. V. (1971). Effect of high winter water temperatures on adult emergence of aquatic insects. Water Research, 5(9), 777–783. https://doi.org/10.1016/0043-1354(71)90100-X

Nebel, S., Mills, A., Mccracken, J. D., & Taylor, P. D. (2010). Declines of aerial insectivores in North America follow a geographic gradient. Avian Conservation & Ecology, 5(2), 1. https://doi.org/10.5751/ACE-00391-050201

Nelson, K. C., & Palmer, M. A. (2007). Stream temperature surges under urbanization and climate change: data, models, and responses. Journal of the American Water Resources Association, 43(2), 440–452.

Newhouse, M. J., Marra, P. P., & Johnson, L. S. (2008). Reproductive success of House Wrens in suburban and rural landscapes. The Wilson Journal of Ornithology, 120(1), 99–104. https://doi.org/10.1676/06-156.1

Nooker, J. K., Dunn, P. O., & Whittingham, L. a. (2005). Effects of food abundance, weather, and female condition on reproduction in Tree Swallows (Tachycineta bicolor). The Auk, 122(4), 1225–1238. https://doi.org/10.1642/0004- 8038(2005)122{[}1225:EOFAWA]2.0.CO;2

Nordlie, K. J., & Arthur, J. W. (1981). Effect of elevated water temperature on insect emergence in outdoor experimental channels. Environmental Pollution, 25(1), 53–65.

Norris, A. R., Aitken, K. E. H., Martin, K., & Pokorny, S. (2018). Nest boxes increase reproductive output for Tree Swallows in a forest grassland matrix in central British Columbia. Plos One, 13(10), e0204226. https://doi.org/10.1371/journal.pone.0204226

Ohio Environmental Protection Agency. (2014). Scioto River watershed. Retrieved from http://www.epa.ohio.gov/dsw/tmdl/sciotoriver.aspx#122556530-implementation

Ohlendorf, H. M., Kilness, A. W., Simmons, J. L., Richard, K., Hoffman, D. J., Moore, J. F., … Dakota, S. (1988). Selenium toxicosis in wild aquatic birds. Journal of Toxicology and Environmental Health, 24(1), 67–92. https://doi.org/10.1080/15287398809531141

Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108(455), 1–24. https://doi.org/10.1002/qj.49710845502

Parnell, A. C., Inger, R., Bearhop, S., & Jackson, A. L. (2010). Source partitioning using stable isotopes: Coping with too much variation. PLoS ONE, 5(3), e9672. https://doi.org/10.1371/journal.pone.0009672

Parnell, A., & Jackson, A. (2013). SIAR. Retrieved from https://cran.r-project.org/package=siar

Parnell, A., & Jackson, A. (2015). Package ‘ siar ’ documentation. https://doi.org/10.1080/07351690701310649

154

Paul, M. J., & Meyer, J. L. (2001). Streams in the urban landscape. Annual Review of Ecology and Systematics, 32, 333–365. https://doi.org/10.1146/annurev.ecolsys.32.081501.114040

Peig, J., & Green, A. J. (2017). New perspectives for estimating body condition from mass/length data: The scaled mass index as an alternative method. Oikos, 118(12), 1883– 1891.

Perez, J. H., Ardia, D. R., Chad, E. K., & Clotfelter, E. D. (2008). Experimental heating reveals nest temperature affects nestling condition in tree swallows (Tachycineta bicolor). Biology Letters, 4(5), 468–471. https://doi.org/10.1098/rsbl.2008.0266

Peters, N. E. (2009). Effects of urbanization on stream water quality in the city of Atlanta, Georgia, USA. Hydrological Processes, 23(20), 2860–2878. https://doi.org/10.1002/hyp

Peterson, B. J., & Fry, B. (1987). Stable isotopes in ecosystem studies. Annual Review of Ecology and Systematics, 18(1), 293–320. https://doi.org/10.1146/annurev.es.18.110187.001453

Piland, N. C., & Winkler, D. W. (2015). Tree Swallow frugivory in winter. Southeastern Naturalist, 14(1), 123–137.

Pilgrim, J. M., Fang, X., & Stefan, H. G. (1999). Stream temperature correlations with air temperatures in Minnesota: implications for climate warming. Journal of the American Water Resources Association, 34(5), 1109–1121.

Pipoly, I., Bókony, V., Seress, G., Szabó, K., & Liker, A. (2013). Effects of extreme weather on reproductive success in a temperate-breeding songbird. PLoS ONE, 8(11), 1–11. https://doi.org/10.1371/journal.pone.0080033

Pirrone, N., Cinnirella, S., Feng, X., Finkelman, R. B., Friedli, H. R., Leaner, J., … Mukherjee, A. B. (2010). Global mercury emissions to the atmosphere from anthropogenic and natural sources. Atmospheric Chemistry and Physics, 10(13), 5951–5964. https://doi.org/10.5194/acp-10-5951-2010

Polis, G. A., Anderson, W. B., & Holt, R. D. (1997). Toward an integration of landscape and food web ecology: The dynamics of spatially subsidized food webs. Annual Review of Ecology and Systematics, 28, 289–316.

Post, D. M. (2002). Using stable isotopes to estimate trophic position: models, methos, and assumptions. Ecology, 83(3), 703–718. https://doi.org/Doi 10.2307/3071875

Post, D. M., Pace, M. L., & Hairston, N. G. (2000). Ecosystem size determines food chain-length in lakes. Nature, 405(6790), 1047–1049.

Poulin, B., Lefebvre, G., & Paz, L. (2010). Red flag for green spray: adverse trophic effects of Bti on breeding birds. Journal of Applied Ecology, 47(4), 884–889. 155

https://doi.org/10.1111/j.1365-2664.2010.01821.x

Powell, G. V. N. (1983). Industrial effluents as a source of mercury contamination in terrestrial riparian vertebrates. Environmental Pollution Series B, Chemical and Physical, 5(1), 51–57.

Power, M. E., & Dietrich, W. E. (2002). Food webs in river networks. Ecological Research, 17(4), 451–471.

QGIS Development Team. (2017). QGIS Geographic Information System. Open Source Geospatial Foundation Project.

Quinney, T. E., & Ankney, C. D. (1985). Prey size selection by Tree Swallows. The Auk, 102(2), 245–250.

Quinney, T. E., Hussell, D. J. T., Ankney, C. D., & Rowan, P. (1986). Sources of variation in the growth of Tree Swallows. The Auk, 103(April), 389–400.

R Core Team. (2018). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Retrieved from https://www.r-project.org

Ramírez, A., De Jesús-Crespo, R., Martinó-Cardona, D. M., Martínez-Rivera, N., & Burgos- Caraballo, S. (2009). Urban streams in Puerto Rico: what can we learn from the tropics? Journal of the North American Benthological Society, 28(4), 1070–1079. https://doi.org/10.1899/08-165.1

Rau, G. H., Sweeney, R. E., Kaplan, I. R., Mearns, A. J., & Young, D. R. (1981). Differences in animal 13C, 15N and D abundance between a polluted and an unpolluted coastal site: Likely indicators of sewage uptake by a marine food web. Estuarine, Coastal and Shelf Science, 13(6), 701–707. https://doi.org/10.1016/S0302-3524(81)80051-5

Razeng, E., & Watson, D. M. (2015). Nutritional composition of the preferred prey of insectivorous birds: popularity reflects quality. Journal of Avian Biology, 46(1), 89–96. https://doi.org/10.1111/jav.00475

Reavie, E. D., Jicha, T. M., Angradi, T. R., Bolgrien, D. W., & Hill, B. H. (2010). Algal assemblages for large river monitoring: Comparison among biovolume, absolute and relative abundance metrics. Ecological Indicators, 10(2), 167–177. https://doi.org/10.1016/j.ecolind.2009.04.009

Ren, W., Zhong, Y., Meligrana, J., Anderson, B., Watt, W. E., Chen, J., & Leung, H. (2003). Urbanization, land use, and water quality in Shanghai 1947 – 1996. Environment International, 29(5), 649–659. https://doi.org/10.1016/S0160-4120(03)00051-5

Rencher, A. C. (1995). Methods of multivariate analysis. New York: John Wiley and Sons, Inc.

Rendell, W. B., & Robertson, R. J. (1989). Nest-site characteristics, reproductive success and 156

cavity avilaiblity for Tree Swallows breeding in natural cavities. The Condor, 91(4), 875– 885.

Rendell, W. B., & Robertson, R. J. (1993). Cavity size, clutch‐size and the breeding ecology of Tree Swallows Tachycineta bicolor. Ibis, 135(3), 305–310. https://doi.org/10.1111/j.1474- 919X.1993.tb02848.x

Richardson, J. S., & Sato, T. (2015). Resource subsidy flows across freshwater-terrestrial boundaries and influence on processes linking adjacent ecosystems. Ecohydrology, 8(3), 406–415. https://doi.org/10.1002/eco.1488

Richmond, E. K., Rosi, E. J., Walters, D. M., Fick, J., Hamilton, S. K., Brodin, T., … Grace, M. R. (2018). A diverse suite of pharmaceuticals contaminates stream and riparian food webs. Nature Communications, 9(1), 4491. https://doi.org/10.1038/s41467-018-06822-w

Rioux-Paquette, S., Pelletier, F., Garant, D., & Bélisle, M. (2014). Severe recent decrease of adult body mass in a declining insectivorous bird population. Proceedings of the Royal Society B: Biological Sciences, 281(1786). https://doi.org/10.1098/rspb.2014.0649

Robertson, R. J., Stutchbury, B. J., & Cohen, R. R. (2011). Tree Swallow. Retrieved March 1, 2017, from https://birdsna.org/Species-Account/bna/species/011/articles/introduction

Rodewald, A. D., & Bakermans, M. H. (2006). What is the appropriate paradigm for riparian forest conservation? Biological Conservation, 128(2), 193–200. https://doi.org/10.1016/j.biocon.2005.09.041

Rodewald, A. D., Kearns, L. J., & Shustack, D. P. (2013). Consequences of urbanizing landscapes to reproductive performance of birds in remnant forests. Biological Conservation, 160, 32–39. https://doi.org/10.1016/j.biocon.2012.12.034

Rodrigues, L., Train, S., Bovo-Scomparin, V., Jati, S., Borsalli, C., & Marengoni, E. (2009). Interannual variability of phytoplankton in the main rivers of the Upper Paraná River floodplain, Brazil: influence of upstream reservoirs. Brazilian Journal of Biology, 69(2), 501–516. https://doi.org/10.1590/S1519-69842009000300006

Rodríguez, S., & Barba, E. (2016). Nestling growth is impaired by heat stress: an experimental study in a mediterranean Great Tit population. Zoological Studies, 55(40), 1–13. https://doi.org/10.6620/ZS.2016.55-40

Roth, N. E., Allan, J. D., & Erickson, D. L. (1996). Landscape influences on stream biotic integrity assessed at multiple spatial scales. Landscape Ecology, 11(3), 141–156. https://doi.org/10.1007/BF02447513

Rottenborn, S. C. (1999). Predicting the impacts of urbanization on riparian bird communities. Biological Conservation, 88(3), 289–299. https://doi.org/10.1016/S0006-3207(98)00128-1

157

Rounick, J. S., & Winterbourn, M. J. (1986). Stable carbon isotopes and carbon flow in ecosystems. BioScience, 36(3), 171–177. https://doi.org/10.2307/1310304

Rowse, L. M., Rodewald, A. D., & Sullivan, S. M. P. (2014). Pathways and consequences of contaminant flux to Acadian flycatchers (Empidonax virescens) in urbanizing landscapes of Ohio, USA. Science of the Total Environment, 485–486(1), 461–467. https://doi.org/10.1016/j.scitotenv.2014.03.095

Roy, A. H., Rosemond, A. D., Paul, M. J., Leigh, D. S., & Wallace, J. B. (2003). Stream macroinvertebrate response to catchment urbanisation (Georgia, U.S.A.). Freshwater Biology, 48(2), 329–346.

RStudio Team. (2016). RStudio: Integrated Development Environment for R. Boston: RStudio, Inc. Retrieved from http://www.rstudio.com/

Rubin, D. B. (1988). Using the SIR algorithm to simulate posterior distributions. Bayesian Statistics 3: Proceedings ofthe Third Valencia International Meeting, June 1–5, 1987. Oxford.

Schaffers, A. P., Raemakers, I. P., Sýkora, K. V, & ter Braak, C. J. F. (2008). Arthropod assemblages are best predicted by plant species composition. Ecology, 89(3), 782–794. https://doi.org/10.1890/07-0361.1

Schindler, D. W. (1978). Factors regulating phytoplankton production and standing crop in the world’s freshwaters. Limnology and Oceanography, 23(3), 478–486. https://doi.org/10.4319/lo.1978.23.3.0478

Schlesinger, M. D., Manley, P. N., & Holyoak, M. (2008). Distinguishing stressors acting on land bird communities in an urbanizing environment. Ecology, 89(8), 2302–2314. https://doi.org/10.1890/07-0256.1

Schneider, S. C., & Miller, J. R. (2014). Response of avian communities to invasive vegetation in urban forest fragments. The Condor, 116(3), 459–471. https://doi.org/10.1650/CONDOR-13-009R1.1

Schueler, T. R. (1994). The importance of imperviousness. Watershed Protection Techniques, 1(3), 100–111.

Seto, K. C., Guneralp, B., & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences, 109(40), 16083–16088. https://doi.org/10.1073/pnas.1211658109

Shlosberg, A., Rumbeiha, W. K., Lublin, A., & Kannan, K. (2011). A database of avian blood spot examinations for exposure of wild birds to environmental toxicants: The DABSE biomonitoring project. Journal of Environmental Monitoring, 13(6), 1547–1558.

158

https://doi.org/10.1039/c0em00754d

Singmann, H., Bolker, B., Westfall, J., & Aust, F. (2018). afex. Retrieved from https://github.com/singmann/afex

Smith, A. C., Hudson, M.-A. R., Downes, C. M., & Francis, C. M. (2015). Change points in the population trends of aerial-insectivorous birds in North America: synchronized in time across species and regions. PLoS ONE, 10(7), 1–23. https://doi.org/10.1371/journal.pone.0130768

Smith, V. H., Tilman, G. D., & Nekola, J. C. (1998). Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environmental Pollution, 100(1– 3), 179–196. https://doi.org/10.1016/S0269-7491(99)00091-3

Smits, J. E. G., & Fernie, K. J. (2013). Avian wildlife as sentinels of ecosystem health. Comparative Immunology, Microbiology and Infectious Diseases, 36(3), 333–342. https://doi.org/10.1016/j.cimid.2012.11.007

Sponseller, R. A., Benfield, E. F., & Valett, H. M. (2001). Relationships between land use, spatial scale and stream macroinvertebrate communities. Acta Psychiatrica Scandinavica, 46(10), 1409–1424. https://doi.org/10.1111/j.1600-0447.1963.tb07839.x

Stanton, R. S., Lark, R. G. C. O. G. C., & Morrissey, C. A. M. (2017). Intensive agriculture and insect prey availability influence oxidative status and return rates of an aerial insectivore. Ecosphere, 8(3), e01746. https://doi.org/10.1002/ecs2.1746

Stenroth, K., Polvi, L. E., Fältström, E., Jonsson, M., & Science, E. (2015). Land-use effects on terrestrial consumers through changed size structure of aquatic insects. Freshwater Biology, 60(1), 136–149. https://doi.org/10.1111/fwb.12476

Steuer, J. J., Bales, J. D., Giddings, E. M. P., Steuer, J. J., & Giddings, E. M. P. (2009). Relationship of stream ecological conditions to simulated hydraulic metrics across a gradient of basin urbanization Published by : The University of Chicago Press on behalf of the Society for Freshwater Science Relationship of stream ecological conditions, 28(4), 955–976. https://doi.org/10.1899/08-157.1

Stewart, P. M., Butcher, J. T., & Swinford, T. O. (2000). Land use, habitat, and water quality effects on macroinvertebrate communities in three watersheds of a lake Michigan associated marsh system. Aquatic Ecosystem Health and Management, 3(1), 179–189. https://doi.org/10.1080/14634980008656999

Stone, B., Hess, J. J., & Frumkin, H. (2010). Urban form and extreme heat events: Are sprawling cities more vulnerable to climate change than compact cities? Environmental Health Perspectives, 118(10), 1425–1428. https://doi.org/10.1289/ehp.0901879

159

Strasevicius, D., Jonsson, M., Nyholm, N. E. I., & Malmqvist, B. (2013). Reduced breeding success of Pied Flycatchers Ficedula hypoleuca along regulated rivers. Ibis, 155(2), 348– 356. https://doi.org/10.1111/ibi.12024

Strayer, D. L., Beighley, R. E., Thompson, L. C., Brooks, S., Nilsson, C., Pinay, G., & Naiman, R. J. (2003). Effects of land cover on stream ecosystems: Roles of empirical models and scaling issues. Ecosystems, 6(5), 407–423. https://doi.org/10.1007/s10021-002-0170-0

Stutchbury, B. J., & Robertson, R. J. (1985). Floating populations of female Tree Swallows. The Auk, 102(3), 651–654.

Sullivan, S. M. P., Boaz, L. E., & Hossler, K. (2016). Fluvial geomorphology and aquatic-to- terrrestrial Hg export are weekly coupled in small urban streams of Columbus, Ohio. Water Resources Research, 52(4), 2822–2839. https://doi.org/10.1002/2014WR015716

Sullivan, S. M. P., Hossler, K., & Cianfrani, C. M. (2015). Ecosystem structure emerges as a strong determinant of food-chain length in linked stream–riparian ecosystems. Ecosystems, 18(8), 1356–1372. https://doi.org/10.1007/s10021-015-9904-7

Sullivan, S. M. P., Manning, D. W. P., & Davis, R. P. (2018). Do the ecological impacts of dam removal extend across the aquatic–terrestrial boundary? Ecosphere, 9(4), 1–19. https://doi.org/10.1002/ecs2.2180

Sullivan, S. M. P., & Rodewald, A. D. (2012). In a state of flux: The energetic pathways that move contaminants from aquatic to terrestrial environments. Environmental Toxicology and Chemistry, 31(6), 1175–1183. https://doi.org/10.1002/etc.1842

Sullivan, S. M. P., & Vierling, K. T. (2012). Exploring the influences of multiscale environmental factors on the American dipper Cinclus mexicanus. Ecography, 35(7), 624– 636. https://doi.org/10.1111/j.1600-0587.2011.07071.x

Sullivan, S. M. P., Watzin, M. C., & Hession, W. C. (2006). Differences in the reproductive ecology of belted kingfishers (Ceryle alcyon) across streams with varying geomorphology and habitat quality. Waterbirds, 29(3), 258–270. https://doi.org/Doi 10.1675/1524- 4695(2006)29[258:Ditreo]2.0.Co;2

Tam, B. Y., Gough, W. A., & Mohsin, T. (2015). The impact of urbanization and the urban heat island effect on day to day temperature variation. Urban Climate, 12, 1–10. https://doi.org/10.1016/j.uclim.2014.12.004

Taylor, L. R. (1963). Analysis of the effect of temperature on insects in flight. Journal of Animal Ecology, 32(1), 99–117.

Teglhøj, P. G. (2017). A comparative study of insect abundance and reproductive success of barn swallows Hirundo rustica in two urban habitats. Journal of Avian Biology, 48(6), 846–853.

160

https://doi.org/10.1111/jav.01086

Thomas, D. W., Blondel, J., Perret, P., Lambrechts, M. M., & Speakman, J. R. (2001). Energetic and fitness costs of mismatching resource supply and demand in seasonally breeding birds. Science, 291(5513), 2598–2601.

Thorp, J. H., & Delong, M. D. (1994). The riverine productivity model: An heuristic view of carbon sources and organic processing in large river ecosystems. Oikos, 70(2), 305–308.

Townes, H. (1972). A light-weight Malaise trap. Entomological News, 83, 239–247.

Townsend, A. K., Sillett, T. S., Lany, N. K., Kaiser, S. A., Rodenhouse, N. L., Webster, M. S., & Holmes, R. T. (2013). Warm springs, early lay dates, and double brooding in a North American migratory songbird, the Black-throated Blue Warbler. PLoS ONE, 8(4), e59467. https://doi.org/10.1371/journal.pone.0059467

Tromboni, F., & Dodds, W. K. (2017). Relationships between land use and stream nutrient concentrations in a Highly urbanized tropical region of Brazil: thresholds and riparian zones. Environmental Management, 60(1), 30–40. https://doi.org/10.1007/s00267-017- 0858-8

Twining, C. W., Brenna, J. T., Lawrence, P., Shipley, J. R., Tollefson, T. N., Winkler, D. W., … Winkler, D. W. (2016). Omega-3 long-chain polyunsaturated fatty acids support aerial insectivore performance more than food quantity. Proceedings of the National Academy of Sciences of the United States of America, 113(46), 10920–10925. https://doi.org/10.1073/pnas.1616962113

Twining, C. W., Shipley, J. R., & Winkler, D. W. (2018). Aquatic insects rich in omega-3 fatty acids drive breeding success in a widespread bird. Ecology Letters, 12(21), 1812–1820. https://doi.org/10.1111/ele.13156

U.S. Census Bureau. (2010). TIGER/Line shapefile, 2010, 2010 state, Ohio, 2010 census block state-based. Washington: U.S. Census Bureau.

U.S. Geological Survey. (2014a). NLCD 2011 percent developed imperviousness (2011 edition, amended 2014) - National Geospatial Data Asset (NGDA) land use land cover. Sioux Falls: U.S. Geological Survey.

U.S. Geological Survey. (2014b). NLCD2011 USFS percent tree canopy (cartographic version). Sioux Falls: U.S. Geological Survey.

U.S. Geological Survey. (2018). Bird Banding Laboratory. Retrieved from https://www.usgs.gov/centers/pwrc/science/bird-banding-laboratory

Uesugi, A., & Murakami, M. (2007). Do seasonally fluctuating aquatic subsidies influence the distribution pattern of birds between riparian and upland forests? Ecological Research, 161

22(2), 274–281. https://doi.org/10.1007/s11284-006-0028-6

Urban, M. C., Skelly, D. K., Burchsted, D., Price, W., & Lowry, S. (2006). Stream communities across a rural–urban landscape gradient. Diversity and Distributions, 12(4), 337–350. https://doi.org/10.1111/j.1366-9516.2005.00226.x

US EPA. (2008). Reducing urban heat islands: compendium of strategies urban heat island basics. Retrieved from http://www.epa.gov/hiri/resources/compendium.htm

Vander Zanden, M. J., & Rasmussen, J. B. (2001). Variation in 15N and 13C trophic fractionation: Implications for aquatic food web studies. Limnology and Oceanography, 46(8), 2061–2066. https://doi.org/10.4319/lo.2001.46.8.2061

Vannote, R. L., Minshall, G. W., Cummins, K. W., Sedell, J. R., & Cushing, C. E. (1980). The river continuum concept. Canadian Journal Fishery and Aquatic Sciences, 37(1), 130–137.

Varian-Ramos, C. W., Swaddle, J. P., & Cristol, D. A. (2014). Mercury reduces avian reproductive success and imposes selection : an experimental study with adult- or lifetime- exposure in Zebra Finch. PLoS ONE, 9(4), e95674. https://doi.org/10.1371/journal.pone.0095674

Vietz, G. J., Walsh, C. J., & Fletcher, T. D. (2015). Urban hydrogeomorphology and the urban stream syndrome: treating the symptoms and causes of geomorphic change. Progress in Physical Geography, 40(3), 480–492. https://doi.org/10.1177/0309133315605048

Violin, C. R., Cada, P., Sudduth, E. B., Hassett, B. A., Penrose, D. L., & Bernhardt, E. S. (2011). Effects of urbanization and urban stream restoration on the physical and biological structure of stream ecosystems. Ecological Applications, 21(6), 1932–1949. https://doi.org/10.1890/10-1551.1

Visser, A. M. E., Noordwijk, A. J. Van, Tinbergen, J. M., Lessells, C. M., Visser, M. E., Noordwijk, A. J. Van, … Lessells, C. M. (1998). Warmer springs lead to mistimed reproduction in Great Tits (Parus major). Proceedings of the Royal Society B-Biological Sciences, 265(1408), 1867–1870.

Wahl, C. M., Neils, A., & Hooper, D. (2013). Impacts of land use at the catchment scale constrain the habitat benefits of stream riparian buffers. Freshwater Biology, 58(11), 2310– 2324. https://doi.org/10.1111/fwb.12211

Wallace, J. B., Eggert, S. L., Meyer, J. L., & Webster, J. R. (1997). Multiple trophic levels of a forest stream linked to terrestrial litter inputs. Science, 277(5322), 102–104. https://doi.org/10.1126/science.277.5322.102

Walsh, C. J., Roy, A. H., Feminella, J. W., Cottingham, P. D., Groffman, P. M., & Morgan, R. P. (2005). The urban stream syndrome: current knowledge and the search for a cure. Journal

162

of the North American Benthological Society, 24(3), 706–723.

Walsh, C. J., Sharpe, A. K., Breen, P. F., & Sonneman, J. A. (2001). Effects of urbanization on streams of the Melbourne region, Victoria, Australia. I. Benthic macroinvertebrate communities. Freshwater Biology, 46(4), 535–551.

Walsh, C. J., Waller, K. A., Gehling, J., & Mac Nally, R. (2007). Riverine invertebrate assemblages are degraded more by catchment urbanisation than by riparian deforestation. Freshwater Biology, 52(3), 574–587. https://doi.org/10.1111/j.1365-2427.2006.01706.x

Walters, D. M., Fritz, K. M., & Otter, R. R. (2008). The dark side of subsidies: adult stream insects export organic contaminants to riparian predators. Ecological Applications, 18(8), 1835–1841.

Wang, L., Robertson, D. M., & Garrison, P. J. (2007). Linkages between nutrients and assemblages of macroinvertebrates and fish in wadeable streams: Implication to nutrient criteria development. Environmental Management, 39(2), 194–212. https://doi.org/10.1007/s00267-006-0135-8

Wenger, S. J., Roy, A. H., Jackson, C. R., Bernhardt, E. S., Carter, T. L., Filoso, S., … Walsh, C. J. (2009). Twenty-six key research questions in urban stream ecology: an assessment of the state of the science. Journal of the North American Benthological Society, 28(4), 1080– 1098. https://doi.org/10.1899/08-186.1

Whitaker, D. M., Carroll, A. L., & Montevecchi, W. A. (2000). Elevated numbers of flying insects and insectivorous birds in riparian buffer strips. Canadian Journal of Zoology, 78(5), 740–747. https://doi.org/10.1139/z99-254

Winkler, D. W., & Allen, P. E. (1996). The seasonal decline in Tree Swallow clutch size: physiological constraint or strategic adjustment? Ecology, 77(3), 922–932.

Winkler, D. W., Dunn, P. O., & Mcculloch, C. E. (2002). Predicting the effects of climate change on avian life-history traits. Proceedings of the National Academy of Sciences of the United States of America, 99(21), 13595–13599.

Winkler, D. W., Luo, M. K., & Rakhimberdiev, E. (2013). Temperature effects on food supply and chick mortality in tree swallows (Tachycineta bicolor). Oecologia, 173(1), 129–138. https://doi.org/10.1007/s00442-013-2605-z

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Table 3.1. Results from linear mixed-effects models with fixed (year, land use [urban or protected], and year × land use) and random (site, nestbox, site × nestbox). ** indicates a significant (p < 0.05) effect. * indicates evidence of a trend; i.e., 0.5 ≥ p < 0.10. Marginal R² = variation explained by fixed effects alone, while conditional R² = variation explained by both fixed and random effects. TP = trophic position. ADE = aquatically derived energy (i.e., nutritional subsidies originating from algae/periphyton).

Linear Mixed Fixed Effects Random Effects Models Year Land Use Year × Land Use Site Site × Nestbox Residuals df F p df F p df F p variance sd variance sd variance sd

ADE - adult 41.11 0.72 0.490 5.61 0.55 0.490 41.11 0.01 0.990 0.002 0.045 n/a n/a 0.003 0.054

R 2 marginal: 0.07 R 2 conditional: 0.45

ADE - nestling 240.31 7.06 0.001** 5.24 0.36 0.570 236.46 1.3 0.260 0.003 0.053 0.001 0.032 0.003 0.052 R 2 marginal: 0.07 R 2 conditional: 0.62

inverts early - adult 50.63 4.23 0.010** 5.48 0.9 0.380 50.46 2 0.150 0.012 0.110 n/a n/a 0.013 0.114

R 2 marginal: 0.15 R 2 conditional: 0.56

inverts early - nestling 292.47 16.26 <0.001** 5.12 1.29 0.310 293.01 18.35 <0.001** 0.010 0.099 0.001 0.037 0.074 0.086

2 0.23 2 0.69 R marginal R conditional:

inverts late - adult 49.38 0.2 0.820 5.31 0.09 0.770 49.38 2.24 0.120 0.015 0.121 n/a n/a 0.011 0.105

R 2 marginal: 0.06 R 2 conditional: 0.60

inverts late - nestling 272.11 2.06 0.130 5.2 0.25 0.640 272.11 1.47 0.230 0.006 0.078 0.003 0.056 0.008 0.089 R 2 marginal: 0.04 R 2 conditional: 0.56

TP - adult 41.57 0.18 0.830 5.95 10.64 0.020** 41.57 1.89 0.160 0.034 0.185 n/a n/a 0.097 0.311

R 2 marginal: 0.48 R 2 conditional: 0.61

TP - nestling 233.17 133.42 <0.001** 5.06 0.72 0.430 242.82 2.81 0.100* 0.435 0.660 0.056 0.237 0.043 0.207

2 0.14 2 0.93 R marginal: R conditional: 164

Figure 3.1 Tree Swallow study sites (i.e., reaches) in urban and natural/protected areas in the greater Columbus, Ohio area. Source: Homer, et al., 2015 and QGIS Dev Team, 2017.

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B A

A A

Figure 3.2 Annual means from 2015-2017 by land use (i.e., natural/protected or urban) for Tree Swallow trophic position of: (a) adults (LMM: p = 0.020) and (b) nestlings at ~13 days (LMM: p = 0.430). Error bars indicate +/- 1 SE. Different letters A, B indicate significant pairwise differences.

166

A A

A

A

Figure 3.3 Annual means from 2015-2017 by land use (i.e., natural/protected or urban) for Tree Swallow nutritional reliance on aquatically derived energy

(e.g., originating from algae/periphyton) for (a) adults (LMM: p = 0.490) and

(b) nestlings at ~13 days (LMM: p = 0.570). Error bars indicate +/- 1 SE.

Different letters A, B indicate significant pairwise differences.

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Figure 3.4 Relationships between the Urban Stream Index (USI) for study sites and Tree

Swallow trophic position for (a) 2015, (b) 2016, and (c) 2017. Separate multiple regression models with year as a categorical variable were developed for adults (R2 = 0.23, F = 6.04, p =

0.001) and nestlings (R2 = 0.22, F = 24.75, p < 0.001). For the regression lines, gold = adult

swallows and green = nestlings at ~13 days.

168

Figure 3.5 Relationships between Urban Stream Index and Tree Swallow nutritional reliance on emergent aquatic insects (vs. terrestrial flying insects) for (a) 2014, (b) 2015, and (c) 2016, and (d) 2017. Separate multiple regression models with year as a categorical variable were developed for adults (R2 = 0.10, 2 F = 2.77, p = 0.036) and nestlings (R = 0.23, F = 23.40, p < 0.001). For the regression lines, pink = adult swallows and blue = nestlings at ~13 days.

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Figure 3.6 Composition of emergent aquatic and terrestrial flying insects (by percentage) in Tree Swallows diets across all study sites, 2014-2017. Sites are organized according to their Urban Stream Index (USI), with the lowest (i.e., least urbanized) on the left, and highest on the right. Note that positions of each plot are laterally equidistant from one another for display purposes, and do not necessarily reflect the magnitude of the USI. Blue = emergent aquatic insects, brown = terrestrial insects. Results for adult swallows are shown on the left side of each plot, nestlings on the right.

170

Figure 3.7 Tree Swallow nutritional reliance on aquatically derived energy (e.g., originating from algae/periphyton) across all study sites, 2015-2017. Sites are organized according to their Urban Stream Index (USI), with the lowest (i.e., least urbanized) on the left, and highest on the right. Note that positions of each plot are laterally equidistant from one another for display purposes, and do not necessarily reflect the magnitude of the USI. Results for adult swallows are shown on the left side of each plot, nestlings on the right.

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a b

Figure 3.8 Relationships between Tree Swallow nutritional reliance on emergent aquatic insects and reliance on aquatically derived energy (e.g., originating from algae/periphyton) for (a) early- season insects, (b) late-season insects. Separate linear regression models were developed for early-season insects and adult swallows (R2 = 0.01, F = 0.76, p = 0.390) early-season insects and nestlings (R2 = 0.01, F = 3.87, p = 0.050), late-season insects and adult swallows (R2 = 0.01, F = 1.03, p = 0.318), and late-season insects and nestlings (R2 = 0.01, F = 3.41, p = 0.066). For the regression lines, pink = adult swallows and blue = nestlings at ~13 days.

172

Complete References

Adams, T. S., & Sterner, R. W. C. N.-289. (2000). The effects of dietary nitrogen on trophic level 15N enrichment. Limnology and Oceanography, 45(3), 601–607.

Alberts, J. M., Sullivan, S. M. P., & Kautza, A. (2013). Riparian swallows as integrators of landscape change in a multiuse river system: Implications for aquatic-to-terrestrial transfers of contaminants. Science of the Total Environment, 463–464, 42–50. https://doi.org/10.1016/j.scitotenv.2013.05.065

Allan, J. D. (2004). Influence of land use and landscape setting on the ecological status of rivers. Limnetica, 23(3–4), 187–198. https://doi.org/10.1146/annurev.ecolsys.35.120202.110122

Allan, J. D., Erickson, D. L., & Fay, J. (1997). The influence of catchment land use on stream integrity across multiple spatial scales. Freshwater Biology, 37(1), 149–161.

Allan, J. D., & Flecker, A. S. (1993). Biodiversity conservation in running waters. BioScience, 43(1), 32–43.

Anderson, C., & Cabana, G. (2007). Estimating the trophic position of aquatic consumers in river food webs using stable nitrogen isotopes. Journal of the North American Benthological Society, 26(2), 273–285. https://doi.org/10.1899/0887- 3593(2007)26[273:ETTPOA]2.0.CO;2

Andrew, S. C., Hurley, L. L., Mariette, M. M., & Griffith, S. C. (2017). Higher temperatures during development reduce body size in the zebra finch in the laboratory and in the wild. Journal of Evolutionary Biology, 30(12), 2156–2164. https://doi.org/10.1111/jeb.13181

Ardia, D. R. (2013). The effects of nestbox thermal environment on fledging success and haematocrit in Tree Swallows. Avian Biology Research, 6(2), 99–103. https://doi.org/10.3184/175815513X13609528031394

Ardia, D. R., Cooper, C. B., & Dhondt, A. (2006). Warm temperatures lead to early onset of incubation, shorter incubation periods and greater hatching asynchrony in Tree Swallows Tachycineta bicolor at the extremes of their range. Journal of Avian Biology, 37(2), 137– 142.

Ardia, D. R., Wasson, M. F., & Winkler, D. W. (2006). Individual quality and food availability determine yolk and egg mass and egg composition in tree swallows Tachycineta bicolor. Journal of Avian Biology, 37(3), 252–260.

Arnold, C. L., Boison, P. J., & Patton, P. C. (1982). Sawmill Brook: an example of rapid geomorphic change related to urbanization. The Journal of Geology, 90(2), 155–166.

Arnold, C. L., & Gibbon, C. J. (1996). Impervious surface coverage: The emergence of a key

173

environmental indicator. Journal of the American Planning Association, 62(2), 243–258.

Aubin, A., Bourassa, J. P., & Pellisier, M. (1973). An effective emergence trap for the capture of mosquitoes. Mosquito News, 33(2), 251–252.

Bartoń, K. (2018). MuMIn. Retrieved from https://cran.r-project.org/package=MuMIn

Baxter, C. V, Fausch, K. D., & Saunders, W. C. (2005). Tangled webs: Reciprocal flows of invertebrate prey link streams and riparian zones. Freshwater Biology, 50(2), 201–220. https://doi.org/10.1111/j.1365-2427.2004.01328.x

Bearhop, S., Thompson, D. R., Waldron, S., Russell, I. C., Alexander, G., & Furness, R. W. (1999). Stable isotopes indicate the extent of freshwater feeding by cormorants Phalacrocorax carbo shot at inland fisheries in England. Journal of Applied Ecology, 36(1), 75–84. https://doi.org/10.1046/j.1365-2664.1999.00378.x

Bearhop, S., Waldron, S., Votier, S. C., & Furness, R. W. (2002). Factors That influence assimilation rates and fractionation of nitrogen and carbon stable isotopes in avian blood and feathers. Physiological and Biochemical Zoology, 75(5), 451–458.

Beck, M. L., Hopkins, W. A., & Jackson, B. P. (2014). Variation in riparian consumer diet composition and differential bioaccumulation by prey influence the risk of exposure to elements from a recently remediated fly ash spill. Environmental Toxicology and Chemistry, 33(11), 2595–2608. https://doi.org/10.1002/etc.2719

Becker, M. E., & Weisberg, P. J. (2015). Synergistic effects of spring temperatures and land cover on nest survival of urban birds. The Condor, 117(1), 18–30. https://doi.org/10.1650/CONDOR-14-1.1

Benke, A., Wallace, J., & Harrison, J. (2001). Food web quantification using secondary production analysis: predaceous …. Freshwater …, 329–346. https://doi.org/10.1046/j.1365-2427.2001.00680.x

Bennett, P. M., & Hobson, K. A. (2009). Trophic structure of a boreal forest arthropod community revealed by stable isotope (d13C, d15N) analyses. Entomological Science, 12(1), 17–24. https://doi.org/10.1111/j.1479-8298.2009.00308.x

Blair, R. B. (1996). Land use and avian species diversity along an urban gradient. Ecological Applications, 6(2), 506–519.

Boening, D. W. (2000). Ecological effects, transport, and fate of mercury: a general review. Chemosphere, 40(12), 1335–1351.

Bohning-Gaese, K., Taper, M. L., & Brown, J. H. (1993). Are declines in North American insectivorous songbirds due to Causes on the breeding range? Conservation Biology, 7(1), 76–86. Retrieved from http://www.jstor.org/stable/2386644%0Ahttp://about.jstor.org/terms 174

Booth, D. B., & Jackson, C. R. (1998). Urbanization of aquatic systems: degradation thresholds, stormwater detection, and the limits of mitigation. Journal of the American Water Resources Association, 33(5), 1077–1090.

Both, C., Van Turnhout, C. A. M., Bijlsma, R. G., Siepel, H., Van Strien, A. J., & Foppen, R. P. B. (2010). Avian population consequences of climate change are most severe for long- distance migrants in seasonal habitats. Proceedings of the Royal Society B-Biological Sciences, 277(1685), 1259–1266. https://doi.org/10.1098/rspb.2009.1525

Bourret, A., Bélisle, M., Pelletier, F., & Garant, D. (2015). Multidimensional environmental influences on timing of breeding in a tree swallow population facing climate change. Evolutionary Applications, 8(10), 933–944. https://doi.org/10.1111/eva.12315

Brasso, R. L., & Cristol, D. A. (2008). Effects of mercury exposure on the reproductive success of Tree Swallows (Tachycineta bicolor). Ecotoxicology, 17(2), 133–141. https://doi.org/10.1007/s10646-007-0163-z

Brigham, R. M. (1989). Roost and nest sites of Common Nighthawks: are gravel roofs important? The Condor, 91, 122–124.

Brown, L. R., Cuffney, T. F., Coles, J. F., Fitzpatrick, F., McMahon, G., Steuer, J., … May, J. T. (2009). Urban streams across the USA: lessons learned from studies in 9 metropolitan areas. Journal of the North American Benthological Society, 28(4), 1051–1069. https://doi.org/10.1899/08-153.1

Burdon, F. J., & Harding, J. S. (2008). The linkage between riparian predators and aquatic insects across a stream-resource spectrum. Freshwater Biology, 53(2), 330–346. https://doi.org/10.1111/j.1365-2427.2007.01897.x

Burger, J., & Gochfeld, M. (1997). Risk, mercury levels, and birds: relating adverse laboratory effects to field biomonitoring. Environmental Research, 172(2), 160–172.

Butler, R. W. (1988). Population dynamics and migration routes of Tree Swallows, Tachycineta bicolor, in North America. Journal of Field Ornithology, 59(4), 395–402.

Cabana, G., & Rasmussen, J. (1996). Comparison of aquatic food chains using nitrogen isotopes. Proceedings of the National Academy of Sciences of the United States of America, 93(20), 10844–10847.

Caquet, T. (2006). Use of carbon and nitrogen stable isotope ratios to assess the effects of environmental contaminants on aquatic food webs. Environmental Pollution, 141(1), 54–59. https://doi.org/10.1016/j.envpol.2005.08.029

Caut, S., Angulo, E., & Courchamp, F. (2008). Caution on isotopic model use for analyses of consumer diet. Canadian Journal of Zoology, 86(5), 438–445. https://doi.org/10.1139/Z08-

175

012

Caut, S., Angulo, E., & Courchamp, F. (2009). Variation in discrimination factors (Δ15N and Δ13C): The effect of diet isotopic values and applications for diet reconstruction. Journal of Applied Ecology, 46(2), 443–453. https://doi.org/10.1111/j.1365-2664.2009.01620.x

Chalmers, A. T., Krabbenhoft, D. P., Metre, P. C. Van, & Nilles, M. A. (2014). Effects of urbanization on mercury deposition and accumulation in New England. Environmental Pollution, 192, 104–112. https://doi.org/10.1016/j.envpol.2014.05.003

Chamberlain, D., Hatchwell, B., & Gaston, K. J. (2009). Avian productivity in urban landscapes: a review and meta-analysis. Ibis, 151(1), 1–18. https://doi.org/10.1111/j.1474- 919X.2008.00899.x

Chislock, M. F., Doster, E., Zitomer, R. A., & Wilson, A. E. (2013). Eutrophication: causes, consequences, and controls in aquatic ecosystems. Nature Education Knowledge, 4(4), 10. Retrieved from http://www.wilsonlab.com/publications/2013_NE_Chislock_et_al.pdf

Collier, K. J., Bury, S., & Gibbs, M. (2002). A stable isotope study of linkages between stream and terrestrial food webs through spider predation. Freshwater Biology, 47(9), 1651–1659. https://doi.org/10.1046/j.1365-2427.2002.00903.x

Compin, A., & Céréghino, R. (2003). Sensitivity of aquatic insect species richness to disturbance in the Adour–Garonne stream system (France). Ecological Indicators, 3(2), 135–142. https://doi.org/10.1016/S1470-160X(03)00016-5

Compson, Z. G., Adams, K. J., Edwards, J. A., Maestas, J. M., Whitham, T. G., & Marks, J. C. (2013). Leaf litter quality affects aquatic insect emergence: contrasting patterns from two foundation trees. Oecologia, 173(2), 507–519. https://doi.org/10.1007/s00442-013-2643-6

Cox, A. R., Robertson, R. J., Fedy, B. C., Rendell, W. B., & Bonier, F. (2018). Demographic drivers of local population decline in Tree Swallows (Tachycineta bicolor). The Condor, 120(4), 842–851. https://doi.org/10.1650/CONDOR-18-42.1

Crick, H. Q. P. (2004). The impact of climate change on birds. Ibis, 146(Suppl. 1), 48–56.

Cristol, D., Brasso, R., Monroe, A., Condon, R., Fovargue, A., Friedman, S., … White, A. (2008). The movement of aquatic mercury through terrestrial food webs. Science, 320(5874), 335.

Crooks, K. R., Suarez, A. V., & Bolger, D. T. (2004). Avian assemblages along a gradient of urbanization in a highly fragmented landscape. Biological Conservation, 115(3), 451–462. https://doi.org/10.1016/S0006-3207(03)00162-9

Cummins, K. W., & Klug, M. J. (1979). Feeding ecology of stream invertebrates. Annual Review of Ecology and Systematics, 10(1), 147–172. 176

https://doi.org/10.1146/annurev.es.10.110179.001051

Cunningham, S. J., Martin, R. O., Hojem, C. L., & Hockey, P. A. R. (2013). Temperatures in excess of critical thresholds threaten nestling growth and survival in A rapidly-warming arid savanna: a study of Common Fiscals. PLoS ONE, 8(9), 1–10. https://doi.org/10.1371/journal.pone.0074613

Custer, C. M., Custer, T. W., Dummer, P. M., Munney, K. L., Midwest, U., Sciences, E., … Office, F. (2003). Exposure and effects of chemical contaminants on Tree Swallows nesting along the Housatonic River, Berkshire County, Massachusetts, USA, 1998 – 2000. Environmental Toxicology and Chemistry, 22(7), 1605–1621.

DeNiro, M. J., & Epstein, S. (1978). Influence of diet on the distribution of nitrogen isotopes in animals. Geochimica et Cosmochimica Acta, 42(3), 495–506. https://doi.org/10.1016/0016- 7037(81)90244-1

Dodds, W. K., & Smith, V. H. (2016). Nitrogen, phosphorus, and eutrophication in streams. Inland Waters, 6(2), 155–164. https://doi.org/10.5268/IW-6.2.909

Dods, P. L., Birmingham, E. M., Williams, T. D., Ikonomou, M. G., Bennie, D. T., & Elliott, J. E. (2005). Reproductive success and contaminants in tree swallows (Tachycineta bicolor) breeding at a wastewater treatment plant. Environmental Toxicology and Chemistry, 24(12), 3106–3112. https://doi.org/10.1897/04-547R.1

Driscoll, C. T., Han, Y., Chen, C. Y., Evers, D. C., Lambert, K. F., Holsen, T. M., … Munson, R. K. (2007). Mercury contamination in forest and freshwater ecosystems in the Northeastern United States. BioScience, 57(1), 17–28.

Dunn, P., & Hannon, S. J. (1992). Effects of food abundance and male parental care on reproductive success and monogamy in Tree Swallows. The Auk, 109(3), 488–499.

Dunn, P. O., & Winkler, D. W. (1999). Climate change has affected the breeding date of tree swallows throughout North America. Proceedings of the Royal Society B-Biological Sciences, 266(1437), 2487–2490.

Durance, I., & Ormerod, S. J. (2007). Climate change effects on upland stream macroinvertebrates over a 25-year period. Global Change Biology, 13(5), 942–957. https://doi.org/10.1111/j.1365-2486.2007.01340.x

Eeva, T., Veistola, S., & Lehikoinen, E. (2000). Timing of breeding in subarctic passerines in relation to food availability. Canadian Journal of Zoology, 78(1), 67–78. https://doi.org/10.1139/cjz-78-1-67

English, P. A., Green, D. J., & Nocera, J. J. (2018). Stable isotopes from museum specimens may provide evidence of long-term change in the trophic ecology of a migratory aerial

177

insectivore. Frontiers in Ecology and Evolution, 6(February), 14. https://doi.org/10.3389/FEVO.2018.00014

Environment Canada. (2007). Chimney swift (Chaetura pelagica) COSEWIC assessment and status report. Ottawa.

Environment Canada. (2012). The State of Canada’s Birds. Ottawa.

Evers, D. C., Burgess, N. M., Champoux, L., Hoskins, B., Major, A., Goodale, W. M., … Daigle, T. (2005). Patterns and interpretation of mercury exposure in freshwater avian communities in northeastern North America. Ecotoxicology, 14(1–2), 193–221.

Fausch, K. D., Baxter, C. V., & Murakami, M. (2010). Multiple stressors in north temperate streams: lessons from linked forest-stream ecosystems in northern Japan. Freshwater Biology, 55(SUPPL. 1), 120–134. https://doi.org/10.1111/j.1365-2427.2009.02378.x

Fimreite, N. (1974). Mercury contamination of aquatic birds in Northwestern Ontario. The Journal of Wildlife Management, 38(1), 120–131.

Finlay, J. C. (2001). Stable carbon isotope ratios of river biota: implications for energy flow in lotic food webs. Ecology, 82(4), 1052–1064.

Fraser, K. C., Stutchbury, B. J. M., Silverio, C., Kramer, P. M., Barrow, J., Newstead, D., … Tautin, J. (2012). Continent-wide tracking to determine migratory connectivity and tropical habitat associations of a declining aerial insectivore. Proceedings of the Royal Society B- Biological Sciences, 279(1749), 4901–4906. https://doi.org/10.1098/rspb.2012.2207

Freeman, P. L., & Schorr, M. S. (2004). Influence of watershed urbanization on fine sediment and macroinvertebrate assemblage characteristics in Tennessee ridge and valley streams. Journal of Freshwater Ecology, 19(3), 353–362. https://doi.org/10.1080/02705060.2004.9664908

Fry, B. (2006). Stable isotope ecology. Stable isotope ecology. New York: Springer Science+Business Media. https://doi.org/10.1016/j.dsr2.2015.11.009

Gage, M. S., Spivak, A., & Paradise, C. J. (2004). Effects of land use and disturbance on benthic insects in headwater streams drainging small watersheds. Southeastern Naturalist, 3(2), 345–358.

Gentes, M., Waldner, C., Papp, Z., & Smits, J. E. G. (2006). Effects of oil sands tailings compounds and harsh weather on mortality rates, growth and detoxification efforts in nestling Tree Swallows (Tachycineta bicolor). Environmental Pollution, 142(1), 24–33. https://doi.org/10.1016/j.envpol.2005.09.013

Gerald, M., & Tebaldi, C. (2004). More intense, more frequent, and longer-lasting heat waves in the 21st Century. Science, 305(August), 994–997. https://doi.org/10.1126/science.1098704 178

Ghilain, A., & Bélisle, M. (2008). Breeding success of Tree Swallows along a gradient of agricultural intensification. Ecological Applications, 18(5), 1140–1154. https://doi.org/10.1890/07-1107.1

Golondrinas de las Americas. (2011). Nest box design.

Grable, J. L., & Harden, C. P. (2006). Geomorphic response of an Appalachian Valley and Ridge stream to urbanization. Earth Surface Processes and Landforms, 31(13), 1707–1720. https://doi.org/10.1002/esp

Gray, L. J. (1993). Response of insectivorous birds to emerging aquatic insects in riparian habitats of a tallgrass prairie stream. American Midland Naturalist, 129(2), 288–300.

Gurtz, M. E., & Wallace, J. B. (1984). Substrate-mediated response of stream invertebrates to disturbance. Ecology, 65(5), 1556–1569.

Hagar, J. C., Li, J., Sobota, J., & Jenkins, S. (2012). Arthropod prey for riparian associated birds in headwater forests of the Oregon Coast Range. Forest Ecology and Management, 285, 213–226. https://doi.org/10.1016/j.foreco.2012.08.026

Hallinger, K. K., & Cristol, D. A. (2011). The role of weather in mediating the effect of mercury exposure on reproductive success in Tree Swallows. Ecotoxicology, 20(6), 1368–1377. https://doi.org/10.1007/s10646-011-0694-1

Harper, M. P. H., & Peckarsky, B. L. (2006). Emergence cues of a mayfly in a high-altitude stream ecosystem: potential response to climate change. Ecological Applications, 16(2), 612–621.

Harris, D. J. (2009). Clinical tests. Handbook of Avian Medicine (Second Edi). Elsevier Limited. Retrieved from http://dx.doi.org/

Harris, G. P., & Baxter, G. (1996). Interannual variability in phytoplankton biomass and species composition in a subtropical reservoir. Freshwater Biology, 35(3), 545–560. https://doi.org/10.1111/j.1365-2427.1996.tb01768.x

Harvey, C. J., & Kitchell, J. F. (2000). A stable isotope evaluation of the structure and spatial heterogeneity of a Lake Superior food web. Canadian Journal of Fisheries and Aquatic Sciences, 57(7), 1395–1403.

Hawkins, C. P., Hogue, J. N., Decker, L. M., & Feminella, J. W. (1997). Channel morphology, water temperature, and assemblage structure of stream insects. Journal of the North American Benthological Society, 16(4), 728–749.

Hawley, D. M., Hallinger, K. K., & Cristol, D. A. (2009). Compromised immune competence in free-living tree swallows exposed to mercury. Ecotoxicology, 18(5), 499–503. https://doi.org/10.1007/s10646-009-0307-4 179

Heinrich, K. K., Whiles, M. R., & Roy, C. (2014). Cascading ecological responses to an in- stream restoration project in a midwestern river. Restoration Ecology, 22(1), 72–80. https://doi.org/10.1111/rec.12026

Helms, B. S., Schoonover, J. E., & Feminella, J. W. (2009). Seasonal variability of landuse impacts on macroinvertebrate assemblages in streams of western Georgia, USA. Journal of the North American Benthological Society, 28(4), 991–1006. https://doi.org/10.1899/08- 162.1

Hendrickx, F., Maelfait, J., Wingerden, W. Van, Schweiger, O., Speelmans, M., Aviron, S., … Bugter, R. (2007). How landscape structure, land‐use intensity and habitat diversity affect components of total arthropod diversity in agricultural landscapes. Journal of Applied Ecology, 44(2), 340–351.

Hespenheide, H. A. (1971). Food preference and the extent of overlap in some insectivorous birds, with special reference to the Tyrannidae. Ibis, 113(1), 59–72. https://doi.org/10.1111/j.1474-919X.1971.tb05123.x

Hession, W. C., Pizzuto, J. E., Johnson, T. E., & Horwitz, R. J. (2003). Influence of bank vegetation on channel morphology in rural and urban watersheds. Geology, 31(2), 147–150. https://doi.org/10.1130/0091-7613(2003)031<0147:IOBVOC>2.0.CO;2

Homer, C. G., Dewitz, J. A., Yang, L., Jin, S., Danielson, P., Xian, G., … Megown, K. (2015). Completion of the 2011 National Land Cover Database for the conterminous United States- representing a decade of land cover change information. Photogrammetric Engineering and Remote Sensing, 81(5), 345–354.

Hughes, L. (2000). Biological consequences of global warming: is the signal already apparent? Trends in Ecology & Evolution, 15(2), 56–61. https://doi.org/10.1016/S0169- 5347(99)01764-4

Hussell, D. (2003). Climate change, spring temperatures, and timing of breeding of Tree Swallows (Tachycineta bicolor) in southern Ontario. The Auk, 120(3), 607–618.

Hussell, D., & Quinney, T. E. (1987). Food abundance and clutch size of Tree Swallows Tachycineta bicolor. Ibis, 129(1), 243–258. https://doi.org/10.1111/fwb.12476

Iwata, T., Nakano, S., & Murakami, M. (2003). Stream meanders increase insectivorous bird abundance in riparian deciduous forests. Ecography, 26(September 2002), 325–337. https://doi.org/10.1034/j.1600-0587.2003.03355.x

Jackson, A. K., Evers, D. C., Etterson, M. A., Condon, A. M., Sarah, B., Detweiler, J., … Thryothorus, D. (2011). Mercury exposure affects the reproductive success of a free-living terrestrial songbird, the Carolina Wren (Thryothorus ludovicianus). The Auk, 128(4), 759– 769. 180

Jackson, J. K., & Fisher, S. G. (1986). Secondary production, emergence, and export of aquatic insects of a Sonoran Desert stream. Ecology, 67(3), 629–638.

Johnson, N. F., & Triplehorn, C. A. (2005). c (7th ed.). Boston: Brooks/Cole.

Johnson, R. C., Jin, H., Carreiro, M. M., & Jack, J. D. (2013). Macroinvertebrate community structure, secondary production and trophic-level dynamics in urban streams affected by non-point-source pollution. Freshwater Biology, 58(5), 843–857. https://doi.org/10.1111/fwb.12090

Jones, J. (2003). Tree swallows (Tachycineta bicolor): A new model organism? The Auk, 120(3), 591–599.

Jonsson, M., Hedström, P., Stenroth, K., Hotchkiss, E. R., Vasconcelos, F. R., Karlsson, J., & Byström, P. (2015). Climate change modifies the size structure of assemblages of emerging aquatic insects. Freshwater Biology, 60(1), 78–88. https://doi.org/10.1111/fwb.12468

Jonsson, M., Strasevicius, D., & Malmqvist, B. (2012). Influences of river regulation and environmental variables on upland bird assemblages in northern Sweden. Ecological Research, 27(5), 945–954. https://doi.org/10.1007/s11284-012-0974-0

Karagicheva, J., Liebers, M., Rakhimberdiev, E., Hallinger, K. K., Saveliev, A., & Winkler, D. W. (2016). Differences in size between first and replacement clutches match the seasonal decline in single clutches in Tree Swallows Tachycineta bicolor. Ibis, 158(3), 607–613.

Kautza, A., & Sullivan, S. M. P. (2015). Shifts in reciprocal river-riparian arthropod fluxes along an urban-rural landscape gradient. Freshwater Biology, 60(10), 2156–2168. https://doi.org/10.1111/fwb.12642

Kautza, A., & Sullivan, S. M. P. (2016a). Anthropogenic and natural determinants of fish food- chain length in a midsize river system. Freshwater Science, 35(3), 895–908. https://doi.org/10.1086/685932

Kautza, A., & Sullivan, S. M. P. (2016b). The energetic contributions of aquatic primary producers to terrestrial food webs in a mid-size river system. Ecology, 97(3), 694–705. https://doi.org/10.1890/15-1095.1

Kenward, A., Yawitz, D., Sanford, T., & Wang, R. (2014). Summer in the city: Hot and getting hotter. Princeton.

Klein, R. D. (1980). Urbanization and stream quality impairment. Water Resources Bulletin, 15(4), 948–963.

Kondolf, G. M. (1995). Five elements for effective evaluation of stream restoration. Restoration Ecology. https://doi.org/10.1111/j.1526-100X.1995.tb00086.x

181

Kuznetsova, A., Brockhoff, P. B., Haubo, R., & Christensen, B. (2017). lmerTest. Retrieved from https://github.com/runehaubo/lmerTestR

Labocha, M. K., & Hayes, J. P. (2012). Morphometric indices of body condition in birds: a review. Journal of Ornithology, 153(1), 1–22. https://doi.org/10.1007/s10336-011-0706-1

Langham, G., Schuetz, J., Soykan, C., Wilsey, C., Auer, T., LeBaron, G., … Distler, T. (2014). Audubon’s Birds and Climate Change Report. New York.

Layman, C. A., Araujo, M. S., Boucek, R., Hammerschlag-Peyer, C. M., Harrison, E., Jud, Z. R., … Bearhop, S. (2012). Applying stable isotopes to examine food-web structure: An overview of analytical tools. Biological Reviews, 87(3), 545–562. https://doi.org/10.1111/j.1469-185X.2011.00208.x

Learner, M. A., & Potter, D. W. B. (1974). The seasonal periodicity of emergence of insects from two Ponds in Hertfordshire, England, with special reference to the Chironomidae (Diptera: Nematocera). Hydrobiologia, 44(4), 495–510.

Leffelaar, D., & Robertson, R. J. (1986). Equality of feeding roles and the maintenance of monogamy in Tree Swallows. Behavioral Ecology and Sociobiology, 18(3), 199–206.

Lenat, D. R. (1988). Water quality assessment of streams using a qualitative collection method for benthic macroinvertebrates. Journal of the North American Benthological Society, 7(3), 222–233. https://doi.org/10.2307/1467422

Lenat, D. R., & Crawford, J. K. (1994). Effect of land use on water quality and aquatic biota of three North Carolina Piedmont streams. Hydrobiologia, 294(3), 185–199. https://doi.org/10.3923/ijb.2012.181.191

Li, Y., & Cai, Y. (2013). Progress in the study of mercury methylation and demethylation in aquatic environments. Chinese Science Bulletin, 58(2), 177–185.

Lifjeld, J. T., Dunn, P. O., & Whittingham, L. A. (2002). Short-term fluctuations in cellular immunity of tree swallows feeding nestlings. Oecologia, 130(2), 185–190. https://doi.org/10.1007/s004420100798

Lill, A. (2011). Sources of variation in blood glucose concentrations of free-living birds. Avian Biology Research, 4(2), 78–87. https://doi.org/10.3184/175815511X13073729328092

Lussier, S. M., da Silva, S. N., Charpentier, M., Heltshe, J. F., Cormier, S. M., Klemm, D. J., … Jayaraman, S. (2008). The influence of suburban land use on habitat and biotic integrity of coastal Rhode Island streams. Environmental Monitoring and Assessment, 139(1–3), 119– 136. https://doi.org/10.1007/s10661-007-9820-1

Lussier, S. M., Enser, R. W., Dasilva, S. N., & Charpentier, M. (2006). Effects of habitat disturbance from residential development on breeding bird communities in riparian 182

corridors. Environmental Management, 38(3), 504–521. https://doi.org/10.1007/s00267- 005-0088-3

Lutz, M. A., Brigham, M. E., Krabbenhoft, D. P., Aiken, G. R., & Orem, W. H. (2009). methylmercury production and bed sediment-pore water partitioning. Environmental Science & Technology, 43(8), 2726–2732.

MacHunter, J., Wright, W., Loyn, R., & Rayment, P. (2006). Bird declines over 22 years in forest remnants in southeastern Australia: Evidence of faunal relaxation? Canadian Journal of Forest Research, 36(11), 2756–2768. https://doi.org/10.1139/x06-159

Macivor, J. S., & Lundholm, J. (2011). Insect species composition and diversity on intensive green roofs and adjacent level-ground habitats. Urban Ecosystems, 14(2), 225–241. https://doi.org/10.1007/s11252-010-0149-0

Marczak, L. B., Sakamaki, T., Turvey, S. L., Deguise, I., Wood, S. L. R., & Richardson, J. S. J. S. (2010). Are forested buffers an effecive conservation strategy for riparian fauna? An assessment using meta-analysis. Ecological Applications, 20(1), 126–134. https://doi.org/10.1890/08-2064.1

McArthur, S. L., McKellar, A. E., Flood, N. J., & Reudink, M. W. (2017). Local weather and regional climate influence breeding dynamics of Mountain Bluebirds (Sialia currucoides) and Tree Swallows (Tachycineta bicolor): a 35-year study. Canadian Journal of Zoology, 95(4), 271–277.

McCarty, J. P. (1997). Aquatic community characteristics influence the foraging patterns of Tree Swallows. The Condor, 99(1), 210–213. https://doi.org/10.2307/1370241

McCarty, J. P. (2001). Review: ecological consequences of recent climate change. Conservation Biology, 15(2), 320–331.

McCarty, J. P. (2002). The number of visits to the nest by parents is an accurate measure of food delivered to nestlings in Tree Swallows. Journal of Field Ornithology, 73(1), 9–14.

McCarty, J. P., & Secord, A. L. (1999). Reproductive ecology of Tree Swallows (Tachycineta bicolor) with high levels of polychlorinated biphenyl contamination. Environmental Toxicology and Chemistry, 18(7), 1433. https://doi.org/10.1897/1551- 5028(1999)018<1433:REOTST>2.3.CO;2

McCarty, J. P., & Winkler, D. W. (1999a). Foraging ecology and diet selectivity of Tree Swallows feeding nestlings. The Condor, 101(2), 246–254. Retrieved from http://www.jstor.org/stable/pdf/1369987.pdf

McCarty, J. P., & Winkler, D. W. (1999b). Relative importance of environmental variables in determining the growth of nestling Tree Swallows Tachycineta bicolor. Ibis, 141(2), 286–

183

296.

McIntyre, N. E. (2000). Ecology of urban arthropods: a review and a call to action. Annals of the Entomological Society of America, 93(4), 825–835. https://doi.org/10.1603/0013- 8746(2000)093[0825:EOUAAR]2.0.CO;2

McKinney, M. (2002). Urbanization, biodiversity, and conservation. BioScience, 52(10), 883– 890.

Mengelkoch, J. M., Niemi, G. J., & Regal, R. R. (2004). Diet of the nestling Tree Swallow. The Condor, 106(2), 423–429.

Merrill, D., & Leatherby, L. (2018). Here’s how America uses its land. Retrieved from https://www.bloomberg.com/graphics/2018-us-land-use/

Merritt, R. W., Cummins, K. . W., & Berg, M. B. (2008). An Introduction to the Aquatic Insects of North America (4th ed.). Dubuque: Kendall Hunt.

Meybeck, M. (1998). Man and river interface: multiple impacts on water and particulates chemistry illustrated in the Seine river basin. Hydrobiologia, 373, 1–20. https://doi.org/10.1023/A:1017067506832

Meyer, J. L., Paul, M. J., & Taulbee, W. K. (2005). Stream ecosystem function in urbanizing landscapes. Journal of the American Benthological Society, 24(3), 602–612.

Michel, N. L., Smith, A. C., Clark, R. G., Morrissey, C. A., & Hobson, K. A. (2016). Differences in spatial synchrony and interspecific concordance inform guild-level population trends for aerial insectivorous birds. Ecography, 39(8), 774–786. https://doi.org/10.1111/ecog.01798

Miller, J. R., Wiens, J. A., Hobbs, N. T., & Theobald, D. M. (2003). Effects of human settlement on bird communities in lowland riparian areas of Colorado (USA). Ecological Applications, 13(4), 1041–1059.

Minagawa, M., & Wada, E. (1984). Stepwise enrichment of 15N along food chains: Further evidence and the relation between 15N and animal age. Geochimica et Cosmochimica Acta, 48(5), 1135–1140. https://doi.org/10.1016/0016-7037(84)90204-7

Minshall, G. W. (1978). Autotropy in Stream Ecosystems. BioScience, 28(12), 767–771. https://doi.org/10.2307/1307250

Monroe, A. P., Hallinger, K. K., Brasso, R. L., & Cristol, D. A. (2008). Occurrence and implications of double brooding in a southern population of Tree Swallows. The Condor, 110(2), 382–386. https://doi.org/10.1525/cond.2008.8341

Moore, J. W., & Semmens, B. X. (2008). Incorporating uncertainty and prior information into stable isotope mixing models. Ecology Letters, 11(5), 470–480. 184

https://doi.org/10.1111/j.1461-0248.2008.01163.x

Morel, F. M. M., Kraepiel, A. M. L., & Amyot, M. (1998). The chemical cycle and bioaccumulation of mercury. Annual Review of Ecology and Systematics, 29(1), 543–566. https://doi.org/10.1146/annurev.ecolsys.29.1.543

Morse, C. C., Huryn, A. D., & Cronan, C. (2003). Impervious surface area as a predictor of the effects of urbanization on stream insect communities in Maine, USA. Environmental Monitoring and Assessment, 89(1), 95–127.

Muehlbauer, J. D., Collins, S. F., Doyle, M. W., & Tockner, K. (2014). How wide is a stream? Spatial extent of the potential “stream signature” in terrestrial food webs using meta- analysis. Ecology, 95(1), 44–55.

Muldal, A., Gibbs, H. L., & Robertson, R. J. (1985). Preferred nest spacing of an obligate cavity- nesting bird, the Tree Swallow. The Condor, 87(3), 356–363. Retrieved from http://www.jstor.org/stable/pdf/1367216.pdf

Munthe, J., Bodaly, R. A. D., Branfireun, B. A., Driscoll, C. T., Cynthia, C., Harris, R., … Harris, R. (2007). Recovery of mercury-contaminated fisheries. AMBIO: A Journal of the Human Environment, 36(1), 33–44.

Murakami, M., & Nakano, S. (2002). Indirect effect of aquatic insect emergence on a terrestrial insect population through bird predation. Ecology Letters, 5(3), 333–337. https://doi.org/10.1046/j.1461-0248.2002.00321.x

Naef-Daenzer, B., & Grüebler, M. U. (2016). Post-fledging survival of altricial birds: ecological determinants and adaptation. Journal of Field Ornithology, 87(3), 227–250. https://doi.org/10.1111/jofo.12157

Naiman, R. J., & Decamps, H. (1997). The ecology of interfaces: Riparian zones. Annual Review of Ecology, Evolution, and Systematics, 28(102), 621–658. https://doi.org/10.1146/annurev.ecolsys.28.1.621

Naiman, R. J., Decamps, H., & Pollock, M. (1993). The role of riparian corridors in maintaining regional biodiversity. Ecological Application, 3(2), 209–212. https://doi.org/10.2307/1941822

Nakano, S., & Murakami, M. (2001). Reciprocal subsidies: dynamic interdependence between terrestrial and aquatic food webs. Proceedings of the National Academy of Sciences of the United States of America, 98(1), 166–170.

Nancy B. Grimm, Sheibley, R. W., Crenshaw, C. L., Dahm, C. N., Roach, W. J., & Zeglin, L. H. (2005). N retention and transformation in urban streams. Journal of the North American Benthological Society, 24(3), 626–642.

185

Nebeker, A. V. (1971). Effect of high winter water temperatures on adult emergence of aquatic insects. Water Research, 5(9), 777–783. https://doi.org/10.1016/0043-1354(71)90100-X

Nebel, S., Mills, A., Mccracken, J. D., & Taylor, P. D. (2010). Declines of aerial insectivores in North America follow a geographic gradient. Avian Conservation & Ecology, 5(2), 1. https://doi.org/10.5751/ACE-00391-050201

Nelson, K. C., & Palmer, M. A. (2007). Stream temperature surges under urbanization and climate change: data, models, and responses. Journal of the American Water Resources Association, 43(2), 440–452.

Newhouse, M. J., Marra, P. P., & Johnson, L. S. (2008). Reproductive success of House Wrens in suburban and rural landscapes. The Wilson Journal of Ornithology, 120(1), 99–104. https://doi.org/10.1676/06-156.1

Nooker, J. K., Dunn, P. O., & Whittingham, L. a. (2005). Effects of food abundance, weather, and female condition on reproduction in Tree Swallows (Tachycineta bicolor). The Auk, 122(4), 1225–1238. https://doi.org/10.1642/0004- 8038(2005)122{[}1225:EOFAWA]2.0.CO;2

Nordlie, K. J., & Arthur, J. W. (1981). Effect of elevated water temperature on insect emergence in outdoor experimental channels. Environmental Pollution, 25(1), 53–65.

Norris, A. R., Aitken, K. E. H., Martin, K., & Pokorny, S. (2018). Nest boxes increase reproductive output for Tree Swallows in a forest grassland matrix in central British Columbia. Plos One, 13(10), e0204226. https://doi.org/10.1371/journal.pone.0204226

Ohio Environmental Protection Agency. (2014). Scioto River watershed. Retrieved from http://www.epa.ohio.gov/dsw/tmdl/sciotoriver.aspx#122556530-implementation

Ohlendorf, H. M., Kilness, A. W., Simmons, J. L., Richard, K., Hoffman, D. J., Moore, J. F., … Dakota, S. (1988). Selenium toxicosis in wild aquatic birds. Journal of Toxicology and Environmental Health, 24(1), 67–92. https://doi.org/10.1080/15287398809531141

Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108(455), 1–24. https://doi.org/10.1002/qj.49710845502

Parnell, A. C., Inger, R., Bearhop, S., & Jackson, A. L. (2010). Source partitioning using stable isotopes: Coping with too much variation. PLoS ONE, 5(3), e9672. https://doi.org/10.1371/journal.pone.0009672

Parnell, A., & Jackson, A. (2013). SIAR. Retrieved from https://cran.r-project.org/package=siar

Parnell, A., & Jackson, A. (2015). Package ‘ siar ’ documentation. https://doi.org/10.1080/07351690701310649

186

Paul, M. J., & Meyer, J. L. (2001). Streams in the urban landscape. Annual Review of Ecology and Systematics, 32, 333–365. https://doi.org/10.1146/annurev.ecolsys.32.081501.114040

Peig, J., & Green, A. J. (2017). New perspectives for estimating body condition from mass/length data: The scaled mass index as an alternative method. Oikos, 118(12), 1883– 1891.

Perez, J. H., Ardia, D. R., Chad, E. K., & Clotfelter, E. D. (2008). Experimental heating reveals nest temperature affects nestling condition in tree swallows (Tachycineta bicolor). Biology Letters, 4(5), 468–471. https://doi.org/10.1098/rsbl.2008.0266

Peters, N. E. (2009). Effects of urbanization on stream water quality in the city of Atlanta, Georgia, USA. Hydrological Processes, 23(20), 2860–2878. https://doi.org/10.1002/hyp

Peterson, B. J., & Fry, B. (1987). Stable isotopes in ecosystem studies. Annual Review of Ecology and Systematics, 18(1), 293–320. https://doi.org/10.1146/annurev.es.18.110187.001453

Piland, N. C., & Winkler, D. W. (2015). Tree Swallow frugivory in winter. Southeastern Naturalist, 14(1), 123–137.

Pilgrim, J. M., Fang, X., & Stefan, H. G. (1999). Stream temperature correlations with air temperatures in Minnesota: implications for climate warming. Journal of the American Water Resources Association, 34(5), 1109–1121.

Pipoly, I., Bókony, V., Seress, G., Szabó, K., & Liker, A. (2013). Effects of extreme weather on reproductive success in a temperate-breeding songbird. PLoS ONE, 8(11), 1–11. https://doi.org/10.1371/journal.pone.0080033

Pirrone, N., Cinnirella, S., Feng, X., Finkelman, R. B., Friedli, H. R., Leaner, J., … Mukherjee, A. B. (2010). Global mercury emissions to the atmosphere from anthropogenic and natural sources. Atmospheric Chemistry and Physics, 10(13), 5951–5964. https://doi.org/10.5194/acp-10-5951-2010

Polis, G. A., Anderson, W. B., & Holt, R. D. (1997). Toward an integration of landscape and food web ecology: The dynamics of spatially subsidized food webs. Annual Review of Ecology and Systematics, 28, 289–316.

Post, D. M. (2002). Using stable isotopes to estimate trophic position: models, methos, and assumptions. Ecology, 83(3), 703–718. https://doi.org/Doi 10.2307/3071875

Post, D. M., Pace, M. L., & Hairston, N. G. (2000). Ecosystem size determines food chain-length in lakes. Nature, 405(6790), 1047–1049.

Poulin, B., Lefebvre, G., & Paz, L. (2010). Red flag for green spray: adverse trophic effects of Bti on breeding birds. Journal of Applied Ecology, 47(4), 884–889. 187

https://doi.org/10.1111/j.1365-2664.2010.01821.x

Powell, G. V. N. (1983). Industrial effluents as a source of mercury contamination in terrestrial riparian vertebrates. Environmental Pollution Series B, Chemical and Physical, 5(1), 51–57.

Power, M. E., & Dietrich, W. E. (2002). Food webs in river networks. Ecological Research, 17(4), 451–471.

QGIS Development Team. (2017). QGIS Geographic Information System. Open Source Geospatial Foundation Project.

Quinney, T. E., & Ankney, C. D. (1985). Prey size selection by Tree Swallows. The Auk, 102(2), 245–250.

Quinney, T. E., Hussell, D. J. T., Ankney, C. D., & Rowan, P. (1986). Sources of variation in the growth of Tree Swallows. The Auk, 103(April), 389–400.

R Core Team. (2018). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Retrieved from https://www.r-project.org

Ramírez, A., De Jesús-Crespo, R., Martinó-Cardona, D. M., Martínez-Rivera, N., & Burgos- Caraballo, S. (2009). Urban streams in Puerto Rico: what can we learn from the tropics? Journal of the North American Benthological Society, 28(4), 1070–1079. https://doi.org/10.1899/08-165.1

Rau, G. H., Sweeney, R. E., Kaplan, I. R., Mearns, A. J., & Young, D. R. (1981). Differences in animal 13C, 15N and D abundance between a polluted and an unpolluted coastal site: Likely indicators of sewage uptake by a marine food web. Estuarine, Coastal and Shelf Science, 13(6), 701–707. https://doi.org/10.1016/S0302-3524(81)80051-5

Razeng, E., & Watson, D. M. (2015). Nutritional composition of the preferred prey of insectivorous birds: popularity reflects quality. Journal of Avian Biology, 46(1), 89–96. https://doi.org/10.1111/jav.00475

Reavie, E. D., Jicha, T. M., Angradi, T. R., Bolgrien, D. W., & Hill, B. H. (2010). Algal assemblages for large river monitoring: Comparison among biovolume, absolute and relative abundance metrics. Ecological Indicators, 10(2), 167–177. https://doi.org/10.1016/j.ecolind.2009.04.009

Ren, W., Zhong, Y., Meligrana, J., Anderson, B., Watt, W. E., Chen, J., & Leung, H. (2003). Urbanization, land use, and water quality in Shanghai 1947 – 1996. Environment International, 29(5), 649–659. https://doi.org/10.1016/S0160-4120(03)00051-5

Rencher, A. C. (1995). Methods of multivariate analysis. New York: John Wiley and Sons, Inc.

Rendell, W. B., & Robertson, R. J. (1989). Nest-site characteristics, reproductive success and 188

cavity avilaiblity for Tree Swallows breeding in natural cavities. The Condor, 91(4), 875– 885.

Rendell, W. B., & Robertson, R. J. (1993). Cavity size, clutch‐size and the breeding ecology of Tree Swallows Tachycineta bicolor. Ibis, 135(3), 305–310. https://doi.org/10.1111/j.1474- 919X.1993.tb02848.x

Richardson, J. S., & Sato, T. (2015). Resource subsidy flows across freshwater-terrestrial boundaries and influence on processes linking adjacent ecosystems. Ecohydrology, 8(3), 406–415. https://doi.org/10.1002/eco.1488

Richmond, E. K., Rosi, E. J., Walters, D. M., Fick, J., Hamilton, S. K., Brodin, T., … Grace, M. R. (2018). A diverse suite of pharmaceuticals contaminates stream and riparian food webs. Nature Communications, 9(1), 4491. https://doi.org/10.1038/s41467-018-06822-w

Rioux-Paquette, S., Pelletier, F., Garant, D., & Bélisle, M. (2014). Severe recent decrease of adult body mass in a declining insectivorous bird population. Proceedings of the Royal Society B: Biological Sciences, 281(1786). https://doi.org/10.1098/rspb.2014.0649

Robertson, R. J., Stutchbury, B. J., & Cohen, R. R. (2011). Tree Swallow. Retrieved March 1, 2017, from https://birdsna.org/Species-Account/bna/species/011/articles/introduction

Rodewald, A. D., & Bakermans, M. H. (2006). What is the appropriate paradigm for riparian forest conservation? Biological Conservation, 128(2), 193–200. https://doi.org/10.1016/j.biocon.2005.09.041

Rodewald, A. D., Kearns, L. J., & Shustack, D. P. (2013). Consequences of urbanizing landscapes to reproductive performance of birds in remnant forests. Biological Conservation, 160, 32–39. https://doi.org/10.1016/j.biocon.2012.12.034

Rodrigues, L., Train, S., Bovo-Scomparin, V., Jati, S., Borsalli, C., & Marengoni, E. (2009). Interannual variability of phytoplankton in the main rivers of the Upper Paraná River floodplain, Brazil: influence of upstream reservoirs. Brazilian Journal of Biology, 69(2), 501–516. https://doi.org/10.1590/S1519-69842009000300006

Rodríguez, S., & Barba, E. (2016). Nestling growth is impaired by heat stress: an experimental study in a mediterranean Great Tit population. Zoological Studies, 55(40), 1–13. https://doi.org/10.6620/ZS.2016.55-40

Roth, N. E., Allan, J. D., & Erickson, D. L. (1996). Landscape influences on stream biotic integrity assessed at multiple spatial scales. Landscape Ecology, 11(3), 141–156. https://doi.org/10.1007/BF02447513

Rottenborn, S. C. (1999). Predicting the impacts of urbanization on riparian bird communities. Biological Conservation, 88(3), 289–299. https://doi.org/10.1016/S0006-3207(98)00128-1

189

Rounick, J. S., & Winterbourn, M. J. (1986). Stable carbon isotopes and carbon flow in ecosystems. BioScience, 36(3), 171–177. https://doi.org/10.2307/1310304

Rowse, L. M., Rodewald, A. D., & Sullivan, S. M. P. (2014). Pathways and consequences of contaminant flux to Acadian flycatchers (Empidonax virescens) in urbanizing landscapes of Ohio, USA. Science of the Total Environment, 485–486(1), 461–467. https://doi.org/10.1016/j.scitotenv.2014.03.095

Roy, A. H., Rosemond, A. D., Paul, M. J., Leigh, D. S., & Wallace, J. B. (2003). Stream macroinvertebrate response to catchment urbanisation (Georgia, U.S.A.). Freshwater Biology, 48(2), 329–346.

RStudio Team. (2016). RStudio: Integrated Development Environment for R. Boston: RStudio, Inc. Retrieved from http://www.rstudio.com/

Rubin, D. B. (1988). Using the SIR algorithm to simulate posterior distributions. Bayesian Statistics 3: Proceedings ofthe Third Valencia International Meeting, June 1–5, 1987. Oxford.

Schaffers, A. P., Raemakers, I. P., Sýkora, K. V, & ter Braak, C. J. F. (2008). Arthropod assemblages are best predicted by plant species composition. Ecology, 89(3), 782–794. https://doi.org/10.1890/07-0361.1

Schindler, D. W. (1978). Factors regulating phytoplankton production and standing crop in the world’s freshwaters. Limnology and Oceanography, 23(3), 478–486. https://doi.org/10.4319/lo.1978.23.3.0478

Schlesinger, M. D., Manley, P. N., & Holyoak, M. (2008). Distinguishing stressors acting on land bird communities in an urbanizing environment. Ecology, 89(8), 2302–2314. https://doi.org/10.1890/07-0256.1

Schneider, S. C., & Miller, J. R. (2014). Response of avian communities to invasive vegetation in urban forest fragments. The Condor, 116(3), 459–471. https://doi.org/10.1650/CONDOR-13-009R1.1

Schueler, T. R. (1994). The importance of imperviousness. Watershed Protection Techniques, 1(3), 100–111.

Seto, K. C., Guneralp, B., & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences, 109(40), 16083–16088. https://doi.org/10.1073/pnas.1211658109

Shlosberg, A., Rumbeiha, W. K., Lublin, A., & Kannan, K. (2011). A database of avian blood spot examinations for exposure of wild birds to environmental toxicants: The DABSE biomonitoring project. Journal of Environmental Monitoring, 13(6), 1547–1558.

190

https://doi.org/10.1039/c0em00754d

Singmann, H., Bolker, B., Westfall, J., & Aust, F. (2018). afex. Retrieved from https://github.com/singmann/afex

Smith, A. C., Hudson, M.-A. R., Downes, C. M., & Francis, C. M. (2015). Change points in the population trends of aerial-insectivorous birds in North America: synchronized in time across species and regions. PLoS ONE, 10(7), 1–23. https://doi.org/10.1371/journal.pone.0130768

Smith, V. H., Tilman, G. D., & Nekola, J. C. (1998). Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environmental Pollution, 100(1– 3), 179–196. https://doi.org/10.1016/S0269-7491(99)00091-3

Smits, J. E. G., & Fernie, K. J. (2013). Avian wildlife as sentinels of ecosystem health. Comparative Immunology, Microbiology and Infectious Diseases, 36(3), 333–342. https://doi.org/10.1016/j.cimid.2012.11.007

Sponseller, R. A., Benfield, E. F., & Valett, H. M. (2001). Relationships between land use, spatial scale and stream macroinvertebrate communities. Acta Psychiatrica Scandinavica, 46(10), 1409–1424. https://doi.org/10.1111/j.1600-0447.1963.tb07839.x

Stanton, R. S., Lark, R. G. C. O. G. C., & Morrissey, C. A. M. (2017). Intensive agriculture and insect prey availability influence oxidative status and return rates of an aerial insectivore. Ecosphere, 8(3), e01746. https://doi.org/10.1002/ecs2.1746

Stenroth, K., Polvi, L. E., Fältström, E., Jonsson, M., & Science, E. (2015). Land-use effects on terrestrial consumers through changed size structure of aquatic insects. Freshwater Biology, 60(1), 136–149. https://doi.org/10.1111/fwb.12476

Steuer, J. J., Bales, J. D., Giddings, E. M. P., Steuer, J. J., & Giddings, E. M. P. (2009). Relationship of stream ecological conditions to simulated hydraulic metrics across a gradient of basin urbanization Published by : The University of Chicago Press on behalf of the Society for Freshwater Science Relationship of stream ecological conditions, 28(4), 955–976. https://doi.org/10.1899/08-157.1

Stewart, P. M., Butcher, J. T., & Swinford, T. O. (2000). Land use, habitat, and water quality effects on macroinvertebrate communities in three watersheds of a lake Michigan associated marsh system. Aquatic Ecosystem Health and Management, 3(1), 179–189. https://doi.org/10.1080/14634980008656999

Stone, B., Hess, J. J., & Frumkin, H. (2010). Urban form and extreme heat events: Are sprawling cities more vulnerable to climate change than compact cities? Environmental Health Perspectives, 118(10), 1425–1428. https://doi.org/10.1289/ehp.0901879

191

Strasevicius, D., Jonsson, M., Nyholm, N. E. I., & Malmqvist, B. (2013). Reduced breeding success of Pied Flycatchers Ficedula hypoleuca along regulated rivers. Ibis, 155(2), 348– 356. https://doi.org/10.1111/ibi.12024

Strayer, D. L., Beighley, R. E., Thompson, L. C., Brooks, S., Nilsson, C., Pinay, G., & Naiman, R. J. (2003). Effects of land cover on stream ecosystems: Roles of empirical models and scaling issues. Ecosystems, 6(5), 407–423. https://doi.org/10.1007/s10021-002-0170-0

Stutchbury, B. J., & Robertson, R. J. (1985). Floating populations of female Tree Swallows. The Auk, 102(3), 651–654.

Sullivan, S. M. P., Boaz, L. E., & Hossler, K. (2016). Fluvial geomorphology and aquatic-to- terrrestrial Hg export are weekly coupled in small urban streams of Columbus, Ohio. Water Resources Research, 52(4), 2822–2839. https://doi.org/10.1002/2014WR015716

Sullivan, S. M. P., Hossler, K., & Cianfrani, C. M. (2015). Ecosystem structure emerges as a strong determinant of food-chain length in linked stream–riparian ecosystems. Ecosystems, 18(8), 1356–1372. https://doi.org/10.1007/s10021-015-9904-7

Sullivan, S. M. P., Manning, D. W. P., & Davis, R. P. (2018). Do the ecological impacts of dam removal extend across the aquatic–terrestrial boundary? Ecosphere, 9(4), 1–19. https://doi.org/10.1002/ecs2.2180

Sullivan, S. M. P., & Rodewald, A. D. (2012). In a state of flux: The energetic pathways that move contaminants from aquatic to terrestrial environments. Environmental Toxicology and Chemistry, 31(6), 1175–1183. https://doi.org/10.1002/etc.1842

Sullivan, S. M. P., & Vierling, K. T. (2012). Exploring the influences of multiscale environmental factors on the American dipper Cinclus mexicanus. Ecography, 35(7), 624– 636. https://doi.org/10.1111/j.1600-0587.2011.07071.x

Sullivan, S. M. P., Watzin, M. C., & Hession, W. C. (2006). Differences in the reproductive ecology of belted kingfishers (Ceryle alcyon) across streams with varying geomorphology and habitat quality. Waterbirds, 29(3), 258–270. https://doi.org/Doi 10.1675/1524- 4695(2006)29[258:Ditreo]2.0.Co;2

Tam, B. Y., Gough, W. A., & Mohsin, T. (2015). The impact of urbanization and the urban heat island effect on day to day temperature variation. Urban Climate, 12, 1–10. https://doi.org/10.1016/j.uclim.2014.12.004

Taylor, L. R. (1963). Analysis of the effect of temperature on insects in flight. Journal of Animal Ecology, 32(1), 99–117.

Teglhøj, P. G. (2017). A comparative study of insect abundance and reproductive success of barn swallows Hirundo rustica in two urban habitats. Journal of Avian Biology, 48(6), 846–853.

192

https://doi.org/10.1111/jav.01086

Thomas, D. W., Blondel, J., Perret, P., Lambrechts, M. M., & Speakman, J. R. (2001). Energetic and fitness costs of mismatching resource supply and demand in seasonally breeding birds. Science, 291(5513), 2598–2601.

Thorp, J. H., & Delong, M. D. (1994). The riverine productivity model: An heuristic view of carbon sources and organic processing in large river ecosystems. Oikos, 70(2), 305–308.

Townes, H. (1972). A light-weight Malaise trap. Entomological News, 83, 239–247.

Townsend, A. K., Sillett, T. S., Lany, N. K., Kaiser, S. A., Rodenhouse, N. L., Webster, M. S., & Holmes, R. T. (2013). Warm springs, early lay dates, and double brooding in a North American migratory songbird, the Black-throated Blue Warbler. PLoS ONE, 8(4), e59467. https://doi.org/10.1371/journal.pone.0059467

Tromboni, F., & Dodds, W. K. (2017). Relationships between land use and stream nutrient concentrations in a Highly urbanized tropical region of Brazil: thresholds and riparian zones. Environmental Management, 60(1), 30–40. https://doi.org/10.1007/s00267-017- 0858-8

Twining, C. W., Brenna, J. T., Lawrence, P., Shipley, J. R., Tollefson, T. N., Winkler, D. W., … Winkler, D. W. (2016). Omega-3 long-chain polyunsaturated fatty acids support aerial insectivore performance more than food quantity. Proceedings of the National Academy of Sciences of the United States of America, 113(46), 10920–10925. https://doi.org/10.1073/pnas.1616962113

Twining, C. W., Shipley, J. R., & Winkler, D. W. (2018). Aquatic insects rich in omega-3 fatty acids drive breeding success in a widespread bird. Ecology Letters, 12(21), 1812–1820. https://doi.org/10.1111/ele.13156

U.S. Census Bureau. (2010). TIGER/Line shapefile, 2010, 2010 state, Ohio, 2010 census block state-based. Washington: U.S. Census Bureau.

U.S. Geological Survey. (2014a). NLCD 2011 percent developed imperviousness (2011 edition, amended 2014) - National Geospatial Data Asset (NGDA) land use land cover. Sioux Falls: U.S. Geological Survey.

U.S. Geological Survey. (2014b). NLCD2011 USFS percent tree canopy (cartographic version). Sioux Falls: U.S. Geological Survey.

U.S. Geological Survey. (2018). Bird Banding Laboratory. Retrieved from https://www.usgs.gov/centers/pwrc/science/bird-banding-laboratory

Uesugi, A., & Murakami, M. (2007). Do seasonally fluctuating aquatic subsidies influence the distribution pattern of birds between riparian and upland forests? Ecological Research, 193

22(2), 274–281. https://doi.org/10.1007/s11284-006-0028-6

Urban, M. C., Skelly, D. K., Burchsted, D., Price, W., & Lowry, S. (2006). Stream communities across a rural–urban landscape gradient. Diversity and Distributions, 12(4), 337–350. https://doi.org/10.1111/j.1366-9516.2005.00226.x

US EPA. (2008). Reducing urban heat islands: compendium of strategies urban heat island basics. Retrieved from http://www.epa.gov/hiri/resources/compendium.htm

Vander Zanden, M. J., & Rasmussen, J. B. (2001). Variation in 15N and 13C trophic fractionation: Implications for aquatic food web studies. Limnology and Oceanography, 46(8), 2061–2066. https://doi.org/10.4319/lo.2001.46.8.2061

Vannote, R. L., Minshall, G. W., Cummins, K. W., Sedell, J. R., & Cushing, C. E. (1980). The river continuum concept. Canadian Journal Fishery and Aquatic Sciences, 37(1), 130–137.

Varian-Ramos, C. W., Swaddle, J. P., & Cristol, D. A. (2014). Mercury reduces avian reproductive success and imposes selection : an experimental study with adult- or lifetime- exposure in Zebra Finch. PLoS ONE, 9(4), e95674. https://doi.org/10.1371/journal.pone.0095674

Vietz, G. J., Walsh, C. J., & Fletcher, T. D. (2015). Urban hydrogeomorphology and the urban stream syndrome: treating the symptoms and causes of geomorphic change. Progress in Physical Geography, 40(3), 480–492. https://doi.org/10.1177/0309133315605048

Violin, C. R., Cada, P., Sudduth, E. B., Hassett, B. A., Penrose, D. L., & Bernhardt, E. S. (2011). Effects of urbanization and urban stream restoration on the physical and biological structure of stream ecosystems. Ecological Applications, 21(6), 1932–1949. https://doi.org/10.1890/10-1551.1

Visser, A. M. E., Noordwijk, A. J. Van, Tinbergen, J. M., Lessells, C. M., Visser, M. E., Noordwijk, A. J. Van, … Lessells, C. M. (1998). Warmer springs lead to mistimed reproduction in Great Tits (Parus major). Proceedings of the Royal Society B-Biological Sciences, 265(1408), 1867–1870.

Wahl, C. M., Neils, A., & Hooper, D. (2013). Impacts of land use at the catchment scale constrain the habitat benefits of stream riparian buffers. Freshwater Biology, 58(11), 2310– 2324. https://doi.org/10.1111/fwb.12211

Wallace, J. B., Eggert, S. L., Meyer, J. L., & Webster, J. R. (1997). Multiple trophic levels of a forest stream linked to terrestrial litter inputs. Science, 277(5322), 102–104. https://doi.org/10.1126/science.277.5322.102

Walsh, C. J., Roy, A. H., Feminella, J. W., Cottingham, P. D., Groffman, P. M., & Morgan, R. P. (2005). The urban stream syndrome: current knowledge and the search for a cure. Journal

194

of the North American Benthological Society, 24(3), 706–723.

Walsh, C. J., Sharpe, A. K., Breen, P. F., & Sonneman, J. A. (2001). Effects of urbanization on streams of the Melbourne region, Victoria, Australia. I. Benthic macroinvertebrate communities. Freshwater Biology, 46(4), 535–551.

Walsh, C. J., Waller, K. A., Gehling, J., & Mac Nally, R. (2007). Riverine invertebrate assemblages are degraded more by catchment urbanisation than by riparian deforestation. Freshwater Biology, 52(3), 574–587. https://doi.org/10.1111/j.1365-2427.2006.01706.x

Walters, D. M., Fritz, K. M., & Otter, R. R. (2008). The dark side of subsidies: adult stream insects export organic contaminants to riparian predators. Ecological Applications, 18(8), 1835–1841.

Wang, L., Robertson, D. M., & Garrison, P. J. (2007). Linkages between nutrients and assemblages of macroinvertebrates and fish in wadeable streams: Implication to nutrient criteria development. Environmental Management, 39(2), 194–212. https://doi.org/10.1007/s00267-006-0135-8

Wenger, S. J., Roy, A. H., Jackson, C. R., Bernhardt, E. S., Carter, T. L., Filoso, S., … Walsh, C. J. (2009). Twenty-six key research questions in urban stream ecology: an assessment of the state of the science. Journal of the North American Benthological Society, 28(4), 1080– 1098. https://doi.org/10.1899/08-186.1

Whitaker, D. M., Carroll, A. L., & Montevecchi, W. A. (2000). Elevated numbers of flying insects and insectivorous birds in riparian buffer strips. Canadian Journal of Zoology, 78(5), 740–747. https://doi.org/10.1139/z99-254

Winkler, D. W., & Allen, P. E. (1996). The seasonal decline in Tree Swallow clutch size: physiological constraint or strategic adjustment? Ecology, 77(3), 922–932.

Winkler, D. W., Dunn, P. O., & Mcculloch, C. E. (2002). Predicting the effects of climate change on avian life-history traits. Proceedings of the National Academy of Sciences of the United States of America, 99(21), 13595–13599.

Winkler, D. W., Luo, M. K., & Rakhimberdiev, E. (2013). Temperature effects on food supply and chick mortality in tree swallows (Tachycineta bicolor). Oecologia, 173(1), 129–138. https://doi.org/10.1007/s00442-013-2605-z

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Appendix A. Chapter 2: Supplemental Material

196

Table A.1 Study-site coordinates, stream order, land-use category (defined by % impervious surface), and % impervious surface coverage.

Impervious Site Latitude Longitude River Order Land Use Surface (%)

Berliner 39.93386 -83.0056 Scioto R. 6th Urban 41.1

Darby 39.91505 -83.21632 Big Darby Cr. 4th Natural/Protected 0.0

Fawcett 40.0106 -83.01818 Olentangy R. 5th Urban 48.3

Highbanks 40.15338 -83.04192 Olentangy R. 5th Natural/Protected 14.2

Mussel 40.16955 -83.13172 Scioto R. 6th Natural/Protected 14.4

Restoration 40.00323 -83.02278 Olentangy R. 5th Urban 64.4

Wetlands 40.01926 -83.01937 Olentangy R. 5th Urban 48.5

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Table A.2 Invertebrates collected 2014-2017, by year, site, season (early/late), transect (top/bottom), family, 10-day count, and mean mass (total family dry mass / count). Note that samples from both transects were pooled in 2015, so no transect is listed (entries represent totals for each family from both transects).

Mass, Mean Year Site Season Transect Habitat Family Count (g) 2014 Berliner early bottom aquatic Ceratopogonidae 18 0.00001 2014 Berliner early bottom aquatic Chaoboridae 1 0.00000 2014 Berliner early bottom aquatic Chironomidae 180 0.00005 2014 Berliner early bottom aquatic Dolichopodidae 6 0.00017 2014 Berliner early bottom aquatic Empididae 1 0.00010 2014 Berliner early bottom aquatic Hydroptilidae 3 0.00000 2014 Berliner early bottom aquatic Nymphomyiidae 1 0.00000 2014 Berliner early bottom aquatic Perlidae 1 0.00090 2014 Berliner early bottom aquatic Sarcophagidae 1 0.00130 2014 Berliner early bottom aquatic Simuliidae 25 0.00006 2014 Berliner early bottom aquatic Sisyridae 1 0.00030 2014 Berliner early top aquatic Dolichopodidae 3 0.00043 2014 Berliner early top aquatic Perlidae 3 0.00207 2014 Berliner early top aquatic Sarcophagidae 1 0.00540 2014 Berliner early top terrestrial Cicadellidae 3 0.00040 2014 Berliner early top terrestrial Elateridae 3 0.00087 2014 Berliner early top terrestrial Latridiidae 2 0.00040 2014 Berliner early top terrestrial Sciaridae 3 0.00023 2014 Darby early bottom aquatic Baetidae 1 0.00010 2014 Darby early bottom aquatic Ceratopogonidae 30 0.00001 2014 Darby early bottom aquatic Chironomidae 181 0.00005 2014 Darby early bottom aquatic Crambidae 1 0.00050 2014 Darby early bottom aquatic Culicidae 2 0.00020 2014 Darby early bottom aquatic Dolichopodidae 39 0.00054 2014 Darby early bottom aquatic Empididae 3 0.00007 2014 Darby early bottom aquatic Muscidae 4 0.00328 2014 Darby early bottom aquatic Oligoneuridae 2 0.00000 2014 Darby early bottom aquatic Simuliidae 1 0.00000 2014 Darby early bottom aquatic Tipulidae 4 0.00020 2014 Darby early top aquatic Ceratopogonidae 10 0.00002 2014 Darby early top aquatic Chaoboridae 2 0.00025 2014 Darby early top aquatic Chironomidae 175 0.00006 2014 Darby early top aquatic Corydalidae 1 0.00080 198

2014 Darby early top aquatic Crambidae 2 0.00045 2014 Darby early top aquatic Culicidae 5 0.00022 2014 Darby early top aquatic Dolichopodidae 5 0.00030 2014 Darby early top aquatic Empididae 1 0.00000 2014 Darby early top aquatic Simuliidae 10 0.00003 2014 Darby early top aquatic Tipulidae 2 0.00245 2014 Darby early bottom terrestrial Cicadellidae 2 0.00020 2014 Darby early bottom terrestrial Curculionidae 1 0.00160 2014 Darby early top terrestrial Aphididae 1 0.00040 2014 Darby early top terrestrial Ceraphronidae 1 0.00020 2014 Darby early top terrestrial Cicadellidae 2 0.00030 2014 Darby early top terrestrial Latridiidae 1 0.00020 2014 Darby early top terrestrial Phoridae 1 0.00020 2014 Darby early top terrestrial Tiphiidae 1 0.00330 2014 Fawcett early bottom terrestrial Cicadellidae 4 0.00030 2014 Fawcett early bottom terrestrial Elateridae 1 0.01310 2014 Fawcett early bottom terrestrial Phoridae 2 0.00040 2014 Fawcett early bottom terrestrial Sciaridae 22 0.00009 2014 Fawcett early top terrestrial Caeciliusidae 1 0.00040 2014 Fawcett early top terrestrial Latridiidae 1 0.00050 2014 Highbanks early bottom aquatic Braconidae 1 0.00020 2014 Highbanks early bottom aquatic Ceratopogonidae 24 0.00003 2014 Highbanks early bottom aquatic Chironomidae 84 0.00001 2014 Highbanks early bottom aquatic Crambidae 2 0.00050 2014 Highbanks early bottom aquatic Culicidae 3 0.00047 2014 Highbanks early bottom aquatic Dolichopodidae 4 0.00042 2014 Highbanks early bottom aquatic Ephydridae 3 0.00010 2014 Highbanks early bottom aquatic Hydropsychidae 1 0.00050 2014 Highbanks early bottom aquatic Hydroptilidae 1 0.00030 2014 Highbanks early bottom aquatic Perlidae 5 0.00314 2014 Highbanks early bottom aquatic Sarcophagidae 1 0.00110 2014 Highbanks early bottom aquatic Simuliidae 16 0.00002 2014 Highbanks early bottom aquatic Tanyderidae 1 0.00060 2014 Highbanks early bottom aquatic Tipulidae 1 0.01170 2014 Highbanks early top aquatic Ceratopogonidae 2 0.00000 2014 Highbanks early top aquatic Chironomidae 10 0.00001 2014 Highbanks early top aquatic Simuliidae 1 0.00000 2014 Highbanks early top aquatic Veliidae 2 0.00000 2014 Highbanks early bottom terrestrial Cicadellidae 4 0.00008 2014 Highbanks early bottom terrestrial Latridiidae 2 0.00005 2014 Highbanks early bottom terrestrial Phoridae 1 0.00000 2014 Highbanks early bottom terrestrial Sciaridae 6 0.00005 199

2014 Highbanks early top terrestrial Ceraphronidae 1 0.00000 2014 Highbanks early top terrestrial Cicadellidae 1 0.00010 2014 Highbanks early top terrestrial Cynipidae 9 0.00007 2014 Highbanks early top terrestrial Pompilidae 1 0.00030 2014 Mussel early top aquatic Ceratopogonidae 4 0.00005 2014 Mussel early top aquatic Ceratopogonidae 10 0.00001 2014 Mussel early top aquatic Chironomidae 595 0.00012 2014 Mussel early top aquatic Chironomidae 188 0.00004 2014 Mussel early top aquatic Hydroptilidae 1 0.00010 2014 Mussel early top aquatic Nymphomyiidae 1 0.00000 2014 Mussel early top aquatic Platygastridae 1 0.00010 2014 Mussel early top aquatic Simuliidae 5 0.00012 2014 Mussel early top terrestrial Ceraphronidae 2 0.00000 2014 Mussel early top terrestrial Cicadellidae 1 0.00010 2014 Mussel early top terrestrial Elateridae 1 0.01340 2014 Mussel early top terrestrial Eupelmidae 1 0.00000 2014 Mussel early top terrestrial Sphecidae 1 0.00210 2014 Mussel early top terrestrial Tingidae 2 0.00035 2014 Restoration early bottom terrestrial Buprestidae 2 0.00090 2014 Restoration early bottom terrestrial Cicadellidae 7 0.00013 2014 Restoration early bottom terrestrial Curculionidae 1 0.00490 2014 Restoration early bottom terrestrial Elateridae 4 0.00205 2014 Restoration early bottom terrestrial Latridiidae 2 0.00020 2014 Restoration early bottom terrestrial Miridae 1 0.00050 2014 Restoration early bottom terrestrial Mycetophilidae 1 0.00050 2014 Restoration early bottom terrestrial Phoridae 3 0.00020 2014 Restoration early bottom terrestrial Sciaridae 13 0.00006 2014 Restoration early bottom terrestrial Syrphidae 3 0.00143 2014 Restoration early bottom terrestrial Tingidae 2 0.00035 2014 Restoration early top terrestrial Cicadellidae 1 0.00090 2014 Restoration early top terrestrial Elateridae 11 0.00181 2014 Restoration early top terrestrial Latridiidae 1 0.00080 2014 Wetlands early bottom terrestrial Cicadellidae 2 0.00050 2014 Wetlands early bottom terrestrial Dryomyzidae 1 0.00080 2014 Wetlands early bottom terrestrial Latridiidae 2 0.00040 2014 Wetlands early bottom terrestrial Miridae 1 0.00130 2014 Wetlands early bottom terrestrial Mycetophilidae 7 0.00029 2014 Wetlands early bottom terrestrial Phoridae 4 0.00020 2014 Wetlands early bottom terrestrial Tenthredinidae 1 0.00140 2014 Wetlands early top terrestrial Mycetophilidae 1 0.00080 2014 Wetlands early top terrestrial Phoridae 1 0.00080 2014 Wetlands early top terrestrial Sciaridae 2 0.00040 200

2014 Wetlands early top terrestrial Stratiomyidae 1 0.01150 2014 Wetlands early top terrestrial Syrphidae 1 0.00210 2015 Berliner early aquatic Chironomidae 97 0.00007 2015 Berliner early aquatic Dolichopodidae 27 0.00064 2015 Berliner early aquatic Hydroptilidae 2 0.00025 2015 Berliner early aquatic Muscidae 4 0.00330 2015 Berliner early aquatic Scathophagidae 3 0.00057 2015 Berliner early aquatic Tipulidae 1 0.00060 2015 Berliner late aquatic Aeshnidae 1 0.08180 2015 Berliner late aquatic Chironomidae 120 0.00008 2015 Berliner late aquatic Culicidae 1 0.00050 2015 Berliner late aquatic Dolichopodidae 24 0.00066 2015 Berliner late aquatic Ephydridae 4 0.00005 2015 Berliner late aquatic Philopotamidae 1 0.00080 2015 Berliner late aquatic Psychodidae 4 0.00008 2015 Berliner early terrestrial Apidae 1 0.01950 2015 Berliner early terrestrial Cicadellidae 3 0.00017 2015 Berliner early terrestrial Elateridae 4 0.00083 2015 Berliner early terrestrial Heleomyzidae 2 0.00010 2015 Berliner early terrestrial Latridiidae 3 0.00010 2015 Berliner early terrestrial Mordellidae 2 0.00570 2015 Berliner early terrestrial Mycetophilidae 7 0.00007 2015 Berliner early terrestrial Saldidae 1 0.00010 2015 Berliner early terrestrial Tingidae 1 0.00010 2015 Berliner late terrestrial Cicadellidae 1 0.00020 2015 Berliner late terrestrial Elateridae 3 0.00490 2015 Berliner late terrestrial Latridiidae 1 0.00020 2015 Berliner late terrestrial Mordellidae 1 0.00010 2015 Berliner late terrestrial Mycetophilidae 3 0.00007 2015 Berliner late terrestrial Phoridae 1 0.00030 2015 Darby early aquatic Chironomidae 153 0.00010 2015 Darby early aquatic Coenagrionidae 1 0.00650 2015 Darby early aquatic Crambidae 2 0.00035 2015 Darby early aquatic Dolichopodidae 1 0.00010 2015 Darby early aquatic Heptageniidae 3 0.00073 2015 Darby early aquatic Muscidae 2 0.00205 2015 Darby early aquatic Perlidae 9 0.00196 2015 Darby late aquatic Blephariceridae 1 0.00040 2015 Darby late aquatic Cecidomyidae 1 0.00020 2015 Darby late aquatic Chironomidae 168 0.00004 2015 Darby late aquatic Culicidae 5 0.00052 2015 Darby late aquatic Dolichopodidae 5 0.00042

201

2015 Darby late aquatic Empididae 2 0.00025 2015 Darby late aquatic Ephydridae 2 0.00015 2015 Darby late aquatic Heptageniidae 5 0.00154 2015 Darby late aquatic Hydroptilidae 1 0.00020 2015 Darby early terrestrial Cicadellidae 6 0.00015 2015 Darby early terrestrial Coccinellidae 1 0.00000 2015 Darby early terrestrial Elateridae 7 0.01130 2015 Darby early terrestrial Eucharitidae 1 0.00020 2015 Darby early terrestrial Laemophloeidae 3 0.00060 2015 Darby early terrestrial Latridiidae 2 0.00005 2015 Darby early terrestrial Lonchaeidae 2 0.00010 2015 Darby early terrestrial Mycetophilidae 1 0.00030 2015 Darby early terrestrial Nemouridae 2 0.00075 2015 Darby early terrestrial Proctotrupidae 1 0.00010 2015 Darby early terrestrial Scarabaeidae 1 0.01450 2015 Darby late terrestrial Buprestidae 1 0.00090 2015 Darby late terrestrial Cerambycidae 1 0.09770 2015 Darby late terrestrial Cicadellidae 11 0.00013 2015 Darby late terrestrial Coccinellidae 1 0.00010 2015 Darby late terrestrial Curculionidae 3 0.00117 2015 Darby late terrestrial Elateridae 4 0.00698 2015 Darby late terrestrial Halictidae 3 0.00170 2015 Darby late terrestrial Latridiidae 3 0.00003 2015 Darby late terrestrial Mordellidae 2 0.00035 2015 Darby late terrestrial Sesiidae 1 0.00200 2015 Darby late terrestrial Tingidae 6 0.00017 2015 Fawcett early aquatic Chironomidae 61 0.00010 2015 Fawcett early aquatic Coenagrionidae 1 0.00700 2015 Fawcett early aquatic Dolichopodidae 12 0.00059 2015 Fawcett early aquatic Hydroptilidae 1 0.00050 2015 Fawcett early aquatic Muscidae 5 0.00196 2015 Fawcett early aquatic Perlidae 12 0.00254 2015 Fawcett early aquatic Philopotamidae 1 0.00120 2015 Fawcett late aquatic Cecidomyidae 2 0.00005 2015 Fawcett late aquatic Ceratopogonidae 1 0.00010 2015 Fawcett late aquatic Chironomidae 54 0.00005 2015 Fawcett late aquatic Culicidae 1 0.00020 2015 Fawcett late aquatic Dolichopodidae 10 0.00071 2015 Fawcett late aquatic Psychodidae 4 0.00000 2015 Fawcett early terrestrial Argidae 1 0.00810 2015 Fawcett early terrestrial Axymyiidae 4 0.00213 2015 Fawcett early terrestrial Cicadellidae 18 0.00016

202

2015 Fawcett early terrestrial Coccinellidae 3 0.00023 2015 Fawcett early terrestrial Elateridae 13 0.00979 2015 Fawcett early terrestrial Gasteruptiidae 3 0.00080 2015 Fawcett early terrestrial Halictidae 1 0.00410 2015 Fawcett early terrestrial Latridiidae 5 0.00010 2015 Fawcett early terrestrial Lonchaeidae 7 0.00017 2015 Fawcett early terrestrial Miridae 1 0.00010 2015 Fawcett early terrestrial Mordellidae 6 0.00258 2015 Fawcett early terrestrial Mycetophilidae 8 0.00009 2015 Fawcett early terrestrial Phoridae 34 0.00021 2015 Fawcett early terrestrial Scathophagidae 1 0.00050 2015 Fawcett early terrestrial Syrphidae 3 0.00163 2015 Fawcett early terrestrial Tenthredinidae 1 0.00170 2015 Fawcett late terrestrial Coccinellidae 1 0.00020 2015 Fawcett late terrestrial Latridiidae 2 0.00005 2015 Highbanks early aquatic Chironomidae 39 0.00004 2015 Highbanks early aquatic Crambidae 1 0.00030 2015 Highbanks early aquatic Hydroptilidae 1 0.00000 2015 Highbanks early aquatic Perlidae 36 0.00181 2015 Highbanks early aquatic Perlodidae 5 0.00300 2015 Highbanks late aquatic Chironomidae 85 0.00006 2015 Highbanks late aquatic Culicidae 1 0.00060 2015 Highbanks late aquatic Dolichopodidae 9 0.00047 2015 Highbanks late aquatic Ephydridae 4 0.00027 2015 Highbanks late aquatic Heptageniidae 1 0.00340 2015 Highbanks late aquatic Philopotamidae 1 0.00090 2015 Highbanks late aquatic Psychodidae 2 0.00025 2015 Highbanks early terrestrial Asilidae 1 0.00410 2015 Highbanks early terrestrial Chloropidae 1 0.00010 2015 Highbanks early terrestrial Cicadellidae 2 0.00020 2015 Highbanks early terrestrial Elateridae 5 0.01614 2015 Highbanks early terrestrial Heleomyzidae 1 0.00030 2015 Highbanks early terrestrial Latridiidae 3 0.00010 2015 Highbanks early terrestrial Mycetophilidae 3 0.00000 2015 Highbanks early terrestrial Saldidae 1 0.00010 2015 Highbanks early terrestrial Sphindidae 1 0.00140 2015 Highbanks late terrestrial Cicadellidae 30 0.00023 2015 Highbanks late terrestrial Eucnemidae 1 0.04010 2015 Highbanks late terrestrial Lonchaeidae 1 0.00000 2015 Highbanks late terrestrial Mordellidae 4 0.00017 2015 Mussel early aquatic Chironomidae 174 0.00017 2015 Mussel early aquatic Culicidae 8 0.00018

203

2015 Mussel early aquatic Dolichopodidae 3 0.00040 2015 Mussel early aquatic Muscidae 2 0.00295 2015 Mussel late aquatic Chironomidae 278 0.00017 2015 Mussel late aquatic Culicidae 3 0.00033 2015 Mussel late aquatic Heptageniidae 2 0.00120 2015 Mussel late aquatic Hydroptilidae 2 0.00020 2015 Mussel late aquatic Ichneumonidae 1 0.00060 2015 Mussel late aquatic Muscidae 1 0.00070 2015 Mussel early terrestrial Cicadellidae 4 0.00023 2015 Mussel early terrestrial Coccinellidae 1 0.00900 2015 Mussel early terrestrial Curculionidae 1 0.00310 2015 Mussel early terrestrial Diapriidae 3 0.00013 2015 Mussel early terrestrial Elateridae 12 0.01911 2015 Mussel early terrestrial Laemophloeidae 2 0.00250 2015 Mussel early terrestrial Latridiidae 1 0.00020 2015 Mussel early terrestrial Lonchaeidae 3 0.00013 2015 Mussel early terrestrial Mycetophilidae 9 0.00008 2015 Mussel late terrestrial Asilidae 1 0.00010 2015 Mussel late terrestrial Calliphoridae 1 0.00220 2015 Mussel late terrestrial Chamaemyidae 2 0.00095 2015 Mussel late terrestrial Chloropidae 1 0.00010 2015 Mussel late terrestrial Chrysomelidae 3 0.00240 2015 Mussel late terrestrial Cicadellidae 1 0.00000 2015 Mussel late terrestrial Elateridae 4 0.00933 2015 Mussel late terrestrial Halictidae 9 0.00363 2015 Mussel late terrestrial Latridiidae 4 0.00002 2015 Mussel late terrestrial Lonchaeidae 12 0.00011 2015 Mussel late terrestrial Megaspilidae 3 0.00023 2015 Mussel late terrestrial Miridae 1 0.00280 2015 Mussel late terrestrial Mordellidae 7 0.00037 2015 Mussel late terrestrial Phoridae 8 0.00000 2015 Mussel late terrestrial Pipunculidae 1 0.00080 2015 Mussel late terrestrial Proctotrupidae 1 0.00000 2015 Mussel late terrestrial Rhagionidae 12 0.00054 2015 Mussel late terrestrial Scarabaeidae 2 0.02695 2015 Mussel late terrestrial Sciaridae 46 0.00032 2015 Mussel late terrestrial Sphecidae 1 0.04240 2015 Mussel late terrestrial Stratiomyidae 2 0.00060 2015 Mussel late terrestrial Tingidae 2 0.00015 2015 Mussel late terrestrial Vespidae 2 0.00485 2015 Restoration early aquatic Chironomidae 221 0.00005 2015 Restoration early aquatic Dolichopodidae 3 0.00050

204

2015 Restoration early aquatic Muscidae 6 0.00193 2015 Restoration late aquatic Baetidae 1 0.00000 2015 Restoration late aquatic Chironomidae 128 0.00005 2015 Restoration late aquatic Dolichopodidae 2 0.00005 2015 Restoration late aquatic Ephydridae 2 0.00000 2015 Restoration late aquatic Muscidae 3 0.00107 2015 Restoration late aquatic Psychodidae 3 0.00003 2015 Restoration late aquatic Tipulidae 1 0.00030 2015 Restoration early terrestrial Chrysomelidae 1 0.00110 2015 Restoration early terrestrial Cicadellidae 1 0.00010 2015 Restoration early terrestrial Elateridae 2 0.01360 2015 Restoration early terrestrial Miridae 3 0.00057 2015 Restoration early terrestrial Mordellidae 1 0.00140 2015 Restoration early terrestrial Mycetophilidae 2 0.00015 2015 Restoration late terrestrial Brentidae 1 0.00000 2015 Restoration late terrestrial Cicadellidae 2 0.00020 2015 Restoration late terrestrial Coccinellidae 1 0.00000 2015 Restoration late terrestrial Elateridae 3 0.01477 2015 Restoration late terrestrial Gasteruptiidae 1 0.00120 2015 Restoration late terrestrial Mordellidae 2 0.00085 2015 Restoration late terrestrial Mycetophilidae 2 0.00005 2015 Restoration late terrestrial Phoridae 1 0.00010 2015 Restoration late terrestrial Scarabaeidae 5 0.02594 2015 Wetland early aquatic Chironomidae 272 0.00009 2015 Wetland early aquatic Culicidae 12 0.00022 2015 Wetland early aquatic Dolichopodidae 23 0.00074 2015 Wetland early aquatic Ephydridae 1 0.00040 2015 Wetland early aquatic Hydroptilidae 1 0.00030 2015 Wetland early aquatic Muscidae 5 0.00316 2015 Wetland early aquatic Sarcophagidae 6 0.00113 2015 Wetland early aquatic Tabanidae 1 0.00510 2015 Wetland early aquatic Tipulidae 1 0.00310 2015 Wetland late aquatic Baetidae 1 0.00010 2015 Wetland late aquatic Blephariceridae 3 0.00020 2015 Wetland late aquatic Cecidomyidae 1 0.00000 2015 Wetland late aquatic Chironomidae 115 0.00007 2015 Wetland late aquatic Dolichopodidae 2 0.00055 2015 Wetland late aquatic Empididae 1 0.00020 2015 Wetland late aquatic Ephydridae 2 0.00000 2015 Wetland late aquatic Psychodidae 1 0.00000 2015 Wetland late aquatic Tipulidae 1 0.00000 2015 Wetlands early terrestrial Apidae 1 0.02010

205

2015 Wetlands early terrestrial Cicadellidae 8 0.00040 2015 Wetlands early terrestrial Coccinellidae 1 0.00040 2015 Wetlands early terrestrial Elateridae 5 0.01620 2015 Wetlands early terrestrial Halictidae 1 0.00120 2015 Wetlands early terrestrial Latridiidae 3 0.00007 2015 Wetlands early terrestrial Miridae 4 0.00025 2015 Wetlands early terrestrial Mordellidae 1 0.01340 2015 Wetlands early terrestrial Mycetophilidae 14 0.00016 2015 Wetlands early terrestrial Stratiomyidae 2 0.00050 2015 Wetlands late terrestrial Asilidae 1 0.00220 2015 Wetlands late terrestrial Cerylonidae 2 0.00000 2015 Wetlands late terrestrial Cicadellidae 6 0.00057 2015 Wetlands late terrestrial Conopidae 1 0.00030 2015 Wetlands late terrestrial Elateridae 2 0.00745 2015 Wetlands late terrestrial Halictidae 5 0.00304 2015 Wetlands late terrestrial Hesperiidae 1 0.01880 2015 Wetlands late terrestrial Lonchaeidae 2 0.00005 2015 Wetlands late terrestrial Megaspilidae 5 0.00000 2015 Wetlands late terrestrial Mordellidae 2 0.00170 2015 Wetlands late terrestrial Mycetophilidae 6 0.00005 2015 Wetlands late terrestrial Phoridae 2 0.00015 2015 Wetlands late terrestrial Rhagionidae 2 0.00020 2015 Wetlands late terrestrial Sciaridae 5 0.00008 2015 Wetlands late terrestrial Stratiomyidae 1 0.00050 2015 Wetlands late terrestrial Xylophagidae 2 0.00195 2016 Berliner early bottom aquatic Chironomidae 78 0.00013 2016 Berliner early bottom aquatic Dytiscidae 1 0.00010 2016 Berliner early bottom aquatic Perlidae 1 0.00450 2016 Berliner early bottom aquatic Simuliidae 1 0.00010 2016 Berliner early top aquatic Braconidae 1 0.00040 2016 Berliner early top aquatic Chironomidae 571 0.00015 2016 Berliner early top aquatic Dolichopodidae 16 0.00056 2016 Berliner early top aquatic Empididae 5 0.00036 2016 Berliner early top aquatic Ephydridae 14 0.00057 2016 Berliner early top aquatic Hydroptilidae 1 0.00010 2016 Berliner early top aquatic Leptoceridae 1 0.00220 2016 Berliner early top aquatic Muscidae 3 0.00243 2016 Berliner late bottom aquatic Chironomidae 135 0.00011 2016 Berliner late bottom aquatic Dolichopodidae 3 0.00077 2016 Berliner late bottom aquatic Hydroptilidae 1 0.00020 2016 Berliner late bottom aquatic Leptoceridae 1 0.00100 2016 Berliner late bottom aquatic Muscidae 2 0.00195 206

2016 Berliner late bottom aquatic Tipulidae 1 0.00010 2016 Berliner late top aquatic Chironomidae 142 0.00008 2016 Berliner late top aquatic Dolichopodidae 2 0.00040 2016 Berliner late top aquatic Hydroptilidae 1 0.00000 2016 Berliner late top aquatic Muscidae 2 0.00355 2016 Berliner late top aquatic Platygastridae 1 0.00010 2016 Berliner late top aquatic Pteromalidae 1 0.00010 2016 Berliner late top aquatic Simuliidae 1 0.00010 2016 Berliner early bottom terrestrial Chrysomelidae 1 0.00030 2016 Berliner early bottom terrestrial Elateridae 3 0.00310 2016 Berliner early bottom terrestrial Scarabaeidae 1 0.00210 2016 Berliner early bottom terrestrial Staphylinidae 1 0.00010 2016 Berliner early top terrestrial Chrysomelidae 3 0.00190 2016 Berliner early top terrestrial Cicadellidae 150 0.00024 2016 Berliner early top terrestrial Drosophilidae 1 0.00040 2016 Berliner early top terrestrial Elateridae 9 0.00467 2016 Berliner early top terrestrial Halictidae 2 0.00390 2016 Berliner early top terrestrial Staphylinidae 1 0.00070 2016 Berliner early top terrestrial Tenthredinidae 1 0.00140 2016 Berliner late bottom terrestrial Chrysomelidae 1 0.00180 2016 Berliner late bottom terrestrial Cicadellidae 1 0.00010 2016 Berliner late bottom terrestrial Elateridae 1 0.00090 2016 Berliner late bottom terrestrial Tingidae 2 0.00025 2016 Berliner late top terrestrial Chrysomelidae 1 0.00060 2016 Berliner late top terrestrial Cicadellidae 5 0.00032 2016 Berliner late top terrestrial Curculionidae 1 0.00020 2016 Berliner late top terrestrial Elateridae 8 0.00510 2016 Berliner late top terrestrial Staphylinidae 2 0.00348 2016 Berliner late top terrestrial Tingidae 1 0.00010 2016 Darby early bottom aquatic (Unk. Lepidoptera) 1 0.00010 2016 Darby early bottom aquatic Cecidomyiidae 1 0.00000 2016 Darby early bottom aquatic Chironomidae 219 0.00008 2016 Darby early bottom aquatic Culicidae 2 0.00060 2016 Darby early bottom aquatic Dolichopodidae 10 0.00092 2016 Darby early bottom aquatic Empididae 2 0.00025 2016 Darby early bottom aquatic Heptageniidae 4 0.00155 2016 Darby early bottom aquatic Leptoceridae 3 0.00115 2016 Darby early bottom aquatic Muscidae 2 0.00495 2016 Darby early bottom aquatic Perlidae 1 0.00190 2016 Darby early bottom aquatic Philopotamidae 3 0.00129 2016 Darby early bottom aquatic Tipulidae 5 0.00072 2016 Darby early top aquatic Chironomidae 379 0.00014 207

2016 Darby early top aquatic Coenagrionidae 1 0.00680 2016 Darby early top aquatic Ephemeridae 1 0.04870 2016 Darby late bottom aquatic Chironomidae 71 0.00004 2016 Darby late bottom aquatic Heptageniidae 3 0.00210 2016 Darby late top aquatic Chironomidae 46 0.00009 2016 Darby late top aquatic Mesoveliidae 1 0.00060 2016 Darby late top aquatic Psychodidae 1 0.00040 2016 Darby late top aquatic Tipulidae 1 0.00060 2016 Darby early bottom terrestrial Apidae 2 0.01280 2016 Darby early bottom terrestrial Chrysomelidae 2 0.00115 2016 Darby early bottom terrestrial Cicadellidae 2 0.00225 2016 Darby early bottom terrestrial Drosophilidae 1 0.00010 2016 Darby early bottom terrestrial Elateridae 3 0.02560 2016 Darby early bottom terrestrial Halictidae 3 0.00183 2016 Darby early bottom terrestrial Laemophloeidae 1 0.00000 2016 Darby early bottom terrestrial Pipunculidae 1 0.00010 2016 Darby early bottom terrestrial Silvanidae 2 0.00125 2016 Darby early bottom terrestrial Staphylinidae 1 0.00230 2016 Darby early bottom terrestrial Syrphidae 1 0.00480 2016 Darby early bottom terrestrial Tenthredinidae 3 0.00043 2016 Darby early top terrestrial Apidae 3 0.01697 2016 Darby early top terrestrial Chrysomelidae 2 0.00175 2016 Darby early top terrestrial Cicadellidae 11 0.00026 2016 Darby early top terrestrial Elateridae 3 0.01003 2016 Darby early top terrestrial Halictidae 1 0.00630 2016 Darby early top terrestrial Lonchopteridae 1 0.00040 2016 Darby early top terrestrial Phengodidae 1 0.00670 2016 Darby early top terrestrial Pipunculidae 2 0.00045 2016 Darby early top terrestrial Rhagionidae 1 0.01220 2016 Darby early top terrestrial Staphylinidae 1 0.03580 2016 Darby late bottom terrestrial Aphididae 4 0.00013 2016 Darby late bottom terrestrial Chrysomelidae 1 0.00130 2016 Darby late bottom terrestrial Cicadellidae 9 0.00011 2016 Darby late top terrestrial Apidae 2 0.01700 2016 Darby late top terrestrial Cerambycidae 3 0.00097 2016 Darby late top terrestrial Chrysomelidae 2 0.00175 2016 Darby late top terrestrial Cicadellidae 380 0.00023 2016 Darby late top terrestrial Coccinellidae 1 0.00030 2016 Darby late top terrestrial Elateridae 1 0.00700 2016 Darby late top terrestrial Halictidae 4 0.00150 2016 Darby late top terrestrial Membracidae 2 0.00122 2016 Darby late top terrestrial Mycetophilidae 1 0.00010 208

2016 Darby late top terrestrial Pentatomidae 1 0.00310 2016 Darby late top terrestrial Pipunculidae 24 0.00013 2016 Darby late top terrestrial Sphaeroceridae 3 0.00003 2016 Darby late top terrestrial Stratiomyidae 1 0.00670 2016 Darby late top terrestrial Syrphidae 2 0.00163 2016 Darby late top terrestrial Tachinidae 1 0.01390 2016 Darby late top terrestrial Tenthredinidae 1 0.00165 2016 Darby late top terrestrial Tephritidae 4 0.00025 2016 Darby late top terrestrial Tingidae 1 0.00060 2016 Darby late top terrestrial Tortricydae 7 0.00956 2016 Darby late top terrestrial Vespidae 7 0.05927 2016 Fawcett early bottom aquatic Chironomidae 99 0.00009 2016 Fawcett early bottom aquatic Perlidae 3 0.00278 2016 Fawcett early top aquatic Chironomidae 435 0.00012 2016 Fawcett early top aquatic Dolichopodidae 30 0.00073 2016 Fawcett early top aquatic Ephydridae 2 0.00020 2016 Fawcett early top aquatic Leptoceridae 1 0.00110 2016 Fawcett early top aquatic Muscidae 4 0.00164 2016 Fawcett early top aquatic Perlidae 1 0.01305 2016 Fawcett early top aquatic Tipulidae 1 0.00050 2016 Fawcett late bottom aquatic Chironomidae 63 0.00009 2016 Fawcett late bottom aquatic Culicidae 1 0.00080 2016 Fawcett late bottom aquatic Formicidae 1 0.00150 2016 Fawcett late bottom aquatic Heptageniidae 2 0.00170 2016 Fawcett late bottom aquatic Muscidae 1 0.01330 2016 Fawcett late top aquatic Chironomidae 217 0.00010 2016 Fawcett late top aquatic Dolichopodidae 8 0.00072 2016 Fawcett late top aquatic Muscidae 3 0.00214 2016 Fawcett late top aquatic Tipulidae 3 0.00020 2016 Fawcett early bottom terrestrial Chrysomelidae 1 0.00010 2016 Fawcett early bottom terrestrial Cicadellidae 1 0.00010 2016 Fawcett early bottom terrestrial Elateridae 1 0.01700 2016 Fawcett early bottom terrestrial Mordellidae 1 0.00060 2016 Fawcett early bottom terrestrial Mycetophilidae 1 0.00020 2016 Fawcett early bottom terrestrial Stratiomyidae 2 0.00080 2016 Fawcett early top terrestrial Chrysomelidae 2 0.00060 2016 Fawcett early top terrestrial Formicidae 1 0.00030 2016 Fawcett early top terrestrial Lyctidae 1 0.00010 2016 Fawcett early top terrestrial Miridae 1 0.00040 2016 Fawcett early top terrestrial Scarabaeidae 2 0.00025 2016 Fawcett early top terrestrial Stratiomyidae 3 0.00100 2016 Fawcett early top terrestrial Tingidae 1 0.00090 209

2016 Fawcett late bottom terrestrial Asilidae 1 0.00220 2016 Fawcett late bottom terrestrial Cicadellidae 3 0.00017 2016 Fawcett late bottom terrestrial Elateridae 2 0.02670 2016 Fawcett late bottom terrestrial Latridiidae 1 0.00070 2016 Fawcett late bottom terrestrial Mordellidae 3 0.00067 2016 Fawcett late bottom terrestrial Mycetophilidae 1 0.00000 2016 Fawcett late bottom terrestrial Staphylinidae 3 0.00027 2016 Fawcett late bottom terrestrial Stratiomyidae 2 0.00110 2016 Fawcett late bottom terrestrial Tephritidae 1 0.00030 2016 Fawcett late bottom terrestrial Tingidae 3 0.00014 2016 Fawcett late top terrestrial Cicadellidae 1 0.00030 2016 Fawcett late top terrestrial Elateridae 1 0.00110 2016 Fawcett late top terrestrial Mordellidae 1 0.00050 2016 Highbanks early bottom aquatic Cecidomyiidae 1 0.00030 2016 Highbanks early bottom aquatic Ceratopogonidae 1 0.00000 2016 Highbanks early bottom aquatic Chironomidae 71 0.00013 2016 Highbanks early bottom aquatic Dolichopodidae 1 0.00050 2016 Highbanks early bottom aquatic Formicidae 1 0.00360 2016 Highbanks early bottom aquatic Heptageniidae 4 0.00192 2016 Highbanks early bottom aquatic Leptoceridae 1 0.00320 2016 Highbanks early bottom aquatic Leptophlebiidae 1 0.01080 2016 Highbanks early bottom aquatic Perlidae 7 0.00162 2016 Highbanks early bottom aquatic Scathophagidae 1 0.00080 2016 Highbanks early bottom aquatic Tipulidae 1 0.00110 2016 Highbanks early top aquatic Chironomidae 218 0.00006 2016 Highbanks early top aquatic Dolichopodidae 1 0.00080 2016 Highbanks early top aquatic Heptageniidae 8 0.00176 2016 Highbanks late bottom aquatic Chironomidae 11 0.00021 2016 Highbanks late top aquatic Caenidae 1 0.00030 2016 Highbanks late top aquatic Ceratopogonidae 1 0.00030 2016 Highbanks late top aquatic Chironomidae 15 0.00009 2016 Highbanks late top aquatic Dolichopodidae 2 0.00060 2016 Highbanks late top aquatic Heptageniidae 26 0.00118 2016 Highbanks late top aquatic Leptoceridae 1 0.00050 2016 Highbanks late top aquatic Muscidae 1 0.00490 2016 Highbanks early bottom terrestrial Ceraphronidae 1 0.00050 2016 Highbanks early bottom terrestrial Elateridae 1 0.00440 2016 Highbanks early bottom terrestrial Latridiidae 1 0.00020 2016 Highbanks early top terrestrial Chrysomelidae 2 0.00030 2016 Highbanks early top terrestrial Elateridae 1 0.02790 2016 Highbanks late bottom terrestrial Elateridae 2 0.01510 2016 Highbanks late top terrestrial (Unk. 1 0.00090 210

Hymenoptera) 2016 Highbanks late top terrestrial Asilidae 2 0.00440 2016 Highbanks late top terrestrial Chrysomelidae 2 0.00045 2016 Highbanks late top terrestrial Cicadellidae 18 0.00029 2016 Highbanks late top terrestrial Coccinellidae 1 0.00020 2016 Highbanks late top terrestrial Elateridae 2 0.03362 2016 Highbanks late top terrestrial Halictidae 1 0.00260 2016 Highbanks late top terrestrial Miridae 1 0.00090 2016 Highbanks late top terrestrial Mordellidae 1 0.00190 2016 Highbanks late top terrestrial Mycetophilidae 1 0.00060 2016 Highbanks late top terrestrial Tenthredinidae 1 0.00380 2016 Mussel early bottom aquatic Chironomidae 64 0.00011 2016 Mussel early bottom aquatic Dolichopodidae 2 0.00090 2016 Mussel early bottom aquatic Ephemeridae 2 0.00260 2016 Mussel early bottom aquatic Hydroptilidae 1 0.00090 2016 Mussel early top aquatic Chironomidae 58 0.00015 2016 Mussel early top aquatic Figitidae 1 0.00070 2016 Mussel early top aquatic Hydroptilidae 1 0.00030 2016 Mussel early top aquatic Muscidae 2 0.00445 2016 Mussel late bottom aquatic Chironomidae 9 0.00016 2016 Mussel late top aquatic Chironomidae 98 0.00022 2016 Mussel early bottom terrestrial Apidae 1 0.14100 2016 Mussel early bottom terrestrial Cantheridae 1 0.00160 2016 Mussel early bottom terrestrial Cicadellidae 6 0.00025 2016 Mussel early bottom terrestrial Curculionidae 2 0.00220 2016 Mussel early bottom terrestrial Elateridae 3 0.03413 2016 Mussel early bottom terrestrial Formicidae 1 0.00070 2016 Mussel early bottom terrestrial Latridiidae 2 0.00045 2016 Mussel early bottom terrestrial Scathophagidae 1 0.00370 2016 Mussel early bottom terrestrial Silvanidae 1 0.00380 2016 Mussel early bottom terrestrial Tortricydae 1 0.00060 (Unk. 2016 Mussel early top terrestrial Hymenoptera) 1 0.00040 2016 Mussel early top terrestrial Apidae 3 0.12533 2016 Mussel early top terrestrial Chrysomelidae 1 0.00180 2016 Mussel early top terrestrial Elateridae 2 0.01167 2016 Mussel early top terrestrial Formicidae 1 0.00160 2016 Mussel early top terrestrial Halictidae 1 0.00210 2016 Mussel early top terrestrial Latridiidae 2 0.00015 2016 Mussel early top terrestrial Scathophagidae 1 0.00240 2016 Mussel early top terrestrial Staphylinidae 1 0.00040 2016 Mussel late bottom terrestrial Elateridae 3 0.02501

211

2016 Mussel late bottom terrestrial Mordellidae 1 0.00060 2016 Mussel late top terrestrial Cicadellidae 1 0.00050 2016 Mussel late top terrestrial Coccinellidae 1 0.00060 2016 Mussel late top terrestrial Elateridae 1 0.01645 2016 Mussel late top terrestrial Rhagionidae 1 0.00260 2016 Restoration early bottom aquatic Caenidae 46 0.00032 2016 Restoration early bottom aquatic Chironomidae 295 0.00009 2016 Restoration early bottom aquatic Dolichopodidae 1 0.00100 2016 Restoration early bottom aquatic Leptoceridae 3 0.00087 2016 Restoration early bottom aquatic Muscidae 5 0.00738 2016 Restoration early bottom aquatic Perlidae 7 0.00211 2016 Restoration early top aquatic Chironomidae 238 0.00010 2016 Restoration early top aquatic Heptageniidae 1 0.00320 2016 Restoration early top aquatic Leptoceridae 2 0.00120 2016 Restoration early top aquatic Muscidae 1 0.01100 2016 Restoration early top aquatic Perlidae 2 0.00295 2016 Restoration late bottom aquatic Caenidae 1 0.00050 2016 Restoration late bottom aquatic Chironomidae 84 0.00012 2016 Restoration late bottom aquatic Dolichopodidae 1 0.00070 2016 Restoration late bottom aquatic Heptageniidae 1 0.00290 2016 Restoration late top aquatic (Unk. Diptera) 1 0.00220 2016 Restoration late top aquatic Chironomidae 759 0.00014 2016 Restoration late top aquatic Dolichopodidae 2 0.00105 2016 Restoration late top aquatic Heptageniidae 2 0.00098 2016 Restoration late top aquatic Muscidae 2 0.00212 2016 Restoration early bottom terrestrial Cicadellidae 2 0.00057 2016 Restoration early bottom terrestrial Elateridae 3 0.02351 2016 Restoration early bottom terrestrial Miridae 1 0.00030 2016 Restoration early bottom terrestrial Mordellidae 1 0.00040 2016 Restoration early top terrestrial Cicadellidae 7 0.00026 2016 Restoration early top terrestrial Formicidae 1 0.00140 2016 Restoration early top terrestrial Miridae 1 0.00070 2016 Restoration late bottom terrestrial Apidae 1 0.02140 2016 Restoration late bottom terrestrial Chrysomelidae 2 0.00025 2016 Restoration late bottom terrestrial Elateridae 1 0.00180 2016 Restoration late bottom terrestrial Latridiidae 1 0.00020 2016 Restoration late bottom terrestrial Scarabaeidae 1 0.02350 2016 Wetlands early bottom aquatic Chironomidae 60 0.00019 2016 Wetlands early bottom aquatic Dolichopodidae 2 0.00075 2016 Wetlands early bottom aquatic Ephydridae 1 0.00010 2016 Wetlands early bottom aquatic Perlidae 1 0.00140 2016 Wetlands early top aquatic (Unk. 2 0.00060 212

Hymenoptera) 2016 Wetlands early top aquatic Chironomidae 97 0.00023 2016 Wetlands early top aquatic Dolichopodidae 21 0.00101 2016 Wetlands early top aquatic Muscidae 3 0.00213 2016 Wetlands early top aquatic Perlidae 8 0.00269 2016 Wetlands early top aquatic Tipulidae 1 0.01020 2016 Wetlands late bottom aquatic Chironomidae 218 0.00011 2016 Wetlands late bottom aquatic Dolichopodidae 1 0.00120 2016 Wetlands late bottom aquatic Ephydridae 5 0.00014 2016 Wetlands late top aquatic Chironomidae 58 0.00011 2016 Wetlands late top aquatic Culicidae 2 0.00065 2016 Wetlands late top aquatic Heptageniidae 3 0.01078 2016 Wetlands late top aquatic Tipulidae 1 0.00060 2016 Wetlands early bottom terrestrial (Unk. Hemiptera) 1 0.00030 (Unk. 2016 Wetlands early bottom terrestrial Hymenoptera) 0 0.00000 2016 Wetlands early bottom terrestrial Agromyzidae 1 0.00090 2016 Wetlands early bottom terrestrial Aphididae 1 0.00060 2016 Wetlands early bottom terrestrial Apidae 3 0.13820 2016 Wetlands early bottom terrestrial Chloropidae 1 0.00060 2016 Wetlands early bottom terrestrial Chrysomelidae 1 0.00060 2016 Wetlands early bottom terrestrial Chrysopidae 1 0.00370 2016 Wetlands early bottom terrestrial Cicadellidae 16 0.00101 2016 Wetlands early bottom terrestrial Curculionidae 1 0.00100 2016 Wetlands early bottom terrestrial Elateridae 2 0.01042 2016 Wetlands early bottom terrestrial Halictidae 4 0.00227 2016 Wetlands early bottom terrestrial Lauxanidae 2 0.00060 2016 Wetlands early bottom terrestrial Mordellidae 6 0.00198 2016 Wetlands early bottom terrestrial Pipunculidae 1 0.00180 2016 Wetlands early bottom terrestrial Scathophagidae 1 0.00570 2016 Wetlands early bottom terrestrial Silvanidae 2 0.00060 2016 Wetlands early bottom terrestrial Syrphidae 2 0.00105 2016 Wetlands early bottom terrestrial Xylomyidae 2 0.00170 2016 Wetlands early top terrestrial Cicadellidae 3 0.00040 2016 Wetlands early top terrestrial Coccinellidae 1 0.00110 2016 Wetlands early top terrestrial Elateridae 1 0.01180 2016 Wetlands early top terrestrial Lampyridae 1 0.00040 2016 Wetlands early top terrestrial Megaspilidae 1 0.00130 2016 Wetlands early top terrestrial Miridae 1 0.00050 2016 Wetlands early top terrestrial Staphylinidae 1 0.00095 2016 Wetlands early top terrestrial Tachinidae 4 0.00055 2016 Wetlands late bottom terrestrial Cicadellidae 6 0.00073

213

2016 Wetlands late bottom terrestrial Coccinellidae 1 0.00050 2016 Wetlands late bottom terrestrial Formicidae 1 0.00080 2016 Wetlands late bottom terrestrial Mordellidae 2 0.00105 2016 Wetlands late bottom terrestrial Mycetophilidae 1 0.00060 2016 Wetlands late top terrestrial Cicadellidae 1 0.00020 2016 Wetlands late top terrestrial Curculionidae 1 0.00050 2016 Wetlands late top terrestrial Mordellidae 1 0.00110 2016 Wetlands late top terrestrial Tachinidae 1 0.00090 2016 Wetlands late top terrestrial Tephritidae 1 0.00010 2017 Berliner early bottom aquatic Cecidomyiidae 1 0.00000 2017 Berliner early bottom aquatic Chironomidae 111 0.00015 2017 Berliner early bottom aquatic Dolichopodidae 1 0.00190 2017 Berliner early bottom aquatic Simuliidae 1 0.00010 2017 Berliner early bottom aquatic Tanyderidae 1 0.00040 2017 Berliner early bottom aquatic Tipulidae 1 0.00050 2017 Berliner early top aquatic Chironomidae 87 0.00022 2017 Berliner early top aquatic Perlidae 1 0.00210 2017 Berliner late bottom aquatic Cecidomyiidae 1 0.00010 2017 Berliner late bottom aquatic Chironomidae 81 0.00007 2017 Berliner late bottom aquatic Mymaridae 1 0.00020 2017 Berliner late top aquatic Cecidomyiidae 1 0.00030 2017 Berliner late top aquatic Ceratopogonidae 1 0.00020 2017 Berliner late top aquatic Chironomidae 220 0.00009 2017 Berliner late top aquatic Dolichopodidae 2 0.00105 2017 Berliner late top aquatic Hydroptilidae 3 0.00010 2017 Berliner early bottom terrestrial Aphididae 4 0.00008 2017 Berliner early bottom terrestrial Bibionidae 1 0.00310 2017 Berliner early bottom terrestrial Chrysomelidae 4 0.00163 2017 Berliner early bottom terrestrial Cicadellidae 11 0.00019 2017 Berliner early bottom terrestrial Elateridae 16 0.00097 2017 Berliner early bottom terrestrial Formicidae 1 0.00500 2017 Berliner early bottom terrestrial Mordellidae 1 0.00020 2017 Berliner early bottom terrestrial Pipunculidae 1 0.00090 2017 Berliner early bottom terrestrial Sciaridae 3 0.00007 2017 Berliner early bottom terrestrial Tortricydae 2 0.00075 2017 Berliner early top terrestrial Agromyzidae 1 0.00020 2017 Berliner early top terrestrial Aphididae 7 0.00010 2017 Berliner early top terrestrial Bibionidae 1 0.00320 2017 Berliner early top terrestrial Chrysomelidae 7 0.00156 2017 Berliner early top terrestrial Cicadellidae 53 0.00020 2017 Berliner early top terrestrial Coccinellidae 1 0.00280 2017 Berliner early top terrestrial Elateridae 29 0.00090 214

2017 Berliner early top terrestrial Halictidae 2 0.00020 2017 Berliner early top terrestrial Lampyridae 1 0.00340 2017 Berliner early top terrestrial Latriididae 3 0.00003 2017 Berliner early top terrestrial Mordellidae 2 0.00035 2017 Berliner early top terrestrial Nitidulidae 1 0.00060 2017 Berliner early top terrestrial Phoridae 4 0.00007 2017 Berliner early top terrestrial Sciaridae 1 0.00060 2017 Berliner early top terrestrial Sepsidae 1 0.00080 2017 Berliner early top terrestrial Staphylinidae 2 0.00010 2017 Berliner early top terrestrial Stratiomyidae 1 0.00150 2017 Berliner early top terrestrial Syrphidae 1 0.00170 2017 Berliner early top terrestrial Tortricydae 1 0.00110 2017 Berliner late bottom terrestrial Asilidae 1 0.00290 2017 Berliner late bottom terrestrial Chrysomelidae 1 0.00200 2017 Berliner late bottom terrestrial Cicadellidae 1 0.00050 2017 Berliner late bottom terrestrial Elateridae 1 0.00190 2017 Berliner late bottom terrestrial Mordellidae 1 0.00120 2017 Berliner late bottom terrestrial 1 0.00040 2017 Berliner late top terrestrial (Unk. Lepidoptera) 1 0.00000 2017 Berliner late top terrestrial Bethylidae 1 0.00010 2017 Berliner late top terrestrial Cicadellidae 4 0.00015 2017 Berliner late top terrestrial Elateridae 1 0.02860 2017 Berliner late top terrestrial Formicidae 1 0.00380 (Unk. 2017 Darby early bottom aquatic Ephemeroptera) 1 0.00090 2017 Darby early bottom aquatic Chironomidae 381 0.00012 2017 Darby early bottom aquatic Leptoceridae 2 0.00125 2017 Darby early bottom aquatic Peltoperlidae 3 0.00327 2017 Darby early bottom aquatic Perlidae 6 0.00434 2017 Darby early bottom aquatic Psychodidae 1 0.00040 2017 Darby early bottom aquatic Simuliidae 1 0.00080 2017 Darby early bottom aquatic Tipulidae 1 0.00060 2017 Darby early top aquatic Ceratopogonidae 6 0.00011 2017 Darby early top aquatic Chironomidae 113 0.00014 2017 Darby early top aquatic Ephydridae 1 0.00060 2017 Darby early top aquatic Tipulidae 1 0.00150 2017 Darby late bottom aquatic Chironomidae 13 0.00024 2017 Darby late bottom aquatic Hydroptilidae 1 0.00020 2017 Darby late bottom aquatic Muscidae 1 0.00000 2017 Darby late top aquatic Braconidae 1 0.00150 2017 Darby late top aquatic Ceratopogonidae 1 0.00010 2017 Darby late top aquatic Chironomidae 38 0.00009

215

2017 Darby late top aquatic Dolichopodidae 1 0.00030 2017 Darby late top aquatic Platygastridae 1 0.00020 2017 Darby late top aquatic Tachinidae 1 0.00050 2017 Darby early bottom terrestrial (Unk. Diptera) 4 0.00023 2017 Darby early bottom terrestrial (Unk. Lepidoptera) 1 0.00120 2017 Darby early bottom terrestrial Apidae 4 0.04110 2017 Darby early bottom terrestrial Chrysomelidae 2 0.00127 2017 Darby early bottom terrestrial Cicadellidae 4 0.00021 2017 Darby early bottom terrestrial Curculionidae 2 0.00200 2017 Darby early bottom terrestrial Elateridae 9 0.00806 2017 Darby early bottom terrestrial Heleomyzidae 1 0.00520 2017 Darby early bottom terrestrial Latridiidae 6 0.00012 2017 Darby early bottom terrestrial Megaspilidae 1 0.00000 2017 Darby early bottom terrestrial Mordellidae 1 0.00040 2017 Darby early bottom terrestrial Mycetophilidae 1 0.00050 2017 Darby early bottom terrestrial Phoridae 2 0.00015 2017 Darby early bottom terrestrial Psocidae 2 0.00032 2017 Darby early bottom terrestrial Pyralidae 2 0.00445 2017 Darby early bottom terrestrial Sarcophagidae 1 0.00210 2017 Darby early bottom terrestrial Stratiomyidae 2 0.00220 2017 Darby early bottom terrestrial Tachinidae 1 0.00310 2017 Darby early bottom terrestrial Tenthredinidae 1 0.00070 2017 Darby early top terrestrial Aphididae 1 0.00000 2017 Darby early top terrestrial Chrysomelidae 6 0.00072 2017 Darby early top terrestrial Cicadellidae 3 0.00197 2017 Darby early top terrestrial Coccinellidae 1 0.00030 2017 Darby early top terrestrial Elateridae 5 0.01190 2017 Darby early top terrestrial Mordellidae 1 0.00080 2017 Darby early top terrestrial Tingidae 1 0.00070 2017 Darby late bottom terrestrial Chloropidae 1 0.00000 2017 Darby late bottom terrestrial Chrysomelidae 1 0.00020 2017 Darby late bottom terrestrial Cicadellidae 4 0.00010 2017 Darby late bottom terrestrial Coccinellidae 1 0.00030 2017 Darby late bottom terrestrial Culicidae 1 0.00100 2017 Darby late bottom terrestrial Elateridae 2 0.01868 2017 Darby late bottom terrestrial Mordellidae 1 0.00180 2017 Darby late bottom terrestrial Phoridae 1 0.00000 2017 Darby late bottom terrestrial Psocidae 3 0.00003 2017 Darby late bottom terrestrial Rhagionidae 3 0.00087 2017 Darby late top terrestrial (Unk. Lepidoptera) 1 0.00170 2017 Darby late top terrestrial Asilidae 17 0.00218 2017 Darby late top terrestrial Cicadellidae 74 0.00014 216

2017 Darby late top terrestrial Curculionidae 2 0.00055 2017 Darby late top terrestrial Elateridae 9 0.02190 2017 Darby late top terrestrial Evaniidae 2 0.00040 2017 Darby late top terrestrial Halictidae 2 0.00125 2017 Darby late top terrestrial Megaspilidae 5 0.00024 2017 Darby late top terrestrial Mordellidae 5 0.00118 2017 Darby late top terrestrial Phoridae 1 0.00030 2017 Darby late top terrestrial Pipunculidae 1 0.00040 2017 Darby late top terrestrial Psocidae 3 0.00010 2017 Darby late top terrestrial Staphylinidae 2 0.00430 2017 Darby late top terrestrial Stratiomyidae 4 0.00135 2017 Darby late top terrestrial Syrphidae 1 0.08250 2017 Darby late top terrestrial Tenthredinidae 1 0.00330 2017 Fawcett early bottom aquatic Cecidomyiidae 1 0.00000 2017 Fawcett early bottom aquatic Chironomidae 67 0.00011 2017 Fawcett early bottom aquatic Empididae 1 0.00070 2017 Fawcett early bottom aquatic Ephydridae 1 0.00030 2017 Fawcett early bottom aquatic Pteromalidae 1 0.00010 2017 Fawcett early top aquatic Ceratopogonidae 3 0.00010 2017 Fawcett early top aquatic Chironomidae 30 0.00013 2017 Fawcett early top aquatic Dolichopodidae 1 0.00150 2017 Fawcett early top aquatic Leptoceridae 1 0.00180 2017 Fawcett late bottom aquatic Chironomidae 20 0.00007 2017 Fawcett late bottom aquatic Culicidae 1 0.00030 2017 Fawcett late bottom aquatic Dolichopodidae 1 0.00050 2017 Fawcett late bottom aquatic Pteromalidae 1 0.00030 2017 Fawcett late bottom aquatic Scathophagidae 1 0.00100 2017 Fawcett late top aquatic Cecidomyiidae 6 0.00007 2017 Fawcett late top aquatic Ceratopogonidae 3 0.00010 2017 Fawcett late top aquatic Chironomidae 16 0.00010 2017 Fawcett late top aquatic Dolichopodidae 1 0.00090 2017 Fawcett early bottom terrestrial Cicadellidae 6 0.00017 2017 Fawcett early bottom terrestrial Curculionidae 1 0.00030 2017 Fawcett early bottom terrestrial Elateridae 2 0.00085 2017 Fawcett early bottom terrestrial Latridiidae 8 0.00009 2017 Fawcett early bottom terrestrial Mordellidae 1 0.00070 2017 Fawcett early bottom terrestrial Phoridae 2 0.00005 2017 Fawcett early bottom terrestrial Psocidae 1 0.00010 2017 Fawcett early bottom terrestrial Scarabaeidae 4 0.01510 2017 Fawcett early bottom terrestrial Staphylinidae 1 0.00050 2017 Fawcett early top terrestrial (Unk. Lepidoptera) 1 0.00100 2017 Fawcett early top terrestrial Apidae 1 0.00460 217

2017 Fawcett early top terrestrial Chrysomelidae 1 0.00130 2017 Fawcett early top terrestrial Cicadellidae 3 0.00032 2017 Fawcett early top terrestrial Elateridae 5 0.00203 2017 Fawcett early top terrestrial Latridiidae 4 0.00018 2017 Fawcett early top terrestrial Megaspilidae 3 0.00013 2017 Fawcett early top terrestrial Miridae 3 0.00055 2017 Fawcett early top terrestrial Mordellidae 1 0.00055 2017 Fawcett early top terrestrial Mycetophilidae 1 0.00040 2017 Fawcett early top terrestrial Phoridae 5 0.00021 2017 Fawcett early top terrestrial Pipunculidae 1 0.00120 2017 Fawcett early top terrestrial Psocidae 1 0.00070 2017 Fawcett early top terrestrial Scarabaeidae 5 0.01651 2017 Fawcett early top terrestrial Sciaridae 1 0.00070 2017 Fawcett early top terrestrial Sepsidae 1 0.00100 2017 Fawcett early top terrestrial Sphaerocidae 2 0.00040 2017 Fawcett early top terrestrial Staphylinidae 1 0.00020 2017 Fawcett early top terrestrial Tenthredinidae 1 0.00230 2017 Fawcett late bottom terrestrial (Unk. Lepidoptera) 8 0.00249 2017 Fawcett late bottom terrestrial Cicadellidae 4 0.00024 2017 Fawcett late bottom terrestrial Elateridae 1 0.00650 2017 Fawcett late bottom terrestrial Mordellidae 3 0.00064 2017 Fawcett late bottom terrestrial Phoridae 1 0.00030 2017 Fawcett late bottom terrestrial Scarabaeidae 4 0.01580 2017 Fawcett late bottom terrestrial Sciaridae 1 0.00020 2017 Fawcett late top terrestrial (Unk. Lepidoptera) 2 0.00115 2017 Fawcett late top terrestrial Aphididae 1 0.00030 2017 Fawcett late top terrestrial Cicadellidae 1 0.00030 2017 Fawcett late top terrestrial Curculionidae 1 0.00000 2017 Fawcett late top terrestrial Elateridae 2 0.00045 2017 Fawcett late top terrestrial Latridiidae 1 0.00020 2017 Fawcett late top terrestrial Megaspilidae 1 0.00040 2017 Fawcett late top terrestrial Phoridae 1 0.00010 2017 Fawcett late top terrestrial Sciaridae 1 0.00040 2017 Highbanks early bottom aquatic Cecidomyiidae 5 0.00010 2017 Highbanks early bottom aquatic Ceratopogonidae 4 0.00012 2017 Highbanks early bottom aquatic Chironomidae 25 0.00009 2017 Highbanks early bottom aquatic Culicidae 2 0.00040 2017 Highbanks early bottom aquatic Dolichopodidae 7 0.00039 2017 Highbanks early bottom aquatic Ephydridae 1 0.00040 2017 Highbanks early bottom aquatic Peltoperlidae 1 0.00145 2017 Highbanks early bottom aquatic Tipulidae 11 0.00251 2017 Highbanks early top aquatic (Unk. Diptera) 1 0.00050 218

2017 Highbanks early top aquatic Cecidomyiidae 1 0.00020 2017 Highbanks early top aquatic Ceratopogonidae 7 0.00005 2017 Highbanks early top aquatic Chironomidae 26 0.00004 2017 Highbanks early top aquatic Ephydridae 1 0.00030 2017 Highbanks early top aquatic Leptoceridae 1 0.00160 2017 Highbanks early top aquatic Simuliidae 1 0.00010 2017 Highbanks late bottom aquatic Cecidomyiidae 1 0.00000 2017 Highbanks late bottom aquatic Ceratopogonidae 13 0.00002 2017 Highbanks late bottom aquatic Chironomidae 32 0.00005 2017 Highbanks late bottom aquatic Dolichopodidae 4 0.00090 2017 Highbanks late bottom aquatic Empididae 2 0.00115 2017 Highbanks late bottom aquatic Heptageniidae 3 0.00120 2017 Highbanks late bottom aquatic Muscidae 1 0.00850 2017 Highbanks late bottom aquatic Psychodidae 1 0.00020 2017 Highbanks late bottom aquatic Pteromalidae 1 0.00020 2017 Highbanks late top aquatic Ceratopogonidae 5 0.00001 2017 Highbanks late top aquatic Chironomidae 43 0.00010 2017 Highbanks late top aquatic Culicidae 3 0.00047 2017 Highbanks late top aquatic Dolichopodidae 2 0.00030 2017 Highbanks late top aquatic Hydroptilidae 1 0.00010 2017 Highbanks late top aquatic Leptoceridae 1 0.00150 2017 Highbanks early bottom terrestrial Agromyzidae 1 0.00010 2017 Highbanks early bottom terrestrial Bibionidae 1 0.00700 2017 Highbanks early bottom terrestrial Cicadellidae 3 0.00022 2017 Highbanks early bottom terrestrial Diapriidae 1 0.00020 2017 Highbanks early bottom terrestrial Elateridae 3 0.01520 2017 Highbanks early bottom terrestrial Lampyridae 2 0.00265 2017 Highbanks early bottom terrestrial Latridiidae 1 0.00010 2017 Highbanks early bottom terrestrial Miridae 2 0.00030 2017 Highbanks early bottom terrestrial Noctuidae 2 0.00040 2017 Highbanks early bottom terrestrial Pipunculidae 3 0.00033 2017 Highbanks early bottom terrestrial Psocidae 1 0.00040 2017 Highbanks early bottom terrestrial Reduviidae 1 0.00190 2017 Highbanks early bottom terrestrial Sphaerocidae 1 0.00040 2017 Highbanks early bottom terrestrial Stratiomyidae 1 0.00160 2017 Highbanks early top terrestrial Aphididae 1 0.00020 2017 Highbanks early top terrestrial Asilidae 1 0.00230 2017 Highbanks early top terrestrial Bibionidae 1 0.00670 2017 Highbanks early top terrestrial Bruchidae 2 0.00040 2017 Highbanks early top terrestrial Cerambycidae 5 0.00020 2017 Highbanks early top terrestrial Cicadellidae 3 0.00015 2017 Highbanks early top terrestrial Elateridae 1 0.01900 219

2017 Highbanks early top terrestrial Latridiidae 2 0.00018 2017 Highbanks early top terrestrial Megaspilidae 4 0.00020 2017 Highbanks early top terrestrial Mordellidae 1 0.00070 2017 Highbanks early top terrestrial Phoridae 9 0.00031 2017 Highbanks early top terrestrial Pipunculidae 1 0.00170 2017 Highbanks early top terrestrial Psocidae 2 0.00045 2017 Highbanks early top terrestrial Staphylinidae 2 0.00055 2017 Highbanks late bottom terrestrial Agromyzidae 1 0.00020 2017 Highbanks late bottom terrestrial Cicadellidae 5 0.00014 2017 Highbanks late bottom terrestrial Elateridae 3 0.02347 2017 Highbanks late bottom terrestrial Phoridae 1 0.00020 2017 Highbanks late bottom terrestrial Pterophoridae 1 0.00280 2017 Highbanks late top terrestrial Asilidae 1 0.01580 2017 Highbanks late top terrestrial Cicadellidae 3 0.00014 2017 Highbanks late top terrestrial Curculionidae 1 0.00110 2017 Highbanks late top terrestrial Elateridae 3 0.01924 2017 Highbanks late top terrestrial Mordellidae 3 0.00098 2017 Highbanks late top terrestrial Phoridae 2 0.00010 2017 Highbanks late top terrestrial Pipunculidae 1 0.00280 2017 Highbanks late top terrestrial Psocidae 2 0.00010 2017 Highbanks late top terrestrial Stratiomyidae 1 0.00080 2017 Mussel early bottom aquatic Cecidomyiidae 4 0.00008 2017 Mussel early bottom aquatic Chironomidae 75 0.00010 2017 Mussel early bottom aquatic Ephemeridae 1 0.00240 2017 Mussel early bottom aquatic Leptophlebiidae 2 0.00035 2017 Mussel early top aquatic Cecidomyiidae 1 0.00010 2017 Mussel early top aquatic Chironomidae 59 0.00020 2017 Mussel early top aquatic Dolichopodidae 1 0.00040 2017 Mussel late bottom aquatic Cecidomyiidae 1 0.00000 2017 Mussel late bottom aquatic Chironomidae 54 0.00007 2017 Mussel late top aquatic Chironomidae 69 0.00009 2017 Mussel early bottom terrestrial Anthomyiidae 2 0.00075 2017 Mussel early bottom terrestrial Aphididae 4 0.00002 2017 Mussel early bottom terrestrial Cicadellidae 2 0.00015 2017 Mussel early bottom terrestrial Cicadidae 2 0.17033 2017 Mussel early bottom terrestrial Derodontidae 1 0.00090 2017 Mussel early bottom terrestrial Elateridae 6 0.01951 2017 Mussel early bottom terrestrial Encyrtidae 1 0.00000 2017 Mussel early bottom terrestrial Faniidae 1 0.00110 2017 Mussel early bottom terrestrial Formicidae 1 0.00050 2017 Mussel early bottom terrestrial Megaspilidae 1 0.00000 2017 Mussel early bottom terrestrial Miridae 1 0.00090 220

2017 Mussel early bottom terrestrial Mycetophilidae 1 0.00220 2017 Mussel early bottom terrestrial Pentatomidae 2 0.05670 2017 Mussel early bottom terrestrial Phoridae 1 0.00000 2017 Mussel early bottom terrestrial Scarabaeidae 2 0.01970 2017 Mussel early bottom terrestrial Sciaridae 8 0.00016 2017 Mussel early bottom terrestrial Silvanidae 1 0.00110 2017 Mussel early top terrestrial 1 0.00000 2017 Mussel early top terrestrial Anthomyiidae 1 0.00120 2017 Mussel early top terrestrial Cicadellidae 1 0.00010 2017 Mussel early top terrestrial Elateridae 4 0.01197 2017 Mussel early top terrestrial Formicidae 4 0.02630 2017 Mussel early top terrestrial Megaspilidae 1 0.00000 2017 Mussel early top terrestrial Meloidae 1 0.00040 2017 Mussel early top terrestrial Orsodacnidae 1 0.00610 2017 Mussel early top terrestrial Sciaridae 2 0.00030 2017 Mussel early top terrestrial Silvanidae 1 0.00070 2017 Mussel late bottom terrestrial Gryllidae 1 0.01510 2017 Mussel late top terrestrial Elateridae 1 0.00080 2017 Mussel late top terrestrial Megaspilidae 1 0.00010 2017 Restoration early bottom aquatic Chironomidae 21 0.00011 2017 Restoration early bottom aquatic Ephydridae 3 0.00167 2017 Restoration early bottom aquatic Tipulidae 1 0.00100 2017 Restoration early top aquatic Chironomidae 286 0.00009 2017 Restoration early top aquatic Dolichopodidae 2 0.00070 2017 Restoration early top aquatic Ephydridae 4 0.00122 2017 Restoration early top aquatic Muscidae 4 0.00243 2017 Restoration early top aquatic Perlidae 1 0.00530 2017 Restoration late bottom aquatic Cecidomyiidae 2 0.00000 2017 Restoration late bottom aquatic Chironomidae 42 0.00007 2017 Restoration late bottom aquatic Dolichopodidae 8 0.00045 2017 Restoration late bottom aquatic Heptageniidae 1 0.00080 2017 Restoration late bottom aquatic Muscidae 2 0.00145 2017 Restoration late bottom aquatic Tipulidae 2 0.00015 2017 Restoration late top aquatic Baetidae 1 0.00055 2017 Restoration late top aquatic Cecidomyiidae 1 0.00000 2017 Restoration late top aquatic Chironomidae 73 0.00006 2017 Restoration late top aquatic Dolichopodidae 2 0.00085 2017 Restoration late top aquatic Ephydridae 1 0.00020 2017 Restoration late top aquatic Hydroptilidae 1 0.00010 2017 Restoration late top aquatic Muscidae 2 0.00345 2017 Restoration late top aquatic Scathophagidae 1 0.00270 2017 Restoration late top aquatic Simuliidae 2 0.00265 221

2017 Restoration late top aquatic Tipulidae 1 0.00040 2017 Restoration early bottom terrestrial Cicadellidae 2 0.00025 2017 Restoration early bottom terrestrial Curculionidae 1 0.00030 2017 Restoration early bottom terrestrial Elateridae 2 0.00558 2017 Restoration early bottom terrestrial Latridiidae 3 0.00013 2017 Restoration early bottom terrestrial Miridae 6 0.00027 2017 Restoration early bottom terrestrial Mordellidae 1 0.00025 2017 Restoration early bottom terrestrial Mycetophilidae 2 0.00080 2017 Restoration early bottom terrestrial Phoridae 1 0.00000 2017 Restoration early bottom terrestrial Psocidae 1 0.00020 2017 Restoration early bottom terrestrial Sciaridae 5 0.00017 2017 Restoration early bottom terrestrial Staphylinidae 1 0.00000 2017 Restoration early bottom terrestrial Syrphidae 1 0.00040 2017 Restoration early bottom terrestrial Tachinidae 1 0.00450 2017 Restoration early top terrestrial Aphididae 1 0.00000 2017 Restoration early top terrestrial Apidae 2 0.03125 2017 Restoration early top terrestrial Cicadellidae 5 0.00034 2017 Restoration early top terrestrial Coccinellidae 2 0.00030 2017 Restoration early top terrestrial Elateridae 1 0.01570 2017 Restoration early top terrestrial Latridiidae 6 0.00012 2017 Restoration early top terrestrial Megaspilidae 2 0.00018 2017 Restoration early top terrestrial Mycetophilidae 1 0.00050 2017 Restoration early top terrestrial Phoridae 3 0.00020 2017 Restoration early top terrestrial Syrphidae 2 0.00175 2017 Restoration late bottom terrestrial (Unk. Lepidoptera) 2 0.00200 2017 Restoration late bottom terrestrial Coccinellidae 1 0.00100 2017 Restoration late bottom terrestrial Curculionidae 1 0.00100 2017 Restoration late bottom terrestrial Elateridae 1 0.00900 2017 Restoration late bottom terrestrial Halictidae 1 0.00225 2017 Restoration late bottom terrestrial Lampyridae 1 0.00800 2017 Restoration late bottom terrestrial Latridiidae 2 0.00030 2017 Restoration late bottom terrestrial Megaspilidae 2 0.00050 2017 Restoration late bottom terrestrial Mordellidae 2 0.00012 2017 Restoration late bottom terrestrial Scarabaeidae 1 0.02010 2017 Restoration late top terrestrial Cicadellidae 1 0.00000 2017 Restoration late top terrestrial Elateridae 1 0.00050 2017 Restoration late top terrestrial Miridae 1 0.00010 2017 Restoration late top terrestrial Mordellidae 1 0.00030 2017 Restoration late top terrestrial Phoridae 1 0.00000 2017 Restoration late top terrestrial Tingidae 1 0.00000 2017 Wetlands early bottom aquatic Cecidomyiidae 9 0.00004 2017 Wetlands early bottom aquatic Ceratopogonidae 1 0.00010 222

2017 Wetlands early bottom aquatic Chironomidae 52 0.00013 2017 Wetlands early bottom aquatic Culicidae 1 0.00140 2017 Wetlands early bottom aquatic Dolichopodidae 2 0.00110 2017 Wetlands early bottom aquatic Muscidae 2 0.00333 2017 Wetlands early bottom aquatic Perlidae 1 0.00170 2017 Wetlands early bottom aquatic Simuliidae 1 0.00060 2017 Wetlands early bottom aquatic Tipulidae 4 0.01138 2017 Wetlands early top aquatic Cecidomyiidae 5 0.00016 2017 Wetlands early top aquatic Ceratopogonidae 1 0.00030 2017 Wetlands early top aquatic Chironomidae 137 0.00010 2017 Wetlands early top aquatic Culicidae 2 0.00045 2017 Wetlands early top aquatic Dytiscidae 1 0.01550 2017 Wetlands early top aquatic Perlidae 8 0.00247 2017 Wetlands early top aquatic Simuliidae 1 0.00030 2017 Wetlands early top aquatic Tipulidae 1 0.00420 2017 Wetlands late bottom aquatic Ceratopogonidae 2 0.00005 2017 Wetlands late bottom aquatic Chironomidae 24 0.00008 2017 Wetlands late bottom aquatic Ephydridae 1 0.00010 2017 Wetlands late bottom aquatic Pteromalidae 1 0.00000 2017 Wetlands late top aquatic Braconidae 1 0.00000 2017 Wetlands late top aquatic Cecidomyiidae 4 0.00002 2017 Wetlands late top aquatic Chironomidae 30 0.00009 2017 Wetlands late top aquatic Dolichopodidae 3 0.00107 2017 Wetlands late top aquatic Simuliidae 1 0.00020 2017 Wetlands late top aquatic Tipulidae 1 0.00030 2017 Wetlands early bottom terrestrial Aphididae 2 0.00010 2017 Wetlands early bottom terrestrial Cicadellidae 15 0.00027 2017 Wetlands early bottom terrestrial Curculionidae 1 0.00040 2017 Wetlands early bottom terrestrial Elateridae 1 0.01550 2017 Wetlands early bottom terrestrial Halictidae 1 0.00720 2017 Wetlands early bottom terrestrial Miridae 2 0.00085 2017 Wetlands early bottom terrestrial Mordellidae 1 0.00040 2017 Wetlands early bottom terrestrial Phoridae 3 0.00013 2017 Wetlands early bottom terrestrial Proctotrupidae 1 0.00050 2017 Wetlands early bottom terrestrial Sciaridae 9 0.00037 2017 Wetlands early bottom terrestrial Staphylinidae 1 0.03740 2017 Wetlands early bottom terrestrial Xylophagidae 1 0.00100 2017 Wetlands early top terrestrial Cicadellidae 2 0.00030 2017 Wetlands early top terrestrial Elateridae 5 0.01517 2017 Wetlands early top terrestrial Megaspilidae 1 0.00010 2017 Wetlands early top terrestrial Miridae 2 0.00105 2017 Wetlands early top terrestrial Mordellidae 2 0.00060 223

2017 Wetlands early top terrestrial Mycetophilidae 1 0.00040 2017 Wetlands early top terrestrial Nitidulidae 1 0.00015 2017 Wetlands early top terrestrial Proctotrupidae 1 0.00050 2017 Wetlands early top terrestrial Pterophoridae 1 0.00090 2017 Wetlands early top terrestrial Pyrochroidae 1 0.00070 2017 Wetlands early top terrestrial Sciaridae 2 0.00120 2017 Wetlands early top terrestrial Staphylinidae 1 0.00040 2017 Wetlands early top terrestrial Syrphidae 1 0.00090 2017 Wetlands late bottom terrestrial Agromyzidae 1 0.00260 2017 Wetlands late bottom terrestrial Asilidae 6 0.00194 2017 Wetlands late bottom terrestrial Berytidae 1 0.00020 2017 Wetlands late bottom terrestrial Cicadellidae 20 0.00014 2017 Wetlands late bottom terrestrial Elateridae 2 0.02512 2017 Wetlands late bottom terrestrial Lampyridae 3 0.00383 2017 Wetlands late bottom terrestrial Mordellidae 1 0.00110 2017 Wetlands late bottom terrestrial Noctuidae 3 0.00113 2017 Wetlands late bottom terrestrial Psocidae 6 0.00007 2017 Wetlands late bottom terrestrial Pyralidae 3 0.00335 2017 Wetlands late bottom terrestrial Sciomyzidae 5 0.00036 2017 Wetlands late bottom terrestrial Stratiomyidae 3 0.00163 2017 Wetlands late bottom terrestrial Tortricydae 3 0.00420 2017 Wetlands late top terrestrial Aphididae 6 0.00005 2017 Wetlands late top terrestrial Asilidae 1 0.00315 2017 Wetlands late top terrestrial Carnidae 1 0.00000 2017 Wetlands late top terrestrial Cicadellidae 23 0.00008 2017 Wetlands late top terrestrial Diapriidae 1 0.00010 2017 Wetlands late top terrestrial Elateridae 2 0.01013 2017 Wetlands late top terrestrial Latridiidae 2 0.00018 2017 Wetlands late top terrestrial Mordellidae 3 0.00061 2017 Wetlands late top terrestrial Noctuidae 1 0.00420 2017 Wetlands late top terrestrial Phoridae 1 0.00000 2017 Wetlands late top terrestrial 4 0.00000 2017 Wetlands late top terrestrial Psocidae 1 0.00010 2017 Wetlands late top terrestrial Rhagionidae 2 0.00070 2017 Wetlands late top terrestrial Sciaridae 1 0.00010 2017 Wetlands late top terrestrial Sepsidae 1 0.00040 2017 Wetlands late top terrestrial Staphylinidae 1 0.00050 2017 Wetlands late top terrestrial Stratiomyidae 1 0.00070

224

Appendix B. Chapter 3: Supplemental Material

225

Table B.1 Carbon (ẟ13C) and nitrogen (ẟ15N) isotopic signatures for Tree Swallows.

Source 13C 15N Site Year Nestbox Tree Swallow, adult -26.65 13.41 Berl 2016 D Tree Swallow, adult -26.76 13.34 Berl 2016 E Tree Swallow, adult -26.85 12.69 Berl 2017 A Tree Swallow, adult -26.46 12.26 Berl 2017 B Tree Swallow, adult -27.82 13.76 Berl 2017 C Tree Swallow, adult -26.6 12.95 Berl 2017 D Tree Swallow, adult -27.15 12.82 Berl 2017 D Tree Swallow, adult -24.96 9.53 Darb 2014 D Tree Swallow, adult -25.24 6.39 Darb 2015 A Tree Swallow, adult -26.46 10.28 Darb 2016 B Tree Swallow, adult -25.34 10.46 Darb 2017 A Tree Swallow, adult -24.52 9.76 Darb 2017 B Tree Swallow, adult -24.85 7.94 Fawc 2014 D Tree Swallow, adult -25.12 10.41 Fawc 2015 A Tree Swallow, adult -25.29 11.12 Fawc 2015 C Tree Swallow, adult -26.49 11.58 Fawc 2016 A Tree Swallow, adult -26.02 12.92 Fawc 2016 C Tree Swallow, adult -27.78 14.04 Fawc 2016 C Tree Swallow, adult -26.11 12.24 Fawc 2016 E Tree Swallow, adult -24.94 11.09 Fawc 2017 C Tree Swallow, adult -25.51 10.74 Fawc 2017 E Tree Swallow, adult -24.42 8.82 High 2015 D Tree Swallow, adult -24.63 9.37 High 2016 D Tree Swallow, adult -24.69 10.42 High 2016 D Tree Swallow, adult -30.88 10.01 High 2017 C Tree Swallow, adult -27.67 10.28 High 2017 D Tree Swallow, adult -24.39 9.7 High 2017 E Tree Swallow, adult -27.26 13.76 Muss 2014 B Tree Swallow, adult -25.53 10.46 Muss 2015 E Tree Swallow, adult -30 10.16 Muss 2016 A Tree Swallow, adult -27.61 9.7 Muss 2016 B Tree Swallow, adult -30.07 10.81 Muss 2016 C Tree Swallow, adult -28.82 10.25 Muss 2016 C Tree Swallow, adult -32.77 10.4 Muss 2017 B Tree Swallow, adult -33.24 9.9 Muss 2017 B Tree Swallow, adult -31.69 10.17 Muss 2017 E Tree Swallow, adult -25.8 11.66 Rest 2014 C Tree Swallow, adult -26.25 11.45 Rest 2015 A

226

Tree Swallow, adult -25.24 12.74 Rest 2016 A Tree Swallow, adult -24.58 11.94 Rest 2016 B Tree Swallow, adult -26 11.48 Rest 2016 D Tree Swallow, adult -25.94 11.38 Rest 2016 E Tree Swallow, adult -26.01 12 Rest 2017 A Tree Swallow, adult -27.05 11.97 Rest 2017 B Tree Swallow, adult -25.94 13.04 Rest 2017 B Tree Swallow, adult -24.86 10.66 Rest 2017 C Tree Swallow, adult -25.29 11.68 Rest 2017 D Tree Swallow, adult -24.81 11.23 Wetl 2014 A Tree Swallow, adult -25.31 11.14 Wetl 2014 A Tree Swallow, adult -25.99 11.88 Wetl 2014 C Tree Swallow, adult -25.43 12.91 Wetl 2014 C Tree Swallow, adult -25 12.05 Wetl 2014 E Tree Swallow, adult -25.91 12.16 Wetl 2015 C Tree Swallow, adult -25.9 11.48 Wetl 2015 D Tree Swallow, adult -25.71 11.77 Wetl 2016 A Tree Swallow, adult -24.28 10.1 Wetl 2016 C Tree Swallow, adult -26.62 11.34 Wetl 2016 C Tree Swallow, adult -26.28 12.64 Wetl 2016 F Tree Swallow, adult -26.75 12.32 Wetl 2017 A Tree Swallow, adult -25.65 11.04 Wetl 2017 A Tree Swallow, adult -25.48 10.43 Wetl 2017 A2 Tree Swallow, adult -26.74 11.02 Wetl 2017 B Tree Swallow, adult -26.45 11.85 Wetl 2017 B Tree Swallow, adult -24.81 11.91 Wetl 2017 D Tree Swallow, adult -25.99 11.28 Wetl 2017 B Tree Swallow, adult -25.12 11.7 Wetl 2017 C Tree Swallow, adult -25.21 11.6 Wetl 2017 C Tree Swallow, adult -25.39 11.82 Wetl 2017 F Tree Swallow, adult -25.01 11.48 Wetl 2017 F Tree Swallow, nestling -28.04 13.4 Berl 2015 A Tree Swallow, nestling -27.59 13.18 Berl 2015 A Tree Swallow, nestling -27.51 12.81 Berl 2015 A Tree Swallow, nestling -28.31 14.5 Berl 2016 A Tree Swallow, nestling -28.39 14.51 Berl 2016 A Tree Swallow, nestling -28.48 15.68 Berl 2016 A Tree Swallow, nestling -26.07 11.04 Berl 2016 D Tree Swallow, nestling -26.15 11.92 Berl 2016 D Tree Swallow, nestling -26.31 12.4 Berl 2016 D Tree Swallow, nestling -26.07 12.05 Berl 2016 D Tree Swallow, nestling -26.1 12.16 Berl 2016 D 227

Tree Swallow, nestling -27.14 13.3 Berl 2016 D Tree Swallow, nestling -27.28 13.43 Berl 2017 A Tree Swallow, nestling -27.05 13.36 Berl 2017 A Tree Swallow, nestling -27.19 13.49 Berl 2017 A Tree Swallow, nestling -27.14 13.24 Berl 2017 A Tree Swallow, nestling -27.15 13.58 Berl 2017 A Tree Swallow, nestling -27.66 13.29 Berl 2017 B Tree Swallow, nestling -27.78 13.15 Berl 2017 B Tree Swallow, nestling -27.94 13.42 Berl 2017 B Tree Swallow, nestling -27.81 13.24 Berl 2017 B Tree Swallow, nestling -27.69 13.17 Berl 2017 B Tree Swallow, nestling -27.63 13.1 Berl 2017 B Tree Swallow, nestling -27.7 13 Berl 2017 B Tree Swallow, nestling -27.06 13.44 Berl 2017 C Tree Swallow, nestling -27.22 13.32 Berl 2017 C Tree Swallow, nestling -27.2 13.42 Berl 2017 C Tree Swallow, nestling -26.29 10.94 Berl 2017 D Tree Swallow, nestling -26.01 11.1 Berl 2017 D Tree Swallow, nestling -26.03 11.09 Berl 2017 D Tree Swallow, nestling -25.93 11.12 Berl 2017 D Tree Swallow, nestling -26.71 11.3 Berl 2017 D Tree Swallow, nestling -27.35 12.95 Berl 2017 F Tree Swallow, nestling -24.94 9.29 Darb 2014 A Tree Swallow, nestling -25.21 9.12 Darb 2014 A Tree Swallow, nestling -25.01 9.15 Darb 2014 A Tree Swallow, nestling -25.25 8.98 Darb 2014 A Tree Swallow, nestling -24.98 9.18 Darb 2014 B Tree Swallow, nestling -25.19 8.15 Darb 2014 D Tree Swallow, nestling -25.18 8.31 Darb 2014 D Tree Swallow, nestling -24.94 8.01 Darb 2014 D Tree Swallow, nestling -25.08 8.45 Darb 2014 D Tree Swallow, nestling -25.4 7.86 Darb 2015 B Tree Swallow, nestling -25.3 7.76 Darb 2015 B Tree Swallow, nestling -25.52 8.43 Darb 2015 B Tree Swallow, nestling -25.49 9.82 Darb 2015 E Tree Swallow, nestling -25.55 9.7 Darb 2015 E Tree Swallow, nestling -25.8 9.98 Darb 2015 E Tree Swallow, nestling -25.79 11.03 Darb 2015 E Tree Swallow, nestling -26.51 9.89 Darb 2016 A Tree Swallow, nestling -26.27 10.2 Darb 2016 A Tree Swallow, nestling -26.41 10.09 Darb 2016 A Tree Swallow, nestling -27.09 12.74 Darb 2016 B 228

Tree Swallow, nestling -27.14 12.67 Darb 2016 B Tree Swallow, nestling -26.99 12.18 Darb 2016 B Tree Swallow, nestling -26.88 12.19 Darb 2016 B Tree Swallow, nestling -27.1 12.49 Darb 2016 B Tree Swallow, nestling -25.41 9.43 Darb 2016 D Tree Swallow, nestling -25.39 9.89 Darb 2016 D Tree Swallow, nestling -25.18 9.67 Darb 2016 D Tree Swallow, nestling -25.33 9.57 Darb 2016 D Tree Swallow, nestling -25.92 9.46 Darb 2017 A Tree Swallow, nestling -25.62 9.67 Darb 2017 A Tree Swallow, nestling -24.59 9.2 Darb 2017 B2 Tree Swallow, nestling -24.69 8.94 Darb 2017 B2 Tree Swallow, nestling -24.37 9.01 Darb 2017 B2 Tree Swallow, nestling -24.64 8.96 Darb 2017 B2 Tree Swallow, nestling -26 9.74 Darb 2017 D Tree Swallow, nestling -26.11 9.49 Darb 2017 D Tree Swallow, nestling -25.94 9.98 Darb 2017 D Tree Swallow, nestling -26.1 9.88 Darb 2017 D Tree Swallow, nestling -26.06 12.97 Fawc 2014 A Tree Swallow, nestling -26.1 13.1 Fawc 2014 A Tree Swallow, nestling -25.73 12.78 Fawc 2014 A Tree Swallow, nestling -26.05 13.09 Fawc 2014 A Tree Swallow, nestling -25.36 9.23 Fawc 2015 A Tree Swallow, nestling -25.15 9.38 Fawc 2015 A Tree Swallow, nestling -25.24 9.55 Fawc 2015 A Tree Swallow, nestling -25.43 11.73 Fawc 2015 C Tree Swallow, nestling -25.22 11.37 Fawc 2015 C Tree Swallow, nestling -25.51 11.98 Fawc 2015 C Tree Swallow, nestling -26.2 13.24 Fawc 2016 A Tree Swallow, nestling -26.17 13.19 Fawc 2016 A Tree Swallow, nestling -26.23 13.32 Fawc 2016 A Tree Swallow, nestling -26.25 13.31 Fawc 2016 A Tree Swallow, nestling -25.13 11.48 Fawc 2016 B Tree Swallow, nestling -24.99 11.75 Fawc 2016 B Tree Swallow, nestling -26.33 12.97 Fawc 2016 D Tree Swallow, nestling -26.25 12.93 Fawc 2016 D Tree Swallow, nestling -26.34 13.14 Fawc 2016 D Tree Swallow, nestling -26.28 13.14 Fawc 2016 D Tree Swallow, nestling -26.26 12.71 Fawc 2016 D Tree Swallow, nestling -26.43 13.65 Fawc 2016 E Tree Swallow, nestling -26.31 13.34 Fawc 2016 E Tree Swallow, nestling -26.33 13.46 Fawc 2016 E 229

Tree Swallow, nestling -26.36 13.53 Fawc 2016 E Tree Swallow, nestling -26.33 13.79 Fawc 2016 E Tree Swallow, nestling -25.51 11.04 Fawc 2017 B Tree Swallow, nestling -25.61 11.03 Fawc 2017 B Tree Swallow, nestling -25.68 11.25 Fawc 2017 B Tree Swallow, nestling -26.1 11.37 Fawc 2017 C Tree Swallow, nestling -25.86 10.92 Fawc 2017 C Tree Swallow, nestling -25.55 11.14 Fawc 2017 C Tree Swallow, nestling -25.63 11.16 Fawc 2017 C Tree Swallow, nestling -25.67 11.23 Fawc 2017 C Tree Swallow, nestling -25.79 12.69 Fawc 2017 D Tree Swallow, nestling -25.55 12.13 Fawc 2017 D Tree Swallow, nestling -26 12.82 Fawc 2017 D Tree Swallow, nestling -25.88 12.75 Fawc 2017 D Tree Swallow, nestling -25.93 12.13 Fawc 2017 D Tree Swallow, nestling -25.8 12.51 Fawc 2017 D Tree Swallow, nestling -24.81 8.86 High 2014 A Tree Swallow, nestling -24.85 9 High 2014 A Tree Swallow, nestling -24.88 9.06 High 2014 A Tree Swallow, nestling -24.8 10.36 High 2014 C Tree Swallow, nestling -24.49 10.38 High 2014 C Tree Swallow, nestling -24.55 10.21 High 2014 D Tree Swallow, nestling -24.71 10.25 High 2014 D Tree Swallow, nestling -24.61 10.2 High 2014 D Tree Swallow, nestling -24.75 10.63 High 2014 D Tree Swallow, nestling -24.45 10.41 High 2014 D Tree Swallow, nestling -24.43 9.69 High 2015 A Tree Swallow, nestling -24.71 9.67 High 2015 A Tree Swallow, nestling -24.59 9.98 High 2015 A Tree Swallow, nestling -24.48 9.13 High 2015 B Tree Swallow, nestling -24.25 9.48 High 2015 B Tree Swallow, nestling -24.78 9.23 High 2015 B Tree Swallow, nestling -24.68 9.23 High 2015 C Tree Swallow, nestling -24.83 8.87 High 2015 C Tree Swallow, nestling -24.52 9.28 High 2015 D Tree Swallow, nestling -24.75 9.55 High 2015 D Tree Swallow, nestling -24.74 9.56 High 2015 D Tree Swallow, nestling -24.69 9.24 High 2016 B Tree Swallow, nestling -24.74 8.93 High 2016 B Tree Swallow, nestling -24.6 9 High 2016 B Tree Swallow, nestling -24.63 8.89 High 2016 B Tree Swallow, nestling -24.59 9.07 High 2016 B 230

Tree Swallow, nestling -24.8 8.97 High 2016 D Tree Swallow, nestling -24.72 9.13 High 2016 D Tree Swallow, nestling -24.7 9.25 High 2016 D Tree Swallow, nestling -25.32 8.9 High 2017 C Tree Swallow, nestling -25.17 8.66 High 2017 C Tree Swallow, nestling -25.11 9.42 High 2017 D Tree Swallow, nestling -25.09 9.45 High 2017 D Tree Swallow, nestling -25.16 9.2 High 2017 D Tree Swallow, nestling -25.1 9.44 High 2017 D Tree Swallow, nestling -24.89 9.23 High 2017 D Tree Swallow, nestling -27.06 13.72 Muss 2014 B Tree Swallow, nestling -27.15 13.69 Muss 2014 B Tree Swallow, nestling -27.22 13.79 Muss 2014 B Tree Swallow, nestling -27.13 13.87 Muss 2014 B Tree Swallow, nestling -27.13 13.87 Muss 2014 B Tree Swallow, nestling -27.18 13.55 Muss 2015 B Tree Swallow, nestling -27.44 13.3 Muss 2015 B Tree Swallow, nestling -27.35 14.43 Muss 2015 B Tree Swallow, nestling -27.12 14.21 Muss 2015 B Tree Swallow, nestling -26.78 12.64 Muss 2015 C Tree Swallow, nestling -26.92 12.42 Muss 2015 C Tree Swallow, nestling -27.13 13.48 Muss 2015 C Tree Swallow, nestling -27.69 12.43 Muss 2015 E Tree Swallow, nestling -27.5 12.61 Muss 2015 E Tree Swallow, nestling -27.76 13.35 Muss 2015 E Tree Swallow, nestling -27.78 13.63 Muss 2015 E Tree Swallow, nestling -27.8 14.03 Muss 2017 B Tree Swallow, nestling -27.91 14.04 Muss 2017 B Tree Swallow, nestling -27.83 13.41 Muss 2017 B Tree Swallow, nestling -27.91 13.63 Muss 2017 B Tree Swallow, nestling -28.04 13.36 Muss 2017 B Tree Swallow, nestling -26.98 12.97 Muss 2017 E Tree Swallow, nestling -27.27 13.4 Muss 2017 E Tree Swallow, nestling -26.78 11.87 Rest 2014 A Tree Swallow, nestling -26.66 11.87 Rest 2014 A Tree Swallow, nestling -27.08 12.07 Rest 2014 A Tree Swallow, nestling -26.86 12.05 Rest 2014 A Tree Swallow, nestling -28.41 11.5 Rest 2014 B Tree Swallow, nestling -28.17 11.26 Rest 2014 B Tree Swallow, nestling -28.13 10.88 Rest 2014 B Tree Swallow, nestling -28.39 11.55 Rest 2014 B Tree Swallow, nestling -28.22 11.25 Rest 2014 B 231

Tree Swallow, nestling -28.51 11.22 Rest 2014 B Tree Swallow, nestling -28.16 11.07 Rest 2014 C Tree Swallow, nestling -28.21 11.26 Rest 2014 C Tree Swallow, nestling -28.08 11.29 Rest 2014 C Tree Swallow, nestling -28.09 11.25 Rest 2014 C Tree Swallow, nestling -28.19 11.09 Rest 2014 C Tree Swallow, nestling -25.19 10.1 Rest 2015 A Tree Swallow, nestling -24.95 10.22 Rest 2015 A Tree Swallow, nestling -24.8 10.7 Rest 2015 A Tree Swallow, nestling -24.56 11.39 Rest 2015 B Tree Swallow, nestling -25.03 12.07 Rest 2015 B Tree Swallow, nestling -24.42 10.39 Rest 2015 B Tree Swallow, nestling -25.72 10.06 Rest 2015 D Tree Swallow, nestling -25.52 10.41 Rest 2015 D Tree Swallow, nestling -24.2 9.69 Rest 2016 A Tree Swallow, nestling -26.12 12.49 Rest 2016 A Tree Swallow, nestling -26.21 12.48 Rest 2016 A Tree Swallow, nestling -26.03 12.51 Rest 2016 A Tree Swallow, nestling -25.91 12.78 Rest 2016 A Tree Swallow, nestling -25.97 12.48 Rest 2016 A Tree Swallow, nestling -26.18 12.55 Rest 2016 B Tree Swallow, nestling -26.22 12.32 Rest 2016 B Tree Swallow, nestling -26.23 12.25 Rest 2016 B Tree Swallow, nestling -26.09 12.15 Rest 2016 B Tree Swallow, nestling -26.39 12.47 Rest 2016 B Tree Swallow, nestling -24.35 9.42 Rest 2016 C Tree Swallow, nestling -24.7 9.99 Rest 2016 C Tree Swallow, nestling -24.82 9.74 Rest 2016 C Tree Swallow, nestling -24.62 9.98 Rest 2016 C Tree Swallow, nestling -25.9 12.57 Rest 2016 C Tree Swallow, nestling -26 12.46 Rest 2016 C Tree Swallow, nestling -26.1 12.46 Rest 2016 C Tree Swallow, nestling -26.13 12.66 Rest 2016 C Tree Swallow, nestling -25.74 11.68 Rest 2016 D Tree Swallow, nestling -25.85 11.93 Rest 2016 D Tree Swallow, nestling -25.62 11.29 Rest 2016 E Tree Swallow, nestling -25.79 11.2 Rest 2016 E Tree Swallow, nestling -25.66 11.4 Rest 2016 E Tree Swallow, nestling -25.73 11.42 Rest 2016 E Tree Swallow, nestling -25.58 11.75 Rest 2016 WA Tree Swallow, nestling -25.46 11.53 Rest 2016 WA Tree Swallow, nestling -26.02 12.83 Rest 2016 WC 232

Tree Swallow, nestling -24.9 11.07 Rest 2017 A Tree Swallow, nestling -24.57 11.03 Rest 2017 A Tree Swallow, nestling -24.91 11.53 Rest 2017 A Tree Swallow, nestling -24.77 11.26 Rest 2017 A Tree Swallow, nestling -25.27 10.3 Rest 2017 B Tree Swallow, nestling -25.17 10.36 Rest 2017 B Tree Swallow, nestling -25.44 10.29 Rest 2017 B Tree Swallow, nestling -25.26 10.6 Rest 2017 B Tree Swallow, nestling -24.9 10.66 Rest 2017 B Tree Swallow, nestling -24.75 10.78 Rest 2017 B Tree Swallow, nestling -24.67 10.55 Rest 2017 B Tree Swallow, nestling -24.71 10.67 Rest 2017 B Tree Swallow, nestling -24.96 10.88 Rest 2017 B Tree Swallow, nestling -24.87 11.65 Rest 2017 B Tree Swallow, nestling -25.28 12.02 Rest 2017 C Tree Swallow, nestling -24.92 11.9 Rest 2017 C Tree Swallow, nestling -25.41 12.22 Rest 2017 C Tree Swallow, nestling -25.07 11.94 Rest 2017 C Tree Swallow, nestling -25.42 10.72 Rest 2017 C2 Tree Swallow, nestling -25.5 10.85 Rest 2017 C2 Tree Swallow, nestling -25.2 10.77 Rest 2017 C2 Tree Swallow, nestling -25.29 10.69 Rest 2017 C2 Tree Swallow, nestling -25.51 9.85 Rest 2017 D Tree Swallow, nestling -25.13 10.96 Rest 2017 R Tree Swallow, nestling -25.46 11.01 Rest 2017 R Tree Swallow, nestling -25.34 10.98 Rest 2017 R Tree Swallow, nestling -25.27 11.14 Rest 2017 R Tree Swallow, nestling -25.36 11.01 Rest 2017 R Tree Swallow, nestling -24.73 11.26 Rest 2017 WA Tree Swallow, nestling -24.93 11 Rest 2017 WA Tree Swallow, nestling -24.55 10.92 Rest 2017 WA Tree Swallow, nestling -24.61 11.14 Rest 2017 WA Tree Swallow, nestling -25.76 11.64 Rest 2017 WC Tree Swallow, nestling -25.21 10.84 Rest 2017 WC Tree Swallow, nestling -25.62 11.32 Rest 2017 WC Tree Swallow, nestling -25.99 11.44 Rest 2017 WC Tree Swallow, nestling -25.3 12.43 Wetl 2014 A Tree Swallow, nestling -25.17 12.71 Wetl 2014 A Tree Swallow, nestling -25.22 12.63 Wetl 2014 A Tree Swallow, nestling -25.45 12.91 Wetl 2014 C Tree Swallow, nestling -25.42 12.68 Wetl 2014 C Tree Swallow, nestling -25.23 12.88 Wetl 2014 C 233

Tree Swallow, nestling -25.39 12.78 Wetl 2014 C Tree Swallow, nestling -25.36 12.7 Wetl 2014 E Tree Swallow, nestling -25.3 12.63 Wetl 2014 E Tree Swallow, nestling -25.4 12.93 Wetl 2014 E Tree Swallow, nestling -24.37 10.34 Wetl 2015 B Tree Swallow, nestling -26.33 11.87 Wetl 2015 B Tree Swallow, nestling -24.46 11.02 Wetl 2015 B Tree Swallow, nestling -24.68 10.8 Wetl 2015 B Tree Swallow, nestling -25.57 12.17 Wetl 2015 C Tree Swallow, nestling -25.37 5.52 Wetl 2015 C Tree Swallow, nestling -24.75 9.86 Wetl 2015 F Tree Swallow, nestling -26.39 12.52 Wetl 2016 A Tree Swallow, nestling -26.44 12.86 Wetl 2016 A Tree Swallow, nestling -26.25 12.83 Wetl 2016 A Tree Swallow, nestling -26.46 12.72 Wetl 2016 A Tree Swallow, nestling -26.71 12.79 Wetl 2016 A Tree Swallow, nestling -26.22 12.93 Wetl 2016 B Tree Swallow, nestling -26.02 11.79 Wetl 2016 B Tree Swallow, nestling -26.27 13.31 Wetl 2016 B Tree Swallow, nestling -26.31 13.14 Wetl 2016 B Tree Swallow, nestling -26.25 12.96 Wetl 2016 B Tree Swallow, nestling -24.79 11.67 Wetl 2016 C Tree Swallow, nestling -24.85 11.39 Wetl 2016 C Tree Swallow, nestling -24.8 11.41 Wetl 2016 C Tree Swallow, nestling -24.92 11.44 Wetl 2016 C Tree Swallow, nestling -24.85 11.48 Wetl 2016 C Tree Swallow, nestling -26.12 12.69 Wetl 2016 D Tree Swallow, nestling -26.28 12.7 Wetl 2016 D Tree Swallow, nestling -26.4 12.6 Wetl 2016 D Tree Swallow, nestling -26.34 12.87 Wetl 2016 D Tree Swallow, nestling -26.34 12.99 Wetl 2016 D Tree Swallow, nestling -26.5 13.05 Wetl 2016 F Tree Swallow, nestling -26.45 13.03 Wetl 2016 F Tree Swallow, nestling -26.5 12.8 Wetl 2016 F Tree Swallow, nestling -26.25 12.9 Wetl 2016 WC Tree Swallow, nestling -26.12 12.84 Wetl 2016 WC Tree Swallow, nestling -26.23 12.76 Wetl 2016 WC Tree Swallow, nestling -25.56 12.23 Wetl 2017 A Tree Swallow, nestling -25.66 12.34 Wetl 2017 A Tree Swallow, nestling -25.65 12.45 Wetl 2017 A Tree Swallow, nestling -25.67 12.39 Wetl 2017 A Tree Swallow, nestling -25 10.7 Wetl 2017 A2 234

Tree Swallow, nestling -24.62 10.16 Wetl 2017 A2 Tree Swallow, nestling -25.43 11.04 Wetl 2017 B Tree Swallow, nestling -25.54 11.11 Wetl 2017 B Tree Swallow, nestling -25.83 10.97 Wetl 2017 B Tree Swallow, nestling -25.69 11.03 Wetl 2017 B Tree Swallow, nestling -25.91 10.91 Wetl 2017 B Tree Swallow, nestling -25.86 11.19 Wetl 2017 B Tree Swallow, nestling -25.52 11.69 Wetl 2017 C

Tree Swallow, nestling -25.59 11.84 Wetl 2017 C

Tree Swallow, nestling -25.37 11.49 Wetl 2017 C

Tree Swallow, nestling -25.53 11.82 Wetl 2017 C

Tree Swallow, nestling -24.91 10.38 Wetl 2017 D Tree Swallow, nestling -24.89 10.47 Wetl 2017 D Tree Swallow, nestling -25 10.55 Wetl 2017 D Tree Swallow, nestling -24.94 10.54 Wetl 2017 D Tree Swallow, nestling -25.29 11.34 Wetl 2017 F Tree Swallow, nestling -25.6 11.43 Wetl 2017 F Tree Swallow, nestling -25.81 11.75 Wetl 2017 F Tree Swallow, nestling -25.57 11.53 Wetl 2017 F Tree Swallow, nestling -25.59 11.49 Wetl 2017 F Tree Swallow, nestling -25.59 11.57 Wetl 2017 F Tree Swallow, nestling -25.61 11.13 Wetl 2017 WA Tree Swallow, nestling -25.33 11.35 Wetl 2017 WA Tree Swallow, nestling -26.03 11.22 Wetl 2017 WA Tree Swallow, nestling -25.82 11.43 Wetl 2017 WA Tree Swallow, nestling -25.39 10.89 Wetl 2017 WB Tree Swallow, nestling -25.26 11.04 Wetl 2017 WB Tree Swallow, nestling -25.31 10.63 Wetl 2017 WB Tree Swallow, nestling -25.5 10.63 Wetl 2017 WB Tree Swallow, nestling -25.46 12.57 Wetl 2017 B

235

Table B.2 Carbon (ẟ13C) and nitrogen (ẟ15N) isotopic signatures for dominant insect families.

Source 13C 15N Site Year Season Family insect, aquatic -25.92 10 Berl 2014 early Chironomidae insect, aquatic -30.41 11.19 Berl 2015 early Chironomidae insect, aquatic -33.05 8.59 Berl 2015 late Chironomidae insect, aquatic -28.74 10.87 Berl 2016 early Chironomidae insect, aquatic -28.39 8.89 Berl 2016 late Chironomidae insect, aquatic -25.46 8.59 Berl 2017 early Chironomidae insect, aquatic -26.4 9.28 Berl 2017 late Chironomidae insect, aquatic -25.25 11.36 Darb 2014 early Chironomidae insect, aquatic -27.25 12.54 Darb 2015 early Chironomidae insect, aquatic -25.23 11.1 Darb 2015 late Heptageniidae insect, aquatic -27.94 12.56 Darb 2016 early Chironomidae insect, aquatic -28.08 14.49 Darb 2016 late Chironomidae insect, aquatic -27.12 9.15 Darb 2017 early Chironomidae insect, aquatic -27.88 11.68 Darb 2017 late Chironomidae insect, aquatic -25.65 8.75 Fawc 2015 early Chironomidae insect, aquatic -25.27 10.87 Fawc 2015 late Chironomidae insect, aquatic -26.42 9.59 Fawc 2016 early Chironomidae insect, aquatic -25.61 12.91 Fawc 2016 late Chironomidae insect, aquatic -24.19 5.01 Fawc 2017 early Chironomidae insect, aquatic -25.86 9.54 Fawc 2017 late Chironomidae insect, aquatic -22.47 10.48 High 2014 early Chironomidae insect, aquatic -25.33 9.67 High 2015 early Chironomidae insect, aquatic -25.29 11.97 High 2015 late Chironomidae insect, aquatic -25.39 11.49 High 2016 early Chironomidae insect, aquatic -25.95 10.66 High 2016 late Chironomidae insect, aquatic -25.72 10.61 High 2017 early Chironomidae insect, aquatic -25.33 11.57 High 2017 late Chironomidae insect, aquatic -29.18 13.46 Muss 2014 early Ceratopogonidae insect, aquatic -30.22 12.42 Muss 2015 early Chironomidae insect, aquatic -31.45 13.67 Muss 2015 late Chironomidae insect, aquatic -30.53 11.79 Muss 2016 early Chironomidae insect, aquatic -30.94 11.48 Muss 2016 late Chironomidae insect, aquatic -29.8 13.04 Muss 2017 early Ephemeridae insect, aquatic -27.76 11.93 Muss 2017 late Chironomidae insect, aquatic -25.72 9.73 Rest 2015 early Chironomidae insect, aquatic -25.73 8.86 Rest 2015 late Chironomidae insect, aquatic -27.04 9.25 Rest 2016 early Chironomidae insect, aquatic -24.93 11.17 Rest 2016 late Chironomidae 236 insect, aquatic -24.7 7.4 Rest 2017 early Chironomidae insect, aquatic -25.34 6.61 Rest 2017 late Chironomidae insect, aquatic -24.9 10.55 Wetl 2015 early Chironomidae insect, aquatic -26.46 10.78 Wetl 2015 late Chironomidae insect, aquatic -25.79 11.62 Wetl 2016 early Dolichopodidae insect, aquatic -29.1 11.72 Wetl 2016 late Heptageniidae insect, aquatic -25.11 5.87 Wetl 2017 early Chironomidae insect, aquatic -25.65 10.35 Wetl 2017 late Dolichopodidae insect, aquatic -28.55 8.22 Berl 2014 early Simuliidae insect, aquatic -25.9 10.01 Berl 2015 early Dolichopodidae insect, aquatic -20.32 10.45 Berl 2015 late Dolichopodidae insect, aquatic -27.09 3.76 Berl 2016 early Dolichopodidae insect, aquatic -24.92 11.11 Berl 2016 late Dolichopodidae insect, aquatic -26.32 11.91 Berl 2017 early Perlidae insect, aquatic -23.45 8.86 Berl 2017 late Dolichopodidae insect, aquatic -20.05 8.32 Darb 2014 early Dolichopodidae insect, aquatic -27.38 12.94 Darb 2015 early Perlidae insect, aquatic -26.88 10.98 Darb 2015 late Chironomidae insect, aquatic -24.82 10.29 Darb 2016 early Dolichopodidae insect, aquatic -29.71 14.57 Darb 2016 late Heptageniidae insect, aquatic -27.17 12.61 Darb 2017 early Perlidae insect, aquatic -24.97 6.15 Darb 2017 late Muscidae insect, aquatic -26.71 11.07 Fawc 2015 early Perlidae insect, aquatic -22.54 14.57 Fawc 2015 late Dolichopodidae insect, aquatic -25.14 9.74 Fawc 2016 early Dolichopodidae insect, aquatic -25.17 10.01 Fawc 2016 late Dolichopodidae insect, aquatic -27.13 12.58 Fawc 2017 early Dolichopodidae insect, aquatic -28.19 8.46 Fawc 2017 late Dolichopodidae insect, aquatic -24.32 5.68 High 2014 early Ceratopogonidae insect, aquatic -25.6 11.92 High 2015 early Perlidae insect, aquatic -24.91 9.23 High 2015 late Dolichopodidae insect, aquatic -26.86 12.55 High 2016 early Heptageniidae insect, aquatic -26.39 13.01 High 2016 late Heptageniidae insect, aquatic -25.71 5.34 High 2017 early Ceratopogonidae insect, aquatic -26.53 8.97 High 2017 late Ceratopogonidae insect, aquatic -29.72 13.08 Muss 2014 early Chironomidae insect, aquatic -26.58 8.87 Muss 2015 early Culicidae insect, aquatic -26.98 10.94 Muss 2015 late Culicidae insect, aquatic -30.63 12.96 Muss 2016 early Ephemeridae insect, aquatic -30.94 11.48 Muss 2016 late Chironomidae insect, aquatic -29.71 11.75 Muss 2017 early Chironomidae insect, aquatic -27.76 11.93 Muss 2017 late Chironomidae 237

insect, aquatic -23.83 8.04 Rest 2015 early Muscidae insect, aquatic -23.93 8.33 Rest 2015 late Muscidae insect, aquatic -28.09 7.71 Rest 2016 early Caenidae insect, aquatic -26.55 12.35 Rest 2016 late Heptageniidae insect, aquatic -23.17 8.27 Rest 2017 early Ephydridae insect, aquatic -22.93 10.54 Rest 2017 late Dolichopodidae insect, aquatic -26.73 11.79 Wetl 2015 early Dolichopodidae insect, aquatic -23.33 8.27 Wetl 2015 late Dolichopodidae insect, aquatic -29.49 8.98 Wetl 2016 early Chironomidae insect, aquatic -25.55 8.56 Wetl 2016 late Chironomidae insect, aquatic -25.43 11.19 Wetl 2017 early Perlidae insect, aquatic -26.3 8.61 Wetl 2017 late Chironomidae Cicadellidae insect, terrestrial -24.82 6.55 Berl 2014 early Sciaridae insect, terrestrial -23.01 9.33 Berl 2015 early Mordellidae Mycetophilidae, Phoridae Mordellidae, insect, terrestrial -24.46 7.58 Berl 2015 late Cicadellidae insect, terrestrial -27.14 8.57 Berl 2016 early Cicadellidae insect, terrestrial -28.19 9.9 Berl 2016 late unk moth insect, terrestrial -26.99 8.29 Berl 2017 early Chrysomelidae insect, terrestrial -27.65 9.13 Berl 2017 late Cicadellidae insect, terrestrial -26.86 2.67 Darb 2014 early Tiphiidae insect, terrestrial -26.05 0.6 Darb 2015 early Cicadellidae insect, terrestrial -26.5 -3.85 Darb 2015 late Cicadellidae insect, terrestrial -27.89 4.68 Darb 2016 early Cicadellidae insect, terrestrial -26.01 6.92 Darb 2016 late Pipunculidae insect, terrestrial -24.87 2.19 Darb 2017 early Chrysomelidae insect, terrestrial -26.59 2.53 Darb 2017 late Cicadellidae insect, terrestrial -24.4 6.52 Fawc 2014 early Sciaridae insect, terrestrial -25.83 7.23 Fawc 2015 early Phoridae insect, terrestrial -25.61 5.86 Fawc 2015 late Ptinidae insect, terrestrial -26.83 6.62 Fawc 2016 early Stratiomyidae insect, terrestrial -27.01 7.36 Fawc 2016 late Stratiomyidae insect, terrestrial -25.61 8.67 Fawc 2017 early Phoridae insect, terrestrial -25.66 10.58 Fawc 2017 late Empididae insect, terrestrial -24.74 1.27 High 2014 early Cynipidae Mycetophilidae insect, terrestrial -24.04 2.18 High 2015 early Cicadellidae insect, terrestrial -26.03 1.29 High 2015 late Cicadellidae insect, terrestrial -31.31 9.13 High 2016 early Ichneumonidae

238 insect, terrestrial -28.81 2.05 High 2016 late Cicadellidae insect, terrestrial -26.31 8.29 High 2017 early Phoridae insect, terrestrial -25.89 4.59 High 2017 late Elateridae insect, terrestrial -29.69 2.71 Muss 2014 early Sphecidae insect, terrestrial -25.85 4.76 Muss 2015 early Mycetophilidae insect, terrestrial -25.49 1.74 Muss 2015 late Sciaridae insect, terrestrial -25 4.46 Muss 2016 early Formicidae insect, terrestrial -24.28 2.13 Muss 2016 late Ichneumonidae insect, terrestrial -24.56 4.22 Muss 2017 early Formicidae insect, terrestrial -24.61 -6.82 Muss 2017 late Ichneumonidae insect, terrestrial -24.85 3.74 Rest 2014 early Sciaridae insect, terrestrial -19.64 4.76 Rest 2015 early Mordellidae insect, terrestrial -24.6 5.18 Rest 2015 late Scarabaeidae insect, terrestrial -24.91 0.88 Rest 2016 early Cicadellidae insect, terrestrial -26 4.89 Rest 2016 late Apidae insect, terrestrial -23.41 6.8 Rest 2017 early Miridae insect, terrestrial -26.74 -0.28 Rest 2017 late Mordellidae insect, terrestrial -26.26 5.94 Wetl 2014 early Phoridae insect, terrestrial -26.55 6.83 Wetl 2015 early Mycetophilidae insect, terrestrial -29.71 0.48 Wetl 2015 late Cicadellidae insect, terrestrial -26.64 5.7 Wetl 2016 early Cicadellidae insect, terrestrial -27.14 2.57 Wetl 2016 late Cicadellidae insect, terrestrial -26.5 4.45 Wetl 2017 early Cicadellidae insect, terrestrial -27.12 2.25 Wetl 2017 late Cicadellidae Cicadellidae insect, terrestrial -24.82 6.55 Berl 2014 early Sciaridae insect, terrestrial -24.18 7.27 Berl 2015 early Mycetophilidae Mycetophilidae, Phoridae Mordellidae, insect, terrestrial -24.46 7.58 Berl 2015 late Cicadellidae insect, terrestrial -21.46 14.96 Berl 2016 early Halictidae Cicadellidae insect, terrestrial -26.6 5.77 Berl 2016 late Tingidae insect, terrestrial -25.66 7.85 Berl 2017 early Cicadellidae insect, terrestrial -24.39 7.66 Berl 2017 late Asilidae insect, terrestrial -25.81 0.77 Darb 2014 early Cicadellidae insect, terrestrial -23.42 3.89 Darb 2015 early Scarabaeidae insect, terrestrial -24.98 3.93 Darb 2015 late Tingidae insect, terrestrial -29.81 8.57 Darb 2016 early Ichneumonidae insect, terrestrial -25.9 2.38 Darb 2016 late Cicadellidae insect, terrestrial -26.24 -0.49 Darb 2017 early Cicadellidae

239 insect, terrestrial -21.15 14.72 Darb 2017 late Asilidae insect, terrestrial -27.74 1.34 Fawc 2014 early Cicadellidae insect, terrestrial -25.82 0.23 Fawc 2015 early Cicadellidae insect, terrestrial -25.62 3.36 Fawc 2015 late Coccinellidae insect, terrestrial -26.78 5.13 Fawc 2016 early Tingidae insect, terrestrial -27.29 4.76 Fawc 2016 late Mordellidae insect, terrestrial -24.13 8.07 Fawc 2017 early Elateridae insect, terrestrial -25.62 4.53 Fawc 2017 late Scarabaeidae insect, terrestrial -23.66 4.49 High 2014 early Sciaridae insect, terrestrial -24.32 4.4 High 2015 early Asilidae insect, terrestrial -23.76 0.74 High 2015 late Mordellidae Ceraphronidae insect, terrestrial -25.57 -1 High 2016 early Platygastridae insect, terrestrial -28.31 3.38 High 2016 late Braconidae insect, terrestrial -27.33 1.67 High 2017 early Cicadellidae insect, terrestrial -27.09 2.18 High 2017 late Cicadellidae insect, terrestrial -28.37 5.42 Muss 2014 early Tingidae insect, terrestrial -26.4 3.68 Muss 2015 early Coccinellidae insect, terrestrial -24.02 5.91 Muss 2015 late Rhagionidae insect, terrestrial -26.9 3.56 Muss 2016 early Cicadellidae insect, terrestrial -24.25 8.82 Muss 2016 late Rhagionidae insect, terrestrial -31.94 12.13 Muss 2017 early Sciaridae insect, terrestrial -24.91 -1.39 Muss 2017 late Gryllidae insect, terrestrial -25.58 3.83 Rest 2014 early Cicadellidae insect, terrestrial -22.48 8.82 Rest 2015 early Miridae insect, terrestrial -23.45 5.05 Rest 2015 late Mordellidae insect, terrestrial -25.76 4.65 Rest 2016 early Miridae insect, terrestrial -24.52 8.35 Rest 2016 late Scarabaeidae insect, terrestrial -24.57 2.62 Rest 2017 early Cicadellidae Halictidae insect, terrestrial -25.24 5.01 Rest 2017 late Scarabaeidae insect, terrestrial -24.58 9.73 Wetl 2014 early Mycetophilidae insect, terrestrial -28.41 1.03 Wetl 2015 early Miridae insect, terrestrial -27.54 3.02 Wetl 2015 late Halictidae insect, terrestrial -22.93 3.35 Wetl 2016 early Halictidae insect, terrestrial -25.81 5.49 Wetl 2016 late Mordellidae insect, terrestrial -23.38 0.36 Wetl 2017 early Sciaridae insect, terrestrial -25.5 8.05 Wetl 2017 late Asilidae

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Table B.3 Carbon (ẟ13C) and nitrogen (ẟ15N) isotopic signatures for primary producers (terrestrial: detritus and aquatic: algae/periphtyton).

Source 13C 15N Site Year

Detritus -27.77 5.32 Berl 2015 Detritus -29.55 8.26 Berl 2015 Detritus -28.93 5.53 Berl 2015 Detritus -29.44 4.29 Berl 2016 Detritus -27.65 4.66 Berl 2016 Detritus -28.3 4.59 Berl 2016 Detritus -29.13 3.85 Berl 2016 Detritus -28.17 4.48 Berl 2016 Detritus -28.5 5.75 Berl 2016 Detritus -28.29 2.78 Berl 2017 Detritus -28.86 6.31 Berl 2017 Detritus -28.92 2.92 Darb 2015 Detritus -28.24 9.04 Darb 2015 Detritus -27.42 5.57 Darb 2015 Detritus -28.51 3.18 Darb 2016 Detritus -27.69 5.55 Darb 2016 Detritus -27.09 6.14 Darb 2016 Detritus -27.36 4.93 Darb 2016 Detritus -28.49 1.7 Darb 2016 Detritus -27.41 6.17 Darb 2016 Detritus -27.53 2.5 Darb 2017 Detritus -28.23 8.93 Darb 2017 Detritus -27.99 5.09 Darb 2017 Detritus -27.3 3.63 Fawc 2015 Detritus -28.47 4.1 Fawc 2015 Detritus -28.89 4.06 Fawc 2015 Detritus -27.29 3.55 Fawc 2016 Detritus -27.81 4.29 Fawc 2016 Detritus -28.28 2.45 Fawc 2016 Detritus -28.55 2.32 Fawc 2016 Detritus -28.04 3.33 Fawc 2016 Detritus -27.56 3.04 Fawc 2016 Detritus -28.46 3.48 Fawc 2017 Detritus -28.76 4.35 Fawc 2017

241

Detritus -29.1 5.43 High 2015 Detritus -29.15 5.32 High 2015 Detritus -26.97 3.74 High 2015 Detritus -27.86 3.6 High 2016 Detritus -27.42 3.99 High 2016 Detritus -28.09 5.4 High 2016 Detritus -28.73 6.06 High 2016 Detritus -28.98 5.54 High 2016 Detritus -28.04 1.99 High 2016 Detritus -27.58 3.03 High 2017 Detritus -29.06 5.17 High 2017 Detritus -28.07 6.32 High 2017 Detritus -28.9 6.6 Muss 2015 Detritus -28.9 6.59 Muss 2015 Detritus -28.66 10.16 Muss 2015 Detritus -27.16 10.12 Muss 2016 Detritus -27.61 2.72 Muss 2016 Detritus -25.02 1.18 Muss 2016 Detritus -28.22 0.63 Muss 2016 Detritus -28.34 4.16 Muss 2016 Detritus -27.55 -0.06 Muss 2017 Detritus -29.06 5.56 Muss 2017 Detritus -27.61 6.59 Rest 2015 Detritus -28.07 6.75 Rest 2015 Detritus -28 4.02 Rest 2015 Detritus -27.48 4.33 Rest 2016 Detritus -26.63 4.13 Rest 2016 Detritus -27.14 3.4 Rest 2016 Detritus -28.47 2.76 Rest 2016 Detritus -27.7 2.58 Rest 2016 Detritus -27.44 1.99 Rest 2016 Detritus -28.16 5.34 Rest 2017 Detritus -28.12 1.66 Rest 2017 Detritus -29.35 4.64 Wetl 2015 Detritus -28.18 4.41 Wetl 2015 Detritus -29.01 4.2 Wetl 2015 Detritus -28.84 3.17 Wetl 2016 Detritus -28.69 3.8 Wetl 2016 Detritus -28.15 2.94 Wetl 2016 Detritus -28.36 4.09 Wetl 2016 Detritus -28.65 3.74 Wetl 2016 Detritus -28.33 3.06 Wetl 2016 242

Detritus -29.19 3.06 Wetl 2017 Detritus -29.23 5.05 Wetl 2017 Periphyton -14.07 9.01 Berl 2015 Periphyton -13.85 9.8 Berl 2015 Periphyton -12.53 8.91 Berl 2015 Periphyton -18.92 9.23 Berl 2016 Periphyton -17.24 9.41 Berl 2016 Periphyton -20.26 8.51 Berl 2016 Periphyton -14.29 9.33 Berl 2016 Periphyton -14.97 8.05 Berl 2016 Periphyton -15.12 8.33 Berl 2016 Periphyton -15.81 6.39 Berl 2017 Periphyton -18.15 10.63 Berl 2017 Periphyton -15.43 10.44 Darb 2016 Periphyton -17.04 10.83 Darb 2016 Periphyton -17.75 10.87 Darb 2016 Periphyton -16.66 12.14 Darb 2016 Periphyton -18.71 11.98 Darb 2016 Periphyton -17.13 10.19 Darb 2016 Periphyton -15.4 5.94 Darb 2017 Periphyton -20.04 10.06 Darb 2017 Periphyton -16.73 12.25 Fawc 2015 Periphyton -18.33 11.17 Fawc 2015 Periphyton -17.3 11.43 Fawc 2015 Periphyton -18.84 11.31 Fawc 2016 Periphyton -20.45 9.38 Fawc 2016 Periphyton -19.97 10.12 Fawc 2016 Periphyton -15.44 10.41 Fawc 2016 Periphyton -15.84 10.66 Fawc 2016 Periphyton -16.9 10.99 Fawc 2016 Periphyton -19.71 10.58 Fawc 2017 Periphyton -18.46 10.65 Fawc 2017 Periphyton -19.7 10.46 High 2016 Periphyton -17.06 10.55 High 2016 Periphyton -20.73 10.79 High 2016 Periphyton -16.93 9.57 High 2016 Periphyton -9.41 8.77 High 2016 Periphyton -15.04 9.74 High 2016 Periphyton -17.73 9.73 High 2017 Periphyton -14.15 11.21 High 2017 Periphyton -17.96 12.03 Muss 2016 Periphyton -18.75 11.81 Muss 2016 243

Periphyton -19.55 11.61 Muss 2016 Periphyton -15.4 11.03 Muss 2016 Periphyton -15.14 10.65 Muss 2016 Periphyton -16.21 10.34 Muss 2016 Periphyton -21.12 9 Muss 2017 Periphyton -18.19 10.65 Muss 2017 Periphyton -16.1 10.72 Rest 2015 Periphyton -15.71 11.04 Rest 2015

Periphyton -16.25 10.94 Rest 2015

Periphyton -20.69 11.46 Rest 2016

Periphyton -18.96 9.28 Rest 2016

Periphyton -19.39 9.78 Rest 2016 Periphyton -15.93 9.66 Rest 2016 Periphyton -11.96 10.83 Rest 2016 Periphyton -16.18 10.39 Rest 2016 Periphyton -17.21 6.35 Rest 2017 Periphyton -16.72 9.22 Rest 2017 Periphyton -18.48 9.91 Wetl 2015 Periphyton -16.54 12.24 Wetl 2015 Periphyton -19.72 10.75 Wetl 2015 Periphyton -18.52 8.56 Wetl 2016 Periphyton -18.39 7.86 Wetl 2016 Periphyton -19.58 9.96 Wetl 2016 Periphyton -18.61 10.31 Wetl 2016 Periphyton -15.86 11.7 Wetl 2016 Periphyton -17.64 10.95 Wetl 2016 Periphyton -22.59 3.85 Wetl 2017 Periphyton -19.54 9.86 Wetl 2017

244

Figure B.1 Annual means from 2014-2017 by land use (i.e., natural/protected or urban) and period (May or July) for Tree Swallow nutritional reliance on emergent aquatic insects (vs. terrestrial flying insects). Flying insects prey is represented by the two most numerically abundant aquatic and terrestrial families in each season per study site. (a) Early season insects consumed by adults (LMM: p = 0.380), (b) early season insects consumed by nestlings at ~13 days (LMM: p = 0.310), (c) late season insects consumed by adults (LMM: p = 0.770), (d) late season insects consumed by nestling at ~13 days (LMM: p = 0.640). Error bars indicate +/- 1 SE. Different letters A, B indicate significant pairwise differences.

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