The Effect of Road Crossings on Stream-Associated Salamanders Within Holly Springs National Forest

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1-1-2017

The effect of road crossings on stream-associated salamanders within Holly Springs National Forest

Caleb Ashton Aldridge University of Mississippi

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Recommended Citation Aldridge, Caleb Ashton, "The effect of road crossings on stream-associated salamanders within Holly Springs National Forest" (2017). Electronic Theses and Dissertations. 1274. https://egrove.olemiss.edu/etd/1274

This Thesis is brought to you for free and open access by the Graduate School at eGrove. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of eGrove. For more information, please contact [email protected]. THE EFFECT OF ROAD CROSSINGS ON STREAM-ASSOCIATED SALAMANDERS WITHIN HOLLY SPRINGS NATIONAL FOREST

A Thesis

presented in partial fulfillment of requirements

for the degree of Master of Science

in the Department of Biological Sciences

The University of Mississippi

CALEB A. ALDRIDGE

May 2017

ABSTRACT

Road crossings have significant effects on wildlife, but there is limited information on how road crossings affect stream-associated salamanders. Stream-associated salamanders are vital to their ecological communities and are likely to experience the effect of roads more readily than other species due to their physiological characteristics. To test the effects of road crossings on stream-associated salamanders, I surveyed 12 pairs of confluent streams – one stream crossed by a road and the other not in each pair – within Holly Springs National Forest, Mississippi.

Surveys in the summer of 2015 were used to measure abundance and species richness of stream- associated salamanders. Transects were established across streams and abundance and species richness were measured at different distances from the road crossing (or stream midpoint where no road was present). Although salamanders were not abundant and only about 40% of samples contained any salamanders, abundance and richness varied between road-free and road-crossed streams, having 2.5 times as many individuals and 2.4 as many species per transect in road-free streams. The effect on abundance associated with roads was greater than previously found in

Appalachia where salamanders are more abundant and species rich. There was no significant difference in abundance or species richness with distance (0–36 m) from the road crossing, but greater statistical power was needed to detect significance for the small effect size observed.

Road-free and road-crossed sampling locations varied from 300–2500 m apart and no relationship existed for distance between and difference in abundance or species richness for paired locations. This lead to the conclusion that the extent of the road-effect zone lies between

36 and 300 m. When the data were re-analyzed without including the least stream-associated species (Plethodon mississippi), the results were essentially the same. There was a significant period × position interaction effect, suggesting that the first effort might have affected salamander abundance in the late summer sampling. Abundance and species richness were not associated with microclimate factors that differed between road-free and road-crossed streams.

Considering the difference in magnitude for road-effects between this and Ward et al. (2008), characteristically similar disturbances in different regions may vary in their magnitude and extent

– this could help explain the effect of sampling disturbance and no association between microclimate factors and salamander abundance and species richness. Additional sampling in other seasons and surveys that include additional, further from the road or midpoint might help to resolve uncertainty about spatial and temporal variation. Future research might also include components of salamander movement using mark-recapture techniques, since there are some suggestions that there are substantial temporal changes in location of the salamanders in this community.

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DEDICATION

This work is for those dedicated to the investigation and protection of nature. It is my hope that all people will soon look upon nature with the love of John Muir, the reverence of

Wendell Berry, respect of Aldo Leopold, and care of Rachel Carson.

ACKNOWLEDGMENTS

I would like to thank my primary thesis advisor, Dr. Stephen Threlkeld, for sharing his scientific experience and mentoring me with patience and dedication. My appreciation also goes to my co-advisor, Dr. William Resetarits, for encouragement and offering the use of his equipment any time I was in need. To Dr. Rebecca Symula, I extend my gratitude for teaching what must have seemed to be elementary principles, but challenged me fully. I also want to thank you for your improvements to this manuscript and learning with me along the way. A thank you also goes to Dr. Marjorie Holland for lending gentle advice, kind encouragement, and thorough comments over the course of my graduate studies.

A few additional people either assisted or supported my work. Dr. Ryan Garrick and his students, for adopting me as an honorary lab member, and allowing me to use equipment while being happy to help at every turn. Jennifer Lamb (University of Southern Mississippi) and

Sheena Feist (Mississippi Museum of Natural Science) provided permanent tissue sample loans.

Carl Kilcrease (USDA FS Holly Springs) and Hal Robinson (University of Mississippi) provided and assisted with the analysis of geospatial data. I must also give a gigantic thank you to Jacob

Houston and Martin Kelly for their help in the field, because, well, “this is research.” Also, I would not have kept my wits throughout this process if it were not for friends and members of the always delightful “Room 302”, Jason Payne, Jarod Sackreiter, Dr. Bridget Piculell, Chaz

Hyseni, Mariah Meachum, Amber Horning, Jake Dennison, Cavan Holley, Seth Johnson, John

Rock, Reese Worthington, and Dr. Ann Rasmussen.

Finally, I would like to thank my wife, Randi Robison, and family for constantly encouraging me. Without question, any good character I possess was built and molded by you.

TABLE OF CONTENTS

ABSTRACT ...... ii

DEDICATION ...... iv

ACKNOWLEDGMENTS ...... v

LIST OF FIGURES ...... viii

LIST OF TABLES ...... x

INTRODUCTION ...... 1

METHODS ...... 4

RESULTS ...... 14

DISCUSSION ...... 26

REFERENCES ...... 30

VITA ...... 37

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LIST OF FIGURES

Figure 1. Map of stream network and paired stream sampling sites within Holly Springs National Forest. Road-free streams are designated by open circles and road-crossed streams by filled circles. Pairs of sampling sites are within 3 km direct distance of one another and located on 1st or 2nd order streams. Inset map shows location of the HSNF boundary within the state of Mississippi...... 6

Figure 2. Sampling schematic illustrating typical layout of transects in relation to road, stream, and one another. Dimensions and distance measurements are provided with notations on where methods began and, or were conducted...... 8

Figure 3. Diagram illustrating hierarchical structure of experimental design and its relation to the sampling design. Abundance and species richness were measured at the transect scale, the sampling unit. Data was aggregated (averaged) to higher order scales for analysis to appropriately partition variance and degrees of freedom. All lower levels shown for Road-crossed streams were also included for Road-free streams although the entire hierarchy is not shown...... 12

Figure 4. Frequency of the number of individuals sampled at each transect. Individuals were pooled together for all species in each sample. All samples taken throughout the study were pooled...... 14

Figure 5. Average abundance and species richness per transect (±1 SE), in road-free versus road-crossed streams. Open bars identify road-free streams and filled bars identify road-crossed streams...... 16

Figure 6. Total salamander abundance (±1 SE) in transects at each of the five positions from road or midpoint in the first (June) and second (mid-July to mid-August) periods; pint = 0.10 for interaction, also shown by intersecting lines...... 19

Figure 7. Salamander species richness (±1 SE) within transects at each of the five positions from road or midpoint in the first (June) and second (mid-July to mid-August) periods; pint = 0.02 for interaction, also shown by intersecting lines...... 19

Figure 8. Average abundance per transect (±1 SE) at each of the five positions from road or midpoint.

Road-free streams are identified by open bars and road-crossed streams are identified by filled bars; pint = 0.30 is the road × position interaction effect...... 20

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Figure 9. Average species richness per transect (±1 SE) of the five positions from road or midpoint. Road- free streams are identified by open bars and road-crossed streams are identified by filled bars; pint = 0.19 is the road × position interaction effect...... 21

Figure 10. Frequency distributions of total number of individuals in a sample of road-crossed and road- free streams (G5 = 42.39, p = <0.01). Road-free streams distribution is identified by open bars and road- crossed stream distribution is identified by filled bars...... 22

LIST OF TABLES

Table 1. Analysis of variance table for stream-associated total salamander abundance...... 17

Table 2. Analysis of variance table for stream-associated salamander species richness...... 18

Table 3. Number of individuals for three most abundant species within road-crossed and road-free streams...... 23

Table 4. Summary of ANOVA results for individual species. Species names appear in the first column, followed by total number of individuals of given species, and p-values for select factors...... 23

Table 5. Number of individuals of the three most abundant species with respect to road and position, and results of Fisher's exact test of contingency of these observations. Probability values for Fisher's exact test are estimated with 1e+06 Monte Carlo simulations...... 23

Table 7. Analysis of variance table for canopy closure at stream scale...... 25

Table 8. Analysis of variance table for air temperature at stream scale...... 25

INTRODUCTION

Roads are a common feature of the landscape that affect wildlife directly through mortality suffered during crossing, and by fragmenting habitat into smaller parts and by creating edge effects that are less than optimal for population sustainability (Cunnington et al. 2014,

Forman and Alexander 1998). Indirect effects of roads may include altering microclimate conditions, such as increased sunlight penetration, runoff from the road surface, and facilitating movement or dispersal of edge-associated invasive species (Arévalo et al. 2005, Collins and

Russell 2009, Delgado et al. 2007). Edges can induce or create conditions that alter an organism’s exposure (e.g., dust, wind), habitat (e.g., vegetative structure), competition and predation, and environmental conditions (e.g., air temperature, water pH) and movement

(Andrews et al. 2008), although it is not certain how far these effects extend beyond the road itself. The area surrounding the road that encompasses the full range of road effects on wildlife and their habitat is known as the road-effect zone (Forman and Alexander 1998). A generalized road-effect zone of 1-km is estimated to affect 15–20% of wildlife communities within the U.S.

(Coffin 2007, Forman and Alexander 1998).

The influence of the road-effect zone on stream-associated salamanders and their communities is of particular concern (Clipp and Anderson 2014, Forman and Alexander 1998,

Marsh and Beckman 2004, Welsh and Ollivier 1998), because of their physiological and life history characteristics that make them vulnerable to environmental change that is often associated with roads (Andrews et al. 2008, Davic and Welsh 2004, Semlitsch et al. 2014). They

1 also have semipermeable skin, which can readily absorb harmful substances potentially present in runoff from road surfaces (e.g., oil and grease, salts; Collins and Russell 2009). Amphibians also respire and perform osmoregulation through their skin (Vitt and Caldwell 2013), so changes caused by edges may alter their ability to perform these tasks (O’Donnell et al. 2014, Peterman and Semlitsch 2013). Determination of the magnitude and extent of the road-effect zone depends on the type and number of species that scientists measure (Andrews et al. 2008, Semlitsch et al.

2007). The Gray Treefrog (Hyla versicolor) showed a threshold response at approximately 250 m from the road, while the Western Chorus Frog (Pseudacris triseriata) showed a threshold at approximately 1400 m (Eigenbrod et al. 2009).

Since salamander assemblages are essential to energy pathways in ecosystems, it is critical to characterize the influence of road-crossings and evaluate the size of the road-effect zone for stream-associated salamanders. Stream-associated salamanders dominate vertebrate assemblages in and along headwater streams (Burton and Likens 1975, Peterman et al. 2008,

Semlitsch et al. 2014). Their biomass often exceeds that of nearby fish and terrestrial salamanders (Petranka 1983, Resetarits 1997, Wilkins and Peterson 2000). They are an abundant, high quality energy source capable of damping random fluctuations in energy flow by acting as nutrient pools for predators through succession after disturbance (Burton and Likens 1975, Davic and Welsh 2004). Members of this obligate carnivore group play a key role in the flow of nutrient and energy by regulation of detritivores and invertebrates within small stream systems – detritivores breakdown leaf matter (Cardinale et al. 2006, Hairston 1987, Peterman et al. 2008).

The absence of stream-associated salamanders could negatively affect riparian forest health and increase nutrient losses downstream (Best and Welsh, Jr. 2014, Petranka and Smith 2005).

Despite the importance of stream-associated salamanders, little is known about the effect

2 of roads on salamanders outside of Appalachia, which is known for its high species diversity and variety of salamander habitats. Marsh and Beckman (2004) and Semlitsch et al. (2007) found that roads lower terrestrial salamander abundance and species richness in the first 20–40 m from the road.

To better understand the road effect zone in salamanders in an area with lower salamander species diversity, I focused on stream-associated salamanders in northern Mississippi

(Holly Springs National Forest) where major disturbances are limited to forest management (e.g., prescribed burns and timber harvest) effects and roads. In this project, I tested three hypotheses:

1. Abundance and species richness would vary between road-crossed and road-free streams;

2. Abundance and species richness would be influenced by distance from the road crossing;

and

3. Areas surrounding roads have differences in physical environment when compared to

areas without roads that would affect abundance and species richness.

METHODS

To examine the effect of road crossings on stream-associated salamanders, I compared abundance and species richness in 12 pairs of streams. Each pair consisted of one road-crossed stream and one road-free stream that were within 3 km direct distance of one another and that were confluent downstream of sample sites. I recorded the number of individuals of each species found (abundance) and species richness at five transects in the upstream and downstream reaches from each road crossing or an equivalent midpoint in the case of road-free streams.

Study area and site selection

The study area was within the Holly Springs National Forest (HSNF) located in north

Mississippi. Holly Springs National Forest is a mix of federally (628 km2) and privately (2,145 km2) owned property composed of pine and upland hardwoods, most of which was converted from eroding farmland during the late 1930s through 1940s (Holly Springs Ranger District

2011). The forest lies at elevations between 130 to 170 m and is managed for production of timber and recreational activities (e.g., camping, swimming, and hiking). Sample streams were chosen within federally managed forestland in areas free of recent prescribed burns, channelized streams and constructed dams.

Streams were not randomly selected across the landscape. Because of possible variation within the forest due to past management, streams with and without a road crossing were paired in the study design. I based the stream selection on criteria with Strahler Stream Order less than

4 or equal to 2nd order, which is based on a hierarchical classification of tributaries — headwaters are 1st order streams and combine to create 2nd order streams and so forth, but only the confluence of two equal streams of equal order result in an increase in stream order (Horton

1945, Strahler 1952). Sampled streams could be either 1st or 2nd order, but each stream in a pair would be of the same order. Selected streams were restricted to those with uninterrupted reach lengths of approximately 150 m, and no more than 3 km direct distance and no more than 9 km stream distance between road-crossed to road-free sites (Allan and Castillo 2007). Selection of streams was narrowed using the Vector Analysis, Geoprocessing, and Geometry tools within the

Quantum Geographic Information Systems Program (QGIS Development Team 2015). The resulting sites were inspected using satellite imagery and ground-truthing. The final twelve pairs of streams were located within sub-watersheds of the Little Tallahatchie Basin (HUC 0803201),

Yocona Basin (HUC 08030203), Wolf Basin (HUC 08010210) and Coldwater Basin (HUC

08030204; Boundary Descriptions and Names of Regions, Subregions, Accounting Units and

Cataloging Units, 2014). Sample coordinates were uploaded to a hand-held GPS unit (Garmin etrex 20) and Google Maps (Google Maps 2015) for use with mobile devices (Fig. 1).

Study species

Using distribution maps (Global Biodiversity Information Facility 2017, Petranka 2010) and natural history characteristics, I identified nine putative species from four salamander families that are likely to occur in HSNF. From the family Plethodontidae there were five species: the Mississippi Slimy Salamander (Plethodon mississippi), the Three-lined Salamander

(Eurycea guttolineata), the Southern Two-lined Salamander (Eurycea cirrigera), the Northern

Red Salamander (Pseudotriton ruber ruber), and the Spotted Dusky Salamander (Desmognathus conanti) (Crother 2012). The Mississippi Slimy Salamander is perhaps the least stream- associated of these species, and uses a wide variety of habitat from bottomland forest to riparian areas and unusual habitat (e.g., they are sometimes found under rubbish; Lannoo 2005). The other four species from this family rely on wetland habitat of various types (e.g., headwater streams, seeps, and springs). They require aquatic habitat to successfully metamorphose and use stream habitat for forage, cover, and reproduction (Petranka 2010). From Proteidae, there were two anticipated species, the Common Mudpuppy (Necturus maculosus maculosus) and the Gulf

Coast Waterdog (Necturus beyeri). There was one species from each of two other families,

Sirenidae and Amphiumidae: the Lesser Siren (Siren intermedia) and the Three-toed Amphiuma

(Amphiuma tridactylum). These latter four species are fully aquatic through all life stages. The

Common Mudpuppy and Gulf Coast Waterdog are typically found in larger streams, but have been caught in smaller headwaters and ditches (Petranka 2010). Lesser Sirens prefer slow moving creeks, ditches, or vegetation-choked streams and the Three-toed Amphiuma can be found in streams and creeks, especially within disturbed habitat (e.g., suburban and agricultural ditches; Petranka 2010, Lannoo 2005). The four fully-aquatic species were expected to be more difficult to capture based on their preferred habitat and secretive nature.

Sampling scheme

All sites were sampled once in June and again in mid-July to mid-August 2015 except for three pairs of streams that were dry during the second visit. Surveys began at least 30 minutes after sunset, as stream-associated salamanders are more active at night and in cooler temperatures, and took approximately 80 minutes per stream to complete (Williams and Berkson

2004).

Five transects at 0 (road-forest edge), 9, 18, 27, and 36 m on each side of the road or midpoint in the case of road-free streams were evaluated. Midpoints of road-free streams were

8 determined by approximating the road and shoulder width (5-25 m) in the road-crossed streams and using these measurements to determine the midpoint for each paired road-free stream. In each stream, a total of ten, 2-m × 20-m transects were searched (five upstream from road- crossing or midpoint and five downstream; Fig. 2).

In order to increase chances of capturing the entire stream-associated salamander assemblage that inhabit many different parts of a stream (e.g., stream bank, riparian area, stream waters), three sampling techniques were used: electroshocking, trap sampling and visual transect surveys (standard methods from Heyer et al. 1994). For each stream, microclimate factors were measured first and were followed by electroshocking at the most distal downstream transect, and continued to the most distal upstream transect. Two people worked together while electroshocking, one controlling the electrode while the other used a net to capture stunned animals. When electroshocking was conducted, a third person followed behind placing funnel traps in pools of the streams. After setting traps visual transect surveys were used, starting at the most distal upstream transect. Each transect began at the water's edge and continued outward, inspecting the ground surface and under natural cover with rakes. As specimens were encountered (visual transect surveys) or captured (electroshocking and traps) salamanders, they were identified to species and returned to where they were found.

Explanation of sampling techniques with justification

Electroshocking – Electroshocking was used to survey aquatic salamander species. The technique works by creating an electric field that organisms pass through and are stunned. While the organism(s) are incapacitated, a partner captures them with a net for species identification

(Cossel et al. 2012). A wide-mouth net and headlamps (>250 lumen) were used to reduce

9 likelihood of missed capture. This method is widely used survey method in fisheries science because of its versatility in various aquatic habitats, low impact on fish and other animals and relative ease of use. It has been shown to detect salamanders more often and detect more total individual salamanders than some other techniques (e.g., seining and rock rolling; Cossel et al.

2012). Thus, it can help provide a more comprehensive description of amphibian assemblages

(Olson and Rugger 2007).

Trap sampling – Minnow traps were set within pools of the stream’s thalweg (deepest part of channel). This technique was chosen as it has been shown to be successful for capturing aquatic salamander species, as they seek refuge within the trap (Johnson and Barichivich 2004).

Commercial minnow funnel traps (32cm × 62cm) were set and secured them with rope tied to a stake driven into the stream bank. Traps were checked and retrieved within 24-hrs.

Visual surveys – At each of the transect locations we preformed visual transect surveys on either side of the stream with aid of headlamps and small garden rakes (to safely move natural cover and limit encounters with venomous snakes). This method of transect sampling consists of thoroughly searching under natural cover (e.g., leaf litter, large woody debris) within the transect area. It was chosen because it is effective in obtaining presence, abundance, and density of stream-associated salamanders. This allows for statistical inferences to be drawn from data, as each transect is considered an independent sample (Heyer et al. 1994).

Microclimate factors

Microclimate measurements were either taken once at each stream location (e.g., water temperature) or pooled from transects (e.g., canopy closure) for stream scale analysis. Three

10 water quality parameters were taken immediately after the first sampling (to avoid pre-sampling disturbance) with a handheld multi-parameter water quality instrument (YSI 556): pH, dissolved oxygen (DO), and water temperature (°C). Other microclimate variables measured included dominant forest type (i.e., coniferous, hardwood), air temperature at ground level (°C), relative humidity at ground level (%), substrate composition, and estimated canopy closure (%; Heyer et al. 1994), all taken with hand-held instruments (Kestrel 4500 Weather & Environmental Meter and optical canopy densitometer).

Sampling Design

I used a sampling design that reflected the hierarchical structure of the experimental design — paired streams representing different areas of the forest, with and without road crossings, reaches upstream and downstream of the crossing or midpoint, position or distance within each reach relative to road or midpoint, and twice sampled (repeated measures; Fig. 3).

Statistical analyses

Because abundance measures are more appropriate for well-sampled and common species and categorical measures (presence or absence) are often more useful for rare species, several data types were prepared for analysis: total salamander counts, species richness, and abundance or presence or absence of individual species.

A nested analysis of variance (ANOVA) model with paired sites as a blocking factor (to account for geographic variation in the forest), road as a whole-plot treatment factor, period as a repeated measures factor, and reach and position (distance from midpoint) as within-treatment factors was used. To assure that variance and degrees of freedom were partitioned appropriately for each level of the design, data was aggregated and the error terms were specified for the whole and subplot in this design (Logan 2010). These models tested two hypotheses: 1) if abundance and species richness differed between road-free and road-crossed streams and 2) if abundance and species richness differed with distance from the road. Association of abundance and species richness with microclimate was evaluated with correlation and regression. For presence or absence data a G-test was used to evaluate association of the responses (presence of individual species) with design features (e.g., road-free vs. road-crossed streams). Correlation and regression analyses were used to examine the relationship of microclimate variables to salamander abundance or species richness.

Significance levels were chosen at ⍺ = 0.10, as failure to reject a false null hypothesis poses a greater risk to evaluating how stream-associated salamanders are affected by roads. All calculations and analysis were conducted in R Development Core Team R v 3.3.2 (2016) and

Microsoft Excel (2016).

RESULTS

A total of 256 salamanders, consisting of five species were caught. The most common species were the Three-lined Salamander (Eurycea guttolineata), Mississippi Slimy Salamander

(Plethodon mississippi), and the Southern Two-lined Salamander (Eurycea cirrigera). These species composed 58.2%, 31.6%, and 8.9% of the captures, respectively. Two Eastern Newt

(Notophthalmus viridescens) and a single Marbled Salamander (Ambystoma opacum) made up the remaining 1.3%. Neither of these species were expected to be captured during the survey, but their presence around streams is not unprecedented (Hurlbert 1969, Marangio and Anderson

1977). The other expected species were not encountered. Roughly sixty percent of the samples taken had no salamanders present when sampled (Fig. 4).

Figure 4. Frequency of the number of individuals sampled at each transect. Individuals were pooled together for all species in each sample. All samples taken throughout the study were pooled. 14

Of the methods used to capture salamanders, visual surveys were most successful.

Electroshocking was effective in sampling fishes and macroinvertebrates, but only three, Three- lined Salamanders were captured using this method. None of the aquatic salamanders for which it was specifically chosen were observed. Most streams were too shallow to permit trap sampling, but when possible, only small fish and macroinvertebrates were captured. The subsequent results focus on abundance and species richness of salamanders captured in the transect surveys.

The nested ANOVA showed that salamander abundance and species richness differed between road-crossed and road-free streams. I found significant differences in total salamander abundance (F1, 11 = 14.44, p = <0.01) and species richness (F1, 11 = 20.58, p = <0.01) between road-crossed and road-free streams (Fig. 5, Tables 1 and 2). Road-free streams averaged 2.5 as many individuals per transect and 2.4 times the species richness per transect as road-crossed streams.

Figure 5. Average abundance and species richness per transect (±1 SE), in road-free versus road-crossed streams. Open bars identify road-free streams and filled bars identify road- crossed streams.

Table 1. Analysis of variance table for stream-associated total salamander abundance. Abundance df SS MS F value p (>F) Site 11 3.92 0.36 3.87 0.02 Road 1 1.33 1.33 14.44 <0.01 Residuals 11 1.01 0.09 Period 1 0.56 0.56 2.87 0.11 Road × Period 1 0.09 0.09 0.44 0.52 Residuals 16 3.14 0.20 Reach 1 0.26 0.26 0.39 0.53 Position 4 0.97 0.24 0.37 0.83 Road × Reach 1 0.05 0.05 0.08 0.78 Period × Reach 1 0.26 0.26 0.39 0.53 Road × Position 4 3.18 0.80 1.21 0.30 Period × Position 4 5.14 1.29 1.96 0.10 Reach × Position 4 2.49 0.62 0.95 0.44 Road × Period × Reach 1 0.20 0.20 0.31 0.58 Road × Period × Position 4 1.94 0.49 0.74 0.56 Road × Reach × Position 4 3.38 0.84 1.29 0.27 Period × Reach × Position 4 1.54 0.39 0.59 0.67 Road × Period × Reach × Position 4 0.94 0.24 0.36 0.87 Residuals 342 224.06 0.66

Table 2. Analysis of variance table for stream-associated salamander species richness. Species Richness df SS MS F value p (>F) Site 11 2.01 0.18 4.55 <0.01 Road 1 0.83 0.83 20.58 <0.01 Residuals 11 0.44 0.04 Period 1 0.15 0.15 1.88 0.19 Road × Period 1 0.03 0.03 0.39 0.54 Residuals 16 1.25 0.08 Reach 1 0.02 0.02 0.08 0.78 Position 4 1.38 0.35 1.13 0.34 Road × Reach 1 0.05 0.05 0.15 0.70 Period × Reach 1 0.56 0.56 1.83 0.18 Road × Position 4 1.84 0.46 1.51 0.19 Period × Position 4 3.78 0.94 3.09 0.02 Reach × Position 4 0.78 0.20 0.64 0.64 Road × Period × Reach 1 0.22 0.22 0.71 0.40 Road × Period × Position 4 0.56 0.14 0.46 0.77 Road × Reach × Position 4 2.33 0.58 1.90 0.11 Period × Reach × Position 4 0.48 0.12 0.40 0.81 Road × Period × Reach × Position 4 1.06 0.27 0.87 0.48 Residuals 342 104.40 0.31

There were no significant effects at the reach scale (upstream and downstream of the road crossing or midpoint); (abundance: F1, 342 = 0.39, p = 0.53; species richness: F1, 342 = 0.08, p =

0.78) or interaction of road × position (both > 0.10). The only other significant effect in the

ANOVA was a position × period interaction (abundance: F4, 342 = 1.96, p = 0.10; species richness: F4, 342 = 3.09, p = 0.02; Fig. 6 and 7). Abundance and species richness varied between periods and position relative to stream’s midpoint in that the first period samples showed no position effect, but the second period showed higher abundance and species richness away from the midpoint (independent of a road crossing being present or not). When the model was re-run with position as a numeric variable (distance from road crossing or midpoint) the results were similar to those found without position in the model.

pint = 0.10

pint = 0.02

There was no position × road and position × road × period interaction effect (Tables 1 and 2), but it may be possible to estimate the extent of the road-effect zone given the significant road effect that was found. Abundance and species richness did not differ with distance from the road-crossing (Fig. 8 and 9). Neither abundance or species richness had slopes significantly different from zero, indicating that the road-effect zone extends beyond the 36-m distance measured. The statistical power (1 - β) for the position × road interaction effect on abundance and species richness was low, given the small effect size (abundance: β = 0.33; species richness:

β = 0.32).

pint = 0.30

Figure 8. Average abundance per transect (±1 SE) at each of the five positions from road or midpoint. Road-free streams are identified by open bars and road-crossed streams are identified by filled bars; pint = 0.30 is the road × position interaction effect.

pint = 0.19

Figure 9. Average species richness per transect (±1 SE) of the five positions from road or midpoint. Road-free streams are identified by open bars and road-crossed streams are identified by filled bars; pint = 0.19 is the road × position interaction effect..

Another approach to estimating a position effect is to see if differences in abundance and richness between the paired streams were related to the distance between paired streams, either overland or by stream network. For stream-associated salamanders neither the overland distance between each pair of streams (p = 0.47) nor the within-stream distance (p = 0.92) explained the observed variation in abundance. Overland distance (p = 0.51) and within-stream distance (p =

0.99) also failed to explain variation in species richness.

Given that only 40% of the samples contained salamanders, it could be helpful to examine road and other effects using frequency data. Using only the frequency of number of individuals in a sample in the analysis, the number of individuals in a sample varied significantly with roads (G5 = 42.39, p = <0.01; Fig. 10). When considering the effect of road × position interaction for frequency of samples containing salamanders, the analyses showed no road × position effect (G4 = 5.88, p = 0.21).

Figure 10. Frequency distributions of total number of individuals in a sample of road-crossed and road-free streams (G5 = 42.39, p = <0.01). Road-free streams distribution is identified by open bars and road-crossed stream distribution is identified by filled bars.

Based on frequency of occurrence it appears that Three-lined Salamanders are the most tolerant to roads as they experienced the least overall relative change between road-free and road-crossed streams (G2 = 17.15, p = <0.01; 36%, Mississippi Slimy Salamanders 77%,

Southern Two-lined Salamanders 90%, Table 3). When the three species abundances are analyzed separately using ANOVA, the results show a different significant effect of road and position to roads for the most abundant species (E. guttolineata), a road and period effect for P. mississippi and no effect of any model term on E. cirrigera (Table 4). Although the frequency analysis suggests the most dramatic road effect (90%) on the least abundant species and the smallest effect (36%) for the most common salamander species, the ANOVA suggests that the results differ and are more consistent with the numbers of salamanders collected providing better resolution of road effects (Table 3 and 4).

Table 3. Number of individuals for three most abundant species within road-crossed and road-free streams. E. guttolineata P. mississippi E. cirrigera Road-crossed 58 15 2 Road-free 91 66 21 G2 = 17.15, p = <0.01

Table 4. Summary of ANOVA results for individual species. Species names appear in the first column, followed by total number of individuals of given species, and p-values for select factors. Species n Site Road Period Road × Position E. guttolineata 149 0.03 0.08 ns 0.05 P. mississippi 81 0.07 <0.01 0.03 ns E. cirrigera 23 ns ns ns ns

When the frequency of samples with each species is analyzed using Fisher’s exact test with respect to the presence of roads and position (relative to the midpoint), none of the individual species show any relationship with the road × position (Table 5).

Plethodon mississippi 0 m 9 m 18 m 27 m 36 m Road-crossed 2 4 1 4 1 Road-free 14 4 12 9 11 p = 0.11

Erycea cirrigera 0 m 9 m 18 m 27 m 36 m Road-crossed 1 0 0 0 1 Road-free 1 3 5 5 2 p = 0.12

Air temperature (F1, 11 = 5.11, p = 0.04; d = 0.65) and canopy closure (F1, 10= 3.79, p =

0.08; d = 0.53) were the only microclimate variables that significantly differed between road- crossed and road-free streams. As an exploratory analysis differences between stream pairs of these microclimate variables were tested for correlations to differences in abundance and species richness. Air temperature and canopy closure were not related to difference in abundance and species richness (abundance × air temp: r = -0.37, t10 = -1.25, p = 0.24; abundance × canopy closure: r = 0.21, t10 = 0.67, p = 0.52; species richness × air temp: r = -0.30, t10 = -0.99, p = 0.34; species richness × canopy closure: r = 0.30, t10 = 1.00, p = 0.34).

Table 6. Direct and stream network distance between paired sample sites and differences in air temperature, canopy closure, abundance, and species richness between road-free to road-crossed sites. Canopy Species Block Direct (m) Stream (m) Air Temp Abundance Closure Richness 1 748.34 1227.93 0.8 21 1.45 1 2 2526.67 3540.56 0.7 21.5 1.15 0.75 3 1947.31 3765.87 1.75 5.5 0.5 0.4 4 1200.57 2108.24 1.75 17 0.3 0.3 5 576.15 725.81 1.35 5 0.45 0.35 6 1409.79 2314.46 1.35 29 0.25 0.3 7 534.3 1226.32 0.8 23 0.45 0.35 8 326.14 556.83 1.75 20.5 0.45 0.45 9 1260.82 2574.95 2.1 9 0 0 10 1705.91 9462.94 1.2 41 0.3 0.3 11 296.57 1506.35 1.2 12.5 0.4 0.3 12 540.74 476.37 0.3 0.5 -0.05 -0.05

Table 7. Analysis of variance table for canopy closure at stream scale. Variable df SS MS F p Site 11 3589.90 326.35 1.95 0.14 Road 1 635.50 635.50 3.79 0.08 Residuals 11 1842.60 167.51

Table 8. Analysis of variance table for air temperature at stream scale. Variable df SS MS F p Site 11 38.51 3.50 5.13 0.01 Road 1 3.49 3.49 5.12 0.04 Residuals 11 7.50 0.68

DISCUSSION

Roads are common features that created edge effects that affect wildlife, sometimes hundreds of meters from the road’s edge. These road edge effects have been shown to reduce abundance and richness of salamanders, an ecologically important group. Road-effect zones have also been characterized for these organisms, but studies have been limited to terrestrial landscapes in Appalachia and the pattern not well delineated within the first 40 m from the road’s edge. In this study, I compared abundance and richness of stream-associated salamanders using a hierarchical design approach (distance from road nested within stream reach nested within road-free or road-crossed streams).

The results of this study allow certain insights into the effects of road crossings on stream-associated salamanders. Stream-associated salamanders showed reduced abundance

(2.5×) and species richness (2.4×) in road-crossed streams as compared to road-free streams (Fig.

5). The average number (F1, 11 = 14.44, p = <0.01; Fig. 5) and proportion of total number of individual salamanders (G5 = 42.39, p = <0.01; Fig. 10) were significantly lower in the presence of a road crossing. The spatial extent of this effect was difficult to measure and remains uncertain due to low power to detect effects with either the ANOVA, the G-test and Fisher’s exact tests (i.e., road × position and road × position × period interactions; Fig. 8–10). However, data suggest that the road-effect zone extended beyond the 36-m position sampled, but was less than 300 m because there was no difference in abundance when road-free streams were compared to paired road-crossed streams. Since the differences in abundance and species

26 richness between road-free and road-crossed streams were not significantly correlated to differences in microclimate factors (Tables 6–8), this suggests that other factors or a combination of factors near roads contribute to reduced salamander abundance and richness. There was a sample period by distance from road interaction which suggests that sampling in the first period

(which showed no position effect relative to the road or midpoint of each sampled stream) might have influenced the distribution of salamanders in the second sampling period.

When compared to Ward et al. (2008), road crossings in this study had a larger effect on salamander abundance (2.5× v. 1.2×), despite lower overall abundance. However, the abundances observed in this study are not markedly different from others observed within

Mississippi (Hines et al. 2004, Lee 2009). Combined, these results suggest that roads negatively affect salamanders, even in an area that does not support as high a density and diversity of salamanders as found in Appalachia.

It also seems that a salamander species’ degree of association with streams does not alter the deleterious effects of road crossings. This gains support when excluding the least stream- associated species (Plethodon mississippi) and no improvement in resolution (detection a road × position effect) is made in the ANOVA models.

The magnitude of road-effects varied from species to species (Table 3) as in Ward et al.

(2008) and Eigenbrod et al. (2009; anurans), and suggests that the most tolerant species to road- effects may gain a competitive advantage. The road crossing by distance from road effect was detected for only Three-lined Salamanders (E. guttolineata; Table 4), but when frequency of samples containing individual species was examined, there was no dependence on distance from the road (Table 5). This was somewhat surprising because Marsh and Beckman (2004) and Ward et al. (2008) reported no reduction and no response in other Eurycea and Plethodon species and

27 thus, I had expected Mississippi Slimy Salamanders (P. mississippi) and Southern Two-lined

Salamanders (E. cirrigera) to be more tolerant of road crossings. This differs from the results of previous studies on which my study was based, which found the extent of road crossing effects to be 20–40 m from the road (Marsh 2007, Marsh and Beckman 2004, Semlitsch et al. 2007,

Ward et al. 2008).

Only two microclimate factors were found to differ due to roads, although other studies have shown that roads change vegetative communities and alter microclimate conditions

(Arévalo et al. 2005, Delgado et al. 2007, Forman and Alexander 1998). The factors that varied significantly with roads (canopy closure and air temperature) were not associated with abundance or species richness, unlike the results of some studies (Crawford and Semlitsch 2008,

Homyack and Haas 2009). If significant associations had been detected, they would have suggested that the altered microclimate conditions could be drivers behind reduced salamander abundance and species richness.

Considering the contrast above, it appears that characteristically similar disturbances in different regions vary in their magnitude and extent. This variation could be the result of overriding area effects (e.g., residential development) and, or an area’s disturbance regime (i.e., the magnitude, extent, and frequency of disturbance; Turner and Gardener 2001). The second of these notions introduces interesting hypotheses regarding the context dependency of characteristically similar disturbances (i.e., the magnitude of road-effects differ between areas) and could help explain the sampling period by distance form road interaction within this study.

For instance, sampling disturbance within this study area (low topological variability) could have a greater magnitude than in areas with greater topological variability (i.e., Appalachia) due to how disturbance permeates through the landscape. It is also interesting to recognized that the

28 idea of context dependency for characteristically similar disturbances may elicit different responses from similar assemblages because of an area’s disturbance frequency. Context dependency of characteristically similar disturbances might help to explain the response of salamanders to roads when little difference in microclimate can be attributed to the road.

Some limitations and assumptions to this study should be noted. I assumed that all roads, regardless of surface type, traffic frequency, or other factors fundamentally affected salamanders the same. I also sampled during hot and dry months of the year, which affect salamander activity

— salamanders will retreat underground during unfavorable surface conditions (O’Donnell and

Semlitsch 2015, Walls et al. 2013, Walls et al. 2013). Because of small sample sizes and the number of samples without any salamanders, uncertainty remains about the spatial and temporal extent of road effects. Improvements to counter these limitations would likely lead to a better delineation of road-effects’ extent, rather than only distinguishing differences between road-free and road-crossed streams.

In conclusion, roads have negative effects on stream-associated salamander abundance and species richness. The magnitude of road-effects on salamander abundance varies by species and likely extend beyond 36 m. These deleterious effects have implications for the disruption of energy pathways in ecosystems, regulation of invertebrate assemblages, and riparian forest health (Best and Welsh, Jr. 2014, Burton and Likens 1975, Davic and Welsh 2004, Peterman et al. 2008, Petranka and Smith 2005, Semlitsch et al. 2014). Additional sampling in other seasons and expanded surveys might help to resolve uncertainty about spatial and temporal variation.

Future research might also include components of salamander movement using mark-recapture techniques, since there are some suggestions that there are substantial temporal changes in location of the salamanders in this community.

REFERENCES

Allan, J.D., and M.M. Castillo. 2007. Stream ecology: Structure and function of running waters. Ecology. Second. Springer, Dordrecht, Netherlands. 436 pp.

Andrews, K., W. Gibbons, and D. Jochimsen. 2008. Ecological effects of roads on amphibians and reptiles: a literature review. Pp. 121–143, In. Herpetological Conservation. Vol. 3. Available online at http://transwildalliance.org/resources/2009101416234.pdf.

Arévalo, J.R., J.D. Delgado, R. Otto, A. Naranjo, M. Salas, and J.M. Fernández-Palacios. 2005. Distribution of alien vs. native plant species in roadside communities along an altitudinal gradient in Tenerife and Gran Canaria (Canary Islands). Perspectives in Plant Ecology, Evolution and Systematics 7:185–202.

Best, M.L.M., and H.H. Welsh, Jr. 2014. The trophic role of a forest salamander: impacts on invertebrates, leaf litter retention, and the humification process. Ecosphere 5:1–19. Available online at http://www.esajournals.org/doi/abs/10.1890/ES13-00302.1.

Burton, T.M., and G.E. Likens. 1975. Salamander Populations and Biomass in the Hubbard Brook Experimental Forest, New Hampshire. Copeia 1975:541. Available online at http://www.jstor.org/stable/1443655?origin=crossref.

Cardinale, B.J., D.S. Srivastava, J.E. Duffy, J.P. Wright, A.L. Downing, M. Sankaran, and C. Jouseau. 2006. Effects of biodiversity on the functioning of trophic groups and ecosystems. Nature 443:989–992. Available online at http://www.ncbi.nlm.nih.gov/pubmed/17066035.

Clipp, H.L., and J.T. Anderson. 2014. Environmental and Anthropogenic Factors Influencing Salamanders in Riparian Forests: A Review. 2679–2702.

Coffin, A.W. 2007. From roadkill to road ecology: A review of the ecological effects of roads. Journal of Transport Geography 15:396–406.

Collins, S.J., and R.W. Russell. 2009. Toxicity of road salt to Nova Scotia amphibians.

Environmental Pollution 157:320–324. Elsevier Ltd. Available online at http://dx.doi.org/10.1016/j.envpol.2008.06.032.

Cossel, J.O., M.G. Gaige, and J.D. Sauder. 2012. Electroshocking as a survey technique for stream-dwelling amphibians. Wildlife Society Bulletin 36:358–364.

Crawford, J. a., and R.D. Semlitsch. 2008. Abiotic factors influencing abundance and microhabitat use of stream salamanders in southern Appalachian forests. Forest Ecology and Management 255:1841–1847.

Crother (ed.), B.I. 2012. Scientific and standard English names of amphibians and reptiles of North America north of Mexico, with comments regarding confidence in our understanding. SSAR Herpetological Circular. Vol. 39. 1-92 pp. Available online at http://www.ssarherps.org.

Cunnington, G.M., E. Garrah, E. Ewen, and L. Fahrig. 2014. Culverts Alone do not Reduce Road Mortality in Anurans. Ecoscience 21:69–78. Available online at http://www.bioone.org/doi/abs/10.2980/21-1-3673.

Davic, R.D., and H.H.J. Welsh. 2004. On the Ecological Roles of Salamanders. Annu. Rev. Ecol. Evol. Syst. 35:405–434.

Delgado, J.D., N.L. Arroyo, J.R. Arévalo, and J.M. Fernández-Palacios. 2007. Edge effects of roads on temperature, light, canopy cover, and canopy height in laurel and pine forests (Tenerife, Canary Islands). Landscape and Urban Planning 81:328–340.

Eigenbrod, F., S.J. Hecnar, and L. Fahrig. 2009. Quantifying the road-effect zone: Threshold effects of a motorway on anuran populations in Ontario, Canada. Ecology and Society 14.

Forman, R.T.T., and L.E. Alexander. 1998. Roads and Their Major Ecological Effects. Annual Review of Ecology and Systematics 29:207–231.

Global Biodiversity Information Facility. 2017. Eurycea guttolineata and Eurycea cirrigera and Plethodon mississippi and Pseudotriton ruber ruber and Desmognathus conanti and Necturus maculosus and Necturus beyeri and Amphiuma tridactylum and Siren intermedia. GBIF.org, Copenhagen. Available online at http://data.gbif.org.

Google Maps. 2015. M.Sc. Map. Available online at

https://www.google.com/maps/@34.6491798,- 89.50426,10z/data=!3m1!4b1!4m2!6m1!1szG7irc0PqrAI.k5XEqN8t4Ob0?hl=en. Accessed May 20, 2015.

Hairston, N.G. 1987. Community ecology and salamander guilds. 1st edition. Cambridge University Press, New York. 230 pp.

Heyer, W.R., M.A. Donnelly, R.W. McDiarmid, L.-A.C. Hayek, and M.S. Foster. 1994. Measuring and Monitoring Biological Diversity: Standard Methods for Amphibians. Biological Diversity Handbook Series. Vol. 44. 364 pp.

Holly Springs Ranger District. 2011. About the National Forest in Mississippi. Available online at http://www.fs.usda.gov/detail/mississippi/about-forest/districts/?cid=stelprdb5209589. Accessed February 11, 2016.

Homyack, J.A., and C.A. Haas. 2009. Long-term effects of experimental forest harvesting on abundance and reproductive demography of terrestrial salamanders. Biological Conservation 142:110–121. Elsevier Ltd. Available online at http://dx.doi.org/10.1016/j.biocon.2008.10.003.

Horton, R.E. 1945. Erosional development of streams and their drainage basins: hydro-physical approach to quantitative morphology. Geological Society of America Bulletin 56:275–370.

Hurlbert, S.H. 1969. The Breeding Migrations and Interhabitat Wandering of the Vermilion- Spotted Newt Notophthalmus viridescens (Rafinesque). Ecological Monographs 39:465– 488. Available online at http://www.jstor.org.umiss.idm.oclc.org/stable/pdf/1942356.pdf. Accessed April 9, 2017.

Johnson, S.A., and W.J. Barichivich. 2004. A simple technique for trapping Siren lacertina, Amphiuma means, and other aquatic vertebrates. Journal of Freshwater Ecology 19:263– 269. Available online at http://dx.doi.org/10.1080/02705060.2004.9664540.

Lannoo, M.J. (Ed.). 2005. Amphibian declines: The conservation status of Unites States species. University of California Press, Ltd., Berkely and Los Angeles, CA. 1097 pp.

Logan, M. 2010. Biostatistical Design and Analysis Using R. 517 pp. Available online at http://doi.wiley.com/10.1002/9781444319620.

Marangio, M.S., and J.D. Anderson. 1977. Soil moisture preference and water relations of the marbled salamander, Ambystoma opacum (Amphibia, Urodela, Ambystomatidae). Journal of Herpetology 169–176.

Marsh, D.M., and N.G. Beckman. 2004. Effects of forest roads on the abundance and activity of terrestrial salamanders. Ecological Applications 14:1882–1891.

Microsoft. 2016. Microsoft Excel 2016. Redmond, Washington.

O’Donnell, K.M., F.R. ThompsonIii, and R.D. Semlitsch. 2014. Predicting Variation in Microhabitat Utilization of Terrestrial Salamanders. Herpetologica 70:259–265. Available online at http://dx.doi.org/10.1655/HERPETOLOGICA-D-13-00036.

Olson, D.H., and C. Rugger. 2007. Preliminary study of the effects of headwater riparian reserves with upslope thinning on stream habitats and amphibians in western Oregon. Forest Science 53:331–342.

Peterman, W.E., J.A. Crawford, and R.D. Semlitsch. 2008. Productivity and significance of headwater streams: Population structure and biomass of the black-bellied salamander (Desmognathus quadramaculatus). Freshwater Biology 53:347–357.

Peterman, W.E., J. a. Crawford, and R.D. Semlitsch. 2008. Productivity and significance of headwater streams: Population structure and biomass of the black-bellied salamander (Desmognathus quadramaculatus). Freshwater Biology 53:347–357.

Peterman, W.E., and R.D. Semlitsch. 2013. Fine-Scale Habitat Associations of a Terrestrial Salamander: The Role of Environmental Gradients and Implications for Population Dynamics. PLoS ONE 8.

Petranka, J. 1983. Fish predation: a factor affecting the spatial distribution of a stream-breeding salamander. Copeia 1983:624–628. Available online at http://www.jstor.org/stable/1444326.

Petranka, J.W. 2010. Salamanders of the United States and Canada. P. Strupp, R. Spiegel, and L. McKnight (Eds.). Smithsonian Institution, Washington DC. 587 pp.

Petranka, J.W., and C.K. Smith. 2005. A functional analysis of streamside habitat use by southern Appalachian salamanders: Implications for riparian forest management. Forest

Ecology and Management 210:443–454.

QGIS Development Team. 2015. Quantum Geographic Information Systems. Project Open Source Geospatial Foundation. Available online at http://qgis.osgeo.org.

R Core Team. 2016. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available online at https://www.r-project.org/.

Resetarits, W.J. 1997. Differences in an ensemble of streamside salamanders (Plethodontidae) above and below a barrier to brook trout. Amphibia-Reptilia 18:15–25.

Semlitsch, R.D., K.M. O’Donnell, and F.R. Thompson III. 2014. Abundance, biomass production, nutrient content, and the possible role of terrestrial salamanders in Missouri Ozark forest ecosystems. Canadian Journal of Zoology.

Semlitsch, R.D., T.J. Ryan, K. Hamed, M. Chatfield, B. Drehman, N. Pekarek, M. Spath, and A. Watland. 2007. Salamander abundance along road edges and within abandoned logging roads in Appalachian Forests. Conservation Biology 21:159–167.

Strahler, A.N. 1952. Hypsometric (area-altitude) analysis of erosional topology. Geological Society of America Bulletin 63:1117–1142.

Vitt, L.J., and J.P. Caldwell. 2013. Herpetology: an introductory biology of amphibians and reptiles. 4th edition. Academic Press.

Ward, R.L., J.T. Anderson, and J.T. Petty. 2008. Effects of road crossings on stream and streamside salamanders. Journal of Wildlife Management 72:760–771. Available online at http://www.bioone.org/doi/abs/10.2193/2006-420%5Cn%3CGo to ISI%3E://WOS:000254412800024.

Welsh, H.H., and L.M. Ollivier. 1998. Stream amphibians as indicators of ecosystem stress: A case study from California’s redwoods. Ecological Applications 8:1118–1132.

Wilkins, R.N., and N.P. Peterson. 2000. Factors related to amphibian occurrence and abundance in headwater streams draining second-growth Douglas-fir forests in southwestern Washington. Forest Ecology and Management 139:79–91.

Williams, A., and J. Berkson. 2004. Reducing false absences in survey data: detection probabilities of red-backed salamanders. Journal of Wildlife Management 68:418–428.

Available online at http://www.bioone.org/doi/abs/10.2193/0022- 541X(2004)068[0418:RFAISD]2.0.CO;2.

VITA

Caleb A. Aldridge was born in Winfield, Alabama, on September 23, 1989. He graduated from Hubbertville School in Glen Allen, Alabama in May of 2008 and began work on his undergraduate degree the following fall. He graduated from the University of North Alabama in the summer of 2012 with a Bachelor of Science in Biology, minoring in Chemistry. Following graduation, he interned with the Alabama Wildlife and Fisheries Department at Freedom Hills

Wildlife Management Area in Cherokee, Alabama under the supervision of Mitchell Marks. In

August 2014 he enrolled at the University in pursuit of a Master of Science in Biology, and defended his thesis on March 29, 2017. He currently works as a research associate for the

R.E.A.C.H. program in the Wildlife, Fisheries, and Aquaculture Department at Mississippi State

University, Starkville, MS.