Habitat Selection of Dusky Grouse on a Biosolids-Remediated

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HABITAT SELECTION OF DUSKY GROUSE ON A BIOSOLIDS-REMEDIATED

CATTLE RANCH IN BRITISH COLUMBIA

Kirstie Jaylene Lawson

B.S., University of Montana, 2012

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF

THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF SCIENCE

THE COLLEGE OF GRADUATE STUDIES

(Biology)

THE UNIVERSITY OF BRITISH COLUMBIA

(Okanagan)

July 2018

HABITAT SELECTION OF DUSKY GROUSE ON A BIOSOLIDS-REMEDIATED CATTLE RANCH IN BRITISH COLUMBIA

submitted by Kirstie Jaylene Lawson in partial fulfillment of the requirements of

the degree of Master of Science .

Dr. Karen Hodges, Irving K. Barber School of Arts and Sciences

Supervisor

Frank Doyle, Wildlife Dynamics Consulting

Supervisory Committee Member

Dr. Bob Lalonde, Irving K. Barber School of Arts and Sciences

Supervisory Committee Member

John Lavery, SYLVIS Environmental Services

Supervisory Committee Member

Dr. Trudy Kavanaugh, Irving K. Barber School of Arts and Sciences

University Examiner

Abstract

In North America, habitat loss and fragmentation have caused declines in many gallinaceous species. Before we can understand how these changes to a landscape affect an individual species, we must first understand how that species uses their habitat. Our understanding of dusky grouse (Dendragapus obscurus) habitat selection is lacking and I focus my research on increasing our knowledge of this forest grouse species. In this thesis, I assess microhabitat selection at nesting and brood-rearing sites, as well as patch-level habitat selection and the effects of biosolids on amendments on habitat selection of dusky grouse. I trapped and radio-collared 26 dusky grouse hens during 2016-2017 and tracked individuals throughout the summer months (May-July). I used model selection in an AIC framework to determine which vegetation variables affect dusky grouse choice of nesting and brood-rearing sites at the microhabitat level. Dusky grouse are habitat generalists. However, hens selected nest sites with high visual cover, and nest success was positively influenced by visual obstruction of the nest bowl. This suggests that cover from predators is important when hens select nest sites, and that predation may be influenced by the predator’s ability to see the nest. Brood sites were more variable, and brood hens appeared to choose sites based on non-vegetative variables.

Furthermore, the use of biosolids, treated human waste, on the landscape allowed me to look at dusky grouse use these amendments. I assess broad-scale habitat select through patch-level use of available habitat types and the distance dusky grouse traveled into biosolids-amended and untreated grasslands. I found drastic year differences in selection and use of grasslands, and weather or food abundance may play a role in site selection. In 2017, a much drier, warmer year, dusky grouse hens traveled significantly further into biosolids-amended grasslands than untreated grasslands. In 2016, hens traveled much further into grasslands overall, showing

iii similar distributions in both biosolids-amended and untreated grasslands. My research suggests that biosolids may be beneficial for dusky grouse in drought years, by enhancing plant growth and increasing insect densities.

Lay Summary

Little is known about how dusky grouse, a forest grouse species found in Western North

America, use the habitat available to them. I evaluated use of this habitat at a small scale, choice of nest sites and sites to raise their chicks, and at a large scale, choice of forest and grassland patches. I found that the amount of visual cover is important to the choice of nest sites and to nest success, providing cover from animals that might attack the nest. Dusky grouse prefer conifer forests, but females will travel further into grasslands during years with more precipitation and cooler summers. The use of biosolids, treated human waste, on grasslands at the ranch may be beneficial to dusky grouse during drought years, decreasing the rate at which the vegetation dries out and increasing food available to grouse.

Preface

For this research, I was responsible for designing the study, conducting fieldwork, analyzing the data, and writing and editing this thesis. Dr. Karen Hodges and Frank Doyle provided feedback throughout the process and guided me on which techniques to use. The original research idea was requested by the Upland Bird Society, and Dr. Hodges and Frank

Doyle came up with the initial concepts of the research. Frank Doyle assisted with fieldwork, training me on trapping techniques for dusky grouse, and provided field support throughout the study.

Dr. Bob Lalonde and John Lavery provided comments on the original research proposal and the written thesis. Fieldwork was completed with the help of Megan Buers and Emma

Gaudreault.

Both data chapters will be submitted to peer-reviewed journals. The publications arising from Chapter 2 and Chapter 3 will be co-authored by myself, Dr. Karen Hodges, and Frank

Doyle. This research will also be published in concert with a larger study on biosolids impacts on wildlife.

All animal handling techniques used in this research were approved by the University of

British Columbia Animal Care Committee (Certificate # A15-0216) and the British Columbia

Ministry of Forests, Lands, and Natural Resource Operations (Permit # WL17-263857).

Table of Contents

Abstract ...... iii Lay Summary ...... v Preface...... vi Table of Contents...... vii List of Tables ...... ix List of Figures ...... x Acknowledgements ...... xi Chapter 1: Introduction ...... 1 1.1 Focal species: Dusky Grouse ...... 1 1.2 Speciation of Dusky Grouse ...... 3 1.3 Landscape Restoration and Wildlife Habitat ...... 3 1.4 What are Biosolids? ...... 4 1.5 Regulation of Biosolids ...... 6 1.6 Wildlife Response to Biosolids ...... 7 1.7 Research Objectives ...... 9 Chapter 2: Microhabitat selection of nest and brood sites by Dusky grouse (Dendragapus obscurus) in Southern Interior British Columbia ...... 10 2.1 Background ...... 10 2.2 Methods ...... 13 2.3 Results ...... 18 2.3.1 Nest Sites ...... 18 2.3.2 Nest Success ...... 19 2.3.3 Brood Sites ...... 21 2.4 Discussion ...... 22 Chapter 3: Patch-level habitat selection by Dusky Grouse (Dendragapus obscurus) in a biosolids- amended landscape ...... 34 3.1 Background ...... 34 3.2 Methods ...... 38 3.3 Results ...... 41 3.4 Discussion ...... 44 Chapter 4: Conclusions ...... 54

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References ...... 58 Appendices ...... 72 Appendix A: Microhabitat model selection ...... 72 Appendix B: GIS Layer and Weather Information ...... 76

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List of Tables

Table 2.1 Description of habitat variables assessed for nest site selection, nest success, and

brood site selection……………………………………………………………………….26

Table 2.2 Summary of dusky grouse nests at the OK Ranch in 2016 – 2017 and timing of nest

initiation and hatch in 2017………………………………………………………….……27

Table 2.3 Summary of microhabitat metrics for dusky grouse nests at the OK Ranch………….28

Table 2.4 Nest structures used by dusky grouse…………………………………………………29

Table 2.5 Top models (∆AICc < 2) explaining nest site selection and nest success for dusky

grouse hens at the OK Ranch…………………………………………………………….30

Table 2.6 Model-averaged parameter estimates and importance of variables for nest selection,

nest success, and brood site selection……………………………………………….……31

Table 2.7 Summary of microhabitat metrics for dusky grouse broods at the OK Ranch in

2016……………………………………………………………………………..………..32

Table 3.1 Grassland use by radio-collared dusky grouse hens and brood hens…………………48

Table 3.2 Comparisons of dusky grouse use of biosolids-amended and untreated grasslands.…49

Table A.1 Model-averaged parameter estimates and importance of variables for dusky grouse

nest site selection…………………………………………………………………..….….72

Table A.2 Model-averaged parameter estimates and importance of variables for dusky grouse

nest success…………………………………………………………………..…………..73

Table A.3 Top models (∆AICc < 2) explaining brood site selection for dusky grouse hens at the

OK Ranch in 2016…………………………………………………………..……………74

Table A.4 Model-averaged parameter estimates and importance of variables for dusky grouse

selection of brood sites………………………………………………...…………………75

List of Figures

Figure 2.1 Interaction plot for the key variable for nest site selection………………..………….33

Figure 3.1 Habitat selection by all radio-collared grouse at the OK Ranch in 2016 and 2017……50

Figure 3.2 Habitat selection by all dusky grouse brood hens at the OK Ranch in 2016 and

2017…………………………………………………………………………………....…51

Figure 3.3 Grassland distribution comparisons for all grouse in 2016 and 2017……………..….52

Figure 3.4 Grassland distribution comparisons for brood hens in 2016 and 2017…………....….53

Acknowledgements

There are many who have supported me through this endeavor. First and foremost, I would like to thank my supervisors, Dr. Karen Hodges and Frank Doyle. Their combined knowledge of wildlife, ecology, and life in general was a blessing and made my time in British

Columbia an experience that will help me in my future career and life. You both have become wonderful mentors.

My other committee members, Dr. Bob Lalonde and John Lavery, provided wonderful feedback to better this thesis. Dr. Jason Pither helped me better understand model selection and provided me with some of the R code I used in my analyses. Rene-Carl Dionne and many others at SYLVIS provided support through information about biosolids, layers and maps of applications, as well as sightings of grouse around the study site.

Thank you to my lab mates Jenna Hutchen, Kristen Mancuso, Kristine Teichman, TJ

Gooliaff, Logan Volkmann, and Angie Kelly. Your input when I was struggling with a problem was greatly appreciated and you made grad school so much more enjoyable.

I could not have done any of this without the help of the many undergraduates that worked with me. Megan Buers, Emma Gaudreault, Lakesha Smith, Jenna Scherger, and Eamon

Riordan-Short, thank you for all of your hard work. I would not have completed half of my work without the hours of field and lab work you put in. Same to my volunteers, Kristine Teichman,

Moganavalli Kattan, and Timothy Izukawa. No matter how much or how little time you gave, it was all appreciated more than you know.

A big thank you to the Upland Bird Society for supporting a large portion of this research and being the original advocates of the work. My research was also funded by the National

Science and Engineering Research Council through grants awarded to Karen Hodges and a fellowship and teaching assistantship from the University of British Columbia Okanagan.

Last, but far from least, thank you to everyone at the OK Ranch. Lawrence and Allan

Joiner allowed me complete access to their land and provided housing for the summers and the short winter trips to the area. Carol Banman helped us work out some of the logistics of staying and working at the ranch and kept us stocked with vegetables during the field season.

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Chapter 1: Introduction

Habitat loss and degradation are the major causes of declines in many species worldwide

(Loehle and Li 1996, Vitousek 1997, Fahrig 2001, Dunn et al. 2009, Krauss et al. 2010).

Understanding habitat selection by a species is necessary to understand the impacts of alterations to that species’ landscape. A few species thrive in disturbed landscapes, but many do not (Morris and Heidinga 1997, Devictor et al. 2008).

In North America, habitat loss and fragmentation affect many grouse species. Stephens et al. (2004) found that habitat fragmentation increased predation on and reduced nesting success of avian species. Greater sage-grouse (Centrocercus urophasianus) populations have lower survival in and avoid areas where pinyon pine (Pinus monophylla) and juniper (Juniperus osteosperma) encroachment reduces sagebrush habitat (Baruch-Mordo et al. 2013, Coates et al. 2017).

Huggard (2003) found spruce grouse (Falcipennis canadensis) use declined as timber was removed. Many European grouse species respond negatively to fragmentation of habitats due to heavy ungulate browsing and human activities (Henden et al. 2011, Storch 2013, Huhta et al.

2017). Dusky grouse (Dendragapus obscurus) are one of the least studied species of grouse and their response to habitat is not well known (Zwickel and Bendell 2004).

1.1 Focal species: Dusky Grouse

In this thesis, I focus on habitat selection by dusky grouse. Surprisingly little is known about the nesting and brood-rearing habitats of dusky grouse (Johnsgard 2016). This grouse species is a forest grouse native to North America. While their closest relative, the sooty grouse

(D. fuliginosus) is largely associated with coniferous forest, the habitat of the interior dusky

1 grouse may also include a combination of shrub-steppe, grasslands, alpine tundra, forest clear- cuts, and mountain shrub (Mussehl 1960, Boag 1966, Zwickel et al. 1968, Stauffer and Peterson

1986). During the winter, dusky grouse primarily eat conifer needles, twigs, buds, and cones

(Beer 1943, Stewart 1944, Remington and Hoffman 1996, Zwickel and Bendell 2004). This limited diet restricts the birds to conifer forests, though there are varying theories on the drivers of winter habitat selection. Some observational studies have shown dusky grouse move up in elevation in the winter, inhabiting exposed ridges in open coniferous forest, primarily Douglas- fir (Pseudotsuga menziesii) trees (Stauffer and Peterson 1985, Cade and Hoffman 1990). Other studies have suggested that not all birds move upward in winter, but instead exhibit partial migration (Zwickel et al. 1968, Zwickel and Bendell 2004).

During the breeding and brood-rearing months, dusky grouse use more open habitat than in winter. Open habitats provide greater herbaceous vegetation (Mussehl 1963, Zwickel and

Bendell 2004). This herbaceous cover provides both protection and forage for adult hens and chicks. Insects are prevalent among herbaceous vegetation, and are a key source of protein for grouse chicks during the first few weeks after hatch (Beer 1943, Stiven 1961, Mussehl 1963).

Adult grouse feed on insects, forbs, seeds, leaves, and fruits during the breeding and brood- rearing season.

Zwickel and Bendell (2004) suggest that nest structures vary greatly over the range of dusky and sooty grouse. However, coastal sooty grouse hens preferred young conifers, while hens use more grasses and shrubs in the interior. On the coast, sooty grouse nests were depredated primarily by mammals (Sopuck 1979, Zwickel and Bendell 2004). Hens and nests in the interior may see more avian predators than coastal populations, but few predation events have been observed (Zwickel and Bendell 2004).

1.2 Speciation of Dusky Grouse

Prior to 2004, the dusky grouse and its closest relative, the sooty grouse (D. fuliginosus), were considered the same species, known as “blue grouse.” Barrowclough (2004) found a difference in mitochondrial DNA and suggested that this difference may be due to the small movements of grouse and geographic isolation. Previous observations by Brooks (1929) on the physiological and behavioral differences between coastal and interior birds combined with the new genetics data aided in the decision to split blue grouse into two species (Banks et al. 2006).

The interior cohort of blue grouse, ranging from northern New Mexico to the Yukon, makes up the dusky grouse species, and the coastal birds, found in California and the western parts of

Oregon, Washington, British Columbia, and Alaska, became the sooty grouse. The geographical split of the two species corresponds with historic glacial events and speciation patterns found in many other birds (Barrowclough et al. 2004). Previous research on blue grouse was largely focused on the coastal populations, and our knowledge of dusky grouse requirements is lacking

(Zwickel and Bendell 2004, Johnsgard 2016).

1.3 Landscape Restoration and Wildlife Habitat

When we talk about habitat selection of a species, it is important to understand the historical state of the landscape when possible. While we cannot know for certain the exact historical conditions, historical records provide a benchmark that restoration efforts can aim for.

Blackstock and McAllister (2004) record anecdotes from First Nations in the southern interior of

British Columbia to provide a historical record of grassland management in the region. Major changes occurred to these grasslands in the 1850s, when European settlers began grazing cattle and horses. Areas that were largely comprised of bluebunch wheatgrass (Pseudoroegneria

3 spicata) were soon comprised of introduced species that better withstood grazing pressure (Black et al. 1999). In some areas of the southern interior, sagebrush densities rose as native grasses declined (Anderson 1973, Hebda 1982). We do not know the state of dusky grouse populations on this historic landscape, but dusky grouse may inhabit the same range in North America as they did during past glacial maximas (Barrowclough 2004). As dusky grouse rely on conifer needles in the winter, their habitat might have been more widespread at lower elevations during the ice ages when Douglas-fir and other conifers were found at lower elevations (Barrowclough

2004).

As we attempt to restore landscapes to their natural state, various land management practices have been used. One of these practices is fertilization of fields and pastures. Fertilizers are used to improve the nutrient content and moisture of soil and vegetation at degraded sites

(Fageria 2009, Strecker 2015), which has the potential to restore or enhance wildlife habitat (Leff et al. 2015). Nitrogen is believed to be the limiting nutrient for many herbivore species, and fertilization of vegetation can reduce bottom-up limitations from resources (White 1993). Many herbivore species preferentially select habitat and browse on vegetation with increased nitrogen from fertilization (Anderson et al. 1974, Ball et al. 2000, Sullivan et al. 2000b), and similar trends are seen in some omnivorous species (Ball et al. 2000, Sullivan et al. 2000c). More recently, the use of human waste as a fertilizer to forests and grasslands has increased, yet the impacts of these amendments on ecosystems are only partially understood.

1.4 What are Biosolids?

Biosolids are the semi-solid residuals left after municipal wastewater treatment (SYLVIS

2008). They differ from other fertilizers as they are comprised largely of organic matter (Sharma

4 et al. 2017), and landowners have found increased productivity of grasslands from the use of biosolids that was not obtainable with chicken manure or chemical fertilizers (Lawrence Joiner, personal communication). Organic matter and many beneficial nutrients, such as nitrogen, phosphorus, and carbon, enhance physical properties of the soil (Kumpiene et al. 2008, Sharma et al. 2017). Because biosolids are comprised largely of organic matter, they enhance the ability of soils to retain water and nutrients (Shammas and Wang 2008, Kominko et al. 2017). As the organic matter in biosolids decomposes, previously unavailable nutrients become available to plants, providing fertilization over multiple years (Singh and Agrawal 2008). Improvement of the physical condition of soils leads to many positive effects on vegetation, increasing both plant biomass and nutrient quality (Pierce et al. 1998, Newman et al. 2014). Increases in soil fertility can lead to improved browse for range stock, reduced soil erosion, increased plant growth at reclamation sites, and increased timber growth rate in forests (SYLVIS 2008, McFarland et al.

2010).

Previous research on my study site, the OK Ranch, found a 5-fold increase in plant biomass after the application of biosolids (460 kg/ha to 2280 kg/ha) and bunchgrass

(Pseudoroegneria spicata) cover increased from 41% to 99% after application (Newman et al.

2014). A study in Western Washington found 2 to 3-fold increases in yield of tall fescue grass

(Festuca arundinacea; Cogger et al. 2013). The effects of biosolids may be more realized in sites with more available precipitation. While Newman et al. (2014) found increased yields of native grasses on my study site, they did not find similar results at two drier sites. Many plants are limited in nutrient uptake during drought years (Farooq et al. 2009)

1.5 Regulation of Biosolids

As biosolids increase plant yield, they are currently used on agricultural lands, grasslands, forests, and reclamation sites across the world (SYLVIS 2008, Kominko et al. 2017).

With the increase in urbanization and general population density, the production of municipal sewage has also increased (Lu et al. 2012). Wastewater was once discharged directly into natural waters around the globe, but regulations have since limited this dumping into waterways in many countries and the land application of wastewater residuals has become an increasingly attractive option. Dumping of wastewater into U.S. waterways is strictly banned (Ocean Dumping Ban Act

1988), and the Wastewater Systems Effluent Regulations of 2012 regulates treatment of wastewater prior to dumping into Canadian waterways. Current wastewater treatments extract the biological matter, convert it into a solid (sewage sludge), and then apply chemical or heat treatments to remove potentially problematic nutrients (such as P and N) and sterilize the solids

(US Environmental Protection Agency 1994). These wastewater residuals that have undergone treatments allowing their application to lands are known as “biosolids” (Board on Environmental

Studies and Toxicology 2002). Treatment minimizes the number of potential pathogens, the concentration of metals, the nutrient loading, and the attractiveness of the residuals to potential vectors (i.e. birds, rodents, and insects; US Environmental Protection Agency 1994, SYLVIS

2008).

The increased use of recycling biosolids back onto the land has allowed the benefits of using biosolids as a fertilizer to be highlighted (Shammas and Wang 2008, Sharma et al. 2017).

However, some chemical fertilizers have had major impacts on wildlife species and ecosystems, leading to much skepticism about their widespread use (Mortvedt 1996, Jiao et al. 2012). As land applications of biosolids become more widespread, there has been growing concern with the

6 health impacts of applying human waste back into the environment (SYLVIS 2008, Lu et al.

2012). The majority of the regulations on the land application of biosolids relate directly to health concerns for humans and range animals, such as cattle or sheep. These health concerns include the spread of pathogens, the presence of heavy metals, and leaching of contaminants into water (SYLVIS 2008, Lu et al. 2012, Shinbrot 2012). Buffers are used when applying biosolids to reduce the exposure of the public or watershed to potential pathogens or odors and to improve the visual aesthetics of the area (SYLVIS 2008). To reduce the transfer of pathogens to humans and range animals, stockpiles may be left to stand for at least a week before being spread

(Lawrence Joiner, personal communication) and a 60-day grazing restriction is suggested

(SYLVIS 2008).

1.6 Wildlife Response to Biosolids

While the effects of the land application of biosolids on plant and soil characteristics have been studied extensively (Khaleel et al. 1981, Lindsay and Logan 1998, Pierce et al. 1998,

Sullivan et al. 2006a, Lee et al. 2014), little research has been conducted on the effects of biosolids on wildlife. Current regulations for land applications fail to take into account any impacts on wildlife (BC Reg. 18/2002, US 40 CFR Part 503). There have been many studies examining the presence of contaminants in earthworms and soil invertebrates, which are a major food source for many bird species (Kinney et al. 2008, 2012, Snyder et al. 2011, Pannu et al.

2012). When anthropogenic contaminants (such as beauty care products and pharmaceuticals) are present in biosolids, they are transferred to earthworms inhabiting that soil (Kinney et al.

2008). Bioaccumulation in earthworms has been used to address potential impacts of chemicals and organic pollutants to higher trophic levels, as they transfer contaminants (such as

7 organochlorine pesticides) to American robins (Turdus migratorius), Black-billed magpies (Pica pica), shrews (Blarina brevicauda), and other small mammals (Harris et al. 2000). However,

Vermeulen et al. 2010 suggests that direct studies of individual populations are required to fully understand bioaccumulation of toxins at higher trophic levels. Many studies on the vegetative characteristics of lands before and after biosolids treatments suggest implications for the wildlife that rely on that land for habitat, but they do not assess the actual effect (Pierce et al. 1998,

Fuchsman et al. 2010). For example, Sample et al. (1996) assessed the magnitude of contaminant risks that may be present to wildlife by modelling contaminant concentrations in food items, but did not measure actual contaminants in animal tissue.

Washburn and Begier (2011) directly addressed wildlife use of biosolids-treated grasslands in North Carolina, looking at the proportion of use by songbirds and white-tailed deer

(Odocoileus virginianus). A higher proportion of omnivorous birds that forage on the ground were found in the biosolids-treated grasslands compared to control plots. White-tailed deer had no response to biosolids treatments. The few studies that have addressed wildlife responses to biosolids applications have been conducted in areas of the United States where the vegetation and climate are much different than in the southern interior of British Columbia (Nickelson and

West 1996, Brown et al. 2002, Washburn and Begier 2011, Elfroymson et al. 2000). In addition, many of these studies have focused on biosolids applications within forest ecosystems (Cheng et al. 1996, Nickelson and West 1996, Elfroymson et al. 2000). Not only do these sites have different ecological conditions, but they often provide habitat for a different set of species. Birds, mammals, amphibians, and invertebrates will likely have different responses to biosolids and the effects may vary between predators and prey.

1.7 Research Objectives

Our knowledge of the habitat ecology of dusky grouse during the breeding and reproductive seasons, as well as the effects of biosolids on wildlife, is lacking. The goal of this thesis was to address both of these gaps in knowledge. I assessed microhabitat and patch-level habitat selection by female dusky grouse during the nesting and brood-rearing seasons. For each level of habitat selection, I further assessed whether biosolids played a role in selection and use of habitats.

In Chapter 2, I address microhabitat selection at dusky grouse nesting and brood-rearing sites. I use model selection in an AIC framework to identify habitat characteristics that define the sites chosen by hens. Further, I assessed if the success of a nest was characterized by any of the measured habitat variables, including the amount of biosolids-amended pastures surrounding the selected sites.

After assessing habitat selection at a small scale, I look at patch-level selection in Chapter

3. I use standardized selection ratios based on forest and grassland use with and without biosolids amendments to assess if hens are selecting for a particular patch type. Then, I look specifically at use of grasslands in this landscape to assess the extent to which grouse use grasslands and whether biosolids affects how far into the grasslands dusky grouse hens are willing to venture.

In Chapter 4, I summarize the conclusions of this thesis and suggest implications for management and future work on dusky grouse.

Chapter 2: Microhabitat selection of nest and brood sites by Dusky grouse (Dendragapus obscurus) in Southern Interior British Columbia

2.1 Background

The dusky grouse (Dendragapus obscurus) is the largest forest grouse species in North

America. While the species is not recognized as endangered or threatened, overall population trends show a decrease in numbers, with a long-term decline of 50% over 45 years and a short- term decline of 11% over 10 years in British Columbia (Environment and Climate Change

Canada 2017). This decreasing population trend is attributed to loss of habitat and harvest pressure (British Columbia Conservation Data Centre 2015). To fully understand how alterations to habitat might affect population numbers, it is important to understand what habitat dusky grouse require during the reproductive season.

Until 2006, dusky and sooty grouse (D. fuliginosus) were considered the same species, blue grouse (Banks et al. 2006). A combination of genetic, behavioral, and morphological differences found between blue grouse inhabiting regions along the coast and those further inland led to this taxonomic split (Brooks 1929, Barrowclough 2004, Schroeder 2006). In

Canada, most of the research on blue grouse has been conducted on the coastal, sooty grouse populations. In a review of blue grouse studies, Zwickel and Bendell (2004) described only two major studies looking at interior, dusky grouse populations. Boag (1964) studied interior blue grouse in Southwest Alberta, and Zwickel and Degner (unpublished, cited in Zwickel and

Bendell 2004) looked at interior blue grouse using subalpine habitat on Hudson Bay Mountain,

British Columbia. No published studies to date have looked at blue grouse in the southern interior of British Columbia. The coastal and interior regions of British Columbia provide very

10 different available habitat for blue grouse. Coastal regions are characterized by temperate rainforest and a very wet climate, while the southern interior has a much more variable climate and some of the driest regions in the province (BC Biogeoclimatic Ecosystem Classification

Program 2007).

While the interior dusky grouse are considered a forest grouse species, previous studies in the northern United States suggest that dusky grouse spend the summer and breeding months in more open habitats with lower canopy cover (Mussehl 1963, Zwickel and Bendell 2004).

However, our overall knowledge of the nesting and brood-rearing requirements of these interior birds is lacking and much of the previous research was observational or anecdotal in nature

(Zwickel and Bendell 2004, Johnsgard 2016).

Zwickel and Bendell (2004) found that nest structures varied immensely over the range of blue grouse. Hens in coastal populations preferred young conifers where available, and shrubs and grasses were used more often by hens in interior populations. Sopuck (1979) and Zwickel and Bendell (2004) found no correlation between nest success and cover at coastal sooty grouse nest sites, where mammals are the primary nest predators. Few observations have been made on predation of dusky grouse nests in interior populations, but Zwickel and Bendell (2004) found mammals depredated a smaller proportion of nests than in coastal regions.

During the breeding season, adult dusky grouse feed on flowers, fruits, seeds, leaves, and insects (Stewart 1944, Mussehl 1963, Zwickel and Bendell 2004). Young chicks primarily consume invertebrates, before switching to more a more herbivorous diet as they mature (Beer

1943, Stiven 1961, Mussehl 1963). More open habitats with low forest cover generally have higher herbaceous cover, providing both protection and forage for dusky grouse hens and their chicks (Mussehl 1963). Habitat heterogeneity is important for many forest grouse species,

11 providing accessibility to a variety of resources (Fearer and Stauffer 2003, Matysek et al. 2018).

Ruffed grouse (Bonasa umbellus) inhabiting areas with more heterogenous habitat tend to have smaller home ranges, as they do not need to travel far to access food or cover (Fearer and

Stauffer 2003). Many female grouse switch habitats once they have young. Some forest grouse, largely associated with contiguous forest landscapes, will use forest openings and areas with lower canopy cover and higher ground cover or arthropod abundance during brood-rearing

(spruce grouse, Falcipennis canadensis, Allan 1985; ruffed grouse, Sharp 1963, Maxson 1978,

Haulton et al. 2003). Dusky grouse likely show similar patterns of use in interior British

Columbia, where grasslands are more prevalent in the fragmented forest landscapes. In openings, ground cover provides protection from predators and access to herbaceous food items.

The use of fertilizers and other grassland amendments has the potential to increase both herbaceous cover and invertebrate abundance (McFarland et al. 2010, Gaudreault et al. in review). Over the past century, the residuals of treated human waste (hereafter, “biosolids”), have become an increasingly used amendment to landscapes across the globe (Haynes et al.

2009, Lu et al. 2012). Biosolids are applied to select lands occurring in the interior region of

British Columbia to restore degraded grasslands and reclamation sites. The organic materials contained in biosolids increases the nutrient and moisture retention of soil, leading to an increase in plant biomass and growth rate (Shammas and Wang 2008, SYLVIS 2008, Kominko et al.

2017). Previous research on the OK Ranch in British Columbia found a 5-fold increase in plant biomass after biosolids applications, and native grass cover nearly doubled (Newman et al.

2014). Similar effects were found in Western Washington with a 2 to 3-fold increase in tall fescue grass (Cogger et al. 2013). Biosolids are used on ranches to improve browse for range stock, in forests to increase timber growth rates, on reclamation sites to increase plant growth,

12 and on agricultural fields to increase crop yields (SYLVIS 2008, McFarland et al. 2010). The gradual decomposition of organic matter in biosolids allows nutrients to be released to plants over time, providing a multi-year effect of fertilization (Singh and Agrawal 2008).

Despite their increased use over the past century, little is known about how biosolids amendments affect wildlife. In my study area, Gaudreault et al. (in review) found a much higher abundance of grasshoppers in biosolids-amended grasslands. Biosolids may benefit dusky grouse by increasing the biomass of available food or the amount of cover available for nest and brood sites.

In this study, I assessed what habitat characteristics dusky grouse select when choosing nesting and brood-rearing sites. I had three main objectives. First, I wanted to identify what vegetative variables dusky grouse hens select when choosing nest or brood sites. Second, I wanted to assess whether nest success could be explained by the vegetation surrounding the nest site and identify the predator of each failed nest. Third, I wanted to assess whether biosolids affects a hen’s choice of nesting or brood-rearing sites or the success of the nest.

2.2 Methods

This study was conducted on and around the OK Ranch, near Jesmond, BC and abutting the Fraser River and Big Bar Creek. The ranch occurs in the Very Dry Mild Interior Douglas-fir

(IDFxm) and the Alkali Very Dry Warm Bunchgrass (BGxw2) biogeoclimatic zones (BC

Biogeoclimatic Ecosystem Classification Program 2007). These grasslands were once dominated by bluebunch wheatgrass (Pseudoroegneria spicata), needle-and-thread grass (Hesperostipa comata), and junegrass (Koeleria macrantha), but historical grazing has kept bluebunch wheatgrass levels low (Newman 2008). The IDFxm variant of the Interior Douglas-fir zone

13 represents the transition between lower elevation bunchgrass grasslands and continuous forest. It is a mosaic of grasslands and forest, with forest patches dominated by Douglas-fir (Pseudotsuga menziesii) and trembling aspen (Populus tremuloides) occurring patchily throughout (BC

Biogeoclimatic Ecosystem Classification Program 2007).

The OK Ranch is a working cattle ranch, where hunting of grouse is prohibited on the ranch property. The local grouse eat grasshoppers and other insects that compete with cattle for forage (Lawrence Joiner, personal communication). Four native species of grouse have been observed on the ranch: dusky grouse, ruffed grouse, spruce grouse, and sharp-tailed grouse

(Tympanuchus phasianellus). Introduced wild turkeys (Meleagris gallopavo) and ring-necked pheasants (Phasianus colchicus) are also present, but rare on the mountain.

The ranch owner has used biosolids as an amendment to portions of the ranch since 2001.

The nutrients and organic matter contained in biosolids improve moisture retention in soil and soil fertility (Shammas and Wang 2008). This increased soil fertility can improve forage for cattle, reduce soil erosion, increase plant growth at reclamation sites, and increase timber growth rates in forests (SYLVIS 2008, McFarland et al. 2010). Applications of biosolids on the ranch have primarily been conducted on the grasslands, but some applications in less dense forested areas have occurred. Studies from British Columbia, including work on the OK Ranch, found biosolids increased native grass growth (McFarland et al. 2009, Newman et al. 2014). However, biosolids did not restore native grasses on dry sites with invasive species already present

(Newman et al. 2014).

From May 2016 to August 2017, I used radio-telemetry to monitor dusky grouse hens at the OK Ranch. Female dusky grouse were trapped using noose poles (Zwickel and Bendell

1967) and walk-in traps (Pelren and Crawford 1995). I recorded weight, wing chord length, and

14 age class and attached a 22.5-g necklace-style VHF radio-collar (RI-2DM; Holohil Systems Ltd,

Ontario, Canada) to all hens large enough (radio-collar < 5% of body weight). Capture and handling was approved by the University of British Columbia Animal Care Committee

(Certificate #A15-0216) and the British Columbia Ministry of Forest, Land, and Natural

Resource Operations (Permit WL17-263857).

Radio-collared grouse were tracked at least twice a week from May to July and monitored for signs of nesting. When possible, locations were collected for birds during the fall and winter, but many birds moved off the OK ranch to forested hillsides and draws. When a hen was found on a nest, I triangulated her location from at least 10 m away on subsequent visits to determine if she was still nesting. Once the hen had left the nest site, I determined nest success or failure. A nest was considered successful when at least one egg hatched, determined by the presence of the membrane in the cracked eggshells. Depredated or abandoned nests were considered failures.

In 2017, I set trail cameras (Trophy Cam HD No-Glow 2015, Bushnell Outdoor Products,

Overland Park, KS, USA) up at all nests of radio-collared hens. These cameras allowed me to monitor nest success and identify the cause of nest failures. Cameras were placed within 5 m of the nest site, so that there was a mostly unobstructed view of the hen on the nest. If there was no clear view of the nest, I placed the camera in the position that allowed the best view of any nest predator that might prey upon the eggs.

All hens with successful nests were monitored for broods. Brood locations were recorded twice a week from when the chicks hatched through the end of July. I verified that a hen was with a brood by observing at least one chick in the immediate vicinity of the hen or observing the hen displaying indicative behavior (e.g. broken wing display or aggression). Many times, the

15 chicks were sighted before the hen was located, especially when the chicks were greater than 6 weeks of age. I tracked potential brood hens at night and spotlighted the brood when the chicks were 4 weeks old. At 4 weeks of age, chicks have already learned to fly, their juvenile primary feathers are fully grown and about to be molted, and the weight of male and female chicks begins to diverge (Smith and Buss 1963, Zwickel and Lance 1966, Schladweiler 1974, Redfield and

Zwickel 1976). Many sage-grouse (Centrocercus urophasianus) studies use spotlighting techniques to check brood success, as the chicks will roost in the immediate area or under the hen at night (Walker 2008). After nightfall, I located the hen using radio-telemetry and a spotlight. I used a hoop net to catch the chicks as the hen flushed.

Vegetation surveys were conducted at all nest sites, brood sites for chicks under 4 weeks of age, and paired random sites. Random sites were plotted within 100 m of the observed nest or brood using ArcMap version 10.2 (Esri, Redlands, CA, USA), allowing the microhabitat to change but keeping the overall habitat type similar for each paired site. For random nest sites, the closest vegetative structure that could have been used for nesting was used as the center of the plot. As nest structures varied drastically, these structures ranged from tufts of grass to the base of conifers but fell no more than 3 meters away from the given coordinates. I used a combination of grassland and forest variables to determine site characteristics that might affect grouse selection of a site, including vegetative cover and food availability (Daubenmire 1959, B.C.

Ministry of Forests, Lands, and Natural Resource Operations 2015). Vegetation was sampled after the hen had left the nest and nest success was determined. I sampled both the used site and the paired random site on the same day when possible to reduce any confounding effects from temporal change in vegetation.

At each site, I measured eleven variables based on previous grouse literature (Mussehl

1963, Zwickel and Bendell 2004) and 4 variables related to habitat type (Table 2.1). A 30 m x 30 m plot was established at each site using meter tapes laid out North-South and East-West.

Percent cover variables were measured using the Daubenmire (1959) technique. I used line transects to measure shrub cover (Canfield 1941). Shrub density was measured within a 1-m- wide transect along the meter tape in all four cardinal directions. Tree density was measured as a count of trees > 7.5 cm DBH for each quadrant. Robel poles were used to assess the visual obstruction of the nest bowl indicating visual cover from ground predators (Robel et al. 1970). I used ArcMap 10.2 to extract the proportion of each habitat type within 100 m of each site. I used a 100 m radius based on the average distance I located one of the radio-collared hens off her nest in 2017. This particular hen was observed foraging more often than sitting on her nest. McCourt et al. (1973) found spruce grouse hens also foraged around 100 m from nests.

I used Akaike’s Information Criterion corrected for small sample sizes (AICc) was used along with all-subset model selection as an exploratory process of finding what habitat characteristics might identify nest and brood sites in the study area (Akaike 1973, Burnham and

Anderson 2002). As most habitat use studies previously conducted for dusky grouse were based on observational data, and the nesting requirements of dusky grouse are little understood, I was not able to reasonably come up with a priori models to run. I used the “MuMIn” package in R (R

Development Core Team 2016, version 3.3.2) to test all possible models and rank the top models using ∆AICc. Pearson correlation was run on all variables, and those variables with Pearson’s r >

0.6 were not run in the same model. I used Akaike weights and model averaging to assess which variables were the most important to nest or brood site selection and nest success.

2.3 Results

Over two years, I captured and radio-collared 26 dusky grouse hens, 15 in 2016 and 11 in

2017. Most hens were captured using noose poles, with only one hen caught in a walk-in trap in the first year. In 2016, hens were already on nests by the first week of May. I caught 14 out of 15 hens later in the summer during brood-rearing. Hens were less prone to fly into trees when their chicks were on the ground. In 2017, I caught hens during the early breeding season, before nesting began.

2.3.1 Nest Sites

Over two breeding seasons, I found 23 nests of radio-collared hens and 9 nests from other birds, for a total of 32 dusky grouse nests (Table 2.2). I conducted vegetation sampling at 31 nest sites and 31 random sites paired with each sampled nest (Table 2.3). One nest was located under an overhang in the middle of a steep shale draw, so I did not measure vegetation for that site.

Seventy-six percent of nests were located in conifer patches, between 5 – 227 m from the forest- grassland edge (푥̅ = 84 m). I found nest bowls in a wide variety of structures (Table 2.4). Nearly half of the nests were located under shrubs (n = 13), but other structures included perennial bunchgrasses (n = 7), conifers with low branches (n = 5), conifers with no cover at the base (n =

2), and perennial bunchgrasses at the base of conifers (n = 2). Three hens used unique nest structures, nesting under a rock overhang on a steep hillside, the remnants of a burnt slash pile, and a downed, dried-out conifer. Four hens re-nested an average of 201 m (± 80 m) away after their first attempt failed, and three re-nested using similar nest structures as the first attempted nest. The fourth hen moved from nesting in a low juniper bush (Juniperus communis) in conifer

18 forest with 60 % canopy cover to nesting under grass and alfalfa (Medicago sativa) in an open grassland.

In 2016, only one hen was radio-collared before nest initiation. She was found nesting on

May 6th, and the nest was depredated before hatch. In 2017, the first nesting hen was found on

May 2nd. For the 16 hens that nested in 2017, median lay data was May 14th (Table 2.2). I found

44% of first nest attempts succeeded, with a median hatch date of June 10th. Hens incubated eggs for an average of 26 days.

Hens primarily selected nest sites with high visual obstruction. While three vegetation variables appeared in four top models (∆AICc < 2), visual obstruction was the only single- variable model (Table 2.5). Hens did not appear to select for canopy cover and shrub density, but both variables showed up in two of the top models and cannot be excluded as possible influences on selection (importance < 0.3, Table 2.6). On average, birds chose nest sites with 12.7 cm higher visual obstruction, 10.5% higher canopy cover, and 3% less shrub density (Figure 2.1).

2.3.2 Nest Success

Out of the 31 sampled nests, 13 were successful (42%) and 18 were depredated or abandoned by the hens (Table 2.3). The median lay date for both successful and unsuccessful nests was May 14th. The nests at all three unique nest structures were successful, along with one or two nests under each type of nest structure (Table 2.4). I observed 4 re-nest attempts, all of which failed. These hens initiated their second nest 14, 17, 17, and 21 days after their first nest failed.

I set trail cameras up at 19 dusky grouse nests, 10 of which were depredated. Coyotes

(Canis latrans) were the most common predator of the eggs (n = 5). The other predators were

Common Ravens (Corvus corax, n = 3) and a black bear (Ursus americanus, n = 1). I was unable to verify the predator of one clutch, though it was likely a coyote due to the state of the eggshells and an image with a coyote near the nesting hen around the date of depredation. One of the re- nest attempts was depredated within a day of laying, and I was unable to place a camera at the site in time. There were no eggshells left at the nest, and the previous nest attempt had been depredated by a black bear on the same hillside. A red squirrel (Tamiasciurus hudsonicus) was photographed removing an egg from one of the nests while the hen was away, but the hen returned to incubate the remaining eggs. Half of the nests for which I was able to determine predation were depredated during daylight hours (n = 5), while 4 were depredated at night. All of the avian predation events occurred during light, while the one black bear depredation and 2 out of 5 coyote depredations occurred at night.

Nest success was positively correlated with visual obstruction and the amount of biosolids-amended grassland within 100 m of the site. Successful nests had 3 times as much biosolids-amended grassland around the site (푥̅ = 34 ± 10%) and visual obstruction was 6.8 cm higher (푥̅ = 46.7 ± 3.9 cm) than unsuccessful nests (푥̅ = 8 ± 5 %, 39.8 ± 2.7 cm; Figure 2.1). I found no single-variable model in the top nest success models (Table 2.5), but the amount of biosolids-amended grassland was the most important variable for nest success (importance =

0.78). Visual obstruction (importance = 0.43) and percent cover of perennial grass (importance =

0.41) showed similar variable importance (Table 2.6). The percent cover of perennial grass was

38% lower at successful nests (푥̅ = 18.7 ± 3.7%) than unsuccessful nests (푥̅ = 25.8 ± 2.5%).

While perennial grass cover appeared to reduce nest success, variance was high and confidence intervals of the coefficient estimates cross zero (Table 2.6).

2.3.3 Brood Sites

I radio-collared 5 brood hens in 2016, while they were already with chicks. Three of these hens were still with chicks at the end of July. The other two hens had broods until the last week of June. I caught one female chick from one of the successful broods that was too small to radio-collar at the time. I attached a plastic leg band before releasing her. She was observed the next year with 5 chicks of her own about 0.5 km from where she was captured. In 2017, I followed 10 brood hens post-hatch. There was a 30% brood survival rate at 4 weeks post-hatch.

Two brood hens were depredated, and I assume the chicks did not survive on their own. For one of the successful hens, spotlighting at night showed that she had two chicks rather than the one observed when tracking in the daytime. I observed two chicks caught in 2016 with broods of their own in 2017. In August 2016, I caught one hen with two female chicks large enough to radio-collar. One of the chicks survived through the winter and reared a successful brood in

2017. Brood hens were often (72% of locations) observed foraging and roosting in grasslands in

2016. In 2017, 49% of locations were within conifer forest or on the forest-grassland edge.

In 2016, I sampled vegetation at 39 brood sites and 38 random sites (Table 2.7). I was unable to conduct vegetation sampling at brood sites in 2017, as wildfire closures prevented access to the field at the time sampling would have occurred.

Brood sites were highly variable. Dusky grouse hens did not select for any one of the habitat variables that I measured. Thirteen of the 15 habitat variables measured appeared in 22 models with ∆AICc < 2 (Appendix A3). Moss cover (importance = 0.68) was the only variable that appeared relevant to brood site selection (Appendix A4). Model averaging suggests that moss cover negatively affected brood site selection (Table 2.8), but moss cover was low at both brood sites (푥̅ = 0.6 ± 0.3%) and random sites (푥̅ = 2.0 ± 0.6%).

2.4 Discussion

Dusky grouse hens selected nest sites with higher visual obstruction, while brood sites were varied and no single variable was key to site selection. Nest success increased with higher visual obstruction and a higher proportion of biosolids-amended grasslands. While hens may not select sites with biosolids at the microhabitat scale, nest success was positively impacted by biosolids-amended grasslands. Overall, these data suggest that dusky grouse are habitat generalists, and hens use most or all of what is available in the area. I found nests in a wide variety of landscapes, from under rocks on steep hillsides to the open base of trees with no low branches, and there was no clear habitat structure that identified where a nest bowl might be found.

While nest structures varied, dusky grouse still used a few key variables to select nest sites. Visual obstruction (or visual cover) of a nest site was the most important variable affecting nest site selection and was also an important variable for nest success. Nests were in areas with higher visual cover of the nest bowl than random sites, and successful nests had higher visual cover than depredated nests. Visual cover was created by the combination of grasses, shrubs, and trees blocking the view of the nest from nearby predators. The importance of this variable suggests that cover from predators plays a key role in site selection and nest success. These results contradict the previous research on coastal sooty grouse suggesting no correlation between nest success and cover (Sopuck 1979, Zwickel and Bendell 2004). These studies attributed the lack of correlation to the high mammalian predation of nests, as mammals often hunt at night using olfactory senses rather than visual cues. They suggested raptor predation would be higher in central British Columbia, potentially causing visual cover to be more important to nest success. I found mammals were still the primary nest predator, with ravens

22 depredating the other quarter of the nests and no observed depredation by raptors. While all of the avian depredations I observed occurred in daylight, half of the mammalian depredations occurred at night. However, 60% of coyote depredations still occurred during the day. Coyotes, the main nest predator, use visual cues to hunt during the daytime (Wells and Lehner 1978,

Wells and Bekoff 1982). Thus, visual cover is important to hide nests from both avian and mammalian predators in the area, which might explain the higher cover I found at successful nests in this study. This correlation may be more prominent for the interior dusky grouse, as there is more open habitat available and cover is more limited than in denser forests.

Shrub densities at nest sites were very similar to random sites, but I found higher shrub density at failed nests. This result suggests that the visual cover at successful nests was from other habitat features, such as grasses or trees. High shrub density may force the predator on a path closer to the nest as they navigate through the shrubs, but this idea has not been studied.

Dusky and sooty grouse prefer open areas during the breeding season and early summer (Beer

1943, Bendell and Elliott 1966, Stauffer and Peterson 1985). My research suggests that the less dense understory might also improve nest success.

Bendell and Elliott (1966) found that sooty grouse on Vancouver Island preferred areas with canopy cover around 15% during the breeding season. I found nests located in conifer forest with an average canopy cover of 57% (± 6.5%). The use of higher canopy cover may be due to the openness of the understory at our study site. Grazing over the past century has kept much of the understory low and open, allowing more visibility even with high forest canopy cover.

Nesting in areas with high canopy cover may also provide cover from avian predators that cover on the ground does not. Although common ravens were the only avian nest predators observed, raptors were prevalent in the area.

The proportion of biosolids-amended grasslands within 100 m was the most important variable for nest success. Likely, this variable is a surrogate for something that I did not measure, possibly an indicator of visual cover or forage availability. As biosolids increase plant biomass

(Cogger et al. 2013, Newman et al. 2014), visual cover is likely increased through thicker grass patches and other plants surrounding the nest. Hens may nest near more open areas with high insect availability for young chicks upon hatch (Beer 1943, Stiven 1961, Johnsgard 2016). As insects also comprise a portion of the diet of adult hens (Stewart 1944, Mussehl 1963, Zwickel and Bendell 2004), it is possible that nests near biosolids-amended grasslands provide better forage for nesting hens and increased fitness. Grouse have been observed consuming grasshoppers and other insects through the summer on the study site. Gaudreault et al. (in review) found much higher densities of grasshoppers in biosolids-amended grasslands than in control grasslands on the OK Ranch in 2016. Overall insect abundance showed similar trends, with higher average abundance in biosolids-amended grasslands.

Dusky grouse hens also appear to be habitat generalists when with their broods. Broods were observed deep into grasslands, in the center of forests, and in shrubs. Dusky grouse in

Montana and Idaho preferred areas with higher amounts of herbaceous cover for brood-rearing

(Mussehl 1960, Stauffer and Peterson 1986). However, none of the cover variables I sampled supported any trend in habitat use by broods. I did not measure available food biomass at brood sites, and insect or forb availability may play a large role in site selection by brood hens (Beer

1943). If insect availability was driving site selection, broods should use areas with a higher proportion of biosolids. However, the proportion of biosolids did not appear to impact selection of brood sites at this scale. While my results suggest moss might deter brood site selection, there was so little moss in the area (0-18% cover) that this result is likely an artefact. Moss was more

24 prevalent in 2016, when the region saw 4-5 times as much precipitation as in 2017. The little moss observed at the study site in 2017 was usually desiccated. If I had been able to sample vegetation at brood sites in 2017, moss cover would likely not be a statistically important predictor.

Collectively, these data show that dusky grouse are habitat generalists. However, visual cover appears to be key for nest selection and success. Maintaining habitat with high ground cover provides cover for hens and chicks, especially in a landscape with a high abundance of predators. Biosolids appear to be beneficial for nest success. These amendments may be a tool for restoration of degraded habitats, increasing visual cover through plant biomass and increasing insect abundance during the breeding season.

Table 2.1 Habitat variables assessed for nest site selection, nest success, and brood site selection of dusky grouse.

Variable Description Daubenmire Plots Perennial Grass Percent cover perennial grass Residual Grass Percent cover residual grass left from the previous year Forbs Percent cover forbs Debris Percent cover debris Moss Percent cover moss Grass Height Height of tallest perennial or residual grass (cm) 30 m2 Plot Canopy Cover Percent cover of forest canopy Visual Obstruction Average visual cover of the nest bowl (cm) from 5, 10, 15 m away in each cardinal direction Shrub Cover Percent shrub cover, using line intersect method Shrub Density Shrub density (shrubs/30 m2), all shrubs with cover greater than 3 cm Tree Density Tree density (trees/30 m2), all trees with DBH > 7.5 cm 100 m Radius Biosolids Grassland Percent of biosolids-amended grassland Grassland Percent of untreated grassland Biosolids Conifer Percent of biosolids-amended forest Conifer Percent of untreated forest

Table 2.2 Dusky grouse nests at the OK Ranch in 2016 – 2017. Timing of nest initiation and hatch are from 2017 data. No dates are provided for abandoned nests, as one of them was a re-nest and the other failed due to hen mortality.

Mean Radio- Un- Median Median Hatch Subset of Grouse Nest Initiation Hatch Dates Days on collared collared Lay Date Date Nest All Nests 23 9 May 2 – 23 May 14 ------

Successful Nests 9 5 May 2 – 20 May 14 May 26 – June 24 June 10 26

Failed Nests 14 4 May 5 – 23 May 12 ------

Depredated 12 -- May 5 – 23 May 11 ------

Abandoned 2 ------

Re-nests 4 -- May 22 – 7 June 4 ------

Table 2.3 Microhabitat metrics for dusky grouse nests at the OK Ranch. Values are the mean and standard error for each habitat variable. Successful nests were identified by eggshells broken in half with the membrane still attached, where unsuccessful nests were abandoned or showed signs of depredation. Available sites represent the available habitat on the ranch.

Nests Available Successful Unsuccessful Variable (n = 31) (n = 31) (n = 13) (n = 18) Perennial Grass (%) 23.0 ± 2.2 25.3 ± 2.8 18.7 ± 3.7 25.8 ± 2.5 Residual Grass (%) 13.6 ± 1.4 12.7 ± 1.1 15.2 ± 2.9 12.5 ± 1.5 Forbs (%) 8.3 ± 1.0 8.2 ± 0.8 7.2 ± 1.2 9.0 ± 1.4 Debris (%) 35.6 ± 2.8 36.3 ± 3.7 40.0 ± 4.4 32.8 ± 3.6 Moss (%) 1.1 ± 0.5 1.0 ± 0.5 0.6 ± 0.6 1.5 ± 0.8 Grass Height (cm) 43.5 ± 2.0 41.7 ± 2.1 43.1 ± 3.5 43.7 ± 2.5 Canopy Cover (%) 56.6 ± 6.5 46.1 ± 7.3 53.8 ± 11.4 58.4 ± 8.1 Visual Obstruction (cm) 42.5 ± 3.3 29.8 ± 2.1 46.7 ± 3.9 39.8 ± 2.7 Shrub Cover (%) 7.0 ± 2.0 5.0 ± 1.0 7.0 ± 2.0 7.0 ± 2.0 Shrub Density (n/30 m2) 0.6 1± 0.1 0.64 ± 0.1 0.42 ± 0.2 0.74 ± 0.2 Tree Density (n/30 m2) 0.64 ± 0.1 0.63 ± 0.1 0.61 ± 0.2 0.66± 0.1 Biosolids Grassland (%) 18.1 ± 5.5 18.7 ± 5.6 33.6 ± 10.2 8.3 ± 5.3 Grassland (%) 46.5 ± 6.1 43.6 ± 5.6 41.9 ± 9.9 49.4 ± 7.9 Biosolids Conifer (%) 8.6 ± 3.5 10.2 ± 3.6 7.8 ± 4.8 9.1 ± 5.0 Conifer (%) 29.0 ± 6.2 28.3 ± 6.1 19.5 ± 8.7 35.1 ± 8.4

Table 2.4 Nest structures used by dusky grouse. Numbers of hens using each nest structure type are given along with the number of successful nests in each type.

Total Successful Nest Structure Nests Nests Shrubs 13 5 Perennial bunchgrasses 9 1 Base of tree (low branches) 5 4 Base of tree (no branches) 2 1 Rock overhang 1 1 Dead, felled tree 1 1 Burnt slash pile 1 1

Table 2.5 Top models (∆AICc < 2) explaining nest site selection and nest success for dusky grouse hens at the OK Ranch. Vegetative characteristics at 31 nests, 31 random sites, 13 successful nests, and 18 unsuccessful nests were measured.

Adjusted Akaike 2 Model R K AICc ∆AICc Weight Nest Site

Visual Obstruction 0.21 3 80.85 0 0.05

Visual Obstruction + Canopy Cover 0.22 4 81.22 0.37 0.04

Visual Obstruction – Shrub Density 0.20 4 82.54 1.69 0.02

Visual Obstruction + Canopy Cover 0.22 5 82.72 1.87 0.02 – Shrub Density

Null 0 2 94.20 13.35 0.00

Nest Success

Biosolids Grassland + Visual Obstruction – Perennial Grass 0.32 5 40.73 0 0.10

Biosolids Grassland + Visual 0.25 4 41.99 1.26 0.06 Obstruction

Null 0 2 47.81 7.08 0.00

Table 2.6 Important variables for dusky grouse nest and brood sites. Values are model-averaged parameter estimates and variable importance. Variable importance uses Akaike weights of each model containing the variable; high values indicate influential variables. Confidence intervals that do not span zero suggest the variable affects site selection or nest success.

Variable Estimate SE Lower CI Upper CI Importance Nest Site Intercept 0.00 0.06 -0.12 0.12 -- Visual Obstruction 0.48 0.12 0.24 0.72 1.00 Canopy Cover 0.16 0.12 -0.07 0.40 0.26 Shrub Density -0.10 0.13 -0.35 0.15 0.14 Nest Success Intercept 0.00 0.08 -0.17 0.17 -- Biosolids Grassland 0.45 0.18 0.10 0.80 0.78 Visual Obstruction 0.35 0.17 0.01 0.69 0.43 Perennial Grass -0.36 0.20 -0.75 0.04 0.41 Brood Site Intercept 0 0.06 -0.11 0.11 -- Moss -0.28 0.13 -0.53 -0.03 0.68 Visual Obstruction 0.19 0.12 -0.04 0.42 0.29 Canopy Cover 0.21 0.13 -0.05 0.47 0.28 Tree Density 0.22 0.16 -0.08 0.53 0.24 Residual Grass -0.17 0.13 -0.42 0.08 0.21

Table 2.7 Microhabitat metrics for dusky grouse brood sites at the OK Ranch in 2016. Values are the mean and standard error for each habitat variable sampled.

Brood Available Variable (n = 39) (n = 38) Perennial Grass (%) 20.8 ± 2.1 20.3 ± 1.8 Residual Grass (%) 19.1 ± 2.0 23.4 ± 2.1 Forbs (%) 14.3 ± 1.0 14.2 ± 0.9 Debris (%) 35.9 ± 2.5 31.0 ± 2.3 Moss (%) 0.6 ± 0.3 2.0 ± 0.6 Grass Height (cm) 50.3 ± 2.0 52.5 ± 2.1 Canopy Cover (%) 25.8 ± 5.6 15.0 ± 4.5 Shrub Cover (%) 4.0 ± 1.0 3.0 ± 1.0 Shrub Density (n/30 m2) 0.4 ± 0.1 0.3 ± 0.1 Tree Density (n/30 m2) 0.3 ± 0 0.2 ± 0.1 Visual Obstruction (cm) 27.1 ± 1.7 23.4 ± 1.1 Biosolids Conifer (%) 24.5 ± 6.0 23.4 ± 6.0 Biosolids Grassland (%) 2.7 ± 2.4 2.8 ± 2.4 Conifer (%) 35.7 ± 5.0 34.5 ± 5.1 Grassland (%) 37.1 ± 4.9 39.3 ± 5.3

Figure 2.1 Important habitat variables for dusky grouse nest sites. Values are means and standard errors for visual obstruction at a) nest sites and random sites representing availability and b) successful and unsuccessful nests and biosolids-amended grassland at c) nest and random sites and d) successful and unsuccessful nests.

Chapter 3: Patch-level habitat selection by Dusky Grouse (Dendragapus obscurus) in a biosolids-amended landscape

3.1 Background

Biosolids, the semi-solid residuals left after municipal wastewater treatments, have become an increasingly popular amendment in recent decades as regulations prohibit or restrict dumping of wastewater into oceans (U.S. Ocean Dumping Ban Act 1988, Wastewater Systems

Effluent Regulations 2012). The residuals are used as an amendment to grasslands, forests, and reclamation sites around the world (SYLVIS 2008, Lu et al. 2012). Comprised largely of organic matter, biosolids can increase the soil’s ability to retain water and nutrients (Shammas and Wang

2008, Kominko et al. 2017). Soils amended with biosolids see increases in nitrogen, carbon, and phosphorus (Sullivan et al. 2006a), and the decomposition of organic matter over time allows previously unavailable nutrients to become available to plants over multiple years (Singh and

Agrawal 2008). Biosolids increase the nitrogen content and biomass of many plants (Pierce et al.

1998, McFarland et al. 2009). Increases in plant biomass and crop yields can lead to improved forage for cattle, increased timber growth rates, and increased vegetative growth at reclamation sites (Shammas and Wang 2008, SYLVIS 2008, McFarland et al. 2010).

One study in British Columbia found a 5-fold increase in plant biomass after biosolids were applied to the grasslands, where bunchgrass cover nearly doubled (Newman et al. 2014).

Another study in western Washington found 2- to 3-fold increases in the yield of tall fescue grass from biosolids amendments (Cogger et al. 2013). In British Columbia, biosolids increased the growth of native species in areas with adequate precipitation, but did not restore native species to grasslands on drier sites where invasive species were already prevalent (McFarland et al. 2009,

Newman et al. 2014). As precipitation can limit nutrient uptake in plants (Farooq et al. 2009), it is likely that the effects of biosolids is more realized in areas with higher precipitation.

While the effects of biosolids on plant and soil characteristics have been studied extensively (Pierce et al. 1998, Sullivan et al. 2006a, Newman 2008, Newman et al. 2014), few studies have addressed the effects of biosolids on wildlife. Even then, many of these studies have focused on forest ecosystems (Cheng et al. 1996, Nickelson and West 1996, Elfroymson et al.

2000). Only one published study has previously addressed the effects of biosolids applications on wildlife using grasslands. Washburn and Begier (2011) found no effects of biosolids on white- tailed deer (Odocoileus virginianus) use of grasslands, but found an increase in songbird abundance in grasslands applied with biosolids. At my study site, the OK Ranch, located in

Central British Columbia, Canada, Gaudreault et al. (in review) found higher grasshopper abundance in biosolids-amended grasslands in 2016. Many species have been observed feeding on grasshoppers around the ranch, including raptors, songbirds, and grouse (personal observation).

Other fertilization treatments are beneficial for some wildlife species. By increasing the nitrogen and phosphorus of vegetation, many fertilizers increase forage quality and biomass.

Nitrogen is one of the most limiting nutrients for herbivores, and large herbivores prefer fertilized vegetation over non-fertilized (White 1993, Ball et al. 2000). Moose (Alces alces) preferentially browse on vegetation that has been fertilized, and research suggests they select for vegetation with higher nitrogen contents (Ball et al. 2000). Both mule deer (Odocoileus hemionus) and moose use fertilized habitats more frequently than unfertilized (Anderson et al.

1974, Sullivan et al. 2000b).

Similar patterns may exist in smaller herbivores and omnivores, but the trends are less distinct. Some studies suggest snowshoe hares (Lepus americanus) and mountain hares (L. timidus) prefer fertilized plots (Ball et al. 2000, Sullivan et al. 2006c), while others found no preference (Miller 1968). Willow grouse (Lagopus lagopus) in Scotland selected for vegetation with higher nitrogen contents during the winter, but did not show selection during the summer when the diet of grouse was more varied (Miller 1968). More recent research suggests willow grouse, hazel grouse (Bonasa bonasia), black grouse (Lyrurus tetrix), and capercaillie (Tetrao urogallus) do not prefer fertilized plots (Ball et al. 2000).

Species often trade-off between forage quality or quantity and the perceived risk of predation when choosing habitat. This trade-off is more evident in smaller species. Larger herbivores have fewer predators, and can use habitat primarily based on forage quality (Rapp

2017). Small herbivores and omnivores generally have a higher predation risk, causing habitat use to depend on both forage and predation (Sinclair et al. 2003, Rapp 2017). Trade-offs between predation risk and food availability have been recorded for many grouse species (Bergerud and

Gratson 1988, Whitaker et al. 2006). If biosolids increase the quality of vegetation or abundance of insects, small herbivores and omnivores may risk higher predation for access to higher quality food. As biosolids amendments increase across western North America, it is important to assess how these alterations to the landscape affect wildlife. Biosolids may be a tool to restore degraded habitats and reduce or slow population declines stemming from habitat loss.

To explore the relationship of biosolids and habitat, I looked at habitat selection of dusky grouse (Dendragapus obscurus) on the OK Ranch, a large cattle ranch located along the Fraser

River in Central British Columbia. Biosolids are applied as an amendment to grasslands and conifer forests on the ranch to increase browse for cattle. The ranch supports four species of

36 native grouse: dusky grouse, ruffed grouse (Bonasa umbellus), spruce grouse (Falcipennis canadensis), and Columbian sharp-tailed grouse (Tympanachus phasianellus columbianus). The ranch owner prohibits hunting of grouse, as the grouse consume grasshoppers during the summer, which compete with cattle for grass.

While dusky grouse are considered a forest grouse species, they use grasslands during the breeding and brood-rearing months (Mussehl 1963, Zwickel and Bendell 2004). Grasslands and more open areas in mesic forests are believed to support a higher abundance of food for the hens and their young during the summer (Beer 1943, Stiven 1961, Mussehl 1963). Adult grouse feed on insects, seeds, forbs, and green leaves during the summer, while chicks primarily consume invertebrates for the first few weeks after hatching (Stewart 1944, Mussehl 1963, Zwickel and

Bendell 2004). Dusky grouse are inferred to stay close to forest edges while using grasslands, as edges provide cover and escape from predators (Mussehl 1963, Hoffman 1981).

In winter, dusky grouse feed on conifer needles, buds, twigs, and cones (Beer 1943,

Stewart 1944, Remington and Hoffman 1996, Zwickel and Bendell 2004). Dusky grouse spend their winters on exposed ridges and slopes in open coniferous forests, predominantly in Douglas- fir (Pseudotsuga menziesii) stands (Stauffer and Peterson 1985, Cade and Hoffman 1990). Dusky grouse may use multiple migration strategies, with some individuals staying at lower elevations while others move upward in the winter (Zwickel et al. 1968, Zwickel and Bendell 2004).

Dusky grouse are not currently a species of concern in North America, but population declines have been documented across their range and these declines in British Columbia are attributed to habitat loss and harvest pressures (B.C. Conservation Data Centre 2015). Many grouse species are declining in areas where human activities are prevalent (Storch 2000). To

37 understand how biosolids might affect dusky grouse populations, we must first look at how dusky grouse are using their local habitat.

Here, I assess patch-level habitat selection by dusky grouse and whether biosolids affected habitat choice. My three main objectives were to 1) assess what patch type dusky grouse selected, 2) calculate how far into grasslands dusky grouse traveled, and 3) assess whether biosolids affected the distance dusky grouse traveled into grasslands. I assessed each objective for all grouse hens and for brood hens only, as brood hens were likely to be more affected by amendments to grasslands.

3.2 Methods

I worked on the OK Ranch, a private cattle ranch near Jesmond, British Columbia, abutting the Fraser River and Big Bar Creek. The 4100 hectare upland sections of the ranch is a mosaic of grasslands and conifer forest, with forest patches dominated by Douglas-fir and interspersed with small patches of trembling aspen (Populus tremuloides). The average elevation on this upland portion of the ranch is 1100 m, and the region commonly sees dry, warm summers

(푥̅ = 18 cm, 14 °C; Newman et al. 2014).

Biosolids were applied to portions of the OK Ranch between 2000 – 2007, but more extensive applications occurred in 2014 - 2017. Applications have primarily occurred as an effort to restore grassland productivity, but some application has occurred in accessible forest patches.

SYLVIS Environmental Services applies biosolids on the ranch between March – October each year, depending on weather and when the ground is not frozen. Prior to the dusky grouse breeding season in 2017, 1162 hectares of grassland and forest on the ranch had been applied.

Between 2014 – 2016, the area applied each year ranged from 196 – 484 ha.

I trapped female dusky grouse between May 2016 – May 2017 using noose poles

(Zwickel and Bendell 1967) and walk-in traps (Pelren and Crawford 1995). I attached necklace- style VHF radio transmitters (22.5 g, RI-2DM, Holohil, Ltd.) and measured wing chord, mass, and condition of each bird. All capture and handling protocols were approved by the British

Columbia Ministry of Forests, Lands, and Natural Resource Operations (Permit #WL17-263857) and the University of British Columbia Animal Care Committee (Certificate #A15-0216).

I radio-tracked individuals at least twice a week between May and August in 2016 and

2017. I recorded whether the individual was roosting, nesting, or with a brood. Locations of any brood hen, radio-collared or not, were recorded throughout the study. I attached telemetry equipment to an airplane and flew in September 2016 and October 2017 to locate birds that had travelled off the ranch in the fall.

To address patch-level habitat use, I retrieved vegetation layers from the Vegetation

Resource Inventory by the Ministry of Forests, Lands, Natural Resource Operations, and Rural

Development (Appendix B.1). I extracted the vegetation polygons for conifer forest and grasslands and created rasters using ArcMap version 10.2 (Esri, Redlands, CA, USA). SYLVIS provided biosolids application maps for the area (Appendix B.1). I overlaid the two datasets to obtain biosolids-amended and control grassland and conifer locations for the region. Only small portions of the ranch had been applied with biosolids in 2000-2007, and these areas were applied over in 2014-2016, I only use the more recent applications in this analysis.

I mapped habitat availability by creating a 500 m buffer around all dusky grouse telemetry locations collected over the two years. The average daily movements of blue grouse and ruffed grouse are about 400 m (Godfrey 1975, Hannon et al. 1982), and a 500 m buffer allows for some large movements. Using this buffer allowed me to focus on what was available

39 to the grouse I had radio-collared, without bias from habitat in areas where I did not trap grouse.

The percentage of each habitat type (conifer forest, grassland, conifers applied with biosolids, and grasslands applied with biosolids) within this area was considered available in this analysis.

The percentage of grouse points in each habitat type became the proportion of used habitat for each hen. For all locations within treated or untreated grasslands, I measured the Euclidean distance to the closest treated or untreated conifer habitat.

To account for potential yearly differences due to weather, I obtained weather data from the nearest available weather stations, Churn Creek Station #832 and Meadow Lake Station #236 from the Ministry of Forests, Lands, Natural Resources, and Rural Development (Appendix B.2).

Both weather stations lie about 25 km away from the ranch, at similar elevations and within similar habitat types. In 2017, weather was much warmer and drier than in 2016. Both stations received 4-5 times as much precipitation in May – July 2016 (216 cm at Churn Creek, 121 cm at

Meadow Lake) as in 2017 (51 cm at Churn Creek, 21 cm at Meadow Lake). The average maximum daily temperature was also lower in 2017. July showed the most drastic differences between the two years, with 2016 having an average of 70 mm more rainfall and an average temperature 2.0 °C lower (15.2 °C in 2016, 17.2 °C in 2017). Spring weather showed the opposite trends as summer. The area saw higher rainfall amounts and lower temperatures between February – April 2017 than in 2016.

To measure habitat selection by grouse, I calculated standardized Manly selectivity ratios

(Manly’s α) using the “adehabitatHS” package in R (R Development Core Team 2016, version

3.3.2). Manly et al. (2002) describes resource selection as the disproportionate use of a resource in relation to availability. Selection ratios compare used habitat to available habitat, where any alpha value > 0.25 (1/number of habitats available) suggests selection for that habitat. I ran

40 selection analyses on the full set of grouse locations, as well as a subset using data from only those individuals for which I had ten or more locations. I found no difference between the two datasets and here I present results for the full set of locations.

To assess how grouse used grasslands, I measured the distance grouse travelled into grasslands and calculated the mean, median, and maximum distances. I then used the Wilcoxon rank sum test to compare frequency distributions of the distance radio-collared grouse traveled into treated and untreated grasslands. To avoid biases in the data from a higher number of locations from some hens, distances were averaged for each grouse in a given year. Averaging reduces the effects of any correlation between locations of an individual grouse and provides more of a population-level distribution.

As dusky grouse are believed to use grasslands more during the brood-rearing season

(Mussehl 1963, Zwickel and Bendell 2004), I also ran all analyses using only locations from brood sites. Selection ratios were analyzed using radio-collared hens with known broods, and grassland use and frequency distributions were assessed using all brood sites, including observations from uncollared birds.

3.3 Results

A total of 26 grouse dusky grouse hens were captured and radio-collared over the two years, 15 in 2016 and 11 in 2017. I obtained more than 500 locations of the 26 grouse between

May 2016 and August 2017. I recorded 192 brood locations over the two years, with 107 of those locations from radio-collared birds. Each year, I obtained 4 - 41 locations per hen (푥̃ = 15).

Fewer locations were obtained in 2017 due to wildfires in the region in July – August, reducing time spent in the field. Six hens were tracked during both summers.

Individuals began to move off the ranch toward the end of July, with some individuals moving 10 – 20 km away from their summer locations. Between October – March, I obtained 4 locations of birds that had moved off the ranch. In 2016, I obtained 3 locations from flight data.

Two hens were located on the Eastern side of the Marble Range, 5 – 10 km away from their summer locations. The third hen was located 20 km south, along the Fraser River. In 2017, one location was obtained from a flight. This bird was about 20 km away, again on the Eastern side of the Marble Range. The Marble Range consists of alpine and subalpine habitats, primarily dominated by Douglas-fir forest.

During the summer, the proportion of each habitat type available differed only slightly between years. The amount of biosolids-amended land increased by 2% for conifer forest and

6% for grasslands between May 2016 and May 2017 (Figure 3.1a). On average, untreated conifer forest comprised 50% of the study area, untreated grasslands 24%, grasslands amended with biosolids 22%, and conifer forest applied with biosolids 3%. Grouse use of each habitat type varied between years. On average, summer grouse use of untreated conifers was 54%, untreated grasslands 21%, grasslands applied with biosolids 17%, and conifer forest applied with biosolids

9% (Figure 3.1a).

In both years, hens preferred conifer forest applied with biosolids (Figure 3.1b).

However, selection ratios across habitat types in 2016 were much more similar than in 2017, with all alpha values within 0.03 of the preference threshold of 0.25 (Figure 3.1b). In 2017, hens showed stronger preference for conifer forest applied with biosolids (α = 0.57), with the other three habitat types suggesting avoidance (α < 0.2, Figure 3.1b).

On average, brood hens used conifer forests 28% of the time, and grassland habitats 72%

(Figure 3.2a). Brood hens also selected more strongly for conifer forest applied with biosolids (α

= 0.42, 0.68, Figure 3.2b). However, in 2016, brood hens also preferred biosolids-amended grasslands (α = 0.35, Figure 3.2b). Hens showed similar preference for untreated grasslands and conifer forest in both years of the study. Brood hens showed avoidance for untreated conifer forest in both years.

Of the 442 grouse locations recorded in May - July, 171 (39%) were in grasslands. The maximum distance into a grassland where I located a dusky grouse hen was 613 m, and the average distance was 116 m (Table 3.1). The average distance was higher in 2016 (푥̅ = 133 ± 13 m) than in 2017 (푥̅ = 89 ± 14 m; Table 3.1). The majority of the 132 brood locations were recorded in grasslands (69%). The average distance brood hens traveled into grasslands was 148 m. In 2017, brood hens traveled a shorter distance into grasslands (푥̅ = 83 ± 12 m, max = 387 m) than in 2016 (푥̅ = 180 ± 17 m; Table 3.1).

Grouse generally traveled further into biosolids-amended grasslands than untreated grasslands. In 2017, hens traveled significantly farther into biosolids-amended grasslands (W =

673, p = 0.03; Table 3.2) than in 2016, when hens used both biosolids-amended and untreated grasslands similarly (W = 1373, p = 0.45; Figure 3.3).

Brood hens showed an opposite trend in use of grasslands. Overall, brood hens used both biosolids-amended and untreated grasslands similarly. In 2016, brood hens traveled slightly farther into untreated grasslands (W = 740, p = 0.05; Table 3.2). In 2017, brood hens traveled farther into biosolids-amended grasslands, but their distribution into grasslands was similar for both biosolids-amended and untreated grasslands (W = 260, p = 0.45; Figure 3.4).

3.4 Discussion

Dusky grouse hens preferred biosolids-amended conifer forest over untreated forest and grasslands. In 2016, brood hens showed preference for biosolids-amended conifer forest and biosolids-amended grasslands, though preference was weak. Dusky grouse were found up to 613 m into grasslands, and biosolids appear to increase dusky grouse use of grasslands during dry summers. As a forest grouse species, I would expect grouse to select for conifer forest habitats more than grasslands. While I found this trend, I also found brood hens roosting over half a kilometer away from tree and shrub cover. Large annual variability was observed, with the use of grasslands affected by biosolids only in 2017.

In 2016, grouse showed little preference for one habitat type over the other three. This result suggests that dusky grouse hens are habitat generalists. It is possible that food availability might drive use of the landscape, as grasshoppers were common in 2016 and the grouse in the area consume a high number of grasshoppers throughout the summer. 2016 was also much wetter and cooler than 2017. These annual differences in weather likely affect grouse both directly, as hens and chicks need to regulate body temperature, and indirectly, through changes in food availability.

Studies on other gallinaceous species have found that grouse select sites in relation to invertebrate abundance or desiccation of vegetation during the summer and that grouse migration away from summer habitat is directly related to these factors (Fischer and Reese 1996, Baines et al. 1996, Jamison et al. 2002, Haulton et al. 2003). Dusky and sooty grouse also show similar seasonal movements in relation of food abundance and vegetative desiccation (Mussehl 1960,

Bendell and Elliott 1967, Zwickel 1973). In 2017, hot and dry conditions dried vegetation out earlier, forcing hens to find cooler habitat with higher moisture content in the vegetation. An

44 increase in the productivity of vegetation may also provide more forage for grasshoppers and other invertebrates in these grasslands. Many studies have found a correlation between brood sites and areas with better forage, such as high invertebrate abundance, for young chicks (Beer

1943, Wing 1947, Sopuck and Zwickel 1992).

The preference for biosolids-amended conifer forest suggests that grouse use of these areas was high relative to what was available on the landscape. Biosolids have been applied to a small proportion (114 ha) of conifer forest in the study area due to accessibility with the equipment. As biosolids were only spread in forest that was open enough to maneuver a tractor and spreader in nearby applied grasslands, it is possible that these biosolids-amended forests were atypical to other available forest on the ranch. However, the Vegetative Resource Index

(VRI) shows that biosolids-applied forests consisted of both open (51%) and scarce (49%) conifer habitat, similar to that available on the rest of the ranch (64% open, 36% scarce).

I found that grouse venture into grasslands regularly throughout the summer. Mussehl

(1963) suggested that dusky grouse broods usually stay within 50 m of tree or brush cover. The hens I observed routinely ventured much further into grasslands. The maximum distance I measured was 613 m away from the forest edge and the average distance ((푥̅ = 116 ± 10 m) was twice the distance suggested by Mussehl (1963). However, Mussehl (1963) also found grouse ventured further into grasslands during the two years of the study with higher precipitation and stayed closer to the forest edge during drought years. I found similar results, with hens venturing further away from the forest edge during the cold and wet 2016.

My results show that biosolids may increase dusky grouse use of grasslands when available moisture is limited. Hens used both biosolids-amended and untreated grasslands to the same extent in 2016. However, in 2017, when biosolids may have provided increased moisture,

45 grouse traveled further into biosolids-amended grasslands. Biosolids increase moisture retention in soil, thus increasing moisture available to plants above ground (Shammas and Wang 2008,

SYLVIS 2008, Kominko et al. 2017). This increase in moisture would increase grass cover, delay desiccation of vegetation, and provide essential water to the wildlife consuming that vegetation. Though we did not see an effect of biosolids during 2016, when precipitation was high, it is possible that the realized effects of biosolids did not occur until the following year. As organic matter decomposes over time, previously unavailable nutrients become available to plants (Singh and Agrawal 2008). Increased biomass and grass cover may not have been realized until 2017, allowing hens to travel further into biosolids-amended grasslands compared to untreated grasslands.

Forest habitats provide cover for dusky grouse from avian predators, such as Red-tailed

Hawks (Buteo jamaicensis) and Golden Eagles (Aquila chrysaetos). Zwickel and Bendell (2004) found most adult blue grouse depredations were from avian predators, particularly accipters. If biosolids-amended grasslands see an increase in grass cover, they may provide better cover for dusky grouse compared to untreated grasslands. If these grasslands provide better forage quality or quantity, grouse may risk higher predation for access to that food, as seen in other grouse species (Bergerud and Gratson 1988, Whitaker et al. 2006). Avian predators were more abundant in 2017 (unpublished data), which might explain why dusky grouse stayed closer to the forest edge. Another explanation is that the increase in grass cover provides sufficient, or at least better cover, from predators.

These results suggest that patch selection by dusky grouse is likely affected by a combination of interactions between weather, food availability, and predation risk. Grouse use of habitats in the southern interior of British Columbia is highly variable and any attempt to predict

46 use needs to consider insect abundance and forb biomass in a given year. Biosolids may be beneficial for dusky grouse, especially during drought years when available moisture is scarce and vegetation quality is reduced during the summer. Increased forage quality reduces bottom-up limitations on the animals and allows birds to choose habitat based on other requirements.

Table 3.1 Distances dusky grouse hens travelled into grasslands at the OK Ranch in 2016 and 2017.

Number of Distance into grasslands (m) Locations Median Mean Maximum All Hens 2016 106 81 133 613 2017 65 49 89 585 Both Years 171 67 116 613 Brood Hens 2016 89 98 180 613 2017 43 53 82 387 Both Years 132 79 148 613

Table 3.2 Dusky grouse use of biosolids-amended and untreated grasslands. The Wilcoxon rank sum test compares if median distances hens moved into grasslands differed between sites with and without biosolids.

# of Locations Median Distance (m) Rank Sum Test Untreated Biosolids Untreated Biosolids W p-value All Grouse 2016 70 36 77 119 1373 0.453 2017 38 27 37 64 673 0.033 Both Years 108 63 65 80 3981 0.064 Brood Hens 2016 50 39 173 62 740 0.052 2017 24 19 46 77 260 0.445 Both Years 74 58 85 65 1888 0.238

a) Available 2016 0.6 Used 2016 Available 2017 0.5 Used 2017

0.4

0.3

0.2 Proportion of Habitat

0.1

0 Amended Conifer Untreated Conifer Amended Grassland Untreated Grassland

Figure 3.1 Habitat selection for all radio-collared grouse at the OK Ranch in 2016 and 2017. A) Proportion of used and available habitat and B) standardized selection ratios (Manly’s α) for both years. Amended habitat types were applied with biosolids in 2014-2016. The line represents the value where no selection occurs. The further from the line, the stronger the selection (above the line) or avoidance (below the line).

0.6 a) Available 2016 Used 2016 0.5 Available 2017 Used 2017 0.4

0.3

0.2 Proportion of Habitat

0.1

0 Amended Conifer Untreated Conifer Amended Grassland Untreated Grassland

Figure 3.2 Habitat selection for dusky grouse brood hens at the OK Ranch in 2016 and 2017. A) Proportion of used and available habitat and B) standardized selection ratios (Manly’s α) for both years. Amended habitat types were applied with biosolids in 2014-2016. The line represents the value where no selection occurs. The further from the line, the stronger the selection (above the line) or avoidance (below the line).

Figure 3.3 Number of dusky grouse locations at different distances into biosolids-amended (black) and untreated (gray) grasslands in a) 2016 b) 2017. Lines represent the median distance travelled into biosolids-amended (dashed) and untreated (solid) grasslands.

Figure 3.4 Number of dusky grouse brood hen locations at different distances into biosolids- amended (black) and untreated (gray) grasslands in a) 2016 b) 2017. Lines represent median distance travelled into biosolids-amended (dashed) and untreated (solid) grasslands.

Chapter 4: Conclusions

In this thesis, I looked at habitat selection by dusky grouse (Dendragapus obscurus) in the southern interior of British Columbia, Canada. Our knowledge about the nesting and brood- rearing requirements of this species is lacking (Zwickel and Bendell 2004, Johnsgard 2016) and this thesis aimed to find key habitat features used by nesting and brood-rearing dusky grouse hens. In addition, the application of biosolids, residuals left after treatment of wastewater, on my study site allowed me to assess if biosolids amendment affects grouse habitat use. The land application of biosolids has been a contentious issue for human and range stock health (SYLVIS

2008, Lu et al. 2012), yet very few studies have assessed the impact of biosolids on wildlife

(Cheng et al. 1996, Nickelson and West 1996, Brown et al. 2002, Elfroymson et al. 2000,

Washburn and Begier 2011).

In Chapter 2, I addressed microhabitat at nesting and brood-rearing sites. I found that dusky grouse are habitat generalists. Hens did not select for any one structure under which to build their nests. Nests were located under bunchgrasses, low conifer branches, shrubs, rock overhangs, the remains of a burnt slash pile, and at the base of conifers with no low branches to cover the nest. Hens did prefer nest sites with higher visual cover, which was likely correlated with reduced nest predation. I found a high proportion of failed nests were depredated by mammalian predators (coyotes, Canis latrans, black bears, Ursus americanus; red squirrels,

Tamiasciurus hudsonicus), with Common ravens (Corvus corax) being the only avian nest predator recorded. While Sopuck (1979) and Zwickel and Bendell (2004) found that nest success of the closely related coastal sooty grouse was not correlated to nest cover, I found higher visual cover at successful nests than at depredated nests. Many mammalian predators use olfactory

54 senses to hunt at night, but coyotes also use visual cues during the daytime (Wells and Lehner

1978, Wells and Bekhoff 1982). The selection for high visual cover corresponds with the majority of nest depredations occurring during daylight hours.

I found dusky grouse hens with broods showed no preference for any of the habitat variables sampled. Brood hens used open grasslands, forest patches with high canopy cover, and areas with varying shrub cover. It is possible that brood hens in this study selected sites based on food availability rather than habitat type. I did not measure forb or insect biomass, which were possible drivers of site selection. Mussehl (1960) and Stauffer and Peterson (1986) found brood hens in Montana and Idaho selected for sites with high herbaceous cover, providing adequate food for the hens and chicks. While brood hens in my study did not select for grass or forb cover,

I observed large numbers of grasshoppers near brood sites.

Dusky grouse hens did not select nesting or brood-rearing sites based on biosolids amendments. However, nest success was higher in areas with a higher amount of biosolids- amended grassland. The positive effect of biosolids may be correlated with an increase in forage available for nesting hens or cover. Gaudreault et al. (in review) found higher grasshopper densities in biosolids-amended grasslands on the OK Ranch in 2016. As insects comprise part of the adult hen diet during the summer (Stewart 1944, Mussehl 1963, Zwickel and Bendell 2004), nests near biosolids may benefit from higher insect abundance. This higher insect abundance would allow the hens to spend more time incubating eggs and protecting their nests, as the hens would not have to travel as far to find food. As biosolids also increases plant biomass (Cogger et al. 2013, Newman et al. 2014), visual cover of a nest site would likely increase.

In Chapter 3, I assessed dusky grouse habitat selection at a larger patch-level scale. I found further evidence that dusky grouse are habitat generalists. Patch-level selection was highly

55 variable between the two years of the study. Hens used both untreated and biosolids-amended conifer forest and grassland habitats. In both years, grouse selected primarily for biosolids- amended conifer forest. However, hens showed similar preference for all habitat types in 2016. I found dusky grouse traveled farther into grasslands in 2016 (maximum = 613 m, mean = 133 m), more than double the 50 m average that Mussehl (1963) suggested. However, like Mussehl

(1963), I found hens traveled farther into grasslands during the cooler, wetter year and stayed closer to the forest edge during the warmer, drier year of the study. Hens traveled farther into biosolids-amended grasslands than untreated grasslands during the drier year. This change in behavior between years suggests that the increased moisture in soil and plants provided by biosolids may benefit dusky grouse during dry years, delaying desiccation of vegetation and providing water essential to an individual’s survival.

While the benefits of biosolids on vegetation is likely dampened during drought (Farooq et al. 2009), there may be delayed effects on vegetation. Gradual decomposition of the organic matter in biosolids allows multi-year fertilization (Singh and Agrawal 2008). As spring 2017 saw high amounts of precipitation, grasses and forbs on biosolids-amended grasslands may have been exposed to more available nutrients at the beginning of the growing season before nutrient uptake was inhibited. An increase in grass cover and biomass could have provided higher cover to hens using grasslands during that year, allowing hens to travel further into biosolids-amended grasslands than untreated grasslands.

In this thesis, I have shown that, while dusky grouse are habitat generalists, some habitat selection still emerges in their use of the landscape. These choices may be driven by non- vegetation variables including food availability, predation, and weather. A key component of dusky grouse habitat is visual cover. Visual cover provides protection from predators that use

56 visual cues to key into prey. While I found some nests were successful with no cover directly over the nest bowl, successful nests had higher visual cover than unsuccessful nests. Maintaining heterogenous habitats may be beneficial to dusky grouse. Different habitat types provide a different set of resources to the grouse and areas with high heterogeneity would reduce the need for hens to expend energy traveling to other sites.

Biosolids amendments appear to be beneficial to dusky grouse, especially when vegetation quality is reduced due to limited moisture. These amendments may be a useful tool to restore degraded habitats, increasing plant biomass and insect abundance while delaying the desiccation of vegetation during the reproductive season of many wildlife species. While biosolids may not have as much of an impact on dusky grouse during years of high resource availability, they may be key during years of low resource availability. As biosolids provide fertilization over multiple years, there may be delayed effects on the vegetation grouse are using.

Grouse may not realize the effects of biosolids, through increased food availability or increased grass cover, until a year or more after application.

Future work should consider the trophic cascade effects of biosolids amendments and how food availability might affect dusky grouse use of the landscape. If grouse are selecting sites based on food availability, biosolids may indirectly affect habitat use through changes to the available food biomass. As dusky grouse use many habitats, their actual choice of sites is likely limited by food availability rather than habitat type. How treatments affect that food availability may determine where dusky grouse are found.

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Appendices

Appendix A: Microhabitat model selection

This appendix includes the full data from model selection in Chapter 2. Many variables were not important or statistically significant to site selection, so these tables were left out of the chapter.

Table A.1 Important variables for dusky grouse nest sites. Values are model-averaged parameter estimates and variable importance. Variable importance uses Akaike weights of each model containing the variable; high values indicate influential variables. Confidence intervals that do not span zero suggest the variable affects site selection.

Variable Estimate SE Lower CI Upper CI Importance Intercept 0.00 0.06 -0.12 0.12 -- Visual Obstruction 0.48 0.12 0.24 0.72 1.00 Canopy Cover 0.16 0.12 -0.07 0.40 0.26 Shrub Density -0.10 0.13 -0.35 0.15 0.14 Biosolids Grassland 0.06 0.12 -0.18 0.30 0.12 Moss 0.06 0.12 -0.19 0.30 0.11 Residual Grass -0.05 0.12 -0.29 0.19 0.11 Perennial Grass -0.03 0.14 -0.30 0.25 0.11 Biosolids Conifer -0.03 0.13 -0.28 0.22 0.11 Conifer -0.02 0.12 -0.26 0.22 0.10 Grass Height 0.03 0.14 -0.23 0.30 0.10 Forbs -0.02 0.12 -0.26 0.22 0.10 Shrub Cover 0.03 0.14 -0.26 0.31 0.10 Debris -0.02 0.14 -0.30 0.25 0.10 Tree Density -0.01 0.13 -0.26 0.25 0.10 Grassland -0.00 0.12 -0.24 0.24 0.10

Table A.2 Important variables for dusky grouse nest success. Values are model-averaged parameter estimates and variable importance. Variable importance uses Akaike weights of each model containing the variable; high values indicate influential variables. Confidence intervals that do not span zero suggest the variable affects nest success.

Variable Estimate SE Lower CI Upper CI Importance Intercept 0.00 0.08 -0.17 0.17 -- Biosolids Grassland 0.45 0.18 0.10 0.80 0.78 Visual Obstruction 0.35 0.17 0.01 0.69 0.43 Perennial Grass -0.36 0.20 -0.75 0.04 0.41 Debris 0.25 0.26 -0.26 0.77 0.14 Forbs -0.21 0.19 -0.58 0.16 0.12 Shrub Density -0.21 0.22 -0.64 0.22 0.11 Grass Height 0.24 0.29 -0.34 0.81 0.10 Canopy Cover -0.17 0.19 -0.55 0.21 0.09 Residual Grass 0.15 0.19 -0.22 0.53 0.08 Moss -0.15 0.21 -0.55 0.25 0.08 Conifer -0.10 0.25 -0.58 0.38 0.08 Biosolids Conifer -0.07 0.26 -0.58 0.44 0.08 Tree Density -0.12 0.24 -0.59 0.34 0.07 Shrub Cover 0.10 0.26 -0.41 0.61 0.07 Grassland -0.05 0.18 -0.41 0.31 0.06

Table A.3 Top models (∆AICc < 2) explaining brood site selection for dusky grouse hens at the OK Ranch in 2016. Vegetative characteristics at 39 brood sites and 38 randomly sampled sites were measured.

Adjusted Akaike 2 Model R K AICc ∆AICc Weight Tree Density - Moss 0.08 4 111.77 0 0.03 Tree Density - Moss - Residual Grass 0.10 5 111.82 0.05 0.03 Canopy Cover + Visual Obstruction - 0.09 5 111.98 0.21 0.02 Moss Canopy Cover - Moss 0.08 4 111.99 0.22 0.02 Canopy Cover - Moss - Residual Grass 0.09 5 112.31 0.54 0.02 Canopy Cover + Forbs - Moss 0.09 5 112.62 0.85 0.02 Tree Density + Visual Obstruction - 0.09 5 112.63 0.86 0.02 Moss Tree Density + Canopy Cover - Moss 0.08 5 112.78 1.01 0.02 Tree Density + Forbs - Moss 0.08 5 112.88 1.12 0.02 Visual Obstruction - Moss - Residual 0.08 5 113.01 1.24 0.01 Grass Tree Density + Biosolids Grassland - 0.08 5 113.16 1.39 0.01 Moss Visual Obstruction + Debris - Moss 0.08 5 113.25 1.48 0.01 Canopy Cover + Shrub Density - Moss 0.08 5 113.34 1.57 0.01 Debris - Moss 0.06 4 113.35 1.58 0.01 Moss (-) - Residual Grass 0.06 4 113.38 1.61 0.01 Visual Obstruction - Moss 0.06 4 113.44 1.67 0.01 Tree Density - Moss - Conifer 0.08 5 113.49 1.72 0.01 Tree Density - Moss - Shrub Cover 0.07 5 113.53 1.76 0.01 Canopy Cover - Moss - Grasslands 0.07 5 113.54 1.78 0.01 Tree Density - Moss - Grass Height 0.07 5 113.62 1.86 0.01 Tree Density - Moss - Grasslands 0.07 5 113.69 1.93 0.01 Visual Obstruction - Moss - Grass 0.07 5 113.73 1.97 0.01 Height Null 0 2 115.92 4.15 0.00

Table A.4 Important variables for dusky grouse brood sites. Values are model-averaged parameter estimates and variable importance. Variable importance uses Akaike weights of each model containing the variable; high values indicate influential variables. Confidence intervals that do not span zero suggest the variable affects site selection.

Variable Estimate SE Lower CI Upper CI Importance Intercept 0 0.06 -0.11 0.11 NA Moss -0.28 0.13 -0.53 -0.03 0.68 Visual Obstruction 0.19 0.12 -0.04 0.42 0.29 Canopy Cover 0.21 0.13 -0.05 0.47 0.28 Tree Density 0.22 0.16 -0.08 0.53 0.24 Residual Grass -0.17 0.13 -0.42 0.08 0.21 Debris 0.16 0.14 -0.12 0.43 0.16 Shrub Density 0.10 0.13 -0.14 0.35 0.12 Forbs 0.10 0.14 -0.17 0.37 0.11 Grass Height -0.09 0.15 -0.38 0.20 0.10 Biosolids Grassland 0.02 0.14 -0.27 0.30 0.09 Grassland -0.05 0.13 -0.31 0.21 0.09 Perennial Grass 0.03 0.13 -0.23 0.28 0.08 Shrub Cover -0.01 0.14 -0.28 0.27 0.08 Biosolids Conifer 0.03 0.12 -0.20 0.27 0.08 Conifer 0.00 0.13 -0.25 0.25 0.08

Appendix B: GIS Layer and Weather Information

B.1 Vegetation

Layer: veg_comp_lyr_r1_poly Source: British Columbia Ministry of Forests, Lands, and Natural Resource Operations Format: Vector digital data Date of Publication: 12/16/2016 Web Link: https://pub.data.gov.bc.ca/datasets/2ebb35d8-c82f-4a17-9c96-612ac3532d55/- VEG_COMP_LYR_R1_POLY.gdb.zip

Layer: Biosolids applications Source: SYLVIS Format: KML polygon files

I extracted conifer forest and grassland polygons from the provincial Vegetation

Resource Index for my study area. I overlaid biosolids applications each year over the vegetation polygons and created new polygons for biosolids-amended and untreated forests and grasslands.

Then, I converted each habitat type into an individual raster to allow easy extraction in R.

B.2 Weather

Layer: pcds_data Source: Pacific Climate Impacts Consortium – BC Station Data Format: CSV/ASCII Web Link: http://tools.pacificclimate.org/dataportal/pcds/map/

I selected the closest weather stations to Jesmond, British Columbia with data spanning

2016-2017. These were the Meadow Lake Station #236 and Churn Creek Station #832. I then calculated the average monthly temperature and rainfall amounts for each spring and summer.