Science, Irving K. Barber Faculty of (Okanagan)
Biology, Department of (Okanagan)
DSpace
UBCO
Kelly, Angelina
Master of Science - MSc
University of British Columbia
Wildfire influences the ecosystem function of fire adapted ecosystems. Climate change has shifted the natural fire regime of North American forests to tend to larger, higher severity fires. While wildfire is a natural disturbance, it is detrimental to the forestry industry. Salvage logging is a common practice in British Columbia (BC), Canada, forests following wildfire, and it often differs from standard harvesting practices in that it removes timber from larger expanses of land. The impacts of post-fire salvage logging on wildlife are poorly understood and may compromise the ecosystem function of post-fire landscapes. To better understand the impacts of wildfire and post-fire salvage logging on forest ecosystems, I determined the population responses of deermice (Peromyscus maniculatus), southern red-backed voles (Myodes gapperi), snowshoe hares (Lepus americanus), and red squirrels (Tamiasciurus hudsonicus). I studied these important species in a post-fire and salvage-logged interior Douglas fir (Pseudotsuga menziesii) forest on the Chilcotin Plateau, BC. I live-trapped small mammals to estimate their abundances in mature, post-fire, and post-fire salvage-logged habitats. Post-fire regenerating forest supported the highest abundances of southern red-backed voles in the study area. However, post-fire salvage logging reduced southern red-backed vole populations and supported mainly deermice, a generalist species. Snowshoe hare densities were lowest in post-fire salvage-logged sites. These sites supported significantly fewer hares than regenerating post-fire stands that burned eight-nine years ago or mature forest. Early seral post-fire regenerating stands supported the highest densities of snowshoe hares. Red squirrel densities were highest in mature forest sites, but squirrels also used eight to nine-year-old post-fire regenerating sites. Post-fire salvage logging significantly changed vegetation structure by reducing tree basal area, rendering sites unsuitable for snowshoe hares, red squirrels, and southern red-backed voles. Post-fire salvage logging delayed the recolonization of burned areas by voles, snowshoe hares, and red squirrels and removed valuable regenerating forests from the landscape. Given the increasing size of wildfires and the scale of post-fire salvage logging, the decreases in abundances of small mammal species caused by post-fire salvage logging could impact the health of forest ecosystems across entire landscapes.
i SMALL MAMMALS AND MESOMAMMALS IN A POST-FIRE AND SALVAGE-LOGGED LANDSCAPE by Angelina Kelly B.Sc. [Hons], Montana State University, 2016 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE COLLEGE OF GRADUATE STUDIES (Biology) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) January 2021 © Angelina Kelly, 2021 ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis/dissertation entitled: SMALL MAMMALS AND MESOMAMMALS IN A POST-FIRE AND SALVAGE-LOGGED LANDSCAPE submitted by Angelina Kelly in partial fulfillment of the requirements of the degree of Master of Science . Dr. Karen Hodges, Biology Department, Irving K. Barber Faculty of Sciences Supervisor Dr. Adam Ford, Biology Department, Irving K. Barber Faculty of Sciences Supervisory Committee Member Dr. Robert LaLonde, Biology Department, Irving K. Barber Faculty Sciences Supervisory Committee Member Dr. Lori Daniels, Department of Forestry, University of British Columbia Vancouver University Examiner iii Abstract Wildfire influences the ecosystem function of fire adapted ecosystems. Climate change has shifted the natural fire regime of North American forests to tend to larger, higher severity fires. While wildfire is a natural disturbance, it is detrimental to the forestry industry. Salvage logging is a common practice in British Columbia (BC), Canada, forests following wildfire, and it often differs from standard harvesting practices in that it removes timber from larger expanses of land. The impacts of post-fire salvage logging on wildlife are poorly understood and may compromise the ecosystem function of post-fire landscapes. To better understand the impacts of wildfire and post-fire salvage logging on forest ecosystems, I determined the population responses of deermice (Peromyscus maniculatus), southern red-backed voles (Myodes gapperi), snowshoe hares (Lepus americanus), and red squirrels (Tamiasciurus hudsonicus). I studied these important species in a post-fire and salvage-logged interior Douglas fir (Pseudotsuga menziesii) forest on the Chilcotin Plateau, BC. I live-trapped small mammals to estimate their abundances in mature, post-fire, and post-fire salvage-logged habitats. Post-fire regenerating forest supported the highest abundances of southern red-backed voles in the study area. However, post-fire salvage logging reduced southern red-backed vole populations and supported mainly deermice, a generalist species. Snowshoe hare densities were lowest in post-fire salvage-logged sites. These sites supported significantly fewer hares than regenerating post-fire stands that burned eight-nine years ago or mature forest. Early seral post-fire regenerating stands supported the highest densities of snowshoe hares. Red squirrel densities were highest in mature forest sites, but squirrels also used eight to nine-year-old post-fire regenerating sites. iv Post-fire salvage logging significantly changed vegetation structure by reducing tree basal area, rendering sites unsuitable for snowshoe hares, red squirrels, and southern red-backed voles. Post-fire salvage logging delayed the recolonization of burned areas by voles, snowshoe hares, and red squirrels and removed valuable regenerating forests from the landscape. Given the increasing size of wildfires and the scale of post-fire salvage logging, the decreases in abundances of small mammal species caused by post-fire salvage logging could impact the health of forest ecosystems across entire landscapes. v Lay Summary Wildfire is a natural part of fire-prone ecosystems around the world, but it is often at odds with the forestry industry. In British Columbia (BC), Canada, post-fire salvage logging is often done following wildfire to recoup economic losses. However, there is little research on how post-fire salvage logging impacts wildlife. This thesis explores the impact of wildfire and post-fire salvage logging on deermice (Peromyscus maniculatus), voles (Myodes gapperi), snowshoe hares (Lepus americanus), and red squirrels (Tamiasciurus hudsonicus). Post-fire salvage-logged sites had lower vole populations and lower species diversity than post-fire regenerating forest. Post-fire salvage-logged sites were also unsuitable habitats for snowshoe hares and red squirrels, yet post-fire regenerating forests provided habitat for snowshoe hares, red squirrels, and voles. With wildfire increasing with the impacts of climate change, the opportunity for more post-fire salvage logging operations also increases. Changing important small mammal populations has the potential to change forest ecosystems. vi Preface This research was completed under the supervision of Dr. Karen Hodges at the University of British Columbia. The original research concept was created by Dr. Hodges. The study design, data collection methods, and statistical analyses were determined by both Dr. Hodges and me. I was responsible for the identification of all field sites, all data collection and field work, development and analysis of statistical models, writing analysis code in R, displaying, interpreting, and analyzing data, and writing and editing this thesis with feedback from Dr. Hodges. Funding was provided by the Habitat Conservation Trust Foundation and NSERC. All animal handling was approved by the UBC Animal Care (Committee Permit #A17-0118) and permitted by the British Columbia Ministry of Forestry, Lands, Natural Resources and Rural development (Permit #WL18-289077). A version of Chapter 2 will be submitted for publication (Kelly, A.J. and Hodges, K.E., Post-fire salvage logging changes small mammal community structure and abundances in early seral stages). Dr. Robert LaLonde and Dr. Adam Ford provided feedback on the manuscript and the statistical analyses methods used. I was responsible for selecting field sites, collecting and analyzing data, and writing the manuscript. Dr. Karen Hodges was responsible for the original study concept and reviewed drafts of the manuscript. A version of Chapter 3 has been published in Forest Ecology and Management (Kelly, A.J. and Hodges, K.E. 2020. Post-fire salvage logging reduces snowshoe hare and red squirrel presence in early seral stages. Forest Ecology and Management 473:118272). Dr. Adam Ford provided valuable direction in statistical analyses and R code, and Dr. Robert LaLonde provided feedback on the manuscript. Dr. Karen Hodges created the original study concept and the data collection methods, as well as reviewed drafts of the manuscript. I was responsible for selecting study sites, collecting and analyzing all data, and writing the manuscript. vii Table of Contents Abstract ....................................................................................................................................................... iii Lay Summary .............................................................................................................................................. v Preface ......................................................................................................................................................... vi List of Tables ............................................................................................................................................... x List of Figures ............................................................................................................................................ xii Acknowledgements .................................................................................................................................. xiv Chapter 1 Introduction ............................................................................................................................... 1 1.1 Wildfire and shifting fire regimes ............................................................................................. 1 1.2 Post-fire salvage logging ........................................................................................................... 2 1.3 British Columbia wildfires and post-fire salvage logging ......................................................... 4 1.4 Mice, voles, and forest disturbance ........................................................................................... 6 1.5 Snowshoe hares and forest disturbance ..................................................................................... 7 1.6 Red squirrels and forest disturbance.......................................................................................... 8 1.7 Thesis goals ............................................................................................................................... 9 Chapter 2 Small mammal populations in an early seral post-fire and salvage-logged landscape ..... 12 2.1 Background ............................................................................................................................. 12 2.2 Methods ................................................................................................................................... 16 2.2.1 Small mammal trapping .................................................................................................... 16 2.2.2 Vegetation Surveys ........................................................................................................... 18 2.2.3 Statistical Analysis ............................................................................................................ 18 2.3 Results ..................................................................................................................................... 22 2.3.1 Small mammal densities ................................................................................................... 23 2.3.2 Effect of wildfire and post-fire salvage logging on deermice and southern red-backed voles 23 2.3.3 Body mass of deermice and southern red-backed voles ................................................... 24 viii 2.3.4 Demography of deermice and southern red-backed voles ................................................ 24 2.3.5 Impacts of wildfire and post-fire salvage logging on vegetation and small mammal response ......................................................................................................................................... 25 2.4 Discussion ............................................................................................................................... 25 2.4.1 Post-fire salvage logging and clearcut logging ................................................................. 30 2.4.2 Conservation implications ................................................................................................ 33 Chapter 3 Post-fire salvage logging reduces snowshoe hare and red squirrel presence in early seral stages .......................................................................................................................................................... 48 3.1 Background ............................................................................................................................. 48 3.1.1 Snowshoe hare response to forest disturbance .................................................................. 50 3.1.2 Red squirrel resonse to forest disturbance ........................................................................ 52 3.2 Methods ................................................................................................................................... 53 3.2.1 Snowshoe hare surveys ..................................................................................................... 54 3.2.2 Red squirrel surveys .......................................................................................................... 54 3.2.3 Vegetation surveys ............................................................................................................ 55 3.2.4 Statistical analysis ............................................................................................................. 55 3.3 Results ..................................................................................................................................... 58 3.3.1 Snowshoe hares ................................................................................................................. 58 3.3.2 Vegetation as predictors of hare habitat use ..................................................................... 58 3.3.3 Red squirrels ..................................................................................................................... 60 3.4 Discussion ............................................................................................................................... 60 3.4.1 Impacts of wildfire on snowshoe hares and red squirrels ................................................. 60 3.4.2 Impacts of post-fire slavage logging on snowshoe hares and red squirrels ...................... 61 3.4.3 Wildfire and post-fire salvage logging in British Columbia ............................................. 64 Chapter 4 Conclusion ............................................................................................................................... 73 References .................................................................................................................................................. 79 ix Appendices ............................................................................................................................................... 100 Appendix A: Example code and supplementary density estimates of deermice and voles (Chapter 2). 100 Appendix B. Mean snowshoe hare pellet counts and red squirrel middens counts (Chapter 3). ..... 106 x List of Tables Table 2.1 Dates of each trapping session by habitat type during 2018 and 2019. The earliest date of trapping is given, as not all grids of the same habitat type were trapped on the same days. ...................... 35 Table 2.2 Total small mammal captures across each grid in all habitat types. Chipmunks and shrews were not tagged. For all species, one individual caught multiple times accounts for multiple captures. ............ 36 Table 2.3 Generalized mixed effects model coefficients comparing total individual deermice and southern red-backed voles captured between habitat types and year using a Poisson distribution. All habitat types are compared to mature forest as the control. Year 2019 is compared to 2018. Grid and session were included as random effects. ......................................................................................................................... 37 Table 2.4 Generalized linear model predicting the effects of habitat type + year on deermouse and southern red-backed vole masses. All habitat types were compared against mature forest as the control. Year 2019 is compared to 2018. All data were from the late-summer sessions of each year. .................... 38 Table 2.5 Generalized quasi-binomial model coefficients predicting the effect of habitat type + year on the proportion of juvenile and reproductive adult deermice and southern red-backed voles in the population. All habitat types were compared against mature forest as the control. Year 2019 is compared to 2018. All data was from the late-summer session of each year. ............................................................. 39 Table 2.6 Vegetation attributes by habitat type. Grass, moss, forb, shrub cover, and bare ground were measured in 2 m radius plots. Attributes sharing the same superscript letter did not differ significantly as determine by an ANOVA and Tukey HSD post-hoc tests. Values are x̄ ± SD........................................... 40 Table 2.7 Regression parameters for generalized linear models of vegetation attributes and total individuals captured of deermice and southern red-backed voles............................................................... 41 Table 3.1 Vegetation attributes and hare pellets by habitat type. Grass, shrub, and forb cover were measured in 2 m radius circular plots. Superscript letters represent results of Tukey HSD post-hoc test. Habitat types sharing letters did not differ significantly. ............................................................................ 66 xi Table 3.2 Logistic mixed effect models predicting pellet presence with both habitat and vegetation fixed effects. Statistics are for fixed effects and the random effect of Site for all models. All habitat types were compared against mature forest as the control. ........................................................................................... 67 Table 3.3 AICc ranking of vegetation mixed effects models predicting presence of snowshoe hare pellets in sites and habitat types. ............................................................................................................................ 67 Table 3.4 Regression coefficients of the predictive vegetation parameters for the top five vegetation models. ........................................................................................................................................................ 68 xii List of Figures Figure 2.1 Chilcotin study area and location of small mammal live-trappings grids and habitat types. .... 42 Figure 2.2 Mean density and standard deviations of estimates of A) deermice and B) southern red-backed voles by habitat type during 2019, and C) deermice by habitat type during 2018. Session 1 refers to the early-summer session, session 2 is mid-summer session, and session 3 is late-summer session. There were not enough voles captured in 2019 in the 2010 burn + salvage-logged sites or in all sites in 2018 to estimate densities. There were not enough deermice captured in mature forest sites in 2018 to estimate densities. ..................................................................................................................................................... 43 Figure 2.3 A) Deermice and southern red-backed vole total individuals captured during the mid-summer session in relation to live tree basal area. B) deermice total individuals captured in relation to moss during the mid-summer session of 2019. Total individuals from the mid-summer session only were used to match seasonal timing of vegetation surveys, and to avoid repeating models with multiple mouse or vole totals, but only one vegetation dataset. ....................................................................................................... 46 Figure 2.4 The effect of disturbance on the abundances of deermice and southern-red-backed voles. Data of the effect of fire and post-fire salvage logging are effects on abundances from both years of my research in the Chilcotin. Data of the effect of clearcutting is from 17 publications and comes from abundance estimates at least 2 years after clearcutting occurred (Borgne et al. 2018a, b, Darmon et al. 2013, Fauteux et al. 2012, Klenner and Sullivan 2009, Lemaître et al. 2010, Moses and Boutin 2001, Pearce and Venier 2005, Potvin et al. 1999, Ransome et al. 2009, Sullivan and Sullivan 2001, 2008, 2011, 2016, 2018a, 2019, 2020). The degree of effect on abundance plotted is an estimated mean ratio of the change in abundance from either before and after the disturbance, or in disturbed areas compared to mature forest. .............................................................................................................................................. 47 Figure 3.1 The locations of the hare pellet survey sites in relation to habitat type on the Chilcotin Plateau, BC. .............................................................................................................................................................. 69 Figure 3.2 A) The proportion of fecal pellet plots with hare pellets in each site represented by small black dots. The average proportion of plots with pellets present for each habitat type is represented by a xiii triangle. B) The mixed effects logistic regression model predictions of the probability of pellet presence given the habitat type. Standard error is from fixed effects (habitat type) only. ........................................ 70 Figure 3.3 Total red squirrel midden counts by site and mean midden counts by habitat type. Mean midden counts by habitat type are represented by bold hollow diamonds. ................................................. 71 Figure 3.4 Red squirrel midden counts in relation to live canopy tree density. The regression is positive (R2 = 0.23, F1,21 = 6.428, p = 0.02). ............................................................................................................. 72 xiv Acknowledgements I would like to acknowledge that this research was conducted on the traditional and unceded territory of the Tsilhqot’in people, which is now governed by the Tŝilhqot’in National Government. It was an honor to spend so much time in this special place. To Jack Wicks, thank you for your unwavering support. I am grateful for all your encouragement and patience over the past three years. I would not have completed this work without you. I certainly would not be the person I am today without you. I am also grateful to my parents and my sisters for supporting me and encouraging me to pursue this research. To my lab mates, Kirstie Lawson, Kristen Mancuso, Kristine Teichman, Jen Meineke, and Leah Rensel, thank you for your support. Logan Volkmann, thank you for all your help with this work. I am thankful to have shared a study site with you. I am eternally grateful to Luke Crevier for all your help with my R code, and for those long dog park conversations. Your solidarity helped me get through many challenges and reminded me to have patience with myself. To all my field assistants, including Louiza Oukil, Julia Kobetitch, and Jenna Scherger, thank you for your hard work. Our conditions were often less than ideal, and you all worked your hardest every day. I want to extend a deep heart-felt “thank you” to Dan Hunter, Elise Brown-Dussault, and Erica Hannah. The season I spent in the field with you all was one of the most beautiful adventures of my life. You filled every day with laughter, music, and wonderful companionship. I am grateful for all the times you reminded me to eat and sleep, and every cup of coffee you made for me. Without you all I would surely still be wandering through the forest, trying to complete all this work. I am also thankful to the Suters and the Stowells for housing and supporting me through two long field seasons. I am particularly thankful to Shari Suter, for sharing her home and friendship with me, and for teaching me so many things. xv The statistical analyses used in this thesis were made possible under the guidance of Dr. Adam Ford. I had little confidence in my analytical abilities and no experience coding in R, but your assistance allowed me to confidently achieve the analysis I needed. You also pushed me to approach this research from a wider ecological lens, something that improved my writing immensely. Dr. Robert LaLonde, I am grateful for your help in refining my statistical analyses and improving my writing. Frank Doyle, thank you for visiting me in the field and bringing us donuts. You continually lift my spirits and confidence with your knowledge and support. Finally, thank you to my supervisor, Dr. Karen Hodges, for all you have done for me over the past three years. Your confidence in me has given me confidence in myself, and the trust you put in me to complete this research has allowed me to excel as a scientist, and to become a better mentor to others. 1 Chapter 1 Introduction 1.1 Wildfire and shifting fire regimes Terrestrial ecosystems and the plant and animal species that inhabit them have evolved with natural fire regimes, and wildfire drives the evolution of species in these systems (Berry et al. 2015, Bond and Keeley 2005, Fernandez-Garcia et al. 2020). Plants and wildlife survive wildfire and recolonize burns by dispersing from fire refugia that do not burn or that burn at low severities (Berry et al. 2015, Meigs and Krawchuk 2018). Fire regimes and the response of wildlife to wildfire varies by ecosystem. Wildfire is the most dominant natural disturbance in North American boreal forests, and it shapes their ecology (Agee 2000). In the boreal forests of North America, fire severity ranges from low severity, smaller fires that do not often result in large tree mortality to large, high severity crown fires that ocurr every 150-300 years (Agee 2000). Southern interior boreal and montane forests of the west experience more frequent, lower severity fires that ocurr in 20-50 year intervals (Henry 2002). The habitats created by wildfire attract many species in boreal forest systems (Nappi et al. 2004). During the first years after large stand-replacing fires, forest stands are characterized by herbaceous and low shrub cover and woody debris. Coarse woody debris is left behind as a biological legacy that takes 50-100 years to decay (Agee 2000). This coarse woody debris is an important structural habitat component in forest ecosystems and remains on the landscape as forests regenerate (Farnell et al. 2020, Harmon and Hua 1991). Following a fire, open post-fire habitats are replaced by stands of seedlings and saplings after 20-40 years (Agee 2000). These saplings transition to mature trees between 40-300 years following fire. The time the stand takes to return to a late seral stage depends on the dominant tree species, and ranges from 200-400 years (Agee 2000). 2 Regenerating post-fire areas provide important habitat for small mammals and a diversity of predators that prey on them (Fisher and Wilkinson 2005, Nappi et al. 2004, Hutchen et al. 2017, Volkmann et al. 2020), yet fire regimes in North America are changing. Western North American forests are experiencing reduced snowpack, warmer springs and hotter summer dry seasons due to climate change (Westerling et al. 2006). Drought and increased insect outbreaks have increased fuel loading in forests (Littell et al. 2016). Anthropogenic fire suppression as a result of European colonization has increased the severity of fire regimes in North America (Littell et al. 2016, Hessburg et al. 2019, Marlon et al. 2012, Miller et al. 2012, Parisien et al. 2020). Historical indigenous burning practices have ended under colonial governments, suppressing fire that has occurred for thousands of years (Christianson 2015, Eisenberg et al. 2019, Lake and Christianson 2019, Liebmann et al. 2016, Turner et al. 2000). The compounded effects of climate change and fire suppression are predicted to contribute to an increase in fire activity and severity (Dennison et al. 2014, Hanes et al. 2019, Miller et al. 2009, Prichard et al. 2017, Westerling et al. 2006). The changing fire regimes in boreal forests reflect a global trend of increasing wildfire occurrence and size (Seidl et al. 2011). Changing fire regimes have the potential to impact both wildlife and human activity. 1.2 Post-fire salvage logging Despite the positive influence fires have on forest ecosystems, wildfire is detrimental to human ecosystem services like timber production (Brecka et al. 2020). Forests around the world are often salvage-logged following wildfire (Eng 2004, Lindenmayer et al. 2004, Thom and Seidl 2016, Thorn et al. 2018). Salvage logging allows harvesters to mitigate their economic losses following forest disturbance by harvesting the remaining timber (Eng 2004, Saint-Germain and Greene 2009). Salvage logging is also conducted to control fuel loads of dead trees that are 3 thought to increase the severity of future fires (Thompson et al. 2007). While many forestry practices attempt to mimic the effects of a natural disturbance through reduction of cutblock size and tree retention (Bergeron et al. 2007, Delong and Tanner 1996), salvage logging practices are often larger and more intense than standard logging (Thorn et al. 2018). Salvage logging differs from standard practices in that it often removes more timber from larger areas of land, and is often planned and executed quickly following fire as harvesters race to get the timber to market before it decays and loses value (Lindenmayer and Noss 2006, Müller et al. 2018). The impacts of salvage logging on forests are understudied. However, studies that have been done show that salvage logging is often detrimental to forest ecosystem function (Lindenmayer et al. 2004, Thorn et al. 2018). Post-fire salvage logging can compromise the ability of wildfire to act as a crucial, ecosystem-shaping natural process (Schmiegelow et al. 2006, Thorn et al. 2018). Salvage logging decreases forest biodiversity and changes ecological processes, such as altering soil through soil compaction, introducing invasive weeds, changing hydrology, and altering the structural complexity of post-disturbance stands through the building of roads and removal of coarse woody debris (Gayton and Lara Almuedo 2012, Lindenmayer and Noss 2006, Thorn et al. 2018). Furthermore, biological legacies from past wildfire can influence how forests burn and regenerate in future fire events, with low to moderate severity fires producing a higher resilience to high severity fires (Harris et al. 2020, Stevens-Rumann et al. 2016). Salvage logging followed by replanting alters these natural biological legacies homogenizes regeneration of stands and can increase fire severity in future fires, altering the natural fire regime of the forest (Thompson et al. 2007). Because the impacts of salvage logging vary between ecosystems, there are no standards of salvage logging that can be widely applied, therefore its effects should be studied in all 4 ecosystems where this is practiced (Lindenmayer and Noss 2006). With fire severity and size expected to increase (Dennison et al. 2014, Westerling et al. 2006), salvage logging operations may also increase. An increase in large post-fire salvage logging operations risks the homogenization of forest ecosystems and the stability of wildlife populations on a landscape scale. 1.3 British Columbia wildfires and post-fire salvage logging In 2017, British Columbia (BC) experienced the largest wildfire season to date in provincial history, with many large, high-severity fires that burned 1.2 million ha of forest and triggered the longest provincial state of emergency in BC history (BC Wildfire Service 2019). One of the largest wildfires was the 240,000 ha Hanceville fire on the Chilcotin Plateau (BC Wildfire Service 2019). In 2018, 1.3 million hectares of land burned, breaking the record set by the 2017 fire season just one year before (BC Wildfire Service 2019). Following the 2017 fire season, British Columbia Ministry of Forests, Lands, Natural Resource Operations and Rural Development (BC FLRORD) developed a post-fire forest retention guide, released in January 2018. The first priority of the guide to consider when determining tree retention was to maintain human safety, and the second priority was to protect and promote wildlife habitat, and the guide acknowledged the importance of early seral regenerating habitat (BC FLRORD 2018). Following this directive, in October 2018 the Forest Practices Board released a report in response to a complaint by trappers in the Quesnel, BC area. The report found that extensive salvage logging following mountain pine beetle outbreaks in the area significantly damaged the quality of habitat for fisher (Pekania pennanti), a species designated “at risk” by the Forest and Range Practices Act of 2002. The report also found that while the individual licensees made 5 efforts to protect wildlife habitat, the efforts were not enough in the context of the “unprecedented scale” of salvage logging (Forest Practices Board 2018). Furthermore, the report stated that the BC Ministry of Forests did not take appropriate actions to ensure the protection of fisher habitat during salvage logging. Following the large wildfires of 2017 in the Cariboo region of BC, the Forest Practices Board stated that unplanned post-fire salvage logging in the area would worsen an already weakened landscape (Forest Practices Board 2018). The Chilcotin Plateau specifically has experienced large wildfires in recent years, including the Meldrum Creek Fire in 2010 and the record-setting Hanceville Fire in 2017 (BC Wildfire Service 2019). Salvage logging following wildfires in the region has impacted the entire forest landscape. Large salvage logging operations in quick succession compounded with the disturbance of wildfire have the potential to risk important prey species, and thus the health of the forest ecosystem. The lack of research on the effects of post-fire salvage logging on important wildlife is concerning given how widespread the practice of salvage logging is in BC forests. Understanding how post-fire salvage logging impacts wildlife communities is crucial to the responsible management of post-fire forests. Small mammals and mesomammals play important roles in the health of forest ecosystems. Southern red-backed voles (Myodes gapperi), red squirrels (Tamiasciurus hudsonicus), and other small mammals consume fungi and are integral to spore dispersal in forest systems (Fogel and Trappe 1978, Maser et al. 2008). Red squirrels, deermice (Peromyscus maniculatus), and voles (Microtus spp.) also consume and spread seeds in forest systems, sometimes consuming enough to affect the tree composition and regeneration of forests (Boone and Mortelliti 2019, Lobo et al. 2009, Vander Wall 2010). Small mammals and mesomammals are important prey species for many predators in forest ecosystems globally, and in the boreal 6 forests of North America (Carey and Johnson 1995, Krebs 2011). It is important to understand how these species respond to disturbances. 1.4 Mice, voles, and forest disturbance Forest disturbances like wildfire tend to change abundances of small mammals and shift the structure of small mammal communities (Griffiths and Brook 2014, Sullivan and Sullivan 2016). Specifically, forest disturbances like wildfire or clearcut logging shift small mammal communities from specialist to generalist species immediately following the disturbance (Sullivan and Sullivan 2016). Generalist species colonize more recently disturbed areas, while specialist species are more abundant in more mature forest habitats (Sullivan and Sullivan 2016). In western Canadian forests, deermice often dominate small mammal species assemblages following disturbances (Borgne et al 2018a, Darmon et al. 2013, Fisher and Wilkinson 2005, Klenner and Sullivan 2009, Sullivan et al. 1999). Because they are a generalist species, deermice can forage efficiently and are often more successful in post-fire landscapes than specialist species (Fisher and Wilkinson 2005, Gliwicz and Glowacka 2000, Zwolak et al. 2012). Other generalist small mammal species, such as long-tailed voles (Microtus longicaudus) and eastern chipmunks (Tamias amoenus) increase in abundance following logging (Nelson et al. 2019, Sullivan and Sullivan 2011, 2016). Conversely, southern red-backed voles respond negatively to disturbances that remove large trees, including severe wildfire and clearcut logging (Klenner and Sullivan 2009, Sullivan et al. 1999, Sullivan and Sullivan 2011, 2020, Zwolak 2009). They are a specialist species that depend on mature forest conditions (Pearce and Venier 2005). Changes in food availability and competition with deermice following clearcut logging cause steep declines of southern red-backed voles (Borgne et al. 2018a, Lemaître et al. 2010, Martineau et al. 2016). 7 While small mammal responses to clearcut and other logging methods are widely studied (Borgne et al 2018a, Darmon et al. 2013, Fisher and Wilkinson 2005, Klenner and Sullivan 2009, Martineau et al. 2016, Sullivan and Sullivan 2001, 2011, 2016, 2019, 2020, Zwolak 2009), there is little research on small mammal response to post-fire salvage logging (Kronland and Restani 2011, Puig-Gironés et al. 2020). The compounded effects of wildfire and salvage logging may be different than the effects of one disturbance alone. Furthermore, while the trend of replacing specialist species with generalist species is consistent across habitat types, small mammal responses to disturbance can vary widely by year and by location (Klenner and Sullivan 2009, Nelson et al. 2019, Pinotti et al. 2015, Potvin et al. 1999, Püttker et al. 2019). Given this variability in small mammal response to disturbance and the lack of research on post-fire salvage logging, it is important to study small mammal responses to post-fire salvage logging in all ecosystems where it occurs. 1.5 Snowshoe hares and forest disturbance Snowshoe hares (Lepus americanus) are an important keystone mesomammal species in Canadian boreal forest ecosystems and are essential prey for many predators (Krebs et al. 2013), and it is important to understand how forest disturbances impact hare populations. Hares choose habitats with sufficient vegetation cover from predators, including overstory and midstory cover (Cheng et al. 2015, Ferron et al. 1998, Hodges 2000, Thomas et al. 2019). Because hares need cover, their populations decrease immediately following wildfire or logging (Hodges et al. 2009, Potvin et al. 1999, Thornton et al. 2012) and following salvage logging after insect outbreaks (Thomas et al. 2019). However, as forests recover from disturbance, shrub and sapling cover increases and the habitat becomes more suitable for hares (Allard-Duchene et al. 2014). 8 Regenerating forests with browse and cover provide valuable habitat for hares (Hodson et al. 2011, Newbury and Simon 2005, Thornton et al. 2012). Snowshoe hares and their population cycles have been widely studied because of their importance as a keystone prey species in boreal forests (Hodges 2000, Hodges et al. 2001, Koehler 1990, Krebs et al. 2017, Oli et al. 2020). While there are studies on the impacts of wildfire or logging on snowshoe hares (Allard-Duchene et al. 2014, Cheng et al. 2015, Hodges et al 2009, Hodson et al. 2011, Hutchen and Hodges 2019, Koehler 1990, Olnes et al. 2019, Strong and Jung 2012), I am not aware of any studies on the compounded effects of wildfire and post-fire salvage logging on snowshoe hare populations. Understanding the impacts of post-fire salvage logging in early seral stages will be increasingly important as wildfires increase in BC, as forests will be burning and regenerating in quicker succession than under historical fire regimes (Hanes et al. 2019, Prichard et al. 2017). 1.6 Red squirrels and forest disturbance Red squirrels depend on mature forest stands with large trees (Haughland and Larsen 2004), and populations decline following forest disturbance (Allard-Duchene et al. 2014, Fisher and Wilkinson 2005, Fisher and Bradbury 2006). They depend on understory structural diversity, downed woody debris, and canopy cover as escape terrain and cover from predators (Russell et al. 2010), as well as large mature trees and large snags (Holloway and Malcolm 2006). Red squirrels consume conifer seeds as their primary food source and depend on mature forests (Gurnell 1984, Kemp and Keith 1970, Rusch and Reeder 1978). Because they need trees, the detrimental effects of large, tree-removing disturbances on red squirrel populations is predictable and shown in studies on their response to clearcut logging (Allard-Duchene et al. 2014, Fisher et 9 al. 2005, Holloway and Malcolm 2006). However, no studies have shown the impact that post-fire salvage logging has on red squirrel populations and their recolonization times. 1.7 Thesis goals The responses of many small mammals to wildfire or clearcut logging are documented, but there is a glaring gap in research into the effects of compounding these disturbances with the practice of post-fire salvage logging. This lack of research is particularly concerning in BC given the recent record-setting wildfires and the intense salvage-logging practices (BC Wildfire Service 2019, Forest Practices Board 2018). The scale and intensity of wildfire and post-fire salvage logging, combined with a global increase in wildfire activity due to climate change and anthropogenic fire suppression since European colonization, requires an increase in research to guide forest management (Hanes et al. 2019, Lindenmayer and Noss 2006, Miller et al. 2009, Prichard et al. 2017, Westerling et al. 2006, Siedl et al. 2011). To better understand the effects of wildfire and post-fire salvage logging on small mammals, I studied small mammal populations in an interior Douglas fir (Pseudotsuga menziesii) forest on the Chilcotin Plateau in BC. This area has been impacted by large wildfires and post-fire salvage logging. In 2010, The Meldrum Creek Fire Complex burned 47,293 ha of forested area, and much of the burn was salvage-logged. In 2017, 241,160 ha burned in the Hanceville Fire, overlapping the southwestern corner of the study area (BC Wildfire Service 2017). To understand the impacts of these disturbances, I compared small mammal densities and vegetation attributes between four habitat types; mature forest, one to two-year old post-fire forest (2017 burn), eight to nine-year-old post-fire forest (2010 burn), and eight to nine- year-old post-fire sites that were salvage-logged (2010 burn + salvage-logged). I conducted this research for two years during the summer and fall of 2018 and the spring and summer of 2019. 10 In Chapter 2, I offer research on the impacts of post-fire salvage logging on deermice and vole species. I determined density estimates, and population demographics of deermice and southern red-backed voles in mature forest, 2017 burn sites, 2010 burn sites, and 2010 burn + salvage-logged sites. I also measured species richness and diversity in these habitat types. I used live trapping and spatially-explicit capture-recapture modelling, methods that have been widely used to monitor small mammal populations (Borcher and Efford 2008, Efford et al. 2013, Efford 2015, Hamilton et al. 2019, Krebs et al. 2011, Ransome et al. 2009, Sullivan and Sullivan 2010, 2018 a, b). I surveyed vegetation and modelled vegetation attributes with deermouse and southern red-backed vole capture totals to better understand the vegetation attributes driving each species’ habitat use and response to disturbance. In Chapter 3, I address the gap in knowledge regarding the response of snowshoe hares and red squirrels to post-fire salvage logging. I used non-invasive index methods to determine the responses of both species in mature forest, one to two-year-old post-fire forest, eight to nine-year-old post-fire forest, and post-fire salvage-logged areas. I used snowshoe hare fecal pellet counts as an index of hare densities (Hodges and Mills 2008, Krebs et al. 1987, 2001, Mills et al. 2005). I used midden counts as an index of relative red squirrel abundance (Mattson and Reinhart 1996, Podruzny et al. 1999). To gain a better understanding of what vegetation hares select within stands as they forage, I surveyed vegetation and modelled pellet presence with each vegetation attribute. I also modelled vegetation attributes with red squirrel midden counts to better understand what characteristics red squirrels select in a highly disturbed landscape. While population densities do not offer a complete picture of species’ responses to disturbance, they provide a valuable step toward understanding the effects of post-fire salvage logging and informing post-fire forest management. 11 Finally, in Chapter 4 of this thesis, I give a general overview of my research results. I discuss the importance of the results to the Chilcotin region and the forests of British Columbia. I also put the patterns observed in small mammal population responses to disturbance in the context of global patterns following forest disturbance. 12 Chapter 2 Small mammal populations in an early seral post-fire and salvage-logged landscape 2.1 Background Wildfire drives the evolution of species and function of fire-prone ecosystems globally (Bond and Keeley 2005) and positively influences the biodiversity and habitat quality of forest ecosystems (Thom and Seidl 2016). Around the world, plants and wildlife have adapted to the fire regimes specific to their systems (Berry et al. 2015, Fernandez-Garcia et al. 2020, Fisher and Wilkinson, 2005). While wildfire is a natural disturbance essential to fire-prone forest ecosystems, it can be at odds with the forestry industry. Wildfires impact the forestry industry because fires reduce the amount and value of timber available for harvest (Bergeron et al. 2004, Schmiegelow et al. 2006, Thom and Seidl 2016). To recover some economic losses following wildfire, timber companies often harvest burnt trees through post-fire salvage logging (Eng 2004, Garcia-Carmona et al. 2020, Saint-Germain and Greene 2009). Fire refugia, or areas that do not burn or burn at low severities during wildfire, enable recolonization by wildlife following wildfire (Meigs and Krawchuk 2018). Biological legacies like burned trees and unburned patches would naturally remain on the landscape, shaping post-fire habitats and helping to determine future fire regimes (Harris et al. 2020, Gayton and Lara Almuedo 2012, Lindenmayer and Noss 2006), and yet can be lost during post-fire salvage logging (Meigs and Krawchuk 2018). The removal of biological legacies and loss of the natural post-fire mosaic of habitats could impede the natural ecosystem-shaping ability of wildfire (Schmiegelow et al. 2006). Furthermore, wildfire is often seen by society as damaging and detrimental, and this perception allows post-fire salvage logging to be conducted at larger scales and intensities than standard logging (Lindenmayer and Noss 2006, Müller et al. 2018, Noss and Lindenmayer 2006). Salvage 13 logging is done quickly as harvesters try to get timber to market before it decays and loses value (Müller et al. 2018). This combination of urgency and intensity means that harvesters often deviate from standard logging practices that seek to replicate natural disturbances, and instead harvest larger blocks that retain fewer trees (Thorn et al. 2018). Intense and large-scale post-fire harvest could hinder the ability of species adapted to wildfire to rebound from the compounded effects of wildfire and logging. The impacts of salvage logging on wildlife is understudied, and the potential cumulative effects of salvage logging following wildfire are poorly understood (Lindenmayer and Noss 2006). Habitat fragmentation and disturbance can shift community structures by increasing the abundances of generalist species and homogenizing communities (Püttker et al. 2015; 2019, Marvier et al. 2004). Thus, understanding the impacts of both wildfire and post-fire salvage logging on key ecosystem species is vital to responsible management of forests. Western North American forests have historically been subject to low to moderate severity fires that leave mosaics of burn severities on the landscape (Agee 2000). However, fires are increasing in prevalence and severity due to climate change (Agee 1993, Hanes et al. 2019, Loehman et al. 2017, Miller et al. 2009, Prichard et al. 2017, Westerling et al. 2006). An increase in wildfire frequency and severity could lead to an increase in post-fire salvage logging. The compounded effects of both disturbances could drastically change forest ecosystems at a landscape scale. To better understand how post-fire salvage logging impacts wildlife, I studied the impacts of wildfire and post-fire salvage logging on small mammal species in interior dry Douglas fir (Pseudotsuga menziesii) forest in central British Columbia, Canada. Small mammals are important prey species for many predators in forest ecosystems (Carey and Johnson 1995, Krebs 2011, Sullivan and Sullivan 2020) and southern red-backed 14 voles (Myodes gapperi) specifically are primary prey for marten (Martes americana) and weasels (Mustela spp.; Buskirk and Zielinski 2003). They also play an important role in seed consumption and dispersal, and dispersal of mycorrhizal spores through the consumption of fungi (Boone and Mortelliti 2019, Maser et al. 2008). Through seed selection and consumption, small mammals can influence the regeneration and species composition of forest stands following disturbance (Boone and Mortelliti 2019, Lobo et al. 2009, Vander Wall 2010). It is therefore important to understand how small mammals respond to disturbances. Forest disturbances like wildfire shift the small mammal communities from specialist to generalist species immediately post-fire (Sullivan and Sullivan 2016). Generalist species colonize more recently disturbed areas, while specialist species are abundant in more mature forest habitats where it is assumed they out-compete generalists (Pinotti et al. 2015, Sullivan and Sullivan 2016). The specific response of many small mammals to both wildfire and salvage logging depends on vegetation (Krefting and Ahlgren 1974). Deermice (Peromyscus maniculatus) are habitat generalists and dominate post-fire habitats during the initial years following fire (Fisher and Wilkinson 2005, Klenner and Sullivan 2009, Sullivan et al. 1999). Because they are omnivores with flexible diets and consume both seeds and arthropods (Gliwicz and Glowacka 2000, Pearson et al. 2000), they can find food more easily and forage efficiently in post-disturbance landscapes than can more specialized species (Fisher and Wilkinson 2005, Zwolak et al. 2012). Southern red-backed voles are specialists tied to established forest stands and populations respond negatively to disturbances that remove large trees (Klenner and Sullivan 2009, Sullivan et al. 1999, Zwolak 2009). Southern red-backed voles are important mycophagists, consuming fungi and spreading spores (Maser et al. 2008). Southern red-backed voles are indicators of 15 mature forest conditions and their abundances are highest in areas with live trees, complex understory cover, and coarse woody debris (Boonstra and Krebs 2012, Fauteux et al. 2012, Pearce and Venier 2005, Sullivan and Sullivan 2001, Vanderwel et al. 2010). Some southern red-backed vole populations may also fluctuate in three to five-year population cycles, while other populations can fluctuate less regularly (Boonstra and Krebs 2012). Meadow voles (Microtus pennsylvanicus) are also a specialist species and select microhabitats with higher grass cover (Adler and Wilson 1989), thus often respond positively to the increase in grass and forb cover following fire. Similarly, long-tailed voles (Microtus longicaudus) also respond to regenerating grass, forbs, and saplings, and populations can increase following disturbances (Sullivan and Sullivan 2010, 2018a). With fires increasing in North American forests (Hanes et al. 2019, Westerling et al. 2006), there is a potential for an increase in salvage logging, and it is important to understand how both disturbances impact wildlife. My objectives were 1) to estimate species richness and diversity of rodents in post-fire, salvage-logged, and mature forests, 2) to estimate density, body condition, and proportion of juveniles and reproductive individuals of small mammal species in post-fire, salvage-logged, and mature forests; and 3) to characterize vegetation in each habitat and determine important vegetation attributes that influence abundances of small mammals. I hypothesized that 1) post-fire salvage-logged sites would have a lower species diversity than post-fire or mature forests, 2) post-fire salvage-logged sites would support mostly deermice with no vole populations, and 3) post-fire salvage logging would change the vegetation structure of regenerating forest by removing trees and changing ground cover and mid-story cover, and these multi-level changes in vegetation would, in turn, drive the loss of vole populations. 16 2.2 Methods The study area was ~ 32,000 hectares on the eastern edge of the Chilcotin Plateau, BC on Department of National Defense Land and Crown land (Figure 2.1). The forest is dominated by interior Douglas fir, with some Engelmann spruce (Picea engelmannii), lodgepole pine (Pinus contorta), and trembling aspen (Populus tremuloides) in a mosaic of seral stages. There are grasslands and some wetlands that comprise about 15% of the study area. Much of the area is maintained by the Department of National Defense as military training grounds. Cattle from local ranches range over the entire study area, impacting all habitats. The forest is managed for harvest, and logging is the dominant disturbance on the landscape. Recently, this area has been impacted by large wildfires and post-fire salvage logging. The Meldrum Creek Fire Complex burned 47,293 ha of forest in 2010, and approximately 70% of the burned area was salvage-logged within two years following the fire. Most of the harvest was of moderately to severly burned areas. In 2017, 241,160 ha burned in the Hanceville Fire (BC Wildfire Service 2019), located just southwest of the Meldrum Creek Fire and overlapping the southwestern corner of the study area. The Hanceville fire was mostly moderate to high severity and was unique in that it reburned some forest that had burn in 2010. It provided an opportunity to study the impacts of a wildfire almost immediately post-fire, something rarely achieved in small-mammal research (Hutchen et al. 2017). 2.2.1 Small mammal trapping I live-trapped small mammals in four habitat types throughout the study area: mature forest, 2010 burn, 2010 burn + salvage-logged, and 2017 burn. Each habitat type had three replicates, totaling 12 trapping grids. I selected grid locations using satellite imagery, followed by on-ground exploration of sites. I chose sites easily accessible by road, but remote enough to avoid human disturbance. I chose sites that were similar to other sites of the same habitat type 17 and, when possible, I placed sites of different habitat types near each other. Grids in 2017 burn were in severe burns, as severe burns were the most abundant type following the Hanceville fire and it was easiest to choose locations similar to each other. Grids in 2010 burns were in mostly light to moderate burns, as most of the moderate and severe patches had been salvage-logged. I deployed traps in eight by eight arrays with traps 15 m apart, so trapping grids were 105 m by 105 m. I used both Longworth and Sherman traps to reduce sampling bias (Anthony et al. 2005). I placed Longworth and Sherman traps alternately at each trap location in every grid, so each trapping grid had 32 of each trap type. Trapping began in May and went into August in 2018 and 2019. Three trapping sessions were completed in each year. The early-summer session began in May and ended in June, the mid-summer session ran from mid-June until mid-July, and the late-summer session ran from mid-July until August. During both seasons, access to 2017 burn grids was delayed due to seasonal flooding, so trapping in this habitat type did not start until much later in the season (Table 2.1). During a single session, I trapped each grid for three nights. I baited traps with peanut butter, oats, and a cucumber slice. In 2018, traps were stuffed with cotton to provide insulation. In 2019, I stuffed traps with locally sourced wool. I set traps in the evenings before sunset and checked traps the following morning at dawn. Longworth traps were left locked open and Sherman traps were left locked closed throughout the day, to prevent catching animals in the heat of the day. Each mouse or vole captured was given a uniquely numbered ear tag. I recorded the ear tag number, species, sex, mass and reproductive condition of each animal. Southern red-backed voles with a mass < 19 g were considered juveniles, and voles ≥ 19 g were considered adults (Klenner and Sullivan 2009, Sullivan and Sullivan 2020). Deermice with a mass < 15 g were 18 considered juveniles, and adults were ≥ 15 g (Klenner and Sullivan 2009). Females were counted as reproductive if they were pregnant or lactating, and males were recorded as reproductive if their testes were scrotal. All individuals were released at the site of capture. Chipmunks (Tamias amoenus) and shrews (Sorex cinereus) were released without handling. All animal handling was approved by the UBC Animal Care Committee and we obtained BC Animal Care and General Wildlife permits. 2.2.2 Vegetation Surveys I surveyed vegetation on trapping grids between June and August 2018, and May through June 2019. I conducted 20 vegetation surveys in each of the 12 trapping grids. I randomly selected 20 non-overlapping trap sites within each grid to conduct surveys. I surveyed ground cover in a two m radius circle by estimating percentage of each of four categories: bare ground and rocks, grass and forbs, shrubs, and moss and lichen. I estimated shrub cover and counted saplings under two m tall in the two m radius circle. I estimated canopy closure using a densiometer and took four readings, one in each cardinal direction, and averaged the readings. I measured all coarse woody debris over 7.5 cm in diameter and greater than one m long along a 15 m transect centered on the survey point and oriented to a random compass bearing that was consistent at each survey point within the same trapping grid. I measured the diameter at breast height (DBH) of all trees and snags greater than 7.5 cm DBH in a circular 15 m radius plot and recorded the species of all live trees measured. 2.2.3 Statistical Analysis Species richness was determined using all captured species. I used the Shannon diversity index as a measure of species diversity. I used total tagged individuals captured during the late-summer session in each grid and then averaged the diversity across each habitat type. 19 I used spatially explicit capture-recapture models to estimate the densities of each species of small mammal tagged for each year (Efford et al. 2013). I used the secr package version 4.2.0 (Efford 2015) in R Studio version 3.5.1. Spatially explicit capture-recapture models relate an individual animal’s home range to the location of a given detector, or trap, and use capture probability (g0) and spatial scale (σ) to determine a detection function. The probability of capture decreases with increased distance from a trap. I assumed a half normal detection function for all models after comparison with negative exponential showed little difference in density estimates (Hamilton et al. 2019, Krebs et al. 2011). The buffer distance around the trapping grid was 100 m for all models, a value three to four times larger than spatial scale parameter (σ) estimates given by each model (Krebs et al. 2011). I created models to estimate densities for each species on each grid for each primary session. I constructed models with varying predictor values of capture probability (g0), while spatial scale (σ) and density (D) were always a function of session. The null model had g0 as a function of session. Alternate predictor variables of capture probability were function of learned response to capture (b), time of each primary session (t), time as a linear function (T), session and learned capture response (session + b). I compared models for each grid and species combination using Akaike’s Information Criterion adjusted for small sample sizes (AICc) and used density estimates given by the top model for each grid and species combination (Burnham and Anderson 2004, Hamilton et al. 2019, Nelson et al. 2019). I used generalized mixed effects models with a Poisson distribution to determine the relationship between total individuals captured and habitat type for deermice and southern red-backed voles. I used total tagged individuals captured for this analysis because reliable density estimates were not possible for grids with low capture numbers and would have introduced error inherent in estimating densities into the model. I included year as a fixed effect to test for 20 differences in total captures between years. I included grid and session as crossed random effects, because while grids were nested replicates within habitat types, sessions occurred across all grids, and were not exclusive to one particular grid (Schielzeth and Nakagawa 2013). Including these random effects helps control for correlation between capture totals from the same grids and the same sessions. Trapping began much later in 2017 burn sites in 2018 due to flooding, which resulted in misaligned sessions between habitat types; I therefore removed 2017 burn data from the early- and mid-summer sessions during 2018 from these models. All sessions in the 2017 burn sites during 2019 are included in the models. I used a similar generalized linear mixed effects model to determine the effect of habitat type on deermouse and southern red-backed vole masses. However, I used a linear distribution appropriate for continuous data. I also analyzed mass data from only the late-summer session of each season, to avoid repeated measures on the same individual throughout the season. The late summer session was the largest dataset, and thus supported a more complex model structure than the earlier season sessions. Although animals were weighed each time they were captured, I used mass at first capture for each session in the models. I included habitat and year as fixed effects, and grid as a random effect. I used a generalized linear model to determine the effect of habitat type and year on the proportions of juveniles and reproductive adults in the small mammal populations. As this dataset was smaller and simpler, consisting of only one proportional measurement per grid, it did not support a generalized linear mixed effects model. To test for density dependence of deermouse and southern red-backed vole mass, I used a generalized linear mixed effects model. I used masses of adult individuals paired with the corresponding density estimates of the grid and session in which they were trapped, and included 21 grid nested within habitat as random effects, and session as a random effect. I used data from both years for deermice and only 2019 for southern red-backed voles because there were not enough density estimates for southern red-backed voles from 2018 to test for density dependence. Because session was included as a factor, I removed the early and mid-summer sessions from 2018 to account for the misalignment of trapping dates and to keep models consistent. I checked all vegetation attributes for correlation using a Pearson correlation matrix and considered coefficients of |0.7| or greater to be correlated as suggested by Dormann et al. (2013). Canopy closure and tree basal area were correlated with a coefficient of 0.72. I excluded canopy closure because tree basal area was more reliably measured in the field. I included shrub cover, tree basal volume, bare ground, moss and lichen, grass, forbs, sapling density, and coarse woody debris volume as vegetation attributes to compare between habitat types. Coarse woody debris volume was estimated using the following formula: [1] 𝑉 =𝑘𝑎𝑐𝐿∑ 𝑑𝑖2𝑛𝑖=1 where V is the coarse woody debris volume in m2/ ha, k is the unit conversion constant 1.234, a is the lean angle correction factor, c is the slope correction factor, L is the total survey transect length in m, and d is the coarse woody debris diameter at the transect (Woodall and Williams 2007). I set both a and c to one because slope and lean angle were not measured in the field. I conducted an ANOVA and Tukey’s HSD post-hoc test to determine how vegetation attributes varied between habitat types. I then used generalized logistic models in the negative binomial family to determine the relationship between live tree basal area, grass cover, forb cover, moss cover, bare ground, sapling density, shrub cover, coarse woody debris volume and 22 total individual deermice and total individual southern red-backed voles. I scaled vegetation attributes by subtracting the attribute’s mean and dividing by the standard deviation before modeling. I used vegetation survey results from 2019 and individual capture numbers from the mid-summer session of 2019, as capture numbers were higher than the early-summer session and the mid-summer session overlapped with the timing of vegetation surveys. I performed a univariate analysis and modelled each vegetation attribute separately against each species’ total individuals captured. 2.3 Results Over both seasons, deermice and southern red-backed voles made up most of the captures (76% and 17%, respectively). I also captured meadow voles, shrews, and yellow-pine chipmunks. In both years, small mammal species richness was highest in the 2010 burn sites, with five species present. Mature and 2010 burn + salvage-logged sites had three species present in 2018, and 2017 burn had only deermice. In 2019, five species were present and thus, species richness was higher in 2010 burn, mature, and 2010 burn + salvage-logged sites (Table 2.2). In 2019, species richness was also higher than the previous year in 2017 burn sites with four species present. Mean Shannon diversity was highest in mature and 2010 burn grids during 2019 (0.68 ± 0.02 and 0.71 ± 0.04, respectively) and 2018 (0.21 ± 0.36 and 0.45 ± 0.39, respectively). Mean species diversity was lowest in 2017 burn grids (0.52 ± 0.15) and in 2010 burn + salvage-logged grids (0.21 ± 0.10) during late summer in 2019. In 2018, no animals were captured so mean species diversity was zero in 2017 burn and 2010 burn + salvage-logged sites. Mean species diversity was lower in all habitat types in 2018 than in 2019. Deermice were the most dominant species, followed by southern red-backed voles, while meadow voles were rare. 23 2.3.1 Small mammal densities Mean densities of deermice and southern red-backed voles were higher in 2019 than in 2018 on all grids. Total captures in 2018 were low, resulting in low density estimates with higher variance for deermice and few reliable density estimates for southern red-backed voles (Table 2.2, Figure 2.2). Deermice had the highest densities of any species throughout the study area during both years. Deermouse densities were highest in 2010 burn + salvage-logged grids in 2018 (Mean ± S.E., 8.5 ± 4.9 mice/ha). In 2019, deermouse densities were highest in 2017 burn sites (28.7 ± 8.0 mice/ha) and were second highest in 2010 burn + salvage-logged sites (21.6 ± 7.8 mice/ha). Deermouse densities were lowest in 2010 burn and mature forest sites during both years. During both years, mean southern red-backed vole densities were highest in 2010 burn sites and lowest in 2010 burn + salvage-logged sites (Figure 2.2, Appendix A). In 2018, no southern red-backed voles were captured in 2017 burn sites or 2010 burn + salvage-logged sites. Mean southern red-backed vole densities were highest in mature sites in 2018 (6.10 ± 2.88 voles/ha). Meadow voles were captured both years but did not have enough captures for reliable density estimates. Meadow vole captures were highest in 2010 burn and 2010 burn + salvage-logged in 2018 with three individuals each, and lowest in mature and 2017 burn sites with no individuals captured. Individual tagged meadow vole captures were highest in 2010 burn and 2017 burn sites in 2019. Total individual meadow voles ranged from zero to six over both years. 2.3.2 Effect of wildfire and post-fire salvage logging on deermice and southern red-backed voles For deermice, habitat type + year were strong predictors of numbers of individuals captured (Table 2.3). Mature forest had the fewest deermouse captures. 2017 burn and 2010 burn 24 + salvage-logged sites had the highest deermouse captures, and a change from mature forest to 2010 burn, 2017 burn, or 2010 burn + salvage-logged sites had the strongest positive impacts on the total number of captures. More mice were captured in 2019 than in 2018. For southern red-backed voles, habitat type + year were also strong predictors of total individuals captured (Table 2.3). Captures of individual red-backed voles were significantly higher in 2010 burn than in mature forests, and total red-backed voles were significantly lower in 2010 burn + salvage-logged and 2017 burn than mature forest. More southern red-backed voles were captured in 2019 than 2018. 2.3.3 Body mass of deermice and southern red-backed voles Body masses of adult deermice were on average 2.75 g heavier in 2018 than in 2019 (p < 0.001, Table 2.4). Deermice were significantly heavier in 2017 burn than mature forest but body mass did not differ among other habitat types. Density was not a strong predictor of adult deermouse masses (Table 2.4). Body masses of adult southern red-backed voles did not differ significantly between years or habitat type and did not differ with density (Table 2.4, Figure 2.3). 2.3.4 Demography of deermice and southern red-backed voles Proportions of juvenile deermice did not differ significantly between habitat type or year during the late-summer session (Table 2.5, Figure 2.4). Proportions of reproductive adult deermice did not differ between habitat type but were significantly higher in 2018 than in 2019 (p < 0.001, Table 2.5). Proportions of juvenile southern red-backed voles in the population were lower in 2017 burn and 2010 burn + salvage-logged sites than in mature forest, and did not differ between years (Table 2.5, Figure 2.4). Proportions of reproductive adults in the southern red-backed vole 25 population did not differ between habitat type but were higher in 2019 than in 2018 (Table 2.5, Figure 2.4). 2.3.5 Impacts of wildfire and post-fire salvage logging on vegetation and small mammal response Wildfire and post-fire salvage logging significantly changed vegetation and habitat structure. Unsurprisingly, tree basal area was highest in mature forest, followed by 2017 burn, 2010 burn, and lastly 2010 burn + salvage-logged sites (Table 2.6). When only live tree basal area was considered, mature forest and 2010 burn forest had significantly higher tree basal area (mean ± S.D., 23.6 ± 11.7 m2/ha, 8.4 ± 7.2 m2/ha) while 2017 burn and 2010 burn + salvage-logged sites had no live trees. Shrub cover was significantly higher in 2010 burn sites than any other habitat type (49.2 ± 25.9 %, F3, 236 = 42.00, p < 0.001). Shrub cover did not differ significantly between mature and 2010 burn + salvage-logged sites (p = 0.29), but was lowest in 2017 burn sites (10.25 ± 9.93 %). Sapling densities were significantly lower in 2017 burn sites than all other habitats (53.1 ± 323.2 trees/ha, F3, 236 = 15.34, p < 0.001). Sapling densities were highest in 2010 burn + salvage-logged sites. The number of individual deermice captured was negatively correlated with live tree basal area and moss cover (Figure 2.5, p = 0.00 for both). The number of southern red-backed voles captured was positively correlated with live trees (Figure 2.5, p = 0.02). There were no other significant relationships between other vegetation attributes and southern red-backed voles or deermice (Table 2.7). 2.4 Discussion Post-fire forest stands that had been regenerating for eight to nine years supported higher species richness and species diversity of small mammals than did post-fire salvage-logged areas, 26 supporting hypothesis 1. However, species richness increased in post-fire salvage-logged sites and one to two-year-old post-fire regenerating sites as small mammal abundances increased throughout the study area, suggesting that the effect of fire and post-fire salvage logging on species richness may change quickly with shifting small mammal populations. The mean species diversity of newly burned sites showed the biggest increase between years and recovered from 0 to 0.52 from one to two years post-fire. In contrast, post-fire salvage-logged areas supported mainly deermice and few voles, with a mean species diversity of 0.22. Post-fire salvage-logged sites had reduced species diversity in comparison to post-fire regenerating forests nine years post-fire, and species diversity in post-fire salvage-logged sites did not recover as quickly as in post-fire sites that were unharvested. Southern red-backed vole densities were highest in eight to nine-year-old post-fire regenerating forest, suggesting that regenerating post-fire forest provides valuable habitat. Post-fire salvage-logged sites had significantly lower southern red-backed vole densities than all other habitat types, supporting hypothesis two. In 2018 when vole densities were low, southern red-backed voles were not present in one year post-fire forest or post-fire salvage-logged sites. Southern red-backed voles recolonized two year post-fire sites and post-fire salvage-logged sites in 2019 when small mammal densities were much higher in all sites, and vegetation had regenerated further following the 2017 fire. The proportion of reproductive adults in the southern red-backed vole population was higher in 2019 than 2018, suggesting that the population will continue to increase in most of the study area. However, two-year-old post-fire sites and post-fire salvage-logged sites had lower proportions of juveniles than mature forest sites. These sites of more recent and more intense disturbance may not be selected in comparison to mature forest 27 sites, and populations of southern red-backed voles in disturbed areas will likely not increase as quickly as in undisturbed, mature forests. Post-fire salvage logging significantly changed the habitat structure of regenerating areas by removing nearly all trees, which likely resulted in the loss of southern red-backed voles and supports hypothesis three. Southern red-backed vole densities were highest in post-fire regenerating sites and mature forests and southern red-backed vole captures were positively correlated with live tree basal area. The low densities of southern red-backed voles, combined with the low proportion of reproductive adults, suggests that post-fire salvage-logged sites provide low quality habitat for southern red-backed voles. The higher density of southern red-backed voles in post-fire regenerating forest compared to mature forest sites is somewhat surprising, given that southern red-backed voles are closely tied to mature forests, and showed a positive correlation to live tree basal area (Boonstra and Krebs 2012, Pearce and Venier 2005). A possible explanation for the high density of southern red-backed voles in the eight to nine-year-old post-fire regenerating sites could be the burn severity of the sites. Following the 2010 Meldrum Creek Fire in the Chilcotin, most moderate and high-severity burned areas were salvage-logged. Low-severity patches were the only sites available from the 2010 Meldrum Creek Fire for small mammal trapping and provided enough cover to support high densities of southern red-backed voles. Recolonization of post-fire areas may have been different in high severity burns, had those stands remained on the landscape unharvested. However, this harvest pattern does not explain the fact that southern red-backed vole densities were higher in post-fire sites than in mature forest sites. It is possible that voles were responding to vegetation or food availability changes that I did not measure. Further, the mature forest sites I trapped have been impacted by human activity, including timber harvest and 28 cattle grazing, and no forest in the study area resembled old growth forest. It is likely that the mature forest I studied did not provide ideal mature forest conditions for southern red-backed voles. These varying results in southern red-backed vole response to fire and logging highlight the importance of studying the impacts of wildfire and post-fire salvage logging in all forest types in which they occur. In contrast to southern red-backed vole densities, deermouse densities were highest in two-year-old post-fire regenerating sites and post-fire salvage-logged sites, areas of more recent and intense disturbance. Deermouse densities were lower in older regenerating post-fire forest, and lowest in mature forest. Live trees were negatively correlated with deermouse densities. Deermouse densities were also negatively correlated with high moss cover, a ground cover type more common in mature and eight to nine-year post-fire forests. In other systems like the American southwest and grasslands, deermice densities have been higher in larger, open habitats like large meadows (Horncastle et al. 2019, Kaufman et al. 1990). In the Chilcotin, deermouse densities were highest in two-year post-fire sites and could have been responding to a more open understory with fewer shrubs but increased forb and grass growth post-fire. This open understory may have allowed deermice to move and forage more easily (DeGolier et al. 2015). Adult deermouse masses were also significantly higher in two-year post-fire sites than in mature forest, suggesting that these recently burned areas provide high quality habitat for deermice, as mass can reflect habitat quality (Albers et al. 1990, Navarro-Castilla and Barja 2019). The high proportion of juvenile deermice captured in post-fire salvage-logged areas suggests that the population may still be growing. This population growth may be from immigration from nearby habitats, or from higher reproduction within post-fire salvage-logged areas. The proportion of reproductive adults in the deermouse population was higher in 2018 29 than in 2019, which likely led to the higher proportions of juveniles in some sites and higher overall densities in 2019. The discrepancy in mean deermouse mass between trapping years may be due to the younger, increasing population in 2019, as a higher proportion of younger adults in the population would skew the mean mass lower in 2019 than in 2018. However, this effect was not strong enough to result in density dependence of mass when the correlation of measures within the same grids and the same habitat types were also considered. Post-fire salvage logging was an intense and compounded disturbance that allowed deermice to replace specialist species for at least nine years following the original wildfire. The high relative density of deermice in salvage-logged sites and two-year regenerating post-fire forests follows a common pattern of increase in generalist species following disturbance in many systems, in which generalist species benefit from the loss or absence of specialist species (Klenner and Sullivan 2009, Marvier et al. 2004, Pinotti et al. 2015, Püttker et al. 2019, Sullivan and Sullivan 2001, 2016, 2020). However, the increase in deermice may not be due to the direct loss of competition with voles, as deermice and southern red-backed voles do not necessarily compete directly for food (Galindo and Krebs 1985). More likely, deermice may be strong colonizers who are able to forage efficiently in new, high severity burns and salvage-logged sites with less vegetation because of their locomotion of larger leaps, but are not as successful as vole species in later successional stages when food becomes scarcer and ground cover becomes more complex (DeGolier et al. 2015, Pinotti et al. 2015). Deermice may be filling ecological niche space in post-fire salvage-logged sites when southern red-backed voles are lost. Measuring food availability along with species densities would shed more light on the mechanisms driving small mammal community shifts. 30 Long-tailed vole (Microtus longicaudus) and meadow vole populations in southern interior BC have been reported to increase strongly following wildfire (Sullivan et al. 2007), and individuals often consume regenerating tree saplings, grasses, and forbs (Sullivan et al. 1990, Sullivan and Sullivan 2010). The habitat types I trapped supported very few of either of these species. Meadow voles respond mostly to grass cover, and it is possible that the forested and post-fire salvage-logged habitats I live-trapped did not meet a threshold of grass cover to support growing meadow vole or long-tailed vole populations (Adler and Wilson 1989, Getz et al. 2001, Sullivan and Sullivan 2010). It is also possible that the varying trappability and behavior of small mammals resulted in low captures of meadow voles and long-tailed voles that did not reflect their actual densities. 2.4.1 Post-fire salvage logging and clearcut logging Post-fire salvage logging is similar to clearcut logging in intensity but compounds the disturbances of both wildfire and clearcut harvest. While clearcut logging is often planned in smaller cutblocks, post-fire salvage logging occurs quickly after wildfire, and can cover larger areas of already disturbed forest (Lindenmayer and Noss 2006, Thorn et al. 2018). Understanding the differences and similarities of the impacts of clearcut logging and post-fire salvage logging can clarify how these practices should be approached and informs post-fire forest management. Clearcut logging often causes a similar shift in small mammal community structures from specialist species to generalist species. Specifically, it is common for deermouse abundances to increase, or at least stay constant, following clearcut harvesting (Figure 2.6; Borgne et al. 2018a, Craig et al. 2006, Darmon et al. 2013, Klenner and Sullivan 2009, Moses and Boutin 2001, Pearce and Venier 2005, Potvin et al. 1999, Ransome et al. 2009, Sullivan and Sullivan 2001, 31 2019). Deermouse populations also increased in the Chilcotin in post-fire salvage-logged sites. Long-tailed voles, another generalist species, also increase in abundance following clearcut logging, and reach a population peak four years after harvest (Sullivan and Sullivan 2011, 2016, 2018a). Meadow voles also have higher abundances in clearcut sites than variable retention harvests during the first six years postharvest (Sullivan and Sullivan 2011). Abundances of eastern chipmunks (Tamias striatus) also increase following clearcut logging, while white-footed mouse (Peromyscus leucopus) densities remain more constant (Nelson et al. 2019). In the Chilcotin, there was no increase in abundances in any generalist species other than deermice following post-fire salvage logging. Congruent with my findings in post-fire salvage-logged sites, southern red-backed vole abundances decrease following clearcut harvesting (Figure 8; Borgne et al. 2018b, Klenner and Sullivan 2009, Lemaître et al. 2010, Moses and Boutin 2001, Pearce and Venier 2005, Ransome et al. 2009, Sullivan et al. 2008, Sullivan and Sullivan 2011, 2020). This decrease in southern red-backed vole abundance following clearcut logging contrasts with my observations in post-fire regenerating forests where southern red-backed vole densities increased in comparison to mature forest sites. Southern red-backed voles often increase in abundance in clearcuts immediately following harvesting but are lost from clearcut sites after two years post-harvest (Klenner and Sullivan 2009, Martineau et al. 2016, Sullivan and Sullivan 2018b, 2019). However, Potvin et al. (1999) found southern red-backed vole densities did not change significantly during the first four years postharvest. Clearcut sites immediately after harvest provided poor quality habitat for red-backed voles that reduced red-backed vole survival in comparison with mature stands and created a population sink (Martineau et al. 2016). Competition with deermice and intraspecific 32 competition also drove a decline in southern red-backed voles in clearcut areas (Borgne et al. 2018a, Lemaître et al. 2010). Coarse woody debris piles may help mitigate some cover loss caused by harvesting and help southern red-backed voles recover to pre-harvest abundances more quickly than sites with less coarse woody debris (Fauteux et al. 2012, Sullivan and Sullivan 2019). Southern red-backed vole populations tend to increase as forest succession advances (Borgne et al. 2018a; 2018b). Forest disturbances can change not only species abundances, but small mammal community assemblages as well. Of six publications that reported species richness, all found an increase in multiple generalist species that helped maintain species richness and diversity following clearcut logging (Sullivan et al. 2008, Sullivan and Sullivan 2001, 2011, 2016, 2019, 2020). For example, Sullivan and Sullivan (2011; 2016) reported increases in abundances of long-tailed vole and other Microtus species following clearcut logging that helped maintain species diversity postharvest. This increase in other vole species did not occur in the post-fire salvage-logged areas in the Chilcotin. In contrast, post-fire salvage logging in the Chilcotin reduced species richness during the first year of live trapping when species abundances were low. During the second season when abundances were high, post-fire salvage-logged sites supported a species richness equal to that of post-fire regenerating forest and mature forest sites. However, post-fire salvage-logged sites in the Chilcotin had the lowest species diversity of all habitat types over both seasons. The reduction in species richness and diversity in post-fire salvage-logged sites in the Chilcotin compared to the reported use of clearcut sites by several generalist species in other studies suggests post-fire salvage logging may have more detrimental impacts on small mammal community structure than clearcut logging. Furthermore, older post-fire regenerating sites had the highest species richness and diversity of all habitat types in the 33 Chilcotin. The stark difference in species richness and diversity between post-fire regenerating sites and post-fire salvage-logged sites suggests that the compounded effect of post-fire salvage logging and wildfire are stronger and more detrimental than wildfire or clearcut logging alone. The reduction in species abundances by post-fire salvage logging may last longer than reductions caused by clearcut logging. Some populations of southern red-backed voles have recovered to pre-harvest abundances in 11-12 years post-harvest with woody debris pile remediation (Sullivan and Sullivan 2019). Southern red-backed vole populations in the Chilcotin post-fire salvage-logged sites showed little increase in abundances nine years following fire and salvage logging. Because of the variability in small mammal response to forest disturbances, small mammal abundances should be monitored in all habitats where clearcut logging and post-fire salvage logging occur. While clearcut harvesting and post-fire salvage logging change small mammal community structures and abundances, post-fire salvage logging is often done over larger areas than clearcut harvesting, and has the potential to shift communities across landscapes (Lindenmayer and Noss 2006, Müller et al. 2018, Noss and Lindenmayer 2006). 2.4.2 Conservation implications Salvage logging operations often cover larger areas and remove more trees than standard logging practices (Lindenmayer and Noss 2006, van Nieuwstadt et al. 2001), and post-fire salvage logging in the Chilcotin followed this trend. Large, intensely harvested cutblocks risk the homogenization of the landscape and the removal of biological legacies following wildfire. Post-fire salvage logging fragments regenerating habitats, reducing connectivity between forest patches. A reduction in forest connectivity reduces small mammal diversity (Morales-Díaz et al. 2019). Post-fire salvage logging changes vegetation structure and impedes recolonization of 34 post-disturbance areas by reducing small mammal species diversity and vole densities over large areas. Regenerating post-fire stands are important habitat for small mammals. The loss of these habitats to post-fire salvage logging is not only a concern for small mammals, but for the predators and forest ecosystems that depend on these species. As wildfire occurrence increases with climate change, there is potential for post-fire salvage logging activity to increase. Logging vast areas of regenerating post-fire habitat will change small mammal communities across BC forests by reducing vole populations and increasing deermouse populations. While this pattern is concerning for BC ecosystems, it also reflects a global response to habitat change in which specialist species are being replaced by generalist species (Clavel et al. 2011). Thus, I stress the importance of my findings to forest management. Post-fire salvage logging has the potential to change community structures and population abundances of important species in all systems it impacts and should be studied everywhere it is implemented.35 Table 2.1 Dates of each trapping session by habitat type during 2018 and 2019. The earliest date of trapping is given, as not all grids of the same habitat type were trapped on the same days. 2018 Trapping Dates 2019 Trapping Dates Trapping Session Mature 2010 Burn 2017 Burn 2010 Burn + Salvage-logged Mature 2010 Burn 2017 Burn 2010 Burn + Salvage-logged Early-summer Start May 31 June 21 June 16 June 28 July 28 July 31 June 16 June 28 May 15 May 17 May 21 June 1 June 2 June 4 May 21 June 1 End Mid-summer Start July 7 July 9 July 10 July 15 Aug. 8 Aug. 10 July 10 July 15 June 30 July 12 June 17 July 3 July 9 July 16 June 17 July 3 End Late-summer Start Aug. 18 Aug. 20 July 25 Aug. 14 Aug. 21 Aug. 23 July 25 Aug. 11 July 25 July 28 July 20 July 28 July 29 Aug. 4 July 20 July 28 End 36 Table 2.2 Total small mammal captures across each grid in all habitat types. Chipmunks and shrews were not tagged. For all species, one individual caught multiple times accounts for multiple captures. 2018 Total Captures 2019 Total Captures Common Name Species Name Mature 2010 Burn 2017 Burn 2010 Burn + Salvage-logged Mature 2010 Burn 2017 Burn 2010 Burn + Salvage-logged Deermouse Peromyscus maniculatus 30 87 135 285 187 340 790 674 Southern red-backed vole Myodes gapperi 19 16 0 0 181 267 82 20 Meadow vole Microtus pennsylvanicus 0 3 0 5 2 4 8 3 Yellow-pine chipmunk Tamias amoenus 0 30 0 5 1 109 0 28 Cinereous shrew Sorex cinereus 2 2 0 0 1 1 0 1 37 Table 2.3 Generalized mixed effects model coefficients comparing total individual deermice and southern red-backed voles captured between habitat types and year using a Poisson distribution. All habitat types are compared to mature forest as the control. Year 2019 is compared to 2018. Grid and session were included as random effects. Model Parameter Estimate Lower 95% C.I. Upper 95% C.I. Standard Error Z (Wald’s) P value Deermice 2010 Burn 0.56 0.14 0.99 0.20 2.85 0.004 2017 Burn 1.42 1.01 1.84 0.19 7.36 < 0.001 2010 Burn + Salvage-logged 1.36 0.95 1.77 0.19 7.06 < 0.001 Year 2019 1.20 1.07 1.34 0.07 17.41 < 0.001 Southern red-backed voles 2010 Burn 0.33 -0.01 0.68 0.15 2.19 0.028 2017 Burn -0.81 -1.21 -0.42 0.19 -4.37 < 0.001 2010 Burn + Salvage-logged -2.18 -2.77 -1.64 0.28 -7.68 < 0.001 Year 2019 2.72 2.34 3.16 0.21 12.99 < 0.001 38 Table 2.4 Generalized linear model predicting the effects of habitat type + year on deermouse and southern red-backed vole masses. All habitat types were compared against mature forest as the control. Year 2019 is compared to 2018. All data were from the late-summer sessions of each year. Model Parameter Estimate Lower 95% C.I. Upper 95% C.I. Standard Error t value P value Deermice 2010 Burn 0.74 -0.44 1.92 0.60 1.23 0.22 2017 Burn 1.21 0.25 2.18 0.49 2.47 0.01 2010 Burn + Salvage-logged 0.47 -0.52 1.45 0.50 0.93 0.35 Year 2019 -2.89 -3.62 -2.16 0.37 -7.75 <0.001 Southern red-backed voles 2010 Burn 0.78 -0.76 2.32 0.79 0.99 0.32 2017 Burn -0.43 -2.26 1.41 0.93 -0.46 0.65 2010 Burn + Salvage-logged 0.42 -2.92 3.76 1.70 0.25 0.81 Year 2019 3.00 -0.93 6.93 2.01 1.50 0.14 39 Table 2.5 Generalized quasi-binomial model coefficients predicting the effect of habitat type + year on the proportion of juvenile and reproductive adult deermice and southern red-backed voles in the population. All habitat types were compared against mature forest as the control. Year 2019 is compared to 2018. All data was from the late-summer session of each year. Model Parameter Estimate Lower 95% C.I. Upper 95% C.I. Standard Error t value P value Deermice Juveniles 2010 Burn -0.71 -2.05 0.63 0.68 -1.04 0.31 2017 Burn -1.41 -2.93 0.11 0.77 -1.82 0.08 2010 Burn + Salvage-logged -0.19 1.47 1.08 0.65 -0.29 0.77 Year 2019 0.39 -0.60 1.38 0.50 0.78 0.45 Reproductive Adults 2010 Burn 0.51 -0.42 1.43 0.47 1.08 0.29 2017 Burn 0.36 -0.57 1.30 0.48 0.76 0.46 2010 Burn + Salvage-logged -0.83 -1.95 0.29 0.57 -1.45 0.16 Year 2019 -1.80 -2.59 -1.01 0.40 -4.45 0.00 Southern red-backed voles Juveniles 2010 Burn 0.31 -0.87 1.48 0.60 0.51 0.62 2017 Burn -2.15 -3.72 -0.57 0.80 -2.67 0.02 2010 Burn + Salvage-logged -1.66 03.06 -0.27 0.711 -2.34 0.03 Year 2019 0.24 -0.76 1.23 0.51 0.47 0.65 Reproductive Adults 2010 Burn 0.49 -0.83 1.81 0.67 0.73 0.49 2017 Burn 0.43 -0.88 1.74 0.67 0.64 0.53 2010 Burn + Salvage-logged -0.69 -2.15 0.78 0.75 -0.92 0.37 Year 2019 1.93 0.75 3.11 0.60 3.20 0.01 40 Table 2.6 Vegetation attributes by habitat type. Grass, moss, forb, shrub cover, and bare ground were measured in 2 m radius plots. Attributes sharing the same superscript letter did not differ significantly as determine by an ANOVA and Tukey HSD post-hoc tests. Values are x̄ ± SD. Vegetation Attribute Mature 2010 Burn 2010 Burn + Salvage-logged 2017 Burn F P x̄ ± SD x̄ ± SD x̄ ± SD x̄ ± SD Tree Basal Area (m2/ha) 24.6 ± 11.9a 12.4 ± 8.2b 0.4 ± 1.7c 21.6 ± 11.9a 80.35 < 0.001 Live Tree Basal Area (m2/ha) 23.6 ± 11.7a 8.4 ± 7.2b 0 ± 0c 0 ± 0c 157.80 < 0.001 Coarse Woody Debris Volume (m3/ha) 113.3 ± 525.2 39.9 ± 64.2 124.0 ± 100.4 33.6 ± 50.4 1.87 0.14 Grass Cover (%) 47.7 ± 20.5 47.3 ± 17.0 51.6 ± 21.0 41.4 ± 24.8 2.40 0.07 Moss Cover (%) 30.8 ± 20.4a 18.9 ± 13.3b 17.92 ± 14.3b 14.3 ± 9.0b 13.96 < 0.001 Shrub Cover (%) 32.4 ± 18.7a 49.2 ± 25.9b 26.2 ± 18.9a 10.3 ± 9.9c 42.00 < 0.001 Forb Cover (%) 16.8 ± 10.7a 26.8 ± 14.0b 22.6 ± 12.9a, b 29.1 ± 25.0b 6.41 < 0.001 Bare Ground (%) 4.7 ± 7.4a 6.8 ± 10.7a 7.8 ± 10.9a 16.4 ± 13.0b 14.09 < 0.001 Sapling Density / ha 1220.2 ± 1468.6a 1870.1 ± 2672.9a, b 2851.5 ± 3486.6b 53.1 ± 323.2c 15.34 < 0.001 41 Table 2.7 Regression parameters for generalized linear models of vegetation attributes and total individuals captured of deermice and southern red-backed voles. Model Parameters Estimate Standard Error z value p value Deermouse Live Trees Intercept 3.39 0.06 58.76 0.00 Live Trees -0.56 0.07 -7.78 0.00 Grass Cover Intercept 3.51 0.15 23.48 0.00 Grass Cover -0.02 0.16 -0.15 0.88 Forb Cover Intercept 3.50 0.15 24.06 0.00 Forb Cover 0.13 0.15 0.83 0.41 Moss Cover Intercept 3.43 0.10 35.62 0.00 Moss Cover -0.44 0.11 -4.06 0.00 Bare Ground Intercept 3.49 0.13 26.00 0.00 Bare Ground 0.23 0.14 1.68 0.09 Coarse Woody Debris Volume Intercept 3.50 0.14 24.69 0.00 Coarse Woody Debris Volume -0.22 0.15 -1.43 0.15 Shrub Cover Intercept 3.51 0.15 23.92 0.00 Shrub Cover -0.12 0.15 -0.77 0.44 Sapling Density Intercept 3.51 0.15 23.47 0.00 Sapling Density 0.01 0.16 0.07 0.94 Southern red-backed vole Live Trees Intercept 2.35 0.20 11.79 0.00 Live Trees 0.47 0.20 2.33 0.02 Grass Cover Intercept 2.42 0.22 10.76 0.00 Grass Cover -0.21 0.23 -0.91 0.36 Forb Cover Intercept 2.43 0.23 10.68 0.00 Forb Cover 0.14 0.23 0.60 0.55 Moss Cover Intercept 2.41 0.22 10.89 0.00 Moss Cover 0.25 0.23 1.10 0.27 Bare Ground Intercept 2.39 0.22 11.11 0.00 Bare Ground -0.33 0.23 -1.44 0.15 Coarse Woody Debris Volume Intercept 2.42 0.23 10.72 0.00 Coarse Woody Debris Volume -0.14 0.24 -0.59 0.55 Shrub Cover Intercept 2.42 0.22 10.80 0.00 Shrub Cover 0.20 0.23 0.87 0.38 Sapling Density Intercept 2.43 0.23 10.60 0.00 Sapling Density -0.11 0.24 -0.47 0.64 42 Figure 2.1 Chilcotin study area and location of small mammal live-trappings grids and habitat types. 43 Figure 2.2 Mean density and standard deviations of estimates of A) deermice and B) southern red-backed voles by habitat type during 2019, and C) deermice by habitat type during 2018. Session 1 refers to the early-summer session, session 2 is mid-summer session, and session 3 is late-summer session. There were not enough voles captured in 2019 in the 2010 burn + salvage-logged sites or in all sites in 2018 to estimate densities. There were not enough deermice captured in mature forest sites in 2018 to estimate densities. 44 Figure 2.3 A) Adult deermouse mass and densities from 2018 and 2019 and B) adult southern red-backed vole mass and densities from 2019 across all habitat types, grids, and sessions. When the correlation of measures within the same habitat type, grid, and session were taken into account through a generalized linear mixed effects model, the estimated effect of density on deermouse mass was -0.08 (S.E. = 0.01, t = -7.35, lower 95% C.I. = -0.11, upper 95% C.I. = -0.06), and the estimated effect of density on southern red-backed vole mass was 0.03 (S.E. = 0.03, t = 0.96, lower 95% C.I. = -0.03, upper 95% C.I. = 0.09).45 Figure 2.4 The proportion of tagged adults, juveniles, and reproductive adults of A) deermice and B) southern red-backed voles by both year and habitat. Individuals are totaled across all sessions and all grids for each habitat type. No southern red-backed voles were captured in 2010 burn + salvage-logged sites or 2017 burn sites in 2018. 46 Figure 2.3 A) Deermice and southern red-backed vole total individuals captured during the mid-summer session in relation to live tree basal area. B) deermice total individuals captured in relation to moss during the mid-summer session of 2019. Total individuals from the mid-summer session only were used to match seasonal timing of vegetation surveys, and to avoid repeating models with multiple mouse or vole totals, but only one vegetation dataset. 47 Figure 2.4 The effect of disturbance on the abundances of deermice and southern-red-backed voles. Data of the effect of fire and post-fire salvage logging are effects on abundances from both years of my research in the Chilcotin. Data of the effect of clearcutting is from 17 publications and comes from abundance estimates at least 2 years after clearcutting occurred (Borgne et al. 2018a, b, Darmon et al. 2013, Fauteux et al. 2012, Klenner and Sullivan 2009, Lemaître et al. 2010, Moses and Boutin 2001, Pearce and Venier 2005, Potvin et al. 1999, Ransome et al. 2009, Sullivan and Sullivan 2001, 2008, 2011, 2016, 2018a, 2019, 2020). The degree of effect on abundance plotted is an estimated mean ratio of the change in abundance from either before and after the disturbance, or in disturbed areas compared to mature forest.48 Chapter 3 Post-fire salvage logging reduces snowshoe hare and red squirrel presence in early seral stages 3.1 Background Wildfire is a natural disturbance that drives the evolution and function of fire-prone ecosystems globally (Bond and Keeley 2005). Plants and wildlife have adapted to the fire regimes specific to their systems around the world, including the Mediterranean, Australia, and North America (Berry et al. 2015, Fernandez-Garcia et al. 2020). Species recolonize burns by surviving and dispersing from fire refugia, areas that burn at low severities or do not burn at all (Berry et al. 2015, Meigs and Krawchuk 2018). Understanding how quickly wildlife species recolonize diverse post-fire stands is important for basic ecological understanding of habitat needs and post-fire forest management (Banks et al. 2011, Friend 1993, Volkmann et al. 2020, Zwolak 2009). Western forests in North America are shaped by wildfire (Agee 2000, Bond and Keeley 2005, Schmiegelow et al. 2006). In western forests, low to moderate severity fire has historically created mosaics of seral stages (Agee 2000). Following wildfire, open stands and regenerating forests provide habitat for many mammals and their predators (Bull et al. 2001, Fisher and Wilkinson 2005, Hutchen et al. 2019, Nappi et al. 2004, Volkmann et al. 2020). However, anthropogenic fire suppression and climate change are shifting the natural fire regime of western forests towards larger, more frequent, and higher severity fires (Agee 1993, Westerling et al. 2006). While wildfire is a natural disturbance and increases habitat function and biodiversity, it can be detrimental to the forestry industry because it reduces the amount and value of timber available for harvest (Bergeron et al. 2004, Schmiegelow et al. 2006, Thom and Seidl 2016). In British Columbia, Canada, post-fire salvage logging is used to help mitigate economic losses 49 following wildfire (Eng 2004, Saint-Germain and Greene 2009). However, the compounded effects of wildfire and post-fire salvage logging on wildlife are largely unknown. Salvage logging may compromise the ability of wildfire to act as a crucial, ecosystem-shaping natural process (Schmiegelow et al. 2006) by decreasing forest biodiversity and changing ecological processes through the removal of standing and downed trees, which are biological legacies naturally left on the landscape following fire (Gayton and Lara Almuedo 2012, Lindenmayer and Noss 2006). Many forest management approaches seek to replicate natural disturbances and ecosystem function in silvicultural practices, often aiming to replicate impacts of wildfire during timber harvest (Bergeron et al. 2007, Delong and Tanner 1996). Harvesters attempt to replicate the effects of wildfire by reducing the size of cutblocks and retaining stands of trees within cutblocks (Bergeron et al. 2007). However, post-fire salvage logging practices can often differ from these guidelines (Thorn et al. 2018). Salvage logging is often done urgently as harvesters attempt to get salvaged timber to market quickly before the wood deteriorates (Müller et al. 2018). As natural disturbances like wildfire are often seen as damaging events that hurt forests, salvage logging is done at larger scales and intensities than standard harvest (Lindenmayer and Noss 2006, Müller et al. 2018, Noss and Lindenmayer 2006). With the combination of global climate trends and a legacy of fire suppression in North America, wildfires are expected to increase in severity and prevalence (Loehman et al. 2017, Miller et al. 2009, Prichard et al. 2017, Westerling et al. 2006). An increase in wildfires may lead to an increase in post-fire salvage logging in British Columbia (BC) as forestry companies compete with fire for timber resources. If large-scale post-fire salvage logging following wildfire continues as wildfire occurrence increases, the landscapes of British Columbia forests could be 50 drastically changed by these compounded disturbances. Because the impacts of salvage logging vary between ecosystems, there are no standards of salvage logging that can be widely applied, and it should be studied in all systems it impacts (Lindenmayer and Noss 2006). I examined the impact of wildfire and post-fire salvage logging on two important species, snowshoe hares (Lepus americanus) and red squirrels (Tamiasciurus hudsonicus) in BC interior Douglas fir (Psuedotsuga menziesii) forest. 3.1.1 Snowshoe hare response to forest disturbance Snowshoe hares are an abundant and primary prey species in forest ecosystems for many predators across western Canada (Hodges 2000, Krebs et al. 2017). They are preyed on by marten (Martes americana), fisher, lynx (Lynx canadensis), bobcats (Lynx rufus), goshawks (Accipiter gentilis), great horned owls (Bubo virginianus), and coyotes (Canis latrans), and predation is the leading cause of snowshoe hare mortality (Hodges 2000, Hodges et al. 2001, Koehler 1990). To avoid predation, hares select stands based on vegetation cover (Hodges 2000, 2009, Thomas et al. 2019) where they consume shrubs, forbs, and conifer twigs (Hodges 2000). Snowshoe hares avoid open areas like clearcut stands or stands dominated by young regrowth, even if those stands provide food, opting for stands that provide cover from predators (Ferron et al. 1998, Hodges 2000, Thomas et al. 2019). Immediately following clearcut logging, hares increase their home ranges size and sometimes completely relocate their home range to find habitats similar to the habitat they used prior to clearcutting (Ferron et al. 1998). Snowshoe hares require vegetation cover, so their populations decrease immediately following fire (Hodges et al. 2009), clearcut logging (Potvin et al. 1999, Thornton et al. 2012), and after salvage logging following insect outbreaks (Thomas et al. 2019). Hares recolonize stands when shrubs and saplings regrow densely. Early-mid seral stands are valuable hare habitat 51 and provide browsing and cover with understory regrowth of saplings and shrubs (Fisher and Wilkinson 2005, Hodson et al. 2011, Newbury and Simon 2005, Thornton et al. 2012). Hare recolonization times of these regenerating stands vary by forest system (Allard-Duchene et al. 2014, Hodges et al 2007, Cheng et al. 2015). In eastern Canadian boreal forests, Allard-Duchene et al. (2014) found hare browsing intensity to be equally high in both 50-60-year-old fire-origin and logging-origin stands. The similar browsing intensity between stand types is likely because this stand age had the highest density of vertical and horizontal vegetation cover in eastern forests (Hodson et al. 2011). In western lodgepole pine (Pinus contorta) forests, the browsing peak is often around 15-30 years following fire (Hodges 2000, Koehler 1990). Similarly, hare pellet counts were highest in 15-40-year-old clearcut harvested stands in Idaho (Thornton et al. 2012). Browsing intensity and hare density generally peak with maximum sapling and shrub cover in early to mid-seral stands (Allard-Duchene et al. 2014, Hodson 2011, Koehler 1990) regardless of stand origin. As forests reach mature to old growth stages of development, sapling and shrub cover decrease, so these mature forests support lower snowshoe hare densities than early regenerating forests (Hodson 2011, Strong and Jung 2012). As stands age and mature trees fall, openings in the overstory canopy allow for shrub and sapling growth, which creates suitable habitat to support hares at low-medium densities (Hodges et al. 2009, Hodson et al. 2011). While snowshoe hares are well-studied in forest ecosystems (Cheng et al. 2015, Hodges et al. 2009, Hutchen et al. 2017), there are few studies that examine snowshoe hare responses to wildfire (Hodges et al 2009, Hutchen and Hodges 2019, Olnes et al. 2019, Strong and Jung 2012). Furthermore, most research on snowshoe hare response to disturbance focuses on older regenerating stands, often starting 20 years or more after the disturbance (Allard-Duchene et al. 52 2014, Hodson et al. 2011, Koehler 1990, but see Newbury and Simon 2005). While it is important to understand wildlife habitat use as forests regenerate, there is little research on wildlife response to wildfires in very early post-fire years (Hutchen et al. 2017), or in response to salvage logging. 3.1.2 Red squirrel resonse to forest disturbance Red squirrels are also important prey for many predators, including marten (Seip et al. 2018) and lynx (Roth et al. 2007). They also influence seed dispersal through seed consumption (Fogel and Trappe 1978). Red squirrels depend on mature forest stands with large trees that provide escape cover, nesting sites, and food (Fisher and Wilkinson 2005, Haughland and Larsen 2004). They are closely linked to understory structural diversity, downed woody debris, and canopy cover (Russell et al. 2010), as well as large trees and snags (Holloway and Malcolm 2006). Red squirrels depend on conifer seeds for food and build middens of conifer cones in autumn to store food (Gurnell 1984, Kemp and Keith 1970, Rusch and Reeder 1978). Red squirrels defend territories ranging from 0.5-3 ha (Gurnell 1984, Kemp and Keith 1970). Each territory is often centered around one large midden, but one squirrel’s territory can include multiple middens (Rusch and Reeder 1978). Red squirrels use microhabitat structures, such as coarse woody debris and patches of high shrub density, to move rapidly without being detected by predators (Bakker 2006). Red squirrels avoid clearcut stands because of the lack of trees but may use coarse woody debris corridors to cross them during winter (Seip et al. 2018). Red squirrel abundance decreases immediately following severe fire or clearcut logging (Allard-Duchene et al. 2014, Fisher and Wilkinson 2005, Fisher et al. 2005, Fisher and Bradbury 2006) and recolonization rates vary with disturbance and forest type. In eastern Canadian forests, abundance of red squirrels peaked at 40 years post-cutting on clearcut sites, while peak 53 abundance occurred 60 years post-fire (Allard-Duchene et al. 2014). Following prescribed burns in mixed conifer forests in Washington and Idaho, low severity fire had little impact on squirrel populations, and squirrel density increased with an increase in live trees, downed logs, and shrub cover (Russell et al. 2010). The objective of this research was to determine the impacts of wildfire and post-fire salvage logging on these important prey species in BC forests. My hypotheses were: 1) density of snowshoe hares and red squirrels would be highest in mature forest and older regenerating post-fire forests, and salvage-logged areas would support no hares or squirrels, and 2) snowshoe hare and red squirrels would be present in habitats with sufficient vegetation cover, and would avoid open areas that lacked cover. 3.2 Methods The study area was ~ 32,000 hectares on the eastern edge of the Chilcotin Plateau, BC. It was 30 km southwest of Williams Lake on Department of National Defense and adjacent Crown land. The forest is dominated by interior Douglas fir, with some Engelmann spruce (Picea engelmannii), lodgepole pine (Pinus contorta), and trembling aspen (Populus tremuloides) in a mosaic of seral stages. There are grasslands and some wetlands. Much of the area is maintained by the Department of National Defense as military training grounds. There are several local ranches and cattle are ranged over the entire study area, impacting all habitats. The forest is managed for harvest and logging is the dominant disturbance on the landscape. Recently, this area has been impacted by large wildfires and post-fire salvage logging. In 2010, The Meldrum Creek Fire Complex burned 47,293 ha of forested area, and roughly 70% of the burned area was salvage-logged. In 2017, 241,160 ha burned in the Hanceville Fire (BC Wildfire Service 2019), burning about 12,000 ha in the southwestern corner of the study area. 54 The Hanceville fire provided a unique opportunity to study the impacts of a wildfire almost immediately post-fire, something rarely achieved in small-mammal research (Hutchen et al. 2017, Hodges et al. 2009). The close proximity of the Hanceville burn to the Meldrum Creek burn allowed me to compare different burn ages and salvage-logged areas in close proximity. 3.2.1 Snowshoe hare surveys I counted fecal pellets of snowshoe hares as an index of hare abundance. Fecal pellet count methods are strongly linked to estimated snowshoe hare abundances from mark-recapture (Hodges and Mills 2008, Krebs et al. 1987, 2001, Mills et al. 2005), making them a reliable survey method. For snowshoe hare pellet surveys, I selected 20 ha (400 m x 500 m) plots of each habitat of interest using ArcGIS (ESRI 2020). I established seven 2010 burn + salvage-logged sites, eight mature, unburned sites, six 2010 burn sites, and five 2017 burn sites (Figure 3.1). I used ArcGIS (ESRI 2020) to randomly place 80 small rectangular pellet plots (5.08 cm x 305 cm, 2 in. x 10 ft. Krebs et al. 1987) within each 20-ha plot. I then created an efficient walking path between all plots using ArcGIS. In the field, I used a handheld global position system (GPS) to navigate to each random selected plot coordinate in the order I had previously established. I marked plots with a large nail and used a string to measure 10 ft in a pre-determined random orientation to set the plot. Within each plot, I counted all whole pellets at least halfway in the plot. 3.2.2 Red squirrel surveys I conducted red squirrel surveys from August through October 2018 and May through August 2019. I set two 500 m long belt transects in each 20-ha site surveyed for hares. The transects were set 100 m in from the edge of the plot, with 200 m between them. Each transect 55 was 20 m wide, for a total of two hectares surveyed for each site. I walked each transect and looked for middens and listened for red squirrels (Mattson and Reinhart 1996). I counted cone piles as middens when they had at least one tunnel entrance. I assumed equal detection probability between all sites. I surveyed six 2010 burn sites, four 2017 burn sites, seven mature forest sites, and seven 2010 burn + salvage-logged sites, for a total of 24 sites. 3.2.3 Vegetation surveys I conducted vegetation surveys to quantify important habitat attributes for hares and squirrels in each habitat type. I selected 25 random and non-overlapping hare pellet plots per site to survey. Vegetation survey plots were at least 30 m apart. I surveyed ground cover by estimating percentage of each of four categories: bare ground and rocks; grass; forbs; and moss and lichen. Ground cover was estimated in a two m radius circle centered on the survey point. I estimated shrub cover by recording the percentage of area each shrub family covered within a two m radius circle. Total shrub cover could be over 100% because shrubs overlapped one another. I estimated canopy cover using a densiometer and taking one reading in each cardinal direction centered on the survey point. I estimated coarse woody debris along a 15 m transect. I measured all coarse woody debris over 7.5 cm in diameter the transect crossed. I measured trees and snags in a circular 15 m fixed radius plot. I recorded species and diameter at breast height (DBH) of all live trees and snags greater than 7.5 cm DBH. 3.2.4 Statistical analysis To calculate coarse woody debris volume estimates, I used the following formula: [1] 𝑉 =𝑘𝑎𝑐𝐿∑ 𝑑𝑖2𝑛𝑖=1 56 where V is the coarse woody debris volume in m2/ ha, k is the unit conversion constant 1.234, a is the lean angle correction factor, c is the slope correction factor, L is the total survey transect length in m, and d is the coarse woody debris diameter at the transect (Woodall and Williams 2007). I set both a and c to one. To estimate relative abundance of hares from pellet counts, I used the following log-log regression equation from Krebs et al. (2001): [2] ] 𝑙𝑜𝑔𝑒(𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑑𝑒𝑛𝑠𝑖𝑡𝑦) = -1.203 + 0.889 𝑙𝑜𝑔𝑒 (𝑚𝑒𝑎𝑛 𝑛𝑜. 𝑜𝑓 𝑝𝑒𝑙𝑙𝑒𝑡𝑠) I used a one-way ANOVA to compare average pellet counts per site among all habitat types. I compared total midden counts between habitat types using one-way ANOVA. I used linear regressions to relate average midden counts and average live tree density and coarse woody debris volume. I did not model the effects of other habitat features on midden density because of the low sample size of sites and low midden densities. I used a generalized logistic mixed model to determine the relationship between habitat and pellet presence. Because hare pellets are an index of hare abundance, and not an actual count of hares, I used pellet presence or absence to build the models. To estimate the pellet by habitat interaction, I included survey site in the model as a random effect nested within habitat type, the fixed effect. This approach helped control for correlation between repeated measures of pellets at the plot level in different sites within the same habitat type. The generalized linear mixed model structure allowed for flexibility within the model, as the number of site replications in each habitat type was not equal, and the study design was nested (i.e. sites within habitat types; Bolker et al. 2008). 57 After analyzing hare abundances across habitat types, I then examined which habitat features were associated with hare presence. I used a Pearson correlation matrix to determine correlations between vegetation attributes. I considered everything with a correlation coefficient of |0.4| or greater to be correlated, a common threshold below |0.7| as suggested by Dorman et al. (2013). The correlation coefficient between tree density and canopy closure estimates was 0.71. I excluded canopy closure because tree density is measured more accurately in the field. I also excluded bare ground cover estimates and moss cover estimates, as they were significantly negatively correlated with grass cover estimates (PCC = - 0.5 and -0.46, respectively), and do not provide cover or browse for hares. I used a one-way ANOVA and Tukey’s HSD post-hoc test to compare total tree density, live tree density, shrub cover, sapling density, coarse woody debris volume, grass cover, and forb cover between habitat types. I then used a generalized logistic mixed effects model structure to model vegetation attributes to determine the specific vegetation structures that drove hare pellet response within habitat types. I included vegetation attributes as the fixed effects and habitat type and sample site as random effects to account for repeated measures in the same site, and repeated sites in the same habitat type. Total shrub cover, grass cover, forb cover, sapling density, trees per hectare, and coarse woody debris volume were all modeled as fixed effects. All predictive vegetation attributes were scaled before analysis by subtracting the attribute’s mean and dividing by the standard deviation. I modelled each vegetation attribute alone to understand the strength of its estimated effect on hare pellet presence. I also constructed models of combinations of vegetation attributes to understand their influence on hare pellet presence. I chose combinations based on the vegetation attributes’ structural position in the habitat. For example, I used combinations of tree density, mid-level cover like saplings and shrubs, and ground cover, either grass or forbs. I 58 used Akaike’s Information Criterion adjusted for small sample sizes (AICc; Burnham and Anderson 2004) to assess 16 vegetation models for hare correlation with hare pellet presence and to select the strongest models. I used RStudio version 3.5.1 for all analyses and used the MuMin package for multimodel comparisons. 3.3 Results 3.3.1 Snowshoe hares Mean pellet counts per site ranged from 0 to 1.55 ± 5.79 (mean ± S.D., Table 3.1). Mean pellet counts were highest in 2010 burn stands (0.90 ± 2.90) – significantly higher than in 2010 burn + salvage sites (0.01 ± 0.15; F3,22 = 4.69, p = 0.02). Hare densities were low in mature forest (0.35 ± 1.04 hares/ha, Appendix x). Hares were mostly absent in 2017 burn and 2010 burn + salvage sites (average densities 0.08 ± 5.9 and 0.01 ± 12.79 hares/ha, respectively). The highest hare densities were in 2010 burn sites, although hare densities were still low with an average density of 0.43 ± 0.31 hares/ha. All mature forest and 2010 burn sites had hares, 57.8% of 2010 burn + salvage-logged sites and 80.0% of 2017 burn sites had hares. Habitat type was a strong predictor of hare pellet presence (Table 3.2). Specifically, a change in habitat type from mature forest to 2017 burn or 2010 burn + salvage decreased the likelihood of hare pellet presence in any given plot (Figure 3.2). 3.3.2 Vegetation as predictors of hare habitat use Wildfire and post-fire salvage logging resulted in significant changes to habitat structure. Tree density per hectare was highest in mature forest, followed by 2017 burn, then 2010 burn, and lastly 2010 burn + salvage-logged (Table 3.4). Live tree density was highest in mature forest, followed by 2010 burn, 2017 burn, and lastly 2010 burn + salvage-logged sites. Grass cover 59 differed significantly among all habitat types and was highest in 2010 burn sites (mean ± S.D., 53.4 ± 20.67), followed by 2010 burn + salvage logged sites (45.5 ± 19.60), then mature sites (34.2 ± 24.55), then 2017 burn (26.0 ± 20.47, Table 3.4). Sapling densities per ha were significantly higher in 2010 burn + salvage sites than any other habitat type (3932.34 ± 4342.12; F3,642 = 17.06, p = 0.00). Sapling densities did not differ significantly between 2010 burn (2673.80 ± 2675.72) and mature unburned sites (2542.50 ± 4036.20; F3,642 = 17.06, p = 0.98), but 2017 burn sites (1044.06 ± 842.02) had significantly lower sapling densities than any other habitat type (F3,642 = 17.06, p = 0.00). Shrub cover was significantly different between all habitat types except 2010 burn and 2010 burn + salvage-logged sites (p = 0.86), and was highest in 2017 burn sites and lowest in mature forest sites (Table 3.4). Tree density per hectare was significantly positively correlated with pellet presence across all sites (LL = -211.6, p = 0.01). When trees were divided into live and standing dead trees, only live trees were significantly positively correlated with pellet presence, so I used live canopy tree density as the predictive parameter for all tree models (LL = -210.2, p = 0.00). Live canopy tree density + grass cover was the best predictive model of hare pellet presence with a weight of 0.37 (Table 3.3). Live canopy tree density + saplings + grass cover was the next best predictive model, and accounted for both canopy, mid-level, and ground cover vegetation parameters. Three additional models were within ΔAICc of 2.5 of the top two models, with model weight of 0.09 - 0.10. These additional models also included combinations of live canopy tree density, grass cover, and shrub cover. Of all the top vegetation parameters identified in the models, live canopy tree density consistently had the strongest effect and was positively correlated with pellet presence (Table 3.4). Sapling density had a weak positive effect, and shrub and grass cover both had negative correlations with pellet presence. 60 3.3.3 Red squirrels Red squirrel midden counts decreased following wildfire and post-fire salvage logging. Midden densities in 2010 burn + salvage-logged stands were significantly lower than in mature stands (F3,20 = 4.044, p = 0.02). Midden densities did not differ significantly between any other habitat types. Mature forest had an average of 5.1 ± 5.0 middens per site, 2010 burn sites had a mean (± S.D.) of 2.5 ± 2.7 middens per site, and both 2017 burn and 2010 burn + salvage-logged had 0 middens per site (Figure 3.2). There were two squirrel sightings and one squirrel call recorded within the belt transects, and both sightings and call detection occurred in mature forest sites. Midden counts were positively correlated with live canopy tree density (R2 = 0.23, F1,21 = 6.428, p = 0.02) (Figure 3.3). Midden counts had no correlation with coarse woody debris volume. 3.4 Discussion 3.4.1 Impacts of wildfire on snowshoe hares and red squirrels Snowshoe hare and red squirrel densities were highest in mature and 2010 burn sites, confirming my predictions (Figures 3.2 and 3.3). Snowshoe hare density decreased immediately following wildfire, but populations increased in post-fire stands as the forest regenerated to provide more vegetation cover (Table 3.1). Hares were mostly absent from post-fire salvage-logged areas. Red squirrel presence was reduced by wildfire, and post-fire salvage-logging rendered sites unsuitable for red squirrels. Both red squirrels and hares selected sites with sufficient live canopy tree cover. Red squirrel midden counts were highest in mature unburned forest but were also present in 2010 burned forests with residual live canopy trees. 61 Although hare densities were low overall, densities were higher in the regenerating 2010 burn stands than in any other habitat type surveyed. This increase in hare density in regenerating stands is consistent with other findings, as older regenerating burns support more hares than younger burns (Hodges et al. 2009). These regenerating stands provided sufficient canopy tree densities for cover from predation, as well as shrubs and saplings for browsing. In contrast, snowshoe hares were scarce in 2017 burn stands, likely due to lack of live canopy tree cover immediately following fire. Unburned mature forests had less browse, with a more open understory than 2010 burn stands. Mature stands did not provide as much mid-story vegetation cover as did regenerating post-fire stands, and hence they supported fewer hares. However, mature forest stands had the highest live canopy tree density of all habitat types, providing enough cover to support low densities of hares. Both ages of post-fire regenerating forest (one-two year and eight-nine year) had lower midden counts than mature forest sites. However, eight-nine year post-fire regenerating sites supported some squirrels, suggesting red squirrels can recolonize stands soon after fire, given enough residual live canopy trees. This result is similar to other studies suggesting fire severity and time since fire are important factors in squirrel response to fire (Koprowski et al. 2006). Russell et al. (2010) found red squirrel populations were unaffected by low-severity prescribed surface fire that retained canopy and live trees. Similarly, in the Chilcotin, eight-nine year post-fire sites had higher shrub cover and live tree density than one-two year post-fire sites and provided better squirrel habitat. 3.4.2 Impacts of post-fire slavage logging on snowshoe hares and red squirrels Post-fire salvage logging greatly changed the habitat structure of post-fire stands, removing vegetation cover and rendering those sites unsuitable habitat for hares and red 62 squirrels. Post-fire salvage-logged areas supported no hares or red squirrels eight to nine years following the initial wildfire, while un-harvested post-fire stands had recovered to low densities of hares and red squirrels by that time. Thus, post-fire salvage logging appears to delay snowshoe hare and red squirrel recolonization following wildfire by at least nine years. Snowshoe hares defecate while foraging (Hodges 1999), so the plots I sampled that had pellets reflect choices made by active hares. Hares selected foraging sites that had nearby lateral cover and overstory structure, echoing results from elsewhere in their geographic range (Hodges and Sinclair 2005, Hodges et al. 2014, Hutchen and Hodges 2019a). These consistent choices by foraging hares help explain why salvage-logged stands are not used by hares; the loss of cover makes such habitats unsuitable. In contrast, stands that are burned retain more heterogeneity of lateral and vertical cover, and hence become available habitat for foraging hares far more quickly post-disturbance. In the Chilcotin study area, all 2010 burn and mature forest sites had hare pellets, while only 57.8% of 2010 burn + salvage-logged sites and 80.0% of 2017 burn sites had hare pellets. Furthermore, those 2010 burn + salvage-logged sites and 2017 burn sites with pellets tended to have pellets in very few plots per site. This discrepancy in number of plots with pellets indicates that hares were foraging in post-fire regenerating and mature forests and may have been moving through the post-fire salvage-logged and one-two-year-old post-fire sites to find more suitable heterogeneous habitats (Hutchen and Hodges 2019a). Regenerating forests provide high quality habitat for snowshoe hares (Allard-Duchene et al. 2014, Hodson et al. 2011, Koehler 1990). In the Chilcotin study area, live canopy trees provide cover from predators and are the most important habitat attribute driving snowshoe hare habitat selection. Post-fire salvage logging removed standing live and dead trees from 63 regenerating post-fire stands, replacing the valuable regenerating forest with large clearcut areas unsuitable for hares. Snowshoe hares likely did not select open salvage-logged areas stands because of the lack of live canopy tree cover to shelter them from predators, despite the saplings these stands provided. Interestingly, shrub cover was negatively correlated with hare pellet presence, despite evidence suggesting high shrub and other mid-story cover can be important to hare habitat selection in other forest types (Cheng et al. 2015, Hodson et al. 2011). Sapling density was only a predictor of hare pellet presence when modelled with live canopy trees, and in this system did not provide sufficient cover for hares without overstory cover. The relative unimportance of saplings in this system contrasts with lodepole pine (Pinus contorta) forests, where sapling regrowth is often very dense and saplings are a major predictor of hares (Hodges et al. 2009, Cheng et al. 2015, Hutchen and Hodges 2019b). This discrepancy in response to vegetation suggests hares select different vegetation attributes dependent on forest type and highlights the importance of studying the impacts of forest disturbances on wildlife in many forest ecosystems. Red squirrel populations were negatively impacted by salvage logging. Red squirrels depend on understory structural diversity, coarse woody debris, and canopy cover (Haughland and Larsen 2004, Russell et al. 2010), habitat attributes removed by post-fire salvage logging. Red squirrels also depend on tree seeds for food (Rusch and Reeder 1978), making live, seed producing trees an important habitat attribute. Salvage logging removed nearly all trees, leaving the habitat unsuitable for red squirrels, as squirrels were not present in 2010 burn + salvage-logged stands but did use the 2010 burn stands. Red squirrels may be able to use residual forest habitats following disturbance, potentially helping to mitigate the impacts of overall habitat loss due to salvage logging. However, small residual strips may not be enough to support functional 64 populations (Chavel et al. 2017, Potvin and Bertrand 2004), whereas leaving larger residual blocks would likely have a positive impact on squirrels. 3.4.3 Wildfire and post-fire salvage logging in British Columbia In 2017, BC experienced the largest wildfire season to date in provincial history, with many large, high-severity fires (BC Wildfire Service 2019). One of the largest wildfires was the 240,000 ha Hanceville fire on the Chilcotin Plateau (BC Wildfire Service 2019). In 2018, 1.3 million hectares of land burned, breaking the record set by the 2017 fire season (BC Wildfire Service 2019). After the record-setting fire season of 2017, British Columbia Ministry of Forests, Lands, Natural Resource Operations and Rural Development (BC FLRORD) developed a post-fire forest retention guide, which stated that protecting and promoting wildlife habitat was a priority (BC FLRORD 2018). The Forest Practices Board expressed concern that unplanned post-fire salvage logging following the 2017 wildfire season would put too much pressure on an already struggling forest ecosystem (Forest Practices Board 2018). Despite this report, large-scale salvage logging in the Hanceville burn on the Chilcotin Plateau began in spring 2018. Salvage logging is often done at a larger scale than standard logging, with more trees harvested over larger areas (Lindenmayer and Noss 2006, van Nieuwstadt et al. 2001), and post-fire salvage logging in the Chilcotin followed this trend. Such large operations removed biological legacies following wildfire. Unburned fire refugia play an important role in a healthy mosaic of post-fire habitats by facilitating regeneration of nearby burned areas and protecting vegetation and wildlife during future fires (Meigs and Krawchuk 2018). The large scale of salvage operations in the Chilcotin left little post-fire habitat and rendered large areas unsuitable for snowshoe hares and red squirrels. Post-fire salvage logging delayed snowshoe hare and red squirrel 65 recolonization following wildfire. Removing regenerating post-fire stands removes important prey species, threatening forest ecosystem health, and likely risking the loss of the predators that depend on these species. 66 Table 3.1 Vegetation attributes and hare pellets by habitat type. Grass, shrub, and forb cover were measured in 2 m radius circular plots. Superscript letters represent results of Tukey HSD post-hoc test. Habitat types sharing letters did not differ significantly. Mature 2010 Burn 2017 Burn 2010 Burn + Salvage-logged x̄ ± SD x̄ ± SD x̄ ± SD x̄ ± SD F p Hare Pellets 0.71 ± 2.00 a, c 0.90 ± 2.90 a, b 0.14 ± 0.84 a, c 0.01 ± 0.15 c 4.69 0.011 Tree Density / ha 869.7 ± 404.92 a 466.7 ± 356.09 b 792.7 ± 509.68 a 11.9 ± 55.31 c 195.6 < 0.001 Live Tree Density / ha 901.5 ± 400.40 a 344.4 ± 302.57 b 239.5 ± 425.91 c 1.0 ± 12.98 d 255.2 < 0.001 Coarse Woody Debris Volume (m3/ha) 78.68 ± 130.10 a 68.94 ± 93.24 a, b 41.94 ± 76.01 b 146.25 ± 145.25 c 21.8 < 0.001 Grass Cover (%) 34.2 ± 24.55 a 53.4 ± 20.67 b 26.0 ± 20.47 c 45.5 ± 19.60 d 45.04 < 0.001 Shrub Cover (%) 28.2 ± 30.25 a 40.3 ± 17.41b 61.4 ± 25.56 c 38.0 ± 26.10 b 43.28 < 0.001 Forb Cover (%) 13.9 ± 12.82 a 17.6 ± 11.49 a 23.6 ± 17.21 b 16.3 ± 12.28 a 14.00 < 0.001 Sapling Density / ha 2542.50 ± 4036.20 a 2673.80 ± 2675.72 a 1044.06 ± 842.02 b 3932.34 ± 4342.12 c 17.06 < 0.001 67 Table 3.2 Logistic mixed effect models predicting pellet presence with both habitat and vegetation fixed effects. Statistics are for fixed effects and the random effect of Site for all models. All habitat types were compared against mature forest as the control. Fixed Effect Estimate Lower 95% C.I. Upper 95% C.I. Standard Error Z value (Wald’s) P 2010 Burn 0.03 -1.11 1.19 0.55 0.06 0.95 2010 Burn + Salvage-logged -3.67 -5.17 -2.35 0.69 -5.29 0.00 2017 Burn -1.92 -3.29 -0.66 0.64 -3.02 0.00 Table 3.3 AICc ranking of vegetation mixed effects models predicting presence of snowshoe hare pellets in sites and habitat types. Candidate Models k Log Likelihood AICc ΔAICc Weight Live Trees + Grass Cover 5 -208.08 426.25 0.31 Live Trees + Saplings + Grass Cover 6 -207.73 427.6 1.35 0.16 Live Trees 4 -210.22 428.5 2.25 0.10 Live Trees + Shrub Cover 5 -209.31 428.7 2.47 0.09 Grass Cover 4 -210.34 428.7 2.49 0.09 Grass Cover + Shrub Cover 5 -209.68 429.5 3.21 0.06 Live Trees + Saplings 5 -209.95 430.0 3.74 0.05 Live Trees + Coarse Woody Debris Volume 5 -209.97 430.0 3.79 0.05 Live Trees + Forbs 5 -210.03 430.2 3.91 0.04 Grass Cover + Sapling 5 -210.06 430.2 3.97 0.04 Shrub Cover 4 -213.60 435.3 9.02 0.00 Forb Cover 4 -213.69 435.4 9.19 0.00 Shrub Cover + Forb Cover 5 -212.95 436.0 9.74 0.00 Saplings 4 -214.23 436.5 10.28 0.00 Coarse Woody Debris Volume 4 -214.32 436.7 10.46 0.00 Forb Cover + Saplings 5 -213.48 437.1 10.82 0.00 68 Table 3.4 Regression coefficients of the predictive vegetation parameters for the top five vegetation models. Vegetation Parameters Regression Coefficient S.E. Live Trees + Grass Cover Intercept -2.98 0.85 Live Trees 0.39 0.81 Grass Cover -0.32 0.15 Live Trees + Saplings + Grass Cover Intercept -2.99 0.86 Live Trees 0.40 0.18 Saplings 0.10 0.12 Grass Cover -0.33 0.15 Live Trees Intercept -2.94 0.80 Live Trees 0.51 0.17 Live Trees + Shrub Cover Intercept -2.98 0.79 Live Trees 0.52 0.17 Shrub Cover -0.24 0.18 Grass Cover Intercept -3.01 0.97 Grass Cover -0.42 0.15 69 Figure 3.1 The locations of the hare pellet survey sites in relation to habitat type on the Chilcotin Plateau, BC. 70 Figure 3.2 A) The proportion of fecal pellet plots with hare pellets in each site represented by small black dots. The average proportion of plots with pellets present for each habitat type is represented by a triangle. B) The mixed effects logistic regression model predictions of the probability of pellet presence given the habitat type. Standard error is from fixed effects (habitat type) only. 71 Figure 3.3 Total red squirrel midden counts by site and mean midden counts by habitat type. Mean midden counts by habitat type are represented by bold hollow diamonds. 72 Figure 3.4 Red squirrel midden counts in relation to live canopy tree density. The regression is positive (R2 = 0.23, F1,21 = 6.428, p = 0.02).73 Chapter 4 Conclusion My goal in this thesis was to determine how wildfire and extensive post-fire salvage logging impact small mammals, snowshoe hares, and red squirrels in BC forests. Wildfire and post-fire salvage logging have significantly altered the forested landscape of the Chilcotin Plateau, yet each disturbance had different impacts on small mammals, snowshoe hares, and red squirrels. While wildfire created mosaics of valuable regenerating forest that supported a diversity of small mammals, post-fire salvage logging changed this biological legacy by removing burned trees and changing habitat structure. Post-fire salvage-logged sites supported fewer species, and had lower populations of snowshoe hares, red squirrels, and vole species than post-fire regenerating stands or mature forests. In Chapter 2, I compared small mammal densities, demography, and body condition between post-fire forests, salvage-logged areas, and mature forests. I also surveyed vegetation in all treatment types and modelled vegetation attributes with small mammal capture totals to determine what vegetation attributes small mammals selected. I hypothesized that post-fire salvage-logged sites would have fewer small mammal species and would support mainly deermice with no vole populations, due to the drastic change in vegetation. These hypotheses were mostly supported. Unsurprisingly, post-fire salvage logging caused a significant shift in vegetation cover. The loss of trees over large areas made post-fire salvage-logged sites more open clearcut blocks than forest, and rendered them unsuitable for southern red-backed voles, a species strongly associated with mature forest conditions (Maser et al. 2008, Pearce and Venier 2005). Post-fire salvage-logged sites supported the highest densities of deermice in the study, supporting my hypothesis. 74 Early seral post-fire regenerating stands provided high quality habitat for southern red-backed voles and supported higher abundances than in mature forest sites, which I did not anticipate. Southern red-backed voles require sites with live tree cover and complex understory structure (Boonstra and Krebs 2012, Fauteux et al. 2012, Pearce and Venier 2005), and post-fire sites that were left standing following salvage logging provided enough tree cover to support vole populations. These low-severity post-fire areas would have provided refugia from which southern red-backed voles could recolonize more intensely burned areas, had the forest been left to regenerate. However, the intensity of post-fire salvage logging made these salvage-logged sites unsuitable for recolonization by southern red-backed voles 9 years post-fire. Post-fire salvage-logged sites were suitable only for deermice. Deermouse densities were highest in post-fire salvage-logged sites in comparison with mature forest and 8-9-year-old pos-fire regenerating areas. This relatively higher density of deermice is similar to results in other systems where deermice and European mouse species (Apodemus sylvaticus and Mus spretus) increased following post-fire salvage logging (Kronland and Restani 2011, Puig-Gironés et al. 2020). Moreover, the loss of specialist species and replacement by generalist species following post-fire salvage logging echoes a familiar pattern seen in forest ecosystems impacted by disturbances around the world (Clavel et al. 2011, Klenner and Sullivan 2009, Marvier et al. 2004, Pinotti et al. 2015, Püttker et al. 2019, Sullivan and Sullivan 2001). While I did not explore the mechanisms driving this trend beyond vegetation, competition with deermice in clearcuts has reduced southern red-backed vole abundances in other forests (Borgne et al. 2018a, Lemaître et al. 2010). Additional research that measured food availability and survival of small mammals in post-fire salvage-logged areas would help determine if intraspecific competition contributed to the shifts in abundances. 75 In Chapter 3, my objective was to use indices to determine snowshoe hare (Lepus americanus) and red squirrel (Tamiasciurus hudsonicus) densities and compare densities between post-fire salvage-logged sites, post-fire regenerating forests, and mature forests. I hypothesized that post-fire salvage-logged sites would support no red squirrels or snowshoe hares, and mature forests would support the highest densities of red squirrels and post-fire regenerating forest would have the highest densities of snowshoe hares. These hypotheses were supported. The lack of live canopy trees in post-fire salvage-logged sites almost certainly made the sites unusable for snowshoe hares and red squirrels, and post-fire salvage-logged sites had no red squirrels, and almost no snowshoe hares. Despite the high density of saplings in post-fire salvage-logged sites that offered mid-story cover, snowshoe hares and red squirrels did not use these sites. Instead, hares selected 8-9-year old postfire regenerating stands that provided both canopy tree cover and mid-story cover, and red squirrels used mainly mature forests. Post-fire regenerating stands also provided some habitat for red squirrels, although red squirrels did not use regenerating stands as heavily as mature forest. There was a noticeable difference in snowshoe hare, red squirrel, and southern red-backed vole densities between younger, more severe burns and older, lower-severity burns in the Chilcotin. Many of the sites surveyed following the 2017 Hanceville Fire were high severity burns that burned smaller trees, leaving an open understory and little surviving vegetation. The sites left behind after the salvage logging operations following the 2010 Meldrum Creek Fire were mostly low severity burns that provided more live tree and shrub cover. Time since fire and fire severity are important factors that determine how quickly wildlife recolonizes burned areas (Hodges et al. 2009, Hutchen and Hodges 2019b, Koprowski et al. 2006, Russell et al. 2010), and thus may explain the variation in wildlife abundances between fires and years in the 76 Chilcotin The mosaic of seral stages and fire severities left behind following wildfires influence wildlife populations and are a natural component of fire-prone forest ecosystems (Agee 2000). Salvage logging homogenizes post-fire landscapes and changes the natural regeneration of post-fire stands (Lindenmayer and Noss 2006, Thompson et al. 2007, Thorn et al. 2018). In the Chilcotin, this homogenization caused changes in small mammal diversity and abundances. While post-fire salvage-logged areas supported high densities of deermice, they supported very few other small mammals, and red squirrels and snowshoe hares were effectively extirpated from these sites. Shifts in abundance are important not only to the species experiencing the population change, but to the predators that depend on them. For some forest predators, the loss of habitat caused by post-fire salvage logging may be exacerbated by a loss of prey species, even if deermouse populations are high. For example, voles (Microtus and Myodes) are important prey for American marten (Martes americana), and marten are not present in habitats that do not provide sufficient vole abundances (Sullivan and Sullivan 2020, Volkmann 2020, in progress). Snowshoe hares, southern red-backed voles, and red squirrels are principle components of fisher (Pekania pennanti) diets, and a diversity of prey may help fisher populations remain stable through prey population fluctuations (Parsons et al. 2020, Weir et al. 2005). The densities of these small mammals were significantly reduced in post-fire salvage-logged sites in the Chilcotin. Many owl and raptor species also depend on small mammals as a prey source. The diet of the northern hawk owl (Surnia ulula) also depends on small mammals, with a large majority of their diet consisting of Microtus vole species, while deermice made up 1 percent of their diet (Larson et al. 2019). Northern hawk owls also hunt in early seral post-fire forests and depend on snags and cavities for nesting (Hannah and Hoyt 2004, Larson et al. 2019). The dependence of 77 this owl on post-fire forests makes the impacts of post-fire salvage logging observed in this study particularly concerning. These predators may all be negatively impacted by the shifts in small mammal abundances and loss of habitat following post-fire salvage logging. Post-fire salvage logging often occurs over larger areas than standard logging and can even impact forests that would otherwise be protected from harvest (Lindenmayer and Noss 2006, Müller et al. 2018). Salvage logging homogenizes forests and reduces biodiversity (Thompson et al. 2007, Thorn et al. 2018). In the Chilcotin, large post-fire salvage logging operations drastically decreased southern red-backed vole, snowshoe hare, and red squirrel densities. The loss of fire refugia to post-fire salvage logging and the reduction of populations of voles, hares, and squirrels may impact the ability of these species to recolonize following future disturbances (Berry et al. 2015, Meigs and Krawchuk 2018). The loss of important prey species from large areas of forest may have a ripple effect and decrease the abundances of the predators that depend on them. Repeated disturbances and habitat loss are reducing specialist species in systems around the world and contributing to the large-scale functional homogenization of ecosystems (Clavel et al. 2011). Large-scale salvage logging disturbances in the Chilcotin appear to be following this trend. Given BC’s recent severe wildfire years, with record-setting areas burned in 2017 and 2018, and the overall global trend of increasing fire size and severity due to climate change, I stress the importance of my findings to post-fire forest management (BC Wildfire Service 2019, Seidl et al. 2011, Hanes et al. 2019). Continuing intense post-fire salvage logging as wildfire occurrence increase has the potential to impact entire landscapes quickly. The importance of the decrease in small mammal species diversity and densities following disturbances becomes apparent when considering the scale of the disturbance. The fluctuation in small mammal and 78 mesomammal populations following small clearcut operations is well documented, yet populations of snowshoe hares, southern red-backed voles, and red squirrels recover as forest succession advances following standard logging practices (Allard-Duchene et al. 2014, Borgne et al. 2018a; 2018b, Klenner and Sullivan 2009, Martineau et al. 2016, Sullivan and Sullivan 2020). However, post-fire salvage logging can cover much larger areas than clearcut logging (Lindenmayer and Noss 2006, Müller et al. 2018), and can occur following wildfires in proximity, or even overlapping, as shown in the Chilcotin. Post-fire salvage logging occurring in quick succession in neighboring burns give forests little time to regenerate, small mammals, snowshoe hares, and red squirrels little time to recolonize, and few refugia for them to recolonize from. Repeating this pattern of severe wildfire and intense post-fire salvage logging builds the potential for widespread shifts in landscape-scale ecosystem function. Treating post-fire forests differently from unburned forests by logging more intensely over larger areas could lead to mismanagement of forests and increase the severity of future fires (Thomson et al. 2007). Moreover, 8-9-year-old post-fire regenerating forests that were not salvage-logged supported the highest densities of snowshoe hares, highest species diversity of mice and voles, and even supported low levels of red squirrels. This high species diversity and relatively high abundances suggest post-fire regenerating forest is important habitat for small mammals. Small mammals can also effect forest regeneration and tree species composition in turn through seed selection and consumption (Boone and Mortelliti 2019, Lobo et al. 2009, Maser 2008, Vander Wall 2010).Thus, forest managers should consider protecting post-fire regenerating forest to maintain wildlife habitat and ecosystem function. 79 References Adler, G.H. and M.L. Wilson. 1989. Demography of the meadow vole along a simple habitat gradient. Canadian Journal of Zoology 67:772-774. Agee, J.K. 1993. Fire ecology of Pacific Northwest forests. Island Press, Washington, D.C., USA. Agee, J.K. 2000. Disturbance ecology of North American boreal forests and associated northern mixed/subalpine forest. Pages 39-82 in Ecology and Conservation of Lynx in the United States, editors L.F. Ruggiero, K.B. Aubry, S.W. Buskirk, G.M. Koehler, C.J. Krebs, K.S. McKelvey, and J.R. Squires. University of Colorado Press, Boulder, USA. Albers, P.H., G. Linder, and D. Nichols. 1990. Effects of tillage practices and carbofuran exposure on small mammals. Journal of Wildlife Management 54:135-142. Allard-Duchene A., D. Pothier, A. Dupuch, and D. Fortin. 2014. Temporal changes in habitat use by snowshoe hares and red squirrels during post-fire and post-logging forest succession. Forest Ecology and Management 313:17-25. Anthony, N.M., C.A. Ribic, R. Bautz, and T. Garland. 2005. Comparative effectiveness of Longworth and Sherman live traps. Wildlife Society Bulletin 33:1018-1026. Bakker, V.J. 2006. Microhabitat features influence the movements of red squirrels (Tamiasciurus hudsonicus) on unfamiliar ground. Journal of Mammalogy 87:124-131. Banks, S.C., E.J. Knight, L. McBurney, D.B. Lindenmayer. 2011. The effects of wildfire on mortality and resources for an arboreal marsupial: resilience to fire events but susceptibility to fire regime change. PLoS ONE 6:e22952. 80 Bergeron, Y., M. Flannigan, S. Gauthier, A. Leduc and P. Lefort. 2004. Past, current and future fire frequency in the Canadian boreal forest: implications for sustainable forest management. Ambio 33:356-360. Bergeron, Y., P. Drapeau, S. Gauthier and N. Lecomte. 2007. Using knowledge of natural disturbances to support sustainable forest management in the northern Clay Belt. Forestry Chronicle 83:326-337. Berry, L.E., D.A. Driscoll, S.C. Banks, and D.B. Lindenmayer. 2015. The use of topographic fire refuges by the greater glider (Petauroides volans) and the mountain brushtail possum (Trichosurus cunninghami) following a landscape-scale fire. Australian Mammalogy 37:39-45. Bolker, B.M., M.E. Brooks, C.J. Clark, S.W. Geange, J.R. Poulsen, M.H.H. Stevens and J.S. White. 2008. Generalized linear mixed models: a practical guide for ecology and evolution. Trends in Ecology and Evolution 24:127-135. Bond, W.J. and J.E. Keeley. 2005. Fire as a global ‘herbivore’: the ecology and evolution of flammable ecosystems. Trends in Ecology and Evolution 20:387-394. Boone, S.R. and A. Mortelliti. 2019. Small mammal seed tree selection in mixed forests of the Eastern United States. Forest Ecology and Management 449:117487. Boonstra, R. and C.J. Krebs. 2012. Population dynamics of red-backed voles (Myodes) in North America. Oecologia 168:601–620. Borchers, D.L. and M.G. Efford. 2008. Spatially explicit maximum likelihood methods for capture-recapture studies. Biometrics 64:377-385. Borgne, H.L, A. Dupuch, and D. Fortin. 2018a. Ecological processes determining the distribution dynamics of vole populations during forest succession. Oecologia 188:721-732. 81 Borgne, H.L., C. Hébert, A. Dupuch, O. Bichet, D. Pinaud, and D. Fortin. 2018b. Temporal dynamics in animal community assembly during post-logging succession in boreal forest. PLoS ONE 13:e0204445. Brecka, A.F.J, Y. Boulanger, E.B. Searle, A.R. Taylor, D.T. Price, Y. Zhu, C. Shahi, and H.Y.H. Chen. 2020. Sustainability of Canada’s forestry sector may be compromised by impending climate change. Forest Ecology and Management 474:118352. British Columbia Ministry of Forests, Lands, Natural Resource Operations and Rural Development. 2018. Post-natural disturbance forest retention guidance: 2017 wildfires. Victoria, BC: Research Branch, Ministry of Forests. British Columbia Wildfire Service, Government of B.C. 2019. Wildfire Season Summary. https://www2.gov.bc.ca/gov/content/safety/wildfire-status/about-bcws/wildfire-history/wildfire-season-summary (Accessed 3/10/20). Bull, E.L., K.B. Aubry, and B.C. Wales. 2001. Effects of disturbance on forest carnivores of conservation concern in eastern Oregon and Washington. Northwest Science 75(S1):180–184. Burnham, K.P. and D.R. Anderson. 2004. Multimodel inference – understanding AIC and BIC in model selection. Sociological Methods and Research 33:261-304. Buskirk, S.W. and W.J. Zielinski. 2003. Small and mid-sized carnivores. Pages 207-249 in Mammal Community Dynamics. Management and Conservation in the Coniferous Forests of Western North America. Editors: C.J. Zabel and R.G. Anthony. Cambridge University Press, Cambridge. Carey, A.B. and M.L. Johnson. 1995. Small mammals in managed, naturally young, and old-growth forests. Ecological Applications 5:336-352. 82 Chavel, E.E., L. Imbeau, M.J. Mazerolle and P. Drapeau. 2017. Boreal small mammals show evidence of density-dependent patterns with area-sensitivity. Forest Ecology and Management 400:385-501. Cheng, E., K.E. Hodges, and L.S. Mills. 2015. Impacts of fire on snowshoe hares in Glacier National Park, Montana, USA. Fire Ecology 11:119-136. Christianson, A. 2015. Social science research on Indigenous wildfire management in the 21st century and future research needs. International Journal of Wildland Fire 24:190–200. Clavel, J., R. Julliard, and V. Devictor. 2011. Worldwide decline of specialist species: toward a global functional homogenization? Frontiers in Ecology and the Environment 9:222-228. Craig, V.J., K. Walt, M.C. Feller, and T.P. Sullivan. 2006. Relationship between deermice and downed wood in managed forests of southern British Columbia. Canadian Journal of Fire Research 36:2189-2203. Darmon, G., B. Hidding, S. De Bellefeuille, J.-P. Tremblay, and S.D. Cȏté. 2013. A generalist rodent benefits from logging regardless of deer density. Ecoscience 20:319-327. DeGolier, T., J. Port, and S. P. Schottler. 2015. Small mammal habitat preferences in a patchwork of adjacent reconstructed grasslands subject to semiannual burns. Ecological Restoration 33:388–394. Delong, S.C. and D. Tanner. 1996. Managing the patter of forest harvest: lessons from wildfire. Biodiversity and Conservation 5:1191-1205. Dennison, P.E., S.C. Brewer, J.D. Arnold, M.A. Moritz. 2014. Large wildfire trends in the western United States, 1984–2011. Geophysical Research Letters 41:2928-2933. Dormann, C.F., J. Elith, S. Bacher, C. Buchmann, G. Carl, G. Carré, J.R.G. Marquéz, B. Gruber, B. Lafourcade, P.J. Leitão, T. Münkemüller, C. McClean, P.E. Osborne, B. Reineking, B. 83 Schröder, A.K. Skidmore, D. Zurell, and S. Lautenbach. 2013. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36:27–46. Efford, M.G. 2015. secr: spatially explicit capture-recapture models. R package version 4.2.0. Efford, M.G., D.L. Borchers, and G. Mowat. 2013. Varying effort in capture-recapture studies. Methods in Ecology and Evolution 4:629-636. Eisenberg, C., C.L. Anderson, A. Collingwood, R.Sissions, C.J. Dunn, G.W. Meigs, D.E. Hibbs, S. Murphy, S.D. Kuiper, J. SpearChief-Morris, L. Little Bear, B. Johnston, and C.B. Edson. 2019. Out of the ashes: ecological resilience to extreme wildfire, prescribed burns, and indigenous burning in ecosystems. Frontiers in Ecology and Evolution 7:436. Eng, M. 2004. Forest stewardship in the context of large-scale salvage operations: an interpretation paper. B.C. Ministry of Forests, Research Branch, Victoria, B.C. Technical Report, 019. ESRI. 2020. ArcGIS Desktop Release 10.5.1. Redlands, CA: Environmental Systems Research Institute. Farnell, I., C. Elkin, E. Lilles, A.-M. Roberts, and M. Venter. 2020. The effect of variable retention forestry on coarse woody debris dynamics and concomitant impacts on American marten habitat after 27 years. Canadian Journal of Forest Research 50:925-935. Fauteux, D., L. Imbeau, P. Drapeau, and M.J. Mazerolle. 2012. Small mammal responses to coarse woody debris distribution at different spatial scales in managed and unmanaged boreal forests. Forest Ecology and Management 266:194-205. 84 Fernandez-Garcia, V., E. Marcos, P.Z. Fule, O. Reyes, V.M. Santana, and L. Calvo. 2020. Fire regimes shape diversity and traits of vegetation under different climatic conditions. Science of the Total Environment 716:1-11. Ferron, J., F. Potvin and C. Dussault. 1998. Short-term effects of logging on snowshoe hares in the boreal forest. Canadian Journal of Forest Research 28:1335-1343. Fisher, J.T. and S.M. Bradbury. 2006. Understory protection harvest expedites recolonisation of boreal forest stands by North American red squirrels. Forest Ecology and Management 234:40-47. Fisher, J.T., and L. Wilkinson. 2005. The response of mammals to forest fire and timber harvest in the North American boreal forest. Mammal Review 35:51-81. Fisher, J.T., S. Boutin and S.J. Hannon. 2005. The protean relationship between boreal forest landscape structure and red squirrel distribution at multiple spatial scales. Landscape Ecology 20:73-82. Fogel, R. and J.M. Trappe. 1978. Fungus consumption (mycophagy) by small mammals. Northwest Science 52:1-31. Forest and Range Practices Act. S.B.C 2002. c. 69. Forest Practices Board. 2018. Timber salvage harvesting and fisher management in the Nazko area. Forest Practices Board, Victoria, BC. Technical Report, FPB/IRC/217. Friend, G.R. 1993. Impact of fire on small vertebrates in mallee woodlands and heathlands of temperate Australia: a review. Biological Conservation 65:99-114. Galindo, C. and C.J. Krebs. 1985. Habitat use and abundance of deermice: interactions with meadow voles and red-backed voles. Canadian Journal of Zoology 63:1870-1879. 85 García-Carmona, M., V. Arcenegui, F. García-Orenes, and J. Mataix-Solera. 2020. The role of mosses in soil stability, fertility and microbiology six years after a post-fire salvage logging management. Journal of Environmental Management 262:110287. Gayton, D. and P. Lara Almuedo. 2012. Post-disturbance management of biodiversity in BC forests. BC Journal of Ecosystems and Management 13:1–9. Getz, L.L., J.E. Hofmann, B. McGuire, and T.W. Dolan III. 2001. Twenty-five years of population fluctuations of Microtus ochrogaster and M. pennsylvanicus in three habitats in east-central Illinois. Journal of Mammalogy 82:22-34. Gliwicz, J. and B. Glowacka. 2000. Differential responses of Clethrionomys species to forest disturbance in Europe and North America. Canadian Journal of Zoology 78:1340-1348. Griffiths, A.D., and B.W. Brook. 2014. Effect of fire on small mammals: a systematic review. International Journal of Wildland Fire 23:1034-1043. Gurnell, J. 1984. Home range, territoriality, caching behaviour and food supply of the red squirrel (Tamiascurius hudsonicus fremonti) in a subalpine lodgepole pine forest. Animal Behaviour 4:1119-1131. Hamilton, B.T., D.L. Roeder, and M.A. Horner. 2019. Effects of sagebrush restoration and conifer encroachment on small mammal diversity in sagebrush ecosystem. Rangeland Ecology and Management 72:13-22. Hanes, C.C., X. Wang, P. Jain, M.-A. Parisien, J.M. Little, and M.D. Flannigan. 2019. Fire-regime changes in Canada over the last half century. Canadian Journal of Forest Research 49:256-259. Hannah, K.C. and J.S. Hoyt. 2004. Northern hawk owls and recent burns: does burn age matter? Condor 10:420-423. 86 Harmon, M.E. and C. Hua. 1991. Coarse woody debris dynamics in two old-growth ecosystems. Bioscience 41:604-610. Harris, L.B., S.A. Drury, and A.H. Taylor. 2020. Strong legacy effects of prior burn severity on forest resilience to a high-severity fire. Ecosystems 113:11770. Haughland, D.L. and K.W. Larsen. 2004. Ecology of North American red squirrels across contrasting habitats: relating natal dispersal to habitat. Journal of Mammalogy 85:225-236. Henry, D.J. 2002. Canada’s Boreal Forest. Kricher, J, ed. Smithsonian Institute Press, Washington, DC, USA. Hessburg, P.F., Miller, C.L., Parks, S.A., Povak, N.A., Taylor, A.H., Higuera, P.E., Prichard, S.J., North, M.P., Collins, B.M., Hurteau, M.D., Larson, A.J., Allen, C.D., Stephens, S.L., Rivera-Huerta, H., Stevens-Rumann, C.S., Daniels, L.D., Gedalof, Z., Gray, R.W., Kane, V., Churchill, D.J., Hagmann, R.K., Spies, T.A., Cansler, C.A., Belote, R.T., Veblen, T.T., Battaglia, M.A., Hoffman, C., Skinner, C.N., Safford, H.D., and Salter, R.B. 2019. Climate, Environment, and Disturbance History Govern Resilience of Western North American Forests. Frontiers in Ecology and Evolution 7:239. Hodges, K.E. 1999. Proximate factors affecting snowshoe hare movements during a cyclic population low phase. Ecoscience 6:487-496. Hodges, K.E. 2000. The ecology of snowshoe hares in northern boreal forests. Pages 117-161 in Ecology and Conservation of Lynx in the United States, editors L.F. Ruggiero, K.B. Aubry, S.W. Buskirk, G.M. Koehler, C.J. Krebs, K.S. McKelvey, and J.R. Squires. University of Colorado Press, Boulder, USA. 87 Hodges, K.E., and L.S Mills. 2008. Designing fecal pellet surveys for snowshoe hares. Forest Ecology and Management 256:1918-1926. Hodges, K.E., C.J. Krebs, D.S. Hik, C.I. Stefan, E.A. Gills and C.E. Doyle. 2001. Snowshoe hare demography. Pages 143-178 in Ecosystem Dynamics of the Boreal Forest: The Kluane Project, editors C.J. Krebs, S. Boutin, R. Boonstra. Oxford University Press, Oxford, England. Hodges, K.E., L.S. Mills, and K.M. Murphy. 2009. Distribution and abundance of snowshoe hares in Yellowstone National Park. Journal of Mammalogy 90:870-878. Hodges, K.E. and A.R.E. Sinclair. 2005. Browse site selection by snowshoe hares: effects of food supply and predation risk. Canadian Journal of Zoology 83:280-292. Hodson, J., D. Fortin, and L. Belanger. 2011. Changes in relative abundance of snowshoe hares across a 265-year gradient of boreal forest succession. Canadian Journal of Zoology 89:908-920. Holloway, G.L. and J.R. Malcolm. 2006. Sciurid habitat relationships in forests managed under selection and shelterwood silviculture in Ontario. Journal of Wildlife Management 70:1735-1745. Horncastle, V.J., C.L. Chambers, and B.G. Dickson. 2019. Grazing and wildfire effects on small mammals inhabiting montane meadows. Journal of Wildlife Management 83:534-543. Hutchen, J. and K.E. Hodges. 2019a. Foraging behaviour of snowshoe hares (Lepus americanus) in conifer forests regenerating after fire. Canadian Journal of Zoology 97:446-452. Hutchen, J. and K.E. Hodges. 2019b. Impact of wildfire size on snowshoe hare relative abundance in southern British Columbia, Canada. Fire Ecology 15:1-12. 88 Hutchen, J., L.A. Volkmann, and K.E. Hodges. 2017. Experimental designs for studying small-mammal responses to fire in North American conifer forests. International Journal of Wildland Fire 26:523-531. Kaufman, D. W., E. J. Fink, and G. A. Kaufman. 1990. Small mammals and grassland fires. Pp: 46–80 in Fires in North American Tallgrass Prairies. Editors: S. L. Collins and L. L. Wallace. University of Oklahoma Press, Norman, USA. Kemp, G.A. and L.B. Keith. 1970. Dynamics and regulation of red squirrel (Tamiasciurus hudsonicus) populations. Ecology 51:763-779. Klenner, W. and T.P. Sullivan. 2009. Partial and clearcut harvesting of dry Douglas-fir forests: implications for small mammal communities. Forest Ecology and Management 257: 1078-1086. Koehler, G.M. 1990. Population and habitat characteristics of lynx and snowshoe hares in north central Washington. Canadian Journal of Zoology 68:845-851. Koprowski, J.L., K.M. Leonard, C.A. Zugemeyer and J.L. Jolley. 2006. Direct effects of fire on endangered Mount Graham red squirrels. Southwest Naturalist 51:59-63. Krebs, C.J. 2011. Of lemmings and snowshoe hares: the ecology of northern Canada. Proceedings of the Royal Society B 278:481-489. Krebs, C.J., B.S. Gilbert, S. Boutin, and R. Boonstra. 1987. Estimation of snowshoe hare population density from turd transects. Canadian Journal of Zoology 65:565-567. Krebs, C.J., R. Boonstra and S. Boutin. 2017. Using experimentation to understand the 10-year snowshoe hare cycle in the boreal forest of North America. Journal of Animal Ecology 87:87-100. 89 Krebs, C.J., R. Boonstra, S. Gilbert, D. Reid, A.J. Kenney, and E.J. Hofer. 2011. Density estimation for small mammals from livetrapping grids: rodents in northern Canada. Journal of Mammalogy 92:974-981. Krebs, C.J., R. Boonstra, V. Nams, M. O’Donoghue, K.E. Hodges, and S. Boutin. 2001. Estimating snowshoe hare population density from pellet plots: a further evaluation. Canadian Journal of Zoology 79:1-4. Krebs, C.J., K. Kielland, J. Bryant, M. O’Donoghue, F. Doyle, C. McIntyre, D. DiFolco, N. Berg, S. Carriere, R. Boonstra, S. Boutin, A.J. Kenney, D.G. Reid, K. Bodony, J. Putera, H.K. Timm, and T. Burke. 2013. Synchrony in the snowshoe hare (Lepus americanus) cycle in northwestern North America, 1970–2012. Canadian Journal of Zoology 91:562-572. Krefting, L.W. and C.E. Ahlgren. 1974. Small mammals and vegetation changes after fire in a mixed conifer-hardwood forest. Ecology 55:1391-1398. Kronland, W.J. and M. Restani. 2011. Effects of post-fire salvage logging on cavity-nesting birds and small mammals in southeastern Montana. Canadian Field-Naturalist 125:316-326. Lake, F.K. and Christianson, A.C. 2019. Indigenous Fire Stewardship. In Encyclopedia of Wildfire and Wildland-Urban Interface (WUI) Fires Edited by S. Mazello. Springer Nature, Switzerland. Larson, M.D., J.C. Larson, D.W. Holt, S. Gniadek, and A. Eckert. 2019. The northern hawk owl in Montana: a summary of breeding biology, diet, habitat association, and records. Journal of Raptor Research 53:66-74. 90 Lemaître, J., D. Fortin, D.W. Morris, and M. Darveau. 2010. Deermice mediate red-backed vole behaviour and abundance along a gradient of habitat alteration. Evolutionary Ecology Research 12:203-216. Liebmann, M.J., Farella, J., Roos, C.I., Stack, A., Martini, S., and Swetnam, T.W. 2016. Native American depopulation, reforestation, and fire regimes in the Southwest United States, 1492–1900 CE. Proceedings of the National Academy of Sciences. 113:696-704. Lindernmayer, D.B., D.R. Foster, J.F. Franklin, M.L. Hunter, R.F. Noss, F.A. Schiegelow, and D. Perry. 2004. Salvage harvesting policies after natural disturbance. Science 303:1303. Lindenmayer, D.B. and R.F. Noss. 2006. Salvage logging, ecosystem processes, and biodiversity conservation. Conservation Biology 20:949-958. Littell, J.S., D.L. Peterson, K.L. Riley, Y. Liu, and C.H. Luce. 2016. A review of the relationships between drought and forest fire in the United States. Global Change Biology 22:2353-2369. Lobo N., M. Duong, and J.S. Miller. 2009. Conifer-seed preferences of small mammals. Canadian Journal of Zoology 87:773-780. Loehman, R.A., R.E. Keane, L.M. Holsinger, and Z. Wu. 2017. Interactions of landscape disturbances and climate change dictate ecological pattern and process: spatial modeling of wildfire, insect, and disease dynamics under future climates. Landscape Ecology 32:1447-1459. Marlon, J.R., P.J. Bartlein, D.G. Gavin, C.J. Long, R.S. Anderson, C.E. Briles, K.J. Brown, D. Colombaroli, D.J. Hallett, M.J. Power, E.A. Scharf, and M.K. Walsh. 2012. Long-term perspective on wildfires in the western USA. Proceedings of the National Academy of Sciences 109:535-543. 91 Martineau, J., D. Pothier, and D. Fortin. 2016. Processes driving short-term temporal dynamics of small mammal distribution in human-disturbed environments. Ocealogia 181:831-840. Marvier, M., P. Kareiva, and M.G. Nuebert. 2004. Habitat destruction, fragmentation, and disturbance promote invasion by habitat generalists in a multispecies metapopulation. Risk Analysis 24:869-878. Maser, C., A.W. Claridge, and J.M. Trappe. 2008. Trees, truffles, and beasts: how forests function. Rutgers University Press, Piscataway, New Jersey. Mattson, D.J. and D.P. Reinhart. 1996. Indicators of red squirrel (Tamiasciurus hudsonicus) abundance in the whitebark pine zone. Great Basin Naturalist 56:272-275. Meigs, G.W. and M.A. Krawchuk. 2018. Composition and structure of forest fire refugia: what are the ecosystem legacies across burned landscapes? Forests 9:1-20. Miller, J.D., H.D. Safford, M. Crimmins, and A.E. Thode. 2009. Quantitative evidence for increasing forest fire severity in the Sierra Nevada and Southern Cascade Mountains, California and Nevada, USA. Ecosystems 12:16-32. Miller, J.D., C.N. Skinner, H.D. Safford, E.E. Knapp, and C.M. Ramirez. 2012. Trends and causes of severity, size, and number of fires in northwestern California, USA. Ecological Applications 22:184-203. Mills, L.S., P.C. Griffin, K.E. Hodges, K. McKelvey, L. Ruggiero, and T. Ulizio. 2005. Pellet count indices compared to mark-recapture estimates for evaluating snowshoe hare density. Journal of Wildlife Management 69:1053-1062. Morales-Díaz, S.P., M.Y. Alvarez-Añorve, M.E. Zamora-Espinoza, R. Dirzo, K. Oyama, and L.D. Avila-Cabadilla. 2019. Rodent community responses to vegetation and landscape 92 changes in early successional stages of tropical dry forest. Forest Ecology and Management 15:633-644. Moses, R. A. and S. Boutin. 2001. The influence of clearcut logging and residual leave material on small mammal populations in aspen-dominated boreal mixedwoods. Canadian Journal of Forest Research 31:483-495. Müller, J., R.F. Noss, S. Thorn, C. Bassler, A.B. Leverkus, and D. Lindenmayer. 2018. Increasing disturbance demands new policies to conserve intact forest. Conservation Letters 12: 1-7. Nappi, A., P. Drapeau, and J.P.L. Savard. 2004. Salvage logging after wildfire in the boreal forest: Is it becoming a hot issue for wildlife? Forestry Chronicle 80:67-74. Navarro-Castilla, A. and I. Barja. 2019. Stressful living in lower-quality habitats? Body mass, feeding behavior, and physiological stress levels in wood mouse populations. Integrative Zoology 14:114-126. Nelson, D.L., K.F. Kellner, and R.K. Swihart. 2019. Rodent population density and survival respond to disturbance induced by timber harvest. Journal of Mammalogy 100:1253-1262. Newbury, T.L. and N.P.P. Simon. 2005. The effects of clearcutting on snowshoe hare (Lepus americanus) relative abundance in central Labrador. Forest Ecology and Management 210:131-142. Noss, R.F. and D.B. Lindenmayer. 2006. The ecological effects of salvage logging after natural disturbance. Conservation Biology 20:946-948. Oli, M.K., C.J. Krebs, A.J. Kenney, R. Boonstra, S. Boutin, and J.E. Hines. 2020. Demography of snowshoe hare population cycles. Ecology 101: e02969. 93 Olnes, J., K. Kielland, H. Genet, and R. Ruess. 2019. Postfire deciduous canopies drive patterns in snowshoe hare herbivory of regenerating black spruce. Canadian Journal of Forest Research 49:1392-1399. Parisien, M.-A., Q.E. Barber, K.G. Hirsch, C.A. Stockdale, S. Erni, X. Wang, D. Arseneault, and S.A. Parks. 2020. Fire deficit increases wildfire risk for many communities in the Canadian boreal forest. Nature Communications 11:2121. Parsons, M.A., J.C. Lewis, J.N. Pauli, T. Chestnut, J.I. Ransom, D.O. Werntz, and L.R. Prugh. 2020. Prey of reintroduced fishers and their habitat relationships in the Cascades Range, Washington. Forest Ecology and Management 460:117888. Pearce, J. and L. Venier. 2005. Small mammals as bioindicators of sustainable boreal forest management. Forest Ecology and Management 208:153–175. Pearson, D.E., K.S. McKelvey, and L.F. Ruggiero. 2000. Non-target effects of an introduced biological control agent on deermouse ecology. Oecologia 122:121–128. Pinotti, B.T., C.P. Pagotto, and R. Pardini. 2015. Wildlife recovery during tropical forest succession: assessing ecological drivers of community change. Biotropica 47:765-774. Podruzny, S.R., D.P. Reinhart and D.J. Mattson. 1999. Fire, red squirrels, whitebark pine, and Yellowstone grizzly bears. Ursus 11:131-138. Potvin, F. and N. Bertrand. 2004. Leaving forest strips in large clearcut landscapes of boreal forest: a management scenario suitable for wildlife? Forestry Chronicle 80:44-53. Potvin, F., R. Courtois, and L. Bélanger. 1999. Short-term response of wildlife to clear-cutting in Quebec boreal forest: multiscale effects and management implications. Canadian Journal of Forest Research 29:112-1127. 94 Prichard, S.J., C.S. Stevens-Rumann, and P.F. Hessburg. 2017. Shifting global fire regimes: lessons from reburns and research needs. Forest Ecology and Management 396:217-233. Puig-Gironés, R., L. Imbeau, M. Clavero, J. Rost, and P. Pons. 2020. Does post-fire salvage logging affect foraging activity by rodents? European Journal of Forest Research 139:777-790. Püttker, T., A.A. Bueno, P.I. Prado, and R. Pardini. 2015. Ecological filtering or random extinction? Beta-diversity patterns and the importance of niche-based and neutral processes following habitat loss. Oikos 124:206-215. Püttker, T., C.S. Barros, B.T. Pinotti, A.A. Bueno, and R. Pardini. 2019. Co-occurrence patterns of rodents at multiple spatial scales: competitive release of generalists following habitat loss? Journal of Mammalogy 100:1229-1242. Ransome, D.B., P.M.F. Lindgren, M.J. Waterhouse, H.M. Armleder, and T.P. Sullivan. Small-mammal response to group selection silvicultural systems in Engelmann spruce – subalpine fir forests 14 years postharvest. Canadian Journal of Forest Research 39:1698-1708. Roth, J.D., J.D. Marshall, D.L. Murray, D.M. Nickerson, and T.D. Steury. 2007. Geographical gradients in diet affect population dynamics of Canada lynx. Ecology 88:2736-2743. Rusch D.A. and W.G. Reeder. 1978. Population ecology of Alberta red squirrels. Ecology 59:400-420. Russell, R.F., J.F. Lehmkhul, S.T. Buckland, and V.A. Saab. 2010. Short-term responses of red squirrels to prescribed burning in the interior Pacific Northwest, USA. Journal of Wildlife Management 74:12-17. 95 Saint-Germain, M. and D.F. Greene. 2009. Salvage logging in the boreal and cordilleran forests of Canada: Integrating industrial and ecological concerns in management plans. Forestry Chronicle 85:120-134. Schielzeth, H. and S. Nakagawa. 2013. Nested by design: model fitting and interpretation in a mixed model era. Methods in Ecology and Evolution 4:14-24. Schmiegelow, F.K.A., D.P. Stepnisky, C.A. Stambaugh, and M. Koivula. 2006. Reconciling salvage logging of boreal forests with a natural-disturbance management model. Conservation Biology 20:971-983. Seidl, R., M.-J. Schelhaas, and M.J. Lexer. 2011. Unraveling the drivers of intensifying forest disturbance regimes in Europe. Global Change Biology 17:2842-2852. Seip, C.R., D.P. Hodder, S.M. Crowley and C.J. Johnson. 2018. Use of constructed coarse woody debris corridors in a clearcut by American martens (Martes americana) and their prey. Forestry 91:506-513. Stevens-Rumann, C.S., S.J. Prichard, E.K. Strand, and P. Morgan. 2016. Prior wildfires influence burn severity of subsequent large fires. Canadian Journal of Forest Research 46:1375-1385. Strong, W.L. and T.S. Jung. 2012. Stand-level attributes of snowshoe hare (Lepus americanus) habitat in post-fire trembling aspen (Populus tremuloides) chronosequence in central Yukon. Canadian Field Naturalist 126:295-305. Sullivan, T.P. and D.S. Sullivan. 2001. Influence of variable retention harvests on forest ecosystems. II. Diversity and population dynamics of small mammals. Journal of Applied Ecology 38:1234-1252. 96 Sullivan, T.P. and D.S. Sullivan. 2010. Forecasting vole population outbreaks in forest plantations: the rise and fall of a major mammalian pest. Forest Ecology and Management 260:983-993. Sullivan, T.P. and D.S. Sullivan. 2011. Balancing pest management and forest biodiversity: vole populations and habitat in clearcut vs. variable retention harvested sites. Crop Protection 30:833-843. Sullivan, T.P. and D.S. Sullivan. 2016. Wildfire, clearcutting, and vole populations: balancing forest crop protection and biodiversity. Crop Protection 85:9-16. Sullivan, T.P. and D.S. Sullivan. 2018a. Long-tailed vole (Microtus longicaudus) population outbreaks and refugia after clearcutting of coniferous forest: the search for fluctuations and hot spots. Crop Protection 112:49-55. Sullivan, T.P. and D.S. Sullivan. 2018b. Population fluctuations and tree damage by red-backed voles (Myodes gapperi) after clearcutting of coniferous forest. Journal of Forest Research 23:380-386. Sullivan, T.P. and D.S. Sullivan. 2019. Long-term functionality of woody debris structures for forest-floor small mammals on clearcuts. Forest Ecology and Management 451:117535. Sullivan, T.P. and D.S. Sullivan. 2020. Similarity in occupancy of different sized forest patches by small mammals on clearcuts: conservation implications for red-backed voles and small mustelids. Mammal Research 65:255-266. Sullivan, T.P., A.S. Harestad, and B.M. Wikeem, 1990. Control of mammal damage. Pp. 302-318 in: Regenerating British Columbia's Forests. Editors: D.P. Lavender, R. Parish, C.M. Johnson, G. Montgomery, A. Vyse, R.A. Willis, and D. Winston. University of British Columbia Press, Vancouver, British Columbia, Canada. 97 Sullivan, T.P., D.B. Ransome, P.M.F. Lindgren. and D.S. Sullivan. 2007. Small Mammal Population Monitoring and Protection of New Plantations. Annual Report. Forests for Tomorrow, British Columbia Ministry of Forests and Range, Victoria B.C. Sullivan, T.P., D.S. Sullivan, and P.M.F. Lindgren. 2008. Influence of variable retention harvests on forest ecosystems: plant and mammal responses up to 8 years post-harvest. Forest Ecology and Management 254:239-254. Sullivan, T.P., R.A. Lautenschlager and R.G. Wagner. 1999. Clearcutting and burning of Northern spruce-fir forests: implications for small mammal communities. Journal of Applied Ecology 36:327-344. Thom, D. and R. Seidl. 2016. Natural disturbance impacts on ecosystem services and biodiversity in temperate and boreal forests. Biological Reviews 91:760-781. Thomas, J.P., M.L. Reid, R.M.R. Barclay, and T.S. Jung. 2019. Salvage logging after an insect outbreak reduces occupancy by snowshoe hares (Lepus americanus) and their primary predators. Global Ecology and Conservation 17:1-13. Thompson, J.R., T.A. Spies and L.M. Ganio. 2007. Reburn severity in managed and unmanaged vegetation in large wildfires. Proceedings of the National Academy of Sciences 104:10743-10748. Thorn, S., C. Bässler, R. Brandl, P.J. Burton, R. Cahall, J.L. Campbell, J. Castro, C.-Y. Chio, T. Cobb, D.C. Donato, E. Durska, J.B. Fontaine, S. Gauthier, C. Hebert, T. Hothorn, R.L. Hutto, E.J. Lee., A. B. Leverkus, D.B. Lindenmayer, M.K. Obrist, J. Rost, S. Seibold, R. Seidl, D. Thom, K. Waldron, B. Wermelinger, M.-B. Winter, M. Zmihorski, and J. 98 Müller. 2018. Impacts of salvage logging on biodiversity: a meta-analysis. Journal of Applied Ecology 55:279-289. Thornton, D.H., A.J. Wirsing, J.D. Roth, and D.L. Murray. 2012. Complex effects of site preparation and harvest on snowshoe hare abundance across a patchy forest landscape. Forest Ecology and Management 280:132-139. Turner, N.J., Ignace, M.B., and Ignace R. 2000. Traditional ecological knowledge and wisdom of Aboriginal peoples in British Columbia. Ecolological Applications. 105:1275-1787. Van Nieuwstadt, M.G.L., D. Sheil, and K. Kartawinata. 2001. The ecological consequences of logging in the burned forests of East Kalimantan, Indonesia. Conservation Biology 15:1183-1186. Vander Wall, S.B. 2010. How plants manipulate the scatter-hoarding behaviour of seed-dispersing animals. Philosophical Transactions of the Royal Society B 365:989-997. Vanderwel, M.C., J.R. Malcolm, J.P. Caspersen, and M.A. Newman. 2010. Fine-scale habitat associations of red-backed voles in boreal mixedwood stands. Journal of Wildlife Management 74:1492-1501. Volkmann, L.A., J. Hutchen, and K.E. Hodges. 2020. Trends in carnivore and ungulate fire ecology research in North American conifer forests. Forest Ecology and Management 458:117691. Weir, R.D., A.S. Harestad, and R.C. Wright. 2005. Winter diet of fishers in British Columbia. Northwestern Naturalist 86:12-19. Westerling, A.L., H.G. Hidalgo, D.R. Cayan and T.W. Swetnam. 2006. Warming and earlier spring increase western U.S forest wildfires. Science 313:940-943. 99 Woodall, C. and M.S. Williams. 2007. Sampling protocol, estimation, and analysis procedures for the down woody material indicator of the FIA program. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Research Station. Technical Report NC-256. Zwolak, R. 2009. A meta-analysis of the effects of wildfire, clearcutting, and partial harvest on the abundance of North American small mammals. Forest Ecology and Management 258:539-545. Zwolak, R. D.E. Pearson, Y.K. Ortega, and E.E. Crone. 2012. Mechanisms driving postfire abundance of a generalist mammal. Canadian Journal of Zoology 90:51-60. 100 Appendices Appendix A: Example code and supplementary density estimates of deermice and voles (Chapter 2). Equation A.1. Example of R code for generalized linear mixed effects models of individuals captured and habitat. 𝑔𝑙𝑚𝑒𝑟(𝐼𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙𝑠 𝐶𝑎𝑝𝑡𝑢𝑟𝑒𝑑 ~ 𝐻𝑎𝑏𝑖𝑡𝑎𝑡 + 𝑌𝑒𝑎𝑟 + (1|𝐺𝑟𝑖𝑑) + (1|𝑆𝑒𝑠𝑠𝑖𝑜𝑛),𝑑𝑎𝑡𝑎 = 𝑑𝑎𝑡𝑎, 𝑓𝑎𝑚𝑖𝑙𝑦 = poisson) 101 Table A.1. Density estimates of deermice per hectare in 2018 for trapping grids with sufficient capture numbers for estimates. The predictor variable of capture probability (g0) used in each final model is given. The predictor variables selected from were learned response to capture (b), time of each primary session (t), time as a linear function (T), session and learned capture response (session + b). Habitat Grid Session Density (mice/ ha) Standard Error Lower Confidence Interval Upper Confidence Interval g0 model 2010 Burn 10B01 1 1.61 1.34 0.39 6.65 T 10B01 2 1.58 0.98 0.52 4.83 T 10B01 3 1.89 1.77 0.40 8.95 T 10B03 1 0.61 5.07 1.47 25.25 b + session 10B03 2 0.73 0.14 0.50 1.05 b + session 10B03 3 1.43 0.83 0.52 4.12 b + session 2017 Burn 17B01 1 0.53 0.30 0.19 1.50 T 17B01 2 1.68 1.17 0.49 5.76 T 17B01 3 2.66 1.07 1.23 5.69 T 17B02 1 0.24 0.19 0.06 0.95 t 17B02 2 0.99 0.47 0.41 2.40 t 17B02 3 1.95 0.81 0.90 4.26 t 17B03 1 1.51 1.03 0.45 5.06 t 17B03 2 4.98 1.69 2.61 9.51 T 17B03 3 14.52 14.57 2.83 74.55 T 2010 Burn + Salvage-logged SL01 1 11.30 2.85 6.95 18.38 t SL01 2 12.44 2.94 7.88 19.64 t SL01 3 13.68 3.37 8.50 22.02 t SL02 1 1.91 1.15 0.64 5.69 T SL02 2 1.48 0.99 0.45 4.88 T SL02 3 3.79 1.78 1.58 9.07 T SL03 1 10.11 2.75 5.98 17.08 T SL03 2 8.73 2.67 4.86 15.68 T SL03 3 13.3 3.52 7.98 22.16 T 102 Table A.2. Density estimates of southern red-backed voles per hectare in 2018 for trapping grids with sufficient capture numbers for estimates. The predictor variable of capture probability (g0) used in each final model is given. The predictor variables selected from were learned response to capture (b), time of each primary session (t), time as a linear function (T), session and learned capture response (session + b). Habitat Grid Session Density (voles/ha) Standard Error Lower Confidence Interval Upper Confidence Interval g0 model 2010 Burn 10B02 3 2.23 1.37 0.74 6.78 T Mature MA03 3 6.10 2.88 2.53 14.71 T 103 Table A.3. Density estimates of deermice per hectare in 2019 for trapping grids with sufficient capture numbers for estimates. The predictor variable of capture probability (g0) used in each final model is given. The predictor variables selected from were learned response to capture (b), time of each primary session (t), time as a linear function (T), session and learned capture response (session + b). Habitat Grid Session Density (mice/ ha) Standard Error Lower Confidence Interval Upper Confidence Interval g0 model 2010 Burn 10B01 1 5.35 3.95 1.47 19.49 session 10B01 2 18.45 3.89 12.26 27.78 session 10B01 3 14.82 3.26 9.68 22.69 session 10B02 2 8.09 2.33 4.66 14.07 T 10B02 3 9.3 2.56 5.47 15.8 T 10B03 1 13.62 3.77 7.99 23.19 b 10B03 2 43.24 9.89 27.77 67.31 b 10B03 3 21.13 4.97 13.41 33.29 b 2017 Burn 17B01 1 23.37 3.86 16.94 32.24 T 17B01 2 20.05 3.4 14.41 27.9 T 17B01 3 43.79 6.65 32.58 58.86 T 17B02 1 24.07 4.41 16.85 34.38 b 17B02 2 24.39 4.25 17.38 34.22 b 17B02 3 40.26 6.82 28.96 55.98 b 17B03 1 24.35 4.4 17.13 34.6 b + session 17B03 2 29.75 5.61 20.62 42.92 b + session 17B03 3 36.59 7.21 24.96 53.64 b + session Mature MA01 2 20.96 9.44 9.03 48.65 b MA01 3 47.57 16.13 24.92 90.8 b MA02 1 5.49 5.11 1.17 25.82 session MA02 2 8.76 9.83 1.49 51.41 session MA02 3 7.93 2.48 4.36 14.43 session MA03 1 11.5 1.5 0.01 1.92 T MA03 2 11.2 3.74 5.92 21.17 T MA03 3 20.21 3.78 14.06 29.05 T 2010 Burn + SL01 1 18.96 3.68 13.01 27.63 T SL01 2 21 3.7 14.91 29.57 T SL01 3 21.88 3.69 15.76 30.37 T 104 Salvage-logged SL02 1 6.45 1.79 3.79 11 T SL02 2 15.5 3.78 9.68 24.82 T SL02 3 26.17 4.02 19.4 35.32 T SL03 1 22.74 5.16 14.66 35.28 b + session SL03 2 28.34 5.26 19.76 40.65 b + session SL03 3 33.52 5.91 23.79 47.24 b + session 105 Table A.4. Density estimates of southern red-backed voles per hectare in 2019 for trapping grids with sufficient capture numbers for estimates. The predictor variable of capture probability (g0) used in each final model is given. The predictor variables selected from were learned response to capture (b), time of each primary session (t), time as a linear function (T), session and learned capture response (session + b). Habitat Grid Session Density (voles/ ha) Standard Error Lower Confidence Interval Upper Confidence Interval g0 model 2010 Burn 10B01 1 4.01 2.23 1.45 11.08 T 10B01 2 7.20 2.48 3.74 13.87 T 10B01 3 14.48 3.32 9.30 22.55 T 10B02 2 16.23 4.19 9.86 26.71 b 10B02 3 17.62 3.95 11.42 27.20 b 10B03 1 7.92 3.23 3.67 17.08 T 10B03 2 30.01 9.63 16.25 55.43 T 10B03 3 30.61 6.12 20.77 45.11 T 2017 Burn 17B01 1 0.29 1.21 1.03 8.10 b 17B01 2 3.11 2.49 0.78 12.34 b 17B01 3 13.43 8.74 4.19 43.02 b 17B02 2 16.98 11.19 5.23 55.09 b 17B02 3 1.35 0.49 0.67 2.70 b 17B03 2 11.02 6.92 3.56 34.11 b 17B03 3 14.28 6.60 6.02 33.82 b Mature MA01 1 3.06 9.62 3.56 34.11 b MA01 2 4.20 3.74 0.94 18.79 b MA01 3 13.37 13.34 2.61 68.51 b MA02 1 0.15 0.03 0.10 0.22 T MA02 2 7.96 2.86 4.02 15.76 T MA02 3 7.31 3.36 3.10 17.25 T MA03 1 4.06 15.17 0.16 102.02 b + session MA03 2 9.15 4.85 3.45 24.29 b + session MA03 3 7.55 2.52 3.99 14.27 b + session 106 Appendix B. Mean snowshoe hare pellet counts and red squirrel middens counts (Chapter 3). Table B.1. Mean snowshoe hare pellet counts and hare densities per hectare at survey sites. Hare densities were determined using the equation provided by Krebs et al. (2001). Site Mean Pellets ± SD Hares/ha 2010 Burn 01 1.55 ± 5.79 0.69 ± 1.31 2010 Burn 02 0.09 ± 0.40 0.05 ± 7.33 2010 Burn 03 0.31 ± 1.04 0.17 ± 3.5 2010 Burn 04 0.20 ± 0.60 0.11 ± 4.84 2010 Burn 05 1.49 ± 2.22 0.67 ± 1.20 2010 Burn 06 1.78 ± 2.81 0.78 ± 1.73 2010 Burn Mean 0.90 ± 2.90 0.43 ± 0.31 2017 Burn 01 0.03 ± 0.22 0.02 ± 11.1 2017 Burn 02 0 ± 0 0 ± 0 2017 Burn 03 0.34 ± 1.54 0.18 ± 3.23 2017 Burn 04 0.025 ± 0.16 0.02 ± 11.1 2017 Burn 05 0.31 ± 1.03 0.17 ± 3.5 2017 Burn Mean 0.14 ± 0.84 0.08 ± 5.9 Mature 01 0.28 ± 0.83 0.15 ± 3.89 Mature 02 0.13 ± 1.01 0.07 ± 6.26 Mature 03 0.59 ± 1.48 0.29 ± 1.59 Mature 04 0.39 ± 0.92 0.20 ± 2.85 Mature 05 1 ± 2.55 0.47 ± 0 Mature 06 0.45 ± 1.47 0.23 ± 2.4 Mature 07 0.87 ± 1.59 0.41 ± 0.43 Mature 08 1.98 ± 3.70 0.86 ± 2.04 Mature Mean 0.71 ± 2.00 0.35 ± 1.04 107 Site Mean Pellets ± SD Hares/ha Salvage 01 0.01 ± 0.11 0.01 ± 13.19 Salvage 02 0 ± 0 0 ± 0 Salvage 03 0 ± 0 0 ± 0 Salvage 04 0 ± 0 0 ± 0 Salvage 05 0.03 ± 0.22 0.02 ± 11.1 Salvage 06 0.01 ± 0.11 0.01 ± 13.19 Salvage 07 0.05 ± 0.27 0.03 ± 9.02 Salvage Mean 0.01 ± 0.15 0.01 ± 12.79 108 Table B.2. Red squirrel middens per survey site. Site Middens 2010 Burn 01 1 2010 Burn 02 0 2010 Burn 03 0 2010 Burn 04 4 2010 Burn 05 3 2010 Burn 06 7 2010 Burn x̄ ± SD 2.50 ± 2.74 2017 Burn 01 0 2017 Burn 02 0 2017 Burn 03 0 2017 Burn 04 0 2017 Burn x̄ ± SD 0 ± 0 Mature 01 16 Mature 02 2 Mature 03 3 Mature 04 5 Mature 05 1 Mature 06 4 Mature 08 5 Mature x̄ ± SD 5.14 ± 5.01 Salvage 01 0 Salvage 02 0 Salvage 03 0 Salvage 04 0 Salvage 05 0 Salvage 06 0 Salvage 08 0 Salvage x̄ ± SD 0 ± 0
Thesis/Dissertation
eng
Biology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Small mammals and mesomammals in a post-fire and salvage-logged landscape
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