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Habitat Relationships and Gene Flow of Martes Americana in Northern Idaho

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Habitat Relationships and Gene Flow of Martes Americana in Northern Idaho Western Washington University Western CEDAR WWU Graduate School Collection WWU Graduate and Undergraduate Scholarship 2008 Habitat relationships and gene flow of Martes americana in northern Idaho Tzeidle N. (Tzeidle Nichole) Wasserman Western Washington University Follow this and additional works at: https://cedar.wwu.edu/wwuet Part of the Environmental Sciences Commons Recommended Citation Wasserman, Tzeidle N. (Tzeidle Nichole), "Habitat relationships and gene flow of Martes americana in northern Idaho" (2008). WWU Graduate School Collection. 1. https://cedar.wwu.edu/wwuet/1 This Masters Thesis is brought to you for free and open access by the WWU Graduate and Undergraduate Scholarship at Western CEDAR. It has been accepted for inclusion in WWU Graduate School Collection by an authorized administrator of Western CEDAR. For more information, please contact [email protected]. HABITAT RELATIONSHIPS AND GENE FLOW OF MARTES AMERICANA IN NORTHERN IDAHO A Thesis Presented to The Faculty of Western Washington University In Partial Fulfillment of the Requirements for the Degree Master of Science By Tzeidle N. Wasserman February 2008 iii ABSTRACT Forest fragmentation can have a dramatic effect on landscape connectivity and dispersal of animals, potentially reducing gene flow within and among populations. American marten populations (Martes americana) are sensitive to forest fragmentation and the spatial configuration of patches of remnant mature forest has an important impact on habitat quality. This study represents an extensive multiple scale habitat relationships analysis conducted for American marten. In conjunction with Idaho Department of Fish and Game (IDFG) and the U.S. Forest Service, genetic data on marten populations across the Idaho Panhandle National Forest was used to build habitat relationships models. Over 3 years of winter fieldwork during 2004, 2005, and 2006, I detected martens at 569 individual hair snare stations distributed across a 3,000 square kilometer study area covering the Selkirk, Purcell, and Cabinet Mountain ranges. I investigated habitat relationships of this population of Martes americana in the Idaho Panhandle National Forest (IPNF) at three spatial scales: Plot, Home Range, and Multiple-Scale. I used bivariate scaling to measure each environmental variable across a broad range of radii ranging from 90m-1080m around each sample station. I used an information-theoretic approach to rank 45 a priori candidate models that described hypothesized habitat relationships at each spatial scale. At the plot scale, marten presence was positively predicted by the Percentage of Landscape (PLand) comprised of large sawtimber, and negatively predicted by PLand of seedling/sapling timber type. At the home range scale, the probability of detecting a marten decreased with increasing amounts of fragmentation and highly contrasted edges between patches of large sawtimber and patches of seedling/sapling and non-stocked patches. iv In the multiple-scale analysis, I used a variable screening step to find variables that were universal and consistent throughout all models in order to build candidate models. PLand comprised of large homogeneous patches of large sawtimber was a positive predictor of marten presence, while highly contrasted edges and fragmentation were strong negative predictors of marten presence. The scale at which martens selected habitats varied greatly across variables. Martens actively selected for high quality habitat at the fine scale (plot level) and strongly avoided areas comprised of seedling/sapling and non-stocked timber areas. Martens negatively responded to high contrast edges and strongly avoided them. Juxtaposition and configuration of patches of large sawtimber was important to marten habitat selection. This study demonstrates the importance of investigating marten habitat at multiple spatial scales and provides insights to linkages among scales and how martens respond to forest fragmentation. Genetic information was used to model genetic relationships of this marten population with respect to environmental and spatial variables within my study landscape. Over three field seasons 70 individual marten were detected across the study area. The genetic similarities were based on the pair-wise percentage dissimilarity among all individuals based on 7 microsatellite loci. I compared their genetic similarities with several landscape resistance hypotheses. The landscape resistance hypotheses describe a range of potential relationships between movement cost and landcover, elevation, roads, Euclidean distance and valleys between mountain ranges as barriers. The degree of support for each model was tested with causal modeling on resemblance matrices using partial Mantel tests. v Hypotheses of Isolation by Distance and Isolation by Barrier were not supported, and Isolation by Landscape Resistance proved to be the best model describing genetic patterns of Martes americana in the IPNF. Elevation 1600m with a standard deviation of 600m was the most highly supported landscape resistance model correlated to genetic structure of marten in this landscape. Correlating genetic similarity of individuals across large landscapes with hypothetical movement cost models can give reliable inferences about population connectivity. By linking cost modeling to the actual patterns of genetic similarity among individuals it is possible to obtain rigorous, empirical models describing the relationship between landscape structure and gene flow, and to produce species- specific maps of landscape connectivity, and can provide managers with critical information to better administer our forests for meso-carnivores and other species of concern. vi ACKNOWLEDGEMENTS This work was part of a cooperative research project on the American marten (Martes americana) and fisher (Martes pennanti) in conjunction with Idaho Department of Fish and Game, the U.S. Forest Service, and Western Washington University. This work was possible thanks to the hard work and encouragement of Jim Hayden of the Idaho Department of Fish and Game who gave me great support. Funding for this project was provided and by Idaho Department of Fish and Game, the U.S. Forest Service Rocky Mountain Research Station, and grants from Huxley College of the Environment and Western Washington University Bureau for Faculty Research. I would like to thank my committee: David O. Wallin, Leo R. Bodensteiner, and Michael K. Schwartz for their guidance and support. Thank you for all the hard work contributed by the many technicians and volunteers who helped collect this data. Thank you to the Wildlife Genetics Lab in the U.S. Forest Service Rocky Mountain Research Station for aid in genetic analysis. Mostly, I would like to thank my family for their ongoing encouragement, support and advice. vii Table of Contents Abstract............................................................................................................................. iv Acknowledgements..........................................................................................................vii List of Tables and Figures Chapter 1.........................................................................….x List of Tables and Figures Chapter 2…................................................................…...xiv CHAPTER 1.......................................................................................................................1 Introduction........................................................................................................................1 Objectives.............................................................................................…………...2 Marten Ecology...................................................................………………......…..4 Habitat Associations........................................................................……………....6 Study Area....................................……………………………...……..................10 Methods..............................................................................................................………...11 Survey Methods.........................................................................................………11 Genetic Methods....................................................................................................11 Habitat Modeling...................................................................................................12 Plot Level Analysis................................................................................................17 Home Range Analysis......................................................................….…….........18 Multiple-Scale Analysis...........................….........................................….…........19 Model Selection and Analysis.......................................................................…....21 Results...............................................................................................................................24 Survey Results....................................................................................…………...24 Genetic Results…..............................................................................……….…...24 Habitat Models.......................................................................................………....24 Plot Level Analysis................................................................................................24 Home Range Analysis...................................................….....................................26
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