The American marten (Martes americana) is an endangered species in Vermont and a Regional Species of Greatest Conservation Need in the northeastern United States. Though historically widespread in northeastern forests, their range presumably contracted to northern Maine and the High Peaks region of the Adirondacks by the early 1900s. Regionally, populations appear to be in recovery. Natural recolonization is believed to have occurred in New Hampshire, northeastern Vermont and the western Adirondacks. A reintroduction effort in southern Vermont that was originally declared unsuccessful is now believed to be the source of a recently detected population in the area. However, our current knowledge of distribution, population history and population connectivity relies primarily on occurrence data from harvest records, which are limited in scope and resolution. In Vermont, where population size is estimated to be extremely low, more robust estimates of population status may be critical to continued recovery. I genotyped individuals from Maine, New York, New Hampshire, northeastern Vermont and southern Vermont at ten microsatellite loci and amplified a 320 base pair segment of the control region of mtDNA to estimate the source(s) of the two Vermont populations using statistical tests of genetic differentiation. I also used Bayesian and stochastic genetic clustering methods to estimate population genetic structure in the northeastern United States. Genetic structure exists at multiple scales in the region as a result of natural barriers to gene flow, human-mediated gene flow, and lineage sorting in relic populations. My results suggest that New Hampshire is a major source of colonization of northeastern Vermont and the population in southern Vermont is either a remnant of the reintroduction or a pre-reintroduction relic that has experienced introgression from the reintroduction stock. I identified three regions where relic populations perceived to be extirpated in the 1900s may have persisted. I also developed an occupancy model for American marten in the northeastern United States using mixed-effects logistic regression based on expert opinion data. Eighteen experts from Maine, New Hampshire, Vermont and New York with backgrounds in trapping, wildlife management, and wildlife science participated in the survey. Experts were asked to estimate the probability of marten occupancy at 30 sites in the northeastern United States. Three top models described the data. Habitat covariates in those models were 1) percent canopy cover, 2) percent spruce-fir forest cover, 3) winter temperature, 4) elevation, and 5) road density. An AIC-weighted average of these three models had significant predictive ability (area under an ROC curve = 0.88) with respect to occurrence records in the northeastern United States. In addition, the model predicted that high quality habitat existed patchily along the central and northern Green Mountain spine in Vermont – where no occurrence records exist for at least a century. Top-scoring movement corridors between southern Vermont and nearby populations in northeastern Vermont/New Hampshire and New York occurred in the northern and central Green Mountains and across high resistance movement barriers in the Champlain valley. Corridors to New York were considered strong movement barriers and are unlikely to facilitate gene flow.

The American marten (Martes americana) is an endangered species in Vermont and a Regional Species of Greatest Conservation Need in the northeastern United States. Though historically widespread in northeastern forests, their range presumably contracted to northern Maine and the High Peaks region of the Adirondacks by the early 1900s. Regionally, populations appear to be in recovery. Natural recolonization is believed to have occurred in New Hampshire, northeastern Vermont and the western Adirondacks. A reintroduction effort in southern Vermont that was originally declared unsuccessful is now believed to be the source of a recently detected population in the area. However, our current knowledge of distribution, population history and population connectivity relies primarily on occurrence data from harvest records, which are limited in scope and resolution. In Vermont, where population size is estimated to be extremely low, more robust estimates of population status may be critical to continued recovery. I genotyped individuals from Maine, New York, New Hampshire, northeastern Vermont and southern Vermont at ten microsatellite loci and amplified a 320 base pair segment of the control region of mtDNA to estimate the source(s) of the two Vermont populations using statistical tests of genetic differentiation. I also used Bayesian and stochastic genetic clustering methods to estimate population genetic structure in the northeastern United States. Genetic structure exists at multiple scales in the region as a result of natural barriers to gene flow, human-mediated gene flow, and lineage sorting in relic populations. My results suggest that New Hampshire is a major source of colonization of northeastern Vermont and the population in southern Vermont is either a remnant of the reintroduction or a pre-reintroduction relic that has experienced introgression from the reintroduction stock. I identified three regions where relic populations perceived to be extirpated in the 1900s may have persisted. I also developed an occupancy model for American marten in the northeastern United States using mixed-effects logistic regression based on expert opinion data. Eighteen experts from Maine, New Hampshire, Vermont and New York with backgrounds in trapping, wildlife management, and wildlife science participated in the survey. Experts were asked to estimate the probability of marten occupancy at 30 sites in the northeastern United States. Three top models described the data. Habitat covariates in those models were 1) percent canopy cover, 2) percent spruce-fir forest cover, 3) winter temperature, 4) elevation, and 5) road density. An AIC-weighted average of these three models had significant predictive ability (area under an ROC curve = 0.88) with respect to occurrence records in the northeastern United States. In addition, the model predicted that high quality habitat existed patchily along the central and northern Green Mountain spine in Vermont – where no occurrence records exist for at least a century. Top-scoring movement corridors between southern Vermont and nearby populations in northeastern Vermont/New Hampshire and New York occurred in the northern and central Green Mountains and across high resistance movement barriers in the Champlain valley. Corridors to New York were considered strong movement barriers and are unlikely to facilitate gene flow.

Though the American marten (Martes americana) is widely distributed across northern North America, habitat use and population abundance vary widely across the range. Due to its status as a furbearer, the species has been extensively researched, resulting in a large body of knowledge about the species’ ecology, distribution, and abundance, as well as drivers of population structure and dynamics. More recently, marten research has shifted focus to genetics, habitat associations, and estimation of population state variables. The rapid increase in estimation of states such as occupancy, abundance, and density has likely been driven by the increasing accessibility of noninvasive field technology, such as noninvasive genetic sampling and remote camera trapping, and by the statistical development of ecological hierarchical models. This convergence of advances in field and analytical methods is most apparent in the now widespread application of spatial capture-recapture, an approach that produces robust estimates of population densities and abundance that can be compared across time and space. These new models are especially valuable near the edges of marten distribution where populations are often recovering from historic overexploitation, and expanding into areas they have previously been absent from. In these areas, detailed, landscape-scale understanding of marten populations is necessary in order to establish current conditions, effectively monitor changes, and predict what effect management actions may have on marten populations. I utilized these models to study marten populations in New Hampshire where marten are a species of management interest, and recent recovery has led to their removal from the state endangered species list. Through a collaborative effort with New Hampshire Fish and Game Department in the winters of 2017 and 2018, marten were surveyed across northern New Hampshire using a novel camera trap design that allows for the identification of individuals. These data were analyzed using spatial capture-recapture models, allowing me to evaluate habitat associations that explain spatial variation in marten density and provide a population status assessment for the New Hampshire marten population. Marten densities are highest in the White Mountain National Forest, though other protected lands in northern New Hampshire also appear to support larger populations. The greatest population densities coincided with deeper snows, increased canopy closure, and intermediate boreal biomass. These results provide additional support for several hypotheses explaining marten habitat use across their range while also providing novel insight that will inform active management of both marten and the habitat they occur in. In addition to the population status assessment, I evaluated the relationship between estimates of occupancy and density in New Hampshire. Though utility of non-invasive methodology can decrease research costs, the need for individual identification in spatial capture-recapture models represents a cost increase over occupancy models. My results suggest that the two are positively correlated; however, occupancy is a poor predictor of the entire range of density, especially because the variables used to predict each of the state variables are different. Thus, occupancy is likely not a good proxy for density in New Hampshire, however it could be used to track general trends through time so long as density is re-evaluated periodically.

No description available.

Thesis (M. En.)--Miami University, Institute of Environmental Sciences, 2004. / Title from first page of PDF document. Includes bibliographical references (p. 22-26).

No description available.