Interacting effects of climate change, landscape conversion, and harvest on carnivore populations at the range margin: Marten and Lynx in the northern Appalachians

Assessing the effects of climate change on threatened species requires moving beyond simple bioclimatic models to models that incorporate interactions among climatic trends, landscape change, environmental stochasticity, and species life history. Populations of marten (Martes americana) and lynx (Lynx canadensis) in southeastern Canada and the northeastern United States represent peninsular extensions of boreal ranges and illustrate the potential impact of these threats on semi-isolated populations at the range margin. Decreased snowfall may affect marten and lynx through decreased prey vulnerability and decreased competitive advantage over sympatric carnivores. I used a spatially explicit population model to assess potential effects of predicted changes in snowfall by 2055 on regional marten and lynx populations. The models' habitat rankings were derived from previous static models that correlated regional distribution with snowfall and vegetation data. Trapping scenarios were parameterized as a 10% proportional decrease in survival, and logging scenarios were parameterized as a 10% decrease in the extent of older coniferous or mixed forest. Both species showed stronger declines in the simulations due to climate change than to overexploitation or logging. Marten populations declined 40% because of climate change, 16% because of logging, and 30% because of trapping. Lynx populations declined 59% because of climate change, 36% because of trapping, and 20% in scenarios evaluating the effects of population cycles. Climate change interacted with logging in its effects on the marten and with trapping in its effects on the lynx, increasing overall vulnerability. For both species larger lowland populations were vulnerable to climate change, which suggests that contraction may occur in the core of their current regional range as well as among smaller peripheral populations. Despite their greater data requirements compared with bioclimatic models, mesoscale spatial viability models are important tools for generating more biologically realistic hypotheses regarding biotic response to climate change.