Habitat and climatic associations of climate-sensitive species along a southern range boundary.

Climate change and habitat loss are recognized as important drivers of shifts in wildlife species' geographic distributions. While often considered independently, there is considerable overlap between these drivers, and understanding how they contribute to range shifts can predict future species assemblages and inform effective management. Our objective was to evaluate the impacts of habitat, climatic, and anthropogenic effects on the distributions of climate-sensitive vertebrates along a southern range boundary in Northern Michigan, USA. We combined multiple sources of occurrence data, including harvest and citizen-science data, then used hierarchical Bayesian spatial models to determine habitat and climatic associations for four climate-sensitive vertebrate species (American marten [Martes americana], snowshoe hare [Lepus americanus], ruffed grouse [Bonasa umbellus] and moose [Alces alces]). We used total basal area of at-risk forest types to represent habitat, and temperature and winter habitat indices to represent climate. Marten associated with upland spruce-fir and lowland riparian forest types, hares with lowland conifer and aspen-birch, grouse with lowland riparian hardwoods, and moose with upland spruce-fir. Species differed in climatic drivers with hares positively associated with cooler annual temperatures, moose with cooler summer temperatures and grouse with colder winter temperatures. Contrary to expectations, temperature variables outperformed winter habitat indices. Model performance varied greatly among species, as did predicted distributions along the southern edge of the Northwoods region. As multiple species were associated with lowland riparian and upland spruce-fir habitats, these results provide potential for efficient prioritization of habitat management. Both direct and indirect effects from climate change are likely to impact the distribution of climate-sensitive species in the future and the use of multiple data types and sources in the modelling of species distributions can result in more accurate predictions resulting in improved management at policy-relevant scales.

Global state and potential scope of investments in watershed services for large cities.

Investments in watershed services (IWS) programs, in which downstream water users pay upstream watershed service suppliers for actions that protect drinking water, are increasing in number and scope. IWS programs represent over $170 million of investment in over 4.3 million ha of watersheds, providing water to over 230 million people. It is not yet fully clear what factors contribute to the establishment and sustainability of IWS. We conducted a representative global analysis of 416 of the world's largest cities, including 59 (14%) with IWS programs. Using random forest ensemble learning methods, we evaluated the relative importance of social and ecological factors as predictors of IWS presence. IWS programs are more likely present in source watersheds with more agricultural land and less protected area than otherwise similar watersheds. Our results suggest potential to expand IWS as a strategy for drinking water protection and also contribute to decisions regarding suitable program locations.