Summary1. The ability to identify regions of high functional connectivity for multiple wildlife species is of conservation interest with respect to habitat management and corridor planning. We present a method that does not require independent, field-collected data, is insensitive to the placement of source and destination sites (nodes) for modeling connectivity, and does not require the selection of a focal species. 2. In the first step of our approach, we created a cost surface that represented permeability of the landscape to movement for a suite of species. We randomly selected nodes around the perimeter of the buffered study area and used circuit theory to connect pairs of nodes. When the buffer was removed, the resulting current density map represented, for each grid cell, the probability of use by moving animals. 3. We found that using nodes that were randomly located around the perimeter of the buffered study area was less biased by node placement than randomly selecting nodes within the study area. We also found that a buffer of ≥ 20% of the study area width was sufficient to remove the effects of node placement on current density. We tested our method by creating a map of connectivity in the Algonquin to Adirondack region in eastern North America, and we validated the map with independently collected data. We found that amphibians and reptiles were more likely to cross roads in areas of high current density, and fishers (Pekania [Martes] pennanti) used areas with high current density within their home ranges. 4. Our approach provides an efficient and cost effective method of predicting areas with relatively high landscape connectivity for multiple species..

A cost or resistance surface is a representation of a landscape's permeability to animal movement or gene flow and is a tool for measuring functional connectivity in landscape ecology and genetics studies. Parameterizing cost surfaces by assigning weights to different landscape elements has been challenging however, because true costs are rarely known; thus, expert opinion is often used to derive relative weights. Assigning weights would be made easier if the sensitivity of different landscape resistance estimates to relative costs was known. We carried out a sensitivity analysis of three methods to parameterize a cost surface and two models of landscape permeability: least cost path and effective resistance. We found two qualitatively different responses to varying cost weights: linear and asymptotic changes. The most sensitive models (i.e. those leading to linear change) were accumulated least cost and effective resistance estimates on a surface coded as resistance (i.e. where high-quality elements were held constant at a low-value, and low-quality elements were varied at higher values). All other cost surface scenarios led to asymptotic change. Developing a cost surface that produces a linear response of landscape resistance estimates to cost weight variation will improve the accuracy of functional connectivity estimates, especially when cost weights are selected through statistical model fitting procedures. On the other hand, for studies where cost weights are unknown and model selection is not being used, methods where resistance estimates vary asymptotically with cost weights may be more appropriate, because of their relative insensitivity to parameterization.

No abstract

Context Global climatic changes are increasingly producing observable shifts in species distributions. It is widely believed that the northern distribution of white-tailed deer (Odocoileus virginianus) in North America is limited by cold winter temperatures and deep snow. Under all climate change scenarios, it is likely that the adverse effects of winter will diminish, which may result in a northward expansion of the distribution of white-tailed deer. Aims The goal of this project was to quantify the drivers of white-tailed deer distribution identified from a set of climate and land cover variables. We wanted to forecast changes to the northern limit on white-tailed deer distribution under several climate change scenarios. Methods We used an occupancy-modelling approach to identify the variables or combination of variables that best estimated the occupancy of white-tailed deer across a 140-site camera-observation network operating from 2013 to 2015. We validated our model using data from a mammal atlas from 1993. We used available data from climate change scenarios to predict and map changes to the northern limit of white-tailed deer distribution for three time horizons up to 2100. Key results Our models indicated that both climate and land cover had a determining influence on the northern limit of white-tailed deer distribution in our study area. Variables describing winter climate, in particular temperature and snow depth, were most closely associated with the northern edge of white-tailed deer distribution, and land cover variables added explanatory power. Our predictions suggested that white-tailed deer distribution will expand northward, given the retreat of severe winters. Conclusions White-tailed deer distribution is controlled by land-based habitat indicators and limited at a northern boundary by the severity of winter climate. Current CO2 emission scenarios indicate that winter conditions will no longer limit the northern distribution of white-tailed deer in our study area by the year 2100. Implications Under all climate change scenarios, the influx of white-tailed deer to new northern environments will likely impact the dynamics of other wildlife populations. The management of species such as moose (Alces alces) and caribou (Rangifer tarandus caribou) in these regions must anticipate the disruptive potential of white-tailed deer.

We tested whether species-specific behavioral traits could explain patterns of habitat patch occupancy by five different squirrel species in Ontario, Canada: the northern and southern flying squirrel (Glaucomys sabrinus and Glaucomys volans), the North American red squirrel (Tamiasciurus hudsonicus), the eastern chipmunk (Tamias striatus), and the eastern gray squirrel (Sciurus carolinensis). Flying squirrel species exhibit group nesting in winter, which may put them at risk of extirpation in small patches with few individuals to contribute to group nests. Flying squirrels are also volant, potentially making non-treed matrix a barrier. Our surveys revealed that G. sabrinus was most likely to occur in large patches that were embedded in landscapes with low connectivity, and least likely to occur in small patches in highly connected landscapes. Conversely, G. volans was most likely to occur in large, well-connected patches and least likely to occur in small, unconnected patches. Patch occupancy by the cursorial squirrels was not strongly influenced by patch area or isolation. These findings reinforce previous studies suggesting that an understanding of species-specific traits such as behavior is an important consideration when interpreting habitat fragmentation effects.