Jeff Bowman

DISPERSAL DISTANCE OF MAMMALS IS PROPORTIONAL TO HOME RANGE SIZE

We tested the prediction that home range area and dispersal distance in mammals are related when considered independently of body size. Regression of log- transformed data demonstrated that more variance in maximum dispersal distance could be explained by home range area (74%) than could be explained by body size (50%). The relationship between maximum dispersal distance and home range size was isometric (slope 5 1) when the square root of home range area (i.e., linear dimension of home range) was used. Thus, maximum dispersal distance was related to home range size by a single constant of 40. A linear relationship remained between these two variables after the effects of body size were removed (F 5 31.6, df 5 1, 32, P 5 3.2 3 10 26 , R 2 5 0.50). A similar isometric relationship with home range size was found for median dispersal distance (related by a multiple of 7). This isometric relationship between dispersal distance and home range size was tested using a second data source: maximum movements made by mammals after translocation, which also was linearly related to home range area (F 5 94.5, df 5 1, 23, P 5 1.3 3 10 29 , R 2 5 0.81). The slope and intercept of this relationship were not different from those of the relationship between maximum dispersal distance and home range area. We suggest that the vagility of mammals affected both home range size and dispersal distance (or movement after translocation) independently of body size, such that these movements could be predicted by home range area better than by body size alone. The resulting isometric relationship between dispersal distance and home range size has potential as a useful scaling rule for ecological practitioners.

Patch Size and Population Density: the Effect of Immigration Behavior

Many habitat fragmentation experiments make the prediction that animal population density will be positively related to fragment, or patch, size. The mechanism that is supposed to result in this prediction is unclear, but several recent reviews have demonstrated that population density often is negatively related to patch size. Immigration behavior is likely to have an important effect on population density for species that do not show strong edge effects, for species that have low emigration rates, and during short-term habitat fragmentation experiments. We consider the effect that different kinds of immigration behaviors will have on population density and we demonstrate that only a minority of possible scenarios produce positive density vs. patch size relationships. More commonly, these relationships are expected to be negative. Our results demonstrate the importance of considering autecological mechanisms, such as immigration behavior, when developing the predictions that we test in habitat fragmentation or other experiments.

Applications of graph theory to landscape genetics

We investigated the relationships among landscape quality, gene flow, and population genetic structure of fishers (Martes pennanti) in ON, Canada. We used graph theory as an analytical framework considering each landscape as a network node. The 34 nodes were connected by 93 edges. Network structure was characterized by a higher level of clustering than expected by chance, a short mean path length connecting all pairs of nodes, and a resiliency to the loss of highly connected nodes. This suggests that alleles can be efficiently spread through the system and that extirpations and conservative harvest are not likely to affect their spread. Two measures of node centrality were negatively related to both the proportion of immigrants in a node and node snow depth. This suggests that central nodes are producers of emigrants, contain high‐quality habitat (i.e., deep snow can make locomotion energetically costly) and that fishers were migrating from high to low quality habitat. A method of community detection on networks delineated five genetic clusters of nodes suggesting cryptic population structure. Our analyses showed that network models can provide system‐level insight into the process of gene flow with implications for understanding how landscape alterations might affect population fitness and evolutionary potential.

Migration behavior of white-tailed deer under varying winter climate regimes in New Brunswick

White-tailed deer (Odocoileus virginianus) exhibit a variety of migration strategies across northern portions of their range. Factors reported as being responsible for migration initiation have shown no consistent pattern. We monitored 186 radiocollared white-tailed deer from 1994 to 1998 in 2 areas of New Brunswick: a southern area with moderate and variable winter climate and a northern area with consistently severe winter climate. We determined that deer in the south contained a large proportion of conditional migrators (individuals that may or may not migrate to winter range in a given year, and may or may not remain until spring), whereas deer in the north consisted almost entirely of obligate migrators (those that annually migrate to winter range for the duration of winter). Occurrence of conditional migration appeared to be a function of climate variability, although distribution of the behavior among individual deer was influenced by migration distance. Initiation of autumn migration in the south was related to snow depth for most deer and represented a response to the proximate cue of the onset of limiting conditions. Autumn migration in the north appeared to be a response to seasonal cues, and the direct influence of snow depth was reduced. Initiation of spring migration in the 2 study areas showed a similar pattern. Migration distance may represent a factor influencing distribution of migrational cues among individual deer within a population. The effect of winter climate variability on deer migration behavior may account for the disparity in behavior reported in the literature. The differences in migration behavior have implications for deer management surveys in northern areas where deer yarding occurs. Managers have assumed that deer observed during winter surveys were on winter range, hut this may not be a reasonable assumption in areas with variable winter climates.

Hybridization between escaped domestic and wild American mink (Neovison vison)

The release of domesticated organisms into natural populations may adversely affect these populations through predation, resource competition, and the introduction of disease. Additionally, the potential for hybridization between wild and domestic conspecifics is of great concern because it can alter the evolutionary integrity of the affected populations. Wild American mink (Neovison vison) populations may be threatened not only by competition for resources with domestic mink originating from farms, but by breeding with such escapees. Using 10 microsatellite loci, we genotyped mink from Ontario, Canada, sampled from two farms, two putatively mixed populations in regions surrounding the mink farms, and two wild populations with no recent history of mink farming. Using individual‐based Bayesian population assignment, we identified four population clusters, including one wild, and three domestic populations. The latter were not clustered by farm but rather by distinct line‐bred colour phases. Population clustering also identified domestic and hybrid mink in the free‐ranging populations. Nearly two‐thirds of the mink sampled in the two putatively mixed populations (78% and 43%) were either farm escapees or descendants of escapees. Principal components analysis of allele frequencies supported our Bayesian assignment results. The power of our assignment test was assessed using simulated hybrid genotypes which suggested that our overall correct classification rate was 96.2%. The overwhelming presence of domestic animals and their hybridization with mink in natural populations is of great concern for the future sustainability of wild mink populations.

Landscape context and small-mammal abundance in a managed forest

We assessed whether small-mammal abundance was related to landscape context, when context was considered independently of within-stand vegetation and at different spatial extents. The study took place in an industrial forest in northwestern New Brunswick. Within-stand vegetation models explained 9‐32% of the deviance in the abundance of individuals from the four most abundant species: red-backed voles; deer mice; short-tailed shrews; and woodland jumping mice. Landscape context was related to the distributions of two species: red-backed voles were less abundant within contexts of softwood plantations; and jumping mouse abundance was directly related to the amount of softwood forest. Variables measured at the largest radii of landscape context (500 m) were never significantly associated with the abundance of small mammals. Most species appeared robust to forest management with the exception of the negative relationship between redbacked voles and softwood plantations. # 2001 Elsevier Science B.V. All rights reserved.

The Effect of Map Boundary on Estimates of Landscape Resistance to Animal Movement

Background Artificial boundaries on a map occur when the map extent does not cover the entire area of study; edges on the map do not exist on the ground. These artificial boundaries might bias the results of animal dispersal models by creating artificial barriers to movement for model organisms where there are no barriers for real organisms. Here, we characterize the effects of artificial boundaries on calculations of landscape resistance to movement using circuit theory. We then propose and test a solution to artificially inflated resistance values whereby we place a buffer around the artificial boundary as a substitute for the true, but unknown, habitat. Methodology/Principal Findings We randomly assigned landscape resistance values to map cells in the buffer in proportion to their occurrence in the known map area. We used circuit theory to estimate landscape resistance to organism movement and gene flow, and compared the output across several scenarios: a habitat-quality map with artificial boundaries and no buffer, a map with a buffer composed of randomized habitat quality data, and a map with a buffer composed of the true habitat quality data. We tested the sensitivity of the randomized buffer to the possibility that the composition of the real but unknown buffer is biased toward high or low quality. We found that artificial boundaries result in an overestimate of landscape resistance. Conclusions/Significance Artificial map boundaries overestimate resistance values. We recommend the use of a buffer composed of randomized habitat data as a solution to this problem. We found that resistance estimated using the randomized buffer did not differ from estimates using the real data, even when the composition of the real data was varied. Our results may be relevant to those interested in employing Circuitscape software in landscape connectivity and landscape genetics studies.

Using a genetic network to parameterize a landscape resistance surface for fishers, Martes pennanti

Knowledge of dispersal‐related gene flow is important for addressing many basic and applied questions in ecology and evolution. We used landscape genetics to understand the recovery of a recently expanded population of fishers (Martes pennanti) in Ontario, Canada. An important focus of landscape genetics is modelling the effects of landscape features on gene flow. Most often resistance surfaces in landscape genetic studies are built a priori based upon nongenetic field data or expert opinion. The resistance surface that best fits genetic data is then selected and interpreted. Given inherent biases in using expert opinion or movement data to model gene flow, we sought an alternative approach. We used estimates of conditional genetic distance derived from a network of genetic connectivity to parameterize landscape resistance and build a final resistance surface based upon information‐theoretic model selection and multi‐model averaging. We sampled 657 fishers from 31 landscapes, genotyped them at 16 microsatellite loci, and modelled the effects of snow depth, road density, river density, and coniferous forest on gene flow. Our final model suggested that road density, river density, and snow depth impeded gene flow during the fisher population expansion demonstrating that both human impacts and seasonal habitat variation affect gene flow for fishers. Our approach to building landscape genetic resistance surfaces mitigates many of the problems and caveats associated with using either nongenetic field data or expert opinion to derive resistance surfaces.

Thermal Properties of Tree Cavities During Winter in a Northern Hardwood Forest

Abstract Tree cavities likely vary in their thermal quality for cavity-nesting animals, which could be especially important during winter. We conducted a winter field experiment to test whether cavities vary either in their buffering capacity or in their mean temperature according to predictable characteristics. We found that cavities buffered temperature and that there was a lag effect in temperature that appeared to be related to heating and cooling. Diameter at breast height was the most important variable influencing cavity temperature during the day, with smaller trees warming up more. During the night, diameter at breast height and tree decay class were important, such that larger, live trees cooled down less. Maintaining live trees with cavities in managed forests should be considered in addition to snag retention, because live trees appear to provide warmer structures during winter.

Landscape connectivity for wildlife: development and validation of multispecies linkage maps

Summary 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. 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. 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. Our approach provides an efficient and cost effective method of predicting areas with relatively high landscape connectivity for multiple species..