Assessing the influence of resource covariates at multiple spatial scales: an application to forest-dwelling caribou faced with intensive human activity

Efforts in isolating the relative effects of resources and disturbances on animal-distribution patterns remain hindered by the difficulty of accounting for multiple scales of resource selection by animals with seasonally dynamic drivers. We developed multi-scale, seasonal models to explore how local resource selection by the threatened forest-dwelling woodland caribou (Rangifer tarandus caribou) was influenced by both broad-scale landscape context and local resource heterogeneity in the intensively managed region of Charlevoix, Québec, Canada, located on the southern border of the North American caribou range. We estimated resource selection functions using 23 GPS-collared caribou monitored from 2004 to 2006 and landscape data on vegetation classes, terrain conditions, and roads. We found evidence of thresholds in road “proximity” effects (up to 1.25 km), which underscores the importance of including landscape context variables in addition to locally measured variables, and of fitting seasonal-specific models given temporal variation in the magnitude of selection and optimal scale of measurement. Open lichen woodlands were an important cover type for caribou during winter and spring, whereas deciduous forests, wetlands, and even young disturbed stands became important during calving and summer. Caribou consistently avoided roads and rugged terrain conditions at both local and landscape levels. Landscape context fundamentally constrains the choices available to animals, and we showed that failing to consider landscape context, or arbitrarily choosing an inappropriate scale for measuring covariates, may provide biased inferences with respect to habitat selection patterns. Effective habitat management for rare or declining species should carefully consider the hierarchical nature of habitat selection.     

Landscape context and selection for forest edge by breeding Brown-headed Cowbirds

We evaluated support for four alternate hypotheses explaining the distribution of breeding Brown-headed Cowbirds (Molothrus ater) in forests at varying distances from the forest edge in three Midwestern USA landscapes with varying amounts of forest fragmentation (core forest area ranged from 5 to 70%). We focused on breeding cowbirds’ use of forest because of the risk of nest parasitism to forest-dwelling hosts and to identify factors affecting breeding cowbird habitat selection. We compared distances of cowbird locations in the forest from the forest edge (“edge distances”) to distances of random forest locations in the entire landscape or within individual cowbird home ranges. We analyzed 1322 locations of 84 cowbirds across three landscapes. We found support for the landscape context hypothesis that breeding cowbird preference for forest edge varied with landscape context. Ninety percent of cowbird locations were within 150–350 m of forest edge, despite the overall availability of forest at greater distances from edge (as far as 500–1450 m) both within cowbird home ranges and the entire forested landscape. Cowbird preference for edge varied by landscape context largely due to differences in the availability of forest edge. In a highly fragmented forest cowbirds utilized the entire forest and likely viewed it as “all edge.” In less fragmented forests, cowbirds preferred edge. We consider how variation in cowbird edge preference might relate to patterns in host abundance, host diversity, and host quality because cowbird movements indicate they are capable of using forest farther from edges.     

Movement ecology of wolves across an industrial landscape supporting threatened populations of woodland caribou

Woodland caribou (Rangifer tarandus caribou) are a species of increasing conservation concern across North America. Throughout much of boreal Canada, human developments, including forestry and energy development, are now accepted causes of the decline in the number and distribution of caribou. One of the hypothesised mechanisms for the decline is altered predator–prey dynamics. We quantified the impacts of a variety of industrial activities on gray wolf (Canis lupus) and caribou interactions at a regional scale. We used animal locations collected with global positioning system collars and field data to examine how a range of industrial developments influenced the movements of wolves. We quantified the speed of wolf movements and the tortuosity of movement paths at two spatiotemporal scales across forested boreal and mountainous environments occupied by woodland caribou. Habitat and disturbance features better explained wolf movements during the weekly scale. In general, linear movements increased during winter, which paralleled past studies that suggested linear travel by wolves was associated with deep snow and the increased maintenance and patrol of territories. Wolves decreased movement rates but not sinuosity within close proximity to disturbance features, thus implying behaviours near such features were more closely associated with prey searching and hunting. Alternatively, wolves increased movement rates and linear travel through areas with high densities of linear and non-linear industrial features; this response suggested that wolves avoided spending time in high-risk areas associated with human activities. Results of this study further our understanding of wolf distribution and behaviour in habitats supporting populations of caribou within a matrix of industrial developments.     

Spatial versus temporal variation in precipitation in a semiarid ecosystem

Spatial and temporal variations in precipitation are central features of semiarid ecosystems, influencing patterns of plant productivity and the distribution of native fauna. Although temporal variation in precipitation has been studied extensively, far less is known about the spatial scale and pattern of precipitation variability in semiarid regions. I used long-term precipitation records to examine spatial variation across the 63 km² Central Plains Experimental Range in northeastern Colorado, and across the 117,000 km² region of shortgrass steppe in eastern Colorado. Relative to temporal variation, spatial variation was low at scales <10 km, increased linearly across scales of 40–120 km, and was nearly equal in magnitude to temporal variation across distances of 120–160 km. Although I hypothesized that most spatial variation would be generated by early-summer convective thunderstorms in June, I found that the magnitude and spatial pattern of variation was similar for precipitation received in June compared to cumulative precipitation received during the full growing season. The degree of spatial autocorrelation in precipitation across all distances that I evaluated was similar for drought, dry, above-average and wet years. Across distances of 10–120 km, spatial variation within a single growing season was approximately two times greater than spatial variation in long-term mean growing-season precipitation, indicating spatial shifting in the locations of patches of high and low precipitation over multiple years. Overall, these findings suggest spatial variation at scales of 10–160 km may have been an important factor influencing vegetation patterns and migratory fauna of the shortgrass steppe, and have implications for livestock producers and future assessments of climate change.     

The influence of research scale on bald eagle habitat selection along the lower Hudson River,New York (USA)

As the concepts of landscape ecology have been incorporated into otherdisciplines, the influence of spatial patterns on animal abundance anddistribution has attracted considerable attention. However, there remains asignificant gap in the application of landscape ecology theories and techniquesto wildlife research. By combining landscape ecology techniques withtraditionalwildlife habitat analysis methods, we defined an organism-centeredperspectivefor breeding bald eagles (Haliaeetus leucocephalus) alongthe Hudson River, New York, USA. We intensively monitored four pairs ofbreedingeagles during the 1999 and 2000 breeding seasons, and collected detailedinformation on perch and forage locations. Our analysis focused on threecritical habitat elements: available perch trees, access to foraging areas, andfreedom from human disturbance. We hypothesized that eagle habitat selectionrelative to each of these elementswould vary with the spatial scale of analysis, and that these scalingrelationships would vary among habitat elements. We investigated two elementsofspatial scale: grain and local extent. Grain was defined as the minimum mappingunit; local extent was defined by the size of an analysis window placed aroundeach focal point. For each habitat element, we quantified habitat use over arange of spatial scales. Eagles displayed scale-dependent patterns of habitatuse in relation to all habitat features, including multi-scale andthreshold-like patterns. This information supports the existence ofscale-dependant relationships in wildlife habitat use and allowed for a moreaccurate and biologically relevant evaluation of Hudson River breeding eagle habitat.This revised version was published online in May 2005 with corrections to the Cover Date.     

Disentangling habitat and social drivers of nesting patterns in songbirds

Nest locations of breeding birds are often spatially clustered. This tendency to nest together has generally been related to a patchy distribution of nesting habitat in landscape studies, but behavioral studies of species with clustered breeding patterns draw attention to the importance of social and biotic factors. Indeed, it is becoming increasingly apparent that the breeding system of many territorial, migrant birds may be semi-colonial. The reasons for, and extent of, spatial clustering in their breeding systems are not well understood. Our goal was to tease apart the influence of habitat availability and social drivers of clustered breeding in a neotropical migrant species, the hooded warbler (Wilsonia citrina). To test alternative hypotheses related to clustered habitat or conspecific attraction, we combined a habitat classification based on remote sensing with point pattern analysis of nesting sites. Nest locations (n = 150, 1999–2004), collected in a 1213 ha forested area of Southern Ontario (Canada), were analyzed at multiple spatial scales. Ripley’s K and pair-correlation functions g (uni- and bivariate) were used to test whether nests were clustered merely because potential nesting habitat was also clustered, or whether nests were additionally clustered with respect to conspecifics. Nest locations tended to be significantly clustered at intermediate distances (particularly between 240 and 420 m). Nests were randomly distributed within available habitat at larger distance scales, up to 1500 m. A reasonable hypothesis to explain the detected additional clustering, and one that is consistent with the results of several behavioral studies, is that females pack their nests more tightly than the available habitat requires to be situated closer to their neighbors’ mates. Linking spatially explicit, point pattern analysis with strong inference based on Monte Carlo tests may bring us closer to understanding the generality and reasons behind conspecific attraction at different spatial scales. F. Csillag—deceased.     

Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity

Context

High-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species’ potential to link patches or populations are of importance.

Objectives

We introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories’ plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range.

Methods

We used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species’ range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature.

Results

Simulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corroborating previous findings for this species.

Conclusions

We show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting migratory connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.

     

Maintaining or restoring connectivity of modified landscapes: evaluating the least-cost path model with multiple sources of ecological information

Habitat connectivity is an important element of functioning landscapes for mobile organisms. Maintenance or creation of movement corridors is one conservation strategy for reducing the negative effects of habitat fragmentation. Numerous spatial models exist to predict the location of movement corridors. Few studies, however, have investigated the effectiveness of these methods for predicting actual movement paths. We used an expert-based model and a resource selection function (RSF) to predict least-cost paths of woodland caribou. Using independent data for model evaluation, we found that the expert-based model was a poor predictor of long-distance animal movements; in comparison, the RSF model was effective at predicting habitat selection by caribou. We used the Path Deviation Index (PDI), cumulative path cost, and sinuosity to quantitatively compare the spatial differences between inferred caribou movement paths and predicted least-cost paths, and quasi-random null models of directional movement. Predicted movement paths were on average straighter than inferred movement paths for collared caribou. The PDI indicated that the least-cost paths were no better at predicting the inferred paths than either of two null models—straight line paths and randomly generated paths. We found statistically significant differences in cumulative cost scores for the main effects of model and path type; however, post-hoc comparisons were non-significant suggesting no difference among inferred, random, and predicted least cost paths. Paths generated from an expert based cost surface were more sinuous than those premised on the RSF model, but neither differed from the inferred path. Although our results are specific to one species, they highlight the importance of model evaluation when planning for habitat connectivity. We recommend that conservation planners adopt similar techniques when validating the effectiveness of movement corridors for other populations and species.     

Aspen patch and migratory bird relationships in the northern Yellowstone ecosystem

We evaluated the effects of aspen patch area and orientation (relative to North and an elevational gradient) on the early breeding season abundance and species richness of migratory and resident birds in the northern ungulate winter range of the Yellowstone ecosystem, USA. Using an information-theoretic model selection approach, we found patch area and basal area of aspen to be the most important covariates for long distance migrants, and patch orientation relative to elevational gradient the most important covariate for residents/short-distance migrants. Basal area of live aspen and aspen snags was marginally important for both migratory strategies, likely because aspen snags are an important habitat for most cavity-nesting species. Landscape ecological theory postulates passive interception of dispersing or migrating organisms by patches of suitable habitat. Our results suggest that residents/short-distance migrants are intercepted by patches that are oriented perpendicular to the elevational gradient of our study region resulting in greater abundances and species richness in those patches. However, long-distance migrants appear to use aspen patches without regard to orientation, but rather to patch area.     

Post-storm surveys reveal large-scale spatial patterns and influences of site factors,forest structure and diversity in endemic bark-beetle populations

The storm that struck France on december 26^th and 28^th 1999 felled 140 million m³ of timber and had a high economic, social and landscape impact. This event offered the opportunity to study large-scale patterns in populations of forest insect pests that would benefit from the abundant breeding material. A large-scale survey was carried out in France in 2000 to sample the most frequently observed species developing on spruce (Ips typographus, Pityogene schalcographus) and pine (Tomicus piniperda, Ips sexdentatus) in 898 locations distributed throughout wind-damaged areas. The local abundance of each species scored on a 0 to 5 scale was analysed using geostatistical estimators to explore the extent and intensity of spatial autocorrelation, and was related to site, stand, and neighbourhood landscape metrics of the forest cover (in particular the interconnection with broadleaf forest patches) found within dispersal distance. All species but I. sexdentatus, which was much less abundant, displayed large-scale spatial dependence and regional variations in abundance. Lower infestation levels per tree (windfalls and standing trees) were observed in stands with a high proportion of wind-damaged trees, which was interpreted as the result of beetles distributing themselves among the available breeding material. More infestations were observed in wind-broken trees as compared to wind-felled trees. More importantly, populations showed significant relationships with the structure of coniferous stands (in particular with the number of coniferous patches). T. piniperda population levels were negatively correlated to the amount of coniferous edge shared with broadleaf forest patches, possibly because of the disruptive effect of non-host volatiles on host-finding processes at the landscape-scale. The differences observed between species regarding patterns and relationships to site, stand, and forest cover characteristics are discussed in relation to the ecological characteristics of each species.     

Timing of breeding in <Emphasis Type="Italic">Ochrotomys nuttalli</Emphasis> and <Emphasis Type="Italic">Peromyscus leucopus</Emphasis> is related to a latitudinal isotherm

Previous comparative studies on patterns of reproduction in small-mammal species focus primarily on latitudinal differences in average litter size. Few studies compare reproductive patterns among northern and southern populations at the landscape scale. Our study compares differences in seasonal patterns of reproduction in northern and southern populations of the golden mouse, Ochrotomys nuttalli, and the white-footed mouse, Peromyscus leucopus. These are remarkably similar species with regard to bioenergetics, body mass, feeding behavior, home-range size, natural history, nest-site preference, and periods of activity. Both species also exhibit very similar intraspecific seasonal patterns of reproduction across their respective geographic ranges. We found that O. nuttalli and P. leucopus switch from a summer breeding season, extending from late spring through early autumn in the north to a winter breeding season extending from late autumn through early spring in the south, near the isotherm where mean annual temperature is 15.6°C (60°F), or approximately 35° N latitude. This latitudinal isotherm provides a geographic benchmark to address future changes in patterns of reproduction attributed to climate change. Findings also suggest that length of the breeding season and patterns of reproduction between species partially explain why P. leucopus is typically more abundant than O. nuttalli in similar habitat types.     

Landscape effects on mallard habitat selection at multiple spatial scales during the non-breeding period

Previous studies that evaluated effects of landscape-scale habitat heterogeneity on migratory waterbird distributions were spatially limited and temporally restricted to one major life-history phase. However, effects of landscape-scale habitat heterogeneity on long-distance migratory waterbirds can be studied across the annual cycle using new technologies, including global positioning system satellite transmitters. We used Bayesian discrete choice models to examine the influence of local habitats and landscape composition on habitat selection by a generalist dabbling duck, the mallard (Anas platyrhynchos), in the midcontinent of North America during the non-breeding period. Using a previously published empirical movement metric, we separated the non-breeding period into three seasons, including autumn migration, winter, and spring migration. We defined spatial scales based on movement patterns such that movements >0.25 and <30.00 km were classified as local scale and movements >30.00 km were classified as relocation scale. Habitat selection at the local scale was generally influenced by local and landscape-level variables across all seasons. Variables in top models at the local scale included proximities to cropland, emergent wetland, open water, and woody wetland. Similarly, variables associated with area of cropland, emergent wetland, open water, and woody wetland were also included at the local scale. At the relocation scale, mallards selected resource units based on more generalized variables, including proximity to wetlands and total wetland area. Our results emphasize the role of landscape composition in waterbird habitat selection and provide further support for local wetland landscapes to be considered functional units of waterbird conservation and management.     

The response of elephants to the spatial heterogeneity of vegetation in a Southern African agricultural landscape

Based on the agricultural landscape of the Sebungwe in Zimbabwe, we investigated whether and how the spatial distribution of the African elephant (Loxodonta africana) responded to spatial heterogeneity of vegetation cover based on data of the early 1980s and early 1990s. We also investigated whether and how elephant distribution responded to changes in spatial heterogeneity between the early 1980s and early 1990s. Vegetation cover was estimated from a normalised difference vegetation index (NDVI). Spatial heterogeneity was estimated from a new approach based on the intensity (i.e., the maximum variance exhibited when a spatially distributed landscape property such as vegetation cover is measured with a successively increasing window size or scale) and dominant scale (i.e., the scale or window size at which the intensity is displayed). We used a variogram to quantify the dominant scale (i.e., range) and intensity (i.e., sill) of NDVI based congruent windows (i.e., 3.84 km × 3.84 km in a 61 km × 61 km landscape). The results indicated that elephants consistently responded to the dominant scale of spatial heterogeneity in a unimodal fashion with the peak elephant presence occurring in environments with dominant scales of spatial heterogeneity of around 457–734 m. Both the intensity and dominant scale of spatial heterogeneity predicted 65 and 68% of the variance in elephant presence in the early 1980s and in the early 1990s respectively. Also, changes in the intensity and dominant scale of spatial heterogeneity predicted 61% of the variance in the change in elephant distribution. The results imply that management decisions must take into consideration the influence of the levels of spatial heterogeneity on elephants in order to ensure elephant persistence in agricultural landscapes.     

Making molehills out of mountains: landscape genetics of the Mojave desert tortoise

Heterogeneity in habitat often influences how organisms traverse the landscape matrix that connects populations. Understanding landscape connectivity is important to determine the ecological processes that influence those movements, which lead to evolutionary change due to gene flow. Here, we used landscape genetics and statistical models to evaluate hypotheses that could explain isolation among locations of the threatened Mojave desert tortoise (Gopherus agassizii). Within a causal modeling framework, we investigated three factors that can influence landscape connectivity: geographic distance, barriers to dispersal, and landscape friction. A statistical model of habitat suitability for the Mojave desert tortoise, based on topography, vegetation, and climate variables, was used as a proxy for landscape friction and barriers to dispersal. We quantified landscape friction with least-cost distances and with resistance distances among sampling locations. A set of diagnostic partial Mantel tests statistically separated the hypotheses of potential causes of genetic isolation. The best-supported model varied depending upon how landscape friction was quantified. Patterns of genetic structure were related to a combination of geographic distance and barriers as defined by least-cost distances, suggesting that mountain ranges and extremely low-elevation valleys influence connectivity at the regional scale beyond the tortoises’ ability to disperse. However, geographic distance was the only influence detected using resistance distances, which we attributed to fundamental differences between the two ways of quantifying friction. Landscape friction, as we measured it, did not influence the observed patterns of genetic distances using either quantification. Barriers and distance may be more valuable predictors of observed population structure for species like the desert tortoise, which has high dispersal capability and a long generation time.     

莲属植物资源和育种研究进展

介绍了莲属植物的分布及分类，探讨了莲的生态型及栽培品种类型的划分，总结了野生莲和莲栽培品种的遗传多样性研究进展；介绍了莲属植物的资源和育种研究，资源收集、保存及品种选育现状；梳理了莲在组学、遗传图谱构建及基因挖掘等方面的研究进展；对今后莲属植物资源收集、保护和利用提出建议，认为品种的优质、多样化和专用化是莲属植物的育种方向。     

The influence of landscape characteristics and home-range size on the quantification of landscape-genetics relationships

A common approach used to estimate landscape resistance involves comparing correlations of ecological and genetic distances calculated among individuals of a species. However, the location of sampled individuals may contain some degree of spatial uncertainty due to the natural variation of animals moving through their home range or measurement error in plant or animal locations. In this study, we evaluate the ways that spatial uncertainty, landscape characteristics, and genetic stochasticity interact to influence the strength and variability of conclusions about landscape-genetics relationships. We used a neutral landscape model to generate 45 landscapes composed of habitat and non-habitat, varying in percent habitat, aggregation, and structural connectivity (patch cohesion). We created true and alternate locations for 500 individuals, calculated ecological distances (least-cost paths), and simulated genetic distances among individuals. We compared correlations between ecological distances for true and alternate locations. We then simulated genotypes at 15 neutral loci and investigated whether the same influences could be detected in simple Mantel tests and while controlling for the effects of isolation-by-distance using the partial Mantel test. Spatial uncertainty interacted with the percentage of habitat in the landscape, but led to only small reductions in correlations. Furthermore, the strongest correlations occurred with low percent habitat, high aggregation, and low to intermediate levels of cohesion. Overall genetic stochasticity was relatively low and was influenced by landscape characteristics.     

Seismic Cutlines,Changing Landscape Metrics and Grizzly Bear Landscape use in Alberta

Besides providing habitat to the grizzly bear (Ursus arctos) and other wildlife, the Rocky Mountain foothills of Alberta, Canada hosts considerable mining, seismic oil and gas exploration and production, and forest harvesting activities. Worldwide, such human activities influence the configuration and composition of the landscape. We assessed seismic cutline effects on landscape structure and grizzly bear use during early summer of 1999 and 2000. We studied five female and two male bears, which were GPS-collared in the spring following den emergence. The area available to this population was stratified into 49 km² hexagon-shaped sub-landscapes. The scale of this stratification was determined by patterns of bear movement. Fourteen compositional and configurational landscape metrics were calculated within each landscape unit, and bear use points were pooled or ‘binned’ within each unit. Landscape use was related to landscape metrics using a Generalized Linear Model (GLM). We found that seismic cutline proportion did not explain landscape use by grizzly bears; however secondary effects of cutlines on landscape structure did. Declining use was mainly associated with increasing proportions of closed forest, and increasing variation of inter-patch distances, while use was mainly increasing with increasing mean patch size. An earlier investigation had demonstrated that adding seismic cutlines to grizzly bear habitat caused increases in the variation of inter-patch distances. Since the landscape structure of this grizzly bear population will continue to change as a function of increased levels of resource extraction activities in the near future, it is crucial to further study the detailed meaning of landscape structure at the large and small scale for effective conservation efforts.     

Landscape structure influences continental distribution of hantavirus in deer mice

We hypothesized that landscape structure affects movement of individuals through the landscape, which affects the rate and pattern of disease transmission. Based on this hypothesis, we predicted a relationship between landscape structure and disease incidence in spatially structured populations. We tested this prediction for hantavirus incidence in deer mice (Penomysens moniculatus), using a novel index of habitat fragmentation for transect data. A series of four stepwise logistic regression analyses were conducted on serological and ecological data from 2837 mice from 101 sites across Canada. The significant variables, ranked in decreasing order of size of their effect on virus incidence were: human buildings, landscape composition (amount of deer mouse habitat in the 1-km radius landscape surrounding each site), landscape configuration (fragmentation of deer mouse habitat in the 1-km radius landscape surrounding each site), mean annual temperature, and seasonal variation. Our results suggest that epidemiological models should consider not only the demographic structure of the host population, but its spatial structure as well, as inferred from landscape structure. Landscape structure can have a greater effect on the pattern of distribution of a virus in its host population than other ecological variables such as climate and seasonal change. The usefulness of landscape data in epidemiological models depends on the use of the appropriate spatial scale, which can be determined empirically. Epidemiological models with a spatially structured host population can benefit from the explicit consideration of landscape structure.     

Quantifying patch distribution at multiple spatial scales: Applications to wildlife-habitat models

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.     

Quantifying patch distribution at multiple spatial scales: Applications to wildlife-habitat models

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.