Spatial distribution, connectivity, and the influence of scale: habitat availability for the endangered Mona Island rock iguana

The Caribbean region is one of the five leading biodiversity hotspots in the world. Analysis of the spatial structure of critical habitats and how it affects endemic species in this region is essential baseline information for biodiversity monitoring and management. We quantified and evaluated the spatial structure and connectivity of depression forests on Mona Island and their potential impact on Mona Island rock iguana habitat, as a framework to assess spatial distribution, connectivity, and the issue of scale in small and widely dispersed habitats. Using IKONOS imagery, we mapped and delineated depression forests at four different scales (minimum mapping units: <100, 100, 500, and 1,000 m), and calculated landscape metrics describing their spatial structure, and connectivity, for each map resolution. Our approach resulted in a more detailed map than previously described maps, providing better information on habitat connectivity for iguanas. The comparison of the island landscape mapped at different scales provided evidence on how changing scales affect the output of spatial metrics and may have a significant impact when planning decisions and assigning conservation priorities. It also highlighted the importance of adequate ecological scales when addressing landscape management and conservation priorities. The analysis of landscapes at multiple scales provided a mechanism to evaluate the role of patch detection and its effect on the interpretation of connectivity and spatial structure of suitable areas for species with small and widely dispersed habitats. These methodologies can be applied other species, in different environments, with similar limitations related to connectivity and habitat availability.     

Influence of Vegetation on Bat Use of Riparian Areas at Multiple Spatial Scales

ABSTRACT Research on habitat use by bats typically occurs at a single fine spatial scale, despite recent work demonstrating the importance of considering multiple spatial scales when investigating vertebrate habitat selection. We assessed bat use of 118 stream reaches located throughout the Oregon Coast Range, USA, and measured vegetation characteristics at 3 spatial scales surrounding each of these locations. We used an information-theoretic approach to determine vegetation characteristics most closely related to bat activity and a multilevel modeling approach to evaluate variation in bat activity at different spatial scales. Characteristics of vegetation at the finest spatial scale explained more variation in bat activity than did characteristics of vegetation at broader spatial scales, suggesting that fine-scale anthropogenic or natural disturbance events that alter cover of shrubs or trees in riparian areas are likely to influence bat habitat use. The influence of vegetation on activity varied by species of bat and appeared to operate more strongly through constraints imposed by vegetation architecture than through influences on abundance of insect prey. This diversity of responses to vegetation characteristics among bat species suggests that the best strategy for biodiversity conservation over broad spatial scales is maintenance or creation of a diversity of riparian vegetation conditions. We recommend that land managers planning to manipulate riparian vegetation strive to create diversity in shrub coverage, canopy coverage, and open space above the stream channel to promote foraging habitat for all species.     

Identifying multiscale habitat factors influencing koala (Phascolarctos cinereus) occurrence and management in Ballarat, Victoria, Australia

Summary   Modelling for the conservation of koala ( Phascolarctos cinereus ) populations has primarily focused on natural habitat variables (e.g. tree species, soil types and soil moisture). Until recently, limited consideration has been given to modelling the effects of the landscape context (e.g. habitat area, habitat configuration and roads). Yet, the combined influence of natural habitats and anthropogenic impacts at multiple spatial scales are likely to be important determinants of where koala populations occur and remain viable in human-modified landscapes. The study tested the importance of multiscale habitat variables on koala occurrence in Ballarat, Victoria, Australia. The models focused at three spatial scales: site ( <  1 ha), patch (1–100 ha), and landscape (100–1000 s ha). Logistic regression and hierarchical partitioning analyses were used to rank alternative models and key explanatory variables.
The results showed that an increased likelihood of koala presence in fragmented landscapes in the urban–forest interface (as opposed to larger blocks of forest habitat) can best be explained by the positive effects of soil fertility and the presence of preferred koala tree species in these fragmented areas. If koalas are to be effectively conserved in Ballarat, it is critical to (i) protect remaining core areas of high-quality habitat, including regenerating areas; (ii) protect scattered habitat patches which provide connectivity; and (iii) develop and implement habitat restoration programmes to improve habitat connectivity and enhance opportunities for safe koala movement between habitat patches intersected by main roads.     

Developing landscape habitat models for rare amphibians with small geographic ranges: a case study of Siskiyou Mountains salamanders in the western USA

To advance the development of conservation planning for rare species with small geographic ranges, we determined habitat associations of Siskiyou Mountains salamanders (Plethodon stormi) and developed habitat suitability models at fine (10 ha), medium (40 ha), and broad (202 ha) spatial scales using available Geographic Information Systems data and logistic regression analysis with an information theoretic approach. Across spatial scales, there was very little support for models with structural habitat features, such as tree canopy cover and conifer diameter. Model-averaged 95% confidence intervals for regression coefficients and associated odds ratios indicated that the occurrence of Siskiyou Mountains salamanders was positively associated with rocky soils and Pacific madrone (Abutus menziesii) and negatively associated with elevation and white fir (Abies concolor); these associations were consistent across 3 spatial scales. The occurrence of this species also was positively associated with hardwood density at the medium spatial scale. Odds ratios projected that a 10% decrease in white fir abundance would increase the odds of salamander occurrence 3.02–4.47 times, depending on spatial scale. We selected the model with rocky soils, white fir, and Oregon white oak (Quercus garryana) as the best model across 3 spatial scales and created habitat suitability maps for Siskiyou Mountains salamanders by projecting habitat suitability scores across the landscape. Our habitat suitability models and maps are applicable to selection of priority conservation areas for Siskiyou Mountains salamanders, and our approach can be easily adapted to conservation of other rare species in any geographical location.     

Environmental Suitability and Distribution of the Caucasian Rock Agama, Paralaudakia caucasia （Sauria： Agamidae） in Western and Central Asia

Predictive potential distribution modeling is crucial in outlining habitat usage and establishing conservation management priorities. In this paper we provide detailed data on the distribution of the Caucasian rock agama Para- laudakia caucasia, and use species distribution models （MAXENT） to evaluate environmental suitability and potential distribution at a broad spatial scale. Locality data on the distribution of P. caucasia have been gathered over nearly its entire range by various authors from field surveys. The distribution model ofP caucasia showed good performance （AUC = 0.887）, and predicted high suitability in regions mainly located in Tajikistan, north Pakistan, Afghanistan, southeast Turkmenistan, northeast Iran along the Elburz mountains, Transcaueasus （Azerbajan, Armenia, Georgia）, northeastern Turkey and northward along the Caspian Sea coast in Daghestan, Russia. The identification of suitable areas for this species will help to assess conservation status of the species, and to set up management programs.     

Identification of Biodiversity Conservation Priorities using Predictive Modeling: An Application for the Equatorial Pacific Region of South America

We used predictive modeling of species distributions to identify conservation priority areas in the equatorial Pacific region of western Ecuador and northwestern Peru. Museum and herbarium data and predictive models of species distributions are increasingly being used to assess the conservation status of individual species. In this study, we assembled occurrence data for 28 species of vascular plants, birds, and mammals to assess the conservation priorities of the set of natural communities that they represent. Environmental variables were used to predict the species’ distributions using correlative modeling as an alternative to point data, which has been the traditional approach to identify critical areas. Specific priority sites for conservation were identified using an area-selection algorithm based on simulated annealing. Four scenarios of prioritization were created using different criteria for the spatial compactness of the selected sites and fragmentation of remnant habitat. The results provide a preliminary assessment of conservation priorities for the dry ecosystems of the Equatorial Pacific region, and will serve as guidelines to focus future fieldwork.     

Integrating Life Stages into Ecological Niche Models: A Case Study on Tiger Beetles

Detailed understanding of a species’ natural history and environmental needs across spatial scales is a primary requisite for effective conservation planning, particularly for species with complex life cycles in which different life stages occupy different niches and respond to the environment at different scales. However, niche models applied to conservation often neglect early life stages and are mostly performed at broad spatial scales. Using the endangered heath tiger beetle (Cicindela sylvatica) as a model species, we relate presence/absence and abundance data of locally dispersing adults and sedentary larvae to abiotic and biotic variables measured in a multiscale approach within the geographic extent relevant to active conservation management. At the scale of hundreds of meters, fine-grained abiotic conditions (i.e., vegetation structure) are fundamental determinants of the occurrence of both life stages, whereas the effect of biotic factors is mostly contained in the abiotic signature. The combination of dense heath vegetation and bare ground areas is thus the first requirement for the species’ preservation, provided that accessibility to the suitable habitat is ensured. At a smaller scale (centimetres), the influence of abiotic factors on larval occurrence becomes negligible, suggesting the existence of important additional variables acting within larval proximity. Sustained significant correlations between neighbouring larvae in the models provide an indication of the potential impact of neighbourhood crowding on the larval niche within a few centimetres. Since the species spends the majority of its life cycle in the larval stage, it is essential to consider the hierarchical abiotic and biotic processes affecting the larvae when designing practical conservation guidelines for the species. This underlines the necessity for a more critical evaluation of the consequences of disregarding niche variation between life stages when estimating niches and addressing effective conservation measures for species with complex life cycles.     

Sex‐dependent habitat selection in a high‐density Little Bustard Tetrax tetrax population in southern France,and the implications for conservation

Conservation measures often rely on habitat management, so knowledge about a species’ habitat use is a prerequisite for effective conservation planning. The Little Bustard Tetrax tetrax, a medium‐sized bird native to the Palaearctic steppes and today found in extensively farmed habitats, is a threatened species. Its population experienced a 94% decline in farmland habitats in France between 1982 and 1996, and populations all over Europe have suffered equally sharp declines. Due to this steep negative trend, this species has been the subject of a number of habitat selection studies in order to develop relevant conservation measures based on its habitat requirements. In this study, we investigated the habitat selection of a range of habitat types by both sexes and at two nested spatial scales: plot scale and landscape scale. In addition, we analysed intra‐specific social interactions by incorporating conspecific density in the statistical models of habitat use. The study was conducted on a very high‐density population, perhaps the highest ever recorded for this species at around 50 Bustards per 100 ha of suitable habitat. Our methodology combined two field approaches (point counts and quadrat counts). The findings showed rather limited sexual dimorphism in terms of habitat selection at a local scale, with only vegetation height differing between sexes at a micro‐habitat scale, no selection at landscape scale, and a prevailing role of social factors at both scales. The implications for future conservation strategies in relation to population density and landscape composition are discussed.     

Spatially explicit conservation issues for threatened bird species in Mediterranean farmland landscapes

Coupling habitat models based on GIS and on ground variables could help identify suitable areas (by means of landscape models obtained by GIS variables) to concentrate management actions for species’ conservation. In this study, the habitat requirements of Lesser Greys (LGS) and Woodchat Shrikes (WS), two threatened farmland bird species declining in Europe, were assessed in Apulia (south-eastern Italy) by means of binary logistic regression at two different levels: landscape (using GIS-measured variables); and, territory (using ground-measured variables) scales. The LGS occurrence at landscape scale was correlated to steppe-like areas and cereal crops. At the territory level, significant effects were detected for deciduous forests and the presence of isolated trees and shrubs. The WS occurrence at landscape scale was promoted by steppe-like areas and cereal crops, whereas, at the territory level significant effects were detected for steppe-like areas positively and suburban areas negatively. The landscape model was extrapolated to the entire region. Within highly suitable areas (occurrence probability higher than 0.66 according to the landscape model), we measured average habitat features and compared them with the optimal mosaic depicted by the territory level models. This allowed us to give spatially explicit and site-specific management recommendations for these two threatened species. LGS will mostly benefit from an increase in isolated shrubs and trees; whereas for WS, the most widespread recommendations are to increase steppe-like habitat and to prevent further urbanisation.Coupling “coarse” landscape models with the species ecology provided by fine-scaled models can integrate relevant information on species potential distribution and territory level requirements, making planning fine-tuned habitat management (within potentially suitable landscapes) in a spatially explicit way possible.     

Food and habitats requirements of the Eurasian Scops Owl (Otus scops) in Switzerland revealed by very high-resolution multi-scale models

In Europe, agricultural practices have progressively evolved towards high productivity leading either to the intensification of productive and accessible areas or to the abandonment of less profitable sites. Both processes have led to the degradation of semi-natural habitats like extensive grasslands, threatening species such as the Eurasian Scops Owl Otus scops that rely on extensively managed agricultural landscapes. In this work, we aimed to assess the habitat preferences of the Scops Owl using habitat suitability models combined with a multi-scale approach. We generated a set of multi-scale predictors, considering both biotic and abiotic variables, built on two newly developed vegetation management and orthopteran abundance models. To select the variables to incorporate in a ‘best multi-scale model’, we chose the best spatial scale for each variable using univariate models and by calculating their relative importance through multi-model inference. Next, we built ensembles of small models (ESMs) at 10 different scales from 50 to 1000 m, and an additional model with each variable at its best scale (‘best multi-scale model’). The latter performed better than most of the other ESMs and allowed the creation of a high-resolution habitat suitability map for the species. Scops Owls showed a preference for dry sites with extensive and well-structured habitats with 30–40% bush cover, and relied strongly on semi-extensive grasslands covering at least 30% of the surface within 300 m of the territory centre and with high orthopteran availability near the centre (50-m radius), revealing a need for good foraging grounds near the nest. At a larger spatial scale within a radius of 1000 m, the habitat suitability of Scops Owls was negatively related to forest cover. The resulting ESM predictions provide valuable tools for conservation planning, highlighting sites in need of particular conservation efforts together with offering estimates of the percentage of habitat types and necessary prey abundance that could be used as targets in future management plans to ensure the persistence of the population.     

A dynamic multi‐scale occupancy model to estimate temporal dynamics and hierarchical habitat use for nomadic species

Distribution models are increasingly being used to understand how landscape and climatic changes are affecting the processes driving spatial and temporal distributions of plants and animals. However, many modeling efforts ignore the dynamic processes that drive distributional patterns at different scales, which may result in misleading inference about the factors influencing species distributions. Current occupancy models allow estimation of occupancy at different scales and, separately, estimation of immigration and emigration. However, joint estimation of local extinction, colonization, and occupancy within a multi‐scale model is currently unpublished. We extended multi‐scale models to account for the dynamic processes governing species distributions, while concurrently modeling local‐scale availability. We fit the model to data for lark buntings and chestnut‐collared longspurs in the Great Plains, USA, collected under the Integrated Monitoring in Bird Conservation Regions program. We investigate how the amount of grassland and shrubland and annual vegetation conditions affect bird occupancy dynamics and local vegetation structure affects fine‐scale occupancy. Buntings were prevalent and longspurs rare in our study area, but both species were locally prevalent when present. Buntings colonized sites with preferred habitat configurations, longspurs colonized a wider range of landscape conditions, and site persistence of both was higher at sites with greener vegetation. Turnover rates were high for both species, quantifying the nomadic behavior of the species. Our model allows researchers to jointly investigate temporal dynamics of species distributions and hierarchical habitat use. Our results indicate that grassland birds respond to different covariates at landscape and local scales suggesting different conservation goals at each scale. High turnover rates of these species highlight the need to account for the dynamics of nomadic species, and our model can help inform how to coordinate management efforts to provide appropriate habitat configurations at the landscape scale and provide habitat targets for local managers.     

Using Mountain Lion Habitat Selection in Management

Wildlife agencies are generally tasked with managing and conserving species at state and local levels simultaneously. Thus, it is necessary for wildlife agencies to understand basic ecological processes of a given species at multiple scales to aid decision making at commensurately varied spatial and behavioral scales. Mountain lions (Puma concolor) occur throughout California, USA, and are at the center of a variety of management and conservation issues. For example, they are genetically and demographically at risk in 1 region yet apparently stable and negatively affecting endangered species in another. Currently, no formal plan exists for mountain lions in California to deal with these diverse scenarios involving issues of local mountain lion population viability and problems related to predation of endangered species. To facilitate development of a state-wide management and conservation plan, we quantified habitat selection by mountain lions at 2 spatial scales across the range of environmental conditions in which the species is found in California. Our analyses used location data from individuals (n = 263) collared across the state from 2001–2019. At the home range scale, mountain lions selected habitat to prioritize meeting energetic demands. At the within home range scale, mountain lions avoided areas of human activity. Further, our analyses revealed 165,350–170,085 km², depending on season, of suitable mountain lion habitat in California. Fifty percent of the suitable habitat was on unprotected lands and thus vulnerable to development. These habitat selection models will help in the development of a state-wide conservation and management plan for mountain lions in California by guiding mountain lion population monitoring through time, prioritization of habitat to be conserved for maintaining demographic connectivity and gene flow, and efforts to mediate mountain lion-prey interactions. Our work and application area will help with wildlife policy and management decisions related to depredation problems at the local scale and issues of habitat connectivity at the statewide scale. © 2019 The Wildlife Society.     

The NATURA 2000 database as a tool in the analysis of habitat selection at large scales: factors affecting the occurrence of pine and stone martens in Southern Europe

Most studies on habitat selection among animals are conducted at local scales, whereas reliable determination of species requirements at larger spatial scales can be problematic. We used data available for NATURA 2000 sites to determine the habitat requirements of two relatively widespread and common species—pine marten Martes martes and stone marten Martes foina—in Southern Europe. Using presence-absence data, we applied statistical models at two spatial scales. At the local scale (within the dispersal distances of the species), sites occupied by martens were compared with unoccupied sites using buffers of different sizes, whereas at the regional scale, unoccupied sites were selected randomly. To adjust for spatial autocorrelation of data, penalised quasi-likelihood approximations were used. Both species of martens demonstrated preferences for areas with higher proportions of forest cover and steeper terrain. At the local, but not at the regional, scale, pine martens occurred at lower elevations, whilst stone martens occurred at higher elevations. We found that climatic variables (mean temperature, precipitation) had no significant effect on the presence of the martens. The results of our analyses generally confirmed findings of previous studies on habitat selection of both marten species in Southern Europe. This demonstrates the utility of data collected for NATURA 2000 sites for use in various analyses such as conservation planning and evaluating the impact of climate change on the distribution of animal species.     

Measures of giant panda habitat selection across multiple spatial scales for species conservation

Examining ecological processes across spatial scales is crucial as animals select and use resources at different scales. We carried out field surveys in September 2005, March–September 2006, and April 2007, and used ecological niche factor analysis to determine habitat preferences for the giant panda (Ailuropoda melanoleuca) across 4 spatial scales: daily movement, core range, home range, and seasonal elevational migration. We found that giant pandas prefer conifer forest and mixed forest at higher than average elevation (2,157 m) of study area in the 4 scale models. However, we also observed significant scale differences in habitat selection. The strength of habitat preference increased with scale for the 2 disturbed forests (sparse forest and fragmented forest), and decreased with scale for 0–30° gentle slope and south- and north-facing aspect. Furthermore, habitat suitability patterns were scale-dependent. These findings highlight the need to determine species–environment associations across multiple scales for habitat management and species conservation. © 2012 The Wildlife Society.     

Accommodating Species Climate-Forced Dispersal and Uncertainties in Spatial Conservation Planning

Spatial conservation prioritization should seek to anticipate climate change impacts on biodiversity and to mitigate these impacts through the development of dynamic conservation plans. Here, we defined spatial priorities for the conservation of amphibians inhabiting the Atlantic Forest Biodiversity Hotspot that overcome the likely impacts of climate change on the distribution of this imperiled fauna. First, we built ecological niche models (ENMs) for 431 amphibian species both for current time and for the mid-point of a 30-year period spanning 2071–2099 (i.e. 2080). For modeling species'' niches, we combined six modeling methods and three different climate models. We also quantified and mapped model uncertainties. Our consensus models forecasted range shifts that culminate with high species richness in central and eastern Atlantic Forest, both for current time and for 2080. Most species had a significant range contraction (up to 72%) and 12% of species were projected to be regionally extinct. Most species would need to disperse because suitable climatic sites will change. Therefore, we identified a network of priority sites for conservation that minimizes the distance a given species would need to disperse because of changes in future habitat suitability (i.e. climate-forced dispersal) as well as uncertainties associated to ENMs. This network also maximized complementary species representation across currently established protected areas. Priority sites already include possible dispersal corridors linking current and future suitable habitats for amphibians. Although we used the a top-ranked Biodiversity Hotspot and amphibians as a case study for illustrating our approach, our study may help developing more effective conservation strategies under climate change, especially when applied at different spatial scales, geographic regions, and taxonomic groups.     

Relevance of multiple spatial scales in habitat models: A case study with amphibians and grasshoppers

Habitat models for animal species are important tools in conservation planning. We assessed the need to consider several scales in a case study for three amphibian and two grasshopper species in the post-mining landscapes near Leipzig (Germany). The two species groups were selected because habitat analyses for grasshoppers are usually conducted on one scale only whereas amphibians are thought to depend on more than one spatial scale.First, we analysed how the preference to single habitat variables changed across nested scales. Most environmental variables were only significant for a habitat model on one or two scales, with the smallest scale being particularly important. On larger scales, other variables became significant, which cannot be recognized on lower scales. Similar preferences across scales occurred in only 13 out of 79 cases and in 3 out of 79 cases the preference and avoidance for the same variable were even reversed among scales.Second, we developed habitat models by using a logistic regression on every scale and for all combinations of scales and analysed how the quality of habitat models changed with the scales considered. To achieve a sufficient accuracy of the habitat models with a minimum number of variables, at least two scales were required for all species except for Bufo viridis, for which a single scale, the microscale, was sufficient. Only for the European tree frog (Hyla arborea), at least three scales were required.The results indicate that the quality of habitat models increases with the number of surveyed variables and with the number of scales, but costs increase too. Searching for simplifications in multi-scaled habitat models, we suggest that 2 or 3 scales should be a suitable trade-off, when attempting to define a suitable microscale.     

Development and field validation of a regional,management‐scale habitat model: A koala Phascolarctos cinereus case study

Species distribution models have great potential to efficiently guide management for threatened species, especially for those that are rare or cryptic. We used MaxEnt to develop a regional‐scale model for the koala Phascolarctos cinereus at a resolution (250 m) that could be used to guide management. To ensure the model was fit for purpose, we placed emphasis on validating the model using independently‐collected field data. We reduced substantial spatial clustering of records in coastal urban areas using a 2‐km spatial filter and by modeling separately two subregions separated by the 500‐m elevational contour. A bias file was prepared that accounted for variable survey effort. Frequency of wildfire, soil type, floristics and elevation had the highest relative contribution to the model, while a number of other variables made minor contributions. The model was effective in discriminating different habitat suitability classes when compared with koala records not used in modeling. We validated the MaxEnt model at 65 ground‐truth sites using independent data on koala occupancy (acoustic sampling) and habitat quality (browse tree availability). Koala bellows (n = 276) were analyzed in an occupancy modeling framework, while site habitat quality was indexed based on browse trees. Field validation demonstrated a linear increase in koala occupancy with higher modeled habitat suitability at ground‐truth sites. Similarly, a site habitat quality index at ground‐truth sites was correlated positively with modeled habitat suitability. The MaxEnt model provided a better fit to estimated koala occupancy than the site‐based habitat quality index, probably because many variables were considered simultaneously by the model rather than just browse species. The positive relationship of the model with both site occupancy and habitat quality indicates that the model is fit for application at relevant management scales. Field‐validated models of similar resolution would assist in guiding management of conservation‐dependent species.     

The nest predator community of grassland birds responds to agroecosystem habitat at multiple scales

Nest predation is the leading cause of reproductive failure for grassland birds of conservation concern. Understanding variation in nest predation rates is complicated by the diverse assemblage of species known to prey on nests. As part of a long‐term study of grassland bird ecology, we monitored populations of predators known to prey on grassland bird nests. We used information theoretic approach to examine the predator community's association with habitat at multiple scales, including local vegetation structure of grassland patches, spatial attributes of grassland patches (size and shape), and landscape composition surrounding grassland patches (land cover within 400 and 1600 m). Our results confirmed that nest predators respond to habitat at multiple scales and different predator species respond to habitat in different ways. The most informative habitat models we selected included variability in local vegetation (CV in the density of forbs), local patch (area and edge‐to‐interior ratio), and landscape within a 1600 m buffer around grasslands (percent of land covered by human structures and development). As a separate question, we asked if models that incorporated information from multiple scales simultaneously might improve the ability to explain variation in the predator community. Multi‐ scale models were not consistently superior to models derived from variables focused at a single spatial scale. Our results suggest that minimizing human development on and surrounding conservation land and the management of the vegetation structure on grassland fragments both may benefit grassland birds by decreasing the risk of nest predation.     

Habitat change and the scale of habitat selection: shifting gradients used by coexisting Arctic rodents

The conservation and understanding of biodiversity requires development and testing of models that illustrate how climate change and other anthropogenic effects alter habitat and its selection at different spatial scales. Models of fitness along a habitat gradient illustrate the connection between fine‐scale variation in fitness and the selection of habitat as discontinuous patches in the landscape. According to these models, climate change can increase fitness values of static habitats, shift the fitness value of habitat patches along underlying gradients of habitat quality, or alter both fitness and habitat quality. It should be possible to differentiate amongst these scenarios by associating differences in the abundance and distribution of species with metrics of habitat that document the gradient while controlling for changes in density at larger scales of analysis. Comparisons of habitat selection by two species of lemmings, over an interval of 15 years, are consistent with the theory. The pattern of habitat selection at the scale of wet versus dry tundra habitats changed through time. The change in habitat selection was reflected by different, but nevertheless density‐dependent, patterns of association with the structure and composition of habitat. Abundant collared lemmings abandoned stations where altered habitat characteristics caused a shift to new locations along the wet‐to‐dry gradient. The confirmation of scale‐dependent theory provides new insights into how one might begin to forecast future habitat selection under different scenarios of climate and habitat change.     

Spatial scale mediates the influence of habitat fragmentation on dispersal success: Implications for conservation

Increasingly, conservationists are seeking insights from ecological theory to choose strategies of habitat management that will best maintain threatened species. Often, these questions revolve around ways of mitigating the dangers posed by habitat fragmentation. Problems involving the scale of both animal movement and spatial heterogeneity inexorably arise when assessing the effects of fragmentation. We present results from a simple spatial model that simulates the dispersal of animals in a landscape of stochastically clustered habitat fragments. Varying the number of clusters and the spatial scale at which clustering occurs illustrates that heterogeneity has different and conflicting effects on animal movement when it occurs at different scales. Indeed, the scale of clustering is the most important feature in determining disperser performance in our model. Seeking to compare our modeling results with actual data, we review empirical studies of fragmented populations and habitats. Surprisingly, we conclude that very few studies have addressed the mechanisms by which fragmentation will influence population dynamics or, in particular, the ways in which spatial scale mediate these effects. We conclude that the explicit consideration of scale is essential in discussions of habitat fragmentation and of optimal conservation strategies.