Effects of spatial scale and sample size in GPS-based species distribution models: are the best models trivial for red deer management?

Species distribution models (SDMs) are popular in conservation and management of a wide array of taxa. Often parameterized with coarse GIS-based environmental maps, they perform well in macro-ecological settings but it is debated if the models can predict distribution within broadly suitable “known” habitats of interest to local managers. We parameterized SDMs with GIS-derived environmental variables and location data from 82 GPS-collared female red deer (Cervus elaphus) from two study areas in Norway. Candidate GLM models were fitted to address the effect of spatial scale (landscape vs. home range), sample size, and transferability between study areas, with respect to predictability (AUC) and explained variance (Generalized R ² and deviance). The landscape level SDM captured variation in deer distribution well and performed best on all diagnostic measures of model quality, caused mainly by a trivial effect of avoidance of non-habitat (barren mountains). The home range level SDMs were far less predictable and explained comparatively little variation in space use. Landscape scale models stabilized at the low sample size of 5–10 individuals and were highly transferrable between study areas implying a low degree of individual variation in habitat selection at this scale. It is important to have realistic expectations of SDMs derived from digital elevation models and coarse habitat maps. They do perform well in highlighting potential habitat on a landscape scale, but often miss nuances necessary to predict more fine-scaled distribution of wildlife populations. Currently, there seems to be a trade-off between model quality and usefulness in local management.     

Using Landscape and Bioclimatic Features to Predict the Distribution of Lions,Leopards and Spotted Hyaenas in Tanzania's Ruaha Landscape

Tanzania''s Ruaha landscape is an international priority area for large carnivores, supporting over 10% of the world''s lions and important populations of leopards and spotted hyaenas. However, lack of ecological data on large carnivore distribution and habitat use hinders the development of effective carnivore conservation strategies in this critical landscape. Therefore, the study aimed to (i) identify the most significant ecogeographical variables influencing the potential distribution of lions, leopards and spotted hyaenas across the Ruaha landscape; (ii) identify zones with highest suitability for harbouring those species; and (iii) use species distribution modelling algorithms (SDMs) to define important areas for conservation of large carnivores. Habitat suitability was calculated based on environmental features from georeferenced presence-only carnivore location data. Potential distribution of large carnivores appeared to be strongly influenced by water availability; highly suitable areas were situated close to rivers and experienced above average annual precipitation. Net primary productivity and tree cover also exerted some influence on habitat suitability. All three species showed relatively narrow niche breadth and low tolerance to changes in habitat characteristics. From 21,050 km² assessed, 8.1% (1,702 km²) emerged as highly suitable for all three large carnivores collectively. Of that area, 95.4% (1,624 km²) was located within 30 km of the Park-village border, raising concerns about human-carnivore conflict. This was of particular concern for spotted hyaenas, as they were located significantly closer to the Park boundary than lions and leopards. This study provides the first map of potential carnivore distribution across the globally important Ruaha landscape, and demonstrates that SDMs can be effective for understanding large carnivore habitat requirements in poorly sampled areas. This approach could have relevance for many other important wildlife areas that only have limited, haphazard presence-only data, but which urgently require strategic conservation planning.     

How to deal with ground truthing affected by human‐induced habitat change?: Identifying high‐quality habitats for the Critically Endangered Red Siskin

Species distribution models (SDM) can be valuable for identifying key habitats for conservation management of threatened taxa, but anthropogenic habitat change can undermine SDM accuracy. We used data for the Red Siskin (Spinus cucullatus), a critically endangered bird and ground truthing to examine anthropogenic habitat change as a source of SDM inaccuracy. We aimed to estimate: (1) the Red Siskin's historic distribution in Venezuela; (2) the portion of this historic distribution lost to vegetation degradation; and (3) the location of key habitats or areas with both, a high probability of historic occurrence and a low probability of vegetation degradation. We ground‐truthed 191 locations and used expert opinion as well as landscape characteristics to classify species' habitat suitability as excellent, good, acceptable, or poor. We fit a Random Forest model (RF) and Enhanced Vegetation Index (EVI) time series to evaluate the accuracy and precision of the expert categorization of habitat suitability. We estimated the probability of historic occurrence by fitting a MaxLike model using 88 presence records (1960–2013) and data on forest cover and aridity index. Of the entire study area, 23% (20,696 km²) had a historic probability of Red Siskin occurrence over 0.743. Furthermore, 85% of ground‐truthed locations had substantial reductions in mean EVI, resulting in key habitats totaling just 976 km², in small blocks in the western and central regions. Decline in Area of Occupancy over 15 years was between 40% and 95%, corresponding to an extinction risk category between Vulnerable and Critically Endangered. Relating key habitats with other landscape features revealed significant risks and opportunities for proposed conservation interventions, including the fact that ongoing vegetation degradation could limit the establishment of reintroduced populations in eastern areas, while the conservation of remaining key habitats on private lands could be improved with biodiversity‐friendly agri‐ and silviculture programs.     

Relationship between chimpanzee (Pan troglodytes) density and large, fleshy-fruit tree density: conservation implications

Conservation efforts to protect chimpanzees in their natural habitat are of the highest priority. Unfortunately, chimpanzee density is notoriously difficult to determine, making it difficult to assess potential chimpanzee conservation areas. The objective of this study was to determine whether chimpanzee density could be predicted from the density of trees that produce large, fleshy fruits. Using chimpanzee nest counts from six sites within Kibale National Park, Uganda, collected during a year-long study, a predictive trend was found between chimpanzee nest density and large, fleshy-fruit tree density. This relationship may offer a quick, reasonably reliable method of estimating potential chimpanzee densities in previously unsurveyed habitats and may be used to evaluate the suitability of possible re-introduction sites. Thus, in conjunction with other survey techniques, such as forest reconnaissance, it may provide an effective and efficient means of determining appropriate chimpanzee habitat in which to allocate conservation efforts.     

Remote sensing‐based landscape indicators for the evaluation of threatened‐bird habitats in a tropical forest

Avian species persistence in a forest patch is strongly related to the degree of isolation and size of a forest patch and the vegetation structure within a patch and its matrix are important predictors of bird habitat suitability. A combination of space‐borne optical (Landsat), ALOS‐PALSAR (radar), and airborne Light Detection and Ranging (LiDAR) data was used for assessing variation in forest structure across forest patches that had undergone different levels of forest degradation in a logged forest—agricultural landscape in Southern Laos. The efficacy of different remote sensing (RS) data sources in distinguishing forest patches that had different seizes, configurations, and vegetation structure was examined. These data were found to be sensitive to the varying levels of degradation of the different patch categories. Additionally, the role of local scale forest structure variables (characterized using the different RS data and patch area) and landscape variables (characterized by distance from different forest patches) in influencing habitat preferences of International Union for Conservation of Nature (IUCN) Red listed birds found in the study area was examined. A machine learning algorithm, MaxEnt, was used in conjunction with these data and field collected geographical locations of the avian species to identify the factors influencing habitat preference of the different bird species and their suitable habitats. Results show that distance from different forest patches played a more important role in influencing habitat suitability for the different avian species than local scale factors related to vegetation structure and health. In addition to distance from forest patches, LiDAR‐derived forest structure and Landsat‐derived spectral variables were important determinants of avian habitat preference. The models derived using MaxEnt were used to create an overall habitat suitability map (HSM) which mapped the most suitable habitat patches for sustaining all the avian species. This work also provides insight that retention of forest patches, including degraded and isolated forest patches in addition to large contiguous forest patches, can facilitate bird species retention within tropical agricultural landscapes. It also demonstrates the effective use of RS data in distinguishing between forests that have undergone varying levels of degradation and identifying the habitat preferences of different bird species. Practical conservation management planning endeavors can use such data for both landscape scale monitoring and habitat mapping.     

Habitat suitability modelling for species at risk is sensitive to algorithm and scale: A case study of Blanding's turtle,Emydoidea blandingii,in Ontario,Canada

Species distribution modelling (SDM) can help conservation by providing information on the ecological requirements of species at risk. We developed habitat suitability models at multiple spatial scales for a threatened freshwater turtle, Emydoidea blandingii, in Ontario as a case study. We also explored the effect of background data selection and modelling algorithm selection on habitat suitability predictions. We used sighting records, high-resolution land cover data (25 m), and two SDM techniques: boosted regression trees; and maximum entropy modelling. The area under the receiver characteristic operating curve (AUC) for habitat suitability models tested on independent data ranged from 0.878 to 0.912 when using random background and from 0.727 to 0.741 with target-group background. E. blandingii habitat suitability was best predicted by air temperature, wetland area, open water area, road density, and cropland area. Habitat suitability increased with increasing air temperature and wetland area, and decreased with increasing cropland area. Low road density and open water increased habitat suitability, while high levels of either variable decreased habitat suitability. Robust habitat suitability maps for species at risk require using a multi-scale and multi-algorithm approach. If well used, SDM can offer insight on the habitat requirements of species at risk and help guide the development of management plans. Our results suggest that E. blandingii management plans should promote the protection of terrestrial habitat surrounding residential wetlands, halt the building of roads within and adjacent to currently occupied habitat, and identify movement corridors for isolated populations.     

Relative Effects of Road Risk,Habitat Suitability,and Connectivity on Wildlife Roadkills: The Case of Tawny Owls (Strix aluco)

Background

Despite its importance for reducing wildlife-vehicle collisions, there is still incomplete understanding of factors responsible for high road mortality. In particular, few empirical studies examined the idea that spatial variation in roadkills is influenced by a complex interplay between road-related factors, and species-specific habitat quality and landscape connectivity.

Methodology/Principal Findings

In this study we addressed this issue, using a 7-year dataset of tawny owl (Strix aluco) roadkills recorded along 37 km of road in southern Portugal. We used a multi-species roadkill index as a surrogate of intrinsic road risk, and we used a Maxent distribution model to estimate habitat suitability. Landscape connectivity was estimated from least-cost paths between tawny owl territories, using habitat suitability as a resistance surface. We defined 10 alternative scenarios to compute connectivity, based on variation in potential movement patterns according to territory quality and dispersal distance thresholds. Hierarchical partitioning of a regression model indicated that independent variation in tawny owl roadkills was explained primarily by the roadkill index (70.5%) and, to a much lesser extent, by landscape connectivity (26.2%), while habitat suitability had minor effects (3.3%). Analysis of connectivity scenarios suggested that owl roadkills were primarily related to short range movements (<5 km) between high quality territories. Tawny owl roadkills were spatially autocorrelated, but the introduction of spatial filters in the regression model did not change the type and relative contribution of environmental variables.

Conclusions

Overall, results suggest that road-related factors may have a dominant influence on roadkill patterns, particularly in areas like ours where habitat quality and landscape connectivity are globally high for the study species. Nevertheless, the study supported the view that functional connectivity should be incorporated whenever possible in roadkill models, as it may greatly increase their power to predict the location of roadkill hotspots.     

Resistance is futile: effects of landscape features on gene flow of the northern bobwhite

Habitat for the northern bobwhite (Colinus virginianus) has declined and changed drastically in spatial structure throughout the last century. Undoubtedly such changes have impacted bobwhite and may have altered their ability to access available habitat. We investigated whether landscape resistance, geographic distance, or interstate highway barriers were related to dispersal and gene flow of bobwhite in central and southern Illinois. Landscape resistance was determined from two empirically informed models depicting habitat suitability for bobwhite. During 2007–2008, hunters submitted bobwhite tissue samples from which we amplified 11 microsatellites. The relationship between individual genetic distances and spatial variables was analyzed with Mantel tests and causal modeling was used to verify the spatial variables influencing gene flow. Genetic distance was correlated with geographic distance but showed no relationship with interstate highway barriers. Habitat suitability did not enhance gene flow, and was inversely related in some partial Mantel tests. We suggest that bobwhite dispersal from suitable habitat patches may be less frequent than from suboptimal habitats. Bobwhite may be able to access suitable habitat across gaps of unsuitable habitat but distance limits their dispersal. Because available habitat for bobwhites may have a greater likelihood of being colonized when closer to occupied habitat, we suggest that lands closer to occupied habitat should be targeted for conservation or habitat improvement efforts.     

Range‐wide patterns of greater sage‐grouse persistence

Aim Greater sage‐grouse (Centrocercus urophasianus), a shrub‐steppe obligate species of western North America, currently occupies only half its historical range. Here we examine how broad‐scale, long‐term trends in landscape condition have affected range contraction. Location Sagebrush biome of the western USA. Methods Logistic regression was used to assess persistence and extirpation of greater sage‐grouse range based on landscape conditions measured by human population (density and population change), vegetation (percentage of sagebrush habitat), roads (density of and distance to roads), agriculture (cropland, farmland and cattle density), climate (number of severe and extreme droughts) and range periphery. Model predictions were used to identify areas where future extirpations can be expected, while also explaining possible causes of past extirpations. Results Greater sage‐grouse persistence and extirpation were significantly related to sagebrush habitat, cultivated cropland, human population density in 1950, prevalence of severe droughts and historical range periphery. Extirpation of sage‐grouse was most likely in areas having at least four persons per square kilometre in 1950, 25% cultivated cropland in 2002 or the presence of three or more severe droughts per decade. In contrast, persistence of sage‐grouse was expected when at least 30 km from historical range edge and in habitats containing at least 25% sagebrush cover within 30 km. Extirpation was most often explained (35%) by the combined effects of peripherality (within 30 km of range edge) and lack of sagebrush cover (less than 25% within 30 km). Based on patterns of prior extirpation and model predictions, we predict that 29% of remaining range may be at risk. Main Conclusions Spatial patterns in greater sage‐grouse range contraction can be explained by widely available landscape variables that describe patterns of remaining sagebrush habitat and loss due to cultivation, climatic trends, human population growth and peripherality of populations. However, future range loss may relate less to historical mechanisms and more to recent changes in land use and habitat condition, including energy developments and invasions by non‐native species such as cheatgrass (Bromus tectorum) and West Nile virus. In conjunction with local measures of population performance, landscape‐scale predictions of future range loss may be useful for prioritizing management and protection. Our results suggest that initial conservation efforts should focus on maintaining large expanses of sagebrush habitat, enhancing quality of existing habitats, and increasing habitat connectivity.     

农业景观中环境因素对两栖类生物分布的影响

以黄河下游地区封丘县为研究区,在地理信息系统和R软件的支持下,在栖息地水平和景观水平上,分析了两栖类生物分布与栖息地变量(池塘水体溶解氧DO、电导率COND、浊度TURB、水体氨氮NH₃-N、池塘内植被盖度VEG_interior、池塘内挺水植物盖度EMER、池塘边缘植被盖度VEG_edge、两栖类幼虫捕食者PRE和池塘面积AREA)和采样点池塘250、500、1000、2000 m半径缓冲区内景观变量(池塘面积AP、与最近道路的距离DR、耕地面积AF、林地面积AW、Shannon多样性指数SHDI和蔓延度指数CONTAG)的关系.结果表明: 中华大蟾蜍的分布主要与栖息地变量中的PRE和较大缓冲区半径内的景观变量(AW2000、DR2000、SHDI1000、CONTAG1000)相关;黑斑侧褶蛙的分布与栖息地变量中的EMER和较小缓冲区半径内的景观变量(SHDI500)关系密切;金线侧褶蛙的分布主要与栖息地变量中的VEG_interior和PRE相关;泽陆蛙的分布主要与较大缓冲区半径内的景观变量(AF2000、SHDI2000)相关;两栖类生物总体上主要与栖息地变量中的EMER和较小缓冲区半径内的景观变量(SHDI500)相关.在农业景观中,保护两栖类生物应该保护永久性和半永久性池塘、提高池塘内部植被盖度、增强栖息地池塘之间的功能连通性.     

Mapping suitable great ape habitat in and around the Lobéké National Park,South‐East Cameroon

As a result of extensive data collection efforts over the last 20–30 years, there is quite a good understanding of the large‐scale geographic distribution and range limits of African great apes. However, as human activities increasingly fragment great ape spatial distribution, a better understanding of what constitutes suitable great ape habitat is needed to inform conservation and resource extraction management. Chimpanzees (Pan troglodytes troglodytes) and gorillas (Gorilla gorilla gorilla) inhabit the Lobéké National Park and its surrounding forest management units (FMUs) in South‐East Cameroon. Both park and neighboring forestry concessions require reliable evidence on key factors driving great ape distribution for their management plans, yet this information is largely missing and incomplete. This study aimed at mapping great ape habitat suitability in the area and at identifying the most influential predictors among three predictor categories, including landscape predictors (dense forest, swampy forest, distance to water bodies, and topography), human disturbance predictors (hunting, deforestation, distance to roads, and population density), and bioclimatic predictor (annual precipitation). We found that about 63% of highly to moderately suitable chimpanzee habitat occurred within the Lobéké National Park, while only 8.4% of similar habitat conditions occurred within FMUs. For gorillas, highly and moderately suitable habitats occurred within the Lobéké National Park and its surrounding FMUs (82.6% and 65.5%, respectively). Key determinants of suitable chimpanzee habitat were hunting pressure and dense forest, with species occurrence probability optimal at relatively lower hunting rates and at relatively high‐dense forest areas. Key determinants of suitable gorilla habitat were hunting pressure, dense forests, swampy forests, and slope, with species occurrence probability optimal at relatively high‐dense and swampy forest areas and at areas with mild slopes. Our findings show differential response of the two ape species to forestry activities in the study area, thus aligning with previous studies.     

Species Distribution Modelling predicts habitat suitability and reduction of suitable habitat under future climatic scenario for Sclerophrys perreti: A critically endangered Nigerian endemic toad

Sclerophrys perreti is a critically endangered Nigerian native frog currently imperilled by human activities. A better understanding of its potential distribution and habitat suitability will aid in conservation; however, such knowledge is limited for S. perreti. Herein, we used a species distribution model (SDM) approach with all known occurrence data (n = 22) from our field surveys and primary literature, and environmental variable predictors (19 bioclimatic variables, elevation and land cover) to elucidate habitat suitability and impact of climate change on this species. The SDM showed that temperature and precipitation were the predictors of habitat suitability for S. perreti with precipitation seasonality as the strongest predictor of habitat suitability. The following variable also had a significant effect on habitat suitability: temperature seasonality, temperature annual range, precipitation of driest month, mean temperature of wettest quarter and isothermality. The model predicted current suitable habitat for S. perreti covering an area of 1,115 km². However, this habitat is predicted to experience 60% reduction by 2050 owing to changes in temperature and precipitation. SDM also showed that suitable habitat exists in south-eastern range of the inselberg with predicted low impact of climate change compared to other ranges. Therefore, this study recommends improved conservation measures through collaborations and stakeholder's meeting with local farmers for the management and protection of S. perreti.     

基于不同视角与方法的北京市密云区生境规划对比

由快速城市化导致的生境破碎化严重影响了生态系统的服务功能。因此,保护与规划城市生境尤为重要。然而目前科学的生境规划设计方法仍有待探索,因为生境的定义具有不同的视角与内涵。基于保护生物学与景观生态学理论,对比了物种视角与景观视角下的2种规划思路,并结合北京市密云区的生境规划,分析对比2种方法的规划结果。在物种方法中,首先选取承担多种生态作用的豹猫为目标物种,运用HSI模型并结合专家赋值法和层次分析法确定每个评价因子的权重,最后通过ArcGIS计算选取高适宜性源地并建立生态网络。景观方法则基于ArcGIS、Guidos、Conefor等软件平台,采用MSPA和景观连通性分析方法,选取重要核心区源地并建立景观生境网络。研究结果表明,2种方法的源地分布差异较大。因此生境规划不能盲目选择一种方法,需有机结合2种方法得到源地与廊道结果。根据地块承载的生境生态功能重要程度确定源地核心保护区,以实现最佳的生境规划和有效的生态系统服务。     

Patterns of Land Cover Change in and Around Madidi National Park, Bolivia

This study examines how human land uses and biophysical factors serve as predictors of land cover change in and around Madidi National Park in Bolivia. The Greater Madidi Landscape ranges over an elevational gradient from < 200 m in the Amazon basin to 6000 m in the high Andes, contains more than ten major ecosystem types, and several protected areas and sustainable use zones. In this study, Landsat Thematic Mapper satellite images collected over the study area at the beginning of the 1990s and then the 2000s were classified according to broad land cover types. Below elevations of 3000 m, the landscape experienced equal rates of deforestation and secondary forest increases of approximately 0.63 percent annually, resulting in no significant net change. Below elevations of 1000 m, however, we found an annual net loss in forest cover of 0.11 percent. Across the landscape, land cover change was most likely to occur near areas previously deforested, near roads and population centers, and at low elevations. We found net deforestation rates to be inversely related to strength of natural resource protection laws in protected areas and other jurisdictions. Results suggest little net change for the landscape as a whole, but that local scale changes may be significant, particularly near roads. Management policies favorable for biodiversity conservation in this landscape should limit the building of new roads and immigration to biologically sensitive areas and continue to support protected areas, which are achieving a positive result for forest conservation.     

The role of demography,intra‐species variation,and species distribution models in species' projections under climate change

Organisms are projected to shift their distribution ranges under climate change. The typical way to assess range shifts is by species distribution models (SDMs), which predict species’ responses to climate based solely on projected climatic suitability. However, life history traits can impact species’ responses to shifting habitat suitability. Additionally, it remains unclear if differences in vital rates across populations within a species can offset or exacerbate the effects of predicted changes in climatic suitability on population viability. In order to obtain a fuller understanding of the response of one species to projected climatic changes, we coupled demographic processes with predicted changes in suitable habitat for the monocarpic thistle Carlina vulgaris across northern Europe. We first developed a life history model with species‐specific average fecundity and survival rates and linked it to a SDM that predicted changes in habitat suitability through time with changes in climatic variables. We then varied the demographic parameters based upon observed vital rates of local populations from a translocation experiment. Despite the fact that the SDM alone predicted C. vulgaris to be a climate ‘winner’ overall, coupling the model with changes in demography and small‐scale habitat suitability resulted in a matrix of stable, declining, and increasing patches. For populations predicted to experience declines or increases in abundance due to changes in habitat suitability, altered fecundity and survival rates can reverse projected population trends.     

Landscape-scale impacts of transportation infrastructure on spatial dynamics of two vulnerable ungulate species in Ghamishloo Wildlife Refuge,Iran

Development of roads through protected areas can have deleterious effects on natural habitats containing species of conservation concern. During the past decades road construction has affected many former remote areas and led to fragmentation and isolation of wildlife populations. The present study focuses on the ecological impacts of Isfahan's West Freeway, which passes through Ghamishloo Wildlife Refuge; an IUCN category IV protected area, in Isfahan Province. The two key affected species, both classified as vulnerable by IUCN, the goitered gazelle (Gazella subgutturosa subgutturosa) and the wild sheep (Ovis orientalis isphahanica) were subject to impact analyses. We used habitat evaluation procedure (HEP) as a habitat-based impact assessment methodology which considers habitat quality and quantity. Habitat quality was measured as habitat suitability index (HSI) for each species. By literature review and field observations, five variables defining habitat suitability were identified and suitability maps for both species generated. Habitat units (HUs) were derived from multiplying the HSI for each species by the habitat area before and after freeway construction. The results showed that due to the construction of the freeway, about 14% of the HUs for goitered gazelle and about 9% of the HUs for wild sheep were lost. In addition, for quantifying landscape pattern change due to freeway construction, various landscape metrics were calculated for the species distribution polygons for two times before and after freeway construction. Results obtained through quantifying landscape metrics showed that mean nearest neighbor (MNN) and number of patches (NP) metrics increased. On the other hand, CONTAG metric decreased in both goitered gazelle and wild sheep distribution polygons, demonstrating the negative effect of freeway on these species distribution polygons integrity. According to the results of this study, mitigation and compensation activities should be considered in Ghamishloo Wildlife Refuge. Our study demonstrated that HEP method combined with quantifying landscape metrics might provide a powerful tool for assessing ecological impact of technical infrastructures on populations of far-ranging species of conservation concern.     

卧龙自然保护区大熊猫生境破碎化研究

生境破碎化主要有两个方面,一是形态（景观结构）上的破碎化;二是生态功能上的破碎化,将景观连接度的概念引入卧龙自然保护区大熊猫的生境评价研究中,通过选择影响大熊猫生存的３种典型景观因子;地形高度,地形坡度和食物来源,从生态功能上研究３种景观因子由于空间组合的不匹配而形成的生境破碎化现状,在生物各景观因子重要性的基础上进行景观连接模糊相对赋值,并建立景观连接度评价模型,在地理信息系统支持下,研究了卧龙     

A comparison of regression methods for model selection in individual‐based landscape genetic analysis

Anthropogenic migration barriers fragment many populations and limit the ability of species to respond to climate‐induced biome shifts. Conservation actions designed to conserve habitat connectivity and mitigate barriers are needed to unite fragmented populations into larger, more viable metapopulations, and to allow species to track their climate envelope over time. Landscape genetic analysis provides an empirical means to infer landscape factors influencing gene flow and thereby inform such conservation actions. However, there are currently many methods available for model selection in landscape genetics, and considerable uncertainty as to which provide the greatest accuracy in identifying the true landscape model influencing gene flow among competing alternative hypotheses. In this study, we used population genetic simulations to evaluate the performance of seven regression‐based model selection methods on a broad array of landscapes that varied by the number and type of variables contributing to resistance, the magnitude and cohesion of resistance, as well as the functional relationship between variables and resistance. We also assessed the effect of transformations designed to linearize the relationship between genetic and landscape distances. We found that linear mixed effects models had the highest accuracy in every way we evaluated model performance; however, other methods also performed well in many circumstances, particularly when landscape resistance was high and the correlation among competing hypotheses was limited. Our results provide guidance for which regression‐based model selection methods provide the most accurate inferences in landscape genetic analysis and thereby best inform connectivity conservation actions.     

Dynamic Disturbance Processes Create Dynamic Lek Site Selection in a Prairie Grouse

It is well understood that landscape processes can affect habitat selection patterns, movements, and species persistence. These selection patterns may be altered or even eliminated as a result of changes in disturbance regimes and a concomitant management focus on uniform, moderate disturbance across landscapes. To assess how restored landscape heterogeneity influences habitat selection patterns, we examined 21 years (1991, 1993–2012) of Greater Prairie-Chicken (Tympanuchus cupido) lek location data in tallgrass prairie with restored fire and grazing processes. Our study took place at The Nature Conservancy’s Tallgrass Prairie Preserve located at the southern extent of Flint Hills in northeastern Oklahoma. We specifically addressed stability of lek locations in the context of the fire-grazing interaction, and the environmental factors influencing lek locations. We found that lek locations were dynamic in a landscape with interacting fire and grazing. While previous conservation efforts have treated leks as stable with high site fidelity in static landscapes, a majority of lek locations in our study (i.e., 65%) moved by nearly one kilometer on an annual basis in this dynamic setting. Lek sites were in elevated areas with low tree cover and low road density. Additionally, lek site selection was influenced by an interaction of fire and patch edge, indicating that in recently burned patches, leks were located near patch edges. These results suggest that dynamic and interactive processes such as fire and grazing that restore heterogeneity to grasslands do influence habitat selection patterns in prairie grouse, a phenomenon that is likely to apply throughout the Greater Prairie-Chicken’s distribution when dynamic processes are restored. As conservation moves toward restoring dynamic historic disturbance patterns, it will be important that siting and planning of anthropogenic structures (e.g., wind energy, oil and gas) and management plans not view lek locations as static points, but rather as sites that shift around the landscape in response to shifting vegetation structure. Acknowledging shifting lek locations in these landscapes will help ensure conservation efforts are successful by targeting the appropriate areas for protection and management.