Effects of landscape and patch-level attributes on regional population persistence

Species responses are influenced by processes operating at multiple scales, yet many conservation studies and management actions are focused on a single scale. Although landscape-level habitat conditions (i.e., habitat amount, fragmentation and landscape quality) are likely to drive the regional persistence of spatially structured populations, patch-level factors (i.e., patch size, isolation, and quality) may also be important. To determine the spatial scales at which habitat factors influence the regional persistence of endangered Ord's kangaroo rats (Dipodomys ordii) in Alberta, Canada, we simulated population dynamics under a range of habitat conditions. Using a spatially-explicit population model, we removed groups of habitat patches based on their characteristics and measured the resulting time to extinction. We used proportional hazards models to rank the influence of landscape and interacting patch-level variables. Landscape quality was the most influential variable followed by patch quality, with both outweighing landscape- and patch-level measures of habitat quantity and fragmentation/proximity. Although habitat conservation and restoration priorities for this population should be in maximizing the overall quality of the landscape, population persistence depends on how this goal is achieved. Patch quality exerted a significant influence on regional persistence, with the removal of low quality road margin patches (sinks) reducing the risk of regional extinction. Strategies for maximizing overall landscape quality that omit patch-level considerations may produce suboptimal or detrimental results for regional population persistence, particularly where complex local population dynamics (e.g., source-sink dynamics) exist. This study contributes to a growing body literature that suggests that the prediction of species responses and future conservation actions may best be assessed with a multi-scale approach that considers habitat quality and that the success of conservation actions may depend on assessing the influences of habitat factors at multiple scales.     

Predicting greater sage‐grouse habitat selection at the southern periphery of their range

Mapping suitable habitat is an important process in wildlife conservation planning. Species distribution reflects habitat selection processes occurring across multiple spatio‐temporal scales. Because habitat selection may be driven by different factors at different scales, conservation planners require information at the scale of the intervention to plan effective management actions. Previous research has described habitat selection processes shaping the distribution of greater sage‐grouse (Centrocercus urophasianus; sage‐grouse) at the range‐wide scale. Finer‐scale information for applications within jurisdictional units inside the species range is lacking, yet necessary, because state wildlife agencies are the management authority for sage‐grouse in the United States. We quantified seasonal second‐order habitat selection for sage‐grouse across the state of Utah to produce spatio‐temporal predictions of their distribution at the southern periphery of the species range. We used location data obtained from sage‐grouse marked with very‐high‐frequency radio‐transmitters and lek location data collected between 1998 and 2013 to quantify species habitat selection in relation to a suite of topographic, edaphic, climatic, and anthropogenic variables using random forest algorithms. Sage‐grouse selected for greater sagebrush (Artemisia spp.) cover, higher elevations, and gentler slopes and avoided lower precipitations and higher temperatures. The strength of responses to habitat variables varied across seasons. Anthropogenic variables previously reported as affecting their range‐wide distribution (i.e., roads, powerlines, communication towers, and agricultural development) were not ranked as top predictors at our focal scale. Other than strong selection for sagebrush cover, the responses we observed differed from what has been reported at the range‐wide scale. These differences likely reflect the unique climatic, geographic, and topographic context found in the southern peripheral area of the species distribution compared to range‐wide environmental gradients. Our results highlight the importance of considering appropriateness of scale when planning conservation actions for wide‐ranging species.     

Identifying core habitats and corridors for giant pandas by combining multiscale random forest and connectivity analysis

Habitat loss and fragmentation are widely acknowledged as the main driver of the decline of giant panda populations. The Chinese government has made great efforts to protect this charming species and has made remarkable achievements, such as population growth and habitat expansion. However, habitat fragmentation has not been reversed. Protecting giant pandas in a large spatial extent needs to identify core habitat patches and corridors connecting them. This study used an equal‐sampling multiscale random forest habitat model to predict a habitat suitability map for the giant panda. Then, we applied the resistant kernel method and factorial least‐cost path analysis to identify core habitats connected by panda dispersal and corridors among panda occurrences, respectively. Finally, we evaluated the effectiveness of current protected areas in representing core habitats and corridors. Our results showed high scale dependence of giant panda habitat selection. Giant pandas strongly respond to bamboo percentage and elevation at a relatively fine scale (1 km), whereas they respond to anthropogenic factors at a coarse scale (≥2 km). Dispersal ability has significant effects on core habitats extent and population fragmentation evaluation. Under medium and high dispersal ability scenarios (12,000 and 20,000 cost units), most giant panda habitats in the Qionglai mountain are predicted to be well connected by dispersal. The proportion of core habitats covered by protected areas varied between 38% and 43% under different dispersal ability scenarios, highlighting significant gaps in the protected area network. Similarly, only 43% of corridors that connect giant panda occurrences were protected. Our results can provide crucial information for conservation managers to develop wise strategies to safeguard the long‐term viability of the giant panda population.     

Diversity of European habitat types is correlated with geography more than climate and human pressure

Habitat richness, that is, the diversity of ecosystem types, is a complex, spatially explicit aspect of biodiversity, which is affected by bioclimatic, geographic, and anthropogenic variables. The distribution of habitat types is a key component for understanding broad‐scale biodiversity and for developing conservation strategies. We used data on the distribution of European Union (EU) habitats to answer the following questions: (i) how do bioclimatic, geographic, and anthropogenic variables affect habitat richness? (ii) Which of those factors is the most important? (iii) How do interactions among these variables influence habitat richness and which combinations produce the strongest interactions? The distribution maps of 222 terrestrial habitat types as defined by the Natura 2000 network were used to calculate habitat richness for the 10 km × 10 km EU grid map. We then investigated how environmental variables affect habitat richness, using generalized linear models, generalized additive models, and boosted regression trees. The main factors associated with habitat richness were geographic variables, with negative relationships observed for both latitude and longitude, and a positive relationship for terrain ruggedness. Bioclimatic variables played a secondary role, with habitat richness increasing slightly with annual mean temperature and overall annual precipitation. We also found an interaction between anthropogenic variables, with the combination of increased landscape fragmentation and increased population density strongly decreasing habitat richness. This is the first attempt to disentangle spatial patterns of habitat richness at the continental scale, as a key tool for protecting biodiversity. The number of European habitats is related to geography more than climate and human pressure, reflecting a major component of biogeographical patterns similar to the drivers observed at the species level. The interaction between anthropogenic variables highlights the need for coordinated, continental‐scale management plans for biodiversity conservation.     

Habitat selection in a fluctuating ground squirrel population: Density‐dependence and fitness consequences

Investigating individual‐based habitat settlement decisions is a central theme in ecology, yet studies that quantify density‐dependent habitat selection or tie fitness to resource selection decisions remain rare. We quantified habitat selection in golden‐mantled ground squirrels (Callospermophilus lateralis) across two spatial scales (home‐range placement, and occurrence within the home range) by using 11 consecutive years of data on individual space use, and we used resource selection functions and multilevel modeling to address how habitat preferences may be influenced by density or linked to fitness outcomes. Squirrels preferred dry meadow over other habitat types (wet meadow, aspen, spruce, and willow) at both spatial scales. Squirrels were more likely to use dry meadow that contained shorter vegetation and vision‐enhancing prominences such as rocks (“perches”). The use of dry meadow at each scale was not influenced by changes in density. The use of dry meadow did not lead to increased litter size, pre‐hibernation mass, or survival. However, squirrels that experienced a greater number of perches or lower local densities had higher survival rates. Our results suggest that a lack of visual obstruction, probably facilitating detection of predators, drives habitat selection in this system. Surprisingly, squirrels maintained their preference for dry meadow as density increased, and they experienced reduced survival as a result. This work furthers our understanding about the causes and consequences of changes in habitat use, informing wildlife management and conservation.     

Predicting the Distribution Pattern of Small Carnivores in Response to Environmental Factors in the Western Ghats

Due to their secretive habits, predicting the pattern of spatial distribution of small carnivores has been typically challenging, yet for conservation management it is essential to understand the association between this group of animals and environmental factors. We applied maximum entropy modeling (MaxEnt) to build distribution models and identify environmental predictors including bioclimatic variables, forest and land cover type, topography, vegetation index and anthropogenic variables for six small carnivore species in Mudumalai Tiger Reserve. Species occurrence records were collated from camera-traps and vehicle transects during the years 2010 and 2011. We used the average training gain from forty model runs for each species to select the best set of predictors. The area under the curve (AUC) of the receiver operating characteristic plot (ROC) ranged from 0.81 to 0.93 for the training data and 0.72 to 0.87 for the test data. In habitat models for F. chaus, P. hermaphroditus, and H. smithii “distance to village” and precipitation of the warmest quarter emerged as some of the most important variables. “Distance to village” and aspect were important for V. indica while “distance to village” and precipitation of the coldest quarter were significant for H. vitticollis. “Distance to village”, precipitation of the warmest quarter and land cover were influential variables in the distribution of H. edwardsii. The map of predicted probabilities of occurrence showed potentially suitable habitats accounting for 46 km² of the reserve for F. chaus, 62 km² for V. indica, 30 km² for P. hermaphroditus, 63 km² for H. vitticollis, 45 km² for H. smithii and 28 km² for H. edwardsii. Habitat heterogeneity driven by the east-west climatic gradient was correlated with the spatial distribution of small carnivores. This study exemplifies the usefulness of modeling small carnivore distribution to prioritize and direct conservation planning for habitat specialists in southern India.     

At what spatial scales does resource selection vary? A case study of koalas in a semi‐arid region

The conservation of any species requires understanding and predicting the distribution of its habitat and resource use, including the effects of scale‐dependent variation in habitat and resource quality. Consequently, testing for resource selection at the appropriate scales is critical. We investigated how the resource selection process varies across scales, using koalas in a semi‐arid landscape of eastern Australia as a case study. We asked: at what scales does tree selection by koalas vary across regions? We tested the importance of the variation of our ecological predictors at the following scales: (i) the site‐scale (a stand of trees representing an individual koala's perception of local habitat); (ii) the landscape‐scale (10 × 10 km area representing a space within which a population of koalas exists); and (iii) a combination of these scales. We used a mixed‐modelling approach to quantify variation in selection of individual trees by koalas among sites and landscapes within a 1600 km² study area. We found that tree species, and tree height, were the most important factors influencing tree selection, and that their effect did not vary across scales. In contrast, preferences for trees of different condition, which is the state of tree canopy health, did vary across landscapes, indicating spatial variation in the selection of trees with respect to tree condition at the landscape‐scale, but not at the site‐scale. We conclude that resource selection processes can depend on the quality of those resources at different scales and their heterogeneous nature across landscapes, highlighting the consequence of scale‐dependent ecological processes. Designing studies that capture the heterogeneity in habitat and resources used by species that have an extensive distribution is an important prerequisite for effective conservation planning and management.     

Reconsidering the Specialist-Generalist Paradigm in Niche Breadth Dynamics: Resource Gradient Selection by Canada Lynx and Bobcat

The long-standing view in ecology is that disparity in overall resource selection is the basis for identifying niche breadth patterns, with species having narrow selection being classified “specialists” and those with broader selection being “generalists”. The standard model of niche breadth characterizes generalists and specialists as having comparable levels of overall total resource exploitation, with specialists exploiting resources at a higher level of performance over a narrower range of conditions. This view has gone largely unchallenged. An alternate model predicts total resource use being lower for the specialized species with both peaking at a comparable level of performance over a particular resource gradient. To reconcile the niche breadth paradigm we contrasted both models by developing range-wide species distribution models for Canada lynx, Lynx canadensis, and bobcat, Lynx rufus. Using a suite of environmental factors to define each species’ niche, we determined that Canada lynx demonstrated higher total performance over a restricted set of variables, specifically those related to snow and altitude, while bobcat had higher total performance across most variables. Unlike predictions generated by the standard model, bobcat level of exploitation was not compromised by the trade-off with peak performance, and Canada lynx were not restricted to exploiting a narrower range of conditions. Instead, the emergent pattern was that specialist species have a higher total resource utilization and peak performance value within a smaller number of resources or environmental axes than generalists. Our results also indicate that relative differences in niche breadth are strongly dependent on the variable under consideration, implying that the appropriate model describing niche breadth dynamics between specialists and generalists may be more complex than either the traditional heuristic or our modified version. Our results demonstrate a need to re-evaluate traditional, but largely untested, assumptions regarding resource utilization in species with broad and narrow niches.     

Are Sage-Grouse Fine-Scale Specialists or Shrub-Steppe Generalists?

Sage-grouse (Centrocercus spp.) are influencing rapidly evolving land management policy in the western United States. Management objectives for fine-scale vegetation characteristics (e.g., grass height >18 cm) have been adopted by land management agencies based on resource selection or relationships with fitness proxies reported among numerous habitat studies. Some managers, however, have questioned the appropriateness of these objectives. Moreover, it remains untested whether habitat–fitness relationships documented at fine scales (i.e., among individual nests within a study area) also apply at scales of management units (e.g., pastures or grazing allotments), which are many orders of magnitude larger. We employed meta-analyses of studies published from 1991 to 2019 to help resolve the role of fine-scale vegetation structure in nest site selection and nest success across the geographic range of greater sage-grouse (C. urophasianus) and evaluate the validity of established habitat management objectives. Specifically, we incorporated effects of study design and functional responses to resource availability in meta-regression models linking vegetation structure to nest site selection, and used a novel meta-analytic approach to simultaneously model vegetation structure and its relationship to nest success. Our approach tested habitat relationships at a range-wide extent and a grain size closely matching scales at which agencies make management decisions. We found moderate, but context-dependent, effects of shrub characteristics and weak effects of herbaceous vegetation on nest site selection. None of the tested vegetation characteristics were related to variation in nest success, suggesting nesting habitat–fitness relationships have been inappropriately extrapolated in developing range-wide habitat management objectives. Our findings reveal surprising flexibility in habitat use for a species often depicted as having very particular fine-scale habitat requirements, and cast doubt on the practice of adopting precise management objectives for vegetation structure based on findings of individual small-scale field studies. © 2020 The Authors. The Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.     

Scale‐dependent determinants of plant species richness in a semi‐arid fragmented agro‐ecosystem

Aims: (1) Understanding how the relationship between species richness and its determinants depends on the interaction between scales at which the response and explanatory variables are measured. (2) Quantifying the relative contributions of local, intermediate and large‐scale determinants of species richness in a fragmented agro‐ecosystem. (3) Testing the hypothesis that the relative contribution of these determinants varies with the grain size at which species richness is measured. Location: A fragmented agro‐ecosystem in the Southern Judea Lowland, Israel, within a desert–Mediterranean transition zone. Methods: Plant species richness was estimated using hierarchical nested sampling in 81 plots, positioned in 38 natural vegetation patches within an agricultural matrix (mainly wheat fields) among three land units along a sharp precipitation gradient. Explanatory variables included position along that gradient, patch area, patch isolation, habitat heterogeneity and overall plant density. We used general linear models and hierarchical partitioning of variance to test and quantify the effect of each explanatory variable on species richness at four grain sizes (0.0625, 1, 25 and 225 m²). Results: Species richness was mainly affected by position along a precipitation gradient and overall plant density, and to a lesser extent by habitat heterogeneity. It was also significantly affected by patch area and patch isolation, but only for small grain sizes. The contribution of each explanatory variable to explained variance in species richness varied with grain size, i.e. scale‐dependent. The influence of geographic position and habitat heterogeneity on species richness increased with grain size, while the influence of plant density decreased with grain size. Main conclusions: Species richness is determined by the combined effect of several scale‐dependent determinants. Ability to detect an effect and effect size of each determinant varies with the scale (grain size) at which it is measured. The combination of a multi‐factorial approach and multi‐scale sampling reveals that conclusions drawn from studies that ignore these dimensions are restricted and potentially misleading.     

Spatial variation in antler investment of Apennine red deer

Heterogeneity in resource availability and quality can trigger spatial patterns in the expression of sexually selected traits such as body mass and weaponry. While relationships between habitat features and phenotypic quality are well established at broad geographical scales, information is poor on spatial patterns at finer, intrapopulation scales. We analyzed biometric data collected on 1965 red deer Cervus elaphus males over 20 years from a nonmigratory population living on two sides of a mountainous ridge, with substantial differences in land cover and habitat quality but similar climate and population density. We investigate spatial patterns in (i) body mass, (ii) antler mass, and (iii) antler investment. We also tested for site‐ and age‐specific patterns in allometric relationship between body mass and antler mass. Statistically significant fine‐scale spatial variations in body mass, antler mass, and, to a lesser extent, antler allocation matched spatial differences in land cover. All three traits were greater in the northern slope, characterized by higher habitat heterogeneity and greater availability of open habitats, than in the southern slope. Moreover, the allometric relationship between body mass and antler mass differed among age‐classes, in a pattern that was consistent between the two mountain slopes. Our results support the occurrence of spatial patterns in the expression of individual attributes also at a fine, intrapopulation scale. Our findings emphasize the role of environmental heterogeneity in shaping spatial variations of key life‐history traits, with potential consequences for reproductive success.     

Little evidence for climate effects on local-scale structure and dynamics of California kelp forest communities

Climatic variables such as temperature and precipitation play an important role in controlling local and regional scale differences in population dynamics and species distributions, and large-scale climatic events such as El Niño southern oscillation (ENSO) have been shown to affect population dynamics of key species in many ecosystems, particularly in kelp forests. Few studies have been able to evaluate the consequences of climate variables on the structure and dynamics of biological communities, in large part because the lack of data at appropriate spatial and temporal scales has made it difficult to adequately address local-scale responses of species and communities to such events over relevant time scales. Here, we combined an unprecedented dataset of kelp forest species' abundances from the Channel Islands, California with data for several local, regional, and global scale climatic variables to evaluate the temporal and spatial scale at which one can detect community-wide effects of climate variables, in particular ENSO events. We found large and significant local-scale differences in community structure, but these differences were not related to differences in climatic variables. Moreover, giant kelp abundance, which has been shown to be highly sensitive to water temperature and storm disturbance, was a poor predictor of community differences, and all communities tended to decline in abundance over the 20-year sampling period, suggesting a press perturbation to the system such as PDO cycles or sustained fishing pressure. Although ENSO events can have dramatic impacts on the abundance and distribution of giant kelp itself across the range of the species, such events appear to have little effect on local-scale kelp forest community structure or dynamics.     

Landscape‐ and small‐scale determinants of grassland species diversity: direct and indirect influences

Species richness is influenced both by mechanisms occurring at landscape scales, such as habitat availability, and local‐scale processes, that are related to abiotic conditions and plant–plant interactions. However, it is rarely tested to what extent local species richness can be explained by the combined effect of factors measured at multiple spatial scales. In this study, we quantified the simultaneous influence of historical landscape‐scale factors (past human population density, and past habitat availability – an index combining area and connectivity) and small‐scale environmental conditions (shrub cover, and heterogeneity of light, soil depth, and other soil environmental variables) on plant species richness in dry calcareous grasslands (alvars). By applying structural equation modelling (SEM) we found that both landscape conditions and local environmental factors had significant direct and indirect (i.e. through the modification of another factor), effects on species richness. At the landscape scale, we found a direct positive influence of historical habitat availability on species richness, and indirect positive influence of past human population (via its effects on historical habitat availability). At small scales, we found a positive direct influence of light heterogeneity and shrub cover on species richness. Conversely, we found that small‐scale soil environmental heterogeneity, which was mainly determined by soil depth heterogeneity, had a negative effect on species richness. Our study indicates that patterns of species richness in alvar grasslands are positively influenced by the anthropogenic management regime that maintained the landscape habitat conditions in the past. However, the abandonment of management, leading to shrub invasion and increased competition for light resources also influenced species richness. In contrast to the positive heterogeneity–diversity relationship we found that soil heterogeneity reduced species richness. Environmental heterogeneity, occurring at the plant neighbourhood scale (i.e. centimetres), can increase the isolation among suitable soil patches and thus hinder the normal functioning of populations. The combination of previous knowledge of the system with new ecological theories facilitates disentangling how species richness responds to complex relationships among factors operating at multiple scales.     

Reconstruction of the historical range alters niche estimates in an endangered rodent

Defining historical baselines is critical for species conservation. Under the niche reduction hypothesis, species in decline may be restricted disproportionately from parts of their environmental niche. This bias likely has important implications for modeling species’ distributions if only contemporary occurrences (i.e. post‐range reduction) are used, because suitable habitat will be classified as unsuitable. Unfortunately, robust historical occurrence data is rarely available for sensitive species. In this study, we documented historical locations of the endangered, keystone giant kangaroo rat Dipodomys ingens by examining aerial imagery for burrow mounds. These burrow mounds are readily identifiable and distinguishable from other soil disturbances. We found giant kangaroo rat burrows well outside the currently accepted estimate of their historical distribution. Following the niche reduction hypothesis, we found that giant kangaroo rats have been extirpated from the flattest, hottest, driest parts of their range due to agricultural conversion. This reduction in their realized niche led to significant changes between historical and contemporary models of their distribution. We found that giant kangaroo rats may have occupied up to 56% more habitat historically than currently believed. Our results provide new guidance for managers working on restoration and habitat protection for this ecosystem engineer. This study highlights the critical importance of modeling historical distributions using the entire environmental niche once occupied by species of conservation need.     

SCALE-DEPENDENT SUMMER RESOURCE SELECTION BY REINTRODUCED ELK IN WISCONSIN,USA

Abstract: Identifying how habitat use is influenced by environmental heterogeneity at different scales is central to understanding ungulate population dynamics on complex landscapes. We used resource selection functions (RSF) to study summer habitat use in a reintroduced and expanding elk (Cervus elaphus nelsoni) population in the Chequamegon National Forest, Wisconsin, USA. Factors were examined that influenced where elk established home ranges and that influenced habitat use within established home ranges. We also determined grain sizes over which elk responded to environmental heterogeneity and the number of categories of habitat selection from low to high that the elk distinguished. At a large spatial extent, elk home-range establishment was largely explained by the spatial distribution of wolf (Canis lupus) territories. Forage abundance was also influential but was relatively more important at a small spatial extent when elk moved within established home ranges. Areas near roads were avoided when establishing a home-range, but areas near roads were selected for use within the established home range. Elk distinguished among 4 different categories of habitat selection when establishing and moving within home ranges. Spatial and temporal cross validation demonstrated that to improve the predictive strength of habitat models in areas of low inter-annual variability in the environment, it is better to follow more individuals across diverse environmental conditions than to follow the same individuals over a longer time period. Last, our results show that the effects of environmental variables on habitat use were scale-dependent and reemphasize the necessity of analyzing habitat use at multiple scales that are fit to address specific research questions.     

Habitat loss exacerbates pathogen spread: An Agent-based model of avian influenza infection in migratory waterfowl

Habitat availability determines the distribution of migratory waterfowl along their flyway, which further influences the transmission and spatial spread of avian influenza viruses (AIVs). The extensive habitat loss in the East Asian-Australasian Flyway (EAAF) may have potentially altered the virus spread and transmission, but those consequences are rarely studied. We constructed 6 fall migration networks that differed in their level of habitat loss, wherein an increase in habitat loss resulted in smaller networks with fewer sites and links. We integrated an agent-based model and a susceptible-infected-recovered model to simulate waterfowl migration and AIV transmission. We found that extensive habitat loss in the EAAF can 1) relocate the outbreaks northwards, responding to the distribution changes of wintering waterfowl geese, 2) increase the outbreak risk in remaining sites due to larger goose congregations, and 3) facilitate AIV transmission in the migratory population. In addition, our modeling output was in line with the predictions from the concept of “migratory escape”, i.e., the migration allows the geese to “escape” from the location where infection risk is high, affecting the pattern of infection prevalence in the waterfowl population. Our modeling shed light on the potential consequences of habitat loss in spreading and transmitting AIV at the flyway scale and suggested the driving mechanisms behind these effects, indicating the importance of conservation in changing spatial and temporal patterns of AIV outbreaks.     

Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts

Conservation increasingly operates at the landscape scale. For this to be effective, we need landscape scale information on species distributions and the environmental factors that underpin them. Species records are becoming increasingly available via data centres and online portals, but they are often patchy and biased. We demonstrate how such data can yield useful habitat suitability models, using bat roost records as an example. We analysed the effects of environmental variables at eight spatial scales (500 m – 6 km) on roost selection by eight bat species (Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula, Myotis mystacinus, M. brandtii, M. nattereri, M. daubentonii, and Plecotus auritus) using the presence-only modelling software MaxEnt. Modelling was carried out on a selection of 418 data centre roost records from the Lake District National Park, UK. Target group pseudoabsences were selected to reduce the impact of sampling bias. Multi-scale models, combining variables measured at their best performing spatial scales, were used to predict roosting habitat suitability, yielding models with useful predictive abilities. Small areas of deciduous woodland consistently increased roosting habitat suitability, but other habitat associations varied between species and scales. Pipistrellus were positively related to built environments at small scales, and depended on large-scale woodland availability. The other, more specialist, species were highly sensitive to human-altered landscapes, avoiding even small rural towns. The strength of many relationships at large scales suggests that bats are sensitive to habitat modifications far from the roost itself. The fine resolution, large extent maps will aid targeted decision-making by conservationists and planners. We have made available an ArcGIS toolbox that automates the production of multi-scale variables, to facilitate the application of our methods to other taxa and locations. Habitat suitability modelling has the potential to become a standard tool for supporting landscape-scale decision-making as relevant data and open source, user-friendly, and peer-reviewed software become widely available.     

Effects of Prey Presence and Scale on Bobcat Resource Selection during Winter

Factors relevant to resource selection in carnivores may vary across spatial and temporal scales, both in magnitude and rank. Understanding relationships among carnivore occupancy, prey presence, and habitat characteristics, as well as their interactions across multiple scales, is necessary to improve our understanding of resource selection and predict population changes. We used a multi-scale dynamic hierarchical co-occurrence model with camera data to study bobcat and snowshoe hare occupancy in the Upper Peninsula of Michigan during winter 2012–2013. Bobcat presence was influenced at the local scale by snowshoe hare presence, and by road density at the local and larger scale when hare were absent. Hare distribution was related primarily to vegetation cover types, and detectability varied in space and time. Bobcat occupancy dynamics were influenced by different factors depending on the spatial scale considered and the resource availability context. Moreover, considering observed co-occurrence, we suggest that bobcat presence had a greater effect on hare occupancy than hare presence on bobcat occupancy. Our results highlight the importance of studying carnivore distributions in the context of predator-prey relationships and its interactions with environmental covariates at multiple spatial scales. Our approach can be applied to other carnivore species to provide insights beneficial for management and conservation.     

Untangling climate and water chemistry to predict changes in freshwater macrophyte distributions

Forecasting changes in the distributions of macrophytes is essential to understanding how aquatic ecosystems will respond to climate and environmental changes. Previous work in aquatic ecosystems has used climate data at large scales and chemistry data at small scales; the consequence of using these different data types has not been evaluated. This study combines a survey of macrophyte diversity and water chemistry measurements at a large regional scale to demonstrate the feasibility and necessity of including ecological measurements, in addition to climate data, in species distribution models of aquatic macrophytes. A survey of 740 water bodies stratified across 327,000 square kilometers was conducted to document Characeae (green macroalgae) species occurrence and water chemistry data. Chemistry variables and climate data were used separately and in concert to develop species distribution models for ten species across the study area. The impacts of future environmental changes on species distributions were modeled using a range of global climate models (GCMs), representative concentration pathways (RCPs), and pollution scenarios. Models developed with chemistry variables generally gave the most accurate predictions of species distributions when compared with those using climate variables. Calcium and conductivity had the highest total relative contribution to models across all species. Habitat changes were most pronounced in scenarios with increased road salt and deicer influences, with two species predicted to increase in range by >50% and four species predicted to decrease in range by >50%. Species of Characeae have distinct habitat ranges that closely follow spatial patterns of water chemistry. Species distribution models built with climate data alone were insufficient to predict changes in distributions in the study area. The development and implementation of standardized, large‐scale water chemistry databases will aid predictions of habitat changes for aquatic ecosystems.