Silvicolous on a Small Scale: Possibilities and Limitations of Habitat Suitability Models for Small,Elusive Mammals in Conservation Management and Landscape Planning

Species distribution and endangerment can be assessed by habitat-suitability modelling. This study addresses methodical aspects of habitat suitability modelling and includes an application example in actual species conservation and landscape planning. Models using species presence-absence data are preferable to presence-only models. In contrast to species presence data, absences are rarely recorded. Therefore, many studies generate pseudo-absence data for modelling. However, in this study model quality was higher with null samples collected in the field. Next to species data the choice of landscape data is crucial for suitability modelling. Landscape data with high resolution and ecological relevance for the study species improve model reliability and quality for small elusive mammals like Muscardinus avellanarius. For large scale assessment of species distribution, models with low-detailed data are sufficient. For regional site-specific conservation issues like a conflict-free site for new wind turbines, high-detailed regional models are needed. Even though the overlap with optimally suitable habitat for M. avellanarius was low, the installation of wind plants can pose a threat due to habitat loss and fragmentation. To conclude, modellers should clearly state the purpose of their models and choose the according level of detail for species and environmental data.     

Modelling habitat-suitability using museum collections: an example with three sympatric Apodemus species from the Alps

Aim, Location Although the alpine mouse Apodemus alpicola has been given species status since 1989, no distribution map has ever been constructed for this endemic alpine rodent in Switzerland. Based on redetermined museum material and using the Ecological-Niche Factor Analysis (ENFA), habitat-suitability maps were computed for A. alpicola , and also for the co-occurring A. flavicollis and A. sylvaticus .
Methods In the particular case of habitat suitability models, classical approaches (GLMs, GAMs, discriminant analysis, etc.) generally require presence and absence data. The presence records provided by museums can clearly give useful information about species distribution and ecology and have already been used for knowledge-based mapping. In this paper, we apply the ENFA which requires only presence data, to build a habitat-suitability map of three species of Apodemus on the basis of museum skull collections.
Results Interspecific niche comparisons showed that A. alpicola is very specialized concerning habitat selection, meaning that its habitat differs unequivocally from the average conditions in Switzerland, while both A. flavicollis and A. sylvaticus could be considered as 'generalists' in the study area.
Main conclusions Although an adequate sampling design is the best way to collect ecological data for predictive modelling, this is a time and money consuming process and there are cases where time is simply not available, as for instance with endangered species conservation. On the other hand, museums, herbariums and other similar institutions are treasuring huge presence data sets. By applying the ENFA to such data it is possible to rapidly construct a habitat suitability model. The ENFA method not only provides two key measurements regarding the niche of a species (i.e. marginality and specialization), but also has ecological meaning, and allows the scientist to compare directly the niches of different species.     

A novel method for targeting survey effort to identify new bat roosts using habitat suitability modelling

In the UK, four out of 18 bat species are listed on the EU Habitats Directive, including the lesser horseshoe bat (Rhinolophus hipposideros), and their population status is closely monitored by visiting known roosts. R. hipposideros predominantly form maternity roosts in buildings, but roosts are impermanent features in the landscape and their distribution changes as bats form new roosts and abandon others. Locating new roosts requires intensive surveys which are challenging and inefficient. In this study, we provide a novel model-based strategy to identify potential R. hipposideros maternity roost sites that can be used to monitor bat populations. First, we model potential maternity roost habitat using record centre data on roost locations across Wales, Great Britain. We then constrain the area identified from modelling using record centre data on locations of bats in areas with no known roosts. We used two variable selection methods and three pseudo-absence data sets (random background points, random points in buildings and target group selection of mammal records) to produce six habitat suitability models. The three pseudo-absence data sets produced different habitat suitability maps, demonstrating the influence of pseudo-absence selection on species distribution models. The six models were combined using weighted mean average to produce an ensemble model that performed better than individual models and that indicated high levels of congruence in areas predicted to have high habitat suitability for maternity roosts. Our model revealed an extensive area (6523 km²; 31% of the area of Wales) containing 18,051 buildings in suitable habitat. Using record centre data on bat activity outside commuting range from known roosts reduced the potential survey area to 133 km² (0.6% of the area of Wales) and 207 buildings. Our modelling outputs can be used to direct volunteers and bat surveyors in more targeted and efficient searches.     

Predicting habitat distribution and frequency from plant species co-occurrence data

Aim Species frequency data have been widely used in nature conservation to aid management decisions. To determine species frequencies, information on habitat occurrence is important: a species with a low frequency is not necessarily rare if it occupies all suitable habitats. Often, information on habitat distribution is available for small geographic areas only. We aim to predict grid‐based habitat occurrence from grid‐based plant species distribution data in a meso‐scale analysis. Location The study was carried out over two spatial extents: Germany and Bavaria. Methods Two simple models were set up to examine the number of characteristic plant species needed per grid cell to predict the occurrence of four selected habitats (species data from FlorKart, http://www.floraweb.de ). Both models were calibrated in Bavaria using available information on habitat distribution, validated for other federal states, and applied to Germany. First, a spatially explicit regression model (generalized linear model (GLM) with assumed binomial error distribution of response variable) was obtained. Second, a spatially independent optimization model was derived that estimated species numbers without using spatial information on habitat distribution. Finally, an additional uncalibrated model was derived that calculated the frequencies of 24 habitats. It was validated using NATURA2000 habitat maps. Results Using the Bavarian models it was possible to predict habitat distribution and frequency from the co‐occurrence of habitat‐specific species per grid cell. As the model validations for other German federal states were successful, the models were applied to all of Germany, and habitat distribution and frequencies could be retrieved for the national scale on the basis of habitat‐specific species co‐occurrences per grid cell. Using the third, uncalibrated model, which includes species distribution data only, it was possible to predict the frequencies of 24 habitats based on the co‐occurrence of 24% of formation‐specific species per grid cell. Predicted habitat frequencies deduced from this third model were strongly related to frequencies of NATURA2000 habitat maps. Main conclusions It was concluded that it is possible to deduce habitat distributions and frequencies from the co‐occurrence of habitat‐specific species. For areas partly covered by habitat mappings, calibrated models can be developed and extrapolated to larger areas. If information on habitat distribution is completely lacking, uncalibrated models can still be applied, providing coarse information on habitat frequencies. Predicted habitat distributions and frequencies can be used as a tool in nature conservation, for example as correction factors for species frequencies, as long as the species of interest is not included in the model set‐up.     

Can pinewoods provide habitat for a deciduous forest specialist? A two-scale approach to the habitat selection of Bechstein's bat

Populations of Myotis bechsteinii in Sierra de Cazorla, Segura y Las Villas Natural Park (southwestern Spain) survive in a large, old-growth coniferous woodland, which is in contrast with known ecological preferences of the species. We tracked ten lactating females and studied patterns of habitat selection by Bechstein's bat (Myotis bechsteinii) at two spatial scales: macrohabitat and microhabitat, regarding forest essence (coniferous vs. deciduous). The tracked individuals always foraged within forested areas and did not use areas devoid of trees. At the macrohabitat level, no positive selection of deciduous stands was apparent, suggesting selection studies of coarse resolution may not be able to capture subtle selection patterns. At the microhabitat level Myotis bechsteinii selected deciduous patches within the coniferous matrix, therefore, our results corroborate the perception of this species as dependent of services provided by deciduous woodlands. Larger foraging home ranges and commuting distances as compared with other Mediterranean localities suggest that our studied population inhabits a marginal or suboptimal environment in terms of habitat quality. We argue that this population of Bechstein's bat has survived as a relict one probably as a consequence of fragmentation and transformation of deciduous forest ecosystems in the Mediterranean range.     

Integrating Multiple Distribution Models to Guide Conservation Efforts of an Endangered Toad

Species distribution models are used for numerous purposes such as predicting changes in species’ ranges and identifying biodiversity hotspots. Although implications of distribution models for conservation are often implicit, few studies use these tools explicitly to inform conservation efforts. Herein, we illustrate how multiple distribution models developed using distinct sets of environmental variables can be integrated to aid in identification sites for use in conservation. We focus on the endangered arroyo toad (Anaxyrus californicus), which relies on open, sandy streams and surrounding floodplains in southern California, USA, and northern Baja California, Mexico. Declines of the species are largely attributed to habitat degradation associated with vegetation encroachment, invasive predators, and altered hydrologic regimes. We had three main goals: 1) develop a model of potential habitat for arroyo toads, based on long-term environmental variables and all available locality data; 2) develop a model of the species’ current habitat by incorporating recent remotely-sensed variables and only using recent locality data; and 3) integrate results of both models to identify sites that may be employed in conservation efforts. We used a machine learning technique, Random Forests, to develop the models, focused on riparian zones in southern California. We identified 14.37% and 10.50% of our study area as potential and current habitat for the arroyo toad, respectively. Generally, inclusion of remotely-sensed variables reduced modeled suitability of sites, thus many areas modeled as potential habitat were not modeled as current habitat. We propose such sites could be made suitable for arroyo toads through active management, increasing current habitat by up to 67.02%. Our general approach can be employed to guide conservation efforts of virtually any species with sufficient data necessary to develop appropriate distribution models.     

Reconstructing range dynamics and range fragmentation of European bison for the last 8000 years

Aim Understanding what constituted species’ ranges prior to large‐scale human influence, and how past climate and land use change have affected range dynamics, provides conservation planners with important insights into how species may respond to future environmental change. Our aim here was to reconstruct the Holocene range of European bison (Bison bonasus) by combining a time‐calibrated species distribution models (SDM) with a dynamic vegetation model. Location Europe. Method We used European bison occurrences from the Holocene in a maximum entropy model to assess bison range dynamics during the last 8000 years. As predictors, we used bioclimatic variables and vegetation reconstructions from the generalized dynamic vegetation model LPJ‐GUESS. We compared our range maps with maps of farmland and human population expansion to identify the main species range constraints. Results The Holocene distribution of European bison was mainly determined by vegetation patterns, with bison thriving in both broadleaved and coniferous forests, as well as by mean winter temperature. The heartland of European bison was in Central and Eastern Europe, whereas suitable habitat in Western Europe was scarce. While environmentally suitable regions were overall stable, the expansion of settlements and farming severely diminished available habitat. Main conclusions European bison habitat preferences may be wider than previously assumed, and our results suggest that the species had a more eastern and northern distribution than previously reported. Vegetation and climate transformation during the Holocene did not affect the bison’s range substantially. Conversely, human population growth and the spread of farming resulted in drastic bison habitat loss and fragmentation, likely reaching a tipping point during the last 1000 years. Combining SDM and dynamic vegetation models can improve range reconstructions and projections, and thus help to identify resilient conservation strategies for endangered species.     

Habitat selection of three cryptic Plecotus bat species in the European Alps reveals contrasting implications for conservation

Assessing the ecological requirements of species coexisting within a community is an essential requisite for developing sound conservation action. A particularly interesting question is what mechanisms govern the stable coexistence of cryptic species within a community, i.e. species that are almost impossible to distinguish. Resource partitioning theory predicts that cryptic species, like other sympatric taxa, will occupy distinct ecological niches. This prediction is widely inferred from eco-morphological studies. A new cryptic long-eared bat species, Plecotus macrobullaris, has been recently discovered in the complex of two other species present in the European Alps, with even evidence for a few mixed colonies. This discovery poses challenges to bat ecologists concerned with planning conservation measures beyond roost protection. We therefore tested whether foraging habitat segregation occurred among the three cryptic Plecotus bat species in Switzerland by radiotracking 24 breeding female bats (8 of each species). We compared habitat features at locations visited by a bat versus random locations within individual home ranges, applying mixed effects logistic regression. Distinct, species-specific habitat preferences were revealed. P. auritus foraged mostly within traditional orchards in roost vicinity, with a marked preference for habitat heterogeneity. P. austriacus foraged up to 4.7 km from the roost, selecting mostly fruit tree plantations, hedges and tree lines. P. macrobullaris preferred patchy deciduous and mixed forests with high vertical heterogeneity in a grassland dominated-matrix. These species-specific habitat preferences should inform future conservation programmes. They highlight the possible need of distinct conservation measures for species that look very much alike.     

Fauna habitat modelling and mapping: A review and case study in the Lower Hunter Central Coast region of NSW

Abstract Habitat models are now broadly used in conservation planning on public lands. If implemented correctly, habitat modelling is a transparent and repeatable technique for describing and mapping biodiversity values, and its application in peri‐urban and agricultural landscape planning is likely to expand rapidly. Conservation planning in such landscapes must be robust to the scrutiny that arises when biodiversity constraints are placed on developers and private landholders. A standardized modelling and model evaluation method based on widely accepted techniques will improve the robustness of conservation plans. We review current habitat modelling and model evaluation methods and provide a habitat modelling case study in the New South Wales central coast region that we hope will serve as a methodological template for conservation planners. We make recommendations on modelling methods that are appropriate when presence‐absence and presence‐only survey data are available and provide methodological details and a website with data and training material for modellers. Our aim is to provide practical guidelines that preserve methodological rigour and result in defendable habitat models and maps. The case study was undertaken in a rapidly developing area with substantial biodiversity values under urbanization pressure. Habitat maps for seven priority fauna species were developed using logistic regression models of species‐habitat relationships and a bootstrapping methodology was used to evaluate model predictions. The modelled species were the koala, tiger quoll, squirrel glider, yellow‐bellied glider, masked owl, powerful owl and sooty owl. Models ranked sites adequately in terms of habitat suitability and provided predictions of sufficient reliability for the purpose of identifying preliminary conservation priority areas. However, they are subject to multiple uncertainties and should not be viewed as a completely accurate representation of the distribution of species habitat. We recommend the use of model prediction in an adaptive framework whereby models are iteratively updated and refined as new data become available.     

Habitat suitability models to make conservation decisions based on areas of high species richness and endemism

Biodiversity positively relates with the provisioning of ecosystem services and preserving areas with elevated diversity of highly-functional species could help to ensure human well-being. Most studies addressed to make these decisions use maps relying on species occurrences, where sites containing several species are proposed as priority conservation areas. These maps, however, may underestimate species richness because of the incompleteness of occurrence data. To improve this methodology, we propose using habitat suitability models to estimate the potential distribution of species from occurrence data, and later shaping richness maps by overlapping these predicted distribution ranges. We tested this proposal with Mexican oaks because they provide several ecosystem services and habitat suitability models of species were calibrated with MaxEnt. We used linear regressions to compare the outputs of these predictive maps with those of maps based on species occurrences only and, for both mapping methods, we assessed how much surface of sites with elevated richness and endemism of oaks is currently included within nature reserves. Both mapping methods indicated that oak species are concentrated in mountain regions of Mexico, but predictive maps based on habitat suitability models indicated higher oak richness and endemism that maps based on species occurrences only. Our results also indicated that nature reserves cover a small fraction of areas harboring elevated richness and endemism of oaks. These results suggest that estimating richness across extensive geographic regions using habitat suitability models quickly provides accurate information to make conservation decisions for highly-functional species groups.     

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.     

Genetic structure and diversity of a rare woodland bat, <Emphasis Type="Italic">Myotis bechsteinii</Emphasis>: comparison of continental Europe and Britain

The Bechstein’s bat (Myotis bechsteinii) is a rare sedentary bat considered to be highly reliant on the presence of ancient woodland. Understanding the genetic connectivity and population structure of such elusive mammals is important for assessing their conservation status. In this study, we report the genetic diversity and structure of M. bechsteinii across Britain and Europe. Assessments were made using 14 microsatellite markers and a 747 bp region of the mitochondrial cytochrome b gene. Nuclear DNA (microsatellites) showed high levels of genetic diversity and little inbreeding across the species range, though genetic diversity was slightly lower in Britain than in mainland Europe. Bayesian and spatial PCA analysis showed a clear separation between the British and European sites. Within Europe, the Italian population south of the Alps was isolated from the other sites. In Britain, there was genetic structuring between the northern and southern part of the geographical range. Despite there being little genetic divergence in mitochondrial DNA (mtDNA) sequences throughout most of Europe, the mtDNA patterns in Britain confirmed this separation of northern and southern populations. Such genetic structuring within Britain—in the absence of any obvious physical barriers—suggests that other factors such as land-use may limit gene-flow.     

Predicting Distribution and Density of European Badger (<Emphasis Type="Italic">Meles Meles</Emphasis>) Setts in Denmark

Predictive models of the spatial distribution and abundance of species based on habitat characteristics are finding increasing use in management and conservation. The European badger attracts interest as a model species both for conservation reasons and because of the important role the species is playing in understanding carnivore sociality. We developed a statistical habitat model based on presence/absence data on badger setts. To maximise the utility of the model in management, we limited the choice of model variables to those that had a clear basis in badger ecology and that could be obtained on a nation-wide digital format. We extrapolated the habitat model to a region in Denmark and developed a threshold-independent sett distribution algorithm to estimate sett densities. The habitat model was simpler than previously published models of badger sett habitat selection, but nevertheless had a predictive ability in excess of 80% judged against independent data. The sett distribution algorithm was able to simultaneously reproduce several observed patterns of sett density and distribution over the probability gradient. It thus represents a significant improvement over threshold-dependent methods used to discriminate between suitable and unsuitable habitat predicted by presence/absence regression models. Our approach demonstrates that a model of badger sett habitat suitability with high predictive power can be obtained using easily accessible map-variables and presence/absence data. This is a prerequisite for using habitat models as predictive tools over large areas. The use of a simple sett distribution algorithm circumvents the common problem of subjectively fixing a threshold to discriminate between suitable and unsuitable habitat. In conjunction the models presented here constitute an important contribution to the management of the badger in Denmark and, upon further validation, possibly to similar regions in Northern Europe.     

Habitat-Suitability Models for Cavity-Nesting Birds in a Postfire Landscape

ABSTRACT Models of habitat suitability in postfire landscapes are needed by land managers to make timely decisions regarding postfire timber harvest and other management activities. Many species of cavity-nesting birds are dependent on postfire landscapes for breeding and other aspects of their life history and are responsive to postfire management activities (e.g., timber harvest). In addition, several cavity nesters are designated as species at risk. We compare the ability of 2 types of models to distinguish between nest and non-nest locations of 6 cavity-nesting bird species (Lewis's woodpecker [Melanerpes lewis], black-backed woodpecker [Picoides arcticus], hairy woodpecker [P. villosus], northern flicker [Colaptes auratus], western bluebird [Sialia mexicana], and mountain bluebird [S. currucoides]) in the early postfire years for a ponderosa pine (Pinus ponderosa) forest in Idaho, USA. The 2 model sets consisted of 1) models based on readily available remotely sensed data and 2) models containing field-collected data in addition to remotely sensed data (combination models). We evaluated models of nesting habitat by quantifying the model's ability to correctly identify nest and non-nest locations and by determining the percentage of correctly identified nest locations. Additionally, we developed relative habitat-suitability maps for nesting habitat of black-backed and Lewis's woodpeckers from the best models. For all species except Lewis's woodpeckers, model performance improved with the addition of field-collected data. Models containing remotely sensed data adequately distinguished between nest and non-nest locations for black-backed woodpecker and Lewis's woodpecker only, whereas models containing both field-collected and remotely sensed data were adequate for all 6 species. Improvements in the availability of more accurate remote sensing technology would likely lead to improvements in the ability of the models to predict nesting locations. External validation with data from other wildfires is necessary to confirm the general applicability of our habitat-suitability models to other forests. Land managers responsible for maintaining habitat for cavity-nesting birds in postfire landscapes can use these models to identify potential nesting areas for these species and select areas in burned forests where postfire salvage logging is most likely to have minimal impacts on cavity-nesting bird habitats.     

Comparative phylogeography of a vulnerable bat and its ectoparasite reveals dispersal of a non-mobile parasite among distinct evolutionarily significant units of the host

Knowledge about phylogeographical structuring and genetic diversity is of key importance for the conservation of endangered species. Comparative phylogeography of a host and its parasite has the potential to reveal cryptic dispersal and behaviour in both species, and can thus be used to guide conservation management. In this study, we investigate the phylogeographic structure of the Bechstein’s bat, Myotis bechsteinii, and its ectoparasitic bat fly, Basilia nana, at 12 sites across their entire distribution. For both species, a mitochondrial sequence fragment (ND1 and COI respectively) and nuclear microsatellite genotypes (14 and 10 loci respectively) were generated and used to compare the phylogeography of host and parasite. Our findings confirm the presence of three distinct genetic subpopulations of the Bechstein’s bat in (1) Europe, (2) the Caucasus and (3) Iran, which remain isolated from one another. The genetic distinctiveness of host populations in the Caucasus region and Iran emphasize that these populations must be managed as distinct evolutionarily significant units. This phylogeographical pattern is however not reflected in its parasite, B. nana, which shows evidence for more recent dispersal between host subpopulations. The discordant genetic pattern between host and parasite suggest that despite the long-term genetic isolation of the different host subpopulations, long-range dispersal of the parasite has occurred more recently, either as the result of secondary contact in the primary host or via secondary host species. This indicates that a novel pathogenic threat to one host subpopulation may be able to disperse, and thus have important consequences for all subpopulations.     

Bat diversity in the lowland forests of the Heart of Borneo

Borneo’s rainforests are renowned for their high levels of biodiversity, yet information on the distribution and structure of this diversity is lacking, particularly for less charismatic taxonomic groups. We quantified bat diversity across ten sites within a contiguous tract of largely undisturbed rainforest in the Heart of Borneo (HoB) transboundary conservation area. Using comparative analyses of 1,362 bat captures from six sites in Brunei Darussalam, together with data from four additional sites in neighbouring territories, we show that the main differences in bat assemblage composition between sites were driven by the abundances of a few cave-roosting species. Beta diversity (distance decay) was notably low and non-significant. Bat assemblage structure in these undisturbed palaeotropical forests is therefore relatively homogenous in the absence of environmental gradients. By adding 15 bat species to the Brunei national inventory, we confirm the area of north Borneo to be species-diverse and therefore a priority for conservation efforts. However, we also highlight that coastal forest to be included in a recent extension to the HoB hosts bat assemblages with the fewest species and lowest densities. We maintain that extending the HoB in Brunei to include a more diverse portfolio of habitat types is still warranted on the grounds of maximising botanical diversity and habitat area, as long as it does not detract attention from interior forests that support higher vertebrate diversity.     

Habitat associations of bats in a working rangeland landscape

Land‐use change has resulted in rangeland loss and degradation globally. These changes include conversion of native grasslands for row‐crop agriculture as well as degradation of remaining rangeland due to fragmentation and changing disturbance regimes. Understanding how these and other factors influence wildlife use of rangelands is important for conservation and management of wildlife populations. We investigated bat habitat associations in a working rangeland in southeastern North Dakota. We used Petterson d500x acoustic detectors to systematically sample bat activity across the study area on a 1‐km point grid. We identified calls using Sonobat autoclassification software. We detected five species using this working rangeland, which included Lasionycteris noctivagans (2,722 detections), Lasiurus cinereus (2,055 detections), Eptesicus fuscus (749 detections), Lasiurus borealis (62 detections), and Myotis lucifugus (1 detection). We developed generalized linear mixed‐effects models for the four most frequently detected species based on their ecology. The activity of three bat species increased with higher tree cover. While the scale of selection varied between the four species, all three investigated scales were explanatory for at least one bat species. The broad importance of trees to bats in rangelands may put their conservation needs at odds with those of obligate grassland species. Focusing rangeland bat conservation on areas that were treed prior to European settlement, such as riparian forests, can provide important areas for bat conservation while minimizing negative impacts on grassland species.     

Habitat suitability models for the conservation of thermophilic grasshoppers and bush crickets—simple or complex?

One goal of conservation biology is the assessment of effects of land use change on species distribution. One approach for identifying the factors, which determine habitat suitability for a species are statistical habitat distribution models. These models are quantitative and can be used for predictions in management scenarios. However, they often have one major shortcoming, which is their complexity. This means that they need several, often costly-to-determine parameters for predictions of species occurrence. We first used habitat suitability models to investigate and determine habitat preferences of three different Orthoptera species. Second, we compared the predictive powers of simple habitat suitability models considering only the ‘habitat type’ as predictor with more complex models taking different habitat factors into account. We found that the habitat type is the most reliable and robust factor, which determines the occurrence of the species studied. Thus, analyses of habitat suitability can easily be carried out on the basis of existing vegetation maps for the conservation of the three species under study. Our results can serve as a basis for the estimation of spatio-temporal distribution and survival probabilities of the species studied and might also be valuable for other species living in dry grasslands.     

Differential Responses to Woodland Character and Landscape Context by Cryptic Bats in Urban Environments

Urbanisation is one of the most dramatic forms of land use change which relatively few species can adapt to. Determining how and why species respond differently to urban habitats is important in predicting future biodiversity loss as urban areas rapidly expand. Understanding how morphological or behavioural traits can influence species adaptability to the built environment may enable us to improve the effectiveness of conservation efforts. Although many bat species are able to exploit human resources, bat species richness generally declines with increasing urbanisation and there is considerable variation in the responses of different bat species to urbanisation. Here, we use acoustic recordings from two cryptic, and largely sympatric European bat species to assess differential responses in their use of fragmented urban woodland and the surrounding urban matrix. There was a high probability of P. pygmaeus activity relative to P. pipistrellus in woodlands with low clutter and understory cover which were surrounded by low levels of built environment. Additionally, the probability of recording P. pygmaeus relative to P. pipistrellus was considerably higher in urban woodland interior or edge habitat in contrast to urban grey or non-wooded green space. These results show differential habitat use occurring between two morphologically similar species; whilst the underlying mechanism for this partitioning is unknown it may be driven by competition avoidance over foraging resources. Their differing response to urbanisation indicates the difficulties involved when attempting to assess how adaptable a species is to urbanisation for conservation purposes.