Summary1. To manage anthropogenic environmental change for the benefit of biodiversity, we must improve our understanding of the complex relationships between organisms and their environment. We have developed multiscale habitat suitability models (HSMs) for bats, a mobile group of mammals, for a geographically varied region of the UK. We ask whether the models have sufficient accuracy to contribute to informed decision-making in habitat management and in minimizing the impact of climate change and human infrastructural development. 2. We used acoustic surveys supplemented by catching to gather presence data for eight species from 30 sites across the south of the Lake District National Park in NW England. Species were identified by manual and automated extraction and analysis of echolocation calls. Fine-resolution (50 and 100 m) habitat maps were generated at twelve spatial scales by calculating the variables across squares of increasing size, from 100 to 6000 m, around each focal 50 or 100 m square. Presence-only HSM software, MaxEnt, was used to determine the predictive power of each habitat variable at each scale. Multiscale models included data for each variable at the scale at which it had the strongest relationship with the presence of each species. 3. The best multiscale models were selected using fivefold cross-validation, with backwards, stepwise variable removal, whilst minimizing residual spatial autocorrelation and sampling bias. Further tests with independent field data indicated good model transferability across the entire National Park. 4. Foraging bats were generally most strongly associated with variables measured at small spatial scales and distance measures. However, each species responded differently across the range of scales, and strong associations were also found at the largest scale of analysis (6000 m). 5. Synthesis and applications. The best models for determining habitat suitability had few variables, making them easy to interpret and use in practical conservation planning. The approach is applicable to any taxa for which reliable presence records are available, providing insight into the potential impacts of land-use and environmental change. Maps identify areas of conservation concern, such as hot spots for diversity, rare or vulnerable species and potential or threatened network corridors, making them useful for ecological impact assessment of proposed developments, and to conservation managers planning habitat creation or improvement.

Natural experiments have been proposed as a way of complementing manipulative experiments to improve ecological understanding and guide management. There is a pressing need for evidence from such studies to inform a shift to landscape‐scale conservation, including the design of ecological networks. Although this shift has been widely embraced by conservation communities worldwide, the empirical evidence is limited and equivocal, and may be limiting effective conservation. We present principles for well‐designed natural experiments to inform landscape‐scale conservation and outline how they are being applied in the WrEN project, which is studying the effects of 160 years of woodland creation on biodiversity in UK landscapes. We describe the study areas and outline the systematic process used to select suitable historical woodland creation sites based on key site‐ and landscape‐scale variables – including size, age, and proximity to other woodland. We present the results of an analysis to explore variation in these variables across sites to test their suitability as a basis for a natural experiment. Our results confirm that this landscape satisfies the principles we have identified and provides an ideal study system for a long‐term, large‐scale natural experiment to explore how woodland biodiversity is affected by different site and landscape attributes. The WrEN sites are now being surveyed for a wide selection of species that are likely to respond differently to site‐ and landscape‐scale attributes and at different spatial and temporal scales. The results from WrEN will help develop detailed recommendations to guide landscape‐scale conservation, including the design of ecological networks. We also believe that the approach presented demonstrates the wider utility of well‐designed natural experiments to improve our understanding of ecological systems and inform policy and practice.

Wood, Claire M.; Schmucki, Reto; Bullock, James M.; Eigenbrod, Felix. 2019. An analytical framework for spatially targeted management of natural capital. Nature Sustainability, 2 (2). 90-97.

Least-cost models are widely used to study the functional connectivity of habitat within a varied landscape matrix. A critical step in the process is identifying resistance values for each land cover based upon the facilitating or impeding impact on species movement. Ideally resistance values would be parameterised with empirical data, but due to a shortage of such information, expert-opinion is often used. However, the use of expert-opinion is seen as subjective, human-centric and unreliable. This study derived resistance values from grey squirrel habitat suitability models (HSM) in order to compare the utility and validity of this approach with more traditional, expert-led methods. Models were built and tested with MaxEnt, using squirrel presence records and a categorical land cover map for Cumbria, UK. Predictions on the likelihood of squirrel occurrence within each land cover type were inverted, providing resistance values which were used to parameterise a least-cost model. The resulting habitat networks were measured and compared to those derived from a least-cost model built with previously collated information from experts. The expert-derived and HSM-inferred least-cost networks differ in precision. The HSM-informed networks were smaller and more fragmented because of the higher resistance values attributed to most habitats. These results are discussed in relation to the applicability of both approaches for conservation and management objectives, providing guidance to researchers and practitioners attempting to apply and interpret a least-cost approach to mapping ecological networks.

Road vehicle collisions are likely to be an important contributory factor in the decline of the European hedgehog (Erinaceus europaeus) in Britain. Here, a collaborative roadkill dataset collected from multiple projects across Britain was used to assess when, where and why hedgehog roadkill are more likely to occur. Seasonal trends were assessed using a Generalized Additive Model. There were few casualties in winter—the hibernation season for hedgehogs—with a gradual increase from February that reached a peak in July before declining thereafter. A sequential multi-level Habitat Suitability Modelling (HSM) framework was then used to identify areas showing a high probability of hedgehog roadkill occurrence throughout the entire British road network (∼400,000 km) based on multi-scale environmental determinants. The HSM predicted that grassland and urban habitat coverage were important in predicting the probability of roadkill at a national scale. Probabilities peaked at approximately 50% urban cover at a one km scale and increased linearly with grassland cover (improved and rough grassland). Areas predicted to experience high probabilities of hedgehog roadkill occurrence were therefore in urban and suburban environments, that is, where a mix of urban and grassland habitats occur. These areas covered 9% of the total British road network. In combination with information on the frequency with which particular locations have hedgehog road casualties, the framework can help to identify priority areas for mitigation measures.