Data-integration of opportunistic species observations into hierarchical modeling frameworks improves spatial predictions for urban red squirrels

The prevailing trend of increasing urbanization and habitat fragmentation makes knowledge of species’ habitat requirements and distribution a crucial factor in conservation and urban planning. Species distribution models (SDMs) offer powerful toolboxes for discriminating the underlying environmental factors driving habitat suitability. Nevertheless, challenges in SDMs emerge if multiple data sets - often sampled with different intention and therefore sampling scheme – can complement each other and increase predictive accuracy. Here, we investigate the potential of using recent data integration techniques to model potential habitat and movement corridors for Eurasian red squirrels (Sciurus vulgaris), in an urban area. We constructed hierarchical models integrating data sets of different quality stemming from unstructured on one side and semi-structured wildlife observation campaigns on the other side in a combined likelihood approach and compared the results to modeling techniques based on only one data source - wherein all models were fit with the same selection of environmental variables. Our study highlights the increasing importance of considering multiple data sets for SDMs to enhance their predictive performance. We finally used Circuitscape (version 4.0.5) on the most robust SDM to delineate suitable movement corridors for red squirrels as a basis for planning road mortality mitigation measures. Our results indicate that even though red squirrels are common, urban habitats are rather small and partially lack connectivity along natural connectivity corridors in Berlin. Thus, additional fragmentation could bring the species closer to its limit to persist in urban environments, where our results can act as a template for conservation and management implications.

Forecasting shifts in habitat suitability of three marine predators suggests a rapid decline in inter‐specific overlap under future climate change

Understanding how environmental and climate change can alter habitat overlap of marine predators has great value for the management and conservation of marine ecosystems. Here, we estimated spatiotemporal changes in habitat suitability and inter‐specific overlap among three marine predators: Baltic gray seals (Halichoerus grypus), harbor seals (Phoca vitulina), and harbor porpoises (Phocoena phocoena) under contemporary and future conditions. Location data (>200 tagged individuals) were collected in the southwestern region of the Baltic Sea; one of the fastest‐warming semi‐enclosed seas in the world. We used the maximum entropy (MaxEnt) algorithm to estimate changes in total area size and overlap of species‐specific habitat suitability between 1997–2020 and 2091–2100. Predictor variables included environmental and climate‐sensitive oceanographic conditions in the area. Sea‐level rise, sea surface temperature, and salinity data were taken from representative concentration pathways [RCPs] scenarios 6.0 and 8.5 to forecast potential climate change effects. Model output suggested that habitat suitability of Baltic gray seals will decline over space and time, driven by changes in sea surface salinity and a loss of currently available haulout sites following sea‐level rise in the future. A similar, although weaker, effect was observed for harbor seals, while suitability of habitat for harbor porpoises was predicted to increase slightly over space and time. Inter‐specific overlap in highly suitable habitats was also predicted to increase slightly under RCP scenario 6.0 when compared to contemporary conditions, but to disappear under RCP scenario 8.5. Our study suggests that marine predators in the southwestern Baltic Sea may respond differently to future climatic conditions, leading to divergent shifts in habitat suitability that are likely to decrease inter‐specific overlap over time and space. We conclude that climate change can lead to a marked redistribution of area use by marine predators in the region, which may influence local food‐web dynamics and ecosystem functioning.