Forecasting Seasonal Habitat Connectivity in a Developing Landscape

Katherine Zeller,David Wattles,Javan Bauder,Stephen Destefano

doi:10.3390/land9070233

Katherine Zeller, David Wattles + Show 2 more

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https://doi.org/10.3390/land9070233

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Abstract

Connectivity and wildlife corridors are often key components to successful conservation and management plans. Connectivity for wildlife is typically modeled in a static environment that reflects a single snapshot in time. However, it has been shown that, when compared with dynamic connectivity models, static models can underestimate connectivity and mask important population processes. Therefore, including dynamism in connectivity models is important if the goal is to predict functional connectivity. We incorporated four levels of dynamism (individual, daily, seasonal, and interannual) into an individual-based movement model for black bears (Ursus americanus) in Massachusetts, USA. We used future development projections to model movement into the year 2050. We summarized habitat connectivity over the 32-year simulation period as the number of simulated movement paths crossing each pixel in our study area. Our results predict black bears will further colonize the expanding part of their range in the state and move beyond this range towards the greater Boston metropolitan area. This information is useful to managers for predicting and addressing human–wildlife conflict and in targeting public education campaigns on bear awareness. Including dynamism in connectivity models can produce more realistic models and, when future projections are incorporated, can ensure the identification of areas that offer long-term functional connectivity for wildlife.

Highlights

In a developing world, providing connectivity for wildlife is widely recognized as an important component of successful conservation and management plans [1,2]
Across seasons and diel periods, the area covered by pixels with the lowest resistance values (1–2) decreased by an average of 32%, while the area covered by with the lowest resistance values (1–2) decreased by an average of 32 %, while the area covered by pixels with the highest resistance values (9–10) increased by an average of 159%
Individual black We bearwere differences captured in the resistance surfaces and interannual dynamics into our Individual black bear differences were captured the used in the individual-based movement models (IBMMs) by using the spatially-weighted approach presented by Osipova et al [10].inThis resistance surfaces used in the

Summary

Introduction

In a developing world, providing connectivity for wildlife is widely recognized as an important component of successful conservation and management plans [1,2]. Connectivity, the implementation of which ranges from a single road crossing structure to large landscape corridors, is being included as a key part of many conservation plans [4], but well-connected protected areas are still relatively rare and globally fall well short of the Aichi Target 11 of the Convention on Biological Diversity [5]. More connectivity plans are encouraged—and one of the components of successful connectivity plan implementation is the inclusion of one or more focal wildlife species [4]. Wildlife responses to landscapes are inherently dynamic, as

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