Modeling protected species habitat and assigning risk to inform regulatory decisions.

In the United States, environmental regulatory agencies are required to use "best available" scientific information when making decisions on a variety of issues. However, agencies are often hindered by coarse or incomplete data, particularly as it pertains to threatened and endangered species protection. Stakeholders often agree that more resolute and integrated processes for decision-making are desirable. We demonstrate a process that uses species occurrence data for a federally endangered insect (Karner blue butterfly), a readily available habitat modeling tool, and spatially explicit information about an important Michigan commodity (tart cherries). This case study has characteristics of many protected species regulatory decisions in that species occurrence data were sparse and unequally distributed; regulatory decisions (on pesticide use) were required with potentially significant impacts on a viable agricultural industry; and stakeholder relations were diverse, misinformed, and, in some situations, unjustly contentious. Results from our process include a large-scale, empirically derived habitat suitability map for the focal species and a risk ranking of tart cherry orchards with risk based on the likelihood that pesticide applications will influence the focal protected species. Although the majority (77%) of pesticide-influence zones overlapped Karner blue butterfly habitat, risk scores associated with each orchard were low. Through our process we demonstrated that spatially explicit models can help stakeholders visualize and quantify potential protected species effects. In addition, model outputs can serve to guide field activities (e.g., species surveys and implementation of pesticide buffer zones) that help minimize future effects.