Habitat Guard a Predictive Framework for Early Detection of Wildlife Habitat Degradation

Abstract

Often, wildlife habitat degradation occurs slowly, and signs of deterioration are not detected until the habitat has worsened and recovery is difficult and expensive. In this paper a predictive framework for detecting early warning signs to initiate wildlife habitat degradation in a timely manner, before it causes significant ecological harm or damage. It is a three-part framework that includes both continuous monitoring of habitat quality and species-response indicators, as well as compiling these indicators into an early-warning risk profile and converting that profile into specific management alerts for areas at risk. Habitat Guard's unique ability to use recent advancements in artificial-intelligence-aided biodiversity conservation, real-time wildlife monitoring, and habitat quality and ecological risk assessment, as well as spatial wildfire risk analysis for habitat corridors, provides a tool to assist conservation managers in detecting trends of habitat degradation where intervention is still possible. Although the framework has not yet been field-tested, the indicator-based, risk-based design provides a logical progression to better identifying and mitigating habitat degradation. Empirical testing of a variety of habitat types with varying disturbance pressures and species composition is suggested as a future research project.