COS 60-2
Predicting local scale climate change impacts on endangered birds by integrating watershed models and expert knowledge-based models for decision-support
Climate change is expected to have significant impacts on native, threatened and endangered bird species, particularly in terms of habitat alteration. Understanding and modeling these impacts in a manner that is useful for decision-makers or management, however, remains difficult since many empirical modeling frameworks require large amounts of long-term data that can be costly to collect. To address this, we propose an innovative decision support approach to understanding climate change impacts on the habitat, life history functions, and abundance of endangered bird species by coupling regional watershed simulation models (e.g. AnnAGNPS) under IPCC defined scenarios and an expert knowledge-based model of bird ecology using an knowledge based modeling Fuzzy-Logic Cognitive Mapping (FCM) software. To test our approach, we use data from the Hawaiian Stilt, Hawaiian Coot and Hawaiian Moorhen populations and watershed data from the island of Kauai as a case study. The type of decision framework we propose provides wildlife managers a low cost approximate understanding of the dynamic interaction between climate change, habitat and wildlife ecology based on pooling available expert knowledge and existing data about watershed projections.
Results/Conclusions
Model results based on IPCC scenarios suggest that increased precipitation will increase Stilt abundance, but decrease Coot and Moorhen abundance. On the other hand, decreasing precipitation may have similar effects across all three species. Combining empirical and expert-based models allows managers to understand the local ecological impacts associated with global climate change, making it more relevant to the management scale. Additionally we suggest this framework can be easily employed by a range of wildlife managers to understand the impacts of climate change across different types of taxa and across different ecological conditions.