Computational Framework for Illegal Wildlife Trade Reduction: An Integrated Decision Support System

The illegal wildlife trade is among the major threats to the global environment, with at least $26.5 billion lost annually and extreme impacts on biodiversity and ecological sustainability. In response, Sustainable Development Alternative Project (SDAP) will be implemented to serve as an integrated conservation approach. It targets the reduction of fully reported incidents of wildlife trafficking by at least 50% within five years. We have developed Client Suitability System (CSS) that is hybrid, for we combined two models Analytic Hierarchy Process (AHP) and the enhanced Criteria Importance Through Intercriteria Correlation (CRITIC) methods in selecting the best implementer. The highest-ranking institution that emerged was Brazil's Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA). The most effective intervention in reducing the level of illegal wildlife trade is educational intervention on the Crime Index. Predictive analysis based on the Gray Model (GM(1,1)) estimates a reduction of 60% in wildlife trafficking incidents: this over and above what was originally planned with an 83.57% probability of attaining success. Sensitivity analysis has proven, which shines the light very strongly on legal enforcement, in an area where more surveillance is needed. Our integrated computational framework leads to pragmatic recommendations on the optimization of interventions for conserving wildlife.