Conceptual and Analytic Model for Advanced Evaluation of Protected Areas’ Global Evolutionary Trends: The Protected Areas' Trends Assessment and Adaptive Management on the Basis of Long-Term Conservation Objectives or PA-TAMCO Analytic Model

Abstract

Protected areas and biodiversity are currently facing important degradation, especially in tropical regions. This evolution questions the management systems and calls for adaptive and sustainable management on the basis of regular assessments of global evolutionary trends and continuous adjustments of conservation objectives and management tools. Adaptive management is yet missing rigorous and integrated indicators for advanced evaluations for many protected areas which have never been assessed despite periodical updating of management goals and plans. The development of reliable, global and low cost methods for adaptive management is therefore a great concern for scientific and conservationist communities given the limitations of commonly used tools and recurrent problems of conservation funding. The PA-TAMCO Analytic Model was designed to promote adaptive actions and management considering spatialized, categorized and aggregated changes from advanced global evaluations. It is an innovative approach and tool for protected areas’ global evolutionary trends with reference to conservation objectives. Theoretically, the Model is based on land cover concepts and land cover analysis recognized as the most practical approach to assess ecosystem units, with reference to vegetation cover, natural processes and theoretical spatial changes. Basically, it relies on four key indicators and tools: (1) Trend Index, (2) Evolutionary Trend, (3) Evolutionary Trend’s Decision Tree Algorithm and (4) Trend Index and Evolutionary Trend’s Classification Grid. Technically, it is based on Remote Sensing data processing; land cover mapping and land cover change analysis using appropriated Remote Sensing and GIS Softwares. The spatial indices and processes responsible for recorded evolutionary trends are determined using landscape ecology tools. In the field of conservation, positive processes are respectively positive and negative when they affect vegetation classes and anthropogenic classes and vice-versa, for negative ones. The input data for the computation of evolution indicators and spatial processes are derived from raw export results of the classifications of Remote Sensing data to GIS software. The sensitivity and resilience of specific ecosystems units to external stresses are measured by three indicators that are “intrinsic stability” (S_i), “weighted stability” (S _w) and “relative expansion rate” (R_e). These indicators are essential for rational management of strategic ecosystems like savannah, water bodies and wetlands in animal sanctuaries and wildlife parks. The implementation of the Model starts with the knowledge of management category, conservation objectives and desired evolutions. The validation process relies on semi-structured interviews involving technical staff and oldest rangers. The model was successfully applied to the Rusizi National Park (Burundi) from 1984 and 2015.