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” (Si), “weighted stability” (S w) and “relative expansion rate” (Re). 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.
Highlights
Protected areas and biodiversity are facing important and quick degradation worldwide, especially in tropical regions due to continuous human pressures increase and climate change impacts
The observed land cover changes, landscape dynamics and global Evolutionary Trends are explained by spatial indices and specific processes [60, 61, 62] that have to be determined and identified using the "Decision Tree Algorithm" [63] that recognizes 10 theoretical geometries used in landscape ecology which is the theoretical basis of nature conservation
In the framework of PA-TAMCO Analytic Model, the validation process of the Evolutionary Trends is done through two complementary levels: (1) Individual interviews involving the technical staffs who have managed or are still managing interested protected areas during the periods covered by the assessment and (2) Semi-structured focus group interviews involving the protected areas’ oldest rangers in place since the longest time possible
Summary
Protected areas and biodiversity are facing important and quick degradation worldwide, especially in tropical regions due to continuous human pressures increase and climate change impacts. The projected climate changes and expected habitats destruction and biodiversity losses call for questioning management hypothesis, goals and plans [3,4,5] for the protected areas’ adaptive and sustainable management on the basis of periodical assessments of evolutions at global scales This kind of protected areas’ dynamic and efficient management based on prior knowledge of global evolutionary trends is still missing objective and integrated indicators for rigorous and regular assessments of the evolutionary trends and the effectiveness of the management strategies [6]. It strongly and urgently needs reliable methods, tools and indicators on the management systems, reference made to specific long-term conservation goals [7]. It makes use of the rising facilities and opportunities offered by Remote Sensing platforms and open access and free of charge global land products, given the fact that traditional field methods for biodiversity monitoring and analysis require heavy, expert and expensive inventories [25] which do not allow easy data and management plans updating because of the inadequacy and low quality of the data [26]
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