Balancing human energy needs and conservation of panda habitat

Resource extractive activities to meet the basic needs of humans have been the leading causes of habitat degradation and thus biodiversity loss. Complex human-nature interactions make it difficult to understand the impacts of human activities on wildlife habitat and to develop effective solutions for balancing human needs and wildlife conservation. Integrated with modern computer technology and systems modeling and simulation, decision support systems (DSSs) can ease this challenge. Such systems can provide a platform for a variety of stakeholders such as conservation scientists, policy analysts, and decision makers, to quantitatively and visually construct, analyze, and evaluate different solution options.To demonstrate the functionality of such systems, a WebGIS-based DSS named WOW (Wolong Online WebGIS) has been developed. It was applied to Wolong Nature Reserve for giant pandas (Ailuropoda melanoleuca) in southwestern China. The WOW enables various geographically dispersed stakeholders to simulate long-term spatial and temporal dynamics of human population, human energy needs (fuelwood), human activities (fuelwood collection and consumption), and thus the impacts of these activities on panda habitat. This system incorporated the results from an analysis of the spatial and temporal trends of fuelwood collection in the past three decades in the 20th century. It also considers the effects of two conservation policies (Natural Forest Conservation Program [NFCP] and Grain to Green Program [GTGP] implemented since 2000) on fuelwood consumption of rural households in the reserve.As fuelwood is a key issue of natural resource conflict between people and pandas, one model was incorporated into the system to demonstrate the feasibility of thinning plantation forests for fuelwood. It showed that forest plantations in the reserve could sustainably provide rural households with enough fuelwood, if deliberate forest thinning plans and conservation policy regulation were applied. Furthermore, a multi-criteria decision making component was developed for stakeholders to synthesize and compare scenarios or solution options. Since the system was made public, 36 of 76 registered users evaluated four predefined scenarios. The preferred scenario is to thin plantation forests for fuelwood. Thus, we encourage reserve managers to consider this idea and incorporate it with the on-going conservation programs such as the NFCP and GTGP as soon as possible. This dissertation made a novel effort to integrate traditional DSS technology and systems modeling with spatial analyses functionality, a key component of the issue under investigation in a web-based interactive system, which helps stakeholders search for options balancing household energy needs and panda conservation. Besides the practical implications of the results directly for balancing human (energy) needs and panda conservation in the reserve studied, this dissertation has broad methodological applications in developing Web-based decision analysis tools, assisting decision making processes, and integrating multiple sources of data and multiple-disciplines for many of other 2,531 natural reserves in China and many other coupled human-nature systems worldwide.