Monitoring Ecological Impacts provides the tools needed by professional ecologists, scientists, engineers, planners and managers to design assessment programs that can reliably monitor, detect and allow management of human impacts on the natural environment. The procedures described are well grounded in inferential logic, and the statistical models needed to analyse complex data are given. Step-by-step guidelines and flow diagrams provide the reader with clear and useable protocols, which can be applied in any region of the world and to a wide range of human impacts. In addition, real examples are used to show how the theory can be put into practice. Although the context of this book is flowing water environments, especially rivers and streams, the advice for designing assessment programs can be applied to any ecosystem.

Species extinctions and the deterioration of other biodiversity features worldwide have led to the adoption of systematic conservation planning in many regions of the world. As a consequence, various software tools for conservation planning have been developed over the past twenty years. These tools implement algorithms designed to identify conservation area networks for the representation and persistence of biodiversity features. Budgetary, ethical, and other sociopolitical constraints dictate that the prioritized sites represent biodiversity with minimum impact on human interests. Planning tools are typically also used to satisfy these criteria. This chapter reviews both the concepts and technical choices that underlie the development of these tools. Conservation planning problems can be formulated as optimization problems, and we evaluate the suitability of different algorithms for their solution. Finally, we also review some key issues associated with the use of these tools, such as computational efficiency, the effectiveness of taxa and abiotic parameters at choosing surrogates for biodiversity, the process of setting explicit targets of representation for biodiversity surrogates, and dealing with multiple criteria. The review concludes by identifying areas for future research, including the scheduling of conservation action over extensive time periods and incorporating data about site vulnerability.

This paper explores alternative techniques for the selection of conservation contracts under competitive tendering programs. Under these programs, purchasing decisions are often based on the benefits score and cost for proposed projects. The optimisation problem is to maximise the aggregate benefits without exceeding the budget. Because the budget rarely permits all projects to be funded, there is a binary choice problem, known in the operations research published work as a knapsack problem. The decision-maker must choose which projects are funded and which are not. Under some circumstances, the knapsack problem can be unsolvable because computational complexity increases exponentially with the number of projects. This paper explores the use of several decision rules for solving the optimisation problem including the use of advanced meta-heuristics. It is shown that commonly applied techniques for project selection may not be providing the optimal solution. Improved algorithms can increase the environmental programs benefits and staying within budget. The comparison of algorithms is based on real data from the Western Australian Conservation Auction.