Quantitative selection model of ecological indicators and its solving method

Abstract Ecological indicator system (EIS) is widely used in ecosystem monitoring, assessment and management, building a bridge between scientists, environmental managers, and the general public. This paper explores a conceptual model for ecological indicator selection, and a quantitative selection model is formulated based on the conceptual model. The quantitative selection model is a typical zero-one type integer programming problem, and a binary-code genetic algorithm is proposed for solving it. Then the quantitative selection model and its solving method are applied to the Xiamen's coastal ecosystem health framework which comprises 4 levels of ecosystem structure. In this case, the purpose is to reduce the indicator set to minimize overall management costs, and 19 indicators are discarded from the 54 candidate concrete indicators by our method. The selection modeling and its solving method are demonstrated to be a scientific and effective way for ecological indicator application.

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