Single‐species dynamic site selection
Single‐species dynamic site selection
复制标题
单物种动态选址
DOI：
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
M. Cabeza
中科院分区：
文献类型：
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作者：
A. Moilanen;M. Cabeza
区域保护区网络的设计方法主要集中在提供该区域物种的最大代表性。然而，基于表示的方法通常考虑物种发生率的静态快照，并且忽略了物种的空间动态。经验表明，使用代表性设计的储备并不能保证储备设计的另一个重要目标：长期持续性。这里研究的问题是：考虑到每个地点都有成本和资源量，你选择哪个地点子集来最大限度地提高生活在集合种群中的物种的长期持久性（例如，钱）是有限的？我们提出了一种优化方法，它使用进化优化（遗传算法）和局部搜索的组合，找到最佳的网站选择。每个候选解决方案的质量进行评估，使用一个空间上现实的集合种群模型，发病率函数模型。该方法适用于集合种群的假石南贝母蝴蝶，在芬兰的濒危物种。利用该数据集，所提出的估计方法在几分钟的计算时间内产生直观可接受且一致的结果。该算法青睐的网站位于三个补丁集群，他们往往是廉价的，最初被占用。昂贵和/或非常孤立的补丁很少被选入最佳网站选择。
Methods for designing regional reserve networks mostly concentrate on pro- viding maximal representation of species occurring in the region. Representation-based methods, however, typically consider a static snapshot of species incidences, and the spatial dynamics of the species are ignored. It has been empirically demonstrated that reserves designed using representation do not guarantee another important goal of reserve design: long-term persistence. The question studied here is the following: Which subset of sites do you select to maximize the long-term persistence of a species living in a metapopulation, given that each site has a cost and the amount of resource (e.g., money) available is limited? We present an optimization method, which uses a combination of evolutionary optimization (a genetic algorithm) and local search to find the optimal selection of sites. The quality of each candidate solution is evaluated using a spatially realistic metapopulation model, the incidence function model. The proposed method is applied to a metapopulation of the false heath fritillary butterfly, an endangered species in Finland. With this data set, the proposed estimation method produces intuitively acceptable and consistent results within minutes of computation time. Sites favored by the algorithm are located in three patch clusters, and they tend to be inexpensive and initially occupied. Expensive and/or very isolated patches are rarely selected into the optimal site selection.