Iwamura Takuya, Fuller Richard A, Possingham Hugh P
Department of Biology and Department of Environmental Earth System Science, 473 Via Ortega, Stanford University, Stanford, CA 94305, U.S.A.; Australian Research Council Centre of Excellence for Environmental Decisions, School of Biological Sciences, The University of Queensland, St. Lucia, Queensland, 4072, Australia.
Conserv Biol. 2014 Dec;28(6):1710-20. doi: 10.1111/cobi.12319. Epub 2014 Jun 27.
Every year, millions of migratory shorebirds fly through the East Asian-Australasian Flyway between their arctic breeding grounds and Australasia. This flyway includes numerous coastal wetlands in Asia and the Pacific that are used as stopover sites where birds rest and feed. Loss of a few important stopover sites through sea-level rise (SLR) could cause sudden population declines. We formulated and solved mathematically the problem of how to identify the most important stopover sites to minimize losses of bird populations across flyways by conserving land that facilitates upshore shifts of tidal flats in response to SLR. To guide conservation investment that minimizes losses of migratory bird populations during migration, we developed a spatially explicit flyway model coupled with a maximum flow algorithm. Migratory routes of 10 shorebird taxa were modeled in a graph theoretic framework by representing clusters of important wetlands as nodes and the number of birds flying between 2 nodes as edges. We also evaluated several resource allocation algorithms that required only partial information on flyway connectivity (node strategy, based on the impacts of SLR at nodes; habitat strategy, based on habitat change at sites; population strategy, based on population change at sites; and random investment). The resource allocation algorithms based on flyway information performed on average 15% better than simpler allocations based on patterns of habitat loss or local bird counts. The Yellow Sea region stood out as the most important priority for effective conservation of migratory shorebirds, but investment in this area alone will not ensure the persistence of species across the flyway. The spatial distribution of conservation investments differed enormously according to the severity of SLR and whether information about flyway connectivity was used to guide the prioritizations. With the rapid ongoing loss of coastal wetlands globally, our method provides insight into efficient conservation planning for migratory species.
每年,数以百万计的迁徙滨鸟在其北极繁殖地和澳大拉西亚之间飞越东亚-澳大拉西亚迁徙路线。这条迁徙路线包括亚洲和太平洋地区众多的沿海湿地,这些湿地被用作鸟类休息和觅食的中途停留地。海平面上升导致一些重要中途停留地的丧失可能会使鸟类数量突然减少。我们通过数学方法制定并解决了一个问题,即如何确定最重要的中途停留地,通过保护能够促进潮间带向岸迁移以应对海平面上升的土地,从而最大限度地减少整个迁徙路线上鸟类数量的损失。为了指导能将迁徙鸟类数量损失降至最低的保护投资,我们开发了一个空间明确的迁徙路线模型,并结合了最大流算法。在一个图论框架中对10种滨鸟分类群的迁徙路线进行了建模,将重要湿地集群表示为节点,将两个节点之间飞行的鸟类数量表示为边。我们还评估了几种资源分配算法,这些算法只需要关于迁徙路线连通性的部分信息(节点策略,基于海平面上升对节点的影响;栖息地策略,基于地点的栖息地变化;种群策略,基于地点的种群变化;以及随机投资)。基于迁徙路线信息的资源分配算法平均比基于栖息地丧失模式或当地鸟类数量的简单分配方法表现好15%。黄海地区是有效保护迁徙滨鸟的最重要优先区域,但仅在该地区投资并不能确保整个迁徙路线上物种的存续。根据海平面上升的严重程度以及是否使用迁徙路线连通性信息来指导优先排序,保护投资的空间分布差异巨大。随着全球沿海湿地的持续快速丧失,我们的方法为迁徙物种的高效保护规划提供了见解。