Beta Diversity Patterns Derived from Island Biogeography Theory
Beta Diversity Patterns Derived from Island Biogeography Theory
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DOI：
10.1086/704181
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发表时间：
2019-09-01
影响因子：
2.9
通讯作者：
Jetz, Walter
中科院分区：
文献类型：
--
作者：
Lu, Muyang;Vasseur, David;Jetz, Walter
岛屿地理学的元生态理论及其组成理论具有统一不同尺度生态学的潜力。TIB已成功地预测α多样性模式，如物种-面积关系和物种-丰度分布，但在预测空间β多样性模式落后。在这项研究中，我们使用岛屿地理学理论作为出发点，整合空间β多样性模式到元共生理论。我们首先推导出理论预测的预期β多样性模式下的经典麦克阿瑟和威尔逊的框架，所有物种都有相同的殖民化和灭绝率。然后，我们测试这些预测的42个岛屿（和93种）在岛湖，中国的鸟类群落组成。我们的理论结果证实，更长的距离和更小的面积导致更高的β多样性，并进一步揭示，成对β多样性是独立的大陆物种库的大小。我们还发现，对于分区的成对β多样性组件，营业额组件的灭绝率和定殖率的比例增加，而嵌套组件是一个单峰函数的灭绝率和定殖率的比例。对于经验岛系统，我们发现β多样性模式更好地区分物种等价模型从物种不等价模型比α多样性模式。我们的研究结果表明，β多样性模式提供了一个强大的工具，在检测非中性的过程中，我们的模型有可能将更多的生物现实主义在未来的分析。
Metacommunity theory and its constituent theory of island biogeography (TIB) have the potential to unify ecology across different scales. The TIB has been successful in predicting alpha diversity patterns, such as species-area relationships and species-abundance distributions, but lags behind in predicting spatial beta diversity patterns. In this study we use island biogeography theory as the starting point to integrate spatial beta diversity patterns into metacommunity theory. We first derive theoretical predictions for the expected beta diversity patterns under the classic MacArthur and Wilson framework, where all species have equal colonization and extinction rates. We then test these predictions for the avian community composition of 42 islands (and 93 species) in Thousand Island Lake, China. Our theoretical results corroborate that longer distance and smaller area lead to higher beta diversity and further reveal that pairwise beta diversity is independent of the size of the mainland species pool. We also find that for the partitioned pairwise beta diversity components, the turnover component increases with the ratio of extinction rates and colonization rates, while the nestedness component is a unimodal function of the ratio of extinction rates and colonization rates. For the empirical island system, we find that beta diversity patterns better distinguish a species-equivalent model from a species-nonequivalent model than alpha diversity patterns. Our findings suggest that beta diversity patterns provide a powerful tool in detecting nonneutral processes, and our model has the potential to incorporate more biological realism in future analyses.