The emergent interactions that govern biodiversity change
The emergent interactions that govern biodiversity change
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DOI：
10.1073/pnas.2003852117
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发表时间：
2020-07-21
影响因子：
11.1
通讯作者：
Swift, Margaret
中科院分区：
文献类型：
--
作者：
Clark, James S.;Scher, C. Lane;Swift, Margaret
观测研究尚未表明环境变量可以解释物种丰度的普遍非线性模式，因为这些模式可能是由与其他物种的（间接）相互作用造成的（例如，竞争），模型仅估计直接响应。在区域到大陆的范围内提取这些间接影响的实验是不可行的。在这里，生物物理的方法量化的环境物种的相互作用（ESI），管理社区的变化，从现场数据。正如物种之间的相互作用取决于种群的丰度，环境的影响也是如此，比如干旱会因竞争而加剧。通过将动态ESI嵌入到允许在不同尺度上收集数据的框架中，我们量化了通过其他物种间接引起的响应，包括参数，模型规格和数据的概率不确定性。模拟结果表明，ESI需要准确的解释。分析表明，即使它们对环境的直接响应是线性的，非线性响应也会出现。应用到实验湖泊和繁殖鸟类调查（BBS）产生相反的估计ESI。在封闭的湖泊中，浮游植物和浮游动物之间的相互作用起着重要的作用。相比之下，ESI在BBS中较弱，正如预期的那样，逐年的移动降低了当地人口增长和物种相互作用之间的联系。在这两种情况下，对环境梯度的非线性响应是由物种之间的相互作用引起的。稳定性分析表明，在封闭系统的湖泊稳定和BBS的不稳定。概率框架直接应用于保护规划，必须权衡整个栖息地和社区的风险评估对竞争的利益。
Observational studies have not yet shown that environmental variables can explain pervasive nonlinear patterns of species abundance, because those patterns could result from (indirect) interactions with other species (e.g., competition), and models only estimate direct responses. The experiments that could extract these indirect effects at regional to continental scales are not feasible. Here, a biophysical approach quantifies environment-species interactions (ESI) that govern community change from field data. Just as species interactions depend on population abundances, so too do the effects of environment, as when drought is amplified by competition. By embedding dynamic ESI within framework that admits data gathered on different scales, we quantify responses that are induced indirectly through other species, including probabilistic uncertainty in parameters, model specification, and data. Simulation demonstrates that ESI are needed for accurate interpretation. Analysis demonstrates how nonlinear responses arise even when their direct responses to environment are linear. Applications to experimental lakes and the Breeding Bird Survey (BBS) yield contrasting estimates of ESI. In closed lakes, interactions involving phytoplankton and their zooplankton grazers play a large role. By contrast, ESI are weak in BBS, as expected where year-to-year movement degrades the link between local population growth and species interactions. In both cases, nonlinear responses to environmental gradients are induced by interactions between species. Stability analysis indi-cates stability in the closed-system lakes and instability in BBS. The probabilistic framework has direct application to conservation planning that must weigh risk assessments for entire habitats and communities against competing interests.