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Biotic interactions are an unexpected yet critical control on the complexity of an abiotically driven polar ecosystem

机译:生物互动是对生物驱动极性生态系统的复杂性的意外还是关键的控制

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Abiotic and biotic factors control ecosystem biodiversity, but their relative contributions remain unclear. The ultraoligotrophic ecosystem of the Antarctic Dry Valleys, a simple yet highly heterogeneous ecosystem, is a natural laboratory well-suited for resolving the abiotic and biotic controls of community structure. We undertook a multidisciplinary investigation to capture ecologically relevant biotic and abiotic attributes of more than 500 sites in the Dry Valleys, encompassing observed landscape heterogeneities across more than 200 km2. Using richness of autotrophic and heterotrophic taxa as a proxy for functional complexity, we linked measured variables in a parsimonious yet comprehensive structural equation model that explained significant variations in biological complexity and identified landscape-scale and fine-scale abiotic factors as the primary drivers of diversity. However, the inclusion of linkages among functional groups was essential for constructing the best-fitting model. Our findings support the notion that biotic interactions make crucial contributions even in an extremely simple ecosystem. Charles Lee, Daniel Laughlin et al. use structural equation modeling to analyze ecological data from more than 500 sites in the Antarctic Dry Valleys. They find that although abiotic factors are the primary drivers of biodiversity variation, biotic interactions are needed to explain the data fully and may play previously underestimated roles.
机译:非生物和生物因素控制生态系统生物多样性,但它们的相对贡献仍然不明确。南极干燥谷的超微营养植物生态系统,一种简单而高度异质的生态系统,是一种自然的实验室,适合解决群落结构的非生物和生物控制。我们对多学科调查进行了多学科调查,以捕获干燥谷的生态相关的生物和非生物属性,在干燥的山谷中,包括观察到超过200公里的景观异质性。使用富含自养和异养的分类群作为功能复杂性的代理,我们将测量的变量联系起来,在一个解释的又综合结构方程模型中,解释了生物复杂性的显着变化,并确定了景观规模和细微的非生物因素作为多样性的主要驱动因素。然而,包含官能团之间的联系对于构建最佳拟合模型是必不可少的。我们的调查结果支持了生物互动即使在一个极其简单的生态系统中也使关键贡献。 Charles Lee,Daniel Laughlin等。使用结构方程模型从南极干燥谷的500多个站点分析生态数据。他们发现,尽管非生物因素是生物多样性变化的主要驱动因素,但需要充分解释数据并可能发挥以前低估的角色。

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