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首页> 外文期刊>The Journal of Ecology >Incorporating dominant species as proxies for biotic interactions strengthens plant community models.
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Incorporating dominant species as proxies for biotic interactions strengthens plant community models.

机译:将优势物种纳入生物相互作用的代理可以增强植物群落模型。

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Biotic interactions exert considerable influence on the distribution of individual species and should, thus, strongly impact communities. Implementing biotic interactions in spatial models of community assembly is therefore essential for accurately modelling assemblage properties. However, this remains a challenge due to the difficulty of detecting the role of species interactions and because accurate paired community and environment data sets are required to disentangle biotic influences from abiotic effects. Here, we incorporate data from three dominant species into community-level models as a proxy for the frequency and intensity of their interactions with other species and predict emergent assemblage properties for the co-occurring subdominant species. By analysing plant community and field-quantified environmental data from specially designed and spatially replicated monitoring grids, we provide a robust in vivo test of community models. Considering this well-defined and easily quantified surrogate for biotic interactions consistently improved realism in all aspects of community models (community composition, species richness and functional structure), irrespective of modelling methodology. Dominant species reduced community richness locally and favoured species with similar leaf dry matter content. This effect was most pronounced under conditions of high plant biomass and cover, where stronger competitive impacts are expected. Analysis of leaf dry matter content suggests that this effect may occur through efficient resource sequestration. Synthesis. We demonstrate the strong role of dominant species in shaping multiple plant community attributes, and thus the need to explicitly include interspecific interactions to achieve robust predictions of assemblage properties. Incorporating information on biotic interactions strengthens our capacity not only to predict the richness and composition of communities, but also how their structure and function will be modified in the face of global change
机译:生物相互作用对单个物种的分布产生相当大的影响,因此应该强烈影响社区。因此,在社区组装的空间模型中实现生物相互作用对于准确地建模组装属性至关重要。然而,由于难以检测物种相互作用的作用,并且因为需要准确配对的社区和环境数据集来将生物影响与非生物影响区分开来,因此这仍然是一个挑战。在这里,我们将来自三个优势物种的数据整合到社区级模型中,以作为它们与其他物种相互作用的频率和强度的代理,并预测共同存在的主要物种的新兴组合特性。通过分析专门设计并在空间上复制的监视网格中的植物群落和现场量化的环境数据,我们为群落模型提供了可靠的体内测试。考虑到这种对生物相互作用的定义明确且易于量化的替代方法,无论建模方法如何,在社区模型的各个方面(社区组成,物种丰富度和功能结构)始终如一地改善了真实性。优势物种减少了当地的群落丰富度,而青睐具有相似叶干物质含量的物种。在高植物生物量和高覆盖率的条件下,这种影响最为明显,预计会产生更大的竞争影响。对叶片干物质含量的分析表明,这种影响可能通过有效的资源隔离而发生。合成。我们证明了优势物种在塑造多个植物群落属性中的强大作用,因此需要明确包括种间相互作用以实现对组合特性的可靠预测。纳入有关生物相互作用的信息不仅增强了我们预测社区的丰富程度和组成的能力,而且还增强了我们面对全球变化如何改变其结构和功能的能力

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