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Predictability of helminth parasite host range using information on geography, host traits and parasite community structure

机译：使用关于地理，宿主性状和寄生虫群落结构的信息的蠕虫寄生虫宿主范围的可预测性

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摘要

Host-parasite associations are complex interactions dependent on aspects of hosts (e.g. traits, phylogeny or coevolutionary history), parasites (e.g. traits and parasite interactions) and geography (e.g. latitude). Predicting the permissive host set or the subset of the host community that a parasite can infect is a central goal of parasite ecology. Here we develop models that accurately predict the permissive host set of 562 helminth parasites in five different parasite taxonomic groups. We developed predictive models using host traits, host taxonomy, geographic covariates, and parasite community composition, finding that models trained on parasite community variables were more accurate than any other covariate group, even though parasite community covariates only captured a quarter of the variance in parasite community composition. This suggests that it is possible to predict the permissive host set for a given parasite, and that parasite community structure is an important predictor, potentially because parasite communities are interacting non-random assemblages.
机译：寄生术缔合是复杂的相互作用，依赖于宿主的方面（例如特征，系统发育或共轭历史），寄生虫（例如特征和寄生虫相互作用）和地理（例如纬度）。预测寄生虫可以感染的寄生宿主集或寄主社区的子集是寄生虫生态的核心目标。在这里，我们开发模型，可在五种不同的寄生虫分类群中准确地预测562升寄生虫的允许宿主组。我们开发了使用寄主特征，宿主分类，地理协变量和寄生虫群落组成的预测模型，发现寄生虫群落变量培训的模型比任何其他协变量群体更准确，即使寄生虫社区协变量只捕获寄生虫的四分之一差异社区组成。这表明可以预测给定寄生虫的允许宿主，并且寄生虫群落结构是一个重要的预测因子，可能是因为寄生虫社区是相互作用的非随机组装。

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