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Improving species distribution models using biotic interactions: a case study of parasites, pollinators and plants

机译:使用生物相互作用改善物种分布模型:寄生虫,传粉媒介和植物的案例研究

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摘要

Biotic interactions have been considered as an important factor to be included in species distribution modelling, but little is known about how different types of interaction or different strategies for modelling affect model performance. This study compares different methods for including interspecific interactions in distribution models for bees, their brood parasites, and the plants they pollinate. Host–parasite interactions among bumble bees (genus Bombus: generalist pollinators and brood parasites) and specialist plant–pollinator interactions between Centris bees and Krameria flowers udwere used as case studies. We used 7 different modelling algorithms available in the BIOMOD R package. For Bombus, udthe inclusion of interacting species distributions generally increased model predictive accuracy. The improvement was better when the interacting species was included with its raw distribution rather than with its modeled suitability. However, incorporating the distributions of non-interacting species sometimes resulted in similarly increased model accuracy despite their being no significance of any interaction for the distribution. For the Centris-Krameria system the best strategy for modelling biotic interactions was to include the interacting species model-predicted values. However, the results were less consistent than those for Bombus species, and most models including biotic interactions showed no significant improvement over abiotic models. Our results are consistent with previous studies showing that biotic interactions can be important in structuring species distributions at regional scales. However, correlations between species distributions are not necessarily indicative of interactions. Therefore, choosing the correct biotic information, based on biological and ecological knowledge, is critical to improve the accuracy of species distribution models and forecast distribution change.
机译:生物相互作用已被视为包括在物种分布建模中的重要因素,但对于不同类型的相互作用或不同建模策略如何影响模型性能的了解甚少。这项研究比较了在蜜蜂,它们的亲代寄生虫和它们授粉的植物的分布模型中包括种间相互作用的不同方法。案例研究使用了大黄蜂之间的寄主-寄生虫相互作用(Bombus属:普通传粉媒介和育种寄生虫)以及Centris蜜蜂和Krameria花之间的专业植物-授粉媒介相互作用。我们使用了BIOMOD R软件包中提供的7种不同的建模算法。对于Bombus,包括交互物种分布在内通常会提高模型的预测准确性。如果将相互作用的物种包括在其原始分布中,而不是在其建模的适用性中,则改进会更好。但是,合并非相互作用物种的分布有时会导致模型准确性类似地提高,尽管它们对分布没有任何影响。对于Centris-Krameria系统,模拟生物相互作用的最佳策略是包括相互作用物种模型预测的值。但是,结果与Bombus物种的结果不一致,而且大多数模型(包括生物相互作用)都没有显示出比非生物模型明显的改善。我们的结果与先前的研究一致,后者表明生物相互作用在构造区域尺度上的物种分布方面很重要。但是,物种分布之间的相关性不一定表示相互作用。因此,基于生物学和生态学知识选择正确的生物信息对于提高物种分布模型的准确性和预测分布变化至关重要。

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