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Consensual predictions of potential distributional areas for invasive species: a case study of Argentine ants in the Iberian Peninsula

机译:入侵物种潜在分布区域的共识预测:以伊比利亚半岛的阿根廷蚂蚁为例

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摘要

Invasive species are known to influence the structure and function of invaded ecological communities, and preventive measures appear to be the most efficient means of controlling these effects. However, management of biological invasions requires use of adequate tools to understand and predict invasion patterns in recently introduced areas. The present study: (1) estimates the potential geographic distribution and ecological requirements of the Argentine ant (Linepithema humile Mayr), one of the most conspicuous invasive species throughout the world, in the Iberian Peninsula using ecological niche modeling, and (2) provides new insights into the process of selection of consensual areas among predictions from several modeling methodologies. Ecological niche models were developed using 5 modeling techniques: generalized linear models (GLM), generalized additive models (GAM), generalized boosted models (GBM), Genetic Algorithm for Rule-Set Prediction (GARP), and Maximum Entropy (Maxent). Models for the eastern and western portions of the Iberian Peninsula were built using subsets of occurrence and environmental data to investigate the potential for ecological niche differences between the invading populations. Our results indicate geographic differences between predictions of different approaches, and the utility of ensemble predictions in identifying areas of uncertainty regarding the species’ invasive potential. More generally, our models predict coastal areas and major river corridors as highly suitable for Argentine ants, and indicate that western and eastern Iberian Peninsula populations occupy similar environmental conditions.
机译:众所周知,外来入侵物种会影响被入侵的生态群落的结构和功能,而预防措施似乎是控制这些影响的最有效手段。但是,生物入侵的管理需要使用适当的工具来理解和预测最近引入地区的入侵模式。本研究:(1)使用生态位建模方法估算伊比利亚半岛阿根廷蚂蚁(Linepithema humile Mayr)(世界上最引人注目的入侵物种之一)的潜在地理分布和生态需求,以及(2)提供从几种建模方法的预测中选择共识区域的过程的新见解。生态位模型是使用5种建模技术开发的:广义线性模型(GLM),广义加性模型(GAM),广义增强模型(GBM),规则集预测的遗传算法(GARP)和最大熵(Maxent)。利用发生和环境数据的子集建立了伊比利亚半岛东部和西部的模型,以研究入侵种群之间生态位差异的潜力。我们的结果表明,不同方法的预测之间在地理上存在差异,并且集合预测在确定有关物种入侵潜力的不确定区域方面的效用。更广泛地说,我们的模型预测沿海地区和主要河流走廊非常适合阿根廷蚂蚁,并表明伊比利亚半岛西部和东部的人口处于相似的环境条件。

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