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Utility of the CLIMEX ‘match climates regional’ algorithm for pest risk analysis: an evaluation with non-native ants in New Zealand

机译:Climex'匹配气候区域'危害风险分析算法的效用:新西兰非本土蚂蚁评估

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Abstract Pest risk analysts frequently ask if the climate of a pest risk analysis area could be suitable for the establishment of an organism of concern. Species distribution models can help to answer this question, but constructing them is technically complex, time consuming, and uninformative for additional non-modelled species. A quicker more broadly applicable approach involves using environmental distance metrics, including climate matching algorithms such as the ‘match climates regional’ function of CLIMEX (CLIMEX-MCR), to generate indices of climatic similarity between different locations without reference to particular species. Several studies have shown that various environmental distance metrics can provide biologically meaningful results. However, the veracity of the CLIMEX-MCR algorithm remains unevaluated, despite its application in numerous published studies. We used CLIMEX-MCR and high resolution New Zealand climate data to measure climatic similarities between New Zealand and the rest of the world. We then tested the veracity of the climatic match estimates by evaluating if their predictions regarding the suitability of New Zealand’s climate for 43 non-native ant species corresponded with empirical observations of those species in New Zealand. Non-native ants that are, or were once, established outdoors in New Zealand had overseas distributions that were climatically well matched with New Zealand. In contrast, species that either are established only indoors in New Zealand, or were observed to temporarily nest outdoors then die in New Zealand, had overseas distributions that were poorly matched. Species that are frequently intercepted at New Zealand’s border, but are not established there, generally also had overseas distributions with low climatic similarities to New Zealand. We also measured climatic similarities between New Zealand’s 13 national parks and the rest of the world. The overseas distributions of the non-native ants showed poor cli
机译:摘要害虫风险分析师经常询问害虫风险分析区域的气候是否适合建立关注的生物体。物种配送模型可以帮助回答这个问题,但构建它们是技术上复杂,耗时和不合形的额外非建模物种。更快的方法更快地涉及使用环境距离指标,包括气候匹配算法,如“匹配气候区域”功能的CLIMEX(CLIMEX-MCR),以在不参考特定物种之间产生不同位置之间的气候相似性的指标。几项研究表明,各种环境距离指标可以提供生物学上有意义的结果。然而,尽管其在许多公开的研究中应用,但ClimEx-MCR算法的真实性仍未高估了。我们使用Climex-MCR和高分辨率新西兰气候数据,以衡量新西兰与世界其他地区之间的气候相似之处。然后,我们通过评估他们对43种非天然蚂蚁物种的适用性的预测对应于新西兰这些物种的实证观察,通过评估它们的预测,测试了气候比赛估计的真实性。在新西兰的户外建立的非本土蚂蚁有海外分布,与新西兰相匹配。相比之下,只有在新西兰的室内建立的物种,或者被观察到临时巢户外,然后在新西兰死亡,已经匹配的海外分布。经常在新西兰边境截获的物种,但在那里没有建立,通常也有海外分布与新西兰的气候相似。我们还测量了新西兰13个国家公园与世界其他地方之间的气候相似之处。非本土蚂蚁的海外分布显示了贫困的CLI

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