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A predictive distribution map for the giant tropical ant, Paraponera clavata

机译:巨型热带蚂蚁Paraponera clavata的预测分布图

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Paraponera clavata (Fabricius 1775) (Formicidae: Paraponerinae) is a widely distributed Neotropical ant whose large size has attracted the attention of numerous collectors. Working from museum specimens, a georeferenced database of collection localities was developed. This database then served as the source for computer generated predictive distribution maps. Annual rainfall was the most important variable chosen by the computer model to predict the distribution of P. clavata, both on the scale of the neotropics and at a finer scale at the northern end its distribution in Costa Rica and Nicaragua. When the model was forced to use vegetation as the first predictive variable, the Neotropical model used temperature and rainfall variance as additional variables, while the Mesoamerican model used both climatic and soils variables. Overall, the modeling suggests that P. clavata is more sensitive to abiotic factors (rainfall, temperature, soils) than to biotic factors (vegetation type) in its distribution, although this conclusion comes with the caveat that the vegetation types used in the model are quite generalized. Predictive distribution mapping holds great promise for generating more precise representations of insect distributions, thereby allowing better tests of the extent of distribution overlaps and other community relationships.
机译:Paraponera clavata(Fabricius 1775)(Formicidae:Paraponerinae)是分布广泛的新热带蚂蚁,它的大尺寸吸引了众多收藏家的注意。从博物馆的标本开始,开发了一个地理收集地点的数据库。然后,该数据库用作计算机生成的预测分布图的来源。年降水量是计算机模型选择的最重要的变量,可预测新近纪尺度和北端在哥斯达黎加和尼加拉瓜分布较细的蟹爪螺的分布。当模型被迫使用植被作为第一个预测变量时,新热带模型使用温度和降雨量变化作为附加变量,而中美洲模型则使用气候和土壤变量。总体而言,该模型表明P. clavata在分布中对非生物因素(降雨,温度,土壤)比对生物因素(植被类型)更敏感,尽管这一结论附带说明,模型中使用的植被类型为相当笼统。预测性分布图具有产生昆虫分布更精确表示的巨大前景,从而可以更好地测试分布重叠的程度和其他社区关系。

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