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Behavior underpins the predictive power of a trait‐based model of butterfly movement

机译:行为是基于特征的蝴蝶运动模型的预测力

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Dispersal ability is key to species persistence in times of environmental change. Assessing a species' vulnerability and response to anthropogenic changes is often performed using one of two methods: correlative approaches that infer dispersal potential based on traits, such as wingspan or an index of mobility derived from expert opinion, or a mechanistic modeling approach that extrapolates displacement rates from empirical data on short‐term movements. Here, we compare and evaluate the success of the correlative and mechanistic approaches using a mechanistic random‐walk model of butterfly movement that incorporates relationships between wingspan and sex‐specific movement behaviors. The model was parameterized with new data collected on four species of butterfly in the south of England, and we observe how wingspan relates to flight speeds, turning angles, flight durations, and displacement rates. We show that flight speeds and turning angles correlate with wingspan but that to achieve good prediction of displacement even over 10?min the model must also include details of sex‐ and species‐specific movement behaviors. We discuss what factors are likely to differentially motivate the sexes and how these could be included in mechanistic models of dispersal to improve their use in ecological forecasting.
机译:分散能力是在环境变化时期持久性的关键。评估物种的脆弱性和对人为变化的响应通常是使用两种方法之一进行的:基于特征的分散潜力的相关方法,例如翅膀鲍曼或来自专家意见的迁移率指数,或推断出位移的机制建模方法来自短期运动的经验数据的率。在这里,我们使用蝴蝶运动的机械随机步道模型进行比较和评估相关和机械方法的成功,该模型包含翅膀和性别特定运动行为之间的关系。该模型是通过在英格兰南部的四种蝴蝶中收集的新数据进行了参数化,我们观察了翼班潘如何与飞行速度,转动角度,飞行持续性和排量率有关。我们展示了飞行速度和转向角度与翅膀的速度相关,但是为了实现甚至超过10?最小的位移预测,模型还必须包括性别和物种特定运动行为的细节。我们讨论哪些因素可能差异地激励性别,以及如何包含在分散的机械模型中,以改善它们在生态预测中的使用。

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