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The Effects of Spatially Heterogeneous Prey Distributions on Detection Patterns in Foraging Seabirds

机译:空间异类猎物分布对觅食海鸟检测模式的影响

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摘要

Many attempts to relate animal foraging patterns to landscape heterogeneity are focused on the analysis of foragers movements. Resource detection patterns in space and time are not commonly studied, yet they are tightly coupled to landscape properties and add relevant information on foraging behavior. By exploring simple foraging models in unpredictable environments we show that the distribution of intervals between detected prey (detection statistics) is mostly determined by the spatial structure of the prey field and essentially distinct from predator displacement statistics. Detections are expected to be Poissonian in uniform random environments for markedly different foraging movements (e.g. Lévy and ballistic). This prediction is supported by data on the time intervals between diving events on short-range foraging seabirds such as the thick-billed murre (Uria lomvia). However, Poissonian detection statistics is not observed in long-range seabirds such as the wandering albatross (Diomedea exulans) due to the fractal nature of the prey field, covering a wide range of spatial scales. For this scenario, models of fractal prey fields induce non-Poissonian patterns of detection in good agreement with two albatross data sets. We find that the specific shape of the distribution of time intervals between prey detection is mainly driven by meso and submeso-scale landscape structures and depends little on the forager strategy or behavioral responses.
机译:将动物觅食方式与景观异质性联系起来的许多尝试都集中在对觅食者运动的分析上。时空资源检测模式并未得到普遍研究,但它们与景观特性紧密相关,并添加了有关觅食行为的相关信息。通过在不可预测的环境中探索简单的觅食模型,我们表明,所检测猎物之间的间隔分布(检测统计数据)主要由猎物场的空间结构决定,并且与捕食者位移统计数据本质上不同。对于均匀不同的觅食运动(例如Lévy和弹道),预期在统一随机环境中的检测将是Poissonian。该预测得到有关短距离觅食海鸟(如开嘴鱼(Uria lomvia))潜水事件之间时间间隔的数据的支持。然而,由于猎物场的分形特性,其覆盖了广泛的空间尺度,因此在诸如游荡的信天翁(Diomedea exulans)之类的远距离海鸟中未观察到Poissonian检测统计数据。在这种情况下,分形猎物场模型会诱导非泊松检测模式,并与两个信天翁数据集高度吻合。我们发现,猎物检测之间的时间间隔分布的特定形状主要由中观和亚中尺度尺度的景观结构驱动,而很少依赖于觅食者的策略或行为反应。

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