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Composite random search strategies based on non-directional sensory cues

机译：基于无方向感官线索的复合随机搜索策略

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Many foraging animals find food using composite random search strategies, which consist of intensive and extensive search modes. Models of composite search can generate predictions about how optimal foragers should behave in each search mode, and how they should determine when to switch between search modes. Most of these models assume that foragers use resource encounters to decide when to switch between search modes. Empirical observations indicate that a variety of organisms use non-directional sensory cues to identify areas that warrant intensive search. These cues are not precise enough to allow a forager to directly orient itself to a resource, but can be used as a criterion to determine the appropriate search mode. As a potential example, a forager might use olfactory information as a non-directional cue. Even if scent is too imprecise for the forager to immediately locate a specific food item, it might inform the forager that the area is worth searching carefully. We developed a model of composite search based on non-directional sensory cues. With simulations, we compared the search efficiencies of composite foragers that use resource encounters as their mode-switching criterion with those that use non-directional sensory cues. We identified optimal search patterns and mode-switching criteria on a variety of resource distributions, characterized by different levels of resource aggregation and density. On all resource distributions, foraging strategies based on the non-directional sensory criterion were more efficient than those based on the resource encounter criterion. Strategies based on the non-directional sensory criterion were also more robust to changes in resource distribution. Our results suggest that current assumptions about the role of resource encounters in models of optimal composite search should be re-examined. The search strategies predicted by our model can help bridge the gap between random search theory and traditional patch-use foraging theory. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
机译：许多觅食动物使用复合随机搜索策略寻找食物，该策略由密集搜索和广泛搜索模式组成。复合搜索模型可以生成有关最佳觅食者在每种搜索模式下的行为以及如何确定何时在搜索模式之间进行切换的预测。这些模型大多数都假定觅食者使用资源遭遇来决定何时在搜索模式之间切换。经验观察表明，多种生物利用非方向性的感觉线索来识别需要加强搜索的区域。这些提示不够精确，无法让觅食者直接将自己定向到资源上，但是可以用作确定适当搜索模式的标准。作为一个潜在的例子，觅食者可能将嗅觉信息用作无方向提示。即使气味对于觅食者来说太不精确，以至于无法立即找到特定的食物，它也可能会告知觅食者该区域值得仔细搜索。我们开发了一种基于无方向感官线索的复合搜索模型。通过模拟，我们比较了使用资源遭遇作为模式切换标准的复合觅食者与使用无方向感官线索的复合觅食者的搜索效率。我们确定了针对各种资源分布的最佳搜索模式和模式切换标准，这些资源的特征在于不同级别的资源聚集和密度。在所有资源分配上，基于无方向感官标准的觅食策略比基于资源遭遇标准的觅食策略更为有效。基于非方向性感觉标准的策略对于资源分配的变化也更加稳健。我们的结果表明，关于资源组合在最佳复合搜索模型中的作用的当前假设应重新检查。我们的模型预测的搜索策略可以帮助弥补随机搜索理论与传统补丁使用觅食理论之间的差距。 （C）2015作者。由Elsevier B.V.发布。这是CC BY许可下的开放获取文章（http://creativecommons.org/licenses/by/4.0/）。

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