Ferdous Mst Jannatul, Reynolds Andy M, Cheng Ken
1Department of Biological Sciences, Macquarie University, Sydney, NSW 2109 Australia.
2Rothamsted Research, Harpenden, Hertfordshire, AL5 2JQ UK.
Behav Ecol Sociobiol. 2018;72(7):113. doi: 10.1007/s00265-018-2527-1. Epub 2018 Jun 20.
The correlated random walk paradigm is the dominant conceptual framework for modeling animal movement patterns. Nonetheless, we do not know whether the randomness is apparent or actual. Apparent randomness could result from individuals reacting to environmental cues and their internal states in accordance with some set of behavioral rules. Here, we show how apparent randomness can result from one simple kind of algorithmic response to environmental cues. This results in an exponential step-length distribution in homogeneous environments and in generalized stretched exponential step-length distributions in more complex fractal environments. We find support for these predictions in the movement patterns of the Australian bull ant searching on natural surfaces and on artificial uniform and quasi-fractal surfaces. The bull ants spread their search significantly farther on the quasi-fractal surface than on the uniform surface, showing that search characteristics differed as a function of the substrate on which ants are searching. Further tentative support comes from a re-analysis of Australian desert ants moving on smoothed-over sand and on a more strongly textured surface. Our findings call for more experimental studies on different surfaces to test the surprising predicted linkage between fractal dimension and the exponent in the step-length distribution.
Animal search patterns often appear to be irregular and erratic. This behavior is captured by random walk models. Despite their considerable successes, extrapolation and prediction beyond observations remain questionable because the true nature and interpretation of the randomness in these models have until now been elusive. Here, we show how apparent randomness can result from simple algorithmic responses to environmental cues. Distinctive predictions from our theory find support in analyses of the search patterns of two species of Australian ants.
相关随机游走范式是用于模拟动物运动模式的主导概念框架。然而，我们并不清楚这种随机性是表面的还是实际存在的。表面上的随机性可能源于个体根据一系列行为规则对环境线索及其内部状态做出反应。在这里，我们展示了表面上的随机性是如何由对环境线索的一种简单算法响应产生的。这在均匀环境中导致指数步长分布，而在更复杂的分形环境中导致广义拉伸指数步长分布。我们在澳大利亚公牛蚁在自然表面、人工均匀表面和准分形表面上的搜索运动模式中找到了对这些预测的支持。公牛蚁在准分形表面上的搜索范围明显比在均匀表面上更广，这表明搜索特征因蚂蚁搜索的底物不同而有所差异。进一步的初步支持来自对在平滑沙地和纹理更强的表面上移动的澳大利亚沙漠蚁的重新分析。我们的发现呼吁针对不同表面进行更多实验研究，以测试分形维数与步长分布指数之间令人惊讶的预测联系。
动物的搜索模式通常看起来不规则且不稳定。这种行为由随机游走模型来描述。尽管这些模型取得了相当大的成功，但在观测范围之外进行外推和预测仍然存在疑问，因为这些模型中随机性的真正本质和解释至今仍难以捉摸。在这里，我们展示了表面上的随机性是如何由对环境线索的简单算法响应产生的。我们理论的独特预测在对两种澳大利亚蚂蚁搜索模式的分析中得到了支持。
