Misconceptions about quantifying animal encounter and interaction processes
Misconceptions about quantifying animal encounter and interaction processes
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DOI：
10.3389/fevo.2023.1230890
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发表时间：
2023-09
影响因子：
3
通讯作者：
Debraj Das;V. M. Kenkre;Ran Nathan;L. Giuggioli
中科院分区：
文献类型：
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作者：
Debraj Das;V. M. Kenkre;Ran Nathan;L. Giuggioli
量化动物相互作用的时间和地点的能力是理解大量生态过程的关键，从社会群落结构和捕食者-猎物关系到病原体和信息的传播。尽管动物之间的互动过程无处不在，跟踪技术的革命现在允许同时监控多个个体，但仍然缺乏一个共同的理论框架来分析运动数据和提取互动事件。考虑到控制生物有机体如何检测其他生物的接近性的机制范围很广，大多数提出的理论方法都是针对特定物种或经验情况量身定制的，迄今为止还缺乏一种通用的方法来评估和比较不同分类群的发现。在这里，我们通过借用统计物理学，特别是反应扩散过程理论的技术，提出了这样的总体框架。其中一些技术已经被用于预测在家庭范围内生活的动物对病原体传播事件的分析，但尚未普及到运动生态学文献中。利用连续变量和离散变量，我们提出了数学框架，并证明了它对研究相互作用过程的适用性。通过定义每当信息令牌从一个个体转移到另一个个体时的交互作用，我们证明了第一次传递信息的概率相当于在多目标环境中反应的第一次通过概率。当信息传递非常有效时，交互事件减少为遭遇事件，我们将我们的形式主义与最近提出的研究遭遇的方法进行比较。这种方法将两只动物在一个相互作用区域的共同占领概率作为相遇概率的度量，而不是第一次相遇概率。我们通过分析比较连续变量的预测来显示两种方法的差异，而对于离散时空变量，我们量化了它们随时间的差异。最后，我们指出一些尚未解决的问题，反应扩散形式论，或者，反应运动形式论，应该更恰当的称呼，可能能够解决这些问题。
The ability to quantify when and where animals interact is key to the understanding of a plethora of ecological processes, from the structure of social communities and predator–prey relations to the spreading of pathogens and information. Despite the ubiquity of interaction processes among animals and the revolution in tracking technologies that now allows for the monitoring of multiple individuals simultaneously, a common theoretical framework with which to analyze movement data and extract interaction events is still lacking. Given the wide spectrum of mechanisms that governs how a biological organism detects the proximity of other organisms, most of the proposed theoretical approaches have been tailored to specific species or empirical situations and so far have been lacking a common currency with which to evaluate and compare findings across taxa. Here, we propose such general framework by borrowing techniques from statistical physics, specifically from the theory of reaction diffusion processes. Some of these techniques have already been employed to predict analytically pathogen transmission events between pairs of animals living within home ranges, but have not yet pervaded the movement ecology literature. Using both continuous and discrete variables, we present the mathematical framework and demonstrate its suitability to study interaction processes. By defining interactions whenever a token of information is transferred from one individual to another, we show that the probability of transferring information for the first time is equivalent to the first-passage probability of reacting in a multi-target environment. As interaction events reduce to encounter events when information transfer is perfectly efficient, we compare our formalism to a recently proposed approach to study encounters. Such approach takes the joint occupation probability of two animals over a region of interaction as a measure of the probability of encounter, rather than the first-encounter probability. We show the discrepancy of the two approaches by analytically comparing their predictions with continuous variables, while with discrete space–time variables, we quantify their difference over time. We conclude by pointing to some of the open problems that the reaction diffusion formalism, alternatively, the reaction motion formalism, as it should be more appropriately called, might be able to tackle.