The role of memory-based movements in the formation of animal home ranges

IF 2.2 4区 数学 Q2 BIOLOGY Journal of Mathematical Biology Pub Date : 2024-04-08 DOI:10.1007/s00285-024-02055-2
Nathan Ranc, John W. Cain, Francesca Cagnacci, Paul R. Moorcroft
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Abstract

Most animals live in spatially-constrained home ranges. The prevalence of this space-use pattern in nature suggests that general biological mechanisms are likely to be responsible for their occurrence. Individual-based models of animal movement in both theoretical and empirical settings have demonstrated that the revisitation of familiar areas through memory can lead to the formation of stable home ranges. Here, we formulate a deterministic, mechanistic home range model that includes the interplay between a bi-component memory and resource preference, and evaluate resulting patterns of space-use. We show that a bi-component memory process can lead to the formation of stable home ranges and control its size, with greater spatial memory capabilities being associated with larger home range size. The interplay between memory and resource preferences gives rise to a continuum of space-use patterns–from spatially-restricted movements into a home range that is influenced by local resource heterogeneity, to diffusive-like movements dependent on larger-scale resource distributions, such as in nomadism. Future work could take advantage of this model formulation to evaluate the role of memory in shaping individual performance in response to varying spatio-temporal resource patterns.

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基于记忆的运动在形成动物家园范围中的作用
大多数动物都生活在空间受限的家园范围内。这种空间利用模式在自然界的普遍存在表明,一般的生物机制很可能是造成这种现象的原因。基于个体的动物运动模型在理论和实证环境中都证明,通过记忆重访熟悉的区域可以形成稳定的家园范围。在这里,我们建立了一个确定性的、机制性的家园范围模型,其中包括双组分记忆和资源偏好之间的相互作用,并对由此产生的空间利用模式进行了评估。我们的研究表明,双组分记忆过程可以形成稳定的家园范围并控制其大小,空间记忆能力越强,家园范围越大。记忆和资源偏好之间的相互作用产生了连续的空间利用模式--从受当地资源异质性影响的进入家园范围的空间受限运动,到依赖于更大规模资源分布的扩散式运动,如游牧。未来的研究工作可以利用这一模型来评估记忆在塑造个体表现以应对不同的时空资源模式方面所起的作用。
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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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