Search and navigation in dynamic environments - from individual behaviors to population distributions
Search and navigation in dynamic environments - from individual behaviors to population distributions
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DOI：
10.1111/j.0030-1299.2008.16291.x
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发表时间：
2008-05-01
期刊：
影响因子：
3.4
通讯作者：
Fagan, William F.
中科院分区：
文献类型：
--
作者：
Mueller, Thomas;Fagan, William F.
动物运动在生态学和行为学领域受到广泛关注。然而，许多研究局限于孤立的子学科，侧重于单一现象，如导航(例如寻的行为)、搜索策略(例如Levy飞行)或最优种群分散的理论考虑(例如理想的自由分布)。为了帮助综合现有的研究，我们勾勒出一个统一的概念框架，该框架整合了关于时空资源动态的个体水平的行为和群体水平的空间分布。我们区分了(1)基于对近刺激的扩散和运动的非定向运动，(2)利用远处目标的感知线索的定向运动，以及(3)假设目标位置的先验知识的记忆机制。物种对这些机制的使用取决于生活史特征和资源动态，它们共同塑造了种群水平的模式。空间变异性很小的资源应该有利于静止的范围，而空间分布具有可预测的季节变化的资源应该产生迁徙模式。当资源分布在空间和时间上都不可预测时，应该出现第三种模式，即“游牧”。我们总结了动物轨迹分析的最新进展，并概述了未来研究应重点关注的三个主要组成部分：(1)涉及状态变量和特定机制之间联系的跨替代运动机制的整合；(2)考虑资源景观或环境中的动态，其中包括可预测性、可变性、规模和丰度方面的资源梯度；以及(3)区分种群分布的定量方法。我们认为，将进化编程和面向模式的建模等技术相结合，将有助于在潜在的运动机制和广泛的人口分布之间建立强有力的联系。
Animal movement receives widespread attention within ecology and behavior. However, much research is restricted within isolated sub-disciplines focusing on single phenomena such as navigation (e.g. homing behavior), search strategies (e.g. Levy flights) or theoretical considerations of optimal population dispersion (e.g. ideal free distribution). To help synthesize existing research, we outline a unifying conceptual framework that integrates individual-level behaviors and population-level spatial distributions with respect to spatio-temporal resource dynamics. We distinguish among (1) non-oriented movements based on diffusion and kinesis in response to proximate stimuli, (2) oriented movements utilizing perceptual cues of distant targets, and (3) memory mechanisms that assume prior knowledge of a target's location. Species' use of these mechanisms depends on life-history traits and resource dynamics, which together shape population-level patterns. Resources with little spatial variability should facilitate sedentary ranges, whereas resources with predictable seasonal variation in spatial distributions should generate migratory patterns. A third pattern, 'nomadism', should emerge when resource distributions are unpredictable in both space and time. We summarize recent advances in analyses of animal trajectories and outline three major components on which future studies should focus: (1) integration across alternative movement mechanisms involving links between state variables and specific mechanisms, (2) consideration of dynamics in resource landscapes or environments that include resource gradients in predictability, variability, scale, and abundance, and finally (3) quantitative methods to distinguish among population distributions. We suggest that combining techniques such as evolutionary programming and pattern oriented modeling will help to build strong links between underlying movement mechanisms and broad-scale population distributions.