How Territorial Animals Compete for Divisible Space: A Learning‐Based Model with Unequal Competitors
How Territorial Animals Compete for Divisible Space: A Learning‐Based Model with Unequal Competitors
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领地动物如何竞争可分割空间：具有不平等竞争者的基于学习的模型
DOI：
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发表时间：
2001
影响因子：
2.9
通讯作者：
V. V. Krishnan
中科院分区：
文献类型：
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作者：
J. Stamps;V. V. Krishnan
人们普遍认为，侵略行为影响领土物种的空间获取，但迄今为止，大多数工作者都集中在不可分割的空间，即空间，不能分割或共享的竞争。我们提出了一个基于学习的模型，研究了当不平等的竞争者到达并定居在可分空间的补丁时，侵略性交互对空间获取的影响。这个模型假设攻击性的互动作为惩罚，在这个意义上说，以前的攻击性互动在一个给定的区域减少个人的可能性返回该地区。基于个人的，空间上明确的模拟，将此和其他假设被用来调查不同类型的侵略性的相互作用对空间使用的个人和解决在可分空间的二人组的影响。在个人层面上，最终的空间使用与个人在攻击性互动中对对手施加的惩罚量有关;一般来说，高度攻击性的个体比攻击性较低的个体获得更大、更专属的家域。在二元层次上，竞争者之间的空间划分或共享取决于竞争者在侵略性互动中对彼此施加的相对和绝对惩罚。两个参与者强烈惩罚对方的攻击性互动（例如，升级的战斗）产生了相互排斥的家庭范围，与中等惩罚水平的相互作用产生了与惩罚水平的不对称成比例的不对称的空间使用模式，并且对任何一个参与者都没有惩罚的相互作用产生了大的家庭范围，其中有广泛的家庭范围重叠。总的来说，我们的模型意味着领土动物不需要“赢得”侵略性的互动来赢得可分割的空间，反复“唠叨”对手也可能是获得空间的可行策略，并且基于学习的方法可以解释领土文献中令人困惑的模式，例如，观察到通过发起侵略性互动来获得空间的个体，他们从未赢过。
It is widely assumed that aggressive behavior affects space acquisition in territorial species, but to date most workers have focused on competition for indivisible space, that is, space that cannot be divided or shared. We present a learning‐based model that investigates the effects of aggressive interactions on space acquisition when unequal competitors arrive and settle in patches of divisible space. This model assumes that aggressive interactions act as punishment, in the sense that previous aggressive interactions in a given area reduce an individual’s likelihood of returning to that area. Individually based, spatially explicit simulations incorporating this and other assumptions were used to investigate the effects of different types of aggressive interactions on the space use of individuals and dyads settling in divisible space. At the individual level, final space use was related to the amount of punishment that individuals inflicted on their opponents during aggressive interactions; in general, highly aggressive individuals acquired larger, more exclusive home ranges than less aggressive individuals. At the dyadic level, the division or sharing of space between competitors depended on both the relative and absolute punishment that competitors inflicted on one another during aggressive interactions. Aggressive interactions in which both participants strongly punished one another (e.g., escalated fights) produced mutually exclusive home ranges, interactions with intermediate levels of punishment produced asymmetrical space use patterns proportional to asymmetries in punishment levels, and interactions involving little punishment for either participant generated large home ranges with extensive home range overlap. Overall, our model implies that territorial animals need not “win” aggressive interactions to win divisible space, that repeatedly “nagging” an opponent may also be a viable strategy for gaining space, and that a learning‐based approach can account for puzzling patterns in the territorial literature, for example, observations of individuals who acquire space by initiating aggressive interactions that they never win.