Hancock Penelope A, Milner-Gulland E J, Keeling Matthew J
Imperial College London, Division of Biology, Manor House, Silwood Park Campus, Imperial College London, Ascot, Berkshire SL5 7PY, UK.
J Theor Biol. 2006 May 21;240(2):302-10. doi: 10.1016/j.jtbi.2005.09.019. Epub 2005 Nov 10.
We develop a simple individual-based model to gain an understanding of the drivers of aggregation behaviour in nomadic foragers. The model incorporates two key elements influencing nomadic foragers in variable environments: uncertainty regarding the location of food sources and variability in the spatio-temporal distribution of ephemeral food sources. A genetic algorithm is used to evolve parameters describing an individual's movement and aggregation strategy. We apply the aggregation model to a case study of the Bornean bearded pig (Sus barbatus). Bearded pigs are ideal for considering the foraging advantages of aggregation, because they are highly mobile and exhibit a variety of aggregation strategies, ranging from solitary and sedentary to mass aggregation and wide ranging migration. Our model demonstrates the "many-wrongs principle", and shows that environmental variability, uncertainty in the location of food sources, and local population density drive aggregation behaviour.
我们开发了一个简单的基于个体的模型,以了解游牧觅食者聚集行为的驱动因素。该模型纳入了在多变环境中影响游牧觅食者的两个关键因素:食物源位置的不确定性以及短暂食物源时空分布的变异性。使用遗传算法来演化描述个体移动和聚集策略的参数。我们将聚集模型应用于婆罗洲须猪(Sus barbatus)的案例研究。须猪是考虑聚集觅食优势的理想对象,因为它们具有高度的移动性,并且展现出从独居和定居到大规模聚集和大范围迁徙等多种聚集策略。我们的模型证明了“多数错误原则”,并表明环境变异性、食物源位置的不确定性以及当地种群密度驱动着聚集行为。