Hiebeler David E, Morin Benjamin R
Department of Mathematics and Statistics, University of Maine, 333 Neville Hall, Orono, ME 04469-5752, USA.
J Theor Biol. 2007 May 7;246(1):136-44. doi: 10.1016/j.jtbi.2006.12.024. Epub 2006 Dec 28.
Previous models of locally dispersing populations have shown that in the presence of spatially structured fixed habitat heterogeneity, increasing local spatial autocorrelation in habitat generally has a beneficial effect on such populations, increasing equilibrium population density. It has also been shown that with large-scale disturbance events which simultaneously affect contiguous blocks of sites, increasing spatial autocorrelation in the disturbances has a harmful effect, decreasing equilibrium population density. Here, spatial population models are developed which include both of these spatially structured exogenous influences, to determine how they interact with each other and with the endogenously generated spatial structure produced by the population dynamics. The models show that when habitat is fragmented and disturbance occurs at large spatial scales, the population cannot persist no matter how large its birth rate, an effect not seen in previous simpler models of this type. The behavior of the model is also explored when the local autocorrelation of habitat heterogeneity and disturbance events are equal, i.e. the two effects occur at the same spatial scale. When this scale parameter is very small, habitat fragmentation prevents the population from persisting because sites attempting to reproduce will drop most of their offspring on unsuitable sites; when the parameter is very large, large-scale disturbance events drive the population to extinction. Population levels reach their maximum at intermediate values of the scale parameter, and the critical values in the model show that the population will persist most easily at these intermediate scales of spatial influences. The models are investigated via spatially explicit stochastic simulations, traditional (infinite-dispersal) and improved (local-dispersal) mean-field approximations, and pair approximations.
先前关于局域扩散种群的模型表明,在存在空间结构固定的栖息地异质性的情况下,栖息地中局部空间自相关性的增加通常对这类种群有有益影响,会提高平衡种群密度。研究还表明,对于同时影响相邻地块的大规模干扰事件,干扰中空间自相关性的增加会产生有害影响,降低平衡种群密度。在此,我们开发了空间种群模型,该模型包含这两种具有空间结构的外部影响,以确定它们如何相互作用,以及如何与种群动态产生的内生性空间结构相互作用。模型显示,当栖息地破碎化且在大空间尺度上发生干扰时,无论种群出生率有多高,种群都无法持续存在,这种效应在之前此类更简单的模型中并未出现。当栖息地异质性和干扰事件的局部自相关性相等时,即两种效应在相同空间尺度上发生时,我们也对模型的行为进行了探索。当这个尺度参数非常小时,栖息地破碎化会阻止种群持续存在,因为试图繁殖的地点会将大部分后代落在不合适的地点上;当参数非常大时,大规模干扰事件会导致种群灭绝。种群数量在尺度参数的中间值处达到最大值,模型中的临界值表明,种群在这些空间影响的中间尺度上最容易持续存在。我们通过空间明确的随机模拟、传统(无限扩散)和改进(局域扩散)的平均场近似以及配对近似对模型进行了研究。