Spatial dynamics in model plant communities: What do we really know?

Spatial dynamics in model plant communities: What do we really know?
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DOI:
10.1086/376575
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发表时间:
2003-08-01
影响因子:
2.9
通讯作者:
Neuhauser, C
Neuhauser, C
中科院分区:
环境科学与生态学2区
文献类型:
--
作者:
Bolker, BM;Pacala, SW;Neuhauser, C

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各种模型表明,空间动态和小尺度内生异质性(例如,森林空隙或当地资源枯竭区)可以改变植物或其他固着生物群落竞争的速度和结果。然而,该理论显得复杂,难以与真实的系统联系起来。我们综合了三种不同类型的模型的结果:相互作用的粒子系统,空间点过程的矩方程,和集合种群或补丁模型。使用所有三个框架的研究都认为,空间动态不需要加强共存,也不需要减缓动态;它们的影响取决于社区中潜在的竞争性互动。当相似的物种在非空间栖息地共存时,内源性空间结构抑制共存并减缓动态。当一个优势物种分散差,较弱的物种有较高的繁殖力或更好的传播,竞争殖民权衡加强共存。即使当物种有平等的分散和每代繁殖力,空间演替小生境,较弱和快速增长的物种可以迅速利用短暂的本地资源,可以提高共存。当种间竞争是强大的,空间动态减少创始人控制在大尺度和短扩散成为有利的。我们描述了一系列的实证测试,以检测和区分建议的情况。
A variety of models have shown that spatial dynamics and small-scale endogenous heterogeneity (e.g., forest gaps or local resource depletion zones) can change the rate and outcome of competition in communities of plants or other sessile organisms. However, the theory appears complicated and hard to connect to real systems. We synthesize results from three different kinds of models: interacting particle systems, moment equations for spatial point processes, and metapopulation or patch models. Studies using all three frameworks agree that spatial dynamics need not enhance coexistence nor slow down dynamics; their effects depend on the underlying competitive interactions in the community. When similar species would coexist in a nonspatial habitat, endogenous spatial structure inhibits coexistence and slows dynamics. When a dominant species disperses poorly and the weaker species has higher fecundity or better dispersal, competition-colonization trade-offs enhance coexistence. Even when species have equal dispersal and per-generation fecundity, spatial successional niches where the weaker and faster-growing species can rapidly exploit ephemeral local resources can enhance coexistence. When interspecific competition is strong, spatial dynamics reduce founder control at large scales and short dispersal becomes advantageous. We describe a series of empirical tests to detect and distinguish among the suggested scenarios.