用于分析空间树型的密度相关和波动的联合评估
Joint assessment of density correlations and fluctuations for analysing spatial tree patterns
摘要：
理论生态学中的一个关键挑战是推断观察到的模式出现的过程。在过去几十年中，人们作出了很大努力，收集关于热带雨林空间分布的广泛而详细的资料，例如，在巴拿马巴罗科罗拉多岛上50公顷的热带森林里。这些样地对于揭示不同的质量特征至关重要，无论是在单一物种还是在群落水平上，如空间聚集或短尺度聚类。在这里，我们建立在应用于生物系统的密度关联函数的研究中取得的进展，专注于准确地定义树的集合的边界的重要性，并消除诱导的偏见。我们还指出了结合相关性的研究与密度波动的尺度依赖性，这是众所周知的经验泰勒的幂律的重要性。密度相关性和波动，结合起来，提供了一个独特的机会来解释的行为，并可能允许数据和模型之间的比较。我们还研究了这些数量的空间模式的模型，特别是，我们发现，一个空间明确的中性模型产生的模式与许多定性特征的共同经验。
英文摘要：
Inferring the processes underlying the emergence of observed patterns is a key challenge in theoretical ecology. Much effort has been made in the past decades to collect extensive and detailed information about the spatial distribution of tropical rainforests, as demonstrated, e.g., in the 50 ha tropical forest plot on Barro Colorado Island, Panama. These kind of plots have been crucial to shed light on diverse qualitative features, emerging both at the single-species or the community level, like the spatial aggregation or clustering at short scales. Here, we build on the progress made in the study of the density correlation functions applied to biological systems, focusing on the importance of accurately defining the borders of the set of trees, and removing the induced biases. We also pinpoint the importance of combining the study of correlations with the scale dependence of fluctuations in density, which are linked to the well known empirical Taylor's power law. Density correlations and fluctuations, in conjunction, provide an unique opportunity to interpret the behaviors and possibly to allow comparisons between data and models. We also study such quantities in models of spatial patterns and, in particular, we find that a spatially explicit neutral model generates patterns with many qualitative features in common with the empirical ones.
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