论文标题
密度相关性和波动的联合评估用于分析空间树模式
Joint assessment of density correlations and fluctuations for analysing spatial tree patterns
论文作者
论文摘要
推断观测模式出现的过程是理论生态学中的关键挑战。在过去的几十年中,已经付出了很多努力,以收集有关热带雨林的空间分布的广泛而详细的信息,例如,在巴拿马巴罗科罗拉多岛的50公顷热带森林情节中所证明的。这些图对于阐明各种定性特征至关重要,在单物种或社区层面上出现,例如空间聚集或在短尺度上进行聚集。在这里,我们基于研究应用于生物系统的密度相关函数的进展,重点是准确定义树木的边界并消除诱导偏见的重要性。我们还指出了将相关性研究与密度波动的规模依赖性相结合的重要性,密度与众所周知的经验泰勒的权力定律有关。密度相关性和波动共同提供了一个独特的机会来解释行为,并可能允许在数据和模型之间进行比较。我们还研究了在空间模式模型中的这种数量,尤其是,我们发现一个空间显式的中性模型会生成具有许多与经验的模式相同的定性特征。
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.