Villegas P, Cavagna A, Cencini M, Fort H, Grigera T S
Istituto dei Sistemi Complessi, Consiglio Nazionale delle Ricerche, via dei Taurini 19 00185 Rome, Italy.
Dipartimento di Fisica, Università Sapienza, 00185 Rome, Italy.
R Soc Open Sci. 2021 Jan 20;8(1):202200. doi: 10.1098/rsos.202200. eCollection 2021 Jan.
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 kinds 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 a unique opportunity to interpret the behaviours 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.
推断观察到的模式出现背后的过程是理论生态学中的一个关键挑战。在过去几十年里,人们付出了巨大努力来收集有关热带雨林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公顷热带森林样地中所展示的那样。这类样地对于揭示在单物种或群落水平上出现的各种定性特征至关重要,比如短尺度上的空间聚集或聚类。在这里,我们基于在应用于生物系统的密度相关函数研究中所取得的进展,重点关注准确界定树木集合边界以及消除由此产生的偏差的重要性。我们还指出了将相关性研究与密度波动的尺度依赖性相结合的重要性,这与著名的经验性泰勒幂律相关。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,并且有可能允许对数据和模型进行比较。我们还在空间模式模型中研究此类量,特别是我们发现一个空间明确的中性模型生成的模式具有许多与经验模式相同的定性特征。