The glocal forest

Efrat Seri, Elad Shtilerman, Nadav M. Shnerb

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Spatial ecological patterns reflect the underlying processes that shape the structure of species and communities. Mechanisms like intra- and inter-specific competition, dispersal and host-pathogen interactions can act over a wide range of scales. Yet, the inference of such processes from patterns is a challenging task. Here we call attention to a quite unexpected phenomenon in the extensively studied tropical forest at the Barro-Colorado Island (BCI): the spatial deployment of (almost) all tree species is statistically equivalent, once distances are normalized by l0, the typical distance between neighboring conspecific trees. Correlation function, cluster statistics and nearest-neighbor distance distribution become speciesindependent after this rescaling. Global observables (species frequencies) and local spatial structure appear to be interrelated. This "glocality" suggests a radical interpretation of recent experiments that show a correlation between species' abundance and the negative feedback among conspecifics. For the forest to be glocal, the negative feedback must govern spatial patterns over all scales.

Original languageEnglish
Article numbere0126117
JournalPLoS ONE
Volume10
Issue number5
DOIs
StatePublished - 1 May 2015

Bibliographical note

Publisher Copyright:
© 2015 Seri et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding

We thank David Kessler, Lewi Stone, Joe Wright and Richard Condit for helpful discussions and comments. This work was supported by numerous private individuals, and through the hard work of over 100 people from 10 countries over the past two decades. The plot project is part the Center for Tropical Forest Science, a global network of large-scale demographic tree plots.

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