Evidence map›Paper›PMID 33614102›Full record

ArticleRoyal Society open science2021

Joint assessment of density correlations and fluctuations for analysing spatial tree patterns.

P Villegas, A Cavagna, M Cencini, H Fort, T S Grigera

Abstract read
In one paragraph

Article in Royal Society open science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

P VillegasIstituto dei Sistemi Complessi, Consiglio Nazionale delle Ricerche, via dei Taurini 19 00185 Rome, Italy.ORCID 0000-0002-1627-3754
A CavagnaIstituto dei Sistemi Complessi, Consiglio Nazionale delle Ricerche, via dei Taurini 19 00185 Rome, Italy.
M CenciniIstituto dei Sistemi Complessi, Consiglio Nazionale delle Ricerche, via dei Taurini 19 00185 Rome, Italy.ORCID 0000-0001-7073-5000
H FortInstitute of Physics, Faculty of Science, Universidad de la República, Iguá 4225, Montevideo 11400, Uruguay.ORCID 0000-0001-7899-7507
T S GrigeraIstituto dei Sistemi Complessi, Consiglio Nazionale delle Ricerche, via dei Taurini 19 00185 Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Barro coloradoneutral modeltheoretical ecology

Identifiers

PMID33614102
PMCPMC7890483

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.