Evidence map›Paper›PMID 40794745›Full record

ArticlePloS one2025

Capturing temporal heterogeneity of communities: A temporal β-diversity based on Hill numbers and time series analysis.

Daniel J Sánchez-Ochoa, Edgar J González, María Del Coro Arizmendi, Patricia Koleff, Raúl Martell-Dubois, Jorge A Meave, Hibraim A Pérez-Mendoza

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Daniel J Sánchez-OchoaLaboratorio de Ecología Evolutiva y Conservación de Anfibios y Reptiles, Facultad de Estudios Superiores Iztacala, Universidad Autónoma de México, Los Reyes Iztacala, Tlalnepantla, Mexico.
Edgar J GonzálezDepartamento de Ecología y Recursos Naturales, Facultad de Ciencias, Universidad Nacional Autónoma de México, Coyoacán, Mexico City, Mexico.
María Del Coro ArizmendiLaboratorio de Ecología, UBIPRO, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla de Baz, Mexico.
Patricia KoleffComisión Nacional para el Conocimiento y Uso de la Biodiversidad, Tlalpan, Mexico City, Mexico.
Raúl Martell-DuboisComisión Nacional para el Conocimiento y Uso de la Biodiversidad, Tlalpan, Mexico City, Mexico.ORCID 0000-0002-7131-7844
Jorge A MeaveDepartamento de Ecología y Recursos Naturales, Facultad de Ciencias, Universidad Nacional Autónoma de México, Coyoacán, Mexico City, Mexico.ORCID 0000-0002-6241-8803
Hibraim A Pérez-MendozaLaboratorio de Ecología Evolutiva y Conservación de Anfibios y Reptiles, Facultad de Estudios Superiores Iztacala, Universidad Autónoma de México, Los Reyes Iztacala, Tlalnepantla, Mexico.ORCID 0000-0003-1073-9362

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Beta-diversity is a term used to refer to the heterogeneity in the composition of species through space or time. Despite a consensus on the advantages of measuring β-diversity using data on species abundances through Hill numbers, we still lack a measure of temporal β-diversity based on this framework. In this paper, we present the mathematical basis for a temporal β-diversity measure, based on both signal processing and Hill numbers theory through the partition of temporal ƴ-diversity. The proposed measure was tested in four hypothetical simulated communities with species varying in temporal concurrence and abundance and two empirical data sets. The values of each simulation reflected community heterogeneity and changes in abundance over time. In terms of ƴ-diversity, q-values are closely related to total richness (S) and show a negative exponential pattern when they increase. For α-diversity, q-value profiles were more variable than ƴ-diversity, and different decaying patterns in α-diversity can be observed among simulations. Temporal β-diversity shows different patterns, which are principally related to the rate of change between ƴ- and α-diversity. Our framework provides a direct and objective approach for comparing the heterogeneity of temporal community patterns; this measure can be interpreted as the effective number of completely different unique communities over the sampling period indicating either a larger variety of community structures or higher species heterogeneity through time. This method can be applied to any ecological community that has been monitored over time.

Indexed as

BiodiversityEcosystemComputer SimulationTime Factors

Identifiers

PMID40794745
PMCPMC12342289

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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.