Evidence map›Paper›PMID 34015004›Full record

ArticlePloS one2021

Global tropical dry forest extent and cover: A comparative study of bioclimatic definitions using two climatic data sets.

Jonathan Pando Ocón, Thomas Ibanez, Janet Franklin, Stephanie Pau, Gunnar Keppel, Gonzalo Rivas-Torres, Michael Edward Shin, Thomas Welch Gillespie

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Diversity and distribution of acrobat ants,Biodiversity data journal · 2026
    Article
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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

8 authors.

Jonathan Pando OcónDepartment of Geography, University of California Los Angeles, Los Angeles, CA, United States of America.ORCID 0000-0002-3899-9062
Thomas IbanezAMAP, CIRAD, CNRS, INRAE, IRD, Univ Montpellier, Montpellier, France.ORCID 0000-0002-3192-1721
Janet FranklinDepartment of Botany and Plant Sciences, University of California Riverside, Riverside, CA, United States of America.ORCID 0000-0003-0314-4598
Stephanie PauDepartment of Geography, Florida State University, Tallahassee, FL, United States of America.
Gunnar KeppelUniSA STEM and Future Industries Institute, University of South Australia, Adelaide, Australia.
Gonzalo Rivas-TorresColegio de Ciencias Biológicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador.
Michael Edward ShinDepartment of Geography, University of California Los Angeles, Los Angeles, CA, United States of America.
Thomas Welch GillespieDepartment of Geography, University of California Los Angeles, Los Angeles, CA, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a debate concerning the definition and extent of tropical dry forest biome and vegetation type at a global spatial scale. We identify the potential extent of the tropical dry forest biome based on bioclimatic definitions and climatic data sets to improve global estimates of distribution, cover, and change. We compared four bioclimatic definitions of the tropical dry forest biome-Murphy and Lugo, Food and Agriculture Organization (FAO), DryFlor, aridity index-using two climatic data sets: WorldClim and Climatologies at High-resolution for the Earth's Land Surface Areas (CHELSA). We then compared each of the eight unique combinations of bioclimatic definitions and climatic data sets using 540 field plots identified as tropical dry forest from a literature search and evaluated the accuracy of World Wildlife Fund tropical and subtropical dry broadleaf forest ecoregions. We used the definition and climate data that most closely matched field data to calculate forest cover in 2000 and change from 2001 to 2020. Globally, there was low agreement (< 58%) between bioclimatic definitions and WWF ecoregions and only 40% of field plots fell within these ecoregions. FAO using CHELSA had the highest agreement with field plots (81%) and was not correlated with the biome extent. Using the FAO definition with CHELSA climatic data set, we estimate 4,931,414 km2 of closed canopy (≥ 40% forest cover) tropical dry forest in 2000 and 4,369,695 km2 in 2020 with a gross loss of 561,719 km2 (11.4%) from 2001 to 2020. Tropical dry forest biome extent varies significantly based on bioclimatic definition used, with nearly half of all tropical dry forest vegetation missed when using ecoregion boundaries alone, especially in Africa. Using site-specific field validation, we find that the FAO definition using CHELSA provides an accurate, standard, and repeatable way to assess tropical dry forest cover and change at a global scale.

Indexed as

AgricultureEcosystemForestsTropical ClimateAfricaHumansTrees

Identifiers

PMID34015004
PMCPMC8136719

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.