Global tropical dry forest extent and cover: A comparative study of bioclimatic definitions using two climatic data sets
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, co...
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| description | 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. |
| doi_str_mv | 10.1371/journal.pone.0252063 |
| format | Article |
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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.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0252063</identifier><identifier>PMID: 34015004</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Africa ; Agriculture ; Animal behavior ; Bioclimatology ; Biodiversity and Ecology ; Biology and Life Sciences ; Biometeorology ; Canopies ; Climate change ; Climatic data ; Comparative analysis ; Comparative studies ; Coniferous forests ; Conservation ; Conservation status ; Datasets ; Deciduous forests ; Deforestation ; Drought ; Dry forests ; Earth Sciences ; Ecology and Environmental Sciences ; Ecology, environment ; Ecosystem ; Endangered species ; Environmental aspects ; Environmental Sciences ; Forest vegetation ; Forests ; Grasslands ; Humans ; Ibanez, Thomas ; Life Sciences ; Old growth ; People and Places ; Protected areas ; Protected species ; Savannahs ; Trees - growth & development ; Tropical Climate ; Tropical dry forests ; Tropical forests ; Vegetation ; Vegetation cover ; Vegetation type ; Wildlife conservation ; Woodlands</subject><ispartof>PloS one, 2021-05, Vol.16 (5), p.e0252063</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Ocón et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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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. 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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.</description><subject>Africa</subject><subject>Agriculture</subject><subject>Animal behavior</subject><subject>Bioclimatology</subject><subject>Biodiversity and Ecology</subject><subject>Biology and Life Sciences</subject><subject>Biometeorology</subject><subject>Canopies</subject><subject>Climate change</subject><subject>Climatic data</subject><subject>Comparative analysis</subject><subject>Comparative studies</subject><subject>Coniferous forests</subject><subject>Conservation</subject><subject>Conservation status</subject><subject>Datasets</subject><subject>Deciduous forests</subject><subject>Deforestation</subject><subject>Drought</subject><subject>Dry forests</subject><subject>Earth Sciences</subject><subject>Ecology and Environmental Sciences</subject><subject>Ecology, 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tropical dry forest extent and cover: A comparative study of bioclimatic definitions using two climatic data sets</title><author>Ocón, Jonathan Pando ; Ibanez, Thomas ; Franklin, Janet ; Pau, Stephanie ; Keppel, Gunnar ; Rivas-Torres, Gonzalo ; Shin, Michael Edward ; Gillespie, Thomas Welch</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c726t-3ec582f8e25a1e139d0df570b684c522e722cbea3b7ea7129f9e0830af418e8d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Africa</topic><topic>Agriculture</topic><topic>Animal behavior</topic><topic>Bioclimatology</topic><topic>Biodiversity and Ecology</topic><topic>Biology and Life Sciences</topic><topic>Biometeorology</topic><topic>Canopies</topic><topic>Climate change</topic><topic>Climatic data</topic><topic>Comparative analysis</topic><topic>Comparative studies</topic><topic>Coniferous 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Ligne (HAL) (Open Access)</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ocón, Jonathan Pando</au><au>Ibanez, Thomas</au><au>Franklin, Janet</au><au>Pau, Stephanie</au><au>Keppel, Gunnar</au><au>Rivas-Torres, Gonzalo</au><au>Shin, Michael Edward</au><au>Gillespie, Thomas Welch</au><au>Zang, RunGuo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Global tropical dry forest extent and cover: A comparative study of bioclimatic definitions using two climatic data sets</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-05-20</date><risdate>2021</risdate><volume>16</volume><issue>5</issue><spage>e0252063</spage><pages>e0252063-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>34015004</pmid><doi>10.1371/journal.pone.0252063</doi><tpages>e0252063</tpages><orcidid>https://orcid.org/0000-0002-3899-9062</orcidid><orcidid>https://orcid.org/0000-0002-3192-1721</orcidid><orcidid>https://orcid.org/0000-0003-0314-4598</orcidid><orcidid>https://orcid.org/0000-0002-2704-8288</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2021-05, Vol.16 (5), p.e0252063 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2529909720 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Africa Agriculture Animal behavior Bioclimatology Biodiversity and Ecology Biology and Life Sciences Biometeorology Canopies Climate change Climatic data Comparative analysis Comparative studies Coniferous forests Conservation Conservation status Datasets Deciduous forests Deforestation Drought Dry forests Earth Sciences Ecology and Environmental Sciences Ecology, environment Ecosystem Endangered species Environmental aspects Environmental Sciences Forest vegetation Forests Grasslands Humans Ibanez, Thomas Life Sciences Old growth People and Places Protected areas Protected species Savannahs Trees - growth & development Tropical Climate Tropical dry forests Tropical forests Vegetation Vegetation cover Vegetation type Wildlife conservation Woodlands |
| title | Global tropical dry forest extent and cover: A comparative study of bioclimatic definitions using two climatic data sets |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-19T14%3A45%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Global%20tropical%20dry%20forest%20extent%20and%20cover:%20A%20comparative%20study%20of%20bioclimatic%20definitions%20using%20two%20climatic%20data%20sets&rft.jtitle=PloS%20one&rft.au=Oc%C3%B3n,%20Jonathan%20Pando&rft.date=2021-05-20&rft.volume=16&rft.issue=5&rft.spage=e0252063&rft.pages=e0252063-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0252063&rft_dat=%3Cgale_plos_%3EA662418873%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2529909720&rft_id=info:pmid/34015004&rft_galeid=A662418873&rft_doaj_id=oai_doaj_org_article_83d98b1c0bc84beba9319de89dacb44d&rfr_iscdi=true |