Discovering floristic and geoecological gradients across Amazonia

Aim: To map and interpret floristic and geoecological patterns across the Amazon basin by combining extensive field data with basin-wide Landsat imagery and climatic data Location: Amazonia Taxon: Ground truth data on ferns and lycophytes; remote sensing results reflect forest canopy properties Meth...

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Autor Principal: Tuomisto, H. (author)
Outros autores: Van doninck, J. (author), Ruokolainen, K. (author), Massaine Moulatlet, Gabriel (author), Figueiredo, FOG (author), Sirén, A (author), Cárdenas, G (author), Lehtonen, S (author), Zuquim, G (author)
Formato: article
Publicado: 2019
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Acceso en liña:http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/281
https://doi.org/10.1111/jbi.13627
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author Tuomisto, H.
author2 Van doninck, J.
Ruokolainen, K.
Massaine Moulatlet, Gabriel
Figueiredo, FOG
Sirén, A
Cárdenas, G
Lehtonen, S
Zuquim, G
author2_role author
author
author
author
author
author
author
author
author_facet Tuomisto, H.
Van doninck, J.
Ruokolainen, K.
Massaine Moulatlet, Gabriel
Figueiredo, FOG
Sirén, A
Cárdenas, G
Lehtonen, S
Zuquim, G
author_role author
collection Repositorio Universidad Regional Amazónica
dc.creator.none.fl_str_mv Tuomisto, H.
Van doninck, J.
Ruokolainen, K.
Massaine Moulatlet, Gabriel
Figueiredo, FOG
Sirén, A
Cárdenas, G
Lehtonen, S
Zuquim, G
dc.date.none.fl_str_mv 2019-07-02T15:10:01Z
2019-07-02T15:10:01Z
2019
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv Tuomisto H, Van doninck J, Ruokolainen K, Moulatlet GM, Figueiredo FOG, Sirén A, Cárdenas G, Lehtonen S, Zuquim G (2019) Discovering floristic and geoecological gradients across Amazonia. Journal of Biogeography. https://doi.org/10.1111/jbi.13627
http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/281
https://doi.org/10.1111/jbi.13627
dc.language.none.fl_str_mv en
dc.relation.none.fl_str_mv PRODUCCIÓN CIENTÍFICA-ARTÍCULOS;A-IKIAM-000188
dc.rights.none.fl_str_mv Atribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América
http://creativecommons.org/licenses/by-nc-nd/3.0/us/
info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:Repositorio Universidad Regional Amazónica
instname:Universidad Regional Amazónica
instacron:IKIAM
dc.subject.none.fl_str_mv Amazonia
Remote sensing
Medium resolution multispectral imagery
Biogeographical regions
vegetation
Landsat
Geoecological regions
Floristic gradients
dc.title.none.fl_str_mv Discovering floristic and geoecological gradients across Amazonia
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Aim: To map and interpret floristic and geoecological patterns across the Amazon basin by combining extensive field data with basin-wide Landsat imagery and climatic data Location: Amazonia Taxon: Ground truth data on ferns and lycophytes; remote sensing results reflect forest canopy properties Methods: We used field plot data to assess main ecological gradients across Amazonia and to relate floristic ordination axes to soil base cation concentration, CHELSA climatic variables and reflectance values from a basin-wide Landsat image composite with generalized linear models (GLM). Ordination axes were then predicted across all Amazonia using Landsat and CHELSA, and a regional subdivision was obtained using k-medoid classification. Results: The primary floristic gradient was strongly related to base cation concentration in the soil, and the secondary gradient to climatic variables. The Landsat image composite revealed a tapestry of broad-scale variation in canopy reflectance characteristics across Amazonia. Ordination axis scores predicted using Landsat and CHELSA variables produced spatial patterns consistent with existing knowledge on soils, geology and vegetation, but also suggested new floristic patterns. The clearest dichotomy was between central Amazonia and the peripheral areas, and the available data supported a classification into at least eight subregions. Main conclusions Landsat data are capable of predicting soil-related species compositional patterns of understory ferns and lycophytes across the Amazon basin with surprisingly high accuracy. Although the exact floristic relationships may differ among plant groups, the observed ecological gradients must be relevant for other plants as well, since surface reflectance recorded by satellites is mostly influenced by the tree canopy. This opens exciting prospects for species distribution modelling, conservation planning, and biogeographical and ecological studies on Amazonian biota. Our maps provide a preliminary geoecological subdivision of Amazonia that can now be tested and refined using field data of other plant groups and from hitherto unsampled areas.
eu_rights_str_mv openAccess
format article
id IKIAM_7ba47eae7f916eb06be9d74cc28fc6d6
identifier_str_mv Tuomisto H, Van doninck J, Ruokolainen K, Moulatlet GM, Figueiredo FOG, Sirén A, Cárdenas G, Lehtonen S, Zuquim G (2019) Discovering floristic and geoecological gradients across Amazonia. Journal of Biogeography. https://doi.org/10.1111/jbi.13627
instacron_str IKIAM
institution IKIAM
instname_str Universidad Regional Amazónica
language_invalid_str_mv en
network_acronym_str IKIAM
network_name_str Repositorio Universidad Regional Amazónica
oai_identifier_str oai:repositorio.ikiam.edu.ec:RD_IKIAM/281
publishDate 2019
reponame_str Repositorio Universidad Regional Amazónica
repository.mail.fl_str_mv .
repository.name.fl_str_mv Repositorio Universidad Regional Amazónica - Universidad Regional Amazónica
repository_id_str 0
rights_invalid_str_mv Atribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América
http://creativecommons.org/licenses/by-nc-nd/3.0/us/
spelling Discovering floristic and geoecological gradients across AmazoniaTuomisto, H.Van doninck, J.Ruokolainen, K.Massaine Moulatlet, GabrielFigueiredo, FOGSirén, ACárdenas, GLehtonen, SZuquim, GAmazoniaRemote sensingMedium resolution multispectral imageryBiogeographical regionsvegetationLandsatGeoecological regionsFloristic gradientsAim: To map and interpret floristic and geoecological patterns across the Amazon basin by combining extensive field data with basin-wide Landsat imagery and climatic data Location: Amazonia Taxon: Ground truth data on ferns and lycophytes; remote sensing results reflect forest canopy properties Methods: We used field plot data to assess main ecological gradients across Amazonia and to relate floristic ordination axes to soil base cation concentration, CHELSA climatic variables and reflectance values from a basin-wide Landsat image composite with generalized linear models (GLM). Ordination axes were then predicted across all Amazonia using Landsat and CHELSA, and a regional subdivision was obtained using k-medoid classification. Results: The primary floristic gradient was strongly related to base cation concentration in the soil, and the secondary gradient to climatic variables. The Landsat image composite revealed a tapestry of broad-scale variation in canopy reflectance characteristics across Amazonia. Ordination axis scores predicted using Landsat and CHELSA variables produced spatial patterns consistent with existing knowledge on soils, geology and vegetation, but also suggested new floristic patterns. The clearest dichotomy was between central Amazonia and the peripheral areas, and the available data supported a classification into at least eight subregions. Main conclusions Landsat data are capable of predicting soil-related species compositional patterns of understory ferns and lycophytes across the Amazon basin with surprisingly high accuracy. Although the exact floristic relationships may differ among plant groups, the observed ecological gradients must be relevant for other plants as well, since surface reflectance recorded by satellites is mostly influenced by the tree canopy. This opens exciting prospects for species distribution modelling, conservation planning, and biogeographical and ecological studies on Amazonian biota. Our maps provide a preliminary geoecological subdivision of Amazonia that can now be tested and refined using field data of other plant groups and from hitherto unsampled areas.2019-07-02T15:10:01Z2019-07-02T15:10:01Z2019info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfTuomisto H, Van doninck J, Ruokolainen K, Moulatlet GM, Figueiredo FOG, Sirén A, Cárdenas G, Lehtonen S, Zuquim G (2019) Discovering floristic and geoecological gradients across Amazonia. Journal of Biogeography. https://doi.org/10.1111/jbi.13627http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/281https://doi.org/10.1111/jbi.13627enPRODUCCIÓN CIENTÍFICA-ARTÍCULOS;A-IKIAM-000188Atribución-NoComercial-SinDerivadas 3.0 Estados Unidos de Américahttp://creativecommons.org/licenses/by-nc-nd/3.0/us/info:eu-repo/semantics/openAccessreponame:Repositorio Universidad Regional Amazónicainstname:Universidad Regional Amazónicainstacron:IKIAM2023-04-14T08:00:16Zoai:repositorio.ikiam.edu.ec:RD_IKIAM/281Institucionalhttps://repositorio.ikiam.edu.ec/Universidad públicahttps://www.ikiam.edu.ec/https://repositorio.ikiam.edu.ec/oaiEcuador...opendoar:02023-04-14T08:00:16falseInstitucionalhttps://repositorio.ikiam.edu.ec/Universidad públicahttps://www.ikiam.edu.ec/https://repositorio.ikiam.edu.ec/oai.Ecuador...opendoar:02023-04-14T08:00:16Repositorio Universidad Regional Amazónica - Universidad Regional Amazónicafalse
spellingShingle Discovering floristic and geoecological gradients across Amazonia
Tuomisto, H.
Amazonia
Remote sensing
Medium resolution multispectral imagery
Biogeographical regions
vegetation
Landsat
Geoecological regions
Floristic gradients
status_str publishedVersion
title Discovering floristic and geoecological gradients across Amazonia
title_full Discovering floristic and geoecological gradients across Amazonia
title_fullStr Discovering floristic and geoecological gradients across Amazonia
title_full_unstemmed Discovering floristic and geoecological gradients across Amazonia
title_short Discovering floristic and geoecological gradients across Amazonia
title_sort Discovering floristic and geoecological gradients across Amazonia
topic Amazonia
Remote sensing
Medium resolution multispectral imagery
Biogeographical regions
vegetation
Landsat
Geoecological regions
Floristic gradients
url http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/281
https://doi.org/10.1111/jbi.13627