Revealing floristic variation and map uncertainties for different plant groups in western Amazonia
Questions Understanding spatial variation in floristic composition is crucial to quantify the extent, patchiness and connectivity of distinct habitats and their spatial relationships. Broad-scale variation in floristic composition and the degree of uniqueness of different regions remains poorly mapp...
Uloženo v:
Hlavní autor: | |
---|---|
Další autoři: | , , , , , , |
Médium: | article |
Vydáno: |
2021
|
Témata: | |
On-line přístup: | http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/524 |
Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
_version_ | 1840678923367612416 |
---|---|
author | Zuquim, Gabriela |
author2 | Tuomisto, Hanna Thaise, Emilio Perez, Pablo Ruokolainen, Kalle Massaine Moulatlet, Gabriel Van doninck, Jasper Balslev, Henrik |
author2_role | author author author author author author author |
author_facet | Zuquim, Gabriela Tuomisto, Hanna Thaise, Emilio Perez, Pablo Ruokolainen, Kalle Massaine Moulatlet, Gabriel Van doninck, Jasper Balslev, Henrik |
author_role | author |
collection | Repositorio Universidad Regional Amazónica |
dc.creator.none.fl_str_mv | Zuquim, Gabriela Tuomisto, Hanna Thaise, Emilio Perez, Pablo Ruokolainen, Kalle Massaine Moulatlet, Gabriel Van doninck, Jasper Balslev, Henrik |
dc.date.none.fl_str_mv | 2021 2022-05-10T18:01:37Z 2022-05-10T18:01:37Z |
dc.format.none.fl_str_mv | application/pdf |
dc.identifier.none.fl_str_mv | Zuquim, Gabriela & Tuomisto, Hanna & Perez, Pablo & Emilio, Thaise & Moulatlet, G. & Ruokolainen, Kalle & Van doninck, Jasper & Balslev, Henrik. (2021). Revealing floristic variation and map uncertainties for different plant groups in western Amazonia. Journal of Vegetation Science. 32. 10.1111/jvs.13081. DOI:10.1111/jvs.13081 http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/524 |
dc.language.none.fl_str_mv | en |
dc.publisher.none.fl_str_mv | Scopus |
dc.relation.none.fl_str_mv | PRODUCIÓN CIENTIFICA- ARTÍCULOS CIENTÍFICOS;A-IKIAM-000290 |
dc.rights.none.fl_str_mv | 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 | Plant community Área of applicability Remote sensing Vegetation mapping, Tropical forests, Species-environmental relationships Niche, Juruá river, Machine learning Amazonian biogeography Ferns Palms Melastomataceae Zingiberales |
dc.title.none.fl_str_mv | Revealing floristic variation and map uncertainties for different plant groups in western Amazonia |
dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
description | Questions Understanding spatial variation in floristic composition is crucial to quantify the extent, patchiness and connectivity of distinct habitats and their spatial relationships. Broad-scale variation in floristic composition and the degree of uniqueness of different regions remains poorly mapped and understood in several areas across the globe. We here aim to map vegetation heterogeneity in Amazonia. Location Middle Juruá river region, Amazonas State, Brazil. Methods We mapped four plant groups by applying machine learning to scale-up locally observed community composition and using environmental and remote sensed variables as predictors, which were obtained as GIS-layers. To quantify how reliable our predictions were, we made an assessment of model transferability and spatial applicability. We also compared our floristic composition map to the official Brazilian national-level vegetation classification. Results The overall performance of our floristic models was high for all four plant groups, especially ferns, and the predictions were found to be spatially congruent and highly transferable in space. For some areas, the models were assessed not to be applicable, as the field sampling did not cover the spectral or environmental characteristics of those regions. Our maps show extensive habitat heterogeneity across the region. When compared to the Brazilian vegetation classification, floristic composition was relatively homogeneous within dense forests, while floristic heterogeneity in rainforests classified as open was high. Conclusion Our maps provide geoecological characterization of the regions and can be used to test biogeographical hypotheses, develop species distribution models and, ultimately, aid science-based conservation and land-use planning. |
eu_rights_str_mv | openAccess |
format | article |
id | IKIAM_814f2f0608b7dfb15aaa24dc3b4f6f15 |
identifier_str_mv | Zuquim, Gabriela & Tuomisto, Hanna & Perez, Pablo & Emilio, Thaise & Moulatlet, G. & Ruokolainen, Kalle & Van doninck, Jasper & Balslev, Henrik. (2021). Revealing floristic variation and map uncertainties for different plant groups in western Amazonia. Journal of Vegetation Science. 32. 10.1111/jvs.13081. DOI:10.1111/jvs.13081 |
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/524 |
publishDate | 2021 |
publisher.none.fl_str_mv | Scopus |
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 |
spelling | Revealing floristic variation and map uncertainties for different plant groups in western AmazoniaZuquim, GabrielaTuomisto, HannaThaise, EmilioPerez, PabloRuokolainen, KalleMassaine Moulatlet, GabrielVan doninck, JasperBalslev, HenrikPlant communityÁrea of applicabilityRemote sensingVegetation mapping,Tropical forests,Species-environmental relationshipsNiche,Juruá river,Machine learningAmazonian biogeographyFernsPalmsMelastomataceaeZingiberalesQuestions Understanding spatial variation in floristic composition is crucial to quantify the extent, patchiness and connectivity of distinct habitats and their spatial relationships. Broad-scale variation in floristic composition and the degree of uniqueness of different regions remains poorly mapped and understood in several areas across the globe. We here aim to map vegetation heterogeneity in Amazonia. Location Middle Juruá river region, Amazonas State, Brazil. Methods We mapped four plant groups by applying machine learning to scale-up locally observed community composition and using environmental and remote sensed variables as predictors, which were obtained as GIS-layers. To quantify how reliable our predictions were, we made an assessment of model transferability and spatial applicability. We also compared our floristic composition map to the official Brazilian national-level vegetation classification. Results The overall performance of our floristic models was high for all four plant groups, especially ferns, and the predictions were found to be spatially congruent and highly transferable in space. For some areas, the models were assessed not to be applicable, as the field sampling did not cover the spectral or environmental characteristics of those regions. Our maps show extensive habitat heterogeneity across the region. When compared to the Brazilian vegetation classification, floristic composition was relatively homogeneous within dense forests, while floristic heterogeneity in rainforests classified as open was high. Conclusion Our maps provide geoecological characterization of the regions and can be used to test biogeographical hypotheses, develop species distribution models and, ultimately, aid science-based conservation and land-use planning.Scopus2022-05-10T18:01:37Z2022-05-10T18:01:37Z2021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfZuquim, Gabriela & Tuomisto, Hanna & Perez, Pablo & Emilio, Thaise & Moulatlet, G. & Ruokolainen, Kalle & Van doninck, Jasper & Balslev, Henrik. (2021). Revealing floristic variation and map uncertainties for different plant groups in western Amazonia. Journal of Vegetation Science. 32. 10.1111/jvs.13081.DOI:10.1111/jvs.13081http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/524enPRODUCIÓN CIENTIFICA- ARTÍCULOS CIENTÍFICOS;A-IKIAM-000290info:eu-repo/semantics/openAccessreponame:Repositorio Universidad Regional Amazónicainstname:Universidad Regional Amazónicainstacron:IKIAM2023-04-19T08:00:18Zoai:repositorio.ikiam.edu.ec:RD_IKIAM/524Institucionalhttps://repositorio.ikiam.edu.ec/Universidad públicahttps://www.ikiam.edu.ec/https://repositorio.ikiam.edu.ec/oaiEcuador...opendoar:02023-04-19T08:00:18falseInstitucionalhttps://repositorio.ikiam.edu.ec/Universidad públicahttps://www.ikiam.edu.ec/https://repositorio.ikiam.edu.ec/oai.Ecuador...opendoar:02023-04-19T08:00:18Repositorio Universidad Regional Amazónica - Universidad Regional Amazónicafalse |
spellingShingle | Revealing floristic variation and map uncertainties for different plant groups in western Amazonia Zuquim, Gabriela Plant community Área of applicability Remote sensing Vegetation mapping, Tropical forests, Species-environmental relationships Niche, Juruá river, Machine learning Amazonian biogeography Ferns Palms Melastomataceae Zingiberales |
status_str | publishedVersion |
title | Revealing floristic variation and map uncertainties for different plant groups in western Amazonia |
title_full | Revealing floristic variation and map uncertainties for different plant groups in western Amazonia |
title_fullStr | Revealing floristic variation and map uncertainties for different plant groups in western Amazonia |
title_full_unstemmed | Revealing floristic variation and map uncertainties for different plant groups in western Amazonia |
title_short | Revealing floristic variation and map uncertainties for different plant groups in western Amazonia |
title_sort | Revealing floristic variation and map uncertainties for different plant groups in western Amazonia |
topic | Plant community Área of applicability Remote sensing Vegetation mapping, Tropical forests, Species-environmental relationships Niche, Juruá river, Machine learning Amazonian biogeography Ferns Palms Melastomataceae Zingiberales |
url | http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/524 |