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Landscape-scale concordance between local ecological knowledge for tropical wild species and remote sensing of land cover

Monitoring the status of species is crucial for biodiversity conservation and sustainable resource management in tropical forests, but conventional in situ monitoring methods are impractical over large scales. Scientists have resorted to two potentially complementary approaches: local ecological kno...

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Autores principales: Takasaki, Yoshito, Coomes, Oliver T., Abizaid, Christian, Kalacska, Margaret
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9546624/
https://www.ncbi.nlm.nih.gov/pubmed/36161957
http://dx.doi.org/10.1073/pnas.2116446119
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author Takasaki, Yoshito
Coomes, Oliver T.
Abizaid, Christian
Kalacska, Margaret
author_facet Takasaki, Yoshito
Coomes, Oliver T.
Abizaid, Christian
Kalacska, Margaret
author_sort Takasaki, Yoshito
collection PubMed
description Monitoring the status of species is crucial for biodiversity conservation and sustainable resource management in tropical forests, but conventional in situ monitoring methods are impractical over large scales. Scientists have resorted to two potentially complementary approaches: local ecological knowledge (LEK) and remote sensing. To gauge the potential of combining LEK and remote sensing for assessing species status at landscape scales, a large-scale assessment of the reliability of both measures is critical but hampered by the lack of ground-level data. We conducted a landscape-scale assessment of LEK and remote sensing, using a survey of over 900 communities (a near census in our study area) and nearly 4,000 households in 235 randomly selected communities in the Peruvian Amazon—the largest LEK survey as yet undertaken in tropical forests. The survey collected LEK data on the presence of 20 indicator species from both community leaders/elders and randomly sampled households. We assessed LEK and remotely sensed land cover—forest cover and nonmain channel open water—as proxies for species habitat, across species (game, fish, and timber), over time (current and historical), and by indigeneity (Indigenous peoples and mestizos). Overall, LEK and remotely sensed land cover corroborate each other well. Concordance is highest for the current status of game species reported by sampled households, as is the concordance of historical LEK from Indigenous community leaders/elders. The results point to the promise of combining LEK and remote sensing in monitoring the status of species in data-poor tropical forests.
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spelling pubmed-95466242023-03-26 Landscape-scale concordance between local ecological knowledge for tropical wild species and remote sensing of land cover Takasaki, Yoshito Coomes, Oliver T. Abizaid, Christian Kalacska, Margaret Proc Natl Acad Sci U S A Social Sciences Monitoring the status of species is crucial for biodiversity conservation and sustainable resource management in tropical forests, but conventional in situ monitoring methods are impractical over large scales. Scientists have resorted to two potentially complementary approaches: local ecological knowledge (LEK) and remote sensing. To gauge the potential of combining LEK and remote sensing for assessing species status at landscape scales, a large-scale assessment of the reliability of both measures is critical but hampered by the lack of ground-level data. We conducted a landscape-scale assessment of LEK and remote sensing, using a survey of over 900 communities (a near census in our study area) and nearly 4,000 households in 235 randomly selected communities in the Peruvian Amazon—the largest LEK survey as yet undertaken in tropical forests. The survey collected LEK data on the presence of 20 indicator species from both community leaders/elders and randomly sampled households. We assessed LEK and remotely sensed land cover—forest cover and nonmain channel open water—as proxies for species habitat, across species (game, fish, and timber), over time (current and historical), and by indigeneity (Indigenous peoples and mestizos). Overall, LEK and remotely sensed land cover corroborate each other well. Concordance is highest for the current status of game species reported by sampled households, as is the concordance of historical LEK from Indigenous community leaders/elders. The results point to the promise of combining LEK and remote sensing in monitoring the status of species in data-poor tropical forests. National Academy of Sciences 2022-09-26 2022-10-04 /pmc/articles/PMC9546624/ /pubmed/36161957 http://dx.doi.org/10.1073/pnas.2116446119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Social Sciences
Takasaki, Yoshito
Coomes, Oliver T.
Abizaid, Christian
Kalacska, Margaret
Landscape-scale concordance between local ecological knowledge for tropical wild species and remote sensing of land cover
title Landscape-scale concordance between local ecological knowledge for tropical wild species and remote sensing of land cover
title_full Landscape-scale concordance between local ecological knowledge for tropical wild species and remote sensing of land cover
title_fullStr Landscape-scale concordance between local ecological knowledge for tropical wild species and remote sensing of land cover
title_full_unstemmed Landscape-scale concordance between local ecological knowledge for tropical wild species and remote sensing of land cover
title_short Landscape-scale concordance between local ecological knowledge for tropical wild species and remote sensing of land cover
title_sort landscape-scale concordance between local ecological knowledge for tropical wild species and remote sensing of land cover
topic Social Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9546624/
https://www.ncbi.nlm.nih.gov/pubmed/36161957
http://dx.doi.org/10.1073/pnas.2116446119
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