Artigo

Ethnobotanical ground-truthing: Indigenous knowledge, floristic inventories and satellite imagery in the upper Rio Negro, Brazil

Aim: To assess the utility of indigenous habitat knowledge in studies of habitat diversity in Amazonia. Location: Baniwa indigenous communities in Rio Içana, upper Rio Negro, Brazil. Methods: Six campinarana vegetation types, recognized and named by a consensus of Baniwa indigenous informants accord...

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Autor principal: Abraão, Marcia Barbosa
Outros Autores: Nelson, Bruce Walker, Baniwa, João Cláudio, Yu, Douglas W., Shepard, Glenn Harvey
Grau: Artigo
Idioma: English
Publicado em: Journal of Biogeography 2020
Assuntos:
Gps
Habitat
Remote Sensing
Satellite Imagery
Vegetation
Rio Negro [south America]
South America
Acesso em linha: https://repositorio.inpa.gov.br/handle/1/18512
id oai:repositorio:1-18512
recordtype dspace
spelling oai:repositorio:1-18512 Ethnobotanical ground-truthing: Indigenous knowledge, floristic inventories and satellite imagery in the upper Rio Negro, Brazil Abraão, Marcia Barbosa Nelson, Bruce Walker Baniwa, João Cláudio Yu, Douglas W. Shepard, Glenn Harvey Gps Habitat Remote Sensing Satellite Imagery Vegetation Rio Negro [south America] South America Aim: To assess the utility of indigenous habitat knowledge in studies of habitat diversity in Amazonia. Location: Baniwa indigenous communities in Rio Içana, upper Rio Negro, Brazil. Methods: Six campinarana vegetation types, recognized and named by a consensus of Baniwa indigenous informants according to salient indicator species, were studied in 15 widely distributed plots. Floristic composition (using Baniwa plant nomenclature only, after frustrated attempts to obtain botanical collection permits), quantitative measures of forest structure and GPS waypoints of the 4-ha composite plot contours were registered, permitting their location on Landsat satellite images. Non-metric multidimensional scaling (NMDS) ordination was carried out using pc-ord software. Results: The NMDS ordinations of the plot data revealed a clear gradient of floristic composition that was highly correlated with three quantitative measures of forest structure: basal area, canopy height and satellite reflectance. Main conclusions: Baniwa-defined forest types are excellent predictors of habitat diversity along the structural gradient comprising distinctive white-sand campinarana vegetation types. Indigenous ecological knowledge, as revealed by satellite imagery and floristic analyses, proves to be a powerful and efficient shortcut to assessing habitat diversity, promoting dialogue between scientific and indigenous worldviews, and promoting joint study and conservation of biodiversity. © 2008 The Authors. 2020-06-15T22:02:00Z 2020-06-15T22:02:00Z 2008 Artigo https://repositorio.inpa.gov.br/handle/1/18512 10.1111/j.1365-2699.2008.01975.x en Volume 35, Número 12, Pags. 2237-2248 Restrito Journal of Biogeography
institution Instituto Nacional de Pesquisas da Amazônia - Repositório Institucional
collection INPA-RI
language English
topic Gps
Habitat
Remote Sensing
Satellite Imagery
Vegetation
Rio Negro [south America]
South America
spellingShingle Gps
Habitat
Remote Sensing
Satellite Imagery
Vegetation
Rio Negro [south America]
South America
Abraão, Marcia Barbosa
Ethnobotanical ground-truthing: Indigenous knowledge, floristic inventories and satellite imagery in the upper Rio Negro, Brazil
topic_facet Gps
Habitat
Remote Sensing
Satellite Imagery
Vegetation
Rio Negro [south America]
South America
description Aim: To assess the utility of indigenous habitat knowledge in studies of habitat diversity in Amazonia. Location: Baniwa indigenous communities in Rio Içana, upper Rio Negro, Brazil. Methods: Six campinarana vegetation types, recognized and named by a consensus of Baniwa indigenous informants according to salient indicator species, were studied in 15 widely distributed plots. Floristic composition (using Baniwa plant nomenclature only, after frustrated attempts to obtain botanical collection permits), quantitative measures of forest structure and GPS waypoints of the 4-ha composite plot contours were registered, permitting their location on Landsat satellite images. Non-metric multidimensional scaling (NMDS) ordination was carried out using pc-ord software. Results: The NMDS ordinations of the plot data revealed a clear gradient of floristic composition that was highly correlated with three quantitative measures of forest structure: basal area, canopy height and satellite reflectance. Main conclusions: Baniwa-defined forest types are excellent predictors of habitat diversity along the structural gradient comprising distinctive white-sand campinarana vegetation types. Indigenous ecological knowledge, as revealed by satellite imagery and floristic analyses, proves to be a powerful and efficient shortcut to assessing habitat diversity, promoting dialogue between scientific and indigenous worldviews, and promoting joint study and conservation of biodiversity. © 2008 The Authors.
format Artigo
author Abraão, Marcia Barbosa
author2 Nelson, Bruce Walker
Baniwa, João Cláudio
Yu, Douglas W.
Shepard, Glenn Harvey
author2Str Nelson, Bruce Walker
Baniwa, João Cláudio
Yu, Douglas W.
Shepard, Glenn Harvey
title Ethnobotanical ground-truthing: Indigenous knowledge, floristic inventories and satellite imagery in the upper Rio Negro, Brazil
title_short Ethnobotanical ground-truthing: Indigenous knowledge, floristic inventories and satellite imagery in the upper Rio Negro, Brazil
title_full Ethnobotanical ground-truthing: Indigenous knowledge, floristic inventories and satellite imagery in the upper Rio Negro, Brazil
title_fullStr Ethnobotanical ground-truthing: Indigenous knowledge, floristic inventories and satellite imagery in the upper Rio Negro, Brazil
title_full_unstemmed Ethnobotanical ground-truthing: Indigenous knowledge, floristic inventories and satellite imagery in the upper Rio Negro, Brazil
title_sort ethnobotanical ground-truthing: indigenous knowledge, floristic inventories and satellite imagery in the upper rio negro, brazil
publisher Journal of Biogeography
publishDate 2020
url https://repositorio.inpa.gov.br/handle/1/18512
_version_ 1787142770833489920
score 11.755432

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