Trabalho Apresentado em Evento

Deforestation control in Mato Grosso: A new model for slowing the loss of Amazonian forest

Autor principal: Fearnside, Philip Martin
Grau: Trabalho Apresentado em Evento
Publicado em: Brasil 2020
Assuntos:
Causas de Desmatamento
Desmatamento
Acesso em linha: https://repositorio.inpa.gov.br/handle/1/31064
id oai:repositorio:1-31064
recordtype dspace
spelling oai:repositorio:1-31064 Deforestation control in Mato Grosso: A new model for slowing the loss of Amazonian forest Fearnside, Philip Martin Causas de Desmatamento Desmatamento 2020-07-20T13:58:04Z 2020-07-20T13:58:04Z 2002 Trabalho Apresentado em Evento https://repositorio.inpa.gov.br/handle/1/31064 Segunda Conferência Científica Internacional do LBA Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ Brasil Segunda Conferência Científica Internacional do LBA
institution Instituto Nacional de Pesquisas da Amazônia - Repositório Institucional
collection INPA-RI
topic Causas de Desmatamento
Desmatamento
spellingShingle Causas de Desmatamento
Desmatamento
Fearnside, Philip Martin
Deforestation control in Mato Grosso: A new model for slowing the loss of Amazonian forest
topic_facet Causas de Desmatamento
Desmatamento
format Trabalho Apresentado em Evento
author Fearnside, Philip Martin
title Deforestation control in Mato Grosso: A new model for slowing the loss of Amazonian forest
title_short Deforestation control in Mato Grosso: A new model for slowing the loss of Amazonian forest
title_full Deforestation control in Mato Grosso: A new model for slowing the loss of Amazonian forest
title_fullStr Deforestation control in Mato Grosso: A new model for slowing the loss of Amazonian forest
title_full_unstemmed Deforestation control in Mato Grosso: A new model for slowing the loss of Amazonian forest
title_sort deforestation control in mato grosso: a new model for slowing the loss of amazonian forest
publisher Brasil
publishDate 2020
url https://repositorio.inpa.gov.br/handle/1/31064
_version_ 1787142027001987072
score 11.755432

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