24 research outputs found

    REALIDADE E DESAFIOS DA INSTITUCIONALIZAÇÃO DE UNIDADES DE CONSERVAÇÃO MUNICIPAIS DO ESTADO DO PARÁ, BRASIL

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    Esse texto versa sobre desafios da institucionalização de unidades de conservação municipais no estado do Pará, na Amazônia brasileira. Apresenta resultados de pesquisa que vem sendo desenvolvida com apoio da PROPESP/UFPA, cujo objetivo é analisar o grau de adequação das unidades de conservação municipais do estado do Pará à Lei do Sistema Nacional de Unidades de Conservação (SNUC). A maior parte das unidades de conservação municipais do Pará ainda não integra a base de dados oficiais do Brasil em matéria de unidades de conservação. A metodologia utilizada incluiu estudo da legislação pertinente, pesquisa junto a órgãos municipais e estadual de meio ambiente do Pará, entrevistas e acesso a arquivos documentais físicos. Os resultados preliminares apontam para o desconhecimento dos gestores públicos sobre os procedimentos relativos ao Cadastro Nacional de Unidades de Conservação (CNUC) e, sobretudo, sobre os benefícios e vantagens do registro das unidades de conservação no banco de dados oficiais do sistema SNUC. Os resultados indicam aindaque a maioria das unidades de conservação municipais do Pará foi criada antes da Lei federal 9.985/2000, o que implica em atos constitutivos formulados em desconsideração aos requisitos legais necessários à criação de unidades de conservação, estabelecidos pela lei em comento.Palavras-chave: Gestão pública municipal; Unidades de conservação; estado do Pará; Brasil.RÉALITÉ ET ENJEUX DE L’INSTITUTIONNALISATION DES AIRES PROTÉGÉESMUNICIPALES DANS L’ÉTAT DU PARÁ, BRÉSILRésuméCet article porte sur les enjeux de l’institutionnalisation des aires protégées municipales dans l’État du Pará, en Amazonie brésilienne. L’étude fait l’objet d’une recherche en cours d’élaboration avec l’appui dePROPESP/UFPA, visant à examiner dans quelle mesure les aires protégées municipales du Pará ont été établies selon les critères de la Loi du Système national des aires protégées (SNUC). La plupart des aires  protégées municipales du Pará ne font pas partie de la base de données officielle du Brésil sur les aires protégées. Le travail s’appuie sur l’examen de la législation pertinente, enquête auprès des organismes publics chargés de la protection de l’environnement, sur des interviews et des consultations de documents physiques. L’étude indique l’absence de connaissance par les agents publics quant aux procédures à suivre et des conditions à remplir en vue d’obtenir le registre national des aires protégées (CNUC) et, surtout, sur les avantages issus du registre des airesprotégées dans le système officiel. Les résultats indiquent également que la plupart des aires protégées municipales ont été créées avant la loi 9.985/2000, c’est-à-dire sans prise en compte des exigences établies par la loi fédérale au sujet de la création d’aires protégées.Mots-clés : Gestion municipale ; Aires protégées ; État du Pará ; Brésil

    Pacificação e tutela militar na gestão de populações e territórios

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    Pervasive gaps in Amazonian ecological research

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    Pervasive gaps in Amazonian ecological research

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    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

    Pervasive gaps in Amazonian ecological research

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    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
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