Florística, dinâmica e estrutura da regeneração natural em floresta explorada na flona do Tapajós-Pa

Largest area of tropical forest continues in the world, rich and highly diverse biome in plant and animal species, environment full of complex environmental relations and fragile balance, mosaic with varied topographical features and land use, synonymous with what might be called Amazon. From disparities, forest management has emerged as an alternative to the better use of forest resources, and thus the natural regeneration is one of the main mechanisms for maintaining the natural ecosystem and target planning for the future use of the forest, this being considering the current forest legislation. Thus, this study aimed to characterize the floristic composition, dynamics and structure of natural regeneration in a forest area explored in the TNF after 31 years of intervention. Natural regeneration was divided into three size classes and C1, C2 and C3, comprising individuals from 30 cm to 9.9 cm DBH. Being located the margins of BR-163 highway at km 67, Belterra municipality in the state of Pará, the study was based on the use of permanent plots of Embrapa Amazônia Oriental, where they were implements in 1981 (harvested area) and the witness in 2008, the two areas a total of 54 plots being arranged randomly and systematically. From 14.48 ha-1 effective sampling, found 14,628 plants divided into three size classes, these divided into 62 families and 370 species identified botany. The most abundant families were Fabaceae, Lauraceae and Sapotaceae, ordinary families in tropical forests, and at genus richest were Pouteria, Ocotea and Inga. For the structure, the category C3 species of greater VI were Protium apiculatum Swart (3.83%) and Virola michellii Heckel (3.83%), while for C2 were Rinorea guianensis Aubl. (6.31%) and Amphirrhox longifolia (A.St. Hil.) Spreng (5.90%). For Class C3 community mortality behaved with elevation and finally decreased their rates over the 31 years, for this flow C2 acabaou being characterized by several peaks. Assessing the populations of levelsignificance 0.05 C3 class does not havesignificant difference between treatments unlike the C2 class and the TE1 and TE2 differentthe TO.Maior área de floresta tropical contínua do mundo, bioma rico e altamente diverso em espécies vegetais e animais, ambiente cheio de relações ambientais complexas e de equilíbrio frágil, mosaico com variadas características topográficas e de uso da terra, sinônimos do que pode ser chamado de Amazônia. A partir das disparidades existentes, o manejo florestal surgiu como uma alternativa para a melhor utilização dos recursos florestais, e dessa forma a regeneração natural é um dos principais mecanismos de manutenção do ecossistema natural e alvo do planejamento para o uso futuro da floresta, estando contemplado na legislação florestal vigente. Dessa forma, este trabalho caracterizou a composição florística, dinâmica e a estrutura da regeneração natural em uma área de floresta explorada na FLONA do Tapajós, após 31 anos de intervenção. A regeneração natural foi dividida em três classes de tamanho sendo; C1, C2 e C3; compreendendo indivíduos desde 30 cm de altura até 9,9 cm de DAP. O estudo foi baseado no uso de parcelas permanentes da Embrapa Amazônia Oriental, localizadas as margens do km 67 da rodovia BR-163, município de Belterra (PA), onde estas foram implementadas no ano de 1981 (área explorada) e a testemunha, em 2008, tendo as duas áreas um total de 54 parcelas, dispostas de forma aleatória e sistemática. A partir de 14,48 ha-1 de amostragem efetiva, foi encontrado 14.628 plantas divididas nas três classes de tamanho, divididas em 62 famílias e 370 espécies botânica identificadas. As famílias mais abundantes foram Fabaceae, Lauraceae e Sapotaceae, sendo as quais comuns em florestas tropicais; e em nível de gênero Pouteria, Ocotea e Inga. Para a estrutura, na categoria C3, as espécies de maior VI foram Protium apiculatum Swart (3,83%) e Virola michelliiHeckel (3,83%), enquanto para as C2 foram, Rinorea guianensis Aubl. (6,31%) e Amphirrhox longifolia (A.St.-Hil.) Spreng (5,90%). Para a classe C3, a mortalidade da comunidade foi crescente, e por fim diminuiu suas taxas, com o passar dos 31 anos. Para C2, esse fluxo acabou sendo caracterizado por picos. A classe C3 não possui diferença significativa entre os tratamentos ao contrario da classe C2, sendo os TE1 e TE2 diferentes do TO, anível de significância de 0,05%

Capacidade produtiva de biomassa fresca em uma área de manejo florestal no oeste do Pará: Fresh biomass production capacity in a forest management area in the west of Pará

O setor florestal é um dos que mais gera renda no estado do Pará, principalmente pelo potencial produtivo da floresta Amazônica. Assim, o manejo florestal é uma ferramenta viável para a mitigação dos processos degradativos da exploração madeireira. A madeira é ligada ao termo biomassa, apresentando relação direta em sua composição com o carbono, sendo liberado no ecossistema após a derrubada das árvores. Medidas de quantificação do carbono são importantes na discussão das mudanças climáticas e saber o quantitativo da biomassa é a base de todo estudo relacionado. Neste enfoque o trabalhou objetivou quantificar a biomassa fresca com o uso de uma equação global para uma área de manejo florestal sustentável no oeste do Pará. Usou-se as informações do inventário florestal 100%, de um empreendimento localizado em Santarém, que passou pelo processo de licenciamento florestal sendo deferido pelo órgão responsável. Detectou-se um elevado número de espécies na área, sendo a base da identificação listas comerciais, a floresta apresentou características estruturais de uma floresta em equilíbrio e com distribuição normal. Por se tratar de uma floresta densa, os valores de biomassa fresca foram considerados elevados e dentro do esperado para o grande porte das árvores, dando destaque para a biomassa das árvores exploradas, que foi aproximadamente 30 % do valor da comunidade arbórea inventariada. O trabalho quantificou a biomassa fresca de forma satisfatória para a propriedade, e dentro dos erros amostrais, dessa forma contribuindo para o aprofundamento de estudos envolvendo modelos globais e a quantificação de biomassa fresca acima do solo

Pervasive gaps in Amazonian ecological research

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

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

Pervasive gaps in Amazonian ecological research

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