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

Transformation of Mytella falcata residual shell into CaAl/LDH adsorbent: removal of methyl orange and methylene blue dyes

This study analyzed the viability of using malacoculture residue (Mytella falcata) to produce layered double hydroxides (LDHs) and for its subsequent use as an adsorbent. The CaAl/LDH-RE material was produced with calcium oxide from the residue and the CaAl/LDH-AP was produced with a commercial reagent. Both were used to remove methyl orange (MO) and methylene blue (MB) dyes. The CaAl/LDH-RE presented a surface area of 28.54 m2 g−1, being 65.62% larger than the CaAl/LDH-AP material (17.23 m2 g−1). The adsorbents showed mesopores distributed on a surface formed by plates in the form of hexagonal sheets arranged in an overlapping manner. The dosage of 0.05 g L−1 obtained the removal of 95% and 97% for MO, while for MB it was 94% and 93% using the adsorbents LDH/CaAl-AP and LDH/CaAl-RE, respectively. The system reached equilibrium at 90 min for MO and 120 min for MB. The pseudo-second order model well represented the kinetic data reaching 11.36 mg g−1 (CaAl/LDH-RE) and 8.42 mg g−1 (CaAl/LDH-AP) for MO, and 4.47 mg g−1 (CaAl/LDH-RE) and 4.14 mg g−1 (CaAl/LDH-AP) for MB. The Freundlich model better represented the isothermal data, where the temperature exerted little influence. Adsorbents showed similar removal percentages in real and synthetic matrices. The LDH/CaAl-RE can be applied in up to 3 cycles, maintaining its adsorption capacity. These results corroborate the use of MFW to produce CaAl/LDH-RE, which can be used for the efficient removal of organic pollutants in an aqueous solution

Mapeamento participativo do uso dos recursos naturais e conhecimento tradicional sobre ecologia de Quelônios na Várzea do Rio Purus, Brasil (Paper 294)

Na Amazônia, a captura de quelônios pelos indígenas é muito anterior à conquista européia. O estudo do saber popular que é usado na produção em pequena escala pode contribuir para, compreender como os recursos naturais no caso, os quelônios são explorados. O presente estudo foi realizado em três comunidades (São Sebastião, Fazenda e Beabá) da Reserva Biológica do Abufari (RBA), localizada no município de Tapauá, Amazonas, Brasil. Esta reserva pertence a categoria de unidade de conservação de proteção integral que tem como finalidade a proteção de populações de quelônios podocnemidideos. Foram avaliados com base no conhecimento tradicional ecológico o tamanho da área de vida de cada uma das comunidades, produzidos mapas de distribuição de área de pesca, caça, exploração de recursos florestais madeireiros e não-madeireiros e áreas de ocorrências e padrões de movimentação de quelônios na várzea do rio Purus. Os mapeamentos e a história oral mostraram que a maioria das 16 grandes áreas de desova de P. expansa existentes entre Abufari (RBA) e Sacado de Santa Luzia (RDS-PP) foram dizimadas ou extintas, restando somente o tabuleiro de Abufari e Tauamirim como as principais áreas de desova de desta espécie no Purus. O conhecimento tradicional, estimativas de níveis de exploração e dados futuros de estrutura populacional e biologia reprodutiva de quelônios podocnemididae contribuirão para o estabelecimento de programas de conservação de quelônios de base comunitária no ecossistema de várzea do rio Purus.Palavras-Chave: Amazônia. Ribeirinhos. DRP. História oral. Mapeamento participativo. Quelônios; Podocnemis