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, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

Effect of vegetation removal for road building on richness and composition of Odonata communities in Amazonia, Brazil

This study showed that the main impact on Odonata species of removal of riparian vegetation for road building was on community composition, since species richness remained unaltered. This result, most evident in damselflies, was probably driven by the entry of generalist species that replaced specialist species after the impact. We collected adult odonates in forested and deforested streams in the surroundings of Manaus, Amazonas, northern Brazil. We collected 380 specimens belonging to 32 odonate species. Erythrodiplax fusca andArgia sp. 1 could be used in biomonitoring programs, since they were significantly associated with deforested streams. Using odonate community composition and key species appears to be more efficient in biomonitoring programs than simply using species richness. © 2013 Worldwide Dragonfly Association

Composição e distribuição da fauna de Ephemeroptera (Insecta) em área de transição Cerrado-Amazônia, Brasil

O objetivo deste trabalho foi responder se existe padrão na distribuição espacial das ninfas de Ephemeroptera em diferentes córregos e rios da bacia do Rio Suiá-Miçú, MT, e como os córregos estudados estão classificados de acordo com a composição de espécies. Na coleta foram amostrados 12 córregos e rios, em três períodos do ano. Foram coletados 1356 indivíduos, distribuídos em sete famílias, 31 gêneros e 42 espécies e/ou morfoespécies. Os locais mais abundantes foram ambientes semi-lênticos, com pouco sombreamento no leito, sugerindo que a maior entrada de luz disporia, além do material alóctone, material autóctone como fonte de alimento. A maior riqueza de espécie e/ou morfoespécie, estimada, foi em ambientes lóticos enfatizando que os Ephemeroptera apresentam maior riqueza nestes locais uma vez que a correnteza é essencial para transportar a matéria orgânica particulada. Tanto na análise de agrupamento (TWINSPAM) como na ordenação (DCA) observou-se a separação entre ambientes lóticos e semi-lênticos quanto a composição de espécies. Percebeu-se um gradiente na similaridade de composição dos ambientes lóticos de pequeno porte para ambientes lóticos de grande porte e, por fim, os semi-lênticos. Os resultados deste estudo demonstram que a estrutura física dos ambientes aquáticos afeta a composição de espécies. Dessa forma, a retirada das matas ciliares e o represamento dos córregos podem levar à perdas significativas na diversidade