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

On the relevance of floristic and quantitative studies to the restoration of degraded areas: the case of the Atlantic Forest hotspot<br />Running title: Insights for restoration in Atlantic Forest

Ecological restoration is an important tool for the conservation of hotspots, and floristic and structural studies can provide theoretical and empirical support for this practice. Our goal was to highlight the relevance of knowledge provided by these studies to the development and success of restoration programs conducted in degraded areas in the Atlantic Forest, a top global hotspot for biodiversity conservation. Through the assessment of articles, books, book chapters, government documents, dissertations and theses, we comment on how floristic and quantitative parameters can provide structure and dynamic information on biological populations existing at restoration sites, allowing for inferences regarding management practices and strategies for the restoration of degraded areas and conservation of biodiversity

Estrutura de um curso de taxonomia de campo: o modelo aplicado em Ubatuba, São Paulo Structure of taxonomy field course: the model applied at Ubatuba-São Paulo

As atividades de campo são essenciais à formação de um bom taxonomista. Os problemas mais usuais das atividades didáticas no campo são: a) grande número de alunos; b) formação heterogênea e desequilíbrio de conhecimento dos participantes; c) repetições e tendência de coletas direcionadas para as formas de vida mais evidentes. As causas e conseqüências destes problemas são discutidas. Como solução é proposta uma metodologia, fundamentada numa vivência de muitos anos de atividades didáticas no campo em cursos de graduação e pós-graduação. São abordados tópicos como o número ideal de participantes, área de abrangência, época de atividade, divisão de trabalho e material e equipamentos necessários. Dependendo do número de espécies coletadas na mesma localidade, esta metodologia pode gerar uma lista de espécies da região com indicações precisas de hábito, habitat, nomes vulgares, abundância, usos, fenologia e outras informações que sempre afloram em trabalhos desta natureza. Como exemplo são apresentados os resultados da aplicação dessa metodologia em um curso de campo realizado em Ubatuba-SP e região.<br>The field activities are essential for the education of a good taxonomist. The most common problems found in field activities are: a) large number of students, b) heterogeneous educational background and unlevelled knowledge of the participants, c) repetitions and tendency of collecting the more evidents life-forms. The causes and consequences of such problems are discussed herein. The proposed solution is a methodology, based on many years of experience in field courses for undergraduate and graduate courses. Topics about the ideal number of participants, area of coverage, period of activity, division of work and the necessary material and equipment are discussed. According to the number of species collected at the same place, this methodology may result in a list of local species with precise information about the life-forms, habitat, common names, frequency, uses, phenology and further information in this kind of work. The results of the aplication of this metodology in a field course held in the region of Ubatuba-SP are presented