Correction: Pervasive gaps in Amazonian ecological research

In the original version of the article, the authors incorrectly stated the value of current and projected deforestation in the results: the values should be 23.50% and 27.29%, respectively. This error does not impact the results or conclusions presented in the paper. The error has now been corrected online. The authors apologize for the error and any confusion that may have resulted

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

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ

Índices de sazonalidade para regionalização hidrológica de vazões de estiagem no Rio Grande do Sul

Informações sobre vazões de estiagem são cruciais no contexto da gestão de recursos hídricos; todavia, a rede de monitoramento fluviométrico atualmente existente no Brasil não supre as necessidades dos técnicos, caso em que a análise regional pode ser empregada para estimar vazões de estiagem em locais sem monitoramento ou com um curto período de monitoramento. O objetivo deste trabalho foi verificar o potencial de três métodos de sazonalidade aplicados à avaliação do regime temporal e espacial de vazões de estiagem no Rio Grande do Sul, de modo que possam ser usados como subsídio técnico para a regionalização em regiões hidrologicamente homogêneas. Aplicando os métodos Seasonality Ratio (SR), Seasonality Index (SI) e Seasonality Histogram (SH) com base nas séries históricas de 108 estações fluviométricas, foi possível constatar que existe uma forte sazonalidade de vazões de estiagem no estado. Entre as três medidas de sazonalidade, SI e SH foram mais apropriadas em função das características hidrológicas específicas do estado; portanto, elas podem ser consideradas metodologias relevantes para delinear regiões hidrologicamente homogêneas para a regionalização hidrológica de vazões de estiagem

Ostecondroma em um felino jovem infectado pelo vírus da leucemia felina

Osteochondromas are primary bone tumors characterized by cartilage-covered bone projections involving single or multiple masses (osteochondromatosis). This study reports the clinical and pathological findings from a young domestic cat with osteochondroma in the humerus. During the clinical evaluation, the animal had pronounced right forelimb musculature atrophy and an increased distal humeral volume. Histopathological examination of the neoplasm revealed a proliferative lesion characterized mostly by endochondral ossification and peripheral foci of proliferating cartilage tissue. Further testing using immunohistochemical staining and polymerase chain reaction revealed the presence of feline leukemia virus antigens in the hematopoietic cells of the bone marrow and FeLV proviral DNA in the peripheral blood lymphocytes. Clinical and pathological findings are consistent with osteochondroma. This neoplasm occurred in an eight-month-old feline with humeral enlargement that had been present since two months old.O osteocondroma é um tumor ósseo primário que se caracteriza por apresentar uma projeção óssea recoberta por cartilagem que pode ser formado por uma única ou por múltiplas massas (osteocondromatose). O objetivo deste trabalho é descrever os achados clínicos e patológicos de um felino jovem com osteocondroma no úmero. Na avaliação clínica, o felino apresentava atrofia acentuada da musculatura do membro torácico direito além de um aumento de volume em região distal do úmero. No exame histopatológico, observou-se uma lesão proliferativa composta em sua maior parte por ossificação endocondral com focos periféricos de tecido cartilaginoso proliferado. Testes de imuno-histoquímica e reação em cadeia da polimerase revelaram a presença de antígenos de FeLV em células da linhagem hematopoiética da medula óssea e DNA proviral em linfócitos do sangue periférico, respectivamente. Os achados clínicos e patológicos foram consistentes com um osteocondroma em um felino jovem, com oito meses de idade, com lesão em úmero desde os dois meses de idade