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

Histopathology of dairy cows' hooves with signs of naturally acquired laminitis

The purpose of this study was to investigate histological changes in dairy cows' hooves with or without injuries from naturally acquired laminitis. Cull cows with no clinical signs of hoof abnormalities (G1, n=9) and those with macroscopic lesions associated with laminitis without (G2, n=23) or with lameness (G3, n=7) were used in the study. After slaughter, samples of dermo-epidermal junctions of sole, axial and dorsal regions of the hoof were obtained and histologically processed using HE and PAS staining. Congestion, hemorrhage and inflammatory infiltrate in the dermis of sole, axial and dorsal regions were blindly and semiquantitatively evaluated by the same researcher. Inflammatory infiltrate was evaluated in the dermal laminae of axial and dorsal regions. The morphology of epidermal cells and the presence of irregularities in three regions of the basement membrane (BM) length were examined using PAS staining. Scores of lesions in different regions of the hoof in the same group and in different groups for each region of the hoof were compared using non-parametric analyses. Inflammatory infiltrate in the dermis of all regions of the hoof was detected in all groups with no significant statistical difference. Cows with no clinical signs of hoof abnormalities secondary to laminitis (G1) have inflammation scores and epidermal cell changes similar to those of groups with laminitis injuries, suggesting the existence of a prodromal phase for this disease in bovines. BM had irregularities with a variable intensity along its length, however, with no difference among groups. The pattern of BM irregularities found has not been reported so far and does not resemble the BM collapse described in horses and cattle with induced acute laminitis. Is it concluded that even in the absence of macroscopic hoof signs associated to laminitis, dairy cows have histological injuries compatible with inflammation of the dermo-epidermal junction as in affected animals. Basement membrane of cows with or without laminitis associated lesions had irregularities with an irregular distribution along its length which need to be further studied

Histopathology of dairy cows' hooves with signs of naturally acquired laminitis

O objetivo deste trabalho foi investigar as alterações histológicas no casco de vacas leiteiras sem e com lesões de laminite, naturalmente, adquirida. Utilizaram-se animais de descarte sem lesões macroscópicas no casco (G1 n=9) e com lesões macroscópicas associadas à laminite sem (G2 n=23), ou com claudicação (G3 n=7). Após o abate, amostras da junção derme-epiderme das regiões solear, axial e dorsal do casco foram obtidas e processadas, histologicamente, nas colorações de HE e PAS. Avaliou-se, semiquantitativamente, às cegas e por um mesmo pesquisador, congestão, hemorragia e infiltrado inflamatório na derme das regiões solear, axial e dorsal. Avaliou-se infiltrado inflamatório na lâmina dermal das regiões axial e dorsal. A morfologia das células epidermais e a presença de irregularidades em três regiões do comprimento da membrana basal (MB) foram examinadas na coloração de PAS. Os escores das lesões nas diferentes regiões do casco no mesmo grupo e nos diferentes grupos para cada região do casco foram comparados através de análises não paramétricas (P<0,05). Infiltrado inflamatório na derme de todas as regiões do casco foi detectado em todos os grupos sem diferença estatística (P>0,05). Vacas sem lesões macroscópicas secundárias à laminite (G1) apresentaram escores de inflamação e alteração de células epidermais semelhantes aos dos grupos com lesões de laminite, sugerindo a existência de fase prodrômica para a doença em bovinos. A MB apresentou irregularidades com intensidade variável ao longo de seu comprimento (P<0,05), porém, sem diferença entre grupos (P>0,05). O padrão de irregularidades na MB encontrado não foi relatado até o momento e não se assemelha ao colapso de MB descrito em equinos e bovinos com laminite induzida. Concluiu-se que, mesmo na ausência de lesões macroscópicas no casco causadas por laminite, vacas leiteiras apresentam lesões histológicas compatíveis com inflamação da junção derme-epiderme como em animais afetados. A membrana basal de bovinos sem e com lesões de laminite apresenta irregularidades com distribuição irregular ao longo de seu comprimento que precisam ser melhor estudadas