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

Sympathetic hyperactivity differentially affects skeletal muscle mass in developing heart failure: role of exercise training

Bacurau AV, Jardim MA, Ferreira JC, Bechara LR, Bueno CR Jr, Alba-Loureiro TC, Negrao CE, Casarini DE, Curi R, Ramires PR, Moriscot AS, Brum PC. Sympathetic hyperactivity differentially affects skeletal muscle mass in developing heart failure: role of exercise training. J Appl Physiol 106: 1631-1640, 2009. First published January 29, 2009; doi:10.1152/japplphysiol.91067.2008.-Sympathetic hyperactivity (SH) is a hallmark of heart failure (HF), and several lines of evidence suggest that SH contributes to HF-induced skeletal myopathy. However, little is known about the influence of SH on skeletal muscle morphology and metabolism in a setting of developing HF, taking into consideration muscles with different fiber compositions. The contribution of SH on exercise tolerance and skeletal muscle morphology and biochemistry was investigated in 3- and 7-mo-old mice lacking both alpha(2A)- and alpha(2C)-adrenergic receptor subtypes (alpha(2A)/alpha(2C)ARKO mice) that present SH with evidence of HF by 7 mo. To verify whether exercise training (ET) would prevent skeletal muscle myopathy in advanced-stage HF, alpha(2A)/alpha(2C)ARKO mice were exercised from 5 to 7 mo of age. At 3 mo, alpha(2A)/alpha(2C)ARKO mice showed no signs of HF and preserved exercise tolerance and muscular norepinephrine with no changes in soleus morphology. In contrast, plantaris muscle of alpha(2A)/alpha(2C)ARKO mice displayed hypertrophy and fiber type shift (IIA -> IIX) paralleled by capillary rarefaction, increased hexokinase activity, and oxidative stress. At 7 mo, alpha(2A)/alpha(2C)ARKO mice displayed exercise intolerance and increased muscular norepinephrine, muscular atrophy, capillary rarefaction, and increased oxidative stress. ET reestablished alpha(2A)/alpha(2C)ARKO mouse exercise tolerance to 7-mo-old wild-type levels and prevented muscular atrophy and capillary rarefaction associated with reduced oxidative stress. Collectively, these data provide direct evidence that SH is a major factor contributing to skeletal muscle morphological changes in a setting of developing HF. ET prevented skeletal muscle myopathy in alpha(2A)/alpha(2C)ARKO mice, which highlights its importance as a therapeutic tool for HF.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)[2005/59740-7]Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)[2003/10442-9]Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)[2006/56321-6]Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)[473061/2006-6

Potencial evocado auditivo de tronco encefálico no prognóstico do coma superficial

O coma é a redução persistente do nível de consciência, arresponsivo a estímulos, devido à baixa atividade cerebral. Para verificar o nível de consciência, um recurso frequentemente utilizado é a Escala de Coma de Glasgow. Outro método que se destaca é o Potencial Evocado Auditivo de Tronco Encefálico, o qual avalia a atividade elétrica das vias auditivas ascendentes, desde o trajeto periférico até o mesencéfalo. O exame é simples, imune a medicamentos depressores e ambientes eletricamente carregados, sendo o mais adequado dos potenciais para a monitoração dos estados de coma. O presente estudo teve por objetivo verificar as características do Potencial Evocado Auditivo de Tronco Encefálico no estado de coma leve (Glasgow 7 - 8) e suas respectivas contribuições. Foi realizado um estudo prospectivo transversal em dois pacientes em coma (Glasgow 7), estado secundário a traumatismo cranioencefálico. Os resultados do exame evidenciaram presença de atividade elétrica em toda extensão da via estudada, em ambos os casos, com indicações de diferentes alterações, quanto à redução na latência entre os intervalos, morfologia e replicação das ondas. Tais diferenças foram contempladas com a evolução de cada caso: caso 1 evoluiu a alta hospitalar e caso 2 evoluiu a óbito. Os resultados confirmaram os achados da literatura, que descreve que a presença do Potencial Evocado Auditivo de Tronco Encefálico normal está associada à boa evolução do caso clínico, enquanto alterações no exame podem sinalizar para um mau prognóstico

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data