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

Simulation of Electronic Waste Reverse Chains for the Sao Paulo Circular Economy: An Artificial Intelligence-Based Approach for Economic and Environmental Optimizations

The objective of this study was to apply simulation and genetic algorithms for the economic and environmental optimization of the reverse network (manufacturers, waste managers, and recyclers in Sao Paulo, Brazil) of waste from electrical and electronic equipment (WEEE) to promote the circular economy. For the economic evaluation, the reduction in fuel, drivers, insurance, depreciation, maintenance, and charges was considered. For the environmental evaluation, the impact of abiotic, biotic, water, land, air, and greenhouse gases was measured. It was concluded that the optimized structure of the WEEE reverse chains for Sao Paulo, Brazil provided a reduction in the number of collections, thus making the most of cubage. It also generated economic and environmental gains, contributing to the strategic actions of the circular economy. Therefore, the proposed approach is replicable in organizational practice, which is mainly required to meet the 2030 agenda of reducing the carbon footprint generated by transport in large cities. Thus, this study can guide companies in structuring the reverse WEEE chains in Sao Paulo, Brazil, and other states and countries for economic and environmental optimization, which is an aspect of great relevance considering the exponential generation of WEEE

Regional gray matter abnormalities in panic disorder: A voxel-based morphometry study

Although abnonnalities in brain structures involved in the neurobiology of fear and anxiety have been implicated in the pathophysiology of panic disorder (PD), relatively few studies have made use of voxel-based morphometry (VBM) magnetic resonance imaging (MRI) to determine structural brain abnormalities in PD. We have assessed gray matter volume in 19 PD patients and 20 healthy volunteers using VBM. Images were acquired using a 1.5 T MRI scanner, and were spatially normalized and segmented using optimized VBM. Statistical comparisons were performed using the general linear model. A relative increase in gay matter volume was found in the left insula of PD patients compared with controls. Additional structures showing differential increases were the left superior temporal gyrus, the midbrain, and the pons. A relative gray matter deficit was found in the right anterior cingulate cortex. The insula and anterior cingulate abnormalities may be relevant to the pathophysiology of PD, since these structures participate in the evaluation process that ascribes negative emotional meaning to potentially distressing cognitive and interoceptive sensory information. The abnormal brain stem structures may be involved in the generation of panic attacks. (C) 2007 Elsevier Ireland Ltd. All rights reserved

Post-COVID-19 condition: systemic inflammation and low functional exercise capacity

IntroductionPost-COVID-19 condition (PCC) is characterised by a plethora of symptoms, with fatigue appearing as the most frequently reported. The alterations that drive both the persistent and post-acute disease newly acquired symptoms are not yet fully described. Given the lack of robust knowledge regarding the mechanisms of PCC we have examined the impact of inflammation in PCC, by evaluating serum cytokine profile and its potential involvement in inducing the different symptoms reported.MethodsIn this cross-sectional study, we recruited 227 participants who were hospitalised with acute COVID-19 in 2020 and came back for a follow-up assessment 6–12 months after hospital discharge. The participants were enrolled in two symptomatic groups: Self-Reported Symptoms group (SR, n = 96), who did not present major organ lesions, yet reported several debilitating symptoms such as fatigue, muscle weakness, and persistent loss of sense of smell and taste; and the Self-Reported Symptoms and decreased Pulmonary Function group (SRPF, n = 54), composed by individuals with the same symptoms described by SR, plus diagnosed pulmonary lesions. A Control group (n = 77), with participants with minor complaints following acute COVID-19, was also included in the study. Serum cytokine levels, symptom questionnaires, physical performance tests and general clinical data were obtained in the follow-up assessment.ResultsSRPF presented lower IL-4 concentration compared with Control (q = 0.0018) and with SR (q = 0.030), and lower IFN-α2 serum content compared with Control (q = 0.007). In addition, SRPF presented higher MIP-1β serum concentration compared with SR (q = 0.029). SR presented lower CCL11 (q = 0.012 and q = 0.001, respectively) and MCP-1 levels (q = 0.052 for both) compared with Control and SRPF. SRPF presented lower G-CSF compared to Control (q = 0.014). Female participants in SR showed lower handgrip strength in relation to SRPF (q = 0.0082). Male participants in SR and SRPF needed more time to complete the timed up-and-go test, as compared with men in the Control group (q = 0.0302 and q = 0.0078, respectively). Our results indicate that different PCC symptom profiles are accompanied by distinct inflammatory markers in the circulation. Of particular concern are the lower muscle function findings, with likely long-lasting consequences for health and quality of life, found for both PCC phenotypes

Sustainability Agenda for the Pantanal Wetland: Perspectives on a Collaborative Interface for Science, Policy, and Decision-Making

International audienceBuilding bridges between environmental and political agendas is essential nowadays in face of the increasing human pressure on natural environments, including wetlands. Wetlands provide critical ecosystem services for humanity and can generate a considerable direct or indirect income to the local communities. To meet many of the sustainable development goals, we need to move our trajectory from the current environmental destructive development to a wiser wetland use. The current article contain a proposed agenda for the Pantanal aiming the improvement of public policy for conservation in the Pantanal, one of the largest, most diverse, and continuous inland wetland in the world. We suggest and discuss a list of 11 essential interfaces between science, policy, and development in region linked to the proposed agenda. We believe that a functional science network can booster the collaborative capability to generate creative ideas and solutions to address the big challenges faced by the Pantanal wetland

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