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

The global abundance of tree palms

Aim: Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location: Tropical and subtropical moist forests. Time period: Current. Major taxa studied: Palms (Arecaceae). Methods: We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results: On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work. Conclusions: Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests

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

Additional file 1: of Stability of the HTLV-1 glycoprotein 46 (gp46) gene in an endemic region of the Brazilian Amazon and the presence of a significant mutation (N93D) in symptomatic patients

The research ethics committee. Source: Study protocol, 2015, Table S1. Description of values of AICM applied in the statistics (Bayesian inference) in the study data. Source: Study protocol, 2016. (PDF 1549 kb

Genetic polymorphisms influence runners’ responses to the dietary ingestion of antioxidant supplementation based on pequi oil (Caryocar brasiliense Camb.): a before-after study

Genes have been implicated in the levels of oxidative stress, lipids, CVD risk, immune reactivity, and performance. Pequi oil (Caryocar brasiliense) has shown anti-inflammatory and hypotensive effects, besides reducing exercise-induced DNA, tissue damages, and anisocytosis. Given that diet can interact with the human genome to influence health and disease, and because genetic variability can influence response to diet, we aim to investigate the influence of 12 gene polymorphisms on inflammatory markers, postprandial lipids, arterial pressure, and plasma lipid peroxidation of runners (N = 125), before and after 14 days of 400 mg pequi-oil supplementation, after races under closely comparable conditions. Arterial pressure was checked before races; blood samples were taken immediately after racing to perform leukogram and plateletgram, Tbars assay, lipid, and CRP dosages and genotyping. CAT, GST-M1/T1, CRP-G1059C, and MTHFR-C677T polymorphisms influenced post-pequi-oil responses in leukogram; Hp and MTHFR-C677T, in plateletgram; Hp, ACE, GSTT1, and MTHFR-A1298C, in lipid profile; MTHFR-A1298C, in C-reactive protein (CRP) levels; and Hp and MnSOD, in Tbars assay. Differences between ACE genotypes in leukogram and total cholesterol disappeared after pequi, and the same occurred for Hp and MnSOD in Tbars assay and for MTHFR-A1298C with CRP levels. Because genetic inheritance is one of the factors that drive atherosclerosis-related lipid abnormalities, results can contribute to a greater understanding of the influence of genetic polymorphisms in situations that push up free radicals. Knowledge is also expanded on how antioxidant supplementation affects an individual’s genes and how athletic genetic makeup can affect the way a person responds to antioxidant supplements

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