Differences in xylem and leaf hydraulic traits explain differences in drought tolerance among mature Amazon rainforest trees

Considerable uncertainty surrounds the impacts of anthropogenic climate change on the composition and structure of Amazon forests. Building upon results from two large-scale ecosystem drought experiments in the eastern Brazilian Amazon that observed increases in mortality rates among some tree species but not others, in this study we investigate the physiological traits underpinning these differential demographic responses. Xylem pressure at 50% conductivity (xylem-P50 ), leaf turgor loss point (TLP), cellular osmotic potential (πo ), and cellular bulk modulus of elasticity (ε), all traits mechanistically linked to drought tolerance, were measured on upper canopy branches and leaves of mature trees from selected species growing at the two drought experiment sites. Each species was placed a priori into one of four plant functional type (PFT) categories: drought-tolerant versus drought-intolerant based on observed mortality rates, and subdivided into early- versus late-successional based on wood density. We tested the hypotheses that the measured traits would be significantly different between the four PFTs and that they would be spatially conserved across the two experimental sites. Xylem-P50 , TLP, and πo , but not ε, occurred at significantly higher water potentials for the drought-intolerant PFT compared to the drought-tolerant PFT; however, there were no significant differences between the early- and late-successional PFTs. These results suggest that these three traits are important for determining drought tolerance, and are largely independent of wood density-a trait commonly associated with successional status. Differences in these physiological traits that occurred between the drought-tolerant and drought-intolerant PFTs were conserved between the two research sites, even though they had different soil types and dry-season lengths. This more detailed understanding of how xylem and leaf hydraulic traits vary between co-occuring drought-tolerant and drought-intolerant tropical tree species promises to facilitate a much-needed improvement in the representation of plant hydraulics within terrestrial ecosystem and biosphere models, which will enhance our ability to make robust predictions of how future changes in climate will affect tropical forests

Effects of different resistance training frequencies on flexibility in older women

Objective The main purpose of the investigation reported here was to analyze the effect of resistance training (RT) performed at different weekly frequencies on flexibility in older women. Participants and methods Fifty-three older women (≥60 years old) were randomly assigned to perform RT either two (n=28; group “G2x”), or three (n=25; group “G3x”) times per week. The RT program comprised eight exercises in which the participants performed one set of 10–15 repetitions maximum for a period of 12 weeks. Anthropometric, body-composition, and flexibility measurements were made at baseline and post-study. The flexibility measurements were obtained by a fleximeter. Results A significant group-by-time interaction (P\u3c0.01) was observed for frontal hip flexion, in which G3x showed a higher increase than G2x (+12.8% and +3.0%, respectively). Both groups increased flexibility in cervical extension (G2x=+19.1%, G3x=+20.0%), right hip flexion (G2x=+14.6%, G3x=+15.9%), and left hip flexion (G2x=+25.7%, G3x=+19.2%), with no statistical difference between groups. No statistically significant differences were noted for the increase in skeletal muscle mass between training three versus two times a week (+7.4% vs +4.4%, respectively). Conclusion Twelve weeks of RT improves the flexibility of different joint movements in older women, and the higher frequency induces greater increases for frontal hip flexion

Stand dynamics modulate water cycling and mortality risk in droughted tropical forest

Transpiration from the Amazon rainforest generates an essential water source at a global and local scale. However, changes in rainforest function with climate change can disrupt this process, causing significant reductions in precipitation across Amazonia, and potentially at a global scale. We report the only study of forest transpiration following a long-term (>10 year) experimental drought treatment in Amazonian forest. After 15 years of receiving half the normal rainfall, drought-related tree mortality caused total forest transpiration to decrease by 30%. However, the surviving droughted trees maintained or increased transpiration because of reduced competition for water and increased light availability, which is consistent with increased growth rates. Consequently, the amount of water supplied as rainfall reaching the soil and directly recycled as transpiration increased to 100%. This value was 25% greater than for adjacent nondroughted forest. If these drought conditions were accompanied by a modest increase in temperature (e.g., 1.5°C), water demand would exceed supply, making the forest more prone to increased tree mortality.Peer reviewe

Plant traits controlling growth change in response to a drier climate

This is the final version. Available on open access from Wiley via the DOI in this recordPlant traits are increasingly being used to improve prediction of plant function, including plant demography. However, the capability of plant traits to predict demographic rates remains uncertain, particularly in the context of trees experiencing a changing climate. Here we present data combining 17 plant traits associated with plant structure, metabolism and hydraulic status, with measurements of long-term mean, maximum and relative growth rates for 176 trees from the world’s longest running tropical forest drought experiment. We demonstrate that plant traits can predict mean annual tree growth rates with moderate explanatory power. However, only combinations of traits associated more directly with plant functional processes, rather than more commonly employed traits like wood density or leaf mass per area, yield the power to predict growth. Critically, we observe a shift from growth being controlled by traits related to carbon cycling (assimilation and respiration) in well-watered trees, to traits relating to plant hydraulic stress in drought-stressed trees. We also demonstrate that even with a very comprehensive set of plant traits and growth data on large numbers of tropical trees, considerable uncertainty remains in directly interpreting the mechanisms through which traits influence performance in tropical forests.Conselho Nacional de Desenvolvimento Científico e TecnológicoNatural Environment Research Council (NERC)Australian Research Council (ARC)European Union FP7Fundação de Amparo à Pesquisa do Estado de São Paul

The response of carbon assimilation and storage to long‐term drought in tropical trees is dependent on light availability

Whether tropical trees acclimate to long‐term drought stress remains unclear. This uncertainty is amplified if drought stress is accompanied by changes in other drivers such as the increases in canopy light exposure that might be induced by tree mortality or other disturbances. Photosynthetic capacity, leaf respiration, non‐structural carbohydrate (NSC) storage and stomatal conductance were measured on 162 trees at the world's longest running (15 years) tropical forest drought experiment. We test whether surviving trees have altered strategies for carbon storage and carbon use in the drier and elevated light conditions present following drought‐related tree mortality. Relative to control trees, the surviving trees experiencing the drought treatment showed functional responses including: (a) moderately reduced photosynthetic capacity; (b) increased total leaf NSC; and (c) a switch from starch to soluble sugars as the main store of branch NSC. This contrasts with earlier findings at this experiment of no change in photosynthetic capacity or NSC storage. The changes detected here only occurred in the subset of drought‐stressed trees with canopies exposed to high radiation and were absent in trees with less‐exposed canopies and also in the community average. In contrast to previous results acquired through less intensive species sampling from this experiment, we also observe no species‐average drought‐induced change in leaf respiration. Our results suggest that long‐term responses to drought stress are strongly influenced by a tree's full‐canopy light environment and therefore that disturbance‐induced changes in stand density and dynamics are likely to substantially impact tropical forest responses to climate change. We also demonstrate that, while challenging, intensive sampling is essential in tropical forests to avoid sampling biases caused by limited taxonomic coverage.Publicado online em 29 set. 2020

Development of Potential Multi-Target Inhibitors for Human Cholinesterases and Beta-Secretase 1: A Computational Approach

Alzheimer’s disease causes chronic neurodegeneration and is the leading cause of dementia in the world. The causes of this disease are not fully understood but seem to involve two essential cerebral pathways: cholinergic and amyloid. The simultaneous inhibition of AChE, BuChE, and BACE-1, essential enzymes involved in those pathways, is a promising therapeutic approach to treat the symptoms and, hopefully, also halt the disease progression. This study sought to identify triple enzymatic inhibitors based on stereo-electronic requirements deduced from molecular modeling of AChE, BuChE, and BACE-1 active sites. A pharmacophore model was built, displaying four hydrophobic centers, three hydrogen bond acceptors, and one positively charged nitrogen, and used to prioritize molecules found in virtual libraries. Compounds showing adequate overlapping rates with the pharmacophore were subjected to molecular docking against the three enzymes and those with an adequate docking score (n = 12) were evaluated for physicochemical and toxicological parameters and commercial availability. The structure exhibiting the greatest inhibitory potential against all three enzymes was subjected to molecular dynamics simulations (100 ns) to assess the stability of the inhibitor-enzyme systems. The results of this in silico approach indicate ZINC1733 can be a potential multi-target inhibitor of AChE, BuChE, and BACE-1, and future enzymatic assays are planned to validate those results.PPBE and PPGCF/UEFS; Fundação de Amparo à Pesquisa do Estado de Minas Gerais—FAPEMIG, grants APQ-02741-17, APQ-00855-19, APQ-01733-21, and APQ-04559-22Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPq-Brazil, grants 305117/2017-3, 426261/2018-6Fellowship of 2021 (grant 310108/2020-9

Stand dynamics modulate water cycling and mortality risk in droughted tropical forest

Transpiration from the Amazon rainforest generates an essential water source at a global and local scale. However, changes in rainforest function with climate change can disrupt this process, causing significant reductions in precipitation across Amazonia, and potentially at a global scale. We report the only study of forest transpiration following a long-term (>10 year) experimental drought treatment in Amazonian forest. After 15 years of receiving half the normal rainfall, drought-related tree mortality caused total forest transpiration to decrease by 30%. However, the surviving droughted trees maintained or increased transpiration because of reduced competition for water and increased light availability, which is consistent with increased growth rates. Consequently, the amount of water supplied as rainfall reaching the soil and directly recycled as transpiration increased to 100%. This value was 25% greater than for adjacent nondroughted forest. If these drought conditions were accompanied by a modest increase in temperature (e.g., 1.5°C), water demand would exceed supply, making the forest more prone to increased tree mortality.This work is a product of UK NERC grant NE/J011002/1 to PM andMM, CNPQ grant 457914/2013-/MCTI/CNPq/FNDCT/LBA/ESE-CAFLOR to ACLD, an ARC grant FT110100457 to PM and a UKNERC independent fellowship grant NE/N014022/1 to LR. It waspreviously supported by NERC NER/A/S/2002/00487, NERC GR3/11706, EU FP5-Carbonsink and EU FP7-Amazalert to PM. RP acknowledges support of MINECO (Spain), grant CGL2014-5583-JIN

Genome wide association mapping of grain arsenic, copper, molybdenum and zinc in rice (Oryza sativa L.) grown at four international field sites

Peer reviewedPublisher PD

Search for the rare decays B0→J/ψγB^{0}\to J/\psi \gamma and Bs0→J/ψγB^{0}_{s} \to J/\psi \gamma

A search for the rare decay of a $B^{0}$ or $B^{0}_{s}$ meson into the final state $J/\psi\gamma$ is performed, using data collected by the LHCb experiment in $pp$ collisions at $\sqrt{s}=7$ and $8$ TeV, corresponding to an integrated luminosity of 3 fb$^{-1}$. The observed number of signal candidates is consistent with a background-only hypothesis. Branching fraction values larger than $1.7\times 10^{-6}$ for the $B^{0}\to J/\psi\gamma$ decay mode are excluded at 90% confidence level. For the $B^{0}_{s}\to J/\psi\gamma$ decay mode, branching fraction values larger than $7.4\times 10^{-6}$ are excluded at 90% confidence level, this is the first branching fraction limit for this decay.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2015-044.htm

Solar Irradiance Forecasting Using Dynamic Ensemble Selection

Solar irradiance forecasting has been an essential topic in renewable energy generation. Forecasting is an important task because it can improve the planning and operation of photovoltaic systems, resulting in economic advantages. Traditionally, single models are employed in this task. However, issues regarding the selection of an inappropriate model, misspecification, or the presence of random fluctuations in the solar irradiance series can result in this approach underperforming. This paper proposes a heterogeneous ensemble dynamic selection model, named HetDS, to forecast solar irradiance. For each unseen test pattern, HetDS chooses the most suitable forecasting model based on a pool of seven well-known literature methods: ARIMA, support vector regression (SVR), multilayer perceptron neural network (MLP), extreme learning machine (ELM), deep belief network (DBN), random forest (RF), and gradient boosting (GB). The experimental evaluation was performed with four data sets of hourly solar irradiance measurements in Brazil. The proposed model attained an overall accuracy that is superior to the single models in terms of five well-known error metrics