Leafing patterns and drivers across seasonally dry tropical communities

Investigating the timing of key phenological events across environments with variable seasonality is crucial to understand the drivers of ecosystem dynamics. Leaf production in the tropics is mainly constrained by water and light availability. Identifying the factors regulating leaf phenology patterns allows efficiently forecasting of climate change impacts. We conducted a novel phenological monitoring study across four Neotropical vegetation sites using leaf phenology time series obtained from digital repeated photographs (phenocameras). Seasonality differed among sites, from very seasonally dry climate in the caatinga dry scrubland with an eight-month long dry season to the less restrictive Cerrado vegetation with a six-month dry season. To unravel the main drivers of leaf phenology and understand how they influence seasonal dynamics (represented by the green color channel (Gcc) vegetation index), we applied Generalized Additive Mixed Models (GAMMs) to estimate the growing seasons, using water deficit and day length as covariates. Our results indicated that plant-water relationships are more important in the caatinga, while light (measured as day-length) was more relevant in explaining leafing patterns in Cerrado communities. Leafing behaviors and predictor-response relationships (distinct smooth functions) were more variable at the less seasonal Cerrado sites, suggesting that different life-forms (grasses, herbs, shrubs, and trees) are capable of overcoming drought through specific phenological strategies and associated functional traits, such as deep root systems in trees

The use of remote sensing for reliable estimation of net radiation and its components: a case-study for contrasting land covers in an agricultural hotspot of the Brazilian semiarid region

This study aims to ascertain the uncertainties related to the spatiotemporal estimation of net radiation, and its components, using remote sensing data. Geographical focus is an irrigated agricultural hotspot of the Brazilian semiarid region, for which we also investigate the impact that contrasting land-cover types have on the upwelling radiation balance components, and hence on net radiation. Instantaneous (Rn) and daily (Rn,24) values of net radiation were estimated based on OLI/TIRS-Landsat-8 images and key weather variables. In addition, we evaluated two models for downwelling shortwave (Rsw), ten models for downwelling longwave radiation (Rlw), and two models for derivation of Rn,24. The accuracy of each model was evaluated with radiation measurements obtained from research quality sensors installed in micrometeorological towers. The best performances were found for the Allen model, Duarte model, and De Bruin model for Rsw, Rlw, and Rn,24, respectively. The contrasting land-use types exhibited substantial differences in the biophysical variables and radiative properties that affect Rn. The albedo for the irrigated crops has average absolute values that are 0.01–0.03 larger than those found for the pristine caatinga, whereas the land surface temperature, LST, is 3–5 degrees smaller. However, Rn for these two distinctly different surface types was similar, as a result of a considerably lower surface emissivity in the caatinga. For rangeland, the albedo, LST, and hence the upwelling radiation had greater values than those found for the caatinga, which caused reduced values of Rn. The urban areas exhibited the lowest values of Rn, mainly as a consequence of their high albedo values. We show that when in-situ net radiation data are not available, remote sensing data combined with more readily available in-situ weather data can be used to derive spatiotemporal estimates of Rn. This facilitates the identification of anthropogenic impacts on the radiation at the land-surface and ultimately the energy balance, including the short-term seasonal and long-term effects

Relationship between tropical leaf phenology and ecosystem productivity using phenocameras

Introduction: The interplay of water and light, regarded as the main driver of tropical plant dynamics, determines leaf phenology and ecosystem productivity. Leaf phenology has been discussed as a key variable to explain photosynthetic seasonality in evergreen tropical forests, but the question is still open for seasonally tropical ecosystems. In the search for implementing long-term phenology monitoring in the tropics, phenocameras have proven to be an accurate method to estimate vegetative phenology in tropical communities. Here, we investigated the temporal patterns of leaf phenology and their relation to gross primary productivity (GPP) in a comparative study across three contrasting tropical biomes: dry forest (caatinga), woodland savanna (cerrado), and rainforest (Atlantic Forest).Methods: We monitored leaf phenology (phenocameras) and estimated gross primary productivity (eddy-covariance) continuously over time at three study sites. We investigated the main drivers controlling leaf phenology and tested the performance of abiotic (climate) and biotic (phenology) factors to explain gross primary productivity across sites.Results: We found that camera-derived indices presented the best relationships with gross primary productivity across all sites. Gross primary productivity seasonality was controlled by a gradient of water vs. light, where caatinga dry forest was water-limited, cerrado vegetation responded to water seasonality and light, and rainforest was mainly controlled by light availability. Vegetation phenology was tightly associated with productivity in the driest ecosystem (caatinga), where productivity was limited to the wet season, and the camera-derived index (Gcc) was the best proxy for gross primary productivity.Discussion: Leaf phenology increased their relative importance over gross primary productivity seasonality at less seasonal sites (cerrado and rainforest), where multiple leafing strategies influenced carbon exchanges. Our multi-site comparison, along with fine-scale temporal observations of leaf phenology and gross primary productivity patterns, uncovered the relationship between leafing and productivity across tropical ecosystems under distinct water constraints

WATER DEMAND AND WATER USE EFFICIENCY IN ‘PALMER’ MANGO CULTIVATION IN THE LOW-MIDDLE SÃO FRANCISCO VALLEY

ABSTRACT The study aimed to determine the evapotranspiration (ETc) of the mango cv. ‘Palmer’ over two productive cycles, analyzing water-use efficiency (WUE) and crop water productivity (CWP) to propose average crop coefficient (Kc) values for improving irrigation management under cultivation conditions in the Low-Middle São Francisco Valley. The study was conducted from July 2019 to May 2021 in a commercial ‘Palmer’ mango orchard in Petrolina, State of Pernambuco, Brazil. Micrometeorological data was collected throughout the experimental period. The crop evapotranspiration (ETc) was determined using Bowen ratio energy balance (BREB), and then the Kc, WUE, and CWP were determined. The highest ETc values occurred during the floral induction phase (5.14 ± 0.85 mm day-1), with a Kc of 0.85; however, the lowest values were observed during the fruit maturation phase (3.60 ± 0.73 mm day-1), with a Kc of 0.91. Average water consumption per cycle was 1445 mm, with a daily average of 4.39 mm day-1. WUE and CWP were 16.9 and 24.5 kg ha-1 mm-1, respectively. Average Kc values of 0.81, 0.76, 0.85, 0.90, 0.95, and 0.91 are recommended for the vegetative growth, rest period and shoot maturation, floral induction, flowering, fruit development, and fruit maturation phases, respectively

Multiscale phenology of seasonally dry tropical forests in an aridity gradient

The leaf phenology of seasonally dry tropical forests (SDTFs) is highly seasonal, marked by synchronized flushing of new leaves triggered by the first rains of the wet season. Such phenological transitions may not be accurately detected by remote sensing vegetation indices and derived transition dates (TDs) due to the coarse spatial and temporal resolutions of satellite data. The aim of this study was to compared TDs from PhenoCams and satellite remote sensing (RS) and used the TDs calculated from PhenoCams to select the best thresholds for RS time series and calculate TDs. For this purpose, we assembled cameras in seven sites along an aridity gradient in the Brazilian Caatinga, a region dominated by SDTFs. The leafing patterns were registered during one to three growing seasons from 2017 to 2020. We drew a region of interest (ROI) in the images to calculate the normalized green chromatic coordinate index. We compared the camera data with the NDVI time series (2000–2019) derived from near-infrared (NIR) and red bands from MODIS product data. Using calibrated PhenoCam thresholds reduced the mean absolute error by 5 days for SOS and 34 days for EOS, compared to common thresholds in land surface phenology studies. On average, growing season length (LOS) did not differ significantly among vegetation types, but the driest sites showed the highest interannual variation. This pattern was applied to leaf flushing (SOS) and leaf fall (EOS) as well. We found a positive relationship between the accumulated precipitation and the LOS and between the accumulated precipitation and maximum and minimum temperatures and the vegetation productivity (peak and accumulated NDVI). Our results demonstrated that (A) the fine temporal resolution of phenocamera phenology time series improved the definitions of TDs and thresholds for RS landscape phenology; (b) long-term RS greening responded to the variability in rainfall, adjusting their timing of green-up and green-down, and (C) the amount of rainfall, although not determinant for the length of the growing season, is related to the estimates of vegetation productivity

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research