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Regional Model to Predict Sugarcane Yield Using Sentinel-2 Imagery in São Paulo State, Brazil
No full textInternational audienceSugarcane yield prediction is an important tool to support the sugar-energy sector. This study aimed to create a regional empirical model, using the random forest algorithm, to predict sugarcane yield in the state of Sao Paulo. For this, we used Sentinel-2 imagery (vegetation indices NDVIRE and CIRE, spectral bands Red-edge and near-infrared arrow), agronomic data (variety and ratoon stage and plant cane), climatic data (temperature, precipitation) and crop water deficit data from three mills. We created two predictive yield model based on three scenarios with different training and testing data: (SI) Scenario I is the regional model considered all data from the three mills, (SII) Scenario II was training similar SI and testing individuals for each mill, (SIII) Scenario III includes regional individual’s models for sugarcane ratoon stage and plant cane. In each case, 70% of the dataset was used for training and 30% for testing. SI gave R2 equal to 0.72, while SII R2 was between 0.60 and 0.78; the RMSE for SI was 11.7 , while for SII from 8.62 to 15.56 . The rRMSE was 16.5% for SI and from 12.4 to 21.6%, for SII. SIII showed R2 greater than 0.61, and RMSE between 9.6 and 13.5 . The CIRE and NDVIRE vegetation indices, crop water deficit and precipitation were the most important variables to estimate sugarcane yield. The model created considering SI and SII showed potential to be applied to different locals using data from three mills
A new sawfly from the Paleocene of Menat (Hymenoptera: Tenthredinidae)
No full textInternational audienceThe new tenthredinid Palaeocaiina menatensis gen. et sp. nov. is described and illustrated from the Paleocene of Menat (Puy-de-D and ocirc;me, France). Although its preservation complicates the observation of several key characters useful to distinguish between tenthredinid subfamilies, we decided to place this new taxon within the tribe Allantini of the subfamily Allantinae. Its venation of fore- and hind wings combined with the shape of its ovipositor sheaths leads us assume that Palaeocaiina gen. nov. is possibly related to the extant genus Caiina Wei, 2004 distributed in the east Palearctic. Interestingly, this new genus is the oldest known fossil of the subfamily Allantinae
The very-high resolution configuration of the EC-Earth global model for HighResMIP
No full textWe here present the very-high resolution version of the EC-Earth global climate model, EC-Earth3P-VHR, developed for HighResMIP. The model features an atmospheric resolution of ~16 km and an oceanic resolution of 1/12° (~8 km), which makes it one of the finest combined resolutions ever used to complete historical and scenario-like CMIP6 simulations. To evaluate the influence of numerical resolution on the simulated climate, EC-Earth3P-VHR is compared with two configurations of the same model at lower resolution: the ~100-km-grid EC-Earth3P-LR, and the ~25-km-grid EC-Earth3P-HR. The models' biases are evaluated against observations over the period 1980-2014. Compared to LR and HR, VHR shows a reduced equatorial Pacific cold tongue bias, an improved Gulf Stream representation with a reduced coastal warm bias and a reduced subpolar North Atlantic cold bias, and more realistic orographic precipitation over mountain ranges. By contrast, VHR shows a larger warm bias and overly low sea ice extent over the Southern Ocean. Such biases in surface temperature have an impact on the atmospheric circulation aloft, with improved stormtrack over the North Atlantic, yet worsened stormtrack over the Southern Ocean compared to the lower resolution model versions. Other biases persist with increased resolution from LR to VHR, such as the warm bias over the tropical upwelling region and the associated cloud cover underestimation, and the precipitation excess over the tropical South Atlantic and North Pacific. VHR shows improved air-sea coupling over the tropical region, although it tends to overestimate the oceanic influence on the atmospheric variability at mid-latitudes compared to observations and LR and HR. Together, these results highlight the potential for improved simulated climate in key regions, such as the Gulf Stream and the Equator, when the atmospheric and oceanic resolutions are finer than 25 km in both the ocean and atmosphere. Thanks to its unprecedented resolution, EC-Earth3P-VHR offers a new opportunity to study climate variability and change of such areas on regional/local spatial scales, in line with regional climate models
Long-term historical characterization of French vineyard exposure to pests and diseases: a case study of the Bordeaux and Champagne regions
No full textInternational audienceThe French agricultural warning service has historically published weekly reports and annual summaries of key pest and disease pressures (grouped and named “pests” hereafter). The summaries were based on a large number of plots, notably vineyards, monitored in different regions, with different local editions for each region. They constitute a highly valuable corpus of literature on pests' presence and overall damage in vineyards. We used this literature to develop a textual analysis and build an integrative grading system for annual pest occurrence over a long period (1961 to 2020) in the Bordeaux and Champagne regions. To reconstruct the pest occurrences over time in the two regions, we then established a long-term database of annual grades, including various grapevine diseases (mildews, rots, trunk diseases, etc.) and phytophagous or disease vector animals (moths, mites, scale insects, leafhoppers). In this paper, to present and illustrate the new methodology, we focus on two contrasting types of pests, i. e., two grape berry moth species (Lobesia botrana and Eupoecilia ambiguella) and two fungal diseases (rotbrenner and black rot). This tool can be very useful for characterizing the epidemiological status of various years and analysing long-term trends versus isolated events. This will allow us to better understand past pest evolutions and link them to biotic and/or abiotic contexts. This will help anticipate the necessary evolution of grapevine protection against quantitative and/or qualitative losses and adapt to global changes and regulatory or marketing evolutions
Intake of sugar sweetened beverages among children and adolescents in 185 countries between 1990 and 2018: population based study
No full textInternational audienceObjectiveTo quantify global intakes of sugar sweetened beverages (SSBs) and trends over time among children and adolescents. Design Population based study. SettingGlobal Dietary Database. PopulationChildren and adolescents aged 3-19 years in 185 countries between 1990 and 2018, jointly stratified at subnational level by age, sex, parental education, and rural or urban residence. ResultsIn 2018, mean global SSB intake was 3.6 (standardized serving=248 g (8 oz)) servings/week (1.3 (95% uncertainly interval 1.0 to 1.9) in south Asia to 9.1 (8.3 to 10.1) in Latin America and the Caribbean). SSB intakes were higher in older versus younger children and adolescents, those resident in urban versus rural areas, and those of parents with higher versus lower education. Between 1990 and 2018, mean global SSB intakes increased by 0.68 servings/week (22.9%), with the largest increases in sub-Saharan Africa (2.17 servings/week; 106%). Of 185 countries included in the analysis, 56 (30.3%) had a mean SSB intake of ≥7 servings/week, representing 238 million children and adolescents, or 10.4% of the global population of young people. ConclusionThis study found that intakes of SSBs among children and adolescents aged 3-19 years in 185 countries increased by 23% from 1990 to 2018, parallel to the rise in prevalence of obesity among this population globally. SSB intakes showed large heterogeneity among children and adolescents worldwide and by age, parental level of education, and urbanicity. This research should help to inform policies to reduce SSB intake among young people, particularly those with larger intakes across all education levels in urban and rural areas in Latin America and the Caribbean, and the growing problem of SSBs for public health in sub-Saharan Africa
TomoSAR: Unlocking Magnitude 7.8 Turkey Earthquake and its free scientific service
No full textInternational audienceFollowing the 7.8 magnitude earthquake that struck Turkey and Syria on February 6, 2023, TomoSAR, an extensive software designed for SAR image processing, demonstrated its effectiveness in assessing land subsidence. It provided the initial three-dimensional displacement data, marking a significant milestone in this field. Notably, TomoSAR stands out as the first publicly accessible tool capable of jointly processing Persistent and Distributed Scatterers (https://github.com/DinhHoTongMinh/TomoSAR). Continual efforts are underway to elevate TomoSAR’s accessibility and performance. This involves integrating algorithms into a parallel version to facilitate enhanced performance and open avenues for complimentary scientific services at no cost
A new species of planthopper in the genus Paraphenice (Hemiptera: Derbidae: Otiocerinae) from palms in eastern Madagascar
No full textInternational audienceA survey of planthoppers associated with palms in Madagascar was initiated to assess putative vectors of a phytoplasma causing palm decline. Here a derbid collected from a Chinese fan palm (Livistona chinensis) is described as Paraphenice fluctus sp. n., with supplemental molecular data for the cytochrome c oxidase subunit I (COI) gene, 18S rRNA gene, and D9–D10 expansion region of the 28S rRNA gene
Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States
No full textInternational audienceUnderstanding the cooling service provided by vegetation in cities is important to inform urban policy and planning. However, the performance of decision-support tools estimating heat mitigation for urban greening strategies has not been evaluated systematically. Here, we further develop a calibration algorithm and evaluate the performance of the urban cooling model developed within the open-source InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) software. The urban cooling model estimates air temperature reduction due to vegetation based on four predictors, shade, evapotranspiration, albedo, and building density, and was designed for data-rich and data-scarce situations. We apply the calibration algorithm and evaluate the model in two case studies (Paris, France, and Minneapolis–St Paul, USA) by examining the spatial correlation between InVEST predictions and reference temperature data at a 1 km horizontal resolution. In both case studies, model performance was high for nighttime air temperatures, which are an important indicator of human wellbeing. After calibration, we found medium performance for surface temperatures during daytime but low performance for daytime air temperatures in both case studies, which may be due to model and data limitations. We illustrate the model adequacy for urban planning by testing its ability to simulate a green infrastructure scenario in the Paris case study. The predicted air temperature change compared well to that of an alternative physics-based model (r2=0.55 and r2=0.85 for daytime and nighttime air temperatures, respectively). Finally, we discuss opportunities and challenges for the use of such parsimonious decision-support tools, highlighting their importance to mainstream ecosystem services information for urban planning
