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500 results for “semi-arid”
FIGURE 1. A–D in Annotated checklist of Cerambycidae (Coleoptera: Chrysomeloidea) from the Brazilian semi-arid region, with new species and new geographic records
FIGURE 1. A–D, Collection area in Fazenda Lagoa do Tamburi, Aracatu, Bahia, Brazil A, View of the vegetation around the weir located near the farmhouse; B, View of the dry forest area in the farm; C, Temporary stream in the dry forest area of the farm; D, Malaise trap in the dry forest area of the farm during the rainy season.
FIGURE 8. A–F in Annotated checklist of Cerambycidae (Coleoptera: Chrysomeloidea) from the Brazilian semi-arid region, with new species and new geographic records
FIGURE 8. A–F, Pseudomecas mourai sp. nov., holotype female: A–C, Dorsal, lateral, and ventral views; D, Head and pronotum, dorsal view; E, Head, ventral view; F, Head, frontal view; G, Labels.
FIGURE 5. A–F in Annotated checklist of Cerambycidae (Coleoptera: Chrysomeloidea) from the Brazilian semi-arid region, with new species and new geographic records
FIGURE 5. A–F, Species of Eburodacrys White, 1853, dorsal view: A, E. catarina Galileo & Martins, 1992, paratype, female (MZUSP); B, E. eburioides (White, 1853), male, Matelandia, Paraná, Brazil (MZUSP); C, E. flexuosa Gounelle, 1909, male, Buena Vista, Santa Cruz, Bolivia (MZUSP); D, E. lancinata Napp & Martins, 1980, holotype, female (MZUSP); E, E. lenkoi Napp & Martins, 1980, holotype, male (MZUSP); F, E. tuberosa Gounelle, 1909, syntype, female, Goiás, Brazil (MZUSP).
FIGURE 6. A–D in Annotated checklist of Cerambycidae (Coleoptera: Chrysomeloidea) from the Brazilian semi-arid region, with new species and new geographic records
FIGURE 6. A–D, Coccoderus costae sp. nov. Holotype female: A–C, Dorsal, lateral, and ventral views; D, Head and prothorax (dorsal view); E, Labels. F, Coccoderus sexmaculatus Buquet, 1840, female, dorsal view, Itatiaia, Rio de Janeiro, Brazil (MZUSP).
FIGURE 4. A–F in Annotated checklist of Cerambycidae (Coleoptera: Chrysomeloidea) from the Brazilian semi-arid region, with new species and new geographic records
FIGURE 4. A–F, Eburodacrys boteroi sp. nov., holotype female: A–C, Dorsal, lateral, and ventral views; D, Head and prothorax (dorsal view); E, Head (frontal view); F, Mesofemur and metafemur, laterofrontal view; G, Labels. Legend: tb = tubercles; ls = lateral spine
FIGURE 3. A–C in Annotated checklist of Cerambycidae (Coleoptera: Chrysomeloidea) from the Brazilian semi-arid region, with new species and new geographic records
FIGURE 3. A–C, Cerambycidae of the Brazilian semi-arid region. A, Richness in (%) of subfamilies of Cerambycidae of the Brazilian semi-arid region; B, Species richness to the tribes of Cerambycinae of the Brazilian semi-arid region; C, Species richness to the tribes of Lamiinae of the Brazilian semi-arid region.
FIGURE 2. A–C in Annotated checklist of Cerambycidae (Coleoptera: Chrysomeloidea) from the Brazilian semi-arid region, with new species and new geographic records
FIGURE 2. A–C, Collection area in Fazenda Rancho Alto, Cavunge, Ipecaetá, Bahia, Brazil: A, View of the vegetation in the farm during the rainy season; B, View of the light trap in the dry forest area in the farm; C, Ampliated view of the dry forest area of the farm during the rainy season.
Data of Semi-Arid Climate and Environment Observatory Station of Lanzhou University (SACOL) (2019.12.09-2021.12.31)
<p><strong>Data Description</strong></p> <p>The PM<sub>2.5</sub> mass concentrations were observed by using a tapered element oscillating microbalance machine (TEOM, Model RP-1400A, Thermo Scientific, USA) with a temporal resolution of 1 minute. An aethalometer (Model AE31, Magee Scientific, USA) with a PM<sub>2.5</sub> inlet was used to measure the aerosol light absorption coefficients at 370, 470, 520, 590, 660, 880, and 950 nm. Aerosol scattering coefficients of PM<sub>2.5</sub> at 450, 550, and 700 nm wavelengths were observed by using an integrating nephelometer (Model 3563, TSI, USA) with a time resolution of 10 seconds. The micro-pulse lidar was installed approximately 50 m north of the tethered balloon observation site and used to observe atmospheric echoes within 20 km vertically and then invert parameters such as the aerosol σ and aerosol optical depth. The detailed parameters of lidar are shown in Table 1.</p> <p>A tethered balloon (volume: 10 m<sup>3</sup>; payload: 8 kg) was used to carry the following equipment: (1) MA200 micro-aethalometer (Magee Scientific, USA), (2) TSI 9306 optical particle counter (OPC, TSI, USA), (3) KZXLT-II sounding system from the Institute of Atmospheric Physics, and (4) GPSMAP 639sc GPS (GARMIN, USA). Sounding observations were made at 02:00, 08:00, 11:00, 14:00, 17:00, and 20:00 each day from December 9 to 31, 2019. A total of 91 vertical profiles were obtained for each of the available absorbing aerosols, particle number concentrations, and meteorological parameters.</p> <p>The MA200 measures light absorption at 5 wavelengths (375, 470, 528, 625 and 880 nm), and a dual-spot® compensation for loading effect correction is available. The MA200 observations have been converted to 550 nm in this data based on the AAE during the observation period. OPC was used to measure the particle number concentrations and particle number size distribution in the 0–10 μm size range. The temporal resolutions of MA200 and OPC were ~ 10 s, and their vertical resolutions were ~ 10 m. KZXLT-II sounding system was used to measure the vertical distribution of meteorological elements. GPS was used to measure real-time altitude.</p> <p> </p> <p><strong>Table 1.</strong> Main parameters of micro-pulse lidar</p> <table> <tbody> <tr> <td> <p>Projects</p> </td> <td> <p>Parameters</p> </td> </tr> <tr> <td> <p>Detector</p> </td> <td> <p>Avalanche laser APD, photon counting model</p> </td> </tr> <tr> <td> <p>Observation band</p> </td> <td> <p>532 nm</p> </td> </tr> <tr> <td> <p>Pulse frequency</p> </td> <td> <p>2500 Hz</p> </td> </tr> <tr> <td> <p>Pulse energy</p> </td> <td> <p>3~4 µJ</p> </td> </tr> <tr> <td> <p>Maximum observation range</p> </td> <td> <p>15 km</p> </td> </tr> <tr> <td> <p>Time resolution</p> </td> <td> <p>1 min</p> </td> </tr> <tr> <td> <p>Vertical Resolution</p> </td> <td> <p>30 m</p> </td> </tr> </tbody> </table> <p> </p>
CROSMOD project "Crop Stress Monitoring in the semi-arid context of Doukkala, Morocco" supported by ESA and AUC in the framework of EO AFRICA R&D Facility
<p>The CROSMOD project “Crop Stress Monitoring in the semi-arid context of Doukkala, Morocco” supported by ESA and AUC in the framework of EO AFRICA R&D Facility, aimed at developing a procedure for crop yield estimates and extreme events crops shocks monitoring or pest and diseases by integrating multiple satellite data and water-energy-crop modelling, able to support farmers precision agriculture for the case of the Doukkala Irrigation area in Morocco. <strong>The project was run by: Chiara Corbari and Nicola Paciolla from Politecnico di Milano (Italy); and Fatima-ezzahra Elghandour and Youssef Houali from Chouaib Doukkali University (Morocco).</strong></p> <p>The dataset report the results from the three case studies, which are cultivated fields with alfalfa, sugar beet and wheat in Morocco (LE, H, net radiation, land surface temperature, ET, potential irrigation, LAI, soil moisture) generated from FEST-EWB-SAFY model.</p> <p>The crop-energy-water balance FEST-EWB-SAFY model (Corbari et al., 2022) couples the distributed energy-water balance FEST-EWB (Corbari et al, 2011), which allows computing continuously in time and distributed in space both soil moisture and evapotranspiration fluxes, and the SAFY (Duchemin et al, 2008), simple model for yield prediction and plant development. FEST-EWB is based on the system of energy-water balances equations which are written in terms of a LST that allows closing the energy balance equation, so that this model internal variable can be directly compared with EO LST for model parameters calibration (Corbari & Mancini, 2014). The crop growth simple model (SAFY) (Duchemin et al, 2008) simulate yield and LAI prediction based on light-use efficiency theory with leaf partitioning function.</p> <p><strong>The code was developed by Chiara Corbari and Nicola Paciolla from Politecnico di Milano (Italy).</strong></p> <p>[1] Corbari, C., Ravazzani, G. and Mancini, M. (2011), A distributed thermodynamic model for energy and mass balance computation: FEST–EWB. Hydrol. Process., 25: 1443-1452. <a href="https://doi.org/10.1002/hyp.7910">https://doi.org/10.1002/hyp.7910</a></p> <p>[2] Corbari, C., Ben Charfi, I., Al Bitar, A., Skokovic, D., Sobrino, J.A., Perelli, C., Branca, G., Mancini, M. (2022), A fully coupled crop-water-energy balance model based on satellite data for maize and tomato crops yield estimates: The FEST-EWB-SAFY model, Agr. Wat. Man., 272: 107850. <a href="https://doi.org/10.1016/j.agwat.2022.107850%5Cn">https://doi.org/10.1016/j.agwat.2022.107850\n</a></p> <p>[3] Corbari, C., Mancini, M., 2014. Calibration and validation of a distributed energy water balance model using satellite data of land surface temperature and ground discharge measurements. J. Hydrometeorol. 15, 376–392. <a href="https://doi.org/10.1175/JHM-D-12-0173.1">https://doi.org/10.1175/JHM-D-12-0173.1</a></p> <p>[4] Duchemin, B., Maisongrande, P., Boulet, G., Benhadj, I., 2008. A simple algorithm for yield estimates: Evaluation for semi-arid irrigated winter wheat monitored with green leaf area index. Environ. Modell. Softw. 23(7), 876-892. <a href="https://doi.org/10.1016/j.envsoft.2007.10.003">https://doi.org/10.1016/j.envsoft.2007.10.003</a></p>
The dataset for water vapor research in margin of desert, arid and semi-arid area in northwestern China
<p>The dataset for water vapor research in margin of desert, arid and semi-arid area in northwestern China</p>
Data from: Shrub encroachment can reverse desertification in semi-arid Mediterranean grasslands
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Data from: Columnar cacti as sources of energy and protein for frugivorous bats in a semi-arid ecosystem
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Data from: Comparative analysis indicates historical persistence and contrasting contemporary structure in sympatric woody perennials of semi-arid south-west Western Australia
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Data from: Biological soil crusts modulate nitrogen availability in semi-arid ecosystems: insights from a Mediterranean grassland
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Data from: Protected areas buffer the Brazilian semi-arid biome from climate change
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Supporting Data and Code for "Managing to Climatology: Improving semi-arid agricultural risk management using crop models and a dense meteorological network"
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Data from: Thresholds and gradients in a semi-arid grassland: long-term grazing treatments induce slow, continuous and reversible vegetation change
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Trade-off between vegetation type, soil erosion control and surface water in global semi-arid regions: A meta-analysis
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Data from: Litter addition decreases plant diversity by suppressing seeding in a semi-arid grassland, Northern China
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Data from: Sorghum and groundnut sole and intercrop nutrient response in semi-arid West Africa
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.