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  • Rural Digital Europe
  • 2023-2023
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Nakamura, Shoko; Taki, Hisatomo; Arai, Tomonori; Funayama, Ken; +20 Authors

    Table S5 The numbers of visitors in each taxa collected from each site and year

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    ZENODO
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      ZENODO
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    Authors: Oskolski, Alexei A.; Akinlabi, Funmilade M.;

    Table A1. Wood anatomical traits for the plant species occurred in fynbos vegetation. This table can be accessed atTable A2. Wood samples of Thymelaeaceae from the Cape Floristic Region examined in the present study.Table A3. Average values of wood anatomical traits for the plant genera occurred in fynbos vegetation.Table A4. Quantitative wood traits of some species from Israel maquis and batha estimated from the micrographs published by Fahn et al. (1986).

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  • Authors: Tresch, Simon; Braun, Sabine; Hopf, Sven-Eric;

    The IAP has been monitoring forest health since 1984 on behalf of cantonal forest and environmental offices and in collaboration with the Federal Office for the Environment. In the Intercantonal Forest Observation Program (WDB) project, the health, growth and nutrient supply of beech, spruce and oak in managed forest ecosystems are studied on about 190 forest plots. The plots cover the most important gradients of Swiss forests, such as different climatic conditions in precipitation, temperature, as well as differences in soil and in the input of air pollutants such as nitrogen and ozone. Currently (date 2020) 94 plots with 6268 beech trees, 75 plots with 4547 spruce trees, and 50 plots with 1858 oak trees are surveyed in the Intercantonal WDB. Annual investigations include crown condition and tree loss by mortality, uprooting and stem breakage. Every 4 year stem increment is measured on all 12’673 trees and 8 branches are harvested by helicopter very 4 years and subsequently examined for the following parameters: - Nutrient analysis in foliage (N, P, K, Ca, Mg, Mn) - Leaf area and weight - Shoot growth (retrospective for Norway spruce, beech and oak) - Discoloration and parasite infestation - Fructification of beech (retrospectively) In addition, soil samples for analysing the chemistry of the solid phase are taken every 12 years. Also changes in the ground vegetation is assessed every 12 years. On a subset of the plots soil solution is sampled monthly *[(Soil solution monitoring of the Intercantonal Forest Observation Program)](https://www.envidat.ch/dataset/soil-solution-monitoring-of-the-intercantonal-forest-observation-program)*. In addition, soil water potential and soil moisture are measured in a subset of sites of the Intercantonal Forest Observation Program *[(Soil moisture and soil water potential measurements of the Intercantonal Forest Observation Program)](https://www.envidat.ch/dataset/soil-water-measurements-wdb)*. These data allow to gain a unique understanding of the main factors influencing the forest and the most important changes, which are very valuable especially in the context of climate change. The insights are of great importance for cantonal and regional forest planning as well as for national and international determinations of critical loads and limits (e.g. CLempN, UNECE CLRTAP).

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    B2FIND
    Dataset . 2023
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    Environmental Data Portal
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      B2FIND
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    Authors: Xiao Zhiqiang;

    The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 500m spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2018 (continuously updated). It was generated from the MUSES LAI product at 500m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao et al., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2009. Please click here to download the MUSES FVC product in 2008, and click here to download the MUSES FVC product in 2010. Dataset Characteristics: Spatial Coverage: Global Temporal Coverage: 2009 Spatial Resolution: 500m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 Citation (Please cite this paper whenever these data are used): Xiao Zhiqiang, et al. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. Remote Sensing, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).

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    ZENODO
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    ZENODO
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      ZENODO
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      ZENODO
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    Authors: Statistics Canada | Statistique Canada;

    Statistiques de porcs, nombre de porcs par catégorie selon une période semestrielle, États-Unis et Canada (tête x 1 000). Les données sont disponibles sur une base semestrielle. Hogs and pigs statistics, inventory number by class and semi-annual period, United States and Canada (head x 1,000). Data are available on a semi-annual basis.

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  • Authors: Mutualité Sociale Agricole (MSA);

    Données sur les pensionnés non-salariés du régime agricole

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    Authors: Esmaeilzadeh-Salestani, Keyvan; Tohidfar, Masoud; Ghanbari Moheb Seraj, Rahele; Khaleghdoust, Banafsheh; +3 Authors

    Additional file 12: Fig. S12 GO Enrichment Histogram of top 20 enriched terms associated with DEGs of Org2 vs. N2 in biological processes (BP) (A), molecular functions (MF) (B), and cellular components (CC) (C); Org2 vs. Org0 in BP (D), MF (E), and CC (F).

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    Authors: Wood, Eric; Coffey, Julie; Pomara, Lars; Mackey, Heather;

    Sampling design We used a space-for-time sampling design, sampling within the available floodplain area to capture conditions in unburned locations with and without giant reed and burned locations at different times since the last burn. We identified 167 sites distributed throughout the Rio Grande floodplain in BIBE, ranging from Santa Elena Canyon in the western portion of the park to Boquillas Canyon in the east. We used the following criteria to assign sites into 4 management groups, which we used for the basis of our analyses. We used the group recent (n = 21) for sites burned ≤3 years before sampling. These were characterized by bare ground, sparse vegetation, and some resprouting giant reed. The group older (n = 19) described sites burned ≥4 years before sampling. These were characterized by the regrowth of riparian vegetation and some resprouting giant reed. We used the group unburned floodplain (n = 16) for unburned, non-forest sites without significant giant reed cover (<3% cover). We used this group to characterize typical non-forest floodplain conditions. Of the original 167 sites, our analysis included 73 that met the above criteria. The additional 94 sites were primarily in more upland forested floodplain sites (principally honey mesquite gallery forest), which, as previously indicated, was not a target of the management activities Butterfly and bird surveys We surveyed birds and butterflies at each site from May to July 2016 and 2017. We conducted 3 counts at each site each year, with a fourth butterfly count in 2017 to capture mid-summer monsoonal activity. We used 5-minute point counts to record all birds detected by sight or sound within a 100-m radius. To survey butterflies, we established 10 × 100-m belt transects, centered at a bird point count location and oriented approximately parallel to the river. An observer slowly walked the centerline, recording butterflies within a 5-m grid of the observer. Habitat characterization: remote sensing and field surveys We quantified habitat characteristics in the floodplain using a cloud-free NAIP color-infrared air photo mosaic with 1-m2 spatial resolution collected in 2016 (Figure 2). From this image, we computed a vegetation greenness index (the normalized difference vegetation index [NDVI]). We calculated NDVI for each image pixel, then computed the mean value within each 100-m bird survey radius, excluding water pixels. We also computed image texture as the second-order standard deviation of NDVI, capturing the variability in pixel value greenness across a defined area. We first calculated the standard deviation of pixel values within a 5 × 5-pixel moving window and assigned this value to the center pixel. We then calculated the standard deviation of those values within the 100-m survey radius. We computed the NDVI and habitat heterogeneity calculations using the image analysis and focal stats tools in ArcGIS 10.5.1. To quantify the cover of vegetation classes from the NAIP image, we first defined 4 classes that broadly characterized floodplain vegetation and were relevant for giant reed management and for quantifying riparian wildlife habitat use. These classes were giant reed, xeric woody vegetation, mesic woody vegetation, and low herbaceous vegetation (i.e., forbs and grasses, excluding giant reed). The cover of grass and forb vegetation are important butterfly habitat features that were difficult to distinguish from one another with remote sensing. Therefore, we included these 2 ground-based habitat measures in butterfly analyses, replacing the image-based herbaceous cover estimates. We estimated the proportional cover of forbs and grasses (excluding giant reed) within the butterfly transects by visual estimation in the field using a relevé method. Observers walked the length of each transect and sketched the cover of grass and forb vegetation within the 5-m gridded rectangular outline of the transect, from which we estimated cover. Giant reed (Arundo donax) is a prevalent invasive plant in desert riparian ecosystems that threatens wildlife habitat. From 2008 to 2018, under a United States–Mexico partnership, prescribed burns and herbicide applications were used to remove giant reed and promote native revegetation along the Rio Grande – Río Bravo floodplain in west Texas, USA, and Mexico. Our goal was to explore the effects of the removal efforts on butterfly and bird communities and their habitat along the United States portion of the Rio Grande – Río Bravo floodplain in Big Bend National Park, Texas. During spring and summer, 2016–2017, we surveyed butterflies, birds, and their habitat using ground-collected and remotely sensed data. Using a variety of generalized linear and N-mixture modeling routines and multivariate analyses, we found that the initial giant reed removal efforts removed key components of riparian habitat leading to reduced butterfly and bird communities. Within several years following management, giant reed levels remained low, while riparian habitat conditions and butterfly and bird communities largely rebounded, including many disturbance-sensitive butterfly species and riparian-associated bird species. Butterflies were most consistently associated with forb and grass cover, and birds with a remotely sensed index of greenness (the normalized difference vegetation index), several vegetation cover types, and habitat heterogeneity, habitat elements that were most common in locations that had the longest time to recover following management actions. Our results suggest that prescribed burns and herbicide applications, when used following protocols to minimize risk to wildlife, can limit the spread of giant reed in desert riparian systems and introduce habitat conditions that support diverse and abundant butterfly and bird communities. We used R for all data analyses. We have attached R files, with code, adjoining the datasets used for analyses related to our objectives. R Core Team. 2017. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

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    DRYAD; ZENODO
    Dataset . 2023
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      DRYAD; ZENODO
      Dataset . 2023
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    Authors: Oscar Barberà; Davide Vittori;

    Oscar Barberà recieved a Recualifica grant from the Spanish Government and the University of Valencia for a stay at the ESPOL-LAB of the Universityé Catholique de Lille (RC21-012). This project has also been funded through the grant AICO-2020-202 of the Valencian Regional Government and the grant UV-INV_AE-2631662 from the University of Valencia. Dataset with R replication file for the paper: Approaching the Unknown. COVID-19 pandemic, political parties and digital adaptations: party élites' perceptions in Italy and Spain

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    ZENODO
    Dataset . 2023
    License: CC BY
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    ZENODO
    Dataset . 2023
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      Dataset . 2023
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      Dataset . 2023
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  • Authors: Autret, Emmanuelle; Jean-François Piollé;

    This dataset provide a times series of daily multi-sensor composite fields of Sea Surface Temperature (SST) foundation at ultra high resolution (UHR) on a 0.02 x 0.02 degree grid (approximately 2 x 2 km) over Mediterranean Sea, every 24 hours. Whereas along swath observation data essentially represent the skin or sub-skin SST, the L3S SST product is defined to represent the SST foundation (SSTfnd). SSTfnd is defined within GHRSST as the temperature at the base of the diurnal thermocline. It is so named because it represents the foundation temperature on which the diurnal thermocline develops during the day. SSTfnd changes only gradually along with the upper layer of the ocean, and by definition it is independent of skin SST fluctuations due to wind- and radiation-dependent diurnal stratification or skin layer response. It is therefore updated at intervals of 24 hrs. SSTfnd corresponds to the temperature of the upper mixed layer which is the part of the ocean represented by the top-most layer of grid cells in most numerical ocean models. It is never observed directly by satellites, but it comes closest to being detected by infrared and microwave radiometers during the night, when the previous day's diurnal stratification can be assumed to have decayed. The processing combines the observations of multiple polar orbiting and geostationary satellites, embedding infrared of microwave radiometers. All these sources are intercalibrated with each other before merging. A ranking procedure is used to select the best sensor observation for each grid point. The processing is the same (minus the optimal interpolation step) as for the Atlantic Near Real Time (NRT) L3S dataset available on Copernicus Marine Service [SST_ATL_PHY_L3S_NRT_010_037 dataset] and users can refer to the user manual and quality documents available there for more details. This dataset is generated daily within a 24 delay and is therefore suitable for assimilation into operational models.

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    Authors: Nakamura, Shoko; Taki, Hisatomo; Arai, Tomonori; Funayama, Ken; +20 Authors

    Table S5 The numbers of visitors in each taxa collected from each site and year

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      ZENODO
      Dataset . 2023
      License: CC 0
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    Authors: Oskolski, Alexei A.; Akinlabi, Funmilade M.;

    Table A1. Wood anatomical traits for the plant species occurred in fynbos vegetation. This table can be accessed atTable A2. Wood samples of Thymelaeaceae from the Cape Floristic Region examined in the present study.Table A3. Average values of wood anatomical traits for the plant genera occurred in fynbos vegetation.Table A4. Quantitative wood traits of some species from Israel maquis and batha estimated from the micrographs published by Fahn et al. (1986).

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    Dataset . 2023
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    Data sources: Datacite
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    Dataset . 2023
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  • Authors: Tresch, Simon; Braun, Sabine; Hopf, Sven-Eric;

    The IAP has been monitoring forest health since 1984 on behalf of cantonal forest and environmental offices and in collaboration with the Federal Office for the Environment. In the Intercantonal Forest Observation Program (WDB) project, the health, growth and nutrient supply of beech, spruce and oak in managed forest ecosystems are studied on about 190 forest plots. The plots cover the most important gradients of Swiss forests, such as different climatic conditions in precipitation, temperature, as well as differences in soil and in the input of air pollutants such as nitrogen and ozone. Currently (date 2020) 94 plots with 6268 beech trees, 75 plots with 4547 spruce trees, and 50 plots with 1858 oak trees are surveyed in the Intercantonal WDB. Annual investigations include crown condition and tree loss by mortality, uprooting and stem breakage. Every 4 year stem increment is measured on all 12’673 trees and 8 branches are harvested by helicopter very 4 years and subsequently examined for the following parameters: - Nutrient analysis in foliage (N, P, K, Ca, Mg, Mn) - Leaf area and weight - Shoot growth (retrospective for Norway spruce, beech and oak) - Discoloration and parasite infestation - Fructification of beech (retrospectively) In addition, soil samples for analysing the chemistry of the solid phase are taken every 12 years. Also changes in the ground vegetation is assessed every 12 years. On a subset of the plots soil solution is sampled monthly *[(Soil solution monitoring of the Intercantonal Forest Observation Program)](https://www.envidat.ch/dataset/soil-solution-monitoring-of-the-intercantonal-forest-observation-program)*. In addition, soil water potential and soil moisture are measured in a subset of sites of the Intercantonal Forest Observation Program *[(Soil moisture and soil water potential measurements of the Intercantonal Forest Observation Program)](https://www.envidat.ch/dataset/soil-water-measurements-wdb)*. These data allow to gain a unique understanding of the main factors influencing the forest and the most important changes, which are very valuable especially in the context of climate change. The insights are of great importance for cantonal and regional forest planning as well as for national and international determinations of critical loads and limits (e.g. CLempN, UNECE CLRTAP).

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    Environmental Data Portal
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    Authors: Xiao Zhiqiang;

    The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 500m spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2018 (continuously updated). It was generated from the MUSES LAI product at 500m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao et al., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2009. Please click here to download the MUSES FVC product in 2008, and click here to download the MUSES FVC product in 2010. Dataset Characteristics: Spatial Coverage: Global Temporal Coverage: 2009 Spatial Resolution: 500m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 Citation (Please cite this paper whenever these data are used): Xiao Zhiqiang, et al. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. Remote Sensing, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).

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    ZENODO
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    Authors: Statistics Canada | Statistique Canada;

    Statistiques de porcs, nombre de porcs par catégorie selon une période semestrielle, États-Unis et Canada (tête x 1 000). Les données sont disponibles sur une base semestrielle. Hogs and pigs statistics, inventory number by class and semi-annual period, United States and Canada (head x 1,000). Data are available on a semi-annual basis.

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  • Authors: Mutualité Sociale Agricole (MSA);

    Données sur les pensionnés non-salariés du régime agricole

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