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11 results for “EJP SOIL”
SERENA EJP Soil: Green House Gas Regulation Application Emilia-Romagna, Italy (Summer)
<p>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.</p>
SERENA EJP Soil - Map of Soil Sealing of Italy
<p>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.</p>
SERENA EJP Soil: Bundles' cookbook exemplary datasets
<p>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.</p>
SERENA EJP Soil Green house gas aplication Moravia region, Czechia
<p>The present dataset corresponds to a map of Net Ecosystem Productivity (NEP) for Moravia region in Czechia classified as wheat by the Eurocrop 2028 spatial product (d’Andrimont et al. 2021). The map is the result of applying the NEP cookbook developed in SERENA/EJP-Soil to the area of interest (AOI) input data. NEP is expressed for a single 8-day period in early summer as it is the date with the highest value. The NEP value is a 2010-2014 average for the particular 8-day period. The data description document of the cookbook (hereafter “GHG cookbook”) itself corresponds to other document of the SERENA project.</p>
TUdi-Vinedivers_EJP_Vineyard_Soil_Data_Europe
<p>Dataset of soil properties (soil organic carbon contents and soil physical parameters) of vineyard topsoil samples from the TUdi/Vinedivers/EJP Soil vineyard inter-row management study in European vineyard regions.</p>
Soil grid data for agricultural fields in Spain for STEROPES (EJP Soil) project (ECe, texture, soil organic carbon, pH)
<p><span>Soil data collected in an agricultural area with vegetable crops in Spain (Campo de Cartagena). The data refers to soil properties of 141 soil samples collected at a depth of 0-10 cm, considering a regular sampling grid, in different commercial fields with varying soil salinity. The samples were collected at a period when the soil was bare, during two consecutive summers, following the harvest of the annual crops, and pictures of the soil surface were taken for eventual correction of corresponding remote sensing imaging. The data includes: soil organic carbon (SOC) (Walkley-Black method), soil water content, electric conductivity of the saturated soil paste (ECe), EC1:5, soil texture, stone content and pH1:2.5. </span></p> <p><span> </span></p> <p><span>The data may be representative of the soil conditions of the area, which is an intensive productive agricultural low land, potentially prone to the development of soil salinity as a result of the rise of saline groundwater and/or irrigation. The data can be used to establish relations between soil salinity (ECe) and other soil properties as well as build prediction models of the soil properties from remote sensing namely, for developing models for SOC prediction under the STEROPES project (WP3, WP5 and WP6).The aim of the collected dataset was to be able to analyze the influence of soil salinity in SOC prediction from remote sensing.</span></p> <p><span> </span></p> <p><span>Data in the form of MS Excel file (xlsx).</span></p> <p><span> </span></p> <p><span> </span></p>
A stocktaking of European mid- and long-term experiments dealing with the application of external organic matter (EJP SOIL - EOM4SOIL - D 3.1.1)
<p>Extending and optimizing recycling of organic wastes in agriculture is a key element in shifting conventional agriculture towards systems adapted to both energy depletion and climate change. Long-term field experiments (LTEs) play a crucial role in assessing and modelling the effects of repeated exogenous organic matter (EOM) application to soil, which allows to formulate locally adapted recommendations of use. <br>Nevertheless, a specific database focussing on LTEs dealing with organic fertilization in Europe were missing. To close this gap, we listed LTEs dealing with repeated application of EOM from existing online databases, and collected and harmonized all available metadata. The aim of this work was threefold: (1) to facilitate connections between comparable LTEs to foster data harmonization and compilation, (2) to map the diversity of pedoclimatic contexts and experimental designs in the LTE list and, (3) to highlight current knowledge gaps and research needs. <br>Data were collected from five online databases, allowing us to describe 201 LTEs. Key characteristics such as trial name, responsible institution, location, pedoclimatic context, duration, crop type and availability of online resources are well-described in contrast to LTE goal and owner contact, experimental design, soil type, studied EOM and monitored parameters (EOM characteristics, soil and crop properties), which are more difficult to gather and harmonize. The analysis of LTE metadata highlighted first that substantial harmonization efforts are required, particularly regarding the reporting of soil, crop and EOM properties over time. Second, the survey outlines that some European regions are poorly represented in the database, which may result either from an absence of LTE or from a lack of reporting. To close this gap, we call LTE managers to complete the current database with any missing relevant LTE or additional metadata, using the editable online repository attached to this document. In the future, improvement of predictive models could contribute to provide recommendations of EOM use to uncovered situations, whether in terms of soil, climate or type of EOM. Third, long-term effects on soil properties such as changes in soil biology composition or accumulation of organic contaminants (PFAS, microplastics, antibiotics, ...) appear to be poorly documented. LTEs have a key role to play in answering these emerging questions, having the potential to provide the rationale to fix acceptable thresholds in soils and EOMs for emerging pollutants and accordingly provide the best possible guidelines for the use of EOM in agriculture. </p> <p>See related report at <a href="https://doi.org/10.5281/zenodo.14161379" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.14161379</a>.</p>
EJP Soil BioCASH: Deliverable 2.3
<p>EJP Soil BioCASH Deliverable 2.3: Refers to samples collected modelling data in BioCASH. </p>
Biodiversity data and associated data from the EJP-Soil Minotaur project
<p>The dataset concerns data on biodiversity and associated measured data collected within the Minotaur project, an internal projet of EJP-Soil.</p>
EJP SensRes bi-directional reflectance of soils
<div> <p><span><span>Repository of the </span></span><span><span>d</span></span><span><span>atabase of bi-directional soil spectral </span></span><span><span>reflectance </span></span><span><span>measurements and </span></span><span><span>the </span></span><span><span>corresponding </span><span>physico</span></span><span><span>-</span></span><span><span>chemical variables for soil carbon estimation. </span></span></p> </div> <div> <p><span><span>Soil samples from the chemistry laboratory </span></span><span><span>were</span></span><span><span> prepared for the spectral measurements</span></span><span><span> that were carried ou</span></span><span><span>t</span></span><span><span> using a </span></span><span><span>full-range </span></span><span><span>PSR-3500 </span></span><span><span>spectrometer</span></span><span><span> in the range 350-2500 nm</span></span><span><span>.</span></span> <span><span>The spectral sensor was mounted on a robotic arm to perform a regular </span></span><span><span>sampling strategy involving multiple</span></span><span><span> viewing</span></span><span><span> angles and different soil water contents</span></span><span><span>. </span></span><span> </span></p> </div> <div> <p><span><span>Three main datasets were </span></span><span><span>compiled,</span></span><span><span> and they </span></span><span><span>are</span></span><span><span> summarized in Table 1 in the related .doc document</span></span><span><span>. </span></span></p> </div>
EJP SOIL C-arouNd - (Meta)data of Long-term field experiments (LET)
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