1,721,125 research outputs found

    Modelling of soil organic carbon in the Mediterranean area: A systematic map

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    A general feature of soil health is the sustainment of soil organic carbon (SOC) concentration and its stock. Digital soil mapping (DSM) development allowed for the implementation of soil properties mapping at various spatial and time scales. However, many of these studies were made in temperate or cold environments from central and northern Europe or United States or in stably arid ecosystems of Australia. Geographical information on the SOC are often fragmented, and this does not allow for a comparison on SOC regional variability in contrasting areas. Here a systematic research of peer-reviewed papers in the Web of science (WoS) and Scopus databases was carried out to highlight knowledge gaps in SOC studies in the Mediterranean area. The systematic searches identified 500 articles in WoS and 750 in Scopus, but only few of them were eligible as ad hoc studies. Regarding WoS, after screening, 150 studies were further analysed for inclusion in the map and only 128 included in the final map (1995-2018). From Scopus, only 104 studies were included in the map (1995-2017). Of all the countries around the Mediterranean Basin, report studies on SOC are available for 15 countries, only. Data gaps identified included the absence of long-term monitoring networks in the south of Europe, a scarcity of information from countries on the eastern coast of the Adriatic and Mediterranean sea and almost lack of detailed information on SOC models and maps from north Africa. Model exportation built in neighbourhood countries (e.g. from Sicily, Italy, to northern Tunisia, or Andalusia, Spain, to northern Morocco) are strongly needed

    A simple pipeline for the assessment of legacy soil datasets: An example and test with soil organic carbon from a highly variable area

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    Legacy databases provide unique information on soil properties and act as a guide for the setup of monitoring processes. However, their use requires an evaluation of their drawbacks, especially when aiming to model the soil traits by depth. We set up a procedure for the integration and error correction of a soil legacy database. This database consisted of 6994 records in its original form and 6674 records after correction. These records were collected from 2886 locations in the south of Italy on a 25,711-km2 island (Sicily, Italy). Samples were taken in arable lands (5471 records), orchards, vineyards and seminatural lands (3010 records), and woodland and natural areas (1203 records). The procedure for the integration and error highlighting improved the prediction of soil organic carbon (SOC), and a general linear model with covariate selection by Least Absolute Shrinkage and Selection Operator (LASSO) tested the procedure. We focussed on exploring the amount of legacy information as georeferenced soil properties. SOC and fine earth fractions were analysed for each sample. Bulk density was provided for only 20% of the samples. These results will help to account for the legacy data available and propose an analysis to harmonize an SOC dataset; highlight missing or incorrect data; summarize data; and offer synthesis criteria for benchmarking SOC in different land uses and pedological areas. In addition, the results may stimulate funding bodies to support research in an open data frame, which can be turned into more sustainable use of resources, improved communication between governments and farmers, and the production of standard datasets that meet and facilitate the requirements for regional agro-environmental modelling
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