Documents

Over the years, the JRC has produced many publications. These are found in this section. They have been sub-divided in various categories (see Subcategory buttons below). All more than 440 documents can also be inspected irrespective of the category (see 'All documents' below).

Publications in Journals include more than 280 published papers from the Soil Group in the JRC. Most of the papers refer to the last 7 years (2013-2020). In many cases the papers document the datasets published in ESDAC. Almost all the publications are Open Access. 

 

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European contribution towards a global assessment of agricultural soil organic carbon stocks
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

The chapter discusses a study that predicts the global organic carbon stocks for agricultural soils using European databases with geostatistical analysis and modeling. The overall statistical model consists of two submodels namely donor and donee modules. The donor module uses statistics to quantify the relationships between soil organic carbon (SOC) and environmental covariates. The covariates were selected based on their availability at global scale and their roles as major drivers that affect the carbon cycle in terrestrial ecosystems. Multiple linear regression was used in the donor module with the selected covariates and dense SOC measurements coming from LUCAS soil database (Toth et al., 2013a). The LUCAS soil database has more than 22,000 SOC measurements from European countries and a standardized sampling procedure was used routinely to collect samples of around 0.5 kg of topsoil (0–20 cm) each. The donor module reveals and quantifies the relationships between SOC mass concentration in soil and the predictors to be used in the donee model to extend the prediction at global scale using the same set of predictors. We used the WorldClim dataset (Hijmans et al., 2005), which is comprised of global climate data layers representing long-term conditions for the years from 1950 to 2000. The land cover data were extracted from the GlobCover 2009 (ESA and Universite' Catholique de Louvain, 2010) provided by the European Space Agency (ESA), the terrain parameters were derived from CGIAR-CSI SRTM 90 m Database (Jarvis et al., 2008), the soil layers obtained from Harmonized World Soil Database (FAO/IIASA/ISRIC/ISSCAS/JRC, 2012), and the Normalized Difference Vegetation Index (NDVI) data were obtained from Copernicus Global Land Service Data Portal (Copernicus Global Land Service, 2015). The study yielded promising results which are broadly consistent with similar efforts predicting global agricultural SOC stocks. Our model fits the SOC data well (R2 = 0.35) and preliminary results suggest a global agricultural SOC estimate of 100.34 Pg (Petagrams) in the first 20 cm. The study predicts the global agricultural SOC stocks using a geostatistical approach and the results are consistent with previous studies that used process-based SOC models.

https://www.sciencedirect.com/science/article/pii/S0065211316301183

A New Assessment of Soil Loss Due to Wind Erosion in European Agricultural Soils Using a Quantitative Spatially Distributed Modelling Approach
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017
Field measurements and observations have shown that wind erosion is a threat for numerous arable lands in the European Union (EU). Wind erosion affects both the semi‐arid areas of the Mediterranean region as well as the temperate climate areas of the northern European countries. Yet, there is still a lack of knowledge, which limits the understanding about where, when and how heavily wind erosion is affecting European arable lands. Currently, the challenge is to integrate the insights gained by recent pan‐European assessments, local measurements, observations and field‐scale model exercises into a new generation of regional‐scale wind erosion models. This is an important step to make the complex matter of wind erosion dynamics more tangible for decision‐makers and to support further research on a field‐scale level. A geographic information system version of the Revised Wind Erosion Equation was developed to (i) move a step forward into the large‐scale wind erosion modelling; (ii) evaluate the soil loss potential due to wind erosion in the arable land of the EU; and (iii) provide a tool useful to support field‐based observations of wind erosion. The model was designed to predict the daily soil loss potential at a ca. 1 km2 spatial resolution. The average annual soil loss predicted by geographic information system Revised Wind Erosion Equation in the EU arable land totalled 0·53 Mg ha−1 y−1, with the second quantile and the fourth quantile equal to 0·3 and 1·9 Mg ha−1 y−1, respectively. The cross‐validation shows a high consistency with local measurements reported in literature

https://onlinelibrary.wiley.com/doi/full/10.1002/ldr.2588

Complementing the top soil information of the Land Use/Land Cover Area Frame Survey (LUCAS) with modelled N2O emissions
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

Two objectives of the Common Agricultural Policy post-2013 (CAP, 2014–2020) in the European Union (EU) are the sustainable management of natural resources and climate smart agriculture. To understand the CAP impact on these priorities, the Land Use/Cover statistical Area frame Survey (LUCAS) employs direct field observations and soil sub-sampling across the EU. While a huge amount of information can be retrieved from LUCAS points for monitoring the environmental status of agroecosystems and assessing soil carbon sequestration, a fundamental aspect relating to climate change action is missing, namely nitrous oxide (N2O) soil emissions. To fill this gap, we ran the DayCent biogeochemistry model for more than 11’000 LUCAS sampling points under agricultural use, assessing also the model uncertainty. The results showed that current annual N2O emissions followed a skewed distribution with a mean and median values of 2.27 and 1.71 kg N ha-1 yr-1, respectively. Using a Random Forest regression for upscaling the modelled results to the EU level, we estimated direct soil emissions of N2O in the range of 171–195 Tg yr-1 of CO2eq. Moreover, the direct regional upscaling using modelled N2O emissions in LUCAS points was on average 0.95 Mg yr-1 of CO2eq. per hectare, which was within the range of the meta-model upscaling (0.92–1.05 Mg ha-1 yr-1 of CO2eq). We concluded that, if information on management practices would be made available and model bias further reduced by N2O flux measurement at representative LUCAS points, the combination of the land use/soil survey with a well calibrated biogeochemistry model may become a reference tool to support agricultural, environmental and climate policies.

ttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0176111

Soil Functions in Earth’s Critical Zone: Key Results and Conclusions
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017
This chapter summarizes the methods, results, and conclusions of a 5-year research project (SoilTrEC: Soil Transformations in European Catchments) on experimentation, process modeling, and computational simulation of soil functions and soil threats across a network of European, Chinese, and United States Critical Zone Observatories (CZOs). The study focused on the soil functions of biomass production, carbon storage, water storage and transmission, water filtration, transformation of nutrients, and maintaining habitat and genetic diversity.
 
The principal results demonstrate that soil functions can be quantified as biophysical flows and transformations of material and energy. The functions can be simulated with mathematical models of soil processes within the soil profile and at the critical zone interfaces with vegetation and atmosphere, surface waters and the below-ground vadose zone and groundwater. A new dynamic model for soil structure development, together with data sets from the CZOs, demonstrate both seasonal fluctuations in soil structure dynamics related to vegetation dynamics and soil carbon inputs, and long-term trends (decadal) in soil carbon storage and soil structure development.
 
Cross-site comparison for 20 soil profiles at seven field sites with variation in soil type, lithology, land cover, land use, and climate demonstrate that sites can be classified, using model parameter values for soil aggregation processes together with climatic conditions and soil physical properties, along a trajectory of soil structure development from incipient soil formation through productive land use to overly intensive land use with soil degradation.
 
A new modeling code, the Integrated Critical Zone model, was applied with parameter sets developed from the CZO site data to simulate the biophysical flows and transformations that quantify multiple soil functions. Process simulations coupled the new model for soil structure dynamics with existing modeling approaches for soil carbon dynamics, nutrient transformations, vegetation dynamics, hydrological flow and transport, and geochemical equilibria and mineral weathering reactions. Successful calibration, testing, and application of the model with data sets from horticulture plot manipulation experiments demonstrate the potential to apply modeling and simulation to the scoping and design of new practices and policy options to enhance soil functions and reduce soil threats worldwide. Köppen–Geiger Classification).

https://www.sciencedirect.com/science/article/pii/S0065211316301249

Discovering historical rainfall erosivity with a parsimonious approach: A case study in Western Germany
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

An in-depth analysis of the interannual variability of storms is required to detect changes in soil erosive power of rainfall, which can also result in severe on-site and off-site damages. Evaluating long-term rainfall erosivity is a challenging task, mainly because of the paucity of high-resolution historical precipitation observations that are generally reported at coarser temporal resolutions (e.g., monthly to annual totals). In this paper we suggest overcoming this limitation through an analysis of long-term processes governing rainfall erosivity with an application to datasets available the central Ruhr region (Western Germany) for the period 1701–2011. Based on a parsimonious interpretation of seasonal rainfall-related processes (from spring to autumn), a model was derived using 5-min erosivity data from 10 stations covering the period 1937–2002, and then used to reconstruct a long series of annual rainfall erosivity values. Change-points in the evolution of rainfall erosivity are revealed over the 1760s and the 1920s that mark three sub-periods characterized by increasing mean values. The results indicate that the erosive hazard tends to increase as a consequence of an increased frequency of extreme precipitation events occurred during the last decades, characterized by short-rain events regrouped into prolonged wet spells.

https://www.sciencedirect.com/science/article/pii/S0022169416307296

Mapping monthly rainfall erosivity in Europe
Resource Type: Maps & Documents, Documents, Publications in Journals
Year: 2017
Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315 MJ mm ha− 1 h− 1) compared to winter (87 MJ mm ha− 1 h− 1).
 
The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be applied in different seasons of the year.
 
Topological data analysis (TDA) applied to reveal pedogenetic principles of European topsoil system
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

Recent developments in applied mathematics are bringing new tools that are capable to synthesize knowledge in various disciplines, and help in finding hidden relationships between variables. One such technique is topological data analysis (TDA), a fusion of classical exploration techniques such as principal component analysis (PCA), and a topological point of view applied to clustering of results. Various phenomena have already received new interpretations thanks to TDA, from the proper choice of sport teams to cancer treatments. For the first time, this technique has been applied in soil science, to show the interaction between physical and chemical soil attributes and main soil-forming factors, such as climate and land use. The topsoil data set of the Land Use/Land Cover Area Frame survey (LUCAS) was used as a comprehensive database that consists of approximately 20,000 samples, each described by 12 physical and chemical parameters. After the application of TDA, results obtained were cross-checked against known grouping parameters including five types of land cover, nine types of climate and the organic carbon content of soil. Some of the grouping characteristics observed using standard approaches were confirmed by TDA (e.g., organic carbon content) but novel subtle relationships (e.g., magnitude of anthropogenic effect in soil formation), were discovered as well. The importance of this finding is that TDA is a unique mathematical technique capable of extracting complex relations hidden in soil science data sets, giving the opportunity to see the influence of physicochemical, biotic and abiotic factors on topsoil formation through fresh eyes.

https://www.sciencedirect.com/science/article/pii/S0048969717303431

Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha−1 h−1 yr−1 till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April–September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

https://www.sciencedirect.com/science/article/pii/S0022169417301439

LUCAS 2018 - SOIL COMPONENT: Sampling Instructions for Surveyors
Resource Type: Maps & Documents, Documents, Scientific-Technical Reports
Country: LU
Author: FERNANDEZ UGALDE Oihane, ORGIAZZI Alberto, JONES Arwyn, LUGATO Emanuele, PANAGOS Panagiotis
Year: 2017
Publisher: Publications Office of the European Union
Language: en

The European Commission launched a soil assessment component to the periodic LUCAS Land Use/Land Cover Area Frame Survey in 2009. Composite soil samples from 0-20-cm depth were taken, air-dried and sieved to 2 mm in order to analyse physical and chemical parameters of topsoil in 25 Member States (EU-27 except Bulgaria, Romania, Malta and Cyprus). The aim of the LUCAS Soil Component was to create a harmonised and comparable dataset of main properties of topsoil at the EU. The LUCAS Soil Component was extended to Bulgaria and Romania in 2012. Overall, ca. 22,000 soil samples were collected and analysed. All samples were analysed for percentage of coarse fragments, particle-size distribution, pH, organic carbon, carbonates, phosphorous, total nitrogen, extractable potassium, cation exchange capacity, multispectral properties and heavy metals. In 2015, the soil sampling was repeated in the same set of points of LUCAS 2009/2012 to monitor changes in topsoil physical and chemical parameters across the EU. The soil component was extended to points above elevations of 1000 m, which were not sampled in LUCAS 2009/2012. Furthermore, soil samples were taken in Albania, Bosnia-Herzegovina, Croatia, Macedonia, Montenegro, Serbia and Switzerland. The soil sampling was carried out following the instructions already used in LUCAS 2009/2012. Approximately 27,000 samples were collected and will be analysed during 2016 and 2017. In 2018, a new soil sampling campaign will be carried out within the LUCAS framework. Soil samples will be taken in repeated points of LUCAS 2009/2012 and LUCAS 2015. The novelty of the survey is that new physical, chemical and biological parameters will be analysed. Key parameters for evaluating soil quality, such as bulk density and soil biodiversity, will be analysed. These analyses require specific methods of soil sampling, preparation and storage of samples. Furthermore, field measurements such as the thickness of organic layer in peat soils, and visual assessment of signs of soil erosion will be carried out in 2018. This technical report compiles the instructions for collecting the various soil samples and for performing field measurements in the soil survey of 2018. These instructions will be used for all LUCAS surveyors, to create a comparable database of soil characteristics all over Europe.

How does tillage intensity affect soil organic carbon? A systematic review
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017
The loss of carbon (C) from agricultural soils has been, in part, attributed to tillage, a common practice providing a number of benefits to farmers. The promotion of less intensive tillage practices and no tillage (NT) (the absence of mechanical soil disturbance) aims to mitigate negative impacts on soil quality and to preserve soil organic carbon (SOC). Several reviews and meta-analyses have shown both beneficial and null effects on SOC due to no tillage relative to conventional tillage, hence there is a need for a comprehensive systematic review to answer the question: what is the impact of reduced tillage intensity on SOC?
 
European Achievements in soil remediation and brownfield redevelopment
Resource Type: Maps & Documents, Documents
Country: LU
Author: Ana Payá Pérez, Sara Peláez Sánchez
Year: 2017
Publisher: European Commission

With the aim  of sharing best practices of soil restoration and management of contaminated sites among European countries and to raise awareness of the enormous efforts made to succeed in such difficult commitment, the experts of the EIONET Soil working group on contaminated sites and brownfields agreed to gather their country's interesting cases and successful stories of recovery of contaminated areas. This second edition of the monograph presents seventeen new cases from eight European countries and its Regions of how polluted sites and brownfields have been remediated like new methodologies of sustainable restoration of the subsoil, development of innovative technologies, and funding mechanisms etc. These stories have been compiled to present what national, regional or local governments are doing to improve the quality of the environment and the living conditions of their population. A second aim is the promotion of best practices among industry, consultancies and business operators.

 

http://publications.jrc.ec.europa.eu/repository/bitstream/JRC102681/kj0217891enn.pdf

Global rainfall erosivity assessment based on high-temporal resolution rainfall records
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

The exposure of the Earth’s surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha−1 h−1 yr−1, with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.

https://www.nature.com/articles/s41598-017-04282-8

Optimizing the delivery of multiple ecosystem goods and services in agricultural systems
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017
Agricultural land is subjected to a variety of societal pressures, as demands for food, animal feed, and biomass production increase, with an added requirement to simultaneously maintain natural areas, and mitigate climatic and environmental impacts globally (Tilman et al., 2002; Pretty, 2008; Wang and Swallow, 2016). The biotic elements of agricultural systems interact with the abiotic environment to generate a number of ecosystem functions that offer services benefiting humans across many scales of time and space (Swinton et al., 2007; Power, 2010). The intensification of agriculture, particularly of that founded on fossil-fuel derived inputs, generally reduces biodiversity, including soil biodiversity (Tsiafouli et al., 2015) and impacts negatively upon a number of regulating and supporting ecosystem services (Zhang et al., 2007). There is a global need toward achieving sustainable agricultural systems, highlighted also in the UNs' Sustainable Development Goals, where among their targets they state that by 2030 we should globally “ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production, that help maintain ecosystems, that strengthen capacity for adaptation to climate change, extreme weather, drought, flooding and other disasters and that progressively improve land and soil quality” (UN-DESA/DSD, 2014).
 
There is hence an evident need for management regimes that enhance both agricultural production and the provision of multiple ecosystem services. The articles of this Research Topic enhance our knowledge of how management practices applied to agricultural systems affect the delivery of multiple ecosystem services and how trade-offs between provisioning, regulating, and supporting ecosystem services can be handled both above- and below-ground, and across multiple scales of space and time. They also show the diversity of topics that need to be considered within the framework of ecosystem services delivered by agricultural systems, from knowledge on basic concepts and newly-proposed frameworks (§1), to a focus on specific ecosystem types such as grasslands and high nature-value farmlands (§2), pollinator habitats (§3), and soil habitats (§4).

https://www.frontiersin.org/articles/10.3389/fevo.2017.00097/full

Pedotransfer functions for predicting organic carbon in subsurface horizons of European soils
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

There is an increasing demand for information on organic carbon (OC) in subsurface horizons, because subsurface horizons down to the bedrock can contribute to more than half of soil carbon stocks. In this study, we developed pedotransfer functions (PTFs) for predicting OC content in subsurface horizons of European soils. We used a dataset with a wide geographical coverage in Europe. The dataset was stratified sequentially into land‐cover and soil categories. For each category, PTFs were developed by multiple linear regression with the main soil and climatic factors of soil OC storage as predictor variables: OC in topsoil (0–20 cm), depth of subsurface horizons, texture and bulk density (BD) in subsurface horizons, and mean annual temperature and precipitation. Three land‐cover categories were separated: woodland, a combined category of grassland and non‐permanent arable land, and permanent arable land. For the combined land‐cover category, two soil categories were identified: (i) soils with clay‐rich subsoil and soils with little horizon development and (ii) organic‐rich soils and soils rich in Fe and Al compounds. The adjusted R2 of all PTFs was above 0.62. When PTFs were applied to independent data, the adjusted R2 was above 0.51 for all of them. The PTFs showed good prediction ability, with root mean square error (RMSE) values between 2.43 and 13.82 g C kg−1 soil. The adjusted R2 and RMSE of PTFs were better when BD was used as a predictor variable. The PTFs could be implemented easily for applications at the continental scale in Europe.

https://onlinelibrary.wiley.com/doi/full/10.1111/ejss.12464

Predicted distribution of SOC content in Europe (based on LUCAS, BioSoil and CZO) in the context of the EU-funded SoilTrEC project.
Resource Type: Datasets, Maps & Documents, Documents, Publications in Journals
Author: Ece Aksoy , Yusuf Yigini , Luca Montanarella
Year: 2016
Publisher: PLoS ONE 11(3): e0152098. doi:10.1371/journal.pone.0152098

The maps of predicted distribution of SOC content in Europe are based on aggregated 23,835 soil samples collected from the LUCAS Project (samples from agricultural soil), the BioSoil Project (samples from European forest soil), and the “Soil Transformations in European Catchments” (SoilTrEC) Project (samples from local soil data coming from five different critical zone observatories (CZOs) in Europe). The Predicted SOC content was the lowest in permanent crops and arable lands; highest values are found in wetlands and grasslands. Moreover, Hungary and Portugal show the lowest SOC content with the averages 2.21% and 2.68%, whereas Ireland (13.29%) and Sweden (11.15%) hshow ighest SOC contents.  

Spatial coverage: 25 European Union Member States (excluded Romania, Bulgaria, Croatia), and Switzerland
Pixel size: 1Km
Projection: ETRS89-LAEA-10-52
Temporal coverage: 2014
Input data source: LUCAS, BioSoil and CZOs point data

Via this page you can register for downloading the output and input data that are mentioned in the paper

The data are described in:

Combining soil databases for topsoil organic carbon mapping in Europe” (E. Aksoy, Y.Yigini and L. Montanarella), published in PLOS ONE. doi: 10.1371/journal.pone.0152098, that is summarized as follows: 

Accuracy in assessing the distribution of soil organic carbon (SOC) is important because it plays a key role in the functions of both natural ecosystems and agricultural systems. There are several studies in the literature with the aim of finding the best method to assess and map the distribution of SOC content for Europe. This study aims to search for the effects and performances of using aggregated soil samples coming from different studies and land-uses.

The total number of the soil samples in this study was 23,835 and they were collected from the “Land Use/Cover Area frame Statistical Survey” (LUCAS) Project (samples from agricultural soil), the BioSoil Project (samples from forest soil), and the “Soil Transformations in European Catchments” (SoilTrEC) Project (samples from local soil data coming from five different critical zone observatories (CZOs) in Europe). Moreover, 15 spatial indicators (slope, aspect, elevation, compound topographic index (CTI), CORINE land-cover classification, parent material, texture, world reference base (WRB) soil classification, geological formations, annual average temperature, min-max temperature, total precipitation and average precipitation (for the years 1960–1990 and 2000–2010)) were used as auxiliary variables in this prediction. One of the most popular geostatistical techniques, Regression-Kriging (RK), was applied to build the model and assess the distribution of SOC.

This study showed that, even though the RK method was appropriate for successful SOC mapping, using combined databases did not increase the statistical significance of the method results for assessing the SOC distribution as much as expected. Combining local data coming from CZOs with LUCAS samples was found as more significant than combining the two big datasets of the LUCAS and Biosoil Projects. Moreover, the effect of the chosen auxiliary variables on SOC prediction seems more important than increasing the number of the soil samples. According to the results: SOC variation was mainly affected by elevation, slope, CTI, average temperature, average and total precipitation, texture, WRB and CORINE variables at the European scale in the model. Moreover, the highest average SOC contents were found in the wetland areas; agricultural areas have much lower SOC content than forest and semi natural areas; Ireland, Sweden and Finland show the highest SOC values; Portugal, Poland, Hungary, Spain and Italy show the lowest values with an average 3%.

 

Data (available: 3 output datasets and 1 input dataset):

0.     Input: soil sample point data; attribute: SOC for each point.

1.     Predicted distribution of SOC content by using 1 dataset (LUCAS) (Figure 3 in the article)

2.     Predicted distribution of SOC content by using 2 datasets (LUCAS-CZOs) (Figure 4 in the article)

3.     Predicted distribution of SOC content by using 3 datasets (LUCAS-CZOs-BIOSOIL) (Figure 5 in the article)

 

Acknowledgments

Funding support is acknowledged from the European Commission FP 7 Collaborative Project “Soil Transformations in European Catchments” (SoilTrEC) (Grant Agreement no. 244118).

Mapping earthworm communities in Europe
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

Existing data sets on earthworm communities in Europe were collected, harmonized, collated, modelled and depicted on a soil biodiversity map. Digital Soil Mapping was applied using multiple regressions relating relatively low density earthworm community data to soil characteristics, land use, vegetation and climate factors (covariables) with a greater spatial resolution. Statistically significant relationships were used to build habitat–response models for maps depicting earthworm abundance and species diversity. While a good number of environmental predictors were significant in multiple regressions, geographical factors alone seem to be less relevant than climatic factors. Despite differing sampling protocols across the investigated European countries, land use and geological history were the most relevant factors determining the demography and diversity of the earthworms. Case studies from country-specific data sets (France, Germany, Ireland and The Netherlands) demonstrated the importance and efficiency of large databases for the detection of large spatial patterns that could be subsequently applied at smaller (local) scales.

https://www.sciencedirect.com/science/article/abs/pii/S0929139315300688

 

Effect of Good Agricultural and Environmental Conditions on erosion and soil organic carbon balance: A national case study
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

Since, the Common Agricultural Policies (CAP) reform in 2003, many efforts have been made at the European level to promote a more environmentally friendly agriculture. In order to oblige farmers to manage their land sustainably, the GAEC (Good Agricultural and Environmental Conditions) were introduced as part of the Cross Compliance mechanism. Among the standards indicated, the protection of soils against erosion and the maintenance of soil organic matter and soil structure were two pillars to protect and enhance the soil quality and functions. While Member States should specifically define the most appropriate management practices and verify their application, there is a substantial lack of knowledge about the effects of this policy on erosion prevention and soil organic carbon (SOC) change. In order to fill this gap, we coupled a high resolution erosion model based on Revised Universal Soil Loss Equation (RUSLE) with the CENTURY biogeochemical model, with the aim to incorporate the lateral carbon fluxes occurring with the sediment transportation. Three scenarios were simulated on the whole extent of arable land in Italy: (i) a baseline without the GAEC implementation; (ii) a current scenario considering a set of management related to GAEC and the corresponding area of application derived from land use and agricultural management statistics and (iii) a technical potential where GAEC standards are applied to the entire surface. The results show a 10.8% decrease, from 8.33 Mg ha−1 year−1 to 7.43 Mg ha−1 year−1, in soil loss potential due to the adoption of the GAEC conservation practices. The technical potential scenario shows a 50.1% decrease in the soil loss potential (soil loss 4.1 Mg ha−1 year−1). The GAEC application resulted in overall SOC gains, with different rates depending on the hectares covered and the agroecosystem conditions. About 17% of the SOC change was attributable to avoided SOC transport by sediment erosion in the current scenario, while a potential gain up to 23.3 Mt of C by 2020 is predicted under the full GAEC application. These estimates provide a useful starting point to help the decision-makers in both ex-ante and ex-post policy evaluation while, scientifically, the way forward relies on linking biogeochemical and geomorphological processes occurring at landscape level and scaling those up to continental and global scales.

https://www.sciencedirect.com/science/article/pii/S0264837715003257

Selection of biological indicators appropriate for European soil monitoring
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

The selection of biological indicators for monitoring progress towards policy goals for soil quality should be without bias and in line with individual scenarios of need. Here we describe the prescription of a suite of appropriate indicators for potential application in such monitoring schemes across Europe. We applied a structured framework of assessment and ranking (viz. a ‘logical sieve’), building upon published data and a new survey taken from a wide section of the global soil biodiversity research and policy community.

The top ten indicators included four indicators of biodiversity (three microbial and one meso-faunal) by various methods of measurement, and three indicators of ecological function (Multiple enzyme assay, Multiple substrate-induced respiration profiling, and ‘Functional genes by molecular biological means’). Within the techniques assessed, seven out of the top ten indicators made use of molecular methods.

https://www.sciencedirect.com/science/article/abs/pii/S0929139315300585

 

Maps of heavy metals in the soils of the European Union and proposed priority areas for detailed assessment
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

Soil contamination is one of the greatest concerns among the threats to soil resources in Europe and globally. Despite of its importance there was only very course scale (1/5000 km2) data available on soil heavy metal concentrations prior to the LUCAS topsoil survey, which had a sampling density of 200 km2. Based on the results of the LUCAS sampling and auxiliary information detailed and up-to-date maps of heavy metals (As, Cd, Cr, Cu, Hg, Pb, Zn, Sb, Co and Ni) in the topsoil of the European Union were produced. Using the maps of heavy metal concentration in topsoil we made a spatial prediction of areas where local assessment is suggested to monitor and eventually control the potential threat from heavy metals. Most of the examined elements remain under the corresponding threshold values in the majority of the land of the EU. However, one or more of the elements exceed the applied threshold concentration on 1.2 M km2, which is 28.3% of the total surface area of the EU. While natural backgrounds might be the reason for high concentrations on large proportion of the affected soils, historical and recent industrial and mining areas show elevated concentrations (predominantly of As, Cd, Pb and Hg) too, indicating the magnitude of anthropogenic effect on soil quality in Europe.

https://www.sciencedirect.com/science/article/pii/S0048969716310452

The LUCAS 2012 TOPSOIL survey and derived cropland and grassland soil properties of Bulgaria and Romania
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016
As part of the 2012 Land Use/Land Cover Area Frame Survey (LUCAS), topsoil samples were collected in Bulgaria and
Romania using the same methodology as for other EU Member States in an equivalent survey carried out in 2009. In total, 664
Bulgarian and 1384 Romanian samples were collected which enabled a comparative assessment of topsoil properties under
different land covers within, and between, these countries, as well as in a broader European context. The samples were analysed
for basic soil properties, including particle size distribution, pH, organic carbon, carbonates, nitrogen, phosphorus, potassium and
cation exchange capacity together with multispectral signatures. The current paper describes the LUCAS Topsoil 2012 project
and provides both an overview of topsoil properties of cropland and grassland in Bulgaria and Romania, together with a
comparative assessment with earlier findings with the analysis of data from other 25 EU Member States and data from small
scale European soil database. Results show similarities with data from Member States with comparable climatic conditions in
properties where non-anthropogenic soil forming factors play major role (texture, pH, calcium-carbonate, soil organic carbon
content). There are considerable variations in certain soil properties between different land use types, (e.g. soil organic carbon
content in croplands and grasslands in Romania; or potassium content in croplands and grassland in both countries). However,
the most remarkable facts drawn from the current study are the very low phosphorus content in agricultural land in the two
countries relative to other EU Member States, the significantly lower contents of organic carbon compared to modelled data of
literature and legacy national data and the difference in the distribution of texture classes compared to European datasets

http://www.eemj.icpm.tuiasi.ro/pdfs/vol15/no12/10_91_Toth_14.pdf

LUCAS Soil Component: proposal for analysing new physical, chemical and biological soil parameters
Resource Type: Maps & Documents, Documents, Scientific-Technical Reports
Author: Fernández-Ugalde O., Jones A., Tóth G., Orgiazzi A., Panagos P., Eiselt B.
Year: 2016
Publisher: European Commission, Joint Research Centre
Language: en
The European Commission launched a soil assessment component to the periodic LUCAS Land Use/Land Cover Area Frame Survey in 2009. In 2015, the Topsoil Survey was repeated in the same set of points of LUCAS 2009/2012 for monitoring changes in topsoil physical and chemical parameters across the EU. Currently, the European Commission is working on the organization of the upcoming LUCAS Soil Surveys (2018). This technical report is a proposal for analysing new physical, chemical and biological soil parameters within the forthcoming LUCAS Soil Surveys. Soil biodiversity is a key parameter that needs to be added to LUCAS Soil Surveys, due to the contribution of the soil biological community to soil functions such as food and biomass production, genetic pool for developing novel pharmaceuticals, and climate regulation. Among physical properties, bulk density is necessary to assess soil compaction and to estimate soil organic carbon stock in the EU. Field measurements such as signs of soil erosion and thickness of organic layer in Histosols is also important to assess two critical soil degradation processes in the EU: soil erosion and organic carbon decline due to land use changes and land take of Histosols. Finally, it could be interesting to organize a survey of soil profiles to collect information that will help to understand soil-forming processes and to evaluate soil ability for carbon sequestration, nutrient cycling, water storage, and contaminant filtering.
Mapping regional patterns of large forest fires in the Wildland-Urban Interface areas in Europe
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

Over recent decades, Land Use and Cover Change (LUCC) trends in many regions of Europe have reconfigured the landscape structures around many urban areas. In these areas, the proximity to landscape elements with high forest fuels has increased the fire risk to people and property. These Wildland–Urban Interface areas (WUI) can be defined as landscapes where anthropogenic urban land use and forest fuel mass come into contact. Mapping their extent is needed to prioritize fire risk control and inform local forest fire risk management strategies. This study proposes a method to map the extent and spatial patterns of the European WUI areas at continental scale. Using the European map of WUI areas, the hypothesis is tested that the distance from the nearest WUI area is related to the forest fire probability. Statistical relationships between the distance from the nearest WUI area, and large forest fire incidents from satellite remote sensing were subsequently modelled by logistic regression analysis. The first European scale map of the WUI extent and locations is presented. Country-specific positive and negative relationships of large fires and the proximity to the nearest WUI area are found. A regional-scale analysis shows a strong influence of the WUI zones on large fires in parts of the Mediterranean regions. Results indicate that the probability of large burned surfaces increases with diminishing WUI distance in touristic regions like Sardinia, Provence-Alpes-Côte d'Azur, or in regions with a strong peri-urban component as Catalunya, Comunidad de Madrid, Comunidad Valenciana. For the above regions, probability curves of large burned surfaces show statistical relationships (ROC value > 0.5) inside a 5000 m buffer of the nearest WUI. Wise land management can provide a valuable ecosystem service of fire risk reduction that is currently not explicitly included in ecosystem service valuations. The results re-emphasise the importance of including this ecosystem service in landscape valuations to account for the significant landscape function of reducing the risk of catastrophic large fires.

https://www.sciencedirect.com/science/article/pii/S0301479716300548

A knowledge-based approach to estimating the magnitude and spatial patterns of potential threats to soil biodiversity
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

Because of the increasing pressures exerted on soil, below-ground life is under threat. Knowledge-based rankings of potential threats to different components of soil biodiversity were developed in order to assess the spatial distribution of threats on a European scale. A list of 13 potential threats to soil biodiversity was proposed to experts with different backgrounds in order to assess the potential for three major components of soil biodiversity: soil microorganisms, fauna, and biological functions. This approach allowed us to obtain knowledge-based rankings of threats. These classifications formed the basis for the development of indices through an additive aggregation model that, along with ad-hoc proxies for each pressure, allowed us to preliminarily assess the spatial patterns of potential threats. Intensive exploitation was identified as the highest pressure. In contrast, the use of genetically modified organisms in agriculture was considered as the threat with least potential. The potential impact of climate change showed the highest uncertainty. Fourteen out of the 27 considered countries have more than 40% of their soils with moderate-high to high potential risk for all three components of soil biodiversity. Arable soils are the most exposed to pressures. Soils within the boreal biogeographic region showed the lowest risk potential. The majority of soils at risk are outside the boundaries of protected areas. First maps of risks to three components of soil biodiversity based on the current scientific knowledge were developed. Despite the intrinsic limits of knowledge-based assessments, a remarkable potential risk to soil biodiversity was observed. Guidelines to preliminarily identify and circumscribe soils potentially at risk are provided. This approach may be used in future research to assess threat at both local and global scale and identify areas of possible risk and, subsequently, design appropriate strategies for monitoring and protection of soil biota.

https://www.sciencedirect.com/science/article/pii/S004896971531247X

 

Soil conservation in Europe: Wish or Reality?
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

Nearly all of Europe is affected by soil erosion. A major policy response is required to reverse the impacts of erosion in degraded areas, particularly in light of the current climate change and water crisis. Soil loss occurs not because of any lack of knowledge on how to protect soils, but a lack in policy governance. The average rate of soil loss by sheet and rill erosion in Europe is 2·46 Mg ha−1 yr−1. To mitigate the impacts of soil erosion, the European Union's Common Agricultural Policy has introduced conservation measures which reduce soil loss by water erosion by 20% in arable lands. Further economic and political action should rebrand the value of soil as part of ecosystem services, increase the income of rural land owners, involve young farmers and organize regional services for licensing land use changes. In a changing World of 9 billion people with the challenge of climate change, water scarcity and depletion of soil fertility, the agriculture economy should evolve taking into account environmental and ecological aspects.

https://onlinelibrary.wiley.com/doi/full/10.1002/ldr.2538

Assessment of the cover changes and the soil loss potential in European forestland: First approach to derive indicators to capture the ecological impacts on soil-related forest ecosystems
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

The Member States of the European Union have committed to the maintenance and protection of forest lands. More precisely, the Member States aim to ensure the sustainable development and management of the EU's forests. For 2013, Eurostat's statistics about primary and secondary wood products in the European forest land (65% thereof privately owned) estimate a roundwood production of 435 million m3 in total. Harmonised information, i.e., spatially and temporarily differentiated, on forestry and wood harvesting activities in the European forests are missing however. This lack of information impedes the scientific assessment of the impacts that forest management practices have on the soil-related forest ecosystems (e.g., accelerated water soil erosion, delivery of inert sediments and pollutants within the drainage network, pauperization of aquatic ecosystems). It also prevents national and European institutions from taking measures aimed at an effective mitigation of the rapidly advancing land degradation. This study provides a first pan-European analysis that delineates the spatial patterns of forest cover changes in 36 countries. The first dynamic assessment of the soil loss potential in the EU-28 forests is reported. The recently published High-resolution Global Forest Cover Loss map (2000–2012) was reprocessed and validated. Results show that the map is a powerful tool to spatiotemporally indicate the forest sectors that are exposed to cover change risks. The accuracy assessment performed by using a confusion matrix based on 2300 reference forest disturbances distributed across Europe shows values of 55.1% (producer accuracy) for the algorithm-derived forest cover change areas with a Kappa Index of Agreement (KIA) of 0.672. New insights into the distribution of the forest disturbance in Europe and the resulting soil loss potential were obtained. The presented maps provide spatially explicit indicators to assess the human-induced impacts of land cover changes and soil losses on the European soil-related forest ecosystems. These insights are relevant (i) to support policy making and land management decisions to ensure a sustainable forest management strategy and (ii) to provide a solid basis for further spatiotemporal investigations of the forestry practices’ impacts on the European forest ecosystems.

https://www.sciencedirect.com/science/article/pii/S1470160X1500494X