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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Soil biodiversity and soil erosion: It is time to get married
Resource Type: Maps & Documents, Documents, Publications in Journals
Year: 2018

The relationship between erosion and biodiversity is reciprocal. Soil organisms can both reduce soil loss, by improving porosity, and increase it, by diminishing soil stability as a result of their mixing activities. Simultaneously, soil runoff has ecological impacts on belowground communities. Despite clear research into interactions, soil erosion models do not consider biodiversity in their estimates and soil ecology has poorly investigated the effects of erosion. In order to start filling in these research gaps, we present a novel biological factor and introduce it into a well‐known soil erosion model (the revised universal soil loss equation). Furthermore, we propose insights to advance soil erosion ecology. We present three pathways to fill in current knowledge gaps in soil biodiversity and erosion studies: (a) introducing a biological factor into soil erosion models; (b) developing plot‐scale experiments to clarify and quantify the positive/negative effects of soil organisms on erosion; (c) promoting ecological studies to assess both short‐ and long‐term effects of soil erosion on soil biota. We develop a biological factor to be included in soil erosion modelling. Thanks to available data on earthworm diversity (richness and abundance), we generate an “earthworm factor”, incorporate it into a model of soil erosion and produce the first pan‐European maps of it. New estimates of soil loss can be generated by including biological factors in soil erosion models. At the same time, the effects of soil loss on belowground diversity require further investigation. Available data and technologies make both processes possible. We think that it is time to commit to fostering the fundamental, although complex, relationship between soil biodiversity and erosion.

https://onlinelibrary.wiley.com/doi/full/10.1111/geb.12782

A step towards a holistic assessment of soil degradation in Europe: Coupling on-site erosion with sediment transfer and carbon fluxes
Resource Type: Maps & Documents, Documents, Publications in Journals
Year: 2018

Soil degradation due to erosion is connected to two serious environmental impacts: (i) on-site soil loss and (ii) off-site effects of sediment transfer through the landscape. The potential impact of soil erosion processes on biogeochemical cycles has received increasing attention in the last two decades. Properly designed modelling assumptions on effective soil loss are a key pre-requisite to improve our understanding of the magnitude of nutrients that are mobilized through soil erosion and the resultant effects. The aim of this study is to quantify the potential spatial displacement and transport of soil sediments due to water erosion at European scale. We computed long-term averages of annual soil loss and deposition rates by means of the extensively tested spatially distributed WaTEM/SEDEM model. Our findings indicate that soil loss from Europe in the riverine systems is about 15% of the estimated gross on-site erosion. The estimated sediment yield totals 0.164 ± 0.013 Pg yr−1 (which corresponds to 4.62 ± 0.37 Mg ha−1 yr−1 in the erosion area). The greatest amount of gross on-site erosion as well as soil loss to rivers occurs in the agricultural land (93.5%). By contrast, forestland and other semi-natural vegetation areas experience an overall surplus of sediments which is driven by a re-deposition of sediments eroded from agricultural land. Combining the predicted soil loss rates with the European soil organic carbon (SOC) stock, we estimate a SOC displacement by water erosion of 14.5 Tg yr−1. The SOC potentially transferred to the riverine system equals to 2.2 Tg yr−1 (~15%). Integrated sediment delivery-biogeochemical models need to answer the question on how carbon mineralization during detachment and transport might be balanced or even off-set by carbon sequestration due to dynamic replacement and sediment burial.

https://www.sciencedirect.com/science/article/pii/S0013935117308137

Soil erosion is unlikely to drive a future carbon sink in Europe
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018

Understanding of the processes governing soil organic carbon turnover is confounded by the fact that C feedbacks driven by soil erosion have not yet been fully explored at large scale. However, in a changing climate, variation in rainfall erosivity (and hence soil erosion) may change the amount of C displacement, hence inducing feedbacks onto the land C cycle. Using a consistent biogeochemistry-erosion model framework to quantify the impact of future climate on the C cycle, we show that C input increases were offset by higher heterotrophic respiration under climate change. Taking into account all the additional feedbacks and C fluxes due to displacement by erosion, we estimated a net source of 0.92 to 10.1 Tg C year−1 from agricultural soils in the European Union to the atmosphere over the period 2016–2100. These ranges represented a weaker and stronger C source compared to a simulation without erosion (1.8 Tg C year−1), respectively, and were dependent on the erosion-driven C loss parameterization, which is still very uncertain. However, when setting a baseline with current erosion rates, the accelerated erosion scenario resulted in 35% more eroded C, but its feedback on the C cycle was marginal. Our results challenge the idea that higher erosion driven by climate will lead to a C sink in the near future.

Monitoring soil for sustainable development and land degradation neutrality
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018
The adoption of the 17 sustainable development goals (SDGs) listed in the 2030 Agenda for Sustainable Development by the United Nations urged the scientific community to generate information for planning and monitoring socioeconomic development and the underlying environmental compartments. SDGs 2, 3, 6, 11, 13, 14, and 15 have targets which commend direct consideration of soil resources. There are five groups of SDGs and assigned SDG indicators where soil plays a central role. Frameworks of soil-related sustainable development goals and related indicators which can be monitored in current monitoring schemes are proposed.
 
The United Nations’ adoption of the 17 sustainable development goals (SDGs), under the 2030 Agenda for Sustainable Development, urged the scientific community to generate sound information with the aim of supporting planning and monitoring of socioeconomic development interlinking with environmental sustainability dimensions (UN 2015). SDGs 2, 3, 6, 11, 13, 14, and 15 refer to targets which commend direct consideration of soil resources. For instance, food security (SDGs 2 and 6), food safety (SDG 3), land-based nutrient pollution of the seas (SDG 14), urban development (SDG 11), and sustainability of terrestrial ecosystem services (SDG 15) are all depending on the provision of ecosystem services where soil properties and functions play a key role to deliver these. In particular, SDG target 15.3 on land degradation neutrality mentions, by 2030 to combat desertification, restore degraded land and soil, including land affected by desertification, drought and floods, and strive to achieve a land degradation-neutral world. In addition, soils play an important role in mitigating and adapting to climate change (SDG 13). Further, SDGs 7 and 12 will indirectly rely on the availability of healthy soil resources. Regarding the remaining SDGs, linkages can be found to the sustainable management of soils to some extent (Keesstra et al. 2016).

https://link.springer.com/article/10.1007/s10661-017-6415-3

Model-based spatio-temporal analysis of land desertification risk in Greece
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018

Land desertification is recognized as a major threat to soil resources in arid, semi-arid Mediterranean areas. The use of widely applicable methodologies can facilitate the identification of land desertification risk spatio-temporal trends, which allows transnational comparison and support the development of soil management practices and policies, protecting the valuable soil resources. The aim of this study is to improve and use the Environmentally Sensitive Areas (ESAs) MEDALUS methodology, in order to provide a qualitative assessment for desertification risk trends in Greece, within the last 45 years. The Management, Vegetation, Soil and Climate quality indices (MQI, VQI, SQI, CQI) and the sub-sequent Environmental Sensitive Areas Index (ESAI) have been modeled for three periods in the entire Greek territory. The four quality indices are divided in two main categories, based on data availability and inherent characteristics, such as the pace of change during the studied period. Particular emphasis is given to the assessment of MQI, by integrating criteria which derived from national policies and the elaboration of national statistical data. The results show about 9% increase of the areas characterized as Critical to land desertification risk, while Fragile, Potentially affected and Non-affected areas decrease by 3.7%, 3.6%, 2.5% respectively. The applied approach for MQI can reveal areas where particular attention to management practices is required and improves the performance of the overall desertification risk index.

https://www.sciencedirect.com/science/article/pii/S0341816218301577

Object‐oriented soil erosion modelling: A possible paradigm shift from potential to actual risk assessments in agricultural environments
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018

Over the last 2 decades, geospatial technologies such as Geographic Information System and spatial interpolation methods have facilitated the development of increasingly accurate spatially explicit assessments of soil erosion. Despite these advances, current modelling approaches rest on (a) an insufficient definition of the proportion of arable land that is exploited for crop production and (b) a neglect of the intra‐annual variability of soil cover conditions in arable land. To overcome these inaccuracies, this study introduces a novel spatio‐temporal approach to compute an enhanced cover‐management factor (C) for revised universal soil loss equation‐based models. It combines highly accurate agricultural parcel information contained in the Land Parcel Identification System with an object‐oriented Landsat imagery classification technique to assess spatial conditions and interannual variability of soil cover conditions at field scale. With its strong link to Land Parcel Identification System and Earth observation satellite data, the approach documents an unprecedented representation of farming operations. This opens the door for the transition from the currently used potential soil erosion risk assessments towards the assessment of the actual soil erosion risk. Testing this method in a medium‐size catchment located in the Swiss Plateau (Upper Enziwigger River Catchment), this study lays an important foundation for the application of the very same methods for large‐scale or even pan‐European applications. Soil loss rates modelled in this study were compared with the insights gained from emerging techniques to differentiate sediment source contribution through compound‐specific isotope analysis on river sediments. The presented technique is adaptable beyond revised universal soil loss equation‐type soil erosion models.

https://onlinelibrary.wiley.com/doi/abs/10.1002/ldr.2898

Distribution of glyphosate and aminomethylphosphonic acid (AMPA) in agricultural topsoils of the European Union
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018

Approval for glyphosate-based herbicides in the European Union (EU) is under intense debate due to concern about their effects on the environment and human health. The occurrence of glyphosate residues in European water bodies is rather well documented whereas only few, fragmented and outdated information is available for European soils. We provide the first large-scale assessment of distribution (occurrence and concentrations) of glyphosate and its main metabolite aminomethylphosphonic acid (AMPA) in EU agricultural topsoils, and estimate their potential spreading by wind and water erosion. Glyphosate and/or AMPA were present in 45% of the topsoils collected, originating from eleven countries and six crop systems, with a maximum concentration of 2 mg kg− 1. Several glyphosate and AMPA hotspots were identified across the EU. Soil loss rates (obtained from recently derived European maps) were used to estimate the potential export of glyphosate and AMPA by wind and water erosion. The estimated exports, result of a conceptually simple model, clearly indicate that particulate transport can contribute to human and environmental exposure to herbicide residues. Residue threshold values in soils are urgently needed to define potential risks for soil health and off site effects related to export by wind and water erosion.

https://www.sciencedirect.com/science/article/pii/S0048969717327973

Analysis and evaluation of landslide susceptibility: A review on articles published during 2005-2016 (periods of 2005-2012 and 2013-2016)
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018

Landslides are one of the most important environmental hazards occur naturally or human-induced with large-scale social, economic, and environmental impacts. Landslide susceptibility zoning, which has been widely performed in the last decades, allows identifying spatial prediction of areas of landslides, which could be used for land use planning and land management. The present study was conducted as a review with the aim of investigating the research background of landslide susceptibility in the world during the period of 2005–2016. The results showed that the publication of papers related to landslide susceptibility during the period of investigation has been on the rise, and China has produced a larger number of papers and authors (13% of total). In addition, this article reviews the most popularly used models and the most frequently used input factors. Among different models, the logistic regression has been used as the most common method for assessing landslide susceptibility in 28.4% of the articles, and the slope gradient is considered as the most important conditioning factor in landslide occurrence in 94.2% of the articles. Finally, it is concluded that the recent technological developments in the field of remote sensing, computing technologies and Geographic Information Systems (GIS), the increased data availability, and the awareness has arisen among media and recent policy developments are important elements for increasing the research interest in landslide susceptibility.

https://link.springer.com/article/10.1007/s12517-018-3531-5

Filling the European blank spot : Swiss soil erodibility assessment with topsoil samples
Resource Type: Maps & Documents, Documents, Publications in Journals
Year: 2018

Soil erodibility, commonly expressed as the K‐factor in USLE‐type erosion models, is a crucial parameter for determining soil loss rates. However, a national soil erodibility map based on measured soil properties did so far not exist for Switzerland. As an EU non‐member state, Switzerland was not included in previous soil mapping programs such as the Land Use/Cover Area frame Survey (LUCAS). However, in 2015 Switzerland joined the LUCAS soil sampling program and extended the topsoil sampling to mountainous regions higher 1500 m asl for the first time in Europe. Based on this soil property dataset we developed a K‐factor map for Switzerland to close the gap in soil erodibility mapping in Central Europe. The K‐factor calculation is based on a nomograph that relates soil erodibility to data of soil texture, organic matter content, soil structure, and permeability. We used 160 Swiss LUCAS topsoil samples below 1500 m asl and added in an additional campaign 39 samples above 1500 m asl. In order to allow for a smooth interpolation in context of the neighboring regions, additional 1638 LUCAS samples of adjacent countries were considered. Point calculations of K‐factors were spatially interpolated by Cubist Regression and Multilevel B‐Splines. Environmental features (vegetation index, reflectance data, terrain, and location features) that explain the spatial distribution of soil erodibility were included as covariates. The Cubist Regression approach performed well with an RMSE of 0.0048 t ha h ha−1 MJ−1 mm−1. Mean soil erodibility for Switzerland was calculated as 0.0327 t ha h ha−1 MJ−1 mm−1 with a standard deviation of 0.0044 t ha h ha−1 MJ−1 mm−1. The incorporation of stone cover reduces soil erodibility by 8.2%. The proposed Swiss erodibility map based on measured soil data including mountain soils was compared to an extrapolated map without measured soil data, the latter overestimating erodibility in mountain regions (by 6.3%) and underestimating in valleys (by 2.5%). The K‐factor map is of high relevance not only for the soil erosion risk of Switzerland with a particular emphasis on the mountainous regions but also has an intrinsic value of its own for specific land use decisions, soil and land suitability and soil protection.

https://onlinelibrary.wiley.com/doi/full/10.1002/jpln.201800128

Lateral carbon transfer from erosion in noncroplands matters
Resource Type: Maps & Documents, Documents, Publications in Journals
Year: 2018

This study combines two unprecedentedly high resolution (250 × 250 m) maps of soil erosion (inter‐rill and rill processes) and soil organic carbon to calculate a global estimate of erosion‐induced organic carbon (C) displacement. The results indicate a gross C displacement by soil erosion of urn:x-wiley:13541013:media:gcb14125:gcb14125-math-0001 Pg C/year. The greatest share of displaced C (64%) comes from seminatural lands and forests. This suggests that lateral C transfer from erosion in noncroplands may play a more important role than previously assumed. Human civilization has increasingly exploited land and soil for millennia. Today, undisturbed primary vegetation is at its historical minimum with agricultural areas covering about 38% of the Earth's ice‐free land surface (Foley et al., 2011; 12% croplands and 26% pastures). The anthropogenic acceleration of soil erosion and the impacts on soil quality are well‐known (Dotterweich, 2008; García‐Ruiz et al., 2015). Impacts on climate change, however, remain uncertain and contested, due to the extent to which soil erosion increases or decreases CO2 emissions. The extent to which eroded SOC is mineralized or buried in sediment is hotly debated (Lal, 2004; Van Oost et al., 2007). In their recent publication, Wang et al. (2017) introduced new analysis in support of the erosion‐induced C sink theory, suggesting that anthropogenic acceleration of soil erosion over the last 8,000 years would have had the potential to offset 37 ± 10% of previously recognized C emissions resulting from anthropogenic land cover change.

https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.14125

Towards prediction of soil erodibility, SOM and CaCO3 using Laboratory Vis-NIR spectra: a case study in a semi-arid region of Iran
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018

Soil Visible–Near-Infrared (Vis-NIR) spectroscopy has become an applicable and interesting technique to evaluate a number of soil properties because it is a fast, cost-effective, and non-invasive measurement technique. The main objective of the study to predict soil erodibility (K-factor), soil organic matter (SOM), and calcium carbonate equivalent (CaCO3) in calcareous soils of semi-arid regions located in south of Iran using spectral reflectance information in the Vis-NIR range. The K-factor was measured in 40 erosion plots under natural rainfall and the spectral reflectance of soil samples were analyzed in the laboratory. Various soil properties including the CaCO3, soil particle size distribution, SOM, permeability, and wet-aggregate stability were measured. Partial least-squares regression (PLSR) and stepwise multiple linear regression (SMLR) were used to obtain effective bands and develop Spectrotransfer Function (STF) using spectral reflectance information and Pedotransfer Function (PTF) to predict the K-factor, respectively. The derived STF was compared with developed PTF using measurable soil properties by Ostovari et al. (2016) and the Universal Soil Loss Equation (USLE) predictions of the K-factor. The results revealed that the USLE over-predicts (0.030 t h MJ− 1 mm− 1) the K-factor when compared to the ground-truth measurements (0.015 t h MJ− 1) in the semi-arid region of Iran. Results showed that developed PTF had the highest performance (R2 = 0.74, RMSE = 0.004 and ME = − 0.003 t h MJ− 1 mm− 1) to predict K-factor. The results also showed that the PLSR method predicted SOM with R2 values of 0.67 and 0.65 and CaCO3 with R2 values of 0.51 and 0.71 for calibration and validation datasets, respectively. We found good predictions for K-factor with R2 = 0.56 and ratio of predicted deviation (RPD) = 1.5 using the PLSR model. The derived STF (R2 = 0.64, RMSE = 0.002 and ME = 0.001 thMJ− 1 mm− 1) performed better than the USLE (R2 = 0.06, RMSE = 0.0171 and ME = 0.0151 thMJ− 1 mm− 1) for estimating the K-factor.

https://www.sciencedirect.com/science/article/pii/S0016706117314891

Global gaps in soil biodiversity data
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018
 Soil biodiversity represents a major terrestrial biodiversity pool, supports key ecosystem services and is under pressure from human activities1. Yet soil biodiversity has been neglected from many global biodiversity assessments and policies. This omission is undoubtedly related to the paucity of comprehensive information on soil biodiversity, particularly on larger spatial scales. Information on belowground species distributions, population trends, endemism and threats to belowground diversity is important for conservation prioritization, but is practically non-existent. As a consequence, much of our understanding of global macroecological patterns in biodiversity, as well as mapping of global biodiversity hotspots, has been based on aboveground taxa (such as plants2) and has not considered the functionally vital, but less visible, biodiversity found in soil.
 
We mapped the study sites from existing global datasets on soil biodiversity (soil macrofauna3, fungi4 and bacteria5) to examine key data gaps (Fig. 1). Our map indicates significant gaps in soil biodiversity data across northern latitudes, including most of Russia and Canada. Data are also lacking from much of central Asia and central Africa (for example, the Sahara Desert), as well as many tropical regions. The higher density of soil biodiversity sampling sites in Europe and the United States is similar to patterns observed for data on terrestrial bird, mammal and amphibian species6, as well as plants7. Yet, in such aboveground datasets, the gaps in understudied regions are much less pronounced than in the soil biodiversity datasets shown here. The comparative lack of soil biodiversity data across these regions limits our ability to examine global macroecological patterns and to quantify potential mismatches between aboveground and soil biodiversity. The potential for such mismatches (areas with high aboveground diversity, but low soil biodiversity, or vice versa) may be substantial, as evidence suggests that plant species richness declines more rapidly towards the North Pole than fungal species richness, which reaches a plateau.

https://www.nature.com/articles/s41559-018-0573-8

Soil: how much do we value this critical resource?
Resource Type: Maps & Documents, Documents, Scientific-Technical Reports
Country: IT
Author: JRC’s NC-SOIL project
Year: 2018
Publisher: European Commission
Attachments: PDF icon JRC_highlights_eBook

Soil condition underpins food security, green growth, bioeconomies and aboveground biodiversity; it regulates climate, the hydrological and nutrient cycles, while  mitigating climate change. Soils provide resilience against floods and droughts, buffer the effects of pollutants and preserve cultural heritage. Healthy, functional soils underpin several targets of the Sustainable Development Goals.

Pressures on this finite, non-renewable resource, due to competition for land or inappropriate land management choices, severely impact soil functions. Amplified by climate change, these pressures lead to degradation processes such as erosion, contamination, loss of organic matter, shallow landsliding and, in extreme cases, a complete loss of the resource.

https://esdac.jrc.ec.europa.eu/public_path/shared_folder/doc_pub/JRC_Soil_Highlights_eBook_0.pdf

 

 

Climate-scale modelling of suspended sediment load in an Alpine catchment debris flow (Rio Cordon-northeastern Italy)
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018

Pulsing storms and prolonged rainfall can drive hydrological damaging events in mountain regions with soil erosion and debris flow in river catchments. The paper presents a parsimonious model for estimating climate forcing on sediment loads in an Alpine catchment (Rio Cordon, northeastern Italian Alps). Hydroclimatic forcing was interpreted by the novel CliSMSSL (Climate-Scale Modelling of Suspended Sediment Load) model to estimate annual sediment loads. We used annual data on suspended-solid loads monitored at an experimental station from 1987 to 2001 and on monthly precipitation data. The quality of sediment load data was critically examined, and one outlying year was identified and removed from further analyses. This outlier revealed that our model underestimates exceptionally high sediment loads in years characterized by a severe flood event. For all other years, the CliSMSSL performed well, with a determination coefficient (R2) equal to 0.67 and a mean absolute error (MAE) of 129 Mg y−1. The calibrated model for the period 1986–2010 was used to reconstruct sediment loads in the river catchment for historical times when detailed precipitation records are not available. For the period 1810–2010, the model results indicate that the past centuries have been characterized by large interannual to interdecadal fluctuations in the conditions affecting sediment loads. This paper argues that climate-induced erosion processes in Alpine areas and their impact on environment should be given more attention in discussions about climate-driven strategies. Future work should focus on delineating the extents of these findings (e.g., at other catchments of the European Alpine belt) as well as investigating the dynamics for the formation of sediment loads.

https://www.sciencedirect.com/science/article/pii/S0169555X18300849

Mitigation potential of soil carbon management overestimated by neglecting N2O emissions
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018
International initiatives such as the ‘4 per 1000’ are promoting enhanced carbon (C) sequestration in agricultural soils as a way to mitigate greenhouse gas emissions1. However, changes in soil organic C turnover feed back into the nitrogen (N) cycle2, meaning that variation in soil nitrous oxide (N2O) emissions may offset or enhance C sequestration actions3. Here we use a biogeochemistry model on approximately 8,000 soil sampling locations in the European Union4 to quantify the net CO2 equivalent (CO2e) fluxes associated with representative C-mitigating agricultural practices. Practices based on integrated crop residue retention and lower soil disturbance are found to not increase N2O emissions as long as C accumulation continues (until around 2040), thereafter leading to a moderate C sequestration offset mostly below 47% by 2100. The introduction of N-fixing cover crops allowed higher C accumulation over the initial 20 years, but this gain was progressively offset by higher N2O emissions over time. By 2060, around half of the sites became a net source of greenhouse gases. We conclude that significant CO2 mitigation can be achieved in the initial 20–30 years of any C management scheme, but after that N inputs should be controlled through appropriate management.
 
Progress in the management contaminated sites in Europe
Resource Type: Documents, Scientific-Technical Reports, Maps & Documents
Year: 2018
Attachments: PDF icon EUR29124.pdf

On this report the findings of the questionnaire commissioned by the European Commission Joint Research Centre for the revision of the Indicator "Progress in the management of contaminated site in Europe" in 2016 are presented. It has been produced with the contribution of data provided by the National Reference Centres (NRCs) in member states and cooperating countries within EIONET and funded by the country to work with the EEA and relevant European Topic Centres (ETCs) in specific thematic areas related to the EEA work programme

 

Soil Thematic Strategy: An important contribution to policy support, research, data development and raising the awareness
Resource Type: Maps & Documents, Documents, Publications in Journals
Year: 2018

There has been the recognition that trans-national binding legal agreements related to soils are very difficult to achieve, given the sensitivities related to national sovereignty in relation to land and soils. However, the Soil Thematic Strategy played an important role to raise the awareness of soil importance, integrate soils in different policy areas (agriculture, climate change, SDGs), develop research findings and finally increase our know how on European Soils. The Soil Thematic Strategy continue to be the main policy instrument dedicated to foster soil protection in the European Union (EU). The EU consider the importance of soils and land degradation taking into account global challenges such as the sustainable production intensification, food security, climate change and escalating population growth. During the last decade both the 7th Framework Programme for Research (FP7) and the HORIZON2020 financed research and innovation projects for advancing soil protection and better understanding of soil management in EU.

https://www.sciencedirect.com/science/article/pii/S2468584417300533

Copper distribution in European topsoils: An assessment based on LUCAS soil survey
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018
Copper (Cu) distribution in soil is influenced by climatic, geological and pedological factors. Apart from geological sources and industrial pollution, other anthropogenic sources, related to the agricultural activity, may increase copper levels in soils, especially in permanent crops such as olive groves and vineyards. This study uses 21,682 soil samples from the LUCAS topsoil survey to investigate copper distribution in the soils of 25 European Union (EU) Member States.
 
Generalized Linear Models (GLM) were used to investigate the factors driving copper distribution in EU soils. Regression analysis shows the importance of topsoil properties, land cover and climate in estimating Cu concentration. Meanwhile, a copper regression model confirms our hypothesis that different agricultural management practices have a relevant influence on Cu concentration. Besides the traditional use of copper as a fungicide for treatments in several permanent crops, the combined effect of soil properties such as high pH, soil organic carbon and clay, with humid and wet climatic conditions favours copper accumulation in soils of vineyards and tree crops. Compared to the overall average Cu concentration of 16.85 mg kg−1, vineyards have the highest mean soil Cu concentration (49.26 mg kg−1) of all land use categories, followed by olive groves and orchards.
 
Gaussian Process Regression (GPR) combined with kriging were used to map copper concentration in topsoils and to evidence the presence of outliers. GPR proved to be performant in predicting Cu concentration, especially in combination with kriging, accounting for 66% of Cu deviance. The derived maps are novel as they include information about the importance of topsoil properties in the copper mapping process, thus improving its accuracy. Both models highlight the influence of land management practices in copper concentration and the strong correlation between topsoil copper and vineyards.
LUCAS Soil, the largest expandable soil dataset for Europe: a review
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018

Soil is a non‐renewable resource that requires constant monitoring to prevent its degradation and promote its sustainable management. The ‘Land Use/Cover Area frame statistical Survey Soil’ (LUCAS Soil) is an extensive and regular topsoil survey that is carried out across the European Union to derive policy‐relevant statistics on the effect of land management on soil characteristics. Approximately 45 000 soil samples have been collected from two time‐periods, 2009–2012 and 2015. A new sampling series will be undertaken in 2018, with new measurements included. The organization for the 2018 sampling campaign represents an opportunity to summarize past LUCAS Soil achievements and present its future objectives. In 2009–2012 and 2015, LUCAS Soil surveys targeted physicochemical properties, including pH, organic carbon, nutrient concentrations and cation exchange capacity. Data from 2009–2012 (ca. 22 000 points) and derived output (more than 20 maps) are available freely from the European Soil Data Centre website. Analyses of samples collected during 2015 are ongoing and data will be available at the end of 2017. In the 2018 LUCAS Soil sampling campaign, additional properties, including bulk density, soil biodiversity, specific measurements for organic‐rich soil and soil erosion will be measured. Here we present the current dataset (LUCAS Soil 2009–2012 and 2015), its potential for reuse and future development plans (LUCAS Soil 2018 and over). LUCAS Soil represents the largest harmonized open‐access dataset of topsoil properties available for the European Union at the global scale. It was developed as an expandable resource, with the possibility to add new properties and sampling locations during successive sampling campaigns. Data are available to the scientific community and decision makers, thus contributing to both research and the development of the land‐focused policy agenda.

https://onlinelibrary.wiley.com/doi/full/10.1111/ejss.12499

Pan-European landslide susceptibility mapping: ELSUS Version 2
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018

We present an updated version of the European landslide susceptibility map ELSUS 1000 released through the European Soil Data Centre in 2013. The ELSUS V2 map shows the landslide susceptibility zonation for individual climate-physiographic zones across Europe. ELSUS V2 covers a larger area of Europe than ELSUS 1000 at a higher spatial resolution (200 × 200 m). The updated map was prepared using the same semi-quantitative method as for ELSUS 1000, combining landslide frequency ratios information with a spatial multi-criteria evaluation model of three thematic predictors: slope angle, shallow subsurface lithology and land cover. However, the new map was prepared using also: (i) an extended landslide inventory, containing 30% of additional locations for model calibration, map validation and classification and (ii) a new lithological data set derived from the International Hydrogeological Map of Europe (IHME). The new version of the map increases the overall predictive performance of ELSUS by 8%.

https://www.tandfonline.com/doi/full/10.1080/17445647.2018.1432511

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

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

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

An assessment of the global impact of 21st century land use change on soil erosion
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

Human activity and related land use change are the primary cause of accelerated soil erosion, which has substantial implications for nutrient and carbon cycling, land productivity and in turn, worldwide socio-economic conditions. Here we present an unprecedentedly high resolution (250 × 250 m) global potential soil erosion model, using a combination of remote sensing, GIS modelling and census data. We challenge the previous annual soil erosion reference values as our estimate, of 35.9 Pg yr−1 of soil eroded in 2012, is at least two times lower. Moreover, we estimate the spatial and temporal effects of land use change between 2001 and 2012 and the potential offset of the global application of conservation practices. Our findings indicate a potential overall increase in global soil erosion driven by cropland expansion. The greatest increases are predicted to occur in Sub-Saharan Africa, South America and Southeast Asia. The least developed economies have been found to experience the highest estimates of soil erosion rates.

https://www.nature.com/articles/s41467-017-02142-7

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