Publications in Journals

Peer review Papers published in International Journals and Magazines.

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). An important number of papers has been published in high impact factor journals: Nature, Nature Climate Change, Nature Communications, Science Advances, Science, PNAS, Global Change Biology, Science of the Total Environment, etc.

The publications are relevant to soil themes, functions and threats. The datasets generated during and/or analysed during most of the presented studies are available in the ESDAC datasets section. Almost all the publications are Open Access. 

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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

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

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

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

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

The G2 erosion model: An algorithm for month-time step assessments
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018

A detailed description of the G2 erosion model is presented, in order to support potential users. G2 is a complete, quantitative algorithm for mapping soil loss and sediment yield rates on month-time intervals. G2 has been designed to run in a GIS environment, taking input from geodatabases available by European or other international institutions. G2 adopts fundamental equations from the Revised Universal Soil Loss Equation (RUSLE) and the Erosion Potential Method (EPM), especially for rainfall erosivity, soil erodibility, and sediment delivery ratio. However, it has developed its own equations and matrices for the vegetation cover and management factor and the effect of landscape alterations on erosion. Provision of month-time step assessments is expected to improve understanding of erosion processes, especially in relation to land uses and climate change. In parallel, G2 has full potential to decision-making support with standardised maps on a regular basis. Geospatial layers of rainfall erosivity, soil erodibility, and terrain influence, recently developed by the Joint Research Centre (JRC) on a European or global scale, will further facilitate applications of G2

https://www.sciencedirect.com/science/article/pii/S0013935117314044

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

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.

Soil organic carbon estimation in croplands by hyperspectral remote APEX data using the LUCAS topsoil database
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2018

The most commonly used approach to estimate soil variables from remote-sensing data entails time-consuming and expensive data collection including chemical and physical laboratory analysis. Large spectral libraries could be exploited to decrease the effort of soil variable estimation and obtain more widely applicable models. We investigated the feasibility of a new approach, referred to as bottom-up, to provide soil organic carbon (SOC) maps of bare cropland fields over a large area without recourse to chemical analyses, employing both the pan-European topsoil database from the Land Use/Cover Area frame statistical Survey (LUCAS) and Airborne Prism Experiment (APEX) hyperspectral airborne data. This approach was tested in two areas having different soil characteristics: the loam belt in Belgium, and the Gutland–Oesling region in Luxembourg. Partial least square regression (PLSR) models were used in each study area to estimate SOC content, using both bottom-up and traditional approaches. The PLSR model’s accuracy was tested on an independent validation dataset. Both approaches provide SOC maps having a satisfactory level of accuracy (RMSE = 1.5–4.9 g·kg−1; ratio of performance to deviation (RPD) = 1.4–1.7) and the inter-comparison did not show differences in terms of RMSE and RPD either in the loam belt or in Luxembourg. Thus, the bottom-up approach based on APEX data provided high-resolution SOC maps over two large areas showing the within- and between-field SOC variability

https://www.mdpi.com/2072-4292/10/2/153

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

Potential Sources of Anthropogenic Copper Inputs to European Agricultural Soils
Resource Type: Maps & Documents, Documents, Publications in Journals
Year: 2018

In the European Union (EU), copper concentration in agricultural soil stems from anthropogenic activities and natural sources (soil and geology). This manuscript reports a statistical comparison of copper concentrations at different levels of administrative units, with a focus on agricultural areas. Anthropogenic sources of diffuse copper contamination include fungicidal treatments, liquid manure (mainly from pigs), sewage sludge, atmospheric deposition, mining activities, local industrial contamination and particles from car brakes. Sales of fungicides in the EU are around 158,000 tonnes annually, a large proportion of which are copper based and used extensively in vineyards and orchards. Around 10 million tonnes of sewage sludge is treated annually in the EU, and 40% of this (which has a high copper content) is used as fertilizer in agriculture. In the EU, 150 million pigs consume more than 6.2 million tonnes of copper through additives in their feed, and most of their liquid manure ends up in agricultural soil. These three sources (sales of fungicides, sewage sludge and copper consumption for pigs feed) depend much on local traditional farming practices. Recent research towards replacing copper spraying in vineyards and policy developments on applying sewage and controlling the feed given to pigs are expected to reduce copper accumulation in agricultural soil.

https://www.mdpi.com/2071-1050/10/7/2380

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

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.
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

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

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

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

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

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

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?
 
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

Soil legacy data rescue via GlobalSoilMap and other international and national initiatives
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

Legacy soil data have been produced over 70 years in nearly all countries of the world. Unfortunately, data, information and knowledge are still currently fragmented and at risk of getting lost if they remain in a paper format. To process this legacy data into consistent, spatially explicit and continuous global soil information, data are being rescued and compiled into databases. Thousands of soil survey reports and maps have been scanned and made available online. The soil profile data reported by these data sources have been captured and compiled into databases. The total number of soil profiles rescued in the selected countries is about 800,000. Currently, data for 117, 000 profiles are compiled and harmonized according to GlobalSoilMap specifications in a world level database (WoSIS). The results presented at the country level are likely to be an underestimate. The majority of soil data is still not rescued and this effort should be pursued. The data have been used to produce soil property maps. We discuss the pro and cons of top-down and bottom-up approaches to produce such maps and we stress their complementarity. We give examples of success stories. The first global soil property maps using rescued data were produced by a top-down approach and were released at a limited resolution of 1 km in 2014, followed by an update at a resolution of 250 m in 2017. By the end of 2020, we aim to deliver the first worldwide product that fully meets the GlobalSoilMap specifications.

https://www.sciencedirect.com/science/article/pii/S2214242816300699

Storage and stability of biochar-derived carbon and total organic carbon in relation to minerals in an acid forest soil of the Spanish Atlantic area
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

Biochar can largely contribute to enhance organic carbon (OC) stocks in soil and improve soil quality in forest and agricultural lands. Its contribution depends on its recalcitrance, but also on its interactions with minerals and other organic compounds in soil. Thus, it is important to study the link between minerals, natural organic matter and biochar in soil. In this study, we investigated the incorporation of biochar-derived carbon (biochar-C) into various particle-size fractions with contrasting mineralogy and the effect of biochar on the storage of total OC in the particle-size fractions in an acid loamy soil under Pinus radiata (C3 type) in the Spanish Atlantic area. We compared plots amended with biochar produced from Miscanthus sp. (C4 type) with control plots (not amended). We separated sand-, silt-, and clay-size fractions in samples collected from 0 to 20-cm depth. In each fraction, we analyzed clay minerals, metallic oxides and oxy-hydroxides, total OC and biochar-C. The results showed that 51% of the biochar-C was in fractions < 20 μm one year after the application of biochar. Biochar-C stored in clay-size fractions (0.2–2 μm, 0.05–0.2 μm, < 0.05 μm) was only 14%. Even so, we observed that biochar-C increased with decreasing particle-size in clay-size fractions, as it occurred with the vermiculitic phases and metallic oxides and oxy-hydroxides. Biochar also affected to the distribution of total OC among particle-size fractions. Total OC concentration was greater in fractions 2–20 μm, 0.2–2 μm, 0.05–0.2 μm in biochar-amended plots than in control plots. This may be explained by the adsorption of dissolved OC from fraction < 0.05 μm onto biochar particles. The results suggested that interactions between biochar, minerals and pre-existing organic matter already occurred in the first year.

https://www.sciencedirect.com/science/article/pii/S0048969717303698

Assessment of the impacts of clear-cutting on soil loss bywater erosion in Italian forests: First comprehensive monitoring and modelling approach
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017
As a member of the European Union, Italy has committed to the maintenance and protection of its forests based on sustainable forest development and management practices. According to Eurostat, Italy has the seventh largest forest surface available for wood supply in the EU-28, which is equal to 8.086 million hectares. For 2012, the Italian National Institute of Statistics estimated the total roundwood production of Italy to be 7.7 million m3, from a harvested forest surface of 61,038 ha. Large parts of the country's forests, mainly located in vulnerable mountainous landscapes that are highly sensitive to environmental changes, are subject to anthropogenic disturbance driven by wood supply interests. Despite the extensive logging activities and the well-known impacts that such management practices have on the soil-related forest ecosystems, there is a lack of spatially and temporally explicit information about the removal of trees. Hence, this study aims to: i) assess the soil loss by water erosion in Italian forest areas, ii) map forest harvests and iii) evaluate the effects of logging activities in terms of soil loss by means of comprehensive remote sensing and GIS modelling techniques. The study area covers about 785.6 × 104 ha, which corresponds to the main forest units of the CORINE land cover 2006 database (i.e. broad-leaved forests, coniferous forests and mixed forests). Annual forest logging activities were mapped using Landsat imagery. Validation procedures were applied. A revised version of the Universal Soil Loss Equation (USLE) was used to predict the soil loss potential due to rill and inter-rill processes. To ensure a thorough modelling approach, the input parameters were calculated using the original methods reported in the USDA handbooks. The derived high-resolution data regarding forest cover change shows that 317,535 ha (4.04% of the total forest area in Italy) were harvested during the period under review. The predicted long-term annual average soil loss rate was 0.54 Mg ha− 1 yr− 1. The average rate of soil loss in forests that remained undisturbed during the modelled period is equal to 0.33 Mg ha− 1 yr− 1. Notably, about half of the soil loss (45.3%) was predicted for the logged areas, even though these cover only about 10.6% of the Italian forests. The identified erosion hotspots may represent a serious threat for the soil-related forest ecosystems, and are in contrast to the EC Thematic Strategy for Soil Protection and Water Framework Directive.
 
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