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 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

Soil natural capital in europe; a framework for state and change assessment
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

Soils underpin our existence through food production and represent the largest terrestrial carbon store. Understanding soil state-and-change in response to climate and land use change is a major challenge. Our aim is to bridge the science-policy interface by developing a natural capital accounting structure for soil, for example, attempting a mass balance between soil erosion and production, which indicates that barren land, and woody crop areas are most vulnerable to potential soil loss. We test out our approach using earth observation, modelling and ground based sample data from the European Union’s Land Use/Cover Area frame statistical Survey (LUCAS) soil monitoring program. Using land cover change data for 2000–2012 we are able to identify land covers susceptible to change, and the soil resources most at risk. Tree covered soils are associated with the highest carbon stocks, and are on the increase, while areas of arable crops are declining, but artificial surfaces are increasing. The framework developed offers a substantial step forward, demonstrating the development of biophysical soil accounts that can be used in wider socio-economic and policy assessment; initiating the development of an integrated soil monitoring approach called for by the United Nations Intergovernmental Technical Panel on Soils.

https://www.nature.com/articles/s41598-017-06819-3

 

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

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

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

The Impact of Policy Instruments on Soil Multifunctionality in the European Union
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2017

Agricultural ecosystems provide a range of benefits that are vital to human well-being. These benefits are dependent on several soil functions that are affected in different ways by legislation from the European Union, national, and regional levels. We evaluated current European Union soil-related legislation and examples of regional legislation with regard to direct and indirect impacts on five soil functions: the production of food, fiber, and fuel; water purification and regulation; carbon sequestration and climate regulation; habitat for biodiversity provisioning; and the recycling of nutrients/agro-chemicals. Our results illustrate the diversity of existing policies and the complex interactions present between different spatial and temporal scales. The impact of most policies, positive or negative, on a soil function is usually not established, but depends on how the policy is implemented by local authorities and the farmers. This makes it difficult to estimate the overall state and trends of the different soil functions in agricultural ecosystems. To implement functional management and sustainable use of the different soil functions in agricultural ecosystems, more knowledge is needed on the policy interactions as well as on the impact of management options on the different soil functions

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

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

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

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

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

Mapping topsoil physical properties at European scale using the LUCAS database
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016
The Land Use and Cover Area frame Statistical survey (LUCAS) aimed at the collecting harmonised data about the state of land use/cover over the extent of European Union (EU). Among these 2 · 105 land use/cover observations selected for validation, a topsoil survey was conducted at about 10% of these sites. Topsoil sampling locations were selected as to be representative of European landscape using a Latin hypercube stratified random sampling, taking into account CORINE land cover 2000, the Shuttle Radar Topography Mission (SRTM) DEM and its derived slope, aspect and curvature.
 
In this study we will discuss how the LUCAS topsoil database can be used to map soil properties at continental scale over the geographical extent of Europe. Several soil properties were predicted using hybrid approaches like regression kriging. In this paper we describe the prediction of topsoil texture and related derived physical properties. Regression models were fitted using, along other variables, remotely sensed data coming from the MODIS sensor. The high temporal resolution of MODIS allowed detecting changes in the vegetative response due to soil properties, which can then be used to map soil features distribution. We will also discuss the prediction of intrinsically collinear variables like soil texture which required the use of models capable of dealing with multivariate constrained dependent variables like Multivariate Adaptive Regression Splines (MARS).
 
Cross validation of the fitted models proved that the LUCAS dataset constitutes a good sample for mapping purposes leading to cross-validation R2 between 0.47 and 0.50 for soil texture and normalized errors between 4 and 10%.

https://www.sciencedirect.com/science/article/pii/S0016706115300173

Modelling monthly soil losses and sediment yields in Cyprus
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

The aim of this study was to map soil erosion on the Mediterranean island of Cyprus. The G2 model, an empirical model for month-time step erosion assessments, was used. Soil losses in Cyprus were mapped at a 100 m cell size, while sediment yields at a sub-basin scale of 0.62 km2 mean size. The results indicated a mean annual erosion rate of 11.75 t ha−1 y−1, with October and November being the most erosive months. The 34% of the island's surface was found to exceed non-sustainable erosion rates (>10 t ha−1 y−1), with sclerophyllous vegetation, coniferous forests, and non-irrigated arable land being the most extensive non-sustainable erosive land covers. The mean sediment delivery ratio (SDR) was found to be 0.26, while the mean annual specific sediment yield (SSY) value for Cyprus was found to be 3.32 t ha−1 y−1. The annual sediment yield of the entire island was found to be 2.746 Mt y−1. This study was the first to provide complete and detailed erosion figures for Cyprus at a country scale. The geodatabase and all information records of the study are available at the European Soil Data Centre (ESDAC) of the Joint Research Centre (JRC).

https://www.tandfonline.com/doi/abs/10.1080/17538947.2016.1156776

Rainfall erosivity in Italy: A national scale spatio-temporal assessment
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

 

Soil erosion by water is a serious threat for the Mediterranean region. Raindrop impacts and consequent runoff generation are the main driving forces of this geomorphic process of soil degradation. The potential ability for rainfall to cause soil loss is expressed as rainfall erosivity, a key parameter required by most soil loss prediction models. In Italy, rainfall erosivity measurements are limited to few locations, preventing researchers from effectively assessing the geography and magnitude of soil loss across the country. The objectives of this study were to investigate the spatio-temporal distribution of rainfall erosivity in Italy and to develop a national-scale grid-based map of rainfall erosivity. Thus, annual rainfall erosivity values were measured and subsequently interpolated using a geostatistical approach. Time series of pluviographic records (10-years) with high temporal resolution (mostly 30-min) for 386 meteorological stations were analysed. Regression-kriging was used to interpolate rainfall erosivity values of the meteorological stations to an Italian rainfall erosivity map (500-m). A set of 23 environmental covariates was tested, of which seven covariates were selected based on a stepwise approach (mostly significant at the 0.01 level). The interpolation method showed a good performance for both the cross-validation data set ( = 0.777) and the fitting data set (R2 = 0.779)

https://www.tandfonline.com/doi/full/10.1080/17538947.2016.1148203

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

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

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

 

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

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

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

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

 

Assessment of Soil Organic Carbon Stocks under the Future Climate and Land Cover Changes in Europe
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

Soil organic carbon plays an important role in the carbon cycling of terrestrial ecosystems, variations in soil organic carbon stocks are very important for the ecosystem. In this study, a geostatistical model was used for predicting current and future soil organic carbon (SOC) stocks in Europe. The first phase of the study predicts current soil organic carbon content by using stepwise multiple linear regression and ordinary kriging and the second phase of the study projects the soil organic carbon to the near future (2050) by using a set of environmental predictors. We demonstrate here an approach to predict present and future soil organic carbon stocks by using climate, land cover, terrain and soil data and their projections. The covariates were selected for their role in the carbon cycle and their availability for the future model. The regression-kriging as a base model is predicting current SOC stocks in Europe by using a set of covariates and dense SOC measurements coming from LUCAS Soil Database. The base model delivers coefficients for each of the covariates to the future model. The overall model produced soil organic carbon maps which reflect the present and the future predictions (2050) based on climate and land cover projections. The data of the present climate conditions (long-term average (1950–2000)) and the future projections for 2050 were obtained from WorldClim data portal. The future climate projections are the recent climate projections mentioned in the Fifth Assessment IPCC report. These projections were extracted from the global climate models (GCMs) for four representative concentration pathways (RCPs). The results suggest an overall increase in SOC stocks by 2050 in Europe (EU26) under all climate and land cover scenarios, but the extent of the increase varies between the climate model and emissions scenarios.

https://www.sciencedirect.com/science/article/pii/S0048969716305095

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

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

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

 

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

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

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

Spatio-temporal analysis of rainfall erosivity and erosivity density in Greece
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

Rainfall erosivity considers the effects of rainfall amount and intensity on soil detachment. Rainfall erosivity is most commonly expressed as the R-factor in the Universal Soil Loss Equation (USLE) and its revised version, RUSLE. Several studies focus on spatial analysis of rainfall erosivity ignoring the intra-annual variability of this factor. This study assesses rainfall erosivity in Greece on a monthly basis in the form of the RUSLE R-factor, based on a 30-min data from 80 precipitation stations covering an average period of almost 30 years. The spatial interpolation was done through a Generalised Additive Model (GAM). The observed intra-annual variability of rainfall erosivity proved to be high. The warm season is 3 times less erosive than the cold one. November, December and October are the most erosive months contrary to July, August and May which are the least erosive. The proportion between rainfall erosivity and precipitation, expressed as erosivity density, varies throughout the year. Erosivity density is low in the first 5 months (January–May) and is relatively high in the remaining 7 months (June–December) of the year. The R-factor maps reveal also a high spatial variability with elevated values in the western Greece and Peloponnesus and very low values in Western Macedonia, Thessaly, Attica and Cyclades. The East–West gradient of rainfall erosivity differs per month with a smoother distribution in summer and a more pronounced gradient during the winter months. The aggregated data for the 12 months result in an average R-factor of 807 MJ mm ha− 1 h− 1 year− 1 with a range from 84 to 2825 MJ mm ha− 1 h− 1 year− 1. The combination of monthly R-factor maps with vegetation coverage and tillage maps contributes to better monitor soil erosion risk at national level and monthly basis.

https://www.sciencedirect.com/science/article/pii/S0341816215301156

Assessment of soil organic carbon stocks under future climate and land cover changes in Europe
Resource Type: Maps & Documents, Documents, Publications in Journals
Year: 2016

Soil organic carbon plays an important role in the carbon cycling of terrestrial ecosystems, variations in soil organic carbon stocks are very important for the ecosystem. In this study, a geostatistical model was used for predicting current and future soil organic carbon (SOC) stocks in Europe. The first phase of the study predicts current soil organic carbon content by using stepwise multiple linear regression and ordinary kriging and the second phase of the study projects the soil organic carbon to the near future (2050) by using a set of environmental predictors. We demonstrate here an approach to predict present and future soil organic carbon stocks by using climate, land cover, terrain and soil data and their projections. The covariates were selected for their role in the carbon cycle and their availability for the future model. The regression-kriging as a base model is predicting current SOC stocks in Europe by using a set of covariates and dense SOC measurements coming from LUCAS Soil Database. The base model delivers coefficients for each of the covariates to the future model. The overall model produced soil organic carbon maps which reflect the present and the future predictions (2050) based on climate and land cover projections. The data of the present climate conditions (long-term average (1950–2000)) and the future projections for 2050 were obtained from WorldClim data portal. The future climate projections are the recent climate projections mentioned in the Fifth Assessment IPCC report. These projections were extracted from the global climate models (GCMs) for four representative concentration pathways (RCPs). The results suggest an overall increase in SOC stocks by 2050 in Europe (EU26) under all climate and land cover scenarios, but the extent of the increase varies between the climate model and emissions scenarios.

https://www.sciencedirect.com/science/article/pii/S0048969716305095

A method of establishing a transect for biodiversity and ecosystem function monitoring across Europe
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

The establishment of the range of soil biodiversity found within European soils is needed to guide EU policy development regarding the protection of soil. Such a base-line should be collated from a wide-ranging sampling campaign to ensure that soil biodiversity from the majority of soil types, land-use or management systems, and European climatic (bio-geographical zones) were included. This paper reports the design and testing of a method to achieve the large scale sampling associated with the establishment of such a baseline, carried out within the remit of the EcoFINDERS project, and outlines points to consider when such a task is undertaken.

Applying a GIS spatial selection process, a sampling campaign was undertaken by 13 EcoFINDERS partners across 11 countries providing data on the range of indicators of biodiversity and ecosystem functions including; micro and meso fauna biodiversity, extracellular enzyme activity, PLFA and community level physiological profiling (MicroResp™ and Biolog™). Physical, chemical and bio-geographical parameters of the 81 sites sampled were used to determine whether the model predicted a wide enough range of sites to allow assessment of the biodiversity indicators tested.

Discrimination between the major bio-geographical zones of Atlantic and Continental was possible for all land-use types. Boreal and Alpine zones only allowed discrimination in the most common land-use type for that area e.g. forestry and grassland sites, respectively, while the Mediterranean zone did not have enough sites sampled to draw conclusions across all land-use types. The method used allowed the inclusion of a range of land-uses in both the model prediction stage and the final sites sampled. The establishment of the range of soil biodiversity across Europe is possible, though a larger targeted campaign is recommended. The techniques applied within the EcoFINDERS sampling would be applicable to a larger campaign

https://www.sciencedirect.com/science/article/abs/pii/S0929139315300342

Heavy metals in agricultural soils of the European Union with implications for food safety
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

Soil plays a central role in food safety as it determines the possible composition of food and feed at the root of the food chain. However, the quality of soil resources as defined by their potential impact on human health by propagation of harmful elements through the food chain has been poorly studied in Europe due to the lack of data of adequate detail and reliability. The European Union's first harmonized topsoil sampling and coherent analytical procedure produced trace element measurements from approximately 22,000 locations. This unique collection of information enables a reliable overview of the concentration of heavy metals, also referred to as metal(loid)s including As, Cd, Cr, Cu, Hg, Pb, Zn, Sb. Co, and Ni. In this article we propose that in some cases (e.g. Hg and Cd) the high concentrations of soil heavy metal attributed to human activity can be detected at a regional level. While the immense majority of European agricultural land can be considered adequately safe for food production, an estimated 6.24% or 137,000 km2 needs local assessment and eventual remediation action.

https://www.sciencedirect.com/science/article/pii/S0160412015301203

Mapping regional patterns of large forest fires in the Wildland-Urban Interface areas in Europe
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

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

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

High resolution spatiotemporal analysis of erosion risk per land cover category in Korçe region, Albania
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

Some recent land use changes in Albania, such as deforestation, cropland abandonment, and urban sprawl, have caused serious increase of erosion risk. The main objective of this study was to map erosion risk in Korçe region and assess the degree at which every land use is concerned. The G2 erosion model was applied, which can provide erosion maps and statistical figures at month-time intervals using input from free European and global geodatabases. The mapping results in Korçe region were derived at a 30-m cell size, which is an innovation for G2. Autumn-winter months were found to be the most erosive, with average erosion rates reaching the maximum in November and December, i.e. 2.62 and 2.36 t/ha, respectively, while the annual rate was estimated at 10.25 t/ha/yr. Natural grasslands, shurblands, mixed forests, and vineyards showed to exhibit the highest mean erosion rates, while shrublands, broad-leaved forests and natural grasslands were found to be the most extended land covers risky for non-sustainable erosion rates (i.e. >10 t/ha/yr). A detailed examination of the detected hot spots is now necessary by the competent authorities, in order to apply appropriate, site-specific conservation measures. Notably, use of SPOT VGT data did not prevent the maps from having extended gaps due to cloudiness. Sentinel-2 time series, freely available by the European Space Agency (ESA), have the potential to improve spatiotemporal coverage of V-factor, thus further empowering the G2 model, in the near future.

https://link.springer.com/article/10.1007/s12145-016-0269-z

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

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

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

Regionalization of monthly rainfall erosivity patterns in Switzerland
Resource Type: Documents, Publications in Journals, Maps & Documents
Year: 2016

One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy and a maximum 30 min intensity (I30). Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a regional characteristic and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modeling approach to assess simultaneously spatial and monthly patterns of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10 min temporal resolution to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal patterns of the R-factor for each month across Switzerland. The monthly R-factor is mapped by summarizing the predicted R-factor of the regression equation and the corresponding residues of the regression, which are interpolated by ordinary kriging (regression–kriging). As spatial covariates, a variety of precipitation indicator data has been included such as snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily Alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with the highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have the lowest rainfall erosivity. A proportion of 62 % of the total annual rainfall erosivity is identified within four months only (June–September). The highest erosion risk can be expected in July, where not only rainfall erosivity but also erosivity density is high. In addition to the intra-annual temporal regime, a spatial variability of this seasonality was detectable between different regions of Switzerland. The assessment of the dynamic behavior of the R-factor is valuable for the identification of susceptible seasons and regions.

https://hess.copernicus.org/articles/20/4359/2016/