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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

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

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

An 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

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

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

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

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

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

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

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

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

This report presents the result of WP2 of the RECARE project. One of the objectives of WP2 (Base for RECARE data collection and methods) is to provide an improved overview of existing information on soil threats and degradation at the European scale. The report is written by a group of experts from the RECARE team, coordinated by Bioforsk. In total, 60 persons were included in the process of writing, reviewing and editing the report. Eleven soil threats were identified for the report. These soil threats are soil erosion by water, soil erosion by wind, decline of organic matter (OM) in peat, decline of OM in minerals soils, soil compaction, soil sealing, soil contamination, soil salinization, desertification, flooding and landslides and decline in soil biodiversity.
Editors: Jannes Stolte, Mehreteab Tesfai, Lillian Øygarden, Sigrun Kværnø (NIBIO), Jacob Keizer, Frank Verheijen (University of Aveiro), Panos Panagos, Cristiano Ballabio (JRC), Rudi Hessel (Alterra WUR)
EUR27607

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

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

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

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

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

The idea of offsetting anthropogenic CO2 emissions by increasing global soil organic carbon (SOC), as recently proposed by French authorities ahead of COP21 in the ‘four per mil’ initiative, is notable. However, a high uncertainty still exits on land C balance components. In particular, the role of erosion in the global C cycle is not totally disentangled, leading to disagreement whether this process induces lands to be a source or sink of CO2. To investigate this issue, we coupled soil erosion into a biogeochemistry model, running at 1 km2 resolution across the agricultural soils of the European Union (EU). Based on data‐driven assumptions, the simulation took into account also soil deposition within grid cells and the potential C export to riverine systems, in a way to be conservative in a mass balance. We estimated that 143 of 187 Mha have C erosion rates <0.05 Mg C ha−1 yr−1, although some hot‐spot areas showed eroded SOC >0.45 Mg C ha−1 yr−1. In comparison with a baseline without erosion, the model suggested an erosion‐induced sink of atmospheric C consistent with previous empirical‐based studies. Integrating all C fluxes for the EU agricultural soils, we estimated a net C loss or gain of −2.28 and +0.79 Tg yr−1 of CO2eq, respectively, depending on the value for the short‐term enhancement of soil C mineralization due to soil disruption and displacement/transport with erosion. We concluded that erosion fluxes were in the same order of current carbon gains from improved management. Even if erosion could potentially induce a sink for atmospheric CO2, strong agricultural policies are needed to prevent or reduce soil erosion, in order to maintain soil health and productivity.

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

Understanding spatial and temporal patterns in land susceptibility to wind erosion is essential to design effective management strategies to control land degradation. The knowledge about the land surface susceptible to wind erosion in European contexts shows significant gaps. The lack of researches, particularly at the landscape to regional scales, prevents national and European institutions from taking actions aimed at an effective mitigating of land degradation. This study provides a preliminary pan‐European assessment that delineates the spatial patterns of land susceptibility to wind erosion and lays the groundwork for future modelling activities. An Index of Land Susceptibility to Wind Erosion (ILSWE) was created by combining spatiotemporal variations of the most influential wind erosion factors (i.e. climatic erosivity, soil erodibility, vegetation cover and landscape roughness). The sensitivity of each input factor was ranked according to fuzzy logic techniques. State‐of‐the‐art findings within the literature on soil erodibility and land susceptibility were used to evaluate the outcomes of the proposed modelling activity. Results show that the approach is suitable for integrating wind erosion information and environmental factors. Within the 34 European countries under investigation, moderate and high levels of land susceptibility to wind erosion were predicted, ranging from 25·8 to 13·0 M ha, respectively (corresponding to 5·3 and 2·9% of total area). New insights into the geography of wind erosion susceptibility in Europe were obtained and provide a solid basis for further investigations into the spatial variability and susceptibility of land to wind erosion across Europe. 

https://onlinelibrary.wiley.com/doi/full/10.1002/ldr.2318

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

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

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

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

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

As a follow up and an advancement of the recently published Rainfall Erosivity Database at European Scale (REDES) and the respective mean annual R-factor map, the monthly aspect of rainfall erosivity has been added to REDES. Rainfall erosivity is crucial to be considered at a monthly resolution, for the optimization of land management (seasonal variation of vegetation cover and agricultural support practices) as well as natural hazard protection (landslides and flood prediction). We expanded REDES by 140 rainfall stations, thus covering areas where monthly R-factor values were missing (Slovakia, Poland) or former data density was not satisfactory (Austria, France, and Spain). The different time resolutions (from 5 to 60 min) of high temporal data require a conversion of monthly R-factor based on a pool of stations with available data at all time resolutions. Because the conversion factors show smaller monthly variability in winter (January: 1.54) than in summer (August: 2.13), applying conversion factors on a monthly basis is suggested. The estimated monthly conversion factors allow transferring the R-factor to the desired time resolution at a European scale. The June to September period contributes to 53% of the annual rainfall erosivity in Europe, with different spatial and temporal patterns depending on the region. The study also investigated the heterogeneous seasonal patterns in different regions of Europe: on average, the Northern and Central European countries exhibit the largest R-factor values in summer, while the Southern European countries do so from October to January. In almost all countries (excluding Ireland, United Kingdom and North France), the seasonal variability of rainfall erosivity is high. Very few areas (mainly located in Spain and France) show the largest from February to April. The average monthly erosivity density is very large in August (1.67) and July (1.63), while very small in January and February (0.37). This study addresses the need to develop monthly calibration factors for seasonal estimation of rainfall erosivity and presents the spatial patterns of monthly rainfall erosivity in European Union and Switzerland. Moreover, the study presents the regions and seasons under threat of rainfall erosivity.

https://www.mdpi.com/2073-4441/8/4/119

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

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/

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

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

https://www.sciencedirect.com/science/article/pii/S1462901115001884

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

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

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

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

The new assessment of soil loss by water erosion in Europe (Panagos et al., 2015a) was commented by Evans and Boardman (2016), who raised not only concerns related to the spatial differences outlined by our work compared to their visual semi-qualitative assessment conducted in Britain during the late eighties, but also generally to the suitability, validity and scientific robustness of the applied modelling approach. The objective of the pan-European assessment using the Revised Universal Soil Loss Equation (RUSLE) was not to outcompete any regional- or national-scale modelling, but to harmonize and improve our knowledge and our understanding of current soil erosion rates by water across the European Union. The focus of such a modelling project is on the differences and similarities between regions and countries beyond national borders and nationally adapted models. In order to do so, a state-of-the-art large-scale spatially distributed modelling exercise using harmonized datasets and a unified methodology to suit the pan-European scale was carried out. We reply that the semi-qualitative approach proposed by Evans and Boardman (2016) is not suitable for application at the European scale because of work force and time requirements, input data accessibility issues, accuracy of field-based estimates, subjectivity of soil loss estimates during the aerial and terrestrial photo interpretation, impossibility of upscaling or downscaling, inadequate representation of sheet erosion processes, lack of spatial and temporal representativeness, and lack of detailed description expressing the risk level. As such, their methodology has limited applicability, with today’s financial resources it is not feasible at European or at national scale and, most important, cannot respond to policy requests regarding scenarios of climate and land cover/use change. In contrast to Evans and Boardman (2016), we do know that RUSLE, like probably any other approach, is not able to reproduce “reality”. The latter is actually a misjudgment which has been extensively discussed 20 years ago. Modelling in general and large-scale modelling specifically can per se not aim at an accurate prediction of point measurements, but tests our hypothesis on process understanding, relative spatial and temporal variations, scenario development and controlling factors (Oreskes et al., 1994). As such, our approach can be offered as a helpful tool to policy makers at pan-European scale. We are confident that the simple transparent structure of RUSLE as well as the discussion of the uncertainties of each modelling factor will help to supply objective guidance to policy makers.

https://www.sciencedirect.com/science/article/pii/S146290111630034X

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

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

Extending Geographic and Thematic Range of SPADE/M with HYPRES Soil Profile Data The measured soil profile data of the Hydraulic Properties of European Soils (HYPRES) were evaluated for their potential use in extending the geographic coverage and thematic range of the profiles of the Soil Profile Analytical Database of Europe of measured profiles (SPADE/M) database. The aim of increasing the number of measured profiles is to improve the definition of pedo-transfer rules (PTRs) to extend the range of parameters characterizing soils and the validation of model runs.The HYPRES and SPADE/M databases follow different concepts in the compilation of soil profiles. These differences were reflected in the organization of storing profile data in the databases. A specific conceptual problem to extending the SPADE/M data set is posed by recording repeated measurements in the HYPRES database for horizons of a profile and multiple profiles for a plot. The two data sets also differ with respect to the properties recorded, the measurement units and the database model. To increase the number of measured soil profile data of the SPADE/M data set with HYPRES profiles the data from the latter has to be standardized to be adjusted to comply with the specifications of the SPADE/M data set. The standardization process involves conversions of units or reference systems, such as the plot co-ordinate transformation or the extraction of properties from comment fields, but also conceptual adaptations of the method used to characterize a soil horizon in the database. The outcome of the standardization process is a series of soil profiles which can be seamlessly added to the SPADE/M data set. Author(s): R. Hiederer Luxembourg: Publications Office of the European Union 2011 – 43 pp. – EUR 26540 EN Scientific and Technical Research series – ISBN 78-92-79-21593-3(online), doi:10.2788/8209 Download report: (Size: 1 MB) Preview FrontPage : Last Update: 21/08/2014

Towards protecting soil biodiversity in Europe: The EU thematic strategy for soil protection. Luca Montanarella. Biodiversity: Journal of Life on Earth. Volume 9 , Numbers 1 & 2, pp 75-77(2008) The new EU Thematic Strategy for Soil Protection will include a strong reference to soil biodiversity as a key soil component that needs preserving. Since available knowledge on soil biodiversity is recognised as being very limited, the main effort of the strategy will be in stimulating new research programmes for the improved understanding of soil biota. Related to this will be the increased development of soil quality indicators taking into account the biological function of soils. A full range of potential bio-indicators for soil health and soil function is available but needs to be fully explored for operational soil monitoring activities. Existing soil biodiversity monitoring initiatives and the first results of on-going European research programmes are presented and reviewed. Access the paper

Background Guide for the Calculation of Land Carbon Stocks in the Biofuels Sustainability Scheme: Drawing on the 2006 IPCC Guidelines for National Greenhouse Gas Inventories This Guide covers the calculation of carbon-stock changes in soil and above- and below-ground vegetation due to land use conversion in support of Directive 2009/28/EC on the promotion of the use of energy from renewable sources, particularly for assessing carbon-stock changes due to land conversion for biofuel production. The methodology put forward is based on the Tier 1 approach as developed under the IPCC Guidelines 2006. It is based on specifying default values for carbon stocks and using coefficients of divergence from the default values according to land use/cover. The methodological approach of the IPCC was adapted for use with spatial layers instead of data tables. The spatial layers of the factors influencing carbon-stock changes were generated with global coverage and thematically aligned to comply with stipulations made in the Directive. According to the types of land use/cover conversion, a review is made of the methodology of the IPCC (2006). Particular problems regarding peatlands are presented. Drained peatlands cannot be assessed in terms of carbon-stock changes because drainage occurs on the overall peat soil profile (not only on the first 30 cm). This has direct consequences not only on CO2 emissions but also on CH4 and N2O. Tables of coefficients of conversions are then proposed according to climate zone and continental boundaries for soil carbon-stock changes and for above- and below-ground carbon stock changes in biomass in a Technical Annex. Author(s): Florence Carré, Roland Hiederer, Viorel Blujdea, Renate Koeble, 2010 – 109 pp. – EUR 24573 EN– Scientific and Technical Research series – ISSN 1018-5593, ISBN 978-92-79-17455-1, Doi 10.2788/34463 Download report: (Size: 2.5 MB) Preview FrontPage : Last Update: 12/11/2010

Towards an European Soil Data Center in support of the EU thematic strategy for Soil Protection. B. Houskova, L. Montanarella, 2007. Published by Romanian Soil Science 2007, NR.1 pp. 3-17. The establishment of an European Soil Data Centre by the European Commission in support of the new EU thematic strategy for soil protection can certainly contribute to raising awareness in the general public of the importance of soil protection. Keywords: soil protection, EU thematic strategy, European soil data center. Access the paper

Sustainable mineral resources management: from regional mineral resources exploration to spatial contamination risk assessment of mining. Gyozo Jordan and JRC PECOMINES Project (Giovanni Bidoglio, Marco D'Alessandro, Tamas Hamor, Stefan Sommer, Panos Panagos, Marc van Liederkerke, Anca-Marina Vijdea), Environmental Geology, Springer Berlin , ISSN 0943-0105, Issue Volume 58, Number 1 / July, 2009, pp 153-169, DOI 10.1007/s00254-008-1502-y. Wide-spread environmental contamination associated with historic mining in Europe has triggered social responses to improve related environmental legislation, the environmental assessment and management methods for the mining industry. The objective of this paper is to show how regional mineral resources mapping has developed into the spatial contamination risk assessment of mining and how geological knowledge can be transferred to environmental assessment of mines. The paper provides a state-of-the-art review of the spatial mine inventory, hazard, impact and risk assessment and ranking methods developed by national and international efforts in Europe. It is concluded that geological knowledge on mineral resources exploration is essential and should be used for the environmental contamination assessment of mines. Access the paper Last Update: 26/04/2010

Evaluating the Effect of Nutrient Levels of Major Soil Types on the Productivity of Wheatlands in Hungary Tamás Hermann & Gergely Tóth. Evaluating the Effect of Nutrient Levels of Major Soil Types on the Productivity of Wheatlands in Hungary. Communications in Soil Science and Plant Analysis, Volume 42, Issue 13, 2011 Soil nutrient status is one of the most important constituents of land productivity. The research presented in this paper is aimed at describing the influence of nitrogen, phosphorous and potassium availability on crop yield across the major soil types of Hungary, under different climatic conditions. For this purpose, historical times series data from a five year period (1985-1989) regarding soil, land management and crop yield of more than eighty thousand fields, representing approximately four million hectares of arable land, were statistically analyzed. The database was recently recovered from statistical archives stored in the format of digital records of the early 1980s and were used to study the productivity of major soil types for winter wheat cropping under balanced fertilizer input. Calculations were made to quantify the effects of soil nutrient levels. The evaluation was also performed for optimal and suboptimal climate conditions. Results show that the effect of nitrogen availability (as obtained from organic matter content) had the largest influence on winter wheat yields. Up to a 26% difference in yields was observed, both on those soils with balanced material regimes and on those with leaching material regimes, under optimal climatic conditions. Access the paper: http://www.tandfonline.com/doi/abs/10.1080/00103624.2011.581728 Last Update: 05/09/2012

European Digital Archive of Soil Maps (EuDASM) - Soil Maps of Latin America and Caribbean islands European Digital Archive of Soil Maps (EuDASM) - Soil Maps of Latin America and Caribbean islands : DVD-ROM version. EUR 21822. Office for Official Publications of the European Communities, Luxembourg. Selvaradjou, S-K., Montanarella, L., Spaargaren. O. and Dent. D. (2005) Navigate the Contents:

Environmental Monitoring in contaminated area in Pavia Province, Italy. (Monitoraggio ambientale di un' area contaminate nella Provincia di Pavia) This study has as a scope to identify the extension of the area interested from the heavy metals and diossine and to estimate the level of concentration and their dangerousness. EUR 22762IT. 58 pp. Office for Official Publications of the European Communities, Luxembourg. (2007), ISBN 978-92-79-05652-9. Editors: R.M. Cenci and F. Sena Download report: (Size: 2 MB) Preview FrontPage :

Bio Bio Project Biodiversity - Bioindication to evaluate Soil Health. EUR 22245 EN, 134pp. Office for Official Publications of the European Communities, Luxembourg. R.M Cenci and F. Sena Download report: (Size: 7.7 MB) Preview FrontPage :

Guidelines for the use of native mosses, transplanted mosses and soils in assessing organic and inorganic contaminant fallout These guidelines on the use of mosses are of strategic importance in that they make it possible to harmonize the indications obtained from differing environments in terms of extent and, thereby, to compare them with results obtained using other methods. Cenci, R. (2008). European Commission, Joint Research Centre, Ispra, EUR 23292-EN, 33 pp. ISBN: 978-92-79-08719-6, ISSN: 1018-5593 Key words: mosses, soils, dioxins, heavy metals, radioisotopes. Download report: (Size: 2.2 MB) Preview FrontPage : Linee guida per l' utilizzo di muschi indigeni, muschi trapiantati e suoli per valutare le ricadute di contaminanti organici e inorganici. Scaricare il documento: (Taglia: 2.2 MB)

Landscape and Mitigation Factors in Aquatic Ecological Risk Assessment Holmes, A. Huber, F. de Jong, M. Liess, S. Loutseti, N. Mackay, W-M. Maier, S. Maund, C., Pais, W. Reinert, M. Russell, T. Schad, R. Stadler, M. Streloke, M. Styczen, J. van de Zande (2007) Landscape and Mitigation Factors in Aquatic Ecological Risk Assessment. Download Volume I: (Size: 3.2 MB) - Extended Summary and Recommendations. Final Report of the FOCUS Working Group on Landscape and Mitigation Factors in Ecological Risk Assessment. EC Document Reference SANCO/10422/2005 v2.0. 169 pp. Brown, C., A. Alix, J-L Alonso-Prados, D. Auteri, J-J Gril, R. Hiederer, C. Holmes, A. Huber, F. de Jong, M. Liess, S. Loutseti, N. Mackay, W-M. Maier, S. Maund, C., Pais, W. Reinert, M. Russell, T. Schad, R. Stadler, M. Streloke, M. Styczen, J. van de Zande (2007) Landscape and Mitigation Factors in Aquatic Ecological Risk Assessment. Download Volume II: (size 4.5 MB) - Detailed Technical Reviews. Final Report of the FOCUS Working Group on Landscape and Mitigation Factors in Ecological Risk Assessment. EC Document Reference SANCO/10422/2005 v2.0. 436 pp.

Application of the SIte COmparison Method (SICOM) to assess the potential erosion risk — a basis for the evaluation of spatial equivalence of agri-environmental measures. Detlef Deumlich, J. Kiesel, J. Thiere, , H.I. Reuter, L. Völker, and R. Funk, 2006. Published by CATENA Volume 68, Issues 2-3, 31 December 2006, Pages 141-152 . The paper presents a comparative method (SICOM) to evaluate complex site conditions at different area units as a basis for the estimate of spatial equivalence of agri-environmental measures (AEM). . Keywords: Wind erosion; Water erosion; Erosion risk; Moving-window-technique; Site evaluation; Agri-environmental measures (AEM) . Access the paper

Evaluation of BioSoil Demonstration Project - Preliminary Data Analysis. The BioSoil demonstration Project was initiated under the Forest Focus-Scheme (Regulation (EC) Nr. 2152/2003) concerning the monitoring of forests and environmental interactions in the Community, and aimed to broaden the scope of previous forest monitoring activities (on atmospheric pollution and forest fires) to the fields of soil characteristics and biodiversity indicators. The preliminary data analysis concentrated on the evaluation of a selected number of parameters of the data submitted by NFCs and sampling procedures. For soil the parameters needed to establish soil organic carbon densities were analysed. Hiederer, R.and T. Durrant (2010) Evaluation of BioSoil Demonstration Project - Preliminary Data Analysis. EUR 24258 EN. Luxembourg: Office for Official. Publications of the European Communities. 126pp. Keywords: BioSoil, Forest Focus, Soil, Organic Carbon, biodiversity indicators Download report: (Size: 4.8 MB) Preview FrontPage : Last Update: 24/02/2010

Will there be enough plant nutrients to feed a world of 9 billion in 2050? Will there be enough plant nutrients to feed a world of 9 billion in 2050? is the central question addressed by a JRC study. This exercise was based on consultations with experts and a thematic workshop focused on three areas of interest: 1) the demand for fertilizers to sustain crop production necessary to feed the world in 2050; 2) perspectives on the supply of Nitrogen (N), Phosphorus (P) and Potassium (K) to world agriculture and 3) the role of innovation and technology in changing the match between demand and supply of fertilizers. Implications of the main findings for current EU and international policies were addressed. "There is no specific reason to be alarmed about the overall supply of nitrogen, potassium and phosphorus for the world's agriculture but because of changing conditions in production, demand and use, continuous vigilance is called for." Author(s):Jean-Paul Malingreau, Hugh Eva, Albino Maggio. 2012 – 30pp. – EUR 25327 EN – Luxembourg: Publications Office of the European Union – 2012 – 30 pp. – 21.0 x 29.7 cm, EUR – Scientific and Technical Research series – ISSN 1831-9424 (online) ISSN 1018-5593 (print), ISBN 978-92-79-24910-5 (pdf),ISBN 978-92-79-24909-9 (print), doi: 10.2788/26603 Download report: (Size: 1.5 MB) Preview FrontPage : Last Update: 26/09/2012