Luca Montanarella

Bio: Luca Montanarella is an academic researcher from European Commission. The author has contributed to research in topics: European union & Soil carbon. The author has an hindex of 62, co-authored 177 publications receiving 15807 citations.

An assessment of the global impact of 21st century land use change on soil erosion.

Abstract: 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.

Harmonized World Soil Database (version 1.2)

Abstract: METIS-ID: 167825 The Harmonized World Soil Database is a 30 arc-second raster database with over 15000 different soil mapping units that combines existing regional and national updates of soil information worldwide (SOTER, ESD, Soil Map of China, ISRIC-WISE) with the information contained within the 1:5 000 000 scale FAO-UNESCO Soil Map of the World (FAO, 1971-1981). The resulting raster database consists of ... 21600 rows and 43200 columns, which are linked to harmonized soil property data. The use of a standardized structure allows for the linkage of the attribute data with the raster map to display or query the composition in terms of soil units and the characterization of selected soil parameters (organic Carbon, pH, water storage capacity, soil depth, cation exchange capacity of the soil and the clay fraction, total exchangeable nutrients, lime and gypsum contents, sodium exchange percentage, salinity, textural class and granulometry). Reliability of the information contained in the database is variable: the parts of the database that still make use of the Soil Map of the World such as North America, Australia, West Africa and South Asia are considered less reliable, while most of the areas covered by SOTER databases are considered to have the highest reliability (Southern Africa, Latin America and the Caribbean, Central and Eastern Europe). Further expansion and update of the HWSD is foreseen for the near future, notably with the excellent databases held in the USA (Natural Resources Conservation Service US General Soil Map, STATSGO), Canada (Agriculture and AgriFood Canada: The National Soil Database NSDB), and Australia (CSIRO, ACLEP, Nnatural Heritage Trust and National Land and Water Resources Audit: ASRIS), and with the recently released SOTER database for Central Africa (FAO/ISRIC/Univ. Gent, 2007)

The significance of soils and soil science towards realization of the United Nations sustainable development goals

Abstract: . In this forum paper we discuss how soil scientists can help to reach the recently adopted UN Sustainable Development Goals (SDGs) in the most effective manner. Soil science, as a land-related discipline, has important links to several of the SDGs, which are demonstrated through the functions of soils and the ecosystem services that are linked to those functions (see graphical abstract in the Supplement). We explore and discuss how soil scientists can rise to the challenge both internally, in terms of our procedures and practices, and externally, in terms of our relations with colleague scientists in other disciplines, diverse groups of stakeholders and the policy arena. To meet these goals we recommend the following steps to be taken by the soil science community as a whole: (i) embrace the UN SDGs, as they provide a platform that allows soil science to demonstrate its relevance for realizing a sustainable society by 2030; (ii) show the specific value of soil science: research should explicitly show how using modern soil information can improve the results of inter- and transdisciplinary studies on SDGs related to food security, water scarcity, climate change, biodiversity loss and health threats; (iii) take leadership in overarching system analysis of ecosystems, as soils and soil scientists have an integrated nature and this places soil scientists in a unique position; (iii) raise awareness of soil organic matter as a key attribute of soils to illustrate its importance for soil functions and ecosystem services; (iv) improve the transfer of knowledge through knowledge brokers with a soil background; (v) start at the basis: educational programmes are needed at all levels, starting in primary schools, and emphasizing practical, down-to-earth examples; (vi) facilitate communication with the policy arena by framing research in terms that resonate with politicians in terms of the policy cycle or by considering drivers, pressures and responses affecting impacts of land use change; and finally (vii) all this is only possible if researchers, with soil scientists in the front lines, look over the hedge towards other disciplines, to the world at large and to the policy arena, reaching over to listen first, as a basis for genuine collaboration.

Reducing food’s environmental impacts through producers and consumers

Abstract: Food’s environmental impacts are created by millions of diverse producers. To identify solutions that are effective under this heterogeneity, we consolidated data covering five environmental indicators; 38,700 farms; and 1600 processors, packaging types, and retailers. Impact can vary 50-fold among producers of the same product, creating substantial mitigation opportunities. However, mitigation is complicated by trade-offs, multiple ways for producers to achieve low impacts, and interactions throughout the supply chain. Producers have limits on how far they can reduce impacts. Most strikingly, impacts of the lowest-impact animal products typically exceed those of vegetable substitutes, providing new evidence for the importance of dietary change. Cumulatively, our findings support an approach where producers monitor their own impacts, flexibly meet environmental targets by choosing from multiple practices, and communicate their impacts to consumers.

SoilGrids250m: Global gridded soil information based on machine learning

Abstract: This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods-random forest and gradient boosting and/or multinomial logistic regression-as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10-fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.

Greenhouse gas mitigation in agriculture

Abstract: Agricultural lands occupy 37% of the earth's land surface. Agriculture accounts for 52 and 84% of global anthropogenic methane and nitrous oxide emissions. Agricultural soils may also act as a sink or source for CO2, but the net flux is small. Many agricultural practices can potentially mitigate greenhouse gas (GHG) emissions, the most prominent of which are improved cropland and grazing land management and restoration of degraded lands and cultivated organic soils. Lower, but still significant mitigation potential is provided by water and rice management, set-aside, land use change and agroforestry, livestock management and manure management. The global technical mitigation potential from agriculture (excluding fossil fuel offsets from biomass) by 2030, considering all gases, is estimated to be approximately 5500–6000 Mt CO2-eq. yr−1, with economic potentials of approximately 1500–1600, 2500–2700 and 4000–4300 Mt CO2-eq. yr−1 at carbon prices of up to 20, up to 50 and up to 100 US$ t CO2-eq.−1, respectively. In addition, GHG emissions could be reduced by substitution of fossil fuels for energy production by agricultural feedstocks (e.g. crop residues, dung and dedicated energy crops). The economic mitigation potential of biomass energy from agriculture is estimated to be 640, 2240 and 16 000 Mt CO2-eq. yr−1 at 0–20, 0–50 and 0–100 US$ t CO2-eq.−1, respectively.