Abstract
This chapter provides information about an emerging approach for rating agricultural soil quality (SQ) and crop yield potentials consistently over a range of spatial scales. We developed and tested the Muencheberg Soil Quality Rating (M-SQR), a straightforward, indicator-based overall method for agricultural SQ assessment. The aim of this chapter is to improve the precision and consistency of final ratings by updating the rating frames of most crop-yield-relevant indicators. M-SQR is a framework covering aspects of soil texture, structure, topography and climate which is based on 8 Basic Indicators and more than 12 Hazard Indicators. Ratings are performed by visual methods of soil evaluation and supported by monthly climate data. A field manual is then used to provide ratings from tables based on indicator thresholds. Finally, overall rating scores are given, ranging from 0 (worst) to 100 (best) to characterise crop yield potentials. The current approach is valid for grassland and cropland. Field tests in the main global agricultural regions have confirmed the practicability and reliability of the method. Many experimental sites have been assessed in Russia (Siberia included) and Central Asia. We found that at the field scale, soil texture and structure are most important criteria of agricultural SQ. At the global scale, climate-controlled hazard indicators of drought risk and the soil thermal regime are crucial for soil functioning and crop yield potentials. We present new rating tables for indicators that are most relevant to crop yields globally: a too-cold soil thermal regime (Hazard indicator 12) and agricultural drought (Hazard indicator 7). Final rating scores are well correlated with crop yields of cereals and grass. Regression equations express the relationships between overall M-SQR rating numbers and crop yield potentials at defined levels of farming inputs. We conclude that the combination of the Muencheberg Soil Quality Rating (M-SQR) with the World Reference Base of soil resources (WRB 2014) provides key information about main soil functions and processes. This system could be evolved for ranking and controlling agricultural SQ on a global scale. It should become a basis for more objective monitoring of global land quality, promoting sustainable land use and management, serving as one of the decision tools (decision support systems, impact assessment procedures) for economic trade-offs and land use planning. As a first step, the current concepts and data have led to a new crop yield potential map of Germany. The method and data given in this chapter could provide the basis for creating a similar map of Russia using the same methodology.
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Acknowledgements
The authors are grateful for the support of many colleagues and their research teams: Aleksandr Syso, Boris Smolentsev, Yuri Ermolov and teams (ISSA Novosibirsk, Russia); Aleksandr Puzanov and team (IWEP Barnaul, Russia); Sergey Kisinek and team (State farm Krasnoarmejskij, Krasnodar Krai, Russia), Azimbay Otarov and team (Kazakh Research Institute of Soil Science and Agrochemistry Almaty, Kazakhstan); Chunsheng Hu and team (Center for Agricultural Resources Research, Shijiazhuang, Hebei, China); Yong Li and team (Institute of Agro-Environment and Sustainable Development, CAAS, Beijing, China); Robert Evans and team (Agricultural Systems Research Unit (ASRU) und Northern Plains Agricultural Research Laboratory, Sidney, MT, USA); Steve Petrie, Daniel Long and teams (Columbia Basin Agricultural Research Center (CBARC) and USDA- Columbia Plateau Conservation Research Center Pendleton, OR, USA), William Schillinger and team (Washington State University, Lind Dryland Res. Station, Lind, WA, USA); Brenton Sharratt and team (Washington State University und USDA Land Management and Water Conservation Research Unit, Pullman, WA, USA), Lars Munkholm and team (Aarhus University, Denmark), Bev Kay (†), Bill Deen and teams (University of Guelph, Canada); Graham Shepherd (Bio-AgriNomics Ltd, Palmerston North, New Zealand), Bruce C. Ball (SRUC Edinburgh, UK), Ralf Dannowski, Sabine Baur (ZALF Müncheberg, Germany).
The Federal Office for Agriculture and Food (BLE, Bonn, Germany) provided travel funding for research stays with foreign partners. Special thanks go to Mr. Christian Walther. The International Bureau of the Federal Ministry of Education and Research (BMBF, Bonn, Germany) funded contacts and workshops in Novosibirsk and Almaty. The working group “Soil assessment and evaluation” of the German Soil Science Society (DBG) enabled the classification and evaluation on numerous agricultural sites in the framework of scientific excursions. Authors would like to thank all colleagues, teams and funding bodies for their support and engagement.
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Appendix: Further Updated Rating Tables
Appendix: Further Updated Rating Tables
See Tables 7, 8, 9, 10, 11 and 12
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Mueller, L. et al. (2016). An Emerging Method of Rating Global Soil Quality and Productivity Potentials. In: Mueller, L., Sheudshen, A., Eulenstein, F. (eds) Novel Methods for Monitoring and Managing Land and Water Resources in Siberia. Springer Water. Springer, Cham. https://doi.org/10.1007/978-3-319-24409-9_26
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