Editorial: Historical perspectives and future needs in soil mapping, classification, and pedologic modeling

Editorial: Historical perspectives and future needs in soil mapping, classification, and pedologic modeling Eric C. Brevik1*, Andreas Baumgarten2, Costanza Calzolari3, Antonio Jordán4, Cezary Kabala5, Bradley A. Miller6,7, and Paulo Pereira8 1 – Dept. of Natural Sciences, Dickinson State University, Dickinson, ND, USA. [email protected] 2 – AGES, Dept. for Soil Health and Plant Nutrition, Wien, Austria. andreas.baumgar[email protected] 3 – CNR - Ibimet, Sesto Fiorentino (FI), Italy. [email protected] 4 – Universidad de Sevilla, Facultad de Química, Dpto. de Cristalografía, Sevilla , Spain. ajor[email protected] 5 – Wroclaw University of Environmental and Life Sciences, Institute of Soil Science, Wroclaw Poland. cezary.kab[email protected]oc.pl 6 – Agronomy Department, Iowa State University, Ames, IA, USA. [email protected] 7 - Leibniz-Center for Agricultural Landscape Research (ZALF), Müncheberg, Institute of Soil Landscape Research, Eberswalder Str. 84, 15374 Müncheberg, Germany. 8 – Environmental Management Center, Mykolas Romeris University, Ateities St. Vilnius, Lithuania. [email protected] * - corresponding author Brevik, E.C., A. Baumgarten, C. Calzolari, A. Jordán, C. Kabala, B.A. Miller, and P. Pereira. 2016. Editorial: Historical perspectives and future needs in soil mapping, classification, and pedologic modeling. Geoderma 264:253-255. doi: 10.1016/j.geoderma.2015.09.022. Soil mapping, classification, and modelling have been important drivers in the advancement of our understanding of soil from the earliest days of the scientific study of soils. Soil maps were desirable for purposes of land valuation for taxation, agronomic planning (Brevik and Hartemink, 2010; Miller and Schaetzl, 2014), and in military operations (Lark, 2008; Brevik et al., 2015a). Soil mapping required classification systems that would allow accurate and succinct communication of mapped information (Brevik and Hartemink, 2013), classification systems required understanding of the soil system (Marbut, 1922), and gaining that understanding included the creation of soil models (Wilding, 1994). Therefore, advancement in one of these highly interrelated areas tended to lead to corresponding advances in the others, and these relationships persist into the modern era. Furthermore, studying our field’s history allows us to understand how we arrived at our current theories, including better understanding of both the strengths and weaknesses of those theories. Within this special issue (SI), historical aspects of soil mapping, classification, and/or pedogenic models are emphasized in papers by Brevik et al. (2015b), Calzolari and Filippi (2015), Miller and Schaetzl (2015), and Minasny and McBratney (2015) Soil mapping has a long history. The earliest written attempts to link soil attributes to ownership documents date to around 300 CE (Miller and Schaetzl, 2014). By the early 1700s and 1800s soil attributes were being mapped by scientists in Europe and the USA, respectively (Brevik and Hartemink, 2010; Landa and Brevik, 2015). Nationally-organized soil survey programs began in many parts of the world in the early 1900s (Simonson, 1989; Gonzalez et al., 2010; Calzolari, 2013; Hartemink and Sonneveld, 2013). Soil survey activities were relatively well-funded through much of the mid part of the 20th century, including international aid for surveys in developing countries (Brevik and Hartemink, 2010). However, funding was reduced and soil survey activities declined in many parts of the world in the 1980s (Hartemink and McBratney, 2008), with soil survey activities ceasing completely even in some developed countries (Krasilnikov et al., 2009). Many soil maps today are available in digital format, but most were created by digitizing legacy paper maps and they retain the limitations of their source maps (Jones et al., 2005). Future soil mapping would benefit from better consistency between mappers (Hudson, 1992), measures of data uncertainty and improved quantification of soil properties (Gessler et al., 1995; Miller, 2012), and a better understanding of the spatial and temporal variability of soil properties (Ibáñez et al., 2005; Ibáñez et al., 2015). Applications of soil mapping are discussed in papers by Baruck et al. (2015), Brevik et al. (2015b), Calzolari and Filippi (2015), Miller and Schaetzl (2015), Minasny and McBratney (2015), and Wahren et al. (2015) in this SI. Similar to mapping, soil classification has a long history. The first Chinese soil classification system was developed approximately 4,000 BP, in Europe the Greek philosopher Theophrastus (c. 371 – c. 287 BC) developed a classification for soils, and in the Americas the Aztecs developed a soil classification system used during the height of their civilization from the 14th to 16th centuries (Brevik and Hartemink, 2010). As national soil mapping programs became common around the world in the early part of the 20th Century (Brevik et al., 2015b), a wide range of national soil classification systems also developed (Krasilnikov et al., 2009). This profusion of classification systems led to difficulties communicating soil information internationally. The Legend of the Soil Map of the World (FAO-UNESCO, 1974) and the Revised Legend of the Soil Map of the World (FAO, 1988), followed by the creation of the World Reference Base for Soil Resources (WRB; IUSS Working Group WRB, 2014), were intended to provide correlations between all these disparate systems. Two classification systems have emerged to have wide-spread international use in modern soil science, WRB and Soil Taxonomy (Soil Survey Staff, 1999); however, there are still many national systems that are also in use. Efforts recently began to develop a universal soil classification system that may gain wide international acceptance and facilitate the communication of soil information between scientists from different countries (Hempel et al., 2013). Papers that address soil classification needs in this SI include Baruck et al. (2015), Brevik et al. (2015b), Juilleret et al. (2015), and Michéli et al. (2015). The earliest models of soil formation were probably those that viewed soils as a function of the geologic material they formed in (Brevik and Hartemink, 2013), but a major milestone in the development of soil science as an independent, scientific field of study was the development of Dokuchaev’s functional– factoral model, which became a major driving force in the mapping and classification of soils internationally within 50 years of its introduction (Brevik et al., 2015b). Other major milestones in the development of pedogenic models include Jenny’s (1941) casting of the five soil forming factors into state factors in a theoretically solvable equation, Simonson’s (1959) process-systems model, Runge’s (1973) energy transfer model, and Johnson and Watson-Stegner’s (1987) evolutionary model. Soil landscape models introduced and refined by Milne (1935), Bushnell (1943), Ruhe and Walker (1968), Huggett (1975), and Wysocki et al. (2000) have been critical in guiding soil mapping efforts. In more recent years mathematical models have been developed based on remote (Mulder et al., 2011; Naveen et al., 2014) and proximal (Viscarra-Rossel et al., 2006; Doolittle and Brevik, 2014) sensing methods. New techniques of data collection and spatial statistical analysis led to development of the Scorpan model (McBratney et al., 2003). To varying degrees each of these models has influenced our view of the soil system, including the way we map and/or classify soils. Future work in soil modelling needs to address data quality (Carre et al., 2007) and uncertainty (Nauman and Thompson, 2014), reduction of errors (Adhikari et al., 2014), improved calibration and validation (Malone et al., 2011), ways that sampling techniques influence results (Parras-Alcántara et al., 2015), and discovery of covariates that provide better prediction of the soil formation factors (Hengl et al., 2014; Miller et al., 2015). Within this SI various aspects of pedogenic modeling are presented by Brevik et al. (2015b), Haslmayr et al. (2015), Minasny and McBratney (2015), Wahren et al. (2015), and Waroszewski et al. (2015). Although many advances have been made in our understanding of the soil system since the late 1800s, when soil science blossomed into a scientific discipline in its own right, there are still many unanswered questions and additional needs in soil mapping, classification, and modelling. New technologies including GPS, GIS, remote sensing, and on-site geophysical instrumentation (EMI, GPR, PXRF, TDR, etc.) with associated data loggers and the development of geostatistical and other spatial statistical techniques have greatly increased our ability to collect, map, and analyse spatial information related to soils. However, linking all of this new information to soil properties and processes can still be a challenge and enhanced models are needed. The expansion of the use of soil knowledge to address issues beyond agronomic production, such as land use planning, environmental concerns, food security, energy security, water security, and human health requires new ways to communicate what we know about the soils we map as well as bringing forth research questions that were not widely considered in earlier soils studies. At present this information is communicated using dozens of national soil classification systems as well as WRB, but a more universal soil classification system would facilitate international communication of soils information. There are still many significant research needs in the area of soil mapping, classification, and modelling going into the future. Therefore, this special issue was developed to 1) document the history, 2) present some of the latest research, and 3) provide some perspectives on future needs in these areas. This has been accomplished by providing a mix of review papers and original research articles. References Adhikari, K., Minasny, B., Greve, M.B., Greve, M.H., 2014. Constructing soil class map of Denmark based on the FAO legend using digital techniques. Geoderma 214-215, 101-113. Baruck, J., Nestroy, O, Sartori, G., Baize, D., Traidl, R., Vrščaj, B., Bräm, E., Gruber, F.E., Heinrich, K., Geitner, C., 2015. Soil classification and mapping in the Alps: the current state and future challenges. Geoderma, doi: 10.1016/j.geoderma.2015.08.005. Brevik, E.C., Calzolari, C., Miller, B.A., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A., 2015 Soil mapping, classification, and modeling: history and future directions. Geoderma, doi:10.1016/j.geoderma.2015.05.017. Brevik, E.C., Cerdà, A., Mataix-Solera, J., Pereg, L., Quinton, J.N., Six, J., Van Oost. K., 2015. The interdisciplinary nature of SOIL. SOIL 1, 117-129. doi:10.5194/soil-1-117-2015 Brevik, E.C., Hartemink, A.E., 2010. Early soil knowledge and the birth and development of soil science. Catena 83, 23-33. doi:10.1016/j.catena.2010.06.011 Brevik, E.C., Hartemink, A.E., 2013. Soil maps of the United States of America. Soil Sci. Soc. Am. J. 77, 1117-1132. doi:10.2136/sssaj2012.0390. Bushnell, T.M., 1943. Some aspects of the soil catena concept. Soil Sci. Soc. Am. Proc. 7(C), 466-476. Calzolari, C., 2013. Research in pedology: A historical perspective, in: Costantini, E.A.C, Dazzi, C. (Eds.), The soils of Italy. Springer Science+Business Media, Dordrecht, The Netherlands, pp. 1-17. Calzolari, C., Filippi, N., 2015. Evolution of key concepts in modern pedology with reference to Italian soil survey history. Geoderma, doi:10.1016/j.geoderma.2015.08.024. Carre, F., McBratney, A.B., Mayr, T., Montanarella, L., 2007. Digital soil assessments: Beyond DSM. Geoderma 142, 69-79. Doolittle, J., Brevik, E.C., 2014. The use of electromagnetic induction techniques in soils studies. Geoderma 223-225, 33-45. FAO, 1988. Soil map of the world. Revised legend. World Soil Resources Report 60. FAO, Rome. FAO-UNESCO, 1974. Soil Map of the World 1:5000000. Volume I. Legend. UNESCO, Paris. Gessler, P.E., Moore, I.D., McKenzie, N.J., Ryan, P.J., 1995. Soil-landscape modelling and spatial prediction of soil attributes. Int. J. Geogr. Inf. Syst. 9, 421-432. Gonzalez, J.G., Ventura Jr., E., Castellanos, J.Z., Brevik, E.C., 2010. Soil science in Mexico: History, challenges, and future. Soil Surv. Horiz. 51, 63-71. Hartemink, A.E., McBratney, A.B., 2008. A soil science renaissance. Geoderma 148, 123-129. doi:10.1016/j.geoderma.2008.10.006 Hartemink, A.E., Sonneveld, M.P.W., 2013. Soil maps of The Netherlands. Geoderma 204-205, 1-9. Haslmayr, H-P., Geitner, C., Sutor, G., Knoll, A., Baumgarten, A., 2015. Soil function evaluation in Austria – Development, concepts and examples. Geoderma. in press. Hempel, J., Micheli, E., Owens, P., McBratney, A., 2013. Universal Soil Classification System Report from the International Union of Soil Sciences Working Group. Soil Horiz. 54(2), 1-6. Hengl, T., Mendes de Jesus, J., MacMillan, R.A., Batjes, N.H., Heuvelink, G.B.M., Ribeiro, E., Samuel-Rosa, A., Kempen, B., Leenars, J.G.B., Walsh, M.G., Ruiperez Gonzalez, M., 2014. SoilGrids 1km – Global soil information based in automated Mapping. PlosONE 9, e105992. doi:10.1371/journal.pone.0105992 Hudson, B.D., 1992. The soil survey as paradigm-based science. Soil Sci. Soc. Am. J. 56(3), 836-841. doi:10.2136/sssaj1992.03615995005600030027x Huggett, R.J., 1975. Soil landscape systems: A model of soil genesis. Geoderma 13, 1-22. doi: 10.1016/0016-7061(75)90035-X Ibáñez, J.J., Pérez-Gómez, R., Oyonarte, C., Brevik. E.C., 2015. Are there arid land soilscapes in southwestern Europe? Land Degrad. Develop. DOI:10.1002/ldr.2451. Ibáñez, J.J., Sánchez Díaz, J., de Alba, S., López Arias, M., Boixadera, J., 2005. Collection of Soil Information in Spain: A review in 2003, in: Jones, R.J.A., Houšková, B., Bullock, P., Montanarella, L. Soil resources of Europe. Second edition. European Soil Bureau Research Report No.9, EUR20559EN. Office for Official Publications of the European Communities, Luxembourg, pp. 345-356. IUSS working group WRB, 2014. World Reference Base for Soil Resources 2014. International soil classification system for naming soil and creating legends for soil maps. Food and Agriculture Organization of the United Nations. Rome. Jenny, H., 1941. Factors of soil formation: A system of quantitative pedology. Dover Publications, Mineola, NY. (reprinted in 1994) Jones, R.J.A., Houšková, B., Bullock P. and Montanarella L. (eds), 2005a. Soil Resources of Europe, second edition. European Soil Bureau Research Report No.9, EUR 20559 EN, 420pp. Office for Official Publications of the European Communities, Luxembourg. Juilleret, J., Dondeyne, S., Vancampenhout, K., Deckers, J., Hissler, C., 2015. Mind the gap: A classification system for integrating the subsolum into soil surveys. Geoderma, doi:10.1016/j.geoderma.2015.08.031. Krasilnikov, P., Ibáñez, J.J., Arnold, R., Shoba, S., 2009. A handbook of soil terminology, correlation, and classification. Earthscan, London, UK. Landa, E.R., Brevik, E.C., 2015. Soil science and its interface with the history of geology community. Earth Sciences History. in press. Lark, M., 2008. Science on the Normandy Beaches: J.D. Bernal and the prediction of soil trafficability for Operation Overlord. Soil Surv. Horiz. 49:12-15. Malone, B.P., McBratney, A.B., Minasny, B., 2011. Empirical estimates of uncertainty for mapping continuous depth functions of soil attributes. Geoderma 160, 614-616. McBratney, A.B., Mendonça Santos, M.L., Minasny, B., 2003. On digital soil mapping. Geoderma 117, 352. doi:10.1016/S0016-7061(03)00223-4. Michéli, E., Láng, V., Owens, P.R., McBratney, A., Hempel, J., 2015. Testing the pedometric evaluation of taxonomic units on Soil Taxonomy - a step in advancing towards a universal soil classification system. Geoderma, doi: 10.1016/j.geoderma.2015.09.008. Miller, B.A., 2012. The need to continue improving soil survey maps. Soil Horiz. 53, 11-15. doi:10.2136/sh12-02-0005. Miller, B.A., Schaetzl, R.J., 2014. The historical role of base maps in soil geography. Geoderma 230-231, 329-339. doi:10.1016/j.geoderma.2014.04.020. Miller, B.A., Schaetzl, R.J., 2015. History of soil geography in the context of scale. Geoderma, doi:10.1016/j.geoderma.2015.08.041. Miller, B.A., Koszinski, S., Wehrhan, M., Sommer, M., 2015. Impact of multi-scale predictor selection for modeling soil properties. Geoderma 239-240, 97-106. doi:10.1016/j.geoderma.2014.09.018. Milne, G., 1935. Some suggested units of classification and mapping particularly for East African soils. Soil Research 4(3), 183-198. Minasny, B., McBratney, A.B., 2015. Digital soil mapping: A brief history and some lessons. Geoderma, doi:10.1016/j.geoderma.2015.07.017. Mulder, V.L., de Bruin, S., Schaepman, M.E., Mayr, T.R., 2011. The use of remote sensing in soil and terrain mapping - A review. Geoderma 162, 1-19. doi:10.1016/j.geoderma.2010.12.018 Nauman, T.W., Thompson, J.A., 2014. Semi-automated disaggregation of conventional soil maps using knowledge driven data mining and classification trees. Geoderma 213, 385-399. Naveen, J.P.A., Abd-Elrahaman, A.H., Lewis, D.B., Hewitt, N.A., 2014. Modelling soil parameters using hyperspectral image reflectance in subtropical coastal wetlands. Int. J. Appl. Earth Obs. 33, 47-56. Parras-Alcántara, L., Lozano-García, B., Brevik, E.C., Cerdá, A., 2015. Soil organic carbon stocks assessment in Mediterranean natural areas: a comparison of entire soil profiles and soil control sections. J. Environ. Manage., 155, 219-228. Ruhe, R.V., Walker, P.H., 1968. Hillslope models and soil formation. I. Open systems. Transactions of the 9th International Congress of Soil Science 4, 551-560. Runge, E., 1973. Soil development sequences and energy models. Soil Sci. 115, 183-193. Simonson, R.W., 1959. Outline of a generalized theory of soil genesis. Soil Sci. Soc. Am. Proc. 23, 152156. Simonson, R.W., 1989. Historical highlights of soil survey and soil classification with emphasis on the United States, 1899-1970. International Soil Reference and Information Centre Technical Paper 18. Wageningen, The Netherlands. Soil Survey Staff, 1999. Soil Taxonomy: A basic system of soil classification for making and interpreting soil surveys, 2nd Ed. U.S. Department of Agriculture Handbook No. 436, U.S. Government Printing Office, Washington, D.C. Viscarra-Rossel, R.A., McGlynn, R.N., McBratney, A.B., 2006. Determining the composition of mineralorganic mixes using UV-vis-NIR diffuse reflectance spectroscopy. Geoderma 137, 70-82. Wahren, F.T., Julich, S., Nunes, J.P., Gonzalez-Pelayo, O., Hawtree, D., Feger, K-H., Keizer, J.J., 2015. Combining digital soil mapping and hydrological modeling in a data scarce watershed in north-central Portugal. Geoderma, doi:10.1016/j.geoderma.2015.08.023. Waroszewskia,J., Eglic, M., Kabalaa, C., Kierczak, J., Brandova, D., 2015. Mass fluxes and clay mineral formation in soils developed on slope deposits of the Kowarski Grzbiet (Karkonosze Mountains, Czech Republic/Poland). Geoderma, doi:10.1016/j.geoderma.2015.08.044. Wilding, L.P., 1994. Factors of Soil Formation: Contributions to pedology. in: Factors of Soil Formation: A Fiftieth Anniversary Retrospective. SSSA Special Publication 33, Soil Science Society of America, Madison, WI, pp. 15-30. Wysocki, D.A., Schoeneberger, P.J., LaGarry, H.E., 2000. Geomorphology of soil landscapes. in: Sumner, M.E. (Ed.), Handbook of soil science. CRC Press, Boca Raton, FL, p. E-5-E-39.