Modelling water productivity for ecological intensification of crop sequences in the Inner Argentinean Pampas

Abstract The design of crop sequences based on ecological intensification (EI) may help to restore lost agroecosystem services and to increase resource use efficiency. Our aim was to evaluate, using a modelling approach, the impact of EI-based strategies, such as changing crop sequence configuration and increasing cropping intensity and agrobiodiversity, in the Inner Argentinean Pampas (IAP) region on water productivity (WP) of crop sequences and its components, i.e. water capture (Cw) and water use efficiency (WUE). We simulated crop sequences using SWB crop model for a 50-year period in two locations of IAP region. Crop sequences, of two-year duration each, had different configurations and included sole and/or double-crops in the growing season. These crop sequences were characterized using the following indexes of EI: cropping intensity index (CII), agrobiodiversity index (ABDI), cereal proportion (CP), maize (Zea mays L.) proportion (MP) and soybean (Glycine max [L] Merrill) proportion (SP). Our main findings reveal that: i) Regardless of location, all crop sequences alternatives to those based on a high SP had a higher estimated glucose yield, ii) Estimated glucose yield, WP, Cw, and WUE were significantly related to one or more indexes of EI included in multiple lineal models, iii) The role of Cw was more important than that of WUE to increase WP, iv) The choice of crop sequence was more critical to increase Cw when decreasing rainfall, v) vapour pressure deficit appears as a meteorological variable at least as important as the total amount of rainfall and its distribution pattern to design crop sequences in the IAP. Thus, the used modelling approach allowed us to evaluate crop sequences spanning a wide range of ecological intensification indexes, which take into account the level of agrobiodiversity, cropping intensity, and the proportion of key crops in their composition, gaining useful insights to design sustainable cropping systems.

[1]  P. Abbate,et al.  Climatic and Water Availability Effects on Water‐Use Efficiency in Wheat , 2004 .

[2]  Michael Robertson,et al.  Prospects for ecological intensification of Australian agriculture , 2013 .

[3]  P. Tittonell.  Ecological intensification of agriculture — sustainable by nature , 2014 .

[4]  Sven Erik Jørgensen,et al.  Validation of a prognosis based upon a eutrophication model , 1986 .

[5]  Federico Bert,et al.  Shallow groundwater dynamics in the Pampas: Climate, landscape and crop choice effects , 2016 .

[6]  A. Hirschman.  THE PATERNITY OF AN INDEX , 1964 .

[7]  Charles Francis,et al.  How land allocation and technology innovation affect the sustainability of agriculture in Argentina Pampas: An expanded life cycle analysis , 2015 .

[8]  Victor O. Sadras,et al.  Environmental risk analysis of farming systems in a semi-arid environment: effect of rotations and management practices on deep drainage , 2005 .

[9]  J. Annandale,et al.  Calibration and validation of the SWB model for sunflower (Helianthus annuus L.) , 2000 .

[10]  Ann M. Johanns,et al.  Increasing Cropping System Diversity Balances Productivity, Profitability and Environmental Health , 2012, PloS one.

[11]  Z. Hochman,et al.  Cropping system yield gaps can be narrowed with more optimal rotations in dryland subtropical Australia , 2020 .

[12]  V. Sadras,et al.  Production and Environmental Aspects of Cropping Intensification in a Semiarid Environment of Southeastern Australia , 2004, Agronomy Journal.

[13]  Z. Hochman,et al.  Assessment of the sustainability of different cropping systems under three irrigation strategies in the North China Plain under climate change , 2020 .

[14]  F. J. Pierce,et al.  Crop Rotation and Its Impact on Efficiency of Water and Nitrogen Use , 1988 .

[15]  A. Reynaud,et al.  Expected utility or prospect theory maximisers? Assessing farmers' risk behaviour from field-experiment data , 2014 .

[16]  V. Sadras,et al.  Intensification of agriculture in the south-eastern Pampas: I. Capture and efficiency in the use of water and radiation in double-cropped wheat–soybean , 2004 .

[17]  E. F. Viglizzo,et al.  Surface and groundwater dynamics in the sedimentary plains of the Western Pampas (Argentina) , 2011 .

[18]  Peter J. Thorburn,et al.  Modelling nitrogen leaching: Are we getting the right answer for the right reason? , 2014 .

[19]  R. Melchiori,et al.  Water and solar radiation productivity of double-crops in a humid temperate area , 2011 .

[20]  C. Willmott.  Some Comments on the Evaluation of Model Performance , 1982 .

[21]  Gary A. Peterson,et al.  Soil Water Storage in Dryland Cropping Systems: The Significance of Cropping Intensification , 1998 .

[22]  D. Vaughan.  Tourism and Biodiversity: a Convergence of Interests? , 2000 .

[23]  L. Thrupp,et al.  Linking agricultural biodiversity and food security: the valuable role of agrobiodiversity for sustainable agriculture. , 2000, International affairs.

[24]  G. Piñeiro,et al.  Increased cropping intensity improves crop residue inputs to the soil and aggregate-associated soil organic carbon stocks , 2017 .

[25]  P. Racsko,et al.  Stability and instability of an adaptive resource replacement strategy in an agroecological production system , 1987 .

[26]  C. Stöckle,et al.  CropSyst, a cropping systems simulation model , 2003 .

[27]  David Tilman,et al.  National food production stabilized by crop diversity , 2019, Nature.

[28]  C. Everson,et al.  Evaluating of soil water balance (SWB-Sci) model for water and nitrogen interactions in pasture: Example using annual ryegrass , 2014 .

[29]  R. Stirzaker,et al.  Monitoring and modelling draining and resident soil water nitrate concentrations to estimate leaching losses , 2010 .

[30]  J. P. Cooper.  Crop processes in controlled environments: A. R. Rees, K. E. Cockshull, D. W. Hand and R. G. Hurd (Editors). Academic Press, London and New York, 1972, xiii + 391 pp., £6.50 , 1973 .

[31]  Fernando O. García,et al.  Improving resource productivity at a crop sequence level , 2019, Field Crops Research.

[32]  Santiago L. Poggio,et al.  Productivity and resource use in intensified cropping systems in the Rolling Pampa, Argentina , 2015 .

[33]  D. Marino,et al.  Glyphosate and atrazine in rainfall and soils in agroproductive areas of the pampas region in Argentina. , 2018, The Science of the total environment.

[34]  J. Lammel,et al.  Environmental impact assessment of agricultural production systems using the life cycle assessment methodology: I. Theoretical concept of a LCA method tailored to crop production , 2004 .

[35]  R. Stirzaker,et al.  Use of the SWB-Sci model for nitrogen management in sludge-amended land , 2015 .

[36]  M. Nosetto,et al.  Changes in water fluxes partition related to the replacement of native dry forests by crops in the Dry Chaco , 2020 .

[37]  Lóczy Dénes.  Flood hazard in Hungary: a re-assessment , 2010 .

[38]  M. Agnusdei,et al.  Modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences , 2018, Agricultural and Forest Meteorology.

[39]  M. Agnusdei,et al.  Forage yield, water- and solar radiation-productivities of perennial pastures and annual crops sequences in the south-eastern Pampas of Argentina , 2018 .

[40]  K. Cassman.  Ecological intensification of cereal production systems: yield potential, soil quality, and precision agriculture. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[41]  C. Field,et al.  Crop yield gaps: their importance, magnitudes, and causes. , 2009 .

[42]  M. Salam,et al.  Comparing Simulated and Measured Values Using Mean Squared Deviation and its Components , 2000 .

[43]  Valerie O. Snow,et al.  APSIM Next Generation: Overcoming challenges in modernising a farming systems model , 2018, Environ. Model. Softw..

[44]  D. Tilman,et al.  Global food demand and the sustainable intensification of agriculture , 2011, Proceedings of the National Academy of Sciences.

[45]  R. Melchiori,et al.  Impact of soybean cropping frequency on soil carbon storage in Mollisols and Vertisols , 2011 .

[46]  Peter Carberry,et al.  Crop sequences in Australia’s northern grain zone are less agronomically efficient than implied by the sum of their parts , 2014 .

[47]  Nebo Jovanovic,et al.  Modelling the long-term effect of irrigation with gypsiferous water on soil and water resources , 1999 .

[48]  V. Sadras,et al.  Modelling long-term effects of cropping intensification reveals increased water and radiation productivity in the south-eastern Pampas , 2013 .

[49]  Fernando O. García,et al.  Soil Quality Impacts of Current South American Agricultural Practices , 2015 .

[50]  C. W. Richardson.  Wgen: A Model for Generating Daily Weather Variables , 2018 .

[51]  P. Chalk,et al.  Grain legumes in crop rotations under low and variable rainfall: are observed short-term N benefits sustainable? , 2020, Plant and Soil.

[52]  H. Videla Mensegue,et al.  Calibration and validation of soil water balance (SWB) model in the Inner Argentinian Pampas , 2021, Comput. Electron. Agric..

[53]  Santiago L. Poggio,et al.  Land use intensification in the Rolling Pampa, Argentina: Diversifying crop sequences to increase yields and resource use , 2017 .

[54]  Marcelo D. Nosetto,et al.  Higher water-table levels and flooding risk under grain vs. livestock production systems in the subhumid plains of the Pampas , 2015 .