Agronomic benefits and risks associated with the irrigated peanut–maize production system under a changing climate in northern Australia
Yashvir S. Chauhan A D , Peter Thorburn B , Jody S. Biggs B and Graeme C. Wright C
+ Author Affiliations
- Author Affiliations
A Department of Agriculture and Fisheries, PO Box 23, Kingaroy, Qld 4610, Australia.
B CSIRO, GPO Box 2583, Brisbane, Qld 4001, Australia.
C Peanut Company of Australia, Kingaroy, PO Box 26, Kingaroy, Qld 4610, Australia.
D Corresponding author. Email: yash.chauhan@daf.qld.gov.au
Crop and Pasture Science 66(11) 1167-1179 https://doi.org/10.1071/CP15068
Submitted: 25 February 2015 Accepted: 1 July 2015 Published: 29 October 2015
Abstract
With the aim of increasing peanut production in Australia, the Australian peanut industry has recently considered growing peanuts in rotation with maize at Katherine in the Northern Territory—a location with a semi-arid tropical climate and surplus irrigation capacity. We used the well-validated APSIM model to examine potential agronomic benefits and long-term risks of this strategy under the current and warmer climates of the new region. Yield of the two crops, irrigation requirement, total soil organic carbon (SOC), nitrogen (N) losses and greenhouse gas (GHG) emissions were simulated. Sixteen climate stressors were used; these were generated by using global climate models ECHAM5, GFDL2.1, GFDL2.0 and MRIGCM232 with a median sensitivity under two Special Report of Emissions Scenarios over the 2030 and 2050 timeframes plus current climate (baseline) for Katherine. Effects were compared at three levels of irrigation and three levels of N fertiliser applied to maize grown in rotations of wet-season peanut and dry-season maize (WPDM), and wet-season maize and dry-season peanut (WMDP). The climate stressors projected average temperature increases of 1°C to 2.8°C in the dry (baseline 24.4°C) and wet (baseline 29.5°C) seasons for the 2030 and 2050 timeframes, respectively. Increased temperature caused a reduction in yield of both crops in both rotations. However, the overall yield advantage of WPDM increased from 41% to up to 53% compared with the industry-preferred sequence of WMDP under the worst climate projection. Increased temperature increased the irrigation requirement by up to 11% in WPDM, but caused a smaller reduction in total SOC accumulation and smaller increases in N losses and GHG emission compared with WMDP. We conclude that although increased temperature will reduce productivity and total SOC accumulation, and increase N losses and GHG emissions in Katherine or similar northern Australian environments, the WPDM sequence should be preferable over the industry-preferred sequence because of its overall yield and sustainability advantages in warmer climates. Any limitations of irrigation resulting from climate change could, however, limit these advantages.
Additional keywords: APSIM, fertiliser, irrigation, peanut, maize, rotation.
References
Backlund P, Janetos A, Schimel D (2008) ‘The effects of climate change on agriculture, land resources, water resources, and biodiversity.’ Synthesis and Assessment Product 4.3. (U.S. Climate Change Science Program: Washington, DC)Bell M, Harsh G, Tatnell J, Middleton K (2003) The impact of crop rotation on peanut productivity in rainfed cropping systems. In ‘Solutions for a better environment. Proceedings of the 11th Australian Agronomy Conference’. 2–6 February 2003, Geelong, Vic. (Australian Society of Agronomy Inc., The Regional Institute: Gosford, NSW) Available at: www.regional.org.au/au/asa/2003/c/5/bell.htm
Biggs JS, Thorburn PJ, Crimp S, Masters B, Attard SJ (2013) Interactions between climate change and sugarcane management systems for improving water quality leaving farms in the Mackay Whitsunday region, Australia. Agriculture, Ecosystems & Environment 180, 79–89.
| Interactions between climate change and sugarcane management systems for improving water quality leaving farms in the Mackay Whitsunday region, Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXitVShtbzJ&md5=944c8269af3b79b4d59a9662e40b3166CAS |
Birch CJ, Stephen K, McLean G, Doherty A, Hammer GL, Robertson MJ (2008) Reliability of production of quick to medium maturity maize in areas of variable rainfall in north-east Australia. Australian Journal of Experimental Agriculture 48, 326–334.
| Reliability of production of quick to medium maturity maize in areas of variable rainfall in north-east Australia.Crossref | GoogleScholarGoogle Scholar |
Bruget D, Burgess S, Carter J, Chun A, Day K, Panjkov A, Ricketts J, Rosenthal K, Van Bruggen T, Zhang B (2012) ‘Consistent climate scenarios project draft user guide: ‘change factor’ and ‘quantile-matching’ based climate projections data.’ (Queensland Climate Change Centre of Excellence, Department of Science, Information Technology, Innovation and the Arts: Brisbane, Qld) Available at: www.longpaddock.qld.gov.au/climateprojections/pdf/userguide.pdf
Carberry PS, Muchow RC, McCown RL (1989) Testing the CERES-Maize simulation model in a semi-arid tropical environment. Field Crops Research 20, 297–315.
| Testing the CERES-Maize simulation model in a semi-arid tropical environment.Crossref | GoogleScholarGoogle Scholar |
Carberry P, McCown R, Muchow R, Dimes J, Probert M, Poulton P, Dalgliesh N (1996) Simulation of a legume ley farming system in northern Australia using the Agricultural Production Systems Simulator. Animal Production Science 36, 1037–1048.
Chartres C, Williams J (2006) Can Australia overcome its water scarcity problems? Journal of Developments in Sustainable Agriculture 1, 17–24.
Chauhan YS (2010) Potential productivity and water requirements of maize–peanut rotations in Australian semi-arid tropical environments—a crop simulation study. Agricultural Water Management 97, 457–464.
| Potential productivity and water requirements of maize–peanut rotations in Australian semi-arid tropical environments—a crop simulation study.Crossref | GoogleScholarGoogle Scholar |
Chauhan YS, Rachaputi RC (2014) Defining agro-ecological regions for field crops in variable target production environments: A case study on mungbean in the northern grains region of Australia. Agriculture and Forest Meteorology 194, 207–217.
| Defining agro-ecological regions for field crops in variable target production environments: A case study on mungbean in the northern grains region of Australia.Crossref | GoogleScholarGoogle Scholar |
Chauhan YS, Wright GC, Holzworth D, Rachaputi RC, Payero JO (2013) AQUAMAN: a web-based decision support system for irrigation scheduling in peanuts. Irrigation Science 31, 271–283.
| AQUAMAN: a web-based decision support system for irrigation scheduling in peanuts.Crossref | GoogleScholarGoogle Scholar |
Crimp S, Howden M, Power B, Wang E, De Voil P (2008) Global climate change impacts on Australia’s wheat crops. Report for the Garnaut Climate Change Review Secretariat, Commonwealth of Australia.
Döll P (2002) Impact of climate change and variability on irrigation requirements: a global perspective. Climatic Change 54, 269–293.
| Impact of climate change and variability on irrigation requirements: a global perspective.Crossref | GoogleScholarGoogle Scholar |
Galloway JN, Townsend AR, Erisman JW, Bekunda M, Cai Z, Freney JR, Sutton MA (2008) Transformation of the nitrogen cycle: recent trends, questions, and potential solutions. Science 320, 889–892.
| Transformation of the nitrogen cycle: recent trends, questions, and potential solutions.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXlslygsbw%3D&md5=a597d88cffcb1d89fe92484456d8fe14CAS | 18487183PubMed |
Gornall J, Betts R, Burke E, Clark R, Camp J, Willett K, Wiltshire A (2010) Implications of climate change for agricultural productivity in the early twenty-first century. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 365, 2973–2989.
| Implications of climate change for agricultural productivity in the early twenty-first century.Crossref | GoogleScholarGoogle Scholar | 20713397PubMed |
Hammer GL, Dong Z, McLean G, Doherty A, Messina C, Schussler J, Cooper M (2009) Can changes in canopy and/or root system architecture explain historical maize yield trends in the US Corn Belt? Crop Science 49, 299–312.
| Can changes in canopy and/or root system architecture explain historical maize yield trends in the US Corn Belt?Crossref | GoogleScholarGoogle Scholar |
Holzworth DP, Huth NI, deVoil PG, Zurcher EJ, Herrmann NI, McLean G, Chenu K, van Oosterom EJ, Snow V, Murphy C, Moore AD, Brown H, Whish JPM, Verrall S, Fainges J, Bell LW, Peake AS, Poulton PL, Hochman Z, Thorburn PJ, Gaydon DS, Dalgliesh NP, Rodriguez D, Cox H, Chapman S, Doherty A, Teixeira E, Sharp J, Cichota R, Vogeler I, Li FY, Wang E, Hammer GL, Robertson MJ, Dimes JP, Whitbread AM, Hunt J, van Rees H, McClelland T, Carberry PS, Hargreaves JNG, MacLeod N, McDonald C, Harsdorf J, Wedgwood S, Keating BA (2014) APSIM—evolution towards a new generation of agricultural systems simulation. Environmental Modelling & Software 62, 327–350.
| APSIM—evolution towards a new generation of agricultural systems simulation.Crossref | GoogleScholarGoogle Scholar |
Isbell RF (2002) ‘The Australian Soil Classification.’ (CSIRO Publishing: Melbourne)
Keating BA, Carberry PS, Hammer GL, Probert ME, Robertson MJ, Holzworth D, Huth NI, Hargreaves JNG, Meinke H, Hochman Z, McLean G, Verburg K, Snow V, Dimes JP, Silburn M, Wang E, Brown S, Bristow KL, Asseng S, Chapman S, McCown RL, Freebairn DM, Smith CJ (2003) An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy 18, 267–288.
| An overview of APSIM, a model designed for farming systems simulation.Crossref | GoogleScholarGoogle Scholar |
Lal R (2004) Soil carbon sequestration to mitigate climate change. Geoderma 123, 1–22.
| Soil carbon sequestration to mitigate climate change.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXoslSmsLY%3D&md5=62c140d87ad1abfa9db2329628f5d671CAS |
Lobell DB, Field CB (2007) Global scale climate-crop yield relationships and the impact of recent warming. Environmental Research Letters 2, 011002
| Global scale climate-crop yield relationships and the impact of recent warming.Crossref | GoogleScholarGoogle Scholar |
Marshall NA, Dowd AB, Fleming A, Gambley C, Howden SM, Jakku E, Larsen C, Marshall PA, Moon K, Park SE, Thorburn PJ (2014) Transformational capacity in Australian peanut farmers for better climate adaptation. Agronomy for Sustainable Development 34, 583–591.
| Transformational capacity in Australian peanut farmers for better climate adaptation.Crossref | GoogleScholarGoogle Scholar |
Meinke H, Hammer GL (1995) Climatic risk to peanut production: a simulation study for Northern Australia. Animal Science 35, 777–780.
Muchow RC, Sinclair TR, Bennett JM (1990) Temperature and solar radiation effects on potential maize yield across locations. Agronomy Journal 82, 338–343.
| Temperature and solar radiation effects on potential maize yield across locations.Crossref | GoogleScholarGoogle Scholar |
Nelson RA, Dimes JP, Paningbatan EP, Silburn DM (1998) Erosion/productivity modelling of maize farming in the Philippine uplands: Part I: parameterising the Agricultural Production Systems Simulator. Agricultural Systems 58, 129–146.
| Erosion/productivity modelling of maize farming in the Philippine uplands: Part I: parameterising the Agricultural Production Systems Simulator.Crossref | GoogleScholarGoogle Scholar |
Nikolakis W, Nygaard A, Quentin G (2011) Environmental economics research hub research reports: adapting to climate change for water resource management: Issues for northern Australia. Research Report No. 108. Crawford School of Economics and Government, The Australian National University, Canberra, ACT.
Parry ML (Ed.) (2007) ‘Climate change impacts, adaptation and vulnerability.’ Working Group II Contribution to the Fourth Assessment Report of the IPCC Intergovernmental Panel on Climate Change (Vol. 4). (Cambridge University Press: Cambridge, UK)
Payero JO, Singh D, Harris D, Vriesema S, O’Hare J, Pendergast L, Chauhan Y (2011) Application of a new web-based tool (CropWaterUse) for determining evapotranspiration and irrigation requirements of major crops at three locations in Queensland. In ‘Evapotranspiration’. Ch. 13. (Ed. L Labedzki) (InTech: Rijeka, Croatia) Available at: www.intechopen.com/articles/show/title/application-of-a-new-web-based-tool-cropwateruse-for-determining-evapotranspiration-and-irrigation-r
Peoples MB, Freney JR, Mosier AR (1995) Minimizing gaseous losses of nitrogen. In ‘Nitrogen fertilization in the environment’. (Ed. PE Bacon) pp. 565–602. (Marcel Dekker: New York)
Pingali PL, Rosegrant MW (1994) Confronting the environmental consequences of the Green Revolution in Asia (No. 2). International Food Policy Research Institute (IFPRI), Washington, DC.
Ray DK, Mueller ND, West PC, Foley JA (2013) Yield trends are insufficient to double global crop production by 2050. PLoS ONE 8, 1–8.
Rickards L, Howden SM (2012) Transformational adaptation: agriculture and climate change. Crop & Pasture Science 63, 240–250.
| Transformational adaptation: agriculture and climate change.Crossref | GoogleScholarGoogle Scholar |
Robertson MJ, Carberry PS, Huth NI, Turpin JE, Probert ME, Poulton PL, Brinsmead RB (2002) Simulation of growth and development of diverse legume species in APSIM. Crop & Pasture Science 53, 429–446.
| Simulation of growth and development of diverse legume species in APSIM.Crossref | GoogleScholarGoogle Scholar |
Rodriguez D, DeVoil P, Power B, Cox H, Crimp S, Meinke H (2011) The intrinsic plasticity of farm businesses and their resilience to change An Australian example. Field Crops Research 124, 157–170.
| The intrinsic plasticity of farm businesses and their resilience to change An Australian example.Crossref | GoogleScholarGoogle Scholar |
Rosenzweig C, Iglesias A, Yang XB, Epstein PR, Chivian E (2001) Climate change and extreme weather events; implications for food production, plant diseases, and pests. Global Change and Human Health 2, 90–104.
| Climate change and extreme weather events; implications for food production, plant diseases, and pests.Crossref | GoogleScholarGoogle Scholar |
Schlenker W, Roberts MJ (2009) Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proceedings of the National Academy of Sciences of the United States of America 106, 15594–15598.
| Nonlinear temperature effects indicate severe damages to US crop yields under climate change.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhtFyjsLvP&md5=255c0439b21cb1a03b41d2469043283aCAS | 19717432PubMed |
Smith P, Martino D, Cai Z, Gwary D, Janzen H, Kumar P, McCarl B, Ogle S, O’Mara F, Rice C (2008) Greenhouse gas mitigation in agriculture. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 363, 789–813.
| Greenhouse gas mitigation in agriculture.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXislGgtb8%3D&md5=fbb9c1af9fd99af81cda5add92e808b6CAS | 17827109PubMed |
Stafford Smith MS, Horrocks L, Harvey A, Hamilton C (2011) Rethinking adaptation for a 4°C world. Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences 369, 196–216.
| Rethinking adaptation for a 4°C world.Crossref | GoogleScholarGoogle Scholar |
Thorburn PJ, Biggs JS, Collins K, Probert ME (2010) Using the APSIM model to estimate nitrous oxide emissions from diverse Australian sugarcane production systems. Agriculture, Ecosystems & Environment 136, 343–350.
| Using the APSIM model to estimate nitrous oxide emissions from diverse Australian sugarcane production systems.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXisFenurg%3D&md5=0363bc0e608311f67b517fe6e2d1c88bCAS |
Thorburn PJ, Biggs JS, Attard SJ, Kemei J (2011) Environmental impacts of irrigated sugarcane production: nitrogen lost through runoff and leaching. Agriculture, Ecosystems & Environment 144, 1–12.
| Environmental impacts of irrigated sugarcane production: nitrogen lost through runoff and leaching.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXhsFCqsLjP&md5=fa054f44317b0e45b7ca261554a8ed86CAS |
Tilman D, Balzer C, Hill J, Befort BL (2011) Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences of the United States of America 108, 20260–20264.
| Global food demand and the sustainable intensification of agriculture.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXhs1yqsbnM&md5=d2018e43b34e01379558190d7f9db292CAS | 22106295PubMed |
Vara Prasad PVV, Boote KJ, Hartwell AL, Thomas JM (2003) Super‐optimal temperatures are detrimental to peanut (Arachis hypogaea L.) reproductive processes and yield at both ambient and elevated carbon dioxide. Global Change Biology 9, 1775–1787.
| Super‐optimal temperatures are detrimental to peanut (Arachis hypogaea L.) reproductive processes and yield at both ambient and elevated carbon dioxide.Crossref | GoogleScholarGoogle Scholar |
Wahid A, Gelani S, Ashraf M, Foolad MR (2007) Heat tolerance in plants: an overview. Environmental and Experimental Botany 61, 199–223.
| Heat tolerance in plants: an overview.Crossref | GoogleScholarGoogle Scholar |
Wang J, Wang E, Luo Q, Kirby M (2009) Modelling the sensitivity of wheat growth and water balance to climate change in Southeast Australia. Climatic Change 96, 79–96.
| Modelling the sensitivity of wheat growth and water balance to climate change in Southeast Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhtVynsLfL&md5=7ddab4a85efcc9b932b5408db22c6a2bCAS |
Young RR, Wilson B, Harden S, Bernardi A (2009) Accumulation of soil carbon under zero tillage cropping and perennial vegetation on the Liverpool Plains, eastern Australia. Soil Research 47, 273–285.
| Accumulation of soil carbon under zero tillage cropping and perennial vegetation on the Liverpool Plains, eastern Australia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXmtlWrtbY%3D&md5=154599b1b53001a8dcce68376f031359CAS |
