Impact of choice of future climate change projection on growth chamber experimental outcomes: a preliminary study in potato
Understanding the impacts of climate change on agriculture is essential to ensure adequate future food production. Controlled growth experiments provide an effective tool for assessing the complex effects of climate change. However, a review of the use of climate projections in 57 previously published controlled growth studies found that none considered within-season variations in projected future temperature change, and few considered regional differences in future warming. A fixed, often arbitrary, temperature perturbation typically was applied for the entire growing season. This study investigates the utility of employing more complex climate change scenarios in growth chamber experiments. A case study in potato was performed using three dynamically downscaled climate change projections for the mid-twenty-first century that differ in terms of the timing during the growing season of the largest projected temperature changes. The climate projections were used in growth chamber experiments for four elite potato cultivars commonly planted in Michigan’s major potato growing region. The choice of climate projection had a significant influence on the sign and magnitude of the projected changes in aboveground biomass and total tuber count, whereas all projections suggested an increase in total tuber weight and a decrease in specific gravity, a key market quality trait for potato, by mid-century. These results demonstrate that the use of more complex climate projections that extend beyond a simple incremental change can provide additional insights into the future impacts of climate change on crop production and the accompanying uncertainty.
KeywordsClimate change Controlled growth experiments Potato Regional climate model simulations Uncertainty
We would like to acknowledge Megan Conway and Paul Rosemurgy for their help with tuber harvesting. We also thank Chris Long for helpful discussions about potato growing conditions and harvest. We thank the North American Regional Climate Change Assessment Program for providing the regional climate model simulations.
This project was supported by Michigan State University GREEEN Proposal #GR15-008. The climate projections used in the study were developed with support from the National Science Foundation (Award CNH 0909378). Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not reflect the views and policies of the funding agencies.
- Andresen JA, Hilberg SD, Kunkel KE (2013) Historical climate and climate trends in the Midwestern United States. In: Winkler JA, Andresen JL, Hatfield J, Bidwell D, Brown D (eds) Climate change in the Midwest: a synthesis report for the National Climate Assessment. Island Press, Washington, D.C., pp 8–36Google Scholar
- Caldwell CR, Britz SJ, Mirecki RM (2005) Effect of temperature, elevated carbon dioxide, and drought during seed development on the isoflavone content of dwarf soybean [Glycine max (L.) Merrill] grown in controlled environments. J Agr Food Chem 53(4):1125–1129. https://doi.org/10.1021/jf0355351 CrossRefGoogle Scholar
- Collins M, Knutti R, Arblaster J, Dufresne J-L et al (2013) Long-term climate change: projections, commitments and irreversibility. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp 1029–1138Google Scholar
- Fleisher DH, Condori B, Quiroz R, Alva A, Asseng S, Barreda C, Bindi M, Boote KJ, Ferrise R, Franke AC, Govindakrishnan PM, Harahagazwe D, Hoogenboom G, Naresh Kumar S, Merante P, Nendel C, Olesen JE, Parker PS, Raes D, Raymundo R, Ruane AC, Stockle C, Supit I, Vanuytrecht E, Wolf J, Woli P (2017) A potato model intercomparison across varying climates and productivity levels. Glob Chang Biol 23(3):1258–1281. https://doi.org/10.1111/gcb.13411 CrossRefGoogle Scholar
- Hayhoe K, VanDorn J, Croley T II, Schlegal N, Wuebbles D (2010) Regional climate change projections for Chicago and the US Great Lakes. J Great Lakes Res 36:7–21. https://doi.org/10.1016/j.jglr.2010.03.012
- Lawlor DW, Mitchell RAC (1991) The effect of increasing CO2 on crop photosynthesis and productivity: a review of field studies. Plant Cell Environ 14(8):807–818. https://doi.org/10.1111/j.1365-3040.1991.tb01444.x CrossRefGoogle Scholar
- Mearns LO, Arritt R, Biner S, Bukovsky MS, McGinnis S, Sain S, Caya D, Correia J Jr, Flory D, Gutowski W, Takle ES, Jones R, Leung R, Moufouma-Okia W, McDaniel L, Nunes AMB, Roads J, Sloan L, Snyder M (2012) The North American Regional Climate Change Program: overview of phase I results. B Am Meteorol Soc 93(9):1337–1362. https://doi.org/10.1175/BAMS-D-11-00223.1 CrossRefGoogle Scholar
- Michigan Department of Agriculture and Rural Development (MDARD) (2017) www.michigan.gov/mdard. Accessed 2 August 2017
- Nakićenović NJ et al (2000) Special report on emissions scenarios: a special report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, U.K.Google Scholar
- Prasad PVV, Boote KJ, Allen LH Jr, Thomas JMG (2003) Super-optimal temperatures are detrimental to peanut (Arachis hypogaea L.) reproductive processes and yield at both ambient and elevated carbon dioxide. Glob Chang Biol 9(12):1775–1787. https://doi.org/10.1046/j.1365-2486.2003.00708.x CrossRefGoogle Scholar
- R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org/. Accessed 2 August 2017
- Rodrigues WP, Martins MQ, Fortunato AS, Rodrigues AP, Semedo JN, Simões-Costa MC, Pais IP, Leitão AE, Colwell F, Goulao L, Máguas C, Maia R, Partelli FL, Campostrini E, Scotti-Campos P, Ribeiro-Barros AI, Lidon FC, DaMatta FM, Ramalho JC (2016) Long-term elevated air [CO2] strengthens photosynthetic functioning and mitigates the impact of supra-optimal temperatures in tropical Coffea arabica and C. canephora species. Glob Chang Biol 22(1):415–431. https://doi.org/10.1111/gcb.13088 CrossRefGoogle Scholar
- Vu JCV, Gesch RW, Pennanen AH, Hartwell LA Jr, Boote KJ, Bowes G (2001) Soybean photosynthesis, Rubisco, and carbohydrate enzymes function at supraoptimal temperatures in elevated CO2. J Plant Physiol 158:295–307Google Scholar
- Winkler JA, Arritt RW, Pryor SC (2014) Climate projections for the Midwest: availability, interpretation, and synthesis. In: Winkler JA, Andresen JA, Hatfield JL, Bidwell D, Brown D (eds) Climate change in the Midwest: a synthesis report for the National Climate Assessment. Island Press, Washington, D.D, pp 37–69Google Scholar
- Winkler JA, Guentchev GS, Perdinan, Tan P-N, Zhong S, Liszewska M, Abraham Z, Niedźwiedź T, Ustrnul Z (2011) Climate scenario development and applications for local/regional climate change impact assessments: an overview for the non-climate scientist. Part I: scenario development using downscaling methods. Geogr Compass 5(6):275–300. https://doi.org/10.1111/j.1749-8198.2011.00425.x
- Zhou X, Ge Z-M, Kellomaki S, Wang K-Y, Peltola H, Martikainen P (2011) Effects of elevated CO2 and temperature on leaf characteristics, photosynthesis and carbon storage in aboveground biomass of a boreal bioenergy crop (Phalaris arundinacea L.) under varying water regimes. GCB Bioenergy 3(3):223–234. https://doi.org/10.1111/j.1757-1707.2010.01075.x