Skip to main content

Advertisement

SpringerLink
Log in

Heat stress and crop yields in the Mediterranean basin: impact on expected insurance payouts

  • Original Article
  • Published:
Regional Environmental Change Aims and scope Submit manuscript

Abstract

Insurance programmes have been indicated as a tool to reduce the economic risk associated with climate change, and crop growth simulation models can be used effectively to assess future trends in crop insurance payouts. This paper assesses the economic role of increasing weather extremes under future climate change on the expected insurance payouts for durum wheat (Triticum turgidum L. spp. durum) over the Mediterranean basin, focusing attention on the effects of heat stresses (HSs). A crop growth simulation, Sirius Quality version 2 (SQ2), calibrated for three varieties (long, medium and short growth cycle) was applied on seven sites under present (1975–1990) and future climate conditions (2030–2050) obtained from five regional circulation models under SRES scenario A1b. The intensity of HSs at anthesis was included as reducing factor of yield originally simulated by SQ2 calculated according to a specific empirical model. Simulated yields were then fitted to the most appropriate distribution, which was used to calculate the expected payouts according to the probability of yields being below a guaranteed level. We found that the simulated crop yields were, in general, negatively skewed and that Weibull probability density function (PDF), admitting negative skewing, provided the best performances in their fitting. The simulation of HSs modified the original shape of the Weibull PDF by increasing the skewness of the distribution. The results of the insurance model indicated that the modification of crop PDFs induced by HSs led to a general increase in payouts with respect to unstressed conditions, with a marked difference between present (+11 %, on average for the selected sites) and future periods (+25 %). When compared to the present, a general decrease in payouts (−1.1 %) was observed when HSs were not included in the simulations. Conversely, HSs impact resulted in a general increase in payouts (+10.3 %) where the highest increase was detected for the long growth cycle variety (+16.6 %) and the lowest for that with short growth cycle (−1.6 %). These results emphasize the importance of the appropriate characterization of crop yield distribution, the economic implications of HSs in a risk management context and a possible strategy to cope with climate change and variability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Antle JM (2010) Asymmetry, partial, moments, and production risk. Am J Agric Econ 92(5):1294–1309. doi:10.1093/ajae/aaq077

    Article  Google Scholar 

  • Baigorria GA, Jones JW, Shin DW, Mishra A, O Brien JJ (2007) Assessing uncertainties in crop model simulations using daily bias-corrected regional circulation model outputs. Clim Res 34(3):211–222. doi:10.3354/cr00703

    Article  Google Scholar 

  • Bakker AM, Bessembinder JJ, de Wit AJ, van den Hurk BJ, Hoek SB (2014) Exploring the efficiency of bias corrections of regional climate model output for the assessment of future crop yields in Europe. Reg Environ Change 14:865–877. doi:10.1007/s10113-013-0557-9

    Google Scholar 

  • Berg A, de Noblet-Ducoudre M, Sultan B, Langaigne M, Guimberteau M (2013) Projections of Climate Change impacts on potential C4 crop productivity over tropical regions. Agric For Meteorol 170:89–102. doi:10.1016/j.agrformet.2011.12.003

    Article  Google Scholar 

  • Bindi M, Olesen JE (2011) The responses of agriculture in Europe to climate change. Reg Environ Change 11(1):151–158. doi:10.1007/s10113-010-0173-x

    Article  Google Scholar 

  • Challinor AJ, Wheeler TR, Slingo JM (2005) Simulation of the impact of high temperature stress on the yield of an annual crop. Agric For Meteorol 135:180–189. doi:10.1016/j.agrformet.2005.11.015

    Article  Google Scholar 

  • Challinor AJ, Wheeler TR, Hemming D, Upadhyaya HD (2009) Ensemble yield simulations: crop and climate uncertainties, sensitivity to temperature and genotypic adaptation to climate change. Clim Res 38(2):117–127. doi:10.3354/cr00779

    Article  Google Scholar 

  • Christensen JH, Boberg F, Christensen OB, Lucas-Picher P (2008) On the need for bias correction of regional climate change projections of temperature and precipitation. Geophys Res Lett 35(20):L20709. doi:10.1029/2008GL035694

    Article  Google Scholar 

  • David C, Jeuffroy MH (2009) A sequential approach for improving AZODYN crop model under conventional and low-input conditions. Eur J Agron 31(4):177–182. doi:10.1016/j.eja.2009.05.007

    Article  Google Scholar 

  • Deryng D, Sacks WJ, Barford CC, Ramankutty N (2011) Simulating the effects of climate and agricultural management practices on global crop yield. Glob Biogeochem Cycles. doi:10.1029/2009GB003765

    Google Scholar 

  • Du X, Hennessy DA, Cindy LY (2012) Testing Day’s conjecture that more nitrogen decreases crop yield skewness. Am J Agric Econ 94(1):225–237. doi:10.1093/ajae/aar091

    Article  Google Scholar 

  • Eitzinger J, Thaler S, Schmid E, Strauss F, Ferrise R, Moriondo M, Bindi M, Palosuo T, Rötter R, Kersebaum KC, Olesen J, Patil R, Saylan L, Caldag B, Caylak O (2013) Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria. J Agric Sci 151:813–835. doi:10.1017/S0021859612000779

    Article  Google Scholar 

  • Ferris R, Ellis RH, Wheeler TR, Hadley P (1998) Effect of high temperature stress at anthesis on grain yield and biomass of field-grown crops of wheat. Ann Bot 82:631–639. doi:10.1006/anbo.1998.0740

    Article  Google Scholar 

  • Ferrise R, Moriondo M, Bindi M (2011) Probabilistic assessments of climate change impacts on durum wheat in the Mediterranean region. Nat Hazard Earth Syst 11(5):1293–1302. doi:10.5194/nhess-11-1293-2011

    Article  Google Scholar 

  • Ferrise R, Moriondo M, Trombi G, Miglietta F, Bindi M (2013) Climate change impacts on typical Mediterranean crops and evaluation of adaptation strategies to cope with. In: Navarra A, Tubiana L (eds) Regional assessment of climate change in the Mediterranean, advances in global change research. Springer, The Netherlands, pp 49–70

    Chapter  Google Scholar 

  • Gallagher P (1987) US soybean yields: estimation and forecasting with nonsymmetric disturbances. Am J Agric Econ 69(4):796–803. doi:10.2307/1242190

    Article  Google Scholar 

  • Garrido A, Bielza M, Rey D, Mínguez MI, Ruiz-Ramos M (2011) Insurance as an adaptation to climate variability in agriculture. In: Hazell P, Mendelsohn R, Dinar A (eds) Handbook on climate change and agriculture. Edward Elgar Publishing, Cheltenham, UK, pp 420–445

    Google Scholar 

  • Goodwin BK, Ker AP (1998) Nonparametric estimation of crop yield distributions: implications for rating group-risk crop insurance contracts. Am J Agric Econ 80(1):139–153. doi:10.2307/3180276

    Article  Google Scholar 

  • Hollander M, Wolfe DA (1999) Nonparametric statistical methods, 2nd edn. Wiley, New York 787 pp

    Google Scholar 

  • Howden SM, Soussana JF, Tubiello FN, Chhetri N, Dunlop M, Meinke H (2007) Adapting agriculture to climate change. Proc Natl Acad Sci USA 104(50):19691–19696. doi:10.1073/pnas.0701890104

    Article  CAS  Google Scholar 

  • Just RE, Weninger Q (1999) Are crop yields normally distributed? Am J Agric Econ 81(2):287–304. doi:10.2307/1244582

    Article  Google Scholar 

  • Maracchi G, Sirotenko O, Bindi M (2005) Impacts of present and future climate variability on agriculture and forestry in the temperate regions: Europe. Clim Change 70(1–2):117–135. doi:10.1007/1-4020-4166-7_6

    Article  CAS  Google Scholar 

  • Martre P, Jamieson PD, Semenov MA, Zyskowski RF, Porter JR, Triboi E (2006) Modelling protein content and composition in relation to crop nitrogen dynamics for wheat. Eur J Agron 25(2):138–154. doi:10.1016/j.eja.2006.04.007

    Article  CAS  Google Scholar 

  • Matthews RB, Kropff MJ, Horie T, Bachelet D (1997) Simulating the impact of climate change on rice production in Asia and evaluating options for adaptation. Agric Syst 54(3):399–425. doi:10.1016/S0308-521X(95)00060-I

    Article  Google Scholar 

  • Moberg A, Jones PD (2004) Regional climate model simulations of daily maximum and minimum near-surface temperatures across Europe compared with observed station data 1961–1990. Clim Dyn 23:695–715. doi:10.1007/s00382-004-0464-3

    Article  Google Scholar 

  • Moriondo M, Bindi M, Kundzewicz ZW, Szwed M, Chorynski A, Matczak P, Radziejewski M, McEvoy D, Wreford A (2010) Impact and adaptation opportunities for European agriculture in response to climatic change and variability. Mitig Adapt Strateg Glob Change 15(7):657–679. doi:10.1007/s11027-010-9219-0

    Article  Google Scholar 

  • Moriondo M, Giannakopoulos C, Bindi M (2011) Climate change impact assessment: the role of climate extremes in crop yield simulation. Clim Change 104:679–701. doi:10.1007/s10584-010-9871-0

    Article  Google Scholar 

  • Moriondo M, Ferrise R, Trombi G, Brilli L, Dibari C, Bindi M (2015) Modelling olive trees and grapevines in a changing climate. Environ Model Softw. doi:10.1016/j.envsoft.2014.12.016

    Google Scholar 

  • Nendel C, Berg M, Kersebaum KC, Mirschel W, Specka X, Wegehenkel M, Wenkel KO, Wieland R (2011) The Monica model: testing predictability for crop growth, soil moisture and nitrogen dynamics. Ecol Model 222:1614–1625. doi:10.1016/j.ecolmodel.2011.02.018

    Article  CAS  Google Scholar 

  • Olesen JE, Carter TR, Diaz-Ambrona CH, Fronzek S, Heidmann T, Hickler T, Sykes MT (2007) Uncertainties in projected impacts of climate change on European agriculture and terrestrial ecosystems based on scenarios from regional climate models. Clim Change 81(1):123–143. doi:10.1007/s10584-006-9216-1

    Article  Google Scholar 

  • Palosuo T, Kersebaum KC, Angulo C, Hlavinka P, Moriondo M, Olesen JE, Patil RH, Ruget F, Rumbaur C, Takáč J, Trnka M, Bindi M, Çaldaĝ B, Ewert F, Ferrise R, Mirschel W, Şaylan L, Šiška B, Rötter R (2011) Simulation of winter wheat yield and its variability in different climates of Europe: a comparison of eight crop growth models. Eur J Agron 35:103–114. doi:10.1016/j.eja.2011.05.001

    Article  Google Scholar 

  • Park WI, Sinclair TR (1993) Consequences of climate and crop yield limits on the distribution of corn yields. Appl Econ Perspect Policy 15(3):483–493. doi:10.2307/1349483

    Google Scholar 

  • Porter JR, Gawith M (1999) Temperature and the growth and development of wheat: a review. Eur J Agron 10:23–36. doi:10.1016/S1161-0301(98)00047-1

    Article  Google Scholar 

  • Porter JR, Semenov MA (1999) Climatic variability and crop yields in Europe. Nature 400(6746):724. doi:10.1038/23385

    Article  CAS  Google Scholar 

  • Porter JR, Semenov MA (2005) Crop responses to climatic variation. Philos Trans R Soc Lond B Biol Sci 360:2021–2035. doi:10.1098/rstb.2005.1752

    Article  Google Scholar 

  • Rötter RP, Palosuo T, Kersebaum KC, Angulo C, Bindi M, Ewert F, Ferrise R, Hlavinka P, Moriondo M, Nendel C, Olesen JE, Patil RH, Ruget F, Takáč J, Trnka M (2012) Simulation of spring barley yield in different climatic zones of Northern and Central Europe: a comparison of nine crop models. Field Crop Res 133:23–36. doi:10.1016/j.fcr.2012.03.016

    Article  Google Scholar 

  • Scheffe H, Tukey JW (1945) Non-Parametric estimation. I. Validation of order statistics. Ann Math Stat 16:187–192

    Article  Google Scholar 

  • Schlenker W, Roberts MJ (2009) Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proc Natl Acad Sci USA 106(37):15594–15598. doi:10.1073/pnas.0906865106

    Article  CAS  Google Scholar 

  • Semenov MA, Barrow EM (1997) Use of a stochastic weather generator in the development of climate change scenarios. Clim Change 35:397–414. doi:10.1023/A:1005342632279

    Article  Google Scholar 

  • Semenov MA, Porter JR (1995) Climatic variability and the modelling of crop yields. Agric For Meteorol 73:265–283. doi:10.1016/0168-1923(94)05078-K

    Article  Google Scholar 

  • Sherrick BJ, Zanini FC, Schnitkey GD, Irwin SH (2004) Crop insurance valuation under alternative yield distributions. Am J Agric Econ 86:406–419. doi:10.1111/j.0092-5853.2004.00587.x

    Article  Google Scholar 

  • Steduto P, Hsiao TC, Raes D, Fereres E (2009) AquaCrop—the FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agron J 101:426–437. doi:10.2134/agronj2008.0139s

    Article  Google Scholar 

  • Supit I, van Diepen CA, de Wit AJW, Wolf J, Kabat P, Baruth B, Ludwig F (2012) Assessing climate change effects on European crop yields using the Crop Growth Monitoring System and a weather generator. Agric For Meteorol 164:96–111. doi:10.1016/j.agrformet.2012.05.005

    Article  Google Scholar 

  • Swinton SM, King RP (1991) Evaluating robust regression techniques for detrending crop yield data with non normal errors. Am J Agric Econ 73:446–451. doi:10.2307/1242729

    Article  Google Scholar 

  • Tao F, Zhang Z (2010) Adaptation of maize production to climate change in North China Plain: quantify the relative contributions of adaptation options. Eur J Agron 33(3):103–116. doi:10.1016/j.eja.2010.04.002

    Article  Google Scholar 

  • Teixeira EI, Fischer G, Walter H, van Velthuizen C, Ewert F (2013) Global hot-spots of heat stress on agricultural crops due to climate change. Agric For Meteorol 170:206–215. doi:10.1016/j.agrformet.2011.09.002

    Article  Google Scholar 

  • Uchijima T (1976) Some aspects of the relation between low air temperature and sterile spikelets in rice plants. J Agric Meteorol 31:199–202

    Article  Google Scholar 

  • van der Linden P, Mitchell JFB (2009) ENSEMBLES: climate change and its impacts: summary of research and results from the ENSEMBLES project. Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK

  • Wheeler TR, Batts GR, Ellis RH, Hadley P, Morison JIL (1996) Growth and yield of winter wheat (Triticum aestivum L.) crops in response to CO2 and temperature. J Agric Sci Camb 127:37–48. doi:10.1017/S0021859600077352

    Article  Google Scholar 

  • Willmott CJ (1981) On the validation of models. Phys Geogr 2(2):184–194. doi:10.1080/02723646.1981.10642213

    Google Scholar 

  • Yao F, Xu Y, Lin E, Yokozawa M, Zhang J (2007) Assessing the impacts of climate change on rice yields in the main rice areas of China. Clim Change 80(3–4):395–409. doi:10.1007/s10584-006-9122-6

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The authors would like to gratefully acknowledge the constructive comments provided by the two anonymous referees.

Author information

Authors and Affiliations

  1. IBIMET-CNR, Via G. Caproni 8, 50145, Florence, Italy

    Marco Moriondo

  2. University of Florence - DISPAA, Piazzale delle Cascine 18, 50144, Florence, FI, Italy

    Giovanni Argenti, Roberto Ferrise, Camilla Dibari, Giacomo Trombi & Marco Bindi

Authors
  1. Marco Moriondo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Giovanni Argenti
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Roberto Ferrise
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Camilla Dibari
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Giacomo Trombi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Marco Bindi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marco Moriondo.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Moriondo, M., Argenti, G., Ferrise, R. et al. Heat stress and crop yields in the Mediterranean basin: impact on expected insurance payouts. Reg Environ Change 16, 1877–1890 (2016). https://doi.org/10.1007/s10113-015-0837-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10113-015-0837-7

Keywords

Search

Navigation