Winners and losers from climate change in agriculture: Insights from a case study in the Mediterranean basin

The Mediterranean region has always shown a marked inter-annual variability in seasonal weather, creating uncertainty in decisional processes of cultivation and livestock breeding that should not be neglected when modeling farmers' adaptive responses. This is especially relevant when assessing the impact of climate change (CC), which modifies the atmospheric variability and generates new uncertainty conditions, and the possibility of adaptation of agriculture. Our analysis examines this aspect reconstructing the effects of inter-annual climate variability in a diversified farming district that well represents a wide range of rainfed and irrigated agricultural systems in the Mediterranean area. We used a Regional Atmospheric Modelling System and a weather generator to generate 150 stochastic years of the present and near future climate. Then, we implemented calibrated crop and livestock models to estimate the corresponding productive responses in the form of probability distribution functions (PDFs) under the two climatic conditions. We assumed these PDFs able to represent the expectations of farmers in a discrete stochastic programming (DSP) model that reproduced their economic behaviour under uncertainty conditions. The comparison of the results in the two scenarios provided an assessment of the impact of CC, also taking into account the possibility of adjustment allowed by present technologies and price regimes. The DSP model is built in blocks that represent the farm typologies operating in the study area, each one with its own resource endowment, decisional constraints and economic response. Under this latter aspect, major differences emerged among farm typologies and sub-zones of the study area. A crucial element of differentiation was water availability, since only irrigated C3 crops took full advantage from the fertilization effect of increasing atmospheric CO2 concentration. Rainfed crop production was depressed by the expected reduction of spring rainfall associated to the higher temperatures. So, a dualism emerges between the smaller impact on crop production in the irrigated plain sub-zone, equipped with collective water networks and abundant irrigation resources, and the major negative impact in the hilly area, where these facilities and resources are absent. However intensive dairy farming was also negatively affected in terms of milk production and quality, and cattle mortality because of the increasing summer temperatures. This provides explicit guidance for addressing strategic adaptation policies and for framing farmers' perception of CC, in order to help them to develop an awareness of the phenomena that are already in progress, which is a prerequisite for effective adaptation responses.

[1]  S. Gualdi,et al.  Effects of Tropical Cyclones on Ocean Heat Transport in a High-Resolution Coupled General Circulation Model , 2011 .

[2]  A. Garrido,et al.  Modelling water markets under uncertain water supply , 2005 .

[3]  Arnaud Reynaud,et al.  A dynamic bio-economic model to simulate optimal adjustments of suckler cow farm management to production and market shocks in France , 2009 .

[4]  G. Hahn Dynamic responses of cattle to thermal heat loads. , 1999, Journal of animal science.

[5]  N. Lacetera,et al.  The effects of heat stress in Italian Holstein dairy cattle. , 2014, Journal of dairy science.

[6]  N. Lacetera,et al.  Seasonal variations in the composition of Holstein cow's milk and temperature-humidity index relationship. , 2014, Animal : an international journal of animal bioscience.

[7]  H. Mayer,et al.  Heat stress in Greece , 1997, International journal of biometeorology.

[8]  M. Trnka,et al.  Impacts and adaptation of European crop production systems to climate change , 2011 .

[9]  P. Shewry,et al.  Modelling predicts that heat stress, not drought, will increase vulnerability of wheat in Europe , 2011, Scientific reports.

[10]  Graziano Mazzapicchio,et al.  Uncertain water supply in an irrigated Mediterranean area: An analysis of the possible economic impact of climate change on the farm sector , 2010 .

[11]  R. Cortignani,et al.  Income Impacts of Climate Change: Irrigated Farming in the Mediterranean and Expected Changes in Probability of Favorable and Adverse Weather Conditions , 2014 .

[12]  A. Garrido,et al.  Spot water markets and risk in water supply , 2005 .

[13]  L. Garrote,et al.  Impacts of climate change in agriculture in Europe. PESETA-Agriculture study , 2009 .

[14]  Jeanne Y. Coulibaly,et al.  Cotton Price Policy and New Cereal Technology in the Malian Cotton Zone , 2011 .

[15]  John F. B. Mitchell,et al.  The next generation of scenarios for climate change research and assessment , 2010, Nature.

[16]  R. Leemans,et al.  Adaptation to climate change and climate variability in European agriculture: The importance of farm level responses , 2010 .

[17]  T. Kätterer,et al.  Modelling C, N, water and heat dynamics in winter wheat under climate change in southern Sweden , 2001 .

[18]  Pier Paolo Roggero,et al.  Hybrid knowledge for understanding complex agri-environmental issues: nitrate pollution in Italy , 2014 .

[19]  F. Cesarone,et al.  Heat waves in the Mediterranean: a local feature or a larger‐scale effect? , 2006 .

[20]  James W. Jones,et al.  GENCALC: Software to Facilitate the Use of Crop Models for Analyzing Field Experiments , 1993 .

[21]  Giampiero Maracchi,et al.  Sensitivity of meteorological high-resolution numerical simulations of the biggest floods occurred over the Arno river basin, Italy, in the 20th century , 2004 .

[22]  J. Finger,et al.  A Measure of `Export Similarity' and Its Possible Uses , 1979 .

[23]  R. Huirne,et al.  Coping with Risk in Agriculture , 1997 .

[24]  N. Lacetera,et al.  Dynamics of the temperature-humidity index in the Mediterranean basin , 2011, International journal of biometeorology.

[25]  M. Pasqui,et al.  Perceiving to learn or learning to perceive? Understanding farmers' perceptions and adaptation to climate uncertainties , 2016 .

[26]  M. Trnka,et al.  Simulation of winter wheat yield and its variability in different climates of Europe: A comparison of eight crop growth models , 2011 .

[27]  Pier Paolo Roggero,et al.  Long term effects of tillage practices and N fertilization in rainfed Mediterranean cropping systems: durum wheat, sunflower and maize grain yield , 2016 .

[28]  Adrian C. Newton,et al.  Adapting crops and cropping systems to future climates to ensure food security: The role of crop modelling , 2013 .

[29]  Allan N. Rae,et al.  Stochastic Programming, Utility, and Sequential Decision Problems in Farm Management , 1971 .

[30]  E. Schmid,et al.  Integrated Analysis of Climate Change Impacts and Adaptation Measures in Austrian Agriculture , 2014, German Journal of Agricultural Economics.

[31]  M. Trnka,et al.  Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models , 2012 .

[32]  Stephan Dabbert,et al.  Integrating Agri‐Environmental Programs into Regional Production Models: An Extension of Positive Mathematical Programming , 2003 .

[33]  M. Kanamitsu,et al.  NCEP–DOE AMIP-II Reanalysis (R-2) , 2002 .

[34]  John R. Williams,et al.  SENSITIVITY AND UNCERTAINTY ANALYSES OF CROP YIELDS AND SOIL ORGANIC CARBON SIMULATED WITH EPIC , 2005 .

[35]  Darran King,et al.  Impacts of Climate Change on Lower Murray Irrigation , 2009 .

[36]  M. Cabelguenne,et al.  Calibration and validation of EPIC for crop rotations in southern France , 1990 .

[37]  John M. Antle,et al.  A method for evaluating climate change adaptation strategies for small-scale farmers using survey, experimental and modeled data , 2012 .

[38]  M. Colacino,et al.  Heat waves in the central Mediterranean. A synoptic climatology , 1995 .

[39]  A. Crisci,et al.  A synoptic characterization of the dust transport and associated thermal anomalies in the Mediterranean basin , 2016 .

[40]  M. Ward,et al.  Precipitation over Sardinia (Italy) during the 1946-1993 rainy seasons and associated large-scale climate variations , 2000 .

[41]  Elizabeth C. Kent,et al.  Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century , 2003 .

[42]  K. Cocks Discrete Stochastic Programming , 1968 .

[43]  R. Cortignani,et al.  Simulation of the impact of greening measures in an agricultural area of the southern Italy. , 2015 .

[44]  H. Formayer,et al.  Modeling climate change and biophysical impacts of crop production in the Austrian Marchfeld Region , 2012, Climatic Change.

[45]  D. Nickerson,et al.  Estimating Physiological Thresholds with Continuous Two-Phase Regression , 1989, Physiological Zoology.

[46]  James W. Jones,et al.  The DSSAT cropping system model , 2003 .

[47]  James W. Jones,et al.  Decision support system for agrotechnology transfer: DSSAT v3 , 1998 .

[48]  G. Dono,et al.  Irrigation Water: Alternative Pricing Schemes Under Uncertain Climatic Conditions , 2012 .

[49]  N. Lacetera,et al.  Seasonal pattern of mortality and relationships between mortality and temperature-humidity index in dairy cows. , 2009, Journal of dairy science.

[50]  C. Ringler,et al.  Climate change and agriculture: Impacts and adaptation options in South Africa , 2014 .

[51]  F. Tao,et al.  Probabilistic Change of Wheat Productivity and Water Use in China for Global Mean Temperature Changes of 1°, 2°, and 3°C , 2013 .

[52]  Pier Paolo Roggero,et al.  An Integrated Assessment of the Impacts of Changing Climate Variability on Agricultural Productivity and Profitability in an Irrigated Mediterranean Catchment , 2013, Water Resources Management.

[53]  R. Pielke,et al.  A comprehensive meteorological modeling system—RAMS , 1992 .

[54]  Linda O. Mearns,et al.  Reliability and input-data induced uncertainty of the EPIC model to estimate climate change impact on sorghum yields in the U.S. Great Plains , 2009 .

[55]  M. J. Savage,et al.  The soil water balance of rainfed and irrigated oats, Italian rye grass and rye using the CropSyst model , 2008, Irrigation Science.

[56]  N. Khabarov,et al.  Pan-European crop modelling with EPIC: Implementation, up-scaling and regional crop yield validation , 2013 .

[57]  John M. Antle,et al.  Adaptation, Spatial Heterogeneity, and the Vulnerability of Agricultural Systems to Climate Change and CO2 Fertilization: An Integrated Assessment Approach , 2004 .

[58]  M. Llasat,et al.  Monthly rainfall changes in Central and Western Mediterranean basins, at the end of the 20th and beginning of the 21st centuries , 2011 .

[59]  Shailesh Shrestha,et al.  Impacts of climate change on eu agriculture , 2013 .

[60]  Pier Paolo Roggero,et al.  Adapting to uncertainty associated with short-term climate variability changes in irrigated Mediterranean farming systems , 2013 .