publication . Article . 2019

To what extent is climate change adaptation a novel challenge for agricultural modellers?

Kipling, R.P.; Topp, C.F.E.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Cortignani, R.; del Prado, A.; Dono, G.; Faverdin, P.; Graux, A.-I.; ...
Open Access English
  • Published: 29 Jul 2019
  • Publisher: HAL CCSD
Abstract
Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined t...
Subjects
free text keywords: global change, modelling, numerical models, Research challenges, Adaptation, Agricultural modelling, Climate change, changement climatique, modèle, modélisation, agriculture, front de recherche, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Article, Agricultural Science, Adaptation, Agricultural modelling, Climate change, Research challenges, 636, Agricultrual modelling, VDP::Landbruks- og Fiskerifag: 900, Ecological Modelling, Environmental Engineering, Software, Sciences agricoles, Agricultural sciences, Adaptation;Agricultural modelling;Climate change;Research challenges, 636, Technology and Engineering, Earth and Environmental Sciences, GREENHOUSE-GAS EMISSIONS, FARM-LEVEL ADAPTATION, LAND-USE, FOOD SECURITY, ADAPTING AGRICULTURE, LIVESTOCK PRODUCTION, DECISION-MAKING, CHANGE IMPACTS, DAIRY FARMS, CROP, Greenhouse gas, Economics, Agriculture, business.industry, business, Risk assessment, Environmental planning, Climate change adaptation, Land use, Climate change, Food security, Peer review
59 references, page 1 of 4

Acosta-Michlik, L., Espaldon, V., 2008. Assessing vulnerability of selected farming communities in the Philippines based on a behavioural model of agent's adaptation to global environmental change. Glob. Environ. Chang. 18, 554-563. https://doi.org/ 10.1016/j.gloenvcha.2008.08.006.

Acosta-Michlik, L.A., Rounsevell, M.D.A., Bakker, M., Van Doorn, A., Gómez-Delgado, M., Delgado, M., 2014. An agent-based assessment of land use and ecosystem changes in traditional agricultural landscape of Portugal. Intell. Inf. Manag. 6, 55-80. https:// doi.org/10.4236/iim.2014.62008.

Adger, W.N., Brown, I., Surminski, S., 2018. Advances in risk assessment for climate change adaptation policy. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 376. https:// doi.org/10.1098/rsta.2018.0106.

Annetts, J.E., Audsley, E., 2002. Multiple objective linear programming for environmental farm planning. J. Oper. Res. Soc. 53, 933-943. https://doi.org/10.1057/ palgrave.jors.2601404. [OpenAIRE]

Anwar, M.R., Liu, D.L., Macadam, I., Kelly, G., 2013. Adapting agriculture to climate change: a review. Theor. Appl. Climatol. 113, 225-245. https://doi.org/10.1007/ s00704-012-0780-1.

Asseng, S., Ewert, F., Rosenzweig, C., Jones, J.W., Hatfield, J.L., Ruane, A.C., Boote, K.J., Thorburn, P.J., Rötter, R.P., Cammarano, D., Brisson, N., Basso, B., Martre, P., Aggarwal, P.K., Angulo, C., Bertuzzi, P., Biernath, C., Challinor, A.J., Doltra, J., Gayler, S., Goldberg, R., Grant, R., Heng, L., Hooker, J., Hunt, L.A., Ingwersen, J., Izaurralde, R.C., Kersebaum, K.C., Müller, C., Naresh Kumar, S., Nendel, C., O'Leary, G., Olesen, J.E., Osborne, T.M., Palosuo, T., Priesack, E., Ripoche, D., Semenov, M.A., Shcherbak, I., Steduto, P., Stöckle, C., Stratonovitch, P., Streck, T., Supit, I., Tao, F., Travasso, M., Waha, K., Wallach, D., White, J.W., Williams, J.R., Wolf, J., 2013. Uncertainty in simulating wheat yields under climate change. Nat. Clim. Chang. 3, 827. https://doi.org/10.1038/nclimate1916.

Balbi, S., Prado, A.d., Gallejones, P., Geevan, C.P., Pardo, G., Pérez-Miñana, E., Manrique, R., Hernandez-Santiago, C., Villa, F., 2015. Modeling trade-offs among ecosystem services in agricultural production systems. Environ. Model. Softw 72, 314-326. https://doi.org/10.1016/j.envsoft.2014.12.017.

Bellocchi, G., Rivington, M., Matthews, K., Acutis, M., 2015. Deliberative processes for comprehensive evaluation of agroecological models. Rev. Agron. Sustain. Dev. 35, 589-605. https://doi.org/10.1007/s13593-014-0271-0.

Berger, T., Troost, C., 2014. Agent-based modelling of climate adaptation and mitigation options in agriculture. J. Agric. Econ. 65, 323-348. https://doi.org/10.1111/1477- 9552.12045.

Bergez, J.E., Chabrier, P., Gary, C., Jeuffroy, M.H., Makowski, D., Quesnel, G., Ramat, E., Raynal, H., Rousse, N., Wallach, D., Debaeke, P., Durand, P., Duru, M., Dury, J., Faverdin, P., Gascuel-Odoux, C., Garcia, F., 2013. An open platform to build, evaluate and simulate integrated models of farming and agro-ecosystems. Environ. Model. Softw 39, 39-49. https://doi.org/10.1016/j.envsoft.2012.03.011.

Bitsch, V., 2005. Qualitative research: a Grounded Theory example and evaluation criteria. J. Agribus. 23, 75-91. [OpenAIRE]

Briner, S., Elkin, C., Huber, R., Grêt-Regamey, A., 2012. Assessing the impacts of economic and climate changes on land-use in mountain regions: a spatial dynamic modeling approach. Agric. Ecosyst. Environ. 149, 50-63. https://doi.org/10.1016/j. agee.2011.12.011.

Cammarano, D., Rivington, M., Matthews, K.B., Miller, D.G., Bellocchi, G., 2017. Implications of climate model biases and downscaling on crop model simulated climate change impacts. Eur. J. Agron. 88, 63-75. https://doi.org/10.1016/j.eja.2016. 05.012.

Challinor, A.J., Watson, J., Lobell, D.B., Howden, S.M., Smith, D.R., Chhetri, N., 2014. A meta-analysis of crop yield under climate change and adaptation. Nat. Clim. Chang. 4, 287. https://doi.org/10.1038/nclimate2153.

Chardon, X., 2008. Evaluation environnementale des exploitations laitieres par modelisation dynamique de leur fonctionnement et des flux de matiere: developpement et application du simulateur Melodie. AgroParisTech, Paris, France. [OpenAIRE]

59 references, page 1 of 4
Any information missing or wrong?Report an Issue