Climate Services for Agricultural and Livestock Producers: What have we learned?

Norman Breuer, Clyde William Fraisse

Resumo


Climate services are scientifically based products that enhance users’ understanding on the impacts of climate on their decisions and actions. Decision Support Systems (DSSs) are programs that use models and other information to make site-specific recommendations for farm management-related activities. Climate variability is a source of production risk worldwide and is associated with other risks such as pest and disease incidence. Extreme climate events such as drought, intense precipitations, and pest or disease outbreak can also affect commodity prices and increase marketing risk. However, climate forecasts alone usually do not provide actionable information for improving decisions and policy. Climate forecasts are the basis for co-development of DSSs to support improved decisions at different scales to maximize profits and input use, and to minimize climate risks, and negative environmental externalities. Major advances in developing DSSs occurred through design, diffusion, and adoption made possible through continuous interaction among scientists, boundary organizations and end users in a participatory research and development process. This article describes the evolution of this process and addresses issues of co-development, participation, scale, and future research needs through a case study that highlights commonalities and differences between producer needs, perceptions, and adoption at two research sites (one in Florida, USA and the other in southeastern Paraguay).

Palavras-chave


interdisciplinary research; decision support systems scales; decision making; decision support co-development

Texto completo:

PDF (English)

Referências


BAIGORRIA, G.A.; JONES, J.W.; O’BRIEN, J.J. Understanding rainfall spatial variability in the southeast USA at different timescales. International Journal of Climatology, 27: 749-760, 2007.

BERLATO, M.A.; FARENZENA, H.; FONTANA, D.S. Associação entre El Niño Oscilação Sul e a produtividade do milho no Estado do Rio Grande do Sul. Pesq. agropec. bras. vol.40 no.5, 2005. BRADSHAW, B., DOLAN, H.; SMIT, B. Climatic Change, 67: 119, 2004. https://doi.org/10.1007/ s10584-004- 0710-z

BREUER, N.E.; CABRERA, V.E.; INGRAM, K.T.; BROAD, K.; HILDEBRAND, P.E. AgClimate: A case study in participatory decision support system development, Climatic Change, 87: 385-403, 2008.

BREUER, N.E.; CABRERA, V.E.; HILDEBRAND, P.E. Molding the pipeline into a loop: The participatory process of developing AgroClimate, a decision support system for climate risk reduction in agriculture. Journal of Service Climatology, 3:1-12, 2009. CABRERA, V.; LETSON, D.; PODESTA, G. The value of climate information when farm programs matter. Agric Sys 93:25-42, 2007. DOI: 10.1016/j. agsy.2006.04.005

CASH, D.W; CLARK W.C; ALCOCK, F; DICKSON, N.M; ECKLEY, N; GUSTON, D.H; JAGER, J.;MITCHELL, R.B: Knowledge systems for sustainable development. Proc Natl Acad Sci U S A, 100:8086-8091, 2003.

CRANE, T.; RONCOLI, C.A.;HOOGENBOOM, G. Adaptation to climate change and climate variability: The importance of understanding agriculture as performance. NJAS - Wageningen Journal of Life Sciences, 57, 3–4: 179-185, 2011.

DI FALCO, S.; ADINOLFI, F.; BOZZOLA, M.; CAPITANIO, F. Crop Insurance as a Strategy for Adapting to Climate Change. Journal of Agricultural Economics, 65: 485-504, 2014.

DIAZ, A.F.; STUDZINSKI, C.D.; MECHOSO, R.C. Relationship between precipitation anomalies in Uruguay and shouthern Brazil and sea surface temperature in the Pacific and Atlantic Oceans. Journal of Climate, v.11, p.251-271, 1998.

FAO. Insurance of crops in the developing world. 2019. Available: http://www.fao.org/3/y5996e/y5996e02.htm. Accessed on 09/23/2019 FAO. The impact of disasters and crises on agriculture and food security. 2017. Available: http://www.fao.org/3/I8656EN/i8656en.pdf. Accessed 10/28/2019

FINDLATER, K; KANDIKAR, M. Risk Analysis 2019a.. Available: Farmers’ Risk-Based Decision Making Under Pervasive Uncertainty: Cognitive Thresholds and Hazy Hedging. DOI: 10.1111/risa.13290.

FINDLATER, K.M; KANDLIKAR, M; SATTERFIELD, T. Weather and climate variability may be poor proxies for climate change in farmer risk perceptions. Weather, Climate and Society, 2019b. https://doi. org/10.1175/WCAS-D-19-0040.1

GAMARRA, T. Herramientas para la toma de decisonesy tranferencia de riesgos del sector de la agroindustria ante los efectos del cambio climático en Urutuay, Paraguay y Argentina. 2017. Available: http:// saras-institute.org/images/publications/Gamarra_Herramientas_- toma_de_decisiones.pdf. Accessed 09/23/2019.

GRIMM, A.; FERRAZ, S.E.T.; GOMES, J. Precipitation anomalies in southern Brazil associated with El Niño and La Niña events. Journal of Climate, v.11, p.2863-2880, 1998.

HAN, E.; INES, A.V.M.; BAETHGEN, W.E. Climate-Agriculture-Modeling and Decision Tool (CAMDT): A software framework for climate risk management in agriculture. Env. Modelling & Software (95): 102-114, 2017.

JAGTAP, S.S.; JONES, J.W.; HILDEBRAND, P.; LETSON, D.; O’BRIEN, J.J.; PODESTA, G., ZIERDEN, D.; ZAZUETA, F. Responding to stakeholder’s demands for climate Information: from research to applications in Florida. Agricultural Systems, 74: 415-430, 2002.

LETSON, D.; HA NSEN, J.; HILDEBRAND, P.E.; JONES, J.W.; O’BRIEN, J.J.; PODESTÁ, G. P.;ROYCE, F.S.; ZIERDEN, D.F. Florida’s Agriculture and Climatic Variability: Reducing Vulnerability. The Florida Geographer, 32: 41-44, 2001.

MEINKE, H.; BAETHGEN, W.E.; CARBERRY, P.S.; DONATELLI, M.; HAMMER, G.L.; SELVARAJU, R.; STOCKLE, C. Increasing profits and reducing risks in crop production using participative systems simulation approaches. Agr. Syst. 70, 493–513, 2001.

MEINKE, H. et al.. Adaptation science for agriculture and natural resource management— urgency and theoretical basis. Current Opinion in Environmental Sustainability, 1:69–76, 2009.

PODESTÁ, G.; LETSON, D.; MESSINA, C.; ROYCE, F.; FERREYRA, R.A.; JONES, J.W.; HANSEN, J.W.; LLOVET, I.; GRONDONA,M.; O’BRIEN, J.J. Use of ENSO-related climate information in agricultural decision making in Argentina: a pilot experience. Agr Syst 74:371-392, 2002.

PRICE, D.H. Wittfogel’s Neglected Hydraulic/Hydroagricultural Distinction. J Anth Res 50: 187-204, 1994.

PROKOPY, L.S.; CARLTON, J.S.; HAIGH, T.; LEMOS, M.C.; MASE, A.S.; WIDHALM, M. Useful to Usable: Developing usable climate science for agriculture. Climate Risk Management 15: 1-7, 2017.

ROPELEWSKI, C.F.;HALPERT, M.S.. Quantifying southern oscillation-precipitation Relationships. Journal of Climate, 9:1043-1059, 1996.

UN. Sustainable Development Goals. 2015. Available: https://www. un.org/sustainabledevelopment/sustainable-development-goals/. Accessed 09/23/2019.

WMO. Climate Services. Available: https://public.wmo.int/en/bulletin/ what-do-we-mean-climate services#targetText=A%20climate%20 service%20is%20a,ex%2Dante%20decision%2Dmaking. Accessed 09/23/2019.




DOI: http://dx.doi.org/10.31062/agrom.v28.e026654

Apontamentos

  • Não há apontamentos.


Embrapa Trigo

Rodovia BR-285, km 294, Caixa Postal: 3081

CEP 99050-970 Passo Fundo/RS