Climate change impact uncertainties for maize in Panama: Farm information, climate projections, and yield sensitivities

Ruane, Alex C.; Cecil, L. DeWayne; Horton, Radley M.; Gordón, Román; McCollum, R. E.; Brown, Douglas R.; Killough, Brian; Goldberg, R. A.; Greeley, A.; Rosenzweig, Cynthia

doi:10.1016/j.agrformet.2011.10.015

Cited by 97 publications

(59 citation statements)

References 28 publications

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“…Adaptation recommendations made were therefore the most relevant at a local scale and at the time of the study. Regarding the use of climate information, Ruane et al (2013) provide an example of how a place-based study can incorporate GCMs to make risk-based projections of possible future climates to inform adaptation decisions. However, we found that in some other studies, the magnitude or nature of future climate change was discussed only as a justification, rather than given as a calculated risk based on current climate science.…”

Section: Discussionmentioning

confidence: 99%

“…This has enabled them to produce information that is informed by largescale modelled future climate scenarios (A2, business as usual) with quantified uncertainty (generated by use of GCM ensembles, input in to DSSAT), but that is also locally relevant to the specific area using local case studies. Studies by Baca et al (2014) and Rahn et al (2014) and Ruane et al (2013) all discussed adaptation options post-impact assessment; there were no examples of studies that used an iterative process between researchers (impacts modeller, social scientist) and farmers to model the impact of local relevant adaptation strategies on households.…”

Section: Assessing Adaptation Outcomes In a Place-based Contextmentioning

confidence: 99%

“…This indicator of climate change exposure was then used as a point of discussion with stakeholders with the aim to identify locally relevant adaptation strategies based on this information. Ruane et al (2013) and Schmidt et al (2012) used future projections to drive process-based crop models; DSSAT, Ecocrop and CERES-Maize models were utilised to give a quantitative projection of future yield change. Ruane et al (2013) illustrates the importance of household variables as input parameters to improve impact projections for yield on a regional scale.…”

Section: Assessing Adaptation Outcomes In a Place-based Contextmentioning

confidence: 99%

“…Ruane et al (2013) and Schmidt et al (2012) used future projections to drive process-based crop models; DSSAT, Ecocrop and CERES-Maize models were utilised to give a quantitative projection of future yield change. Ruane et al (2013) illustrates the importance of household variables as input parameters to improve impact projections for yield on a regional scale. The study by Schmidt et al (2012) uses crop impact models with climate projections (for maize-bean systems) and household information to calculate a household-specific indicator of exposure to climate change and adaptive capacity.…”

Section: Assessing Adaptation Outcomes In a Place-based Contextmentioning

confidence: 99%

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Crop modelling: towards locally relevant and climate-informed adaptation

Beveridge

Challinor

2018

Climatic Change

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A gap between the potential and practical realisation of adaptation exists: adaptation strategies need to be both climate-informed and locally relevant to be viable. Place-based approaches study local and contemporary dynamics of the agricultural system, whereas climate impact modelling simulates climate-crop interactions across temporal and spatial scales. Cropclimate modelling and place-based research on adaptation were strategically reviewed and analysed to identify areas of commonality, differences, and potential learning opportunities to enhance the relevance of both disciplines through interdisciplinary approaches. Cropmodelling studies have projected a 7-15% mean yield change with adaptation compared to a non-adaptation baseline (Nature Climate Change 4:1-5, 2014). Of the 17 types of adaptation strategy identified in this study as place-based adaptations occurring within Central America, only five were represented in crop-climate modelling literature, and these were as follows: fertiliser, irrigation, change in planting date, change in cultivar and area cultivated. The breath and agency of real-life adaptation compared to its representation in modelling studies is a source of error in climate impact simulations. Conversely, adaptation research that omits assessment of future climate variability and impact does not enable to provide sustainable adaptation strategies to local communities so risk maladaptation. Integrated and participatory methods can identify and reduce these sources of uncertainty, for example, stakeholder's engagement can identify locally relevant adaptation pathways. We propose a research agenda that uses methodological approaches from both the modelling and place-based approaches to work towards climate-informed locally relevant adaptation.

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Section: Discussionmentioning

confidence: 99%

Section: Assessing Adaptation Outcomes In a Place-based Contextmentioning

confidence: 99%

Section: Assessing Adaptation Outcomes In a Place-based Contextmentioning

confidence: 99%

Section: Assessing Adaptation Outcomes In a Place-based Contextmentioning

confidence: 99%

See 2 more Smart Citations

Crop modelling: towards locally relevant and climate-informed adaptation

Beveridge

Challinor

2018

Climatic Change

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“…Crop models and statistical approaches are commonly used to address climate impacts on crop growth and grain yield, both of which, however, have some shortcomings. Crop models do not include potentially relevant processes such as impacts of extremely high temperatures (Lobell and Burke, 2009;Tao et al, 2009;Rötter et al, 2011;Asseng et al, 2013;Ruane et al, 2013;Bassu et al, 2014). Statistical approaches are frequently limited by the quantity and quality of data (Lobell and Burke, 2009).…”

Section: Introductionmentioning

confidence: 99%

Historical data provide new insights into response and adaptation of maize production systems to climate change/variability in China

Tao

Zhang

et al. 2016

Field Crops Research

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a b s t r a c tExtensive studies had been conducted to investigate the impacts of climate change on maize growth and yield in recent decades; however, the dynamics of crop husbandry in response and adaptation to climate change were not taken into account. Based on field observations spanning from 1981 to 2009 at 167 agricultural meteorological stations across China, we found that solar radiation and temperature over the observed maize growth period had decreasing trends during 1981-2009, and maize yields were positively correlated with these climate variables in major production regions. The decreasing trends in solar radiation and temperature during maize growth period were mainly ascribed to the adoption of late maturity cultivars with longer reproductive growth period (RGP). The adoption of late maturing cultivars with longer RGP contributed substantially to grain yield increase during the last three decades. The climate trends during maize growth period varied among different production areas. During 1981During -2009, decreases in mean temperature, precipitation and solar radiation over maize growth period jointly reduced yield most by 13.2-17.3% in southwestern China, by contrast in northwestern China increases in mean temperature, precipitation and solar radiation jointly increased yield most by 12.9-14.4%. Our findings highlight that the adaptations of maize production system to climate change through shifts of sowing date and genotypes are underway and should be taken into accounted when evaluating climate change impacts.

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