| 1. |
- Rodríguez, A., et al.
(author)
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Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations
- 2019
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In: Agricultural and Forest Meteorology. - : Elsevier BV. - 0168-1923 .- 1873-2240. ; 264, s. 351-362
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Journal article (peer-reviewed)abstract
- Climate change is expected to severely affect cropping systems and food production in many parts of the world unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertainty in the simulated crop impact resulting from the crop models themselves. Although some studies have analysed the influence of ensemble size on model outcomes, the effect of ensemble composition has not yet been properly appraised. Moreover, results and derived recommendations typically rely on averaged ensemble simulation results without accounting sufficiently for the spread of model outcomes. Therefore, we developed an Ensemble Outcome Agreement (EOA) index, which analyses the effect of changes in composition and size of a multi-model ensemble (MME) to evaluate the level of agreement between MME outcomes with respect to a given hypothesis (e.g. that adaptation measures result in positive crop responses). We analysed the recommendations of a previous study performed with an ensemble of 17 crop models and testing 54 adaptation options for rainfed winter wheat (Triticum aestivum L.) at Lleida (NE Spain) under perturbed conditions of temperature, precipitation and atmospheric CO2 concentration. Our results confirmed that most adaptations recommended in the previous study have a positive effect. However, we also showed that some options did not remain recommendable in specific conditions if different ensembles were considered. Using EOA, we were able to identify the adaptation options for which there is high confidence in their effectiveness at enhancing yields, even under severe climate perturbations. These include substituting spring wheat for winter wheat combined with earlier sowing dates and standard or longer duration cultivars, or introducing supplementary irrigation, the latter increasing EOA values in all cases. There is low confidence in recovering yields to baseline levels, although this target could be attained for some adaptation options under moderate climate perturbations. Recommendations derived from such robust results may provide crucial information for stakeholders seeking to implement adaptation measures.
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| 2. |
- Ruiz-Ramos, Miguel, et al.
(author)
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Adaptation response surfaces for managing wheat under perturbed climate and CO2 in a Mediterranean environment
- 2018
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In: Agricultural Systems. - : Elsevier BV. - 0308-521X. ; 159, s. 260-274
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Journal article (peer-reviewed)abstract
- Adaptation of crops to climate change has to be addressed locally due to the variability of soil, climate and the specific socio-economic settings influencing farm management decisions. Adaptation of rainfed cropping systems in the Mediterranean is especially challenging due to the projected decline in precipitation in the coming decades, which will increase the risk of droughts. Methods that can help explore uncertainties in climate projections and crop modelling, such as impact response surfaces (IRSs) and ensemble modelling, can then be valuable for identifying effective adaptations. Here, an ensemble of 17 crop models was used to simulate a total of 54 adaptation options for rainfed winter wheat (Triticum aestivum) at Lleida (NE Spain). To support the ensemble building, an ex post quality check of model simulations based on several criteria was performed. Those criteria were based on the "According to Our Current Knowledge" (AOCK) concept, which has been formalized here. Adaptations were based on changes in cultivars and management regarding phenology, vernalization, sowing date and irrigation. The effects of adaptation options under changed precipitation (P), temperature (T), [CO2] and soil type were analysed by constructing response surfaces, which we termed, in accordance with their specific purpose, adaptation response surfaces (ARSs). These were created to assess the effect of adaptations through a range of plausible P, T and [CO2] perturbations. The results indicated that impacts of altered climate were predominantly negative. No single adaptation was capable of overcoming the detrimental effect of the complex interactions imposed by the P, T and [CO2] perturbations except for supplementary irrigation (sI), which reduced the potential impacts under most of the perturbations. Yet, a combination of adaptations for dealing with climate change demonstrated that effective adaptation is possible at Lleida. Combinations based on a cultivar without vernalization requirements showed good and wide adaptation potential. Few combined adaptation options performed well under rainfed conditions. However, a single sI was sufficient to develop a high adaptation potential, including options mainly based on spring wheat, current cycle duration and early sowing date. Depending on local environment (e.g. soil type), many of these adaptations can maintain current yield levels under moderate changes in T and P, and some also under strong changes. We conclude that ARSs can offer a useful tool for supporting planning of field level adaptation under conditions of high uncertainty.
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| 3. |
- D H, Fleisher, et al.
(author)
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Yield Response of an Ensemble of Potato Crop Models to Elevated CO2 in Continental Europe
- 2021
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In: European Journal of Agronomy. - : Elsevier BV. - 1161-0301. ; 126
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Journal article (peer-reviewed)abstract
- A multi-model inter-comparison study was conducted to evaluate the performance of ten potato crop models to accurately predict potato yield in response to elevated CO2 (Ce) when calibrated with ambient CO2 data (Ca). Experimental data from seven open-top chambers (OTC) and free-air CO2-enrichment (FACE) facilities across continental Europe were used. Model ensemble percent errors averaged over all datasets for simulated yields were 26.5 % for Ca and 27.2 % Ce data. Metrics such as Wilmott’s index of agreement (IA) and root mean square relative error (RMSRE) ranged broadly among individual models and locations, such that four of the ten models outperformed the median or mean of the ensemble for about half of the Ce datasets. These top performing models were representative of three different model structural groups, including radiation use efficiency, transpiration efficiency, or leaf-level based approaches. Relative response to an increase in CO2 was more accurately modeled than absolute yield responses when averaged across all locations, and within 3.3 kg ppm 1 (or 5%) of observed values. Specific targets in the model structure needed for improvement were not identified due to large and inconsistent variation in the accuracy of yield predictions across locations. However, models with the lowest calibration errors tended to be top performers for Ce predictions as well. Such results suggest calibration is at least as important as model structure. Where possible, modelers using potato models to estimate Ce responses should use Ce calibration data to improve confidence in such predictions.
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