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Fleisher, D. H., Condori, B., Quiroz, R., Alva, A., Asseng, S., Barreda, C., et al. (2017). A potato model intercomparison across varying climates and productivity levels. Glob. Chang. Biol., 23(3), 1258–1281.
Abstract: A potato crop multimodel assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low-input (Chinoli, Bolivia and Gisozi, Burundi)- and high-input (Jyndevad, Denmark and Washington, United States) management sites. Two calibration stages were explored, partial (P1), where experimental dry matter data were not provided, and full (P2). The median model ensemble response outperformed any single model in terms of replicating observed yield across all locations. Uncertainty in simulated yield decreased from 38% to 20% between P1 and P2. Model uncertainty increased with interannual variability, and predictions for all agronomic variables were significantly different from one model to another (P < 0.001). Uncertainty averaged 15% higher for low- vs. high-input sites, with larger differences observed for evapotranspiration (ET), nitrogen uptake, and water use efficiency as compared to dry matter. A minimum of five partial, or three full, calibrated models was required for an ensemble approach to keep variability below that of common field variation. Model variation was not influenced by change in carbon dioxide (C), but increased as much as 41% and 23% for yield and ET, respectively, as temperature (T) or rainfall (W) moved away from historical levels. Increases in T accounted for the highest amount of uncertainty, suggesting that methods and parameters for T sensitivity represent a considerable unknown among models. Using median model ensemble values, yield increased on average 6% per 100-ppm C, declined 4.6% per °C, and declined 2% for every 10% decrease in rainfall (for nonirrigated sites). Differences in predictions due to model representation of light utilization were significant (P < 0.01). These are the first reported results quantifying uncertainty for tuber/root crops and suggest modeling assessments of climate change impact on potato may be improved using an ensemble approach.
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Tomozeiu, R., Pasqui, M., & Quaresima, S. (2017). Future changes of air temperature over Italian agricultural areas: a statistical downscaling technique applied to 2021–2050 and 2071–2100 periods. Meteorology and Atmospheric Physics, in press.
Abstract: Climate change scenarios of seasonal minimum and maximum temperature over different Italian agricultural areas, during the periods 2021–2050 and 2071–2100 against 1961–1990, are assessed. The areas are those selected in the framework of the Agroscenari project and are represented by: Padano–Veneta plain, Marche, Beneventano, Destra Sele, Oristano, Puglia and Sicilia, all areas of prominent agricultural vocation with excellence productions. A statistical downscaling technique applied to ENSEMBLES global climate simulations, emission scenario A1B, is used to achieve this objective. The statistical scheme consists of a multivariate regression based on Canonical Correlation Analysis. The scheme is constructed using large-scale fields derived from ECMWF reanalysis and seasonal mean minimum, maximum temperature derived from national observed daily gridded data that cover 1959–2008 period. Once the most skillful model has been selected for each season and variable, this is then applied to GCMs of ENSEMBLES runs. The statistical downscaling method developed reveals good skill over the case studies of the present work, underlying the possibility to apply the scheme over whole Italian peninsula. In addition, the results emphasize that the temperature at 850 hPa is the best predictor for surface air temperature. The future projections show that an increase could be expected to occur under A1B scenario conditions in all seasons, both in minimum and maximum temperatures. The projected increases are about 2 °C during 2021–2050 and between 2.5 and 4.5 °C during 2071–2100, respect to 1961–1990. The spatial distribution of warming is projected to be quite uniform over the territory to the end of the century, while some spatial differences are noted over 2021–2050 period. For example, the increase in minimum temperature is projected to be slightly higher in areas from northern and central part than those situated in the southern part of Italian peninsula, during 2021–2050 period. The peak of changes is projected to appear during summer season, for both minimum and maximum temperature. The probability density function tends to shift to warmer values during both periods, with increases more intense during summer and to the end of the century, when the lower tail is projected to shift up to 3 °C and the upper tail up to 6 °C. All these projected changes have important impacts on viticulture, intensive fruit and tomatoes, some of the main agricultural systems analyzed in the Agroscenari project.
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Gutierrez, L. (2017). Impacts of El Niño-Southern Oscillation on the wheat market: A global dynamic analysis. PLoS One, 12(6), e0179086.
Abstract: Although the widespread influence of the El Niño-Southern Oscillation (ENSO) occurrences on crop yields of the main agricultural commodities is well known, the global socio-economic consequences of ENSO still remain uncertain. Given the global importance of wheat for global consumption by providing 20% of global calories and nourishment, the monitoring and prediction of ENSO-induced variations in the worldwide wheat market are essential for allowing national governments to manage the associated risks and to ensure the supplies of wheat for consumers, including the underprivileged. To this end, we propose a global dynamic model for the analysis of ENSO impacts on wheat yield anomalies, export prices, exports and stock-to-use ratios. Our framework focuses on seven countries/regions: the six main wheat-exporting countries-the United States, Argentina, Australia, Canada, the EU, and the group of the main Black Sea export countries, i.e. Russia, Ukraine, and Kazakhstan-plus the rest of the world. The study shows that La Niña exerts, on average, a stronger and negative impact on wheat yield anomalies, exports and stock-to-use ratios than El Niño. In contrast, wheat export prices are positively related to La Niña occurrences evidencing, once again, its steady impact in both the short and long run. Our findings emphasize the importance of the two ENSO extreme phases for the worldwide wheat market.
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Barber, H. M., Lukac, M., Simmonds, J., Semenov, M. A., & Gooding, M. J. (2017). Temporally and Genetically Discrete Periods of Wheat Sensitivity to High Temperature. Front. Plant Sci, 8, 51.
Abstract: Successive single day transfers of pot-grown wheat to high temperature (35/30°C day/night) replicated controlled environments, from the second node detectable to the milky-ripe growth stages, provides the strongest available evidence that the fertility of wheat can be highly vulnerable to heat stress during two discrete peak periods of susceptibility: early booting [decimal growth stage (GS) 41-45] and early anthesis (GS 61-65). A double Gaussian fitted simultaneously to grain number and weight data from two contrasting elite lines (Renesansa, listed in Serbia, Ppd-D1a, Rht8; Savannah, listed in UK, Ppd-D1b, Rht-D1b) identified peak periods of main stem susceptibility centered on 3 (s.e. = 0.82) and 18 (s.e. = 0.55) days (mean daily temperature = 14.3°C) pre-GS 65 for both cultivars. Severity of effect depended on genotype, growth stage and their interaction: grain set relative to that achieved at 20/15°C dropped below 80% for Savannah at booting and Renesansa at anthesis. Savannah was relatively tolerant to heat stress at anthesis. A further experiment including 62 lines of the mapping, doubled-haploid progeny of Renesansa × Savannah found tolerance at anthesis to be associated with Ppd-D1b, Rht-D1b, and a QTL from Renesansa on chromosome 2A. None of the relevant markers were associated with tolerance during booting. Rht8 was never associated with heat stress tolerance, a lack of effect confirmed in a further experiment where Rht8 was included in a comparison of near isogenic lines in a cv. Paragon background. Some compensatory increases in mean grain weight were observed, but only when stress was applied during booting and only where Ppd-D1a was absent.
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Leolini, L., Moriondo, M., Ferrise, R., & Bindi, M. (2017). Relations between micrometeorological conditions and plant physiology (Vol. 10).
Abstract: The changing climate and environmental conditions play a key role on plant physiology. In this context, crop simulation models represent a useful tool for investigating the main plant processes and provide a reliable estimation of crop productivity and quality. However, the most common crop models showed many limitations, with particular concern on the effect of some meteorological variables on plant processes during sensitive stages of development. Improving models by implementing the effect of such variables on crop processes may help to improve the accuracy of models, thus their usefulness. Here we focus on the analysis of the effect of high and low temperatures during flowering in grapevine. To this, the fruit-set index, developed for taking into account for the effect of temperature on setting the number of berries per cluster and the fruit-set percentage, was applied in a preliminary explorative study to assess the impact of different conditions during flowering at European scales. The sensitivity of the index allowed to identify the differential impact of temperature around flowering in different environment and for different varieties. Once meteorological variables are available at field or sub-field scale, the index can be used to provide information about the spatial variability of crop growth, thus allowing to identify the most appropriate interventions to improve productivity.
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