Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

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Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

Rice (Oryza sativa L.) systems rotated with perennial pastures have intensified in South America to increase annual grain productivity, but the effects on rice yield and soil quality remain poorly understood. We evaluated rice grain yield, crop and pasture biomass production, and soil organic carbon (SOC) and total nitrogen stocks (0-15-cm depth) in three rice-based rotations over 8 yr in Uruguay. Treatments were: (a) rice-pasture [a 5 yr rotation of rice-ryegrass (Lolium multiflorum Lam.)-rice, then 3.5 yr of a perennial mixture of tall fescue (Festuca arundinacea Schreb.), white clover (Trifolium repens L.), and birdsfoot trefoil (Lotus corniculatus L.)], (b) rice-soybean [a 2-yr rotation of rice-ryegrass-soybean (Glycine max [L.] Merr.)-Egyptian clover (Trifolium alexandrinum L.)], and (c) rice-cover crop (an annual rotation of rice-Egyptian clover). Rice after soybean or pasture achieved the highest yield (9.8 Mg ha -1 ), 9% higher than rice after rice in the rice-pasture and rice-cover crop systems. Estimated belowground biomass under rice-pasture (2.7 Mg ha -1 ) was 12 and 42% greater than under rice-cover crop and rice-soybean rotations, respectively. Rice-pasture showed an increase of 0.6 Mg ha -1 yr -1 of SOC; no changes were observed in the intensified rotations replacing pasture with additional rice or soybean. All systems sustained soil total N. These results provide insights for implementing sustainable rice-based rotations, with rice-pasture being the only system that increased SOC while achieving high rice yields and belowground biomass productivity.