How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

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(sup 1) per degC. Doubling [CO2] from 360 to 720 lmol 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

How do various maize crop models vary in their responses to climate change factors?

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 lmol 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

How do various maize crop models vary in their responses to climate change factors?

Comments This article is a U.S. government work, and is not subject to copyright in the United States. Abstract 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 lmol 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

Consequences of national food system transitions in Ethiopia for ending hunger and achieving healthy diets

Countries have committed themselves to achieve Sustainable Development Goals, such as Zero Hunger (SDG2), and Life on Land (SDG15). Many countries are still far from reaching the targets as expressed in these goals. To help steer these developments, the necessary transitions in the food system of a country for achieving healthy and affordable diets for all people need to identified, while minimizing negative environmental impacts. The transition to healthy diets means a change in the demand for and consumption of various agricultural commodities. This change in demand will drive price changes, both for consumers and at the farm gate. This affects agricultural incomes, domestic food production and patterns of trade. Changes in domestic food production will in turn alter land use patterns, fertilizer use and other agricultural inputs which have environmental consequences with respect to land demand for agriculture, nutrient emissions, greenhouse gas emissions and irrigation water demand. In this study we investigate a number of aspects of this challenge by linking a biophysical (BIOSPCAS) and an economic (MAGNET) model, and simulating consequences of a transition to a healthy diet in Ethiopia in 2030. The impacts of economic and environmental consequences of a transition to a healthy diet in Ethiopia are compared with the SSP2 (O’Neill et al. 2017) business as usual future projections of the Ethiopian economy and agricultural system in 2030 with the current patterns of consumption, to illustrate the differences and highlight the impacts of the transition. Further as domestic food prices are linked to the global marketplace for agricultural commodities, we explore a scenario where the rest world makes the transition to a healthy diet as well. This global transition will affect the demand for Ethiopian exports and the prices for imports facing farmers and consumers

Consequences of national food system transitions in Ethiopia for ending hunger and achieving healthy diets

Countries have committed themselves to achieve Sustainable Development Goals, such as Zero Hunger (SDG2), and Life on Land (SDG15). Many countries are still far from reaching the targets as expressed in these goals. To help steer these developments, the necessary transitions in the food system of a country for achieving healthy and affordable diets for all people need to identified, while minimizing negative environmental impacts. The transition to healthy diets means a change in the demand for and consumption of various agricultural commodities. This change in demand will drive price changes, both for consumers and at the farm gate. This affects agricultural incomes, domestic food production and patterns of trade. Changes in domestic food production will in turn alter land use patterns, fertilizer use and other agricultural inputs which have environmental consequences with respect to land demand for agriculture, nutrient emissions, greenhouse gas emissions and irrigation water demand. In this study we investigate a number of aspects of this challenge by linking a biophysical (BIOSPCAS) and an economic (MAGNET) model, and simulating consequences of a transition to a healthy diet in Ethiopia in 2030. The impacts of economic and environmental consequences of a transition to a healthy diet in Ethiopia are compared with the SSP2 (O’Neill et al. 2017) business as usual future projections of the Ethiopian economy and agricultural system in 2030 with the current patterns of consumption, to illustrate the differences and highlight the impacts of the transition. Further as domestic food prices are linked to the global marketplace for agricultural commodities, we explore a scenario where the rest world makes the transition to a healthy diet as well. This global transition will affect the demand for Ethiopian exports and the prices for imports facing farmers and consumers

Can large-scale biofuels production be sustainable by 2020?

Worldwide, many nations impose blending of their transport fuels with biofuels, approximating 10% globally by 2020, to contribute to energy security while reducing emission of green house gasses (GHG). Food riots, scientific insights that question the GHG benefits and raised concern about the loss of biodiversity, have lead to the formulation by various governments of sustainability criteria for biofuels to comply with. In this paper, we assess this conditionality and argue that large-scale biofuels production will be unable to comply with these criteria in 2020, and can therefore not be qualified as sustainable.Radiation use efficiency GHG emissions Land use change Development Food security

Trends in global vegetation activity and climatic drivers indicate a decoupled response to climate change

Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982-2010) derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty in trend estimates. Annual total biomass weight (TBW) was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR) with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS-NPP) and TBWper biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land, and for 5% a negative trend. A decoupled trend, indicating positive TBWtrends and monotonic negative or segmented and negative NDVI trends, was observed for 17-36% of all productive areas depending on the NDVI metric used. For only 1-2% of all pixels in productive areas, a diverging and greening trend was found despite a strong negative trend in TBW. The choice of NDVI metric used strongly affected outcomes on regional scales and differences in the fraction of explained variation in MODIS-NPP between biomes were large, and a combination of NDVI metrics is recommended for global studies. We have found an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO2 sequestration capacity

Trends in global vegetation activity and climatic drivers indicate a decoupled response to climate change

Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982-2010) derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty in trend estimates. Annual total biomass weight (TBW) was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR) with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS-NPP) and TBWper biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land, and for 5% a negative trend. A decoupled trend, indicating positive TBWtrends and monotonic negative or segmented and negative NDVI trends, was observed for 17-36% of all productive areas depending on the NDVI metric used. For only 1-2% of all pixels in productive areas, a diverging and greening trend was found despite a strong negative trend in TBW. The choice of NDVI metric used strongly affected outcomes on regional scales and differences in the fraction of explained variation in MODIS-NPP between biomes were large, and a combination of NDVI metrics is recommended for global studies. We have found an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO2 sequestration capacity.</p

Comparing biobased products from oil crops versus sugar crops with regard to non-renewable energy use, GHG emissions and land use

Non-renewable energy use, greenhouse gas emissions and land use of two biobased products and biofuelfrom oil crops is investigated and compared with products from sugar crops. In a bio-based economychemicals, materials and energy carriers will be produced from biomass. Next to side streams, also veg-etable oils and sugars are expected to become important resources for these products. Application ofthese resources calls for effective resource use, with minimal environmental impacts. In this paper westudy a number of available options and their trade-offs. Use of vegetable oils in a chemical and a resinresults in a higher reduction of non- renewable energy use and greenhouse gas emissions than their useas biodiesel. Furthermore, similar savings in environmental impact per unit of land can be reached byproducts from either oil or sugar crops as transportation fuel, but the sugar crops, applied in chemicalsor bioplastics outcompete the oil crops