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Rosenzweig, Cynthia E.

Publications and source records attributed to Rosenzweig, Cynthia E..

Chapter 5: Food Security

The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people. Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability).

Mbow, Cheikh↗

Towards a New Food System Assessment: AgMIP Coordinated Global and Regional Assessments of Climate Change

Agricultural stakeholders need more credible information on which to base adaptation and mitigation policy decisions. In order to provide this, we must improve the rigor of agricultural modelling. Ensemble approaches can be used to address scale issues and integrated teams can overcome disciplinary silos. The AgMIP Coordinated Global and Regional Assessments of Climate Change and Food Security (CGRA) has the goal to link agricultural systems models using common protocols and scenarios to significantly improve understanding of climate effects on crops, livestock and livelihoods across multiple scales. The AgMIP CGRA assessment brings together experts in climate, crop, livestock, economics, and food security to develop Protocols to guide the process throughout the assessment. Scenarios are designed to consistently combine elements of intertwined storylines of future society including, socioeconomic development, greenhouse gas concentrations, and specific pathways of agricultural sector development. Through these approaches, AgMIP partners around the world are providing an evidence base for their stakeholders as they make decisions and investments.

Ensembles↗

Integrating Water Supply Constraints into Irrigated Agricultural Simulations of California

Simulations of irrigated croplands generally lack key interactions between water demand from plants and water supply from irrigation systems. We coupled the Water Evaluation and Planning system (WEAP) and Decision Support System for Agrotechnology Transfer (DSSAT) to link regional water supplies and management with field-level water demand and crop growth. WEAP-DSSAT was deployed and evaluated over Yolo County in California for corn, rice, and wheat. WEAP-DSSAT is able to reproduce the results of DSSAT under well-watered conditions and reasonably simulate observed mean yields, but has difficulty capturing yield interannual variability. Constraining irrigation supply to surface water alone reduces yields for all three crops during the 1987-1992 drought. Corn yields are reduced proportionally with water allocation, rice yield reductions are more binary based on sufficient water for flooding, and wheat yields are least sensitive to irrigation constraints as winter wheat is grown during the wet season.

Agriculture; Irrigation; Water Resources Managemen↗

How Accurately Do Maize Crop Models Simulate the Interactions of Atmospheric CO2 Concentration Levels With Limited Water Supply on Water Use and Yield?

This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration [CO2] on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thunen Institute in Braunschweig, Germany (Manderscheid et al. 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50 percent of models within a range of plus/minus 1 Mg ha(exp. -1) around the mean. The bias of the median of the 21 models was less than 1 Mg ha(exp. -1). However under water deficit in one of the two years, the models captured only 30 percent of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase.

grain number↗

Uncertainty of Wheat Water Use: Simulated Patterns and Sensitivity to Temperature and CO2

Projected global warming and population growth will reduce future water availability for agriculture. Thus, it is essential to increase the efficiency in using water to ensure crop productivity. Quantifying crop water use (WU; i.e. actual evapotranspiration) is a critical step towards this goal. Here, sixteen wheat simulation models were used to quantify sources of model uncertainty and to estimate the relative changes and variability between models for simulated WU, water use efficiency (WUE, WU per unit of grain dry mass produced), transpiration efficiency (Teff, transpiration per kg of unit of grain yield dry mass produced), grain yield, crop transpiration and soil evaporation at increased temperatures and elevated atmospheric carbon dioxide concentrations ([CO2]). The greatest uncertainty in simulating water use, potential evapotranspiration, crop transpiration and soil evaporation was due to differences in how crop transpiration was modelled and accounted for 50 of the total variability among models. The simulation results for the sensitivity to temperature indicated that crop WU will decline with increasing temperature due to reduced growing seasons. The uncertainties in simulated crop WU, and in particularly due to uncertainties in simulating crop transpiration, were greater under conditions of increased temperatures and with high temperatures in combination with elevated atmospheric [CO2] concentrations. Hence the simulation of crop WU, and in particularly crop transpiration under higher temperature, needs to be improved and evaluated with field measurements before models can be used to simulate climate change impacts on future crop water demand.

Sensitivity↗

Next Generation Agricultural System Data, Models and Knowledge Products: Introduction

Agricultural system models have become important tools to provide predictive and assessment capability to a growing array of decision-makers in the private and public sectors. Despite ongoing research and model improvements, many of the agricultural models today are direct descendants of research investments initially made 30-40 years ago, and many of the major advances in data, information and communication technology (ICT) of the past decade have not been fully exploited. The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. The Special Issue is based on a 'NextGen' study led by the Agricultural Model Intercomparison and Improvement Project (AgMIP) with support from the Bill and Melinda Gates Foundation.

Next generation↗

Assessing Impacts of Climate Change on Food Security Worldwide

The combination of a warming Earth and an increasing population will likely strain the world's food systems in the coming decades. Experts involved with the Agricultural Model Intercomparison and Improvement Project (AgMIP) focus on quantifying the changes through time. AgMIP, a program begun in 2010, involves about 800 climate scientists, economists, nutritionists, information technology specialists, and crop and livestock experts. In mid-September 2015, the Aspen Global Change Institute convened an AgMIP workshop to draft plans and protocols for assessing global- and regional-scale modeling of crops, livestock, economics, and nutrition across major agricultural regions worldwide. The goal of this Coordinated Global and Regional Integrated Assessments (CGRA) project is to characterize climate effects on large- and small-scale farming systems.

farm crops↗

Conclusion: Major Findings and Future Activities.

The Agricultural Model Intercomparison and Improvement Project (AgMIP) incorporates a number of major advances in the way that climate impacts, vulnerability, and adaptation are being simulated. At its core is a protocol approach that results in impact assessments being more scientifically credible and thus ultimately having greater value to the wide range of agricultural stakeholders. Moreover, the use of the protocol approach enables closer scrutiny and intercomparison of models and methods so that they can be improved over time. By creating a truly trans-disciplinary, systems-based approach, AgMIP impact assessments and evaluation of adaptations become useful to agricultural decision-makers at multiple scales. The chapters in this two-part set demonstrate the use of this approach and represent early steps towards the full realization of these new methods and their application.

damage assessment↗

Guide for Regional Integrated Assessments: Handbook of Methods and Procedures, Version 5.1

The purpose of this handbook is to describe recommended methods for a trans-disciplinary, systems-based approach for regional-scale (local to national scale) integrated assessment of agricultural systems under future climate, bio-physical and socio-economic conditions. An earlier version of this Handbook was developed and used by several AgMIP Regional Research Teams (RRTs) in Sub-Saharan Africa (SSA) and South Asia (SA)(AgMIP handbook version 4.2, www.agmip.org/regional-integrated-assessments-handbook/). In contrast to the earlier version, which was written specifically to guide a consistent set of integrated assessments across SSA and SA, this version is intended to be more generic such that the methods can be applied to any region globally. These assessments are the regional manifestation of research activities described by AgMIP in its online protocols document (available at www.agmip.org). AgMIP Protocols were created to guide climate, crop modeling, economics, and information technology components of its projects.

protocol (computers)↗

Assessing Agricultural Risks of Climate Change in the 21st Century in a Global Gridded Crop Model Intercomparison

Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

agriculture↗

AgMIP Regional Activities in a Global Framework: The Brazil Experience

Climate variability and change are projected to increate the frequency of extreme high-temperature events, floods, and droughts, which can lead to subsequent changes in soil moister in many locations (Alexandrov and Hoogenboom, 2000). In Brazil, observations reveal a tendency for increasing frequency of extreme rainfall events particularly in south Brazil (Alexander et al., 2006; Carvalho et al., 2014; Groissman et al., 2005), as well as projections for increasing extremes in both maximum and minimum temperatures and high spatial variability for rainfall under the IPCC SRES A2 and B2 scenarios (Marengo et al., 2009).

climate change↗

A global data set of soil particle size properties

A standardized global data set of soil horizon thicknesses and textures (particle size distributions) was compiled. This data set will be used by the improved ground hydrology parameterization designed for the Goddard Institute for Space Studies General Circulation Model (GISS GCM) Model 3. The data set specifies the top and bottom depths and the percent abundance of sand, silt, and clay of individual soil horizons in each of the 106 soil types cataloged for nine continental divisions. When combined with the World Soil Data File, the result is a global data set of variations in physical properties throughout the soil profile. These properties are important in the determination of water storage in individual soil horizons and exchange of water with the lower atmosphere. The incorporation of this data set into the GISS GCM should improve model performance by including more realistic variability in land-surface properties.

Webb, Robert S.↗