Zimmermann, A., & Britz, W. (2016). European farms’ participation in agri-environmental measures. Land Use Policy, 50, 214–228.
Abstract: Due to their diversity and voluntariness, agri-environmental measures (AEMs) are among the Common Agricultural Policy instruments that are most difficult to assess. We provide an EU-wide analysis of AEM adoption and farm’s total AEM support over total Utilised Agricultural Area using a Heckman sample selection approach and single farm data. Our analysis covers 22 Member States over the 2000-2009 period, assesses the entire portfolio of AEMs and focuses on the relationship between AEM participation and farming system. Results show that participation in AEMs is more likely in less intensive production systems, where, however, per committed hectare AEM premiums tend to be lower. Member States group into three categories: high/low intensity farming systems with low/high AEM enrollment rates, respectively, and large high diversity countries with medium AEM enrollment rates. (C) 2015 Elsevier Ltd. All rights reserved.
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Mitter, H., Heumesser, C., & Schmid, E. (2015). Spatial modeling of robust crop production portfolios to assess agricultural vulnerability and adaptation to climate change. Land Use Policy, 46, 75–90.
Abstract: Agricultural vulnerability to climate change is likely to vary considerably between agro-environmental regions. Exemplified on Austrian cropland, we aim at (i) quantifying climate change impacts on agricultural vulnerability which is approximated by the indicators crop yields and gross margins, (ii) developing robust crop production portfolios for adaptation, and (iii) analyzing the effect of agricultural policies and risk aversion on the choice of crop production portfolios. We have employed a spatially explicit, integrated framework to assess agricultural vulnerability and adaptation. It combines a statistical climate change model for Austria and the period 2010-2040, a crop rotation model, the bio-physical process model EPIC (Environmental Policy Integrated Climate), and a portfolio optimization model. We find that under climate change, crop production portfolios include higher shares of intensive crop management practices, increasing average crop yields by 2-15% and expected gross margins by 3-18%, respectively. The results depend on the choice of adaptation measures and on the level of risk aversion and vary by region. In the semi-arid eastern parts of Austria, average dry matter crop yields are lower but gross margins are higher than in western Austria due to bio-physical and agronomic heterogeneities. An abolishment of decoupled farm payments and a threefold increase in agri-environmental premiums would reduce nitrogen inputs by 23-33%, but also crop yields and gross margins by 18-37%, on average. From a policy perspective, a twofold increase in agri-environmental premiums could effectively reduce the trade-offs between crop production and environmental impacts. (C) 2015 Elsevier Ltd. All rights reserved.
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Ewert, F., Rötter, R. P., Bindi, M., Webber, H., Trnka, M., Kersebaum, K. C., et al. (2015). Crop modelling for integrated assessment of risk to food production from climate change. Env. Model. Softw., 72, 287–303.
Abstract: The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches.
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