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Van Oijen, M. (2015). Methods for risk analysis and spatial upscaling of process-based models: Experiences from projects Carbo-Extreme and GREENHOUSE (Vol. 5).
Abstract: In the recently finished EU-funded project Carbo-Extreme, we developed a simple probabilistic method for quantifying vulnerabilities and risks to ecosystems (http://iopscience.iop.org/1748-9326/8/1/015032). The method defines risk as expected loss due to environmental hazards, and shows how such risk can be calculated as the product of ecosystem vulnerability and hazard probability. The method was used with six different vegetation models to estimate current and future drought risks for crops, grasslands and forests across Europe (http://www.biogeosciences.net/11/6357/2014/bg-11-6357-2014.html).In the still ongoing UK-funded project GREENHOUSE, the focus is on spatial upscaling of local measurements and model predictions of greenhouse gas emissions to wider regions. As part of this work, we are comparing different model upscaling methods – ranging from naive input aggregation to geostatistics – and quantify the uncertainties associated with the upscaling. This work builds on an earlier inventory of model upscaling methods that was produced in a collaboration of CEH-Edinburgh and the University of Bonn (https://www.stat.aau.at/Tagungen/statgis/2009/StatGIS2009Van%20Oijen1.pdf). Here we show a comparison of the methods using model predictions for the border region of England and Scotland. No Label
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Topp, C. (2015). Pesticide management in Scottish spring barley – insights from sowing dates (Vol. 5).
Abstract: Better management of pesticides is a potentially important strategy for reducing environmental impact while maintaining yields. Pesticide use is influenced by several drivers, including sowing date, which can directly impact disease burden. Analysis of sowing dates for spring barley was the first stage of this project, which aims to provide insight into areas of farm management which can be optimised to reduce environmental impact. Sowing dates were taken from the Adopt a Crop database, which contains data from 1983 onwards for commercial farms across Scotland. Work was carried out at three levels: national, to provide an overall picture of historical patterns; regional, to highlight differences within Scotland; and case study, to determine whether the national trend was visible in a single region. A general trend towards later sowing of spring barley in Scotland is visible – yet, this pattern is less pronounced in certain regions. Future work must therefore consider what factors have lead to this shift, to more fully understand interactions between sowing date and the environment. No Label
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Topp, K. (2015). Synergies and trade-offs of adaptation and mitigation on dairy farms (Vol. 5).
Abstract: Livestock farms with ruminants have large and diverse fluxes of greenhouse gases, but are also affected in diverse ways by climate change. This calls for assessments of possible options to mitigate GHG and to adapt to changing climate, primarily at the farm-scale. This study focuses on the effects of adaptation and mitigation options, and their synergies and trade-offs on GHG emissions and production on European dairy farms. The impact of climate change on livestock production systems will vary with livestock type, system design and local conditions. These effects are direct through impacts on animal performance and indirect through effects on crop yield and quality. These impacts demand adaptations of farming systems to cope with the changed climate. Adaptation can be categorized in three main categories: feed, livestock and water management. Several of these adaptation options have impact on greenhouse gas emissions and thus on the mitigation potential. There is therefore need to align measures for reducing greenhouse gas emissions with the likely adaptations to be adopted. Based on expert opinion, assessments have been performed on which adaptation and mitigation measures would likely be adopted for real on maritime dairy farms located in Ireland and the Netherlands. No Label
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Tantari, A. (2015). The role of CAP direct payment in the support and stabilisation of farm income: empirical evidences from a constant sample of Italian farms (Vol. 5).
Abstract: The main objective of CAP Direct payments (DP) has been to increase and stabilise farm income together with a large number of additional goals (Gardner, 1991). Despite its importance, there are limited empirical evidences on farm income variability over time at farm level apart Vrolijk and Poppe (2008) and Vrolijk, de Bont, van der Veen, and Poppe (2009). The analysis focuses of the following research questions:• What is the amount of the support provided by DP? How the income of Italian farms will be affected by reductions of DP levels?• What is the extent of farm income variability over time? Is it the same in all types of farms?• Where is this variability coming from?• Do CAP direct payments reduce farm income variability? How do DP affect it? Are DP targeted to stabilise the income of those farms facing larger income variability? The analysis has been developed on the individual farms belonging to the whole Italian sample of the EU FADN farms during all years of the decade 2003-2012. The variability of farm income (FI) is assessed by calculating variance and Coefficient of Variation (CV) over the 10 year period for each farm for each relevant income component. The role of DP on income stabilisation is assessed by means of variance decomposition by income sources (Burt and Finley, 1968; El Benni and Finger, 2013; Mishra and El-Osta, 2001).The presence of DP allows for a reduction of the variability of farm income: the variability of FI when DP are not accounted for is higher than that of the whole FI. Finally, DP seem to be not targeted to those farms facing the highest level of market income variability. These results support the hypothesis that there is a potentially large room for better design the DP policy to reduce income variability. No Label
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Sinabell, F. (2015). Climate change and policy impacts on protein crop production: a case study on integrated modeling (Vol. 5).
Abstract: This paper addresses protein crop production in Europe. European food and feed industries highly depend on imported protein crops and derived products and climate change is likely to affect domestic protein crop production and thus the import dependency. The recent reform of EU agricultural policy reform aims at promoting climate friendly agricultural practices and stimulating the production of protein crops. We choose three contrasting climate change scenarios as well as specifications of the recent CAP reform in order to investigate how farmers might adapt to changing land use restrictions and climate conditions. Output response, land allocation and nitrogen use are the main variables of interest. Exemplified for Austrian cropland, we apply an integrated modeling framework consisting of a statistical climate change model, a crop rotation model, the bio-physical process model EPIC, and the economic bottom-up land use optimization model BiomAT. This model maximizes total gross margins by optimizing for land use and crop management practices for different scenarios of climate change and market conditions. Results obtained at a 1 km grid are aggregated to the national level. The model results indicate that changes in policy conditions, cropland use, and flexibility in crop management practices may have stronger effects on total protein crop production than climate change in the next decades. An expansion of current protein crop production leads to an increase in marginal opportunity costs, reduces mineral fertilizer input demand, and mainly replaces maize in the crop rotations. No Label
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