An integrated assessment approach to conduct analyses of climate change impacts on whole-farm systems

Abstract

This paper argues that an integrated assessment approach, combining simulation modelling with deliberative processes involving decision makers and other stakeholders, has the potential to generate credible and relevant assessments of climate change impacts on farming-systems. The justification for the approach proposed is that while simulation modelling provides an effective way of exploring the range of possible impacts of climate change and a means of testing the consequences of possible management or policy interventions, the interpretation of the outputs is highly dependent on the point of view of the stakeholder. Inevitably, whatever the responses to climate change, there will be trade-offs between the benefits and costs to a range of stakeholders. The use of a deliberative process that includes stakeholders, both in defining the topics addressed and in debating the interpretations of the outcomes, addresses many of the limitations that have been previously identified in the use of computer-based tools for agricultural decision support. The paper further argues that the concepts of resilience and adaptive capacity are useful for the assessment of climate change impacts as they provide an underpinning theory for processes of change in land use systems. The integrated modelling framework (IMF) developed for the simulation of whole-farm systems is detailed, including components for crop and soil processes, livestock systems and a tool for scheduling of resource use within management plans. The use of the IMF for assessing climate change impacts is then outlined to demonstrate the range of analyses possible. The paper concludes with a critique of the IA approach and notes that issues of quantification and communication of uncertainty are central to the success of the methodology.

Farming system design to feed the changing world. A review

“…One noticeable difference with optimisation approaches is that the reviewed articles (Pfister et al 2005;van Wijk et al 2009) pointed to the need to improve our understanding of current farming systems to seek for relevant solutions to their problems. For instance, it was felt necessary to characterize the impact of climate change on farming systems before tackling the identification of possible adaptation strategies (Rivington et al 2007;Martin et al 2011a).…”

“…Two reasons explain this loose formulation of the design problem. First, few approaches (Rivington et al 2007) addressed design problems considering long term horizon. In such cases, in line with Schön's theory, uncertainty about the problem situation is high.…”

“…The mechanistic computer models used for problem situation analysis simulated dynamically crop and grassland production at the field scale on a daily time step and over a single production cycle (Martin et al 2011a;Rivington et al 2007). The single environmental factor considered was weather, to characterize the local impact of climate change on crops and grasslands.…”

“…This position follows Schön's point of view, as the invitation for stakeholders' participation indicates that researchers consider they do not have adequate descriptions of the problem, of perceived solutions and goals and of the promising farming systems reachable from the current farming systems. In addition, computer models were used at this stage in a few of the reviewed approaches (Martin et al 2011a;Rivington et al 2007). They enabled problem situation analysis to characterize the exposure and vulnerability of farming systems to climate change.…”

An open platform to assess vulnerabilities to climate change: An application to agricultural systems

“…Providing simulation modeling tools to accommodate biophysical outputs and supporting utilities for data gap-filling, downscaling/upscaling applications and computation of vulnerability indices, the platform integrates and automates procedures usually employed in isolation and performs model-based inference of agro-ecological systems vulnerability to a variety of climate forcing scenarios. Approaches of this type can support deliberative process in climate change studies (e.g., Bellocchi et al, 2015;Rivington et al, 2007) to provide information to stakeholders (land managers and decision makers) about vulnerability to climate change and generate dialogue around its interpretation. With synthetic indices, in particular, there is the trade-off between the level of detail provided by climate and impact models under sets of conditions and timeliness for decision-making.…”