Impact assessment toolbox of resilience‐enhancing strategies on farming systems

One of the aims of SURE-Farm is to analyse the integrated impact of resilience enhancing strategies and actions on European farming systems. More specifically, it aims to assess how the essential functions of farming systems react to challenges from the environment in terms of resilience. The analysis aims to explore farming systems at different times and conceptual scales, using statics and dynamic perspectives for a) describing the current state of a system, b) outlining its potential developments and c) exploring relationships between resilience and the broader system’s characteristics (resilience attributes).

To achieve this objective, SURE-Farm has put together existing models (static and dynamic, quantitative and qualitative) into an integrated toolbox and uses them for the assessment of resilience. The reasons for using an integrated toolbox instead of a single model are: first, the multi‐scale and multi‐level nature of resilience means that assessing different dimensions and levels of the systems’ resilience with a single tool is complex and complicated; second, there is a large variety of case studies in SURE‐Farm and they differ in terms of farming systems, data availability and model expertise of the local partners, therefore building one flexible model is very difficult.

A number of modelling tools were selected on the basis of their relevance for the assessment of resilience, applicability to the case studies in the project and the experience that project partners have in applying them. The models used include system dynamic models, the agent‐based model of farm structural change AgriPoliS, the Farming System SIMulator (FSSIM), statistical modelling, a stochastic model, a spatially explicit model to assess ecosystem services, and a Framework for Participatory Impact Assessment (FoPIA).

The models use a wide range of inputs, which are fed, with the exception of FoPIA, into mathematical equations. Each model uses different algorithmic methods to estimate optimal states of the system (e.g. FSSIM and the ecosystem services model), structural changes in the system (e.g. AgriPoliS and System Dynamics) or risk (stochastic model).

Since the models have been built separately and for different purposes, each of them produces different outputs and provides different insights about the essential functions of the farming system under study. However, using them together provides a holistic assessment of the farming system under study by producing different economic, social and environmental indicators associated with the different essential functions of the farming system.

Combinations of these different models/approaches included in the toolbox were applied in the SURE-Farm case study regions to assess current and future (scenario analysis) impacts of resilience strategies/actions on farming systems. Additionally, they were applied to identify resilience attributes and strategies which contribute to the robustness, adaptability and transformability of the farming systems.

D5.1 Report on IA tool to assess the resilience of farming systems and their delivery of private and public goods (Protocol)
D5.2 Participatory impact assessment of sustainability and resilience of EU farming systems
D5.3 Resilience assessment of current farming systems across the European Union:
D5.5 Impacts of future scenarios on the resilience of farming systems across the EU assessed with quantitative and qualitative methods
D5.6 Impacts of improved strategies and policy options on the resilience of farming systems across the EU
Relevance for monitoring and evaluation of the CAP

The SURE-Farm integrated toolbox is useful for impact evaluations, notably of the resilience of farming systems. This is not only very relevant for the CAP Specific Objective 1, which focuses on economic resilience, but the SURE-Farm toolbox also allows for the assessment of a farms' numerous functions that encompass economic, environmental and the quality of life dimensions of the CAP Specific Objectives.

This diversity among models, their calculation approaches and their outputs are the main strength of the SURE‐Farm integrated toolbox because it enables the analysis of the farming systems and their resilience from different perspectives.

In the integrated toolbox, each model uses different analytical lenses to assess each particular function. For instance, FSSIM and the Ecosystem Services Model use mathematical optimisation to assess impacts of changes in policy, technology, climate on farming systems, while System Dynamics uses systems thinking to examine changes and evolution over time. The aggregation used in each model is also different. For example, AgriPoliS assesses individual farms and their individual interactions. At the same time, System Dynamics aggregates farms into big groups and focuses on the aggregated dynamics between the different groups and their environment. (Table 3 of Deliverable 5.1 offers a general description of the models in the integrated toolbox).

By using an integrated toolbox rather than a single model, one can get more benefits resulting from different modelling approaches without having to integrate all of the models into one single interconnected modelling system.

The outputs of the models and assessment of the resilience indicators were used on the SURE-Farm case studies to study the relationships between resilience attributes and the resilience indicators. Causal relationships, statistical correlations and stakeholders’ inputs were also used to identify key attributes shaping the identity of farming systems and contributing to specific resilience indicators.

Knowledge of the different tools, including strong mathematical and econometric skills is required for using the toolbox.

Last modification date: 
09/12/2021