Step 1. Climate Region
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Step 2. Baseline System
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Step 3. Climate Impact Driver
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Resilient Land Use
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In the face of future climate challenges, it is of the utmost importance to drive the transition towards more resilient and efficient land use in Europe. Agroecological approaches such as agroforestry and integrated crop and livestock systems (also called mixed farming) have been recognized as “highly effective adaptation options that enhance resilience to climate change” (IPCC, 2022). But can we target the areas where such systems should be established? And what kind of systems should be established according to the farms’s environment, and what are the particular characteristics or mechanisms of these agroecological systems that enhance their resilience, compared with conventional systems?
The LUCIM - Land Use Change Interactive Map - tries to bring these two components together. The first part explores a spatial approach to identify target areas in Europe where resilient and climate-smart agroforestry and mixed farming systems should have high priority for introduction considering existing environmental pressures and socio-economic contexts. The second part establishes a guided cascade of context settings and suggests future scenarios of land use/resilience strategies where different models of land use change can be evaluated as pathways towards increased resilience to climate change.
Farmers and Land managers
Provides inspiration on the resilience path they could take by 1) contextualising their region into climate and environmental risks where an agroforestry approach could be implemented and then 2) identifying a range of agroforestry and mixed farming systems that could increase resilience to climate change, illustrated with existing peer examples from across Europe.
Policy makers
Outcomes of the spatial modelling and land use change pathway development could be used to inform policy development to support the uptake of AF in priority areas while addressing potential social and economic factors that may be barriers to, or conversely, opportunities for implementation.
Interactive maps that explore environmental and climate change pressures across Europe to identify target areas for agroforestry and mixed systems, while also considering the socio-economic context in which the transition of land use needs to occur.
Susanne Schnabel, J. Francisco Lavado Contador, Anthony Gabourel Landaverde - University of Extremadura / INTERRA
The aim of this research was to define target areas where the introduction of mixed farming or agroforestry would provide environmental benefits and also be more resilient to climate change. The selection of these target areas was based on a spatial approach which consists of four steps: (1) selection of suitable potential areas from the total agricultural area in Europe, excluding nature conservation sites and MF/AF areas identified in the land use/land cover cartography, (2) analysis of environmental risks in the potential areas, (3) definition of target areas, and (4) analysis of the socio-economic context. The output of this work is a series of maps illustrating the environmental and climate change pressures to highlight the target areas for agroforestry and mixed farming, and maps describing the socio-economic context of the regions.
Step by step guide through a land use change journey to increase resilience to climate change, by transitioning from a baseline agricultural or forestry system towards more agroecological land use models.
Jo Smith, Ana Tomás and João Palma - Moinhos de Vento Agroecology Research Centre
Agroforestry and Mixed Farming systems are not 'one size fits all' approaches, and a better understanding of the particular characteristics, properties and potential trade-offs of these diverse land use models is needed to provide policy makers, land managers and farmers with the tools they need to make informed decisions regarding a transition towards a more resilient agricultural system for Europe. The aim of this research was to identify which specific land use models increased resilience to which specific climate impact drivers in different regions of Europe, and to identify the key factors driving this higher resilience. As there are significant research and evidence gaps in knowledge concerning the resilience of mixed farming and agroforestry land use models to climate change, an iterative expert knowledge-based approach called the Delphi method was used to bridge knowledge gaps. Delphi is an effective method of facilitating a group of individuals as a whole to deal with a complex problem and reach consensus through an iterative feedback process involving several rounds of questionnaires. In all, 70 researchers from across Europe were involved in this study. The experts were asked to rate the resilience of each land use model compared with the agricultural or forestry baseline and then asked to explain what were the key characteristics of the land use model that made it more resilient, providing scientific references as evidence. After each Round, responses were aggregated and anonymous feedback provided to the participants. Participants were asked to review and confirm or amend their previous responses, considering the opinions and elements that were suggested by the other participants during the preceding round. Consensus was reached when at least 70% of participants have agreed on the same level of resilience for a particular agroforestry type. The LUCIM brings you these results in an interactive way (a peer reviewed publication is undergoing and a link will be added here when it's ready).
Within expert round tables, there is often no consensus on some themes. That is normal and healthy in a discussion group. The lack of consensus towards more resiliency in certain combinations of land use change strengthens a clear sight of where the knowledge gaps are. Such gaps are needed research avenues to pursue. See below for the list of no consensus.
Northern Europe
Forestry x all climate impact combinations, i.e. building resilience to any climate impact in an established forest with changing to other land use, is unknown or there was no consensus;Southern Europe
Forestry x Cold extremes, Forestry x Extreme precipitation and Forestry x Windstorms, i.e. building resilience to 1) cold extremes, 2) extreme precipitation or 3) windstorms in an established forest with changing to other land use, is unknown or there was no consensus;Western and Central Europe
Forestry x Cold extremes, Forestry x Mean precipitation and Forestry x Windstorms, i.e. building resilience to 1) cold extremes, 2) mean precipitation or 3) windstorms decrease in an established forest with changing to other land use, is unknown or there was no consensus;This tool is a deliverable of the AGROMIX project (https://agromixproject.eu/), a European project funded by the European Union’s Horizon 2020 programme. AGROMIX brings together farmers, researchers and policymakers to explore agroecological solutions for more resilient land use in Europe, developing tools to implement these practices. The research behind this tool is summarized above; for more information, please refer to Deliverable 3.5 of the AGROMIX project (weblink D3.5 - to be updated when final version available).
Target areas
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Environmental pressures
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Socio-economic factors
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Economic variables
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Demographic variables
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Education variables
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More detailed information:
| Pressure | Threshold | Threshold source | References |
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Datasets and references:
Please select your climate region from the three subdivisions of land area for Europe:
These subdivisions are based on the Sixth Assessment Report (Bednar-Friedl et al., 2022), specifically Chapter 13 (Europe), by the Intergovernmental Panel on Climate Change (IPCC).
Climate region
Baseline system
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Why this system is more resilient:
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Exposure
Sensitivity
Adaptive Capacity
Caveats:
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Trade-offs:
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Case studies:
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Evidence base:
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None of the agroforestry land use models are considered more resilient to this climate impact driver than their forest or orchard baseline system.
Land use
Climate region
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Description
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Tree
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Crops
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Livestock
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The AGROMIX project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement 862993.
