Cluster A - A05

A05


Representation of adaptation: the on-farm perspective


Prof. Dr. Silke Hüttel
University of Bonn  |    +49 551 39-24846  |   This email address is being protected from spambots. You need JavaScript enabled to view it.

Prof. Dr. Michael Leyer
University of Marburg  |    +49 6421 28-23382  |   This email address is being protected from spambots. You need JavaScript enabled to view it.

Dr. Stefan Seifert
University of Göttingen  |    +49 551 39-24841  |   This email address is being protected from spambots. You need JavaScript enabled to view it.


 

Summary

In A05, we aim at an improved representation of how farmers adapt to climate change, altering weather (extremes), production risk and efficiency, and ultimately expectations on farming returns. Yet to date, farms seem reluctant to adapt their farming structure. Based on the real options approach, we hypothesize that this reluctance can be explained by farms’ investment behavior under risk and various sources of inefficiency. We test this hypothesis using observational data. To understand underlying cognitive decision processes under extreme hydrometeorological events, we test the impact of such perceived instances on farm adaptation decisions using an experimental approach. 

Contribution to the CRC

This project contributes to the understanding of on-farm adaptation processes impacting LULCC. The improved representation of adaptation processes in form of adaptation probabilities and insights on regional LULCC dynamics generated in the partner project A06 will inform LULCC scenario development for earth system modelling in project D01.

Approach

We take the farm perspective and aim at an improved representation of how farmers in the CRC’s EU focus regions adapt to climate change. Climate change alters weather conditions, translating into changes in a farm’s risk profile and production efficiency, in turn influencing expectations on future farming returns. Farms react to these changes by adapting the farming structure, such as crop choice, irrigation expansion and adoption, or termination of farm branches, to better cope with changed risk profiles. However, despite observed trends of changing climatic conditions and thus farm risks, farmers seem reluctant to adapt.

As adaptations encompass partly irreversible investments or disinvestments subject to expectations about uncertain future returns, we hypothesize that this reluctance can be explained by farmers’ investment behavior under risk: under uncertain future returns from farming, costly reversible adaptations, flexible timing and production inefficiency, waiting for new information can be beneficial. Climate change, however, also implies a higher likelihood of extreme hydrometeorological events, which leads us to the hypothesis that adaptation behavior becomes more likely. We proceed as follows:

  1. To enrich farm accountancy data by detailed information on weather, climate, and geography, we develop a probabilistic approach to downscale farm data from NUTS-2 to NUTS-3 level.
  2. Based on these farm observational data, we analyze gaps between economically optimal and realized farm output for given weather data and quantify production inefficiency. We decompose overall production inefficiency into managerial, policy-induced and perceived inefficiency due to weather risk.
  3. We analyze farms’ adaptations under different sources of inefficiency and production relevant risk based on a real options model.
  4. Using an experimental approach, we test relevance of instances from extreme hydrometeorological events for farm adaptation decisions.
  5. The improved representation of adaptation processes in form of adaptation probabilities enter the scenarios in D01.

Main results in 2022

Farm-level data for the analysis has been acquired. First results indicate that state-of-the art econometric methods and crop models can support the accuracy of the spatial probabilistic downscaling approach. A baseline model for farms’ adaptation decisions based on the real options approach shows that uncertainty and risk aversion affect adaptation thresholds and may explain farms’ reluctance to adapt to climate change.

Presentations 2022: DETECT Land and Climate Seminar; Ringvorlesung „Klimawandel Folgenabschätzung und Anpassungsstrategien für die Landwirtschaft“ at the Faculty of Agriculture in Bonn; EWEPA 2022 in Porto; FORLand Webinar (DFG FOR 2569)

Additional: HALLE grant with Emory University and Humboldt-Universität Berlin “Supporting Sustainable Agricultural Landscapes in the EU and US”; von Trott stipend for Moritz Hartig

 

 

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