Combining biophysical optimization with economic preference analysis for agricultural land-use allocation

Agricultural production provides food, feed, and renewable energy, generates economic profits, and contributes to social welfare in many ways. However, intensive farming is one of the biggest threats to biodiversity. Although current market forces and regulations such as the European Union's Co...

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Autores principales:	Andrea Kaim, Bartosz Bartkowski, Nele Lienhoop, Christoph Schröter-Schlaack, Martin Volk, Michael Strauch
Formato:	article
Lenguaje:	EN
Publicado:	Resilience Alliance 2021
Materias:	agricultural production biodiversity multiobjective optimization pareto frontier preferences social welfare trade-offs willingness to pay Biology (General) QH301-705.5 Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/7b956f0535b0495783b14c9aa1c8accc
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spelling	oai:doaj.org-article:7b956f0535b0495783b14c9aa1c8accc2021-12-02T14:14:42ZCombining biophysical optimization with economic preference analysis for agricultural land-use allocation1708-308710.5751/ES-12116-260109https://doaj.org/article/7b956f0535b0495783b14c9aa1c8accc2021-03-01T00:00:00Zhttps://www.ecologyandsociety.org/vol26/iss1/art9/https://doaj.org/toc/1708-3087Agricultural production provides food, feed, and renewable energy, generates economic profits, and contributes to social welfare in many ways. However, intensive farming is one of the biggest threats to biodiversity. Although current market forces and regulations such as the European Union's Common Agricultural Policy, seem to foster agricultural intensification, a socially and ecologically optimal land-use strategy should seek to reconcile agricultural production with biodiversity conservation. Research on spatial land-use allocation lacks studies that consider both aspects simultaneously. Therefore, we developed a method that finds land-use strategies with a maximum contribution to social welfare, taking into account the landscape's biophysical potential. We applied a multiobjective optimization algorithm that identified landscape configurations that maximize agricultural production and biodiversity based on their contribution to social welfare. Social welfare was approximated by the profit contribution of agricultural production and society's willingness to pay for biodiversity. The algorithm simultaneously evaluated the biophysical outcomes of different land uses using the Soil and Water Assessment Tool (SWAT) and a biodiversity model. The method was applied to an agricultural landscape in central Germany. The results show that, in this area, overall social welfare can be increased compared to the status quo if both social benefits from biodiversity and economic profits from agricultural production are considered in land-use allocation. Further, the resulting optimal solutions can create win-win situations between the two, usually conflicting, objectives. The integration of preference information into the biophysical optimization allows reducing the usually large set of Pareto-optimal solutions and thus facilitates further stakeholder-based analyses. Our explorative study provides an example of how socioeconomic data and biophysical models can be combined to support decision making and the development of land-use policies.Andrea KaimBartosz BartkowskiNele LienhoopChristoph Schröter-SchlaackMartin VolkMichael StrauchResilience Alliancearticleagricultural productionbiodiversitymultiobjective optimizationpareto frontierpreferencessocial welfaretrade-offswillingness to payBiology (General)QH301-705.5EcologyQH540-549.5ENEcology and Society, Vol 26, Iss 1, p 9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	agricultural production biodiversity multiobjective optimization pareto frontier preferences social welfare trade-offs willingness to pay Biology (General) QH301-705.5 Ecology QH540-549.5
spellingShingle	agricultural production biodiversity multiobjective optimization pareto frontier preferences social welfare trade-offs willingness to pay Biology (General) QH301-705.5 Ecology QH540-549.5 Andrea Kaim Bartosz Bartkowski Nele Lienhoop Christoph Schröter-Schlaack Martin Volk Michael Strauch Combining biophysical optimization with economic preference analysis for agricultural land-use allocation
description	Agricultural production provides food, feed, and renewable energy, generates economic profits, and contributes to social welfare in many ways. However, intensive farming is one of the biggest threats to biodiversity. Although current market forces and regulations such as the European Union's Common Agricultural Policy, seem to foster agricultural intensification, a socially and ecologically optimal land-use strategy should seek to reconcile agricultural production with biodiversity conservation. Research on spatial land-use allocation lacks studies that consider both aspects simultaneously. Therefore, we developed a method that finds land-use strategies with a maximum contribution to social welfare, taking into account the landscape's biophysical potential. We applied a multiobjective optimization algorithm that identified landscape configurations that maximize agricultural production and biodiversity based on their contribution to social welfare. Social welfare was approximated by the profit contribution of agricultural production and society's willingness to pay for biodiversity. The algorithm simultaneously evaluated the biophysical outcomes of different land uses using the Soil and Water Assessment Tool (SWAT) and a biodiversity model. The method was applied to an agricultural landscape in central Germany. The results show that, in this area, overall social welfare can be increased compared to the status quo if both social benefits from biodiversity and economic profits from agricultural production are considered in land-use allocation. Further, the resulting optimal solutions can create win-win situations between the two, usually conflicting, objectives. The integration of preference information into the biophysical optimization allows reducing the usually large set of Pareto-optimal solutions and thus facilitates further stakeholder-based analyses. Our explorative study provides an example of how socioeconomic data and biophysical models can be combined to support decision making and the development of land-use policies.
format	article
author	Andrea Kaim Bartosz Bartkowski Nele Lienhoop Christoph Schröter-Schlaack Martin Volk Michael Strauch
author_facet	Andrea Kaim Bartosz Bartkowski Nele Lienhoop Christoph Schröter-Schlaack Martin Volk Michael Strauch
author_sort	Andrea Kaim
title	Combining biophysical optimization with economic preference analysis for agricultural land-use allocation
title_short	Combining biophysical optimization with economic preference analysis for agricultural land-use allocation
title_full	Combining biophysical optimization with economic preference analysis for agricultural land-use allocation
title_fullStr	Combining biophysical optimization with economic preference analysis for agricultural land-use allocation
title_full_unstemmed	Combining biophysical optimization with economic preference analysis for agricultural land-use allocation
title_sort	combining biophysical optimization with economic preference analysis for agricultural land-use allocation
publisher	Resilience Alliance
publishDate	2021
url	https://doaj.org/article/7b956f0535b0495783b14c9aa1c8accc
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Combining biophysical optimization with economic preference analysis for agricultural land-use allocation

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