Literature DB >> 21113782

A generic bio-economic farm model for environmental and economic assessment of agricultural systems.

Sander Janssen1, Kamel Louhichi, Argyris Kanellopoulos, Peter Zander, Guillermo Flichman, Huib Hengsdijk, Eelco Meuter, Erling Andersen, Hatem Belhouchette, Maria Blanco, Nina Borkowski, Thomas Heckelei, Martin Hecker, Hongtao Li, Alfons Oude Lansink, Grete Stokstad, Peter Thorne, Herman van Keulen, Martin K van Ittersum.   

Abstract

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.

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Year:  2010        PMID: 21113782      PMCID: PMC3002165          DOI: 10.1007/s00267-010-9588-x

Source DB:  PubMed          Journal:  Environ Manage        ISSN: 0364-152X            Impact factor:   3.266


  3 in total

1.  Modeling the spatial dynamics of regional land use: the CLUE-S model.

Authors:  Peter H Verburg; Welmoed Soepboer; A Veldkamp; Ramil Limpiada; Victoria Espaldon; Sharifah S A Mastura
Journal:  Environ Manage       Date:  2002-09       Impact factor: 3.266

2.  Modelling Common Agricultural Policy-Water Framework Directive interactions and cost-effectiveness of measures to reduce nitrogen pollution.

Authors:  Ioanna Mouratiadou; Graham Russell; Cairistiona Topp; Kamel Louhichi; Dominic Moran
Journal:  Water Sci Technol       Date:  2010       Impact factor: 1.915

3.  Farm management indicators and farm typologies as a basis for assessments in a changing policy environment.

Authors:  Erling Andersen; Berien Elbersen; Frans Godeschalk; David Verhoog
Journal:  J Environ Manage       Date:  2006-11-28       Impact factor: 6.789

  3 in total
  4 in total

1.  Multi-angle indicators system of non-point pollution source assessment in rural areas: a case study near Taihu Lake.

Authors:  Lei Huang; Jie Ban; Yu Ting Han; Jie Yang; Jun Bi
Journal:  Environ Manage       Date:  2013-02-28       Impact factor: 3.266

2.  Towards a new generation of agricultural system data, models and knowledge products: Design and improvement.

Authors:  John M Antle; Bruno Basso; Richard T Conant; H Charles J Godfray; James W Jones; Mario Herrero; Richard E Howitt; Brian A Keating; Rafael Munoz-Carpena; Cynthia Rosenzweig; Pablo Tittonell; Tim R Wheeler
Journal:  Agric Syst       Date:  2017-07       Impact factor: 5.370

3.  Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology.

Authors:  Sander J C Janssen; Cheryl H Porter; Andrew D Moore; Ioannis N Athanasiadis; Ian Foster; James W Jones; John M Antle
Journal:  Agric Syst       Date:  2017-07       Impact factor: 5.370

4.  To what extent is climate change adaptation a novel challenge for agricultural modellers?

Authors:  R P Kipling; C F E Topp; A Bannink; D J Bartley; I Blanco-Penedo; R Cortignani; A Del Prado; G Dono; P Faverdin; A-I Graux; N J Hutchings; L Lauwers; Ş Özkan Gülzari; P Reidsma; S Rolinski; M Ruiz-Ramos; D L Sandars; R Sándor; M Schönhart; G Seddaiu; J van Middelkoop; S Shrestha; I Weindl; V Eory
Journal:  Environ Model Softw       Date:  2019-10       Impact factor: 5.288

  4 in total

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