Empirical Test of an Agricultural Landscape Model
Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. Howev...
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doaj-c29e7ea20c344c08bd0d6c4048de734e2020-11-25T01:25:46ZengSAGE PublishingSAGE Open2158-24402013-04-01310.1177/215824401348649110.1177_2158244013486491Empirical Test of an Agricultural Landscape ModelIra R. Cooke0Elizabeth H. A. Mattison1Eric Audsley2Alison P. Bailey3Robert P. Freckleton4Anil R. Graves5Joe Morris6Simon A. Queenborough7Daniel L. Sandars8Gavin M. Siriwardena9Paul Trawick10Andrew R. Watkinson11William J. Sutherland12 La-Trobe University, Bundoora, Australia University of Reading, UK Cranfield University, Bedfordshire, UK University of Reading, UK University of Sheffield, UK Cranfield University, Bedfordshire, UK Cranfield University, Bedfordshire, UK University of Sheffield, UK Cranfield University, Bedfordshire, UK British Trust for Ornithology, The Nunnery, Thetford, Norfolk, UK Cranfield University, Bedfordshire, UK University of East Anglia, Norwich, UK University of Cambridge, UKDeveloping models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns.https://doi.org/10.1177/2158244013486491 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ira R. Cooke Elizabeth H. A. Mattison Eric Audsley Alison P. Bailey Robert P. Freckleton Anil R. Graves Joe Morris Simon A. Queenborough Daniel L. Sandars Gavin M. Siriwardena Paul Trawick Andrew R. Watkinson William J. Sutherland |
spellingShingle |
Ira R. Cooke Elizabeth H. A. Mattison Eric Audsley Alison P. Bailey Robert P. Freckleton Anil R. Graves Joe Morris Simon A. Queenborough Daniel L. Sandars Gavin M. Siriwardena Paul Trawick Andrew R. Watkinson William J. Sutherland Empirical Test of an Agricultural Landscape Model SAGE Open |
author_facet |
Ira R. Cooke Elizabeth H. A. Mattison Eric Audsley Alison P. Bailey Robert P. Freckleton Anil R. Graves Joe Morris Simon A. Queenborough Daniel L. Sandars Gavin M. Siriwardena Paul Trawick Andrew R. Watkinson William J. Sutherland |
author_sort |
Ira R. Cooke |
title |
Empirical Test of an Agricultural Landscape Model |
title_short |
Empirical Test of an Agricultural Landscape Model |
title_full |
Empirical Test of an Agricultural Landscape Model |
title_fullStr |
Empirical Test of an Agricultural Landscape Model |
title_full_unstemmed |
Empirical Test of an Agricultural Landscape Model |
title_sort |
empirical test of an agricultural landscape model |
publisher |
SAGE Publishing |
series |
SAGE Open |
issn |
2158-2440 |
publishDate |
2013-04-01 |
description |
Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns. |
url |
https://doi.org/10.1177/2158244013486491 |
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