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Estimating UK perennial energy crop supply using farm scale models with spatially disaggregated data

Estimating UK perennial energy crop supply using farm scale models with spatially disaggregated data
Estimating UK perennial energy crop supply using farm scale models with spatially disaggregated data
To achieve the UK Government's aim of expansion in the growth of perennial energy crops requires farmers to select these crops in preference to conventional rotations. Existing studies estimating the total potential resource have either only simplistically considered the farmer decision-making and opportunity costs, for example using an estimate of annual land rental charge; or have not considered spatial variability, for example using representative farm types. This paper attempts to apply a farm-scale modelling approach with spatially specific data to improve understanding of potential perennial energy crop supply. The model main inputs are yield maps for the perennial energy crops, Miscanthus and willow grown as short-rotation coppice (SRC), and regional yields for conventional crops. These are used to configure location specific farm-scale models, which optimize for profit maximization with risk aversion. Areas that are unsuitable or unavailable for energy crops, due to environmental or social factors, are constrained from selection. The results are maps of economic supply, assuming a homogenous farm-gate price, allowing supply cost curves for the UK market to be derived. The results show a high degree of regional variation in supply, with different patterns for each energy crop. Using estimates of yields under climate change scenarios suggests that Miscanthus supply may increase under future climates while the opposite effect is suggested for SRC willow. The results suggest that SRC willow is only likely to able to supply a small proportion of the anticipated perennial energy crop target, without increases in market prices. Miscanthus appears to have greater scope for supply, and its dominance may be amplified over time by the effects of climate change. Finally, the relationship to the demand side of the market is discussed, and work is proposed to investigate the factors impacting how the market as a whole may develop.
economics, energy crops, farm-scale modelling, miscanthus, risk & uncertainty, short-rotation coppice, spatial analysis
1757-1693
142-155
Alexander, Peter
9b0e0950-b6fa-414e-8bc0-c259dea3f36d
Moran, Dominic
57bedeb2-05d9-4045-82bc-17263d3b6155
Smith, Pete
a8a5c7c1-faf6-4b75-b125-ec8c73d104a2
Hastings, Astley
da539d8f-16e4-4898-9b55-1f694d9ff7cc
Wang, Shifeng
8b6d5a58-443e-4fda-b9d1-2c0d44c66c7f
Sunnenberg, Gilla
1599365d-0643-49e0-94be-c149304102aa
Lovett, Andrew
b75a7fb5-4d52-43c7-88c9-5114df60198b
Tallis, M.J.
25cbd143-1f8c-491b-9eac-f1c632dfcfda
Casella, Eric
3a60adce-ddba-4e72-97e2-5ca161f32954
Taylor, Gail
f3851db9-d37c-4c36-8663-e5c2cb03e171
Finch, Jon
af0397ba-8965-480f-aa7e-f3d09d15a51c
Cisowska, Iwona
21e8d0c9-adac-4069-8f2e-a133f1751845
Alexander, Peter
9b0e0950-b6fa-414e-8bc0-c259dea3f36d
Moran, Dominic
57bedeb2-05d9-4045-82bc-17263d3b6155
Smith, Pete
a8a5c7c1-faf6-4b75-b125-ec8c73d104a2
Hastings, Astley
da539d8f-16e4-4898-9b55-1f694d9ff7cc
Wang, Shifeng
8b6d5a58-443e-4fda-b9d1-2c0d44c66c7f
Sunnenberg, Gilla
1599365d-0643-49e0-94be-c149304102aa
Lovett, Andrew
b75a7fb5-4d52-43c7-88c9-5114df60198b
Tallis, M.J.
25cbd143-1f8c-491b-9eac-f1c632dfcfda
Casella, Eric
3a60adce-ddba-4e72-97e2-5ca161f32954
Taylor, Gail
f3851db9-d37c-4c36-8663-e5c2cb03e171
Finch, Jon
af0397ba-8965-480f-aa7e-f3d09d15a51c
Cisowska, Iwona
21e8d0c9-adac-4069-8f2e-a133f1751845

Alexander, Peter, Moran, Dominic, Smith, Pete, Hastings, Astley, Wang, Shifeng, Sunnenberg, Gilla, Lovett, Andrew, Tallis, M.J., Casella, Eric, Taylor, Gail, Finch, Jon and Cisowska, Iwona (2014) Estimating UK perennial energy crop supply using farm scale models with spatially disaggregated data. Global Change Biology Bioenergy, 6 (2), 142-155. (doi:10.1111/gcbb.12121).

Record type: Article

Abstract

To achieve the UK Government's aim of expansion in the growth of perennial energy crops requires farmers to select these crops in preference to conventional rotations. Existing studies estimating the total potential resource have either only simplistically considered the farmer decision-making and opportunity costs, for example using an estimate of annual land rental charge; or have not considered spatial variability, for example using representative farm types. This paper attempts to apply a farm-scale modelling approach with spatially specific data to improve understanding of potential perennial energy crop supply. The model main inputs are yield maps for the perennial energy crops, Miscanthus and willow grown as short-rotation coppice (SRC), and regional yields for conventional crops. These are used to configure location specific farm-scale models, which optimize for profit maximization with risk aversion. Areas that are unsuitable or unavailable for energy crops, due to environmental or social factors, are constrained from selection. The results are maps of economic supply, assuming a homogenous farm-gate price, allowing supply cost curves for the UK market to be derived. The results show a high degree of regional variation in supply, with different patterns for each energy crop. Using estimates of yields under climate change scenarios suggests that Miscanthus supply may increase under future climates while the opposite effect is suggested for SRC willow. The results suggest that SRC willow is only likely to able to supply a small proportion of the anticipated perennial energy crop target, without increases in market prices. Miscanthus appears to have greater scope for supply, and its dominance may be amplified over time by the effects of climate change. Finally, the relationship to the demand side of the market is discussed, and work is proposed to investigate the factors impacting how the market as a whole may develop.

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e-pub ahead of print date: 1 November 2013
Published date: March 2014
Keywords: economics, energy crops, farm-scale modelling, miscanthus, risk & uncertainty, short-rotation coppice, spatial analysis
Organisations: Centre for Biological Sciences

Identifiers

Local EPrints ID: 363101
URI: http://eprints.soton.ac.uk/id/eprint/363101
ISSN: 1757-1693
PURE UUID: e8e7fca3-e993-4dec-9136-6f5b847fcab1
ORCID for Gail Taylor: ORCID iD orcid.org/0000-0001-8470-6390

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Date deposited: 20 Mar 2014 15:19
Last modified: 12 Nov 2019 01:54

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Contributors

Author: Peter Alexander
Author: Dominic Moran
Author: Pete Smith
Author: Astley Hastings
Author: Shifeng Wang
Author: Gilla Sunnenberg
Author: Andrew Lovett
Author: M.J. Tallis
Author: Eric Casella
Author: Gail Taylor ORCID iD
Author: Jon Finch
Author: Iwona Cisowska

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