1. Evaluating the options for economically, socially and ecologically sustainable agriculture
Farmer preferences
Elizabeth Mattison
Anil Graves
Alison Bailey
Joe Morris
Paul Trawick
Weed modelling and surveys
Simon Queenborough
Rob Freckleton
Andrew Watkinson
Bird surveys and modelling
BTO volunteers
Gavin Siriwardena
Phil Atkinson
Juliet Vickery
Ken Norris
Economic modelling
Eric Audsley
Daniel Sandars
Agronomic Advice
Phil Strachan
Model Integration
Ira Cooke
Bill Sutherland

2. Broad objective
Our main aim is to integrate sociology, agricultural science, economics and ecology to explain and ultimately predict the impacts of economic, environmental, technological and social changes on farming practice, farm livelihoods and farm biodiversity.
We have concentrated upon the weeds and birds.

3. Linked Model Economic and physical data
Non-profit drivers to farmer behaviour
Individual farmer
land-use model
Rotations and
cropping
Breeding
habitat
Non-cropping
features
Farmland
bird
populations
Arable weed
Winter food
for birds

4. Farmer behaviour 46 Farms. All farmers interviewed
16 Key management objectives identified through pilot surveys
Satisfaction curves and relative preference weights for 16 management objectives elicited
Results interpreted in a multi-attribute utility theory framework
Farmer preferences quantitatively integrated with the economic decision making model
Detailed management information collected for 10 fields on each farm will enable comparison of predicted and actual decisions

5. Modelling arable land-use
Detailed mixed integer programming model of the farming system
Profit optimization module
Timing of operations
Areas of each crop
Rotations
Profit consequences of all farmer preferences
Farmer preference modules
Crop complexity
Risk
ELS options
Specific management (eg winter stubbles)
Modelled vs Actual cropping across arable farms
(FBS data 2005)
Modelled vs Actual cropping on individual farms
(FBS data )

6. Arable weeds Same 46 arable farms 10 fields per farm
Fields monitored down to 20m x 20m scale
3 surveys per year
7 weed species
~3million data points
46 x Farms
Fields
For our project we have tackled these issues head on. We are working on a system of 45 farms across the UK, and are monitoring 10 fields per farm.
This is a large number of farms and fields, however the density-structured approach is allowing us to work at this scale because the demographic data were collect are relatively straightforward and quick to collect.
The basic unit of measurement is a 20mx20m plot, and within this area weed densities are scored on a simple 5 point ordinal scale based on a visual estimate of density. This allows us to monitor about 2 hectares within each field very rapidly, with the consequence that a PDRA and his assistant are able to monitor at least one farm per day.

7. Bird surveys Bird counts and habitat data collected at a large scale
Bird and habitat surveys by BTO Volunteers at 898 lowland arable squares each with 2 visits
Bird densities, Landscape features, cropping, linear features and soils recorded along 2km transect
Detailed habitat maps collected on our 46 farms
HH= Hedge Height, HW=Hedge Width, T=Tree presence, S1=One sided strip width

8. Examples of questions
(1) Widely fluctuating commodity prices have been accompanied by rising input costs at the same time as climate change is leading to increasingly unreliable weather conditions. What are the likely outcomes of farmers responses to these increased levels of risk on cropping decisions, and consequently on farmland bird and weed populations?
(2) What would be the biodiversity consequences of phasing out or reduction in size of the single farm payment?
(3) What elements of farmer's management practice can be predicted from a pure profit maximisation approach, and what elements are determined much more by farmer preferences.   In particular, how would the uptake of environmental subsidy schemes be affected by the combined effects of economics and individual farmer preference?
(4) What are the most cost effective policy options for increasing farmland bird populations.?
(5) How would the effectiveness of environmental policy options differ if the distribution of farmer preferences were to change, (eg through demographic change)?