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

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.

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

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

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 2000-2005)

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.

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

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)?