1. Daniel L
Sandars
Research Officer:
Decision modelling and analysis (agriculture and environment)
Centre for Natural Resource Management,
Dept. of Natural Resources, School of Applied Science
• ’90 BSc. Hons. Agriculture (Seale-Hayne)
’94 MSc, Applied Environmental Science (Wye, U. London)
‘05 MSc (Dist.), Operational Research (U. Herts.)
• Member of the Institute of Agricultural Engineering (MIAgrE)
Member of the Institute of Agricultural Management (MIAgrM)
Associate Fellow of the Operational Research Society
(AFORS)

2. Common
approaches
• Mathematical Programming
• Long-term optimisation, Rational Behaviour, uncertainty &
multiple criteria
• Systems Modelling
• Life Cycle Assessment (LCA), Data quality, Environmental
Interactions, Long-term steady-state mass balance
• Others
• Knowledge based modelling, Data Envelopment Analysis
(DEA), Discreet event simulation

3. Interests
• Generally sustainability with respect to land-use and
farming. Might go for a CEnv next
• Member of the European Working Group on
Operational Research in agriculture and Forestry
• Chairing sessions on sustainability in July, co-
editing the proceedings and hoping to bring the
entire meeting to the UK in 2008
• Have taken the initiative to launch a University wide
Modeller’s forum. So far so good.

4. A project
• How will farmers react to policy initiatives to promote bio-
diversity? For example, lowland arable birds.
• Developing the whole farm model to predict the rational
response based on long-term profit and other motives
• Need to include weeds, birds and field margins
• Three research councils are funding it via the RELU
programme. Defra are interested as lowland birds are in decline
and a political priority
• Insights into this problem and the methodology, tools and data
to readily address problems of this type

5. Future
• Recycling Organic residues, renewable energy, Food miles
(globalisation), Organic universe or not
• Slow statutory pressure, great lifestyle demands, tiring
resource base
1. Need to improve the computability of MOP
2. Need better analytical understanding of decision behaviour
3. Need better data and modelling (strategic resource)
4. Need to recognize and live with uncertainty and data quality

6. Future
• Recycling Organic residues, renewable energy, Food miles
(globalisation), Organic universe or not
• Slow statutory pressure, great lifestyle demands, tiring
resource base
1. Need to improve the computability of MOP
2. Need better analytical understanding of decision behaviour
3. Need better data and modelling (strategic resource)
4. Need to recognize and live with uncertainty and data quality