Agricultural Sustainability:
Opportunities for contributions from computational sciences
Laurie Drinkwater
Cornell University
Overview of this talk
• Context
– Global situation in terms of food, hunger and environmental change
• Transitioning to sustainable agricultural systems
– What are the challenges that must be addressed?
– Ideology and values play a role in defining sustainable agriculture
– Social-ecological systems: A useful conceptual framework
• Potential questions for computational sciences
– Three examples
Global food situation
• Nearly 900 million people -about 13% of the world
population -- do not have enough
food (FAO)
• About 40% of the world
population relies on subsistence
agricultural systems
• Currently, we have sufficient food
for our population– political and
economic conditions prevent
access
• Can food production continue to
keep pace with population
growth?
• Humans occupy 75% of the ice-free terrestrial
surface and manage 90% of the NPP
• Agricultural systems dominate a majority of the most
productive biomes
Ellis and Ramankutty 2008
Consequences of intensification
• Resource consumption by industrial agriculture is enormous and is
undermining long term productivity of our agricultural lands.
– Fossil fuels, water, soil, land area
• Agricultural systems disrupt the integrity of natural ecosystems and
contribute to widespread losses of biodiversity.
– Movement of nutrients, toxic chemicals and sediments
– Extensive land use
• Agriculture is a major contributor to global climate change.
– 52% and 84% of global anthropogenic CH4 and N2O, significant C02
• Despite progress in food output on a per acre and per capita basis, the
quality of life for farm families and rural communities continues to
decline.
– Reduced income over time, health issues
Human activities
and environmental
consequences are
changing rapidly
Steffan et al. 2004. Global Change and the
Earth System.
Transitioning to sustainable agricultural systems
http://waterweek.wordpress.com/2007/09/19/
Ecosystem Services
The benefits people obtain from ecosystems
Millennium Ecosystem Assessment- www.millenniumassessment.org
What are our goals for agriculture?
• Multifunctional: Food and fiber plus ecosystems services
• Provide healthy, nutritional food in sufficient quantities
• Production and food systems must be resilient
• Quality of life for farm families and vibrant rural
communities
• Reverse environmental degradation: local to global scales
Super techno
Techno-eco
Super eco
http://www.holocene.net/
Agriculture as a social-ecological system
• Food production is still largely
dependent on ecological
processes despite intensification
• Social processes govern the
design and development of
production systems and
agricultural technology as well as
land use patterns
• So far, social processes have not
proven to be adept at responding
to ecosystem change or
mitigating undesirable
consequences
EU: DPSIR Framework
Pressure on
the environment
Social and economic
Driving forces
Societal
Response
State of the
environment
changes
Impacts on
human health,
[Impacts on other
species or undermining
Ecosystem Services(?)]
What areas could benefit from computer
science and mathematics?
Three examples…
• Ecosystem modeling—Flows of
energy and materials
• Resource accounting– Ecological
footprint and life cycle analysis
• Spatial and temporal analysis of
existing (massive) data sets
Ecosystem modeling
Ecosystem process models have five components
1. Forcing functions or external variables-naturally imposed variables that
influence the state of the ecosystem
2. State variables-variables that describe the state of the ecosystem
3. Mathematical equations-represent biological, chemical and physical
functions and describe the relationship between forcing functions and
state variables
4. Parameters-coefficients in the mathematical representation of processes
5. Universal constants-naturally occurring constants
Jorgensen and Bendoricchio 2001
The Decomposition-Denitrification Model
ecological
drivers
Climate
Soil
Vegetation
water demand
water uptake
potential
evapotrans.
evap.
trans.
vertical
water
flow
CO2
O2
diffusion
soil Eh
profile
O2 use
grain
NH4+
NO2-
N2 O
N2
Denitrification
nitrite
denitrifier
N2 O
denitrifier
resistant
labile
resistant
stems
humads
DOC
labile
resistant
Plant growth
passive humus
Temperature
nitrate
denitrifier
labile
root respiration
effect of temperature and moisture on decomposition
soil
environmental
factors
very labile
microbes
N-uptake
roots
Soil climate
NO
N-demand
water stress
soil temp
profile
soil moist
profile
daily growth
litter
annual
average
temp.
LAI-regulated
albedo
Human activity
DOC
Moisture
pH
DOC
NH4+
nitrifiers
NO3NO3-
N2 O
Nitrification
NH3
NO
NH3
Eh
clayNH4+
Decomposition
Substrates: NH4+, NO3-, DOC
soil Eh
CH4 production
aerenchyma
CH4 oxidation
DOC
Fermentation
CH4 transport
CH4
Modeling flows of energy and materials
Water drainage from watersheds planted with corn and
soybean on tile-drained Mollisols in Illinois
180
Observations
DAYCENT
DNDC82a
DNDC82h
Drainage (mm month-1)
160
140
120
100
80
60
40
20
0
97
98
99
00
01
02
Year
Graph courtesy of Christina Tonitto
03
04
05
06
07
Comparison of six widely used process models:
Daily N2+N2O flux predictions across models
1
2
3
4
5
DRAINMOD N-II
SWAT
DAYCENT
DNDC82h
DNDC82a
EPIC
-1
-1
Denitrification (kg N ha d )
0.6
0.5
0.4
0.3
0.2
0.1
0.0
Jan Feb Mar Apr May Jun
Jul
Aug Sep Oct Nov Dec
2002
David et al. 2009
Precipitation (cm)
0
• Models had different predictions
for water flux, soil moisture
status
• They also had very different
seasonal predictions of N gas flux
• With limited field data we can not
distinguish which model perform
best
• Options for resolving this:
massive data collection and
increased complexity of models
• Can we develop simple models to
serve need of policymakers?
• Can we combine spatial and
process modeling?
The Ecological Footprint
• Developed by Wackernagel and Rees, 1996: Our Ecological
Footprint: Reducing Human Impact on the Earth
• Attempts to answer a single question: How much of the
planet’s capacity do we use compared to how much is
available?
• Compares the area we demand to how much area is available
• Currently, it provides the only available comprehensive
answer to this research question.
• Based on real data: consumption and production
• How does this approach differ from carrying capacity?
http://www.footprintnetwork.org/en/index.php/GFN/
Global ecological footprint by component, 1961-2005
http://www.footprintnetwork.org Living Planet Report 2008
Ecological Footprint per person, by country for 2005
http://www.footprintnetwork.org Living Planet Report 2008
Ecological creditor and debtor countries, 2005
Ecological Footprint summary
• Provides insights on sustainability of natural capital use at large scales:
regions, nations and global
• Example: Because the calculations are based on actual consumption rates
that reflect current technology, we can conclude that technology has not
kept pace with increased consumption
• Limitations in terms of env. Impact of toxins, materials that do not
decompose, and resource depletion outside the biosphere
• Strong ecological basis: datasets and calculation methods have improved
since 1996
• Focus on natural capital, efficiency of providing human needs
• Does not assess social indicators of sustainability
• Application to farm-scale production has yet to be clearly demonstrated
but has the potential to be very useful in combination with other
approaches
Life cycle assessment
• Developed in the 1960’s, “industrial ecology”
• A “cradle-to-grave” approach for assessing industrial systems.
• Begins with the gathering of raw materials from the earth to
create the product and ends at the point when all materials
are returned to the earth.
• Quantifies environmental releases to air, water, and land in
relation to each life cycle stage and/or major contributing
process in the course of the product’s life-span
Life cycle stages reflect the industrial
origins
LCA of three contrasting pig production systems
Van der Werf et al. 2003
LCA summary
• Focus is on assessing natural capital: source-sink and
environmental impacts
• Integrates known environmental impacts
• Interpretation of trade-off across env. Impacts depends on
subjective decision-making of the evaluators
• Sound ecological basis but estimating emissions in agricultural
systems presents a formidable challenge (open versus point
emissions)
• Units for reporting resource use and emissions determine
performance of contrasting systems
Spatial and temporal analysis of human
dominated landscapes
Intensification of the landscape continues to
increase: loss of winter annuals
35000
Crop Area (1000 ha)
30000
Corn
25000
Wheat
20000
15000
Hay
10000
Soybean
Oat
5000
0
1940
David et al, in prep.
1950
1960
1970
1980
1990
2000
2010
Crop distribution in Illinois, 2004
Corn
Soybean
Pasture
There is a vast amount of biophysical and social data
available. USDA and Census Bureau, NRCS
Understand spatial patterns and temporal
dynamics of agricultural landscapes
Average N loss at a county level in the
Mississippi River Basin
Leak 2
0 - 26
27 - 67
68 - 116
117 - 171
172 - 259
Mark David et al., in prep
Conservation payments are lowest in the
high yielding regions
Fraction Conservation Payments to Total Payments
0.0 - 9.5
9.6 - 19.7
19.8 - 32.5
32.6 - 48.0
48.1 - 100.0
Conclusions
• Tremendous potential for computational sciences to
contribute
• Vast amounts of information are not being exploited to their
full potential
• The pace of change presents a significant challenge
• Quantitative analysis of systemic trends can help society
adapt and respond appropriately to environmental change