The Role of FMIS in Sustainable Forest Management Practices –
comparisons and future direction
"In the long term, economic sustainability depends on
ecological sustainability.“
— “America’s Living Oceans” [Pew Oceans Report, 2003]
AIS SIGGreen Pre-ICIS 2010 Virtual Workshop
November 12-13, 2010
Ron Berger
Seoul National University
Department of Agricultural Economics & Rural Development
Program in Regional Information
Introduction –
functions of the forest
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Forests can provide
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Estuaries and adjacent upland provide services for
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Wood and fiber
outdoor recreation
stream flow
erosion control
atmospheric CO2 absorption
habitat and biodiversity protection
commercial fisheries
residential space
industrial and commercial structures
absorption of waste products from local runoff and upstream sources along rivers and streams
Environment indirectly support other biological and ecological production
processes that yield value
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nutrient recycling
organic material decomposition
soil fertility generation and renewal
crop and natural vegetation pollination
biological control of agricultural pests
Adger et al., 1994, Pearce, 1993
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Introduction –
change in forest management paradigm
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Forestry initially designed DSS for timber, cultivation and pest management (Reynolds,
2005)
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paradigm shift from sustained yield for maximized profits for timber production to
sustaining multi-objective elements within the ecosystem (Thomas, 1995)
Sustainable forest management requires integration of economic and ecological
objectives (Li et al., 2000)
Forest DSS today provide cultivation prescriptions for ecological objectives such as
timber management, vegetative growth, wildlife, and forest health (Nute et al., 2004)
Forest ecosystem management has more emphasis on socially acceptable,
economically feasible management decisions (Reynolds, 2005)
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Introduction –
ecological, social and economic information
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GIS used in forest management apply spatial data, system queries and summary
display (Rondeaux, 1991), but lack non-use economic value information
Total economic value of a forest ecosystem needs to achieve a financial return (Adger
et al. 1994; Pearce, 1993)
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Non-economic values are important in environmental economics (Adamowicz et al. 1998),
values needed by resource managers for decision-making (Englin et al. 1991)
Regardless of the approach taken, CSR or stakeholder accountability, decisionmakers need access to ecological and socio-economic information for making
proper decisions
IS can shape beliefs about our environment (Melville, 2010) and play a critical role in
assisting sustainable practices and policies
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Objectives and research questions
Proposition – Managing for sustainable forest ecosystems requires adequate estimates
of use and non-use economic values
Objective – review of existing FMIS (forest management information systems) that
deal with multi-objective aspects required for forest ecosystem management
Research Questions –
• To what extent do FMIS deal with multi-objective analysis required for forest
ecosystem management?
• To what extent do FMIS analyze estimated use and non-use economic value?
• To what extent do FMIS provide proper social and economic information for
manager and stakeholder decision-making
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Three levels of organization in ecosystem management
decision-making process
Decision Environment
(goals, values, constraints)
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Organization and
Decision-making Processes
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Decision Support System
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user
DSS software
Concept of forest ecosystem
management has different value for
key players and decision-makers
Continually evolved by social,
economic, political and policy
implications
Goal is long-term protection of the
ecosystem and meeting demand of a
growing population
Requires effective multi-objective
DSS for support, but not replace the
reasoning of stakeholders in the
decision-making process
(social, economic, political and legal context)
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Adapted from Rauscher, 1999
The decision environment
Private landowners
Special interest
Public
Industrial landowners
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Scientist & specialist
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Divided by management and
ecological subsystems
Network of decision-makers and
stakeholders
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Group negotiation process
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Decision-makers (managers,
specialists) determine objectives,
evaluate risks and value
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Managerial
decision-makers
Decision support tools
Ecological assessment
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Ecosystem management DSS
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Management subsystem
Ecological subsystem
(Adapted from Rauscher, 1999)
Resources
Neutral biophysical
different values, goals and constraints
social, economic, political pressures
Values, goals and constraints are
group negotiated
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most difficult part of social process
As goals and conditions change,
so can value
Stakeholder, public preferences,
negotiation conflict management
skills, and economic valuation
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inclusive for understanding
ecosystem management
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Total Economic Value
Non-Use Values
Use Values
Direct Use
Values
Indirect Use
Values
Direct
consumption
Functional
benefits
Future direct
and indirect
use values
Regulating servicesflood prevention, water
purification
Preserving- watersheds,
biodiversity
All services- habitat
and Biodiversity support
Ex.- Old growth Redwoods
In CA. As valued by a NY
taxi driver
Forests- water, fish,
timber, carbon store
Agriculture- food
crops, biomass
energy
Option
Values
Bequest
Values
Value of leaving
use- and non-use
values for future
generations
Existence
Values
Value of
knowledge of
continued
existence
All services- habitat Supporting services support
endangered species (panda,
Irreversible change- blue whale, eagle
Future damages
No benefit expectation
from global warming
Values become increasingly intangible
http://environmentaleconomics.wordpress.com/2010/05/02/valuationhttp://www.slidefinder.net/v/valuation_the_contingent_valuation_method/3190400; (Pearce 1993; Bateman et al., 2003)
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Economic Valuation Techniques
Methods
Direct
Observed behavior (revealed preference)
Market Price
Simulated Markets
Travel Cost
Indirect
Adapted from Mitchell and Carson (1989)
Hypothetical (stated preference)
Contingent Valuation
Attribute-based Models
Hedonic Property Values
Conjoint Analysis
Hedonic Wage values
Choice experiments
Avoidance Expenditures
Contingent Ranking
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Economic Valuation Techniques
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Direct Observational Methods
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Direct Hypothetical Methods
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Contingent valuation method (CVM) - respondents asked what value they would place on some level
of environmental change (change in risk of illness or loss of habitat)
asks people directly how much they would be WTP for environmental services
Indirect Observed Methods
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actual observable choices and/or goods that have market prices
loss in value can be calculated easily if prices are directly observable
estimated from prices in commercial markets – timber, biomass, agriculture
Travel cost methods infer values of recreational resources by determining how much visitors spent
getting to a site and then using this information to estimate a demand curve for that site
Hedonic property value and hedonic wage approaches use regression analysis to infer environmental
values from spending on goods which include those values
Avoidance expenditures are expenditures necessary to take action to reduce the damage caused by
flooding or pollution. These expenditures can be used as a lower bound estimate of damages
Indirect Hypothetical Methods
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Contingent Ranking asks respondents to evaluate bundles of goods with varying levels of certain
characteristics and to rank order the bundles
Conjoint analysis presents respondents with bundles of attributes from which to choose
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Results – comparisons of six forest ecosystem DSS
System
DSS approach
Economic analysis
Stakeholders
CLAMS
• simulation
• employment income, timber
value and production
• contingent value of biodiversity
LUCAS
• simulation
• econometric model outputs
• economic and social information
MRLAM
• simulation
• optimization
• evaluation
• simulation
• evaluation
• managers
•Land owners
Harvest
• simulation
• evaluation
• managers
• researchers
• land owners?
NED
• simulation
• evaluation
WBAFA
• managers
• landowners
• policy-makers
• analysts
• managers
• land owners
• managers
• land owners
• “diverse stakeholders”?
• eco- socio-economic interactions
• timber outputs
• social negotiation/learning ability
•natural resource managers
• “clients”?
CLAMS – Coastal Landscape Analysis and Modeling System LUCAS – Land-Use Change and Analysis System
HARVEST
MRLAM – Multi-Resource Land Allocation Model
WBAFA – Willamette Basin Alternative Futures Analysis NED
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Conclusions
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Forest ecosystem management is in its emerging stage, complicating traditional
forest management practices
Study aimed to describe and compare six advance DSS used in forest ecosystem
management in terms of its capabilities, limitations and effectiveness in analyzing
economic value and stakeholder participation
Discussion, conclusions and DSS applicability are based on subjective analysis
Some authors suggests that some of these models are simulations and the usage
of the term “knowledge-based” DSS by other authors is unclear
Even though total economic value is unclear because of the absence of non-use
values, DSS should develop objective measures for its integration
Economic values for direct use/direct consumption are evaluated in two models
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CLAMS and NED
If the DSS offered any economic information, it was based on the market value of
timber products rather than non-timber/environmental services
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Conclusions
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From a traditional forest management approach, it does not appear that the DSS
evaluate economic options for alternative cultivation strategies
From a forest ecosystem management approach, it does not appear that the DSS
evaluate economic options for disturbance effects (soil, water, wildlife)
Non-use and indirect-use value usage in the models are unclear
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CLAMS – claims to implement contingent value of biodiversity
LUCAS – mentions economic and social information
NED – claims eco-socio-economic interactions are evaluated; social negotiation/learning capabilities
Future DSS should develop objective measures for the integration and evaluation
of estimates for non-use and indirect-use values
Although various DSS are implemented in various regions, the level of utilization
for stakeholder and decision-maker negotiation is underdeveloped
Extending systems to include economic value components could improve decisionmaking and stakeholder negotiation, and increase forest ecosystem sustainability
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References
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Adamowicz, W., Boxall, P., Williams, M., and Louviere J. (1998) Stated Preference Approaches for Measuring Passive Use
Values: Choice Experiments and Contingent Valuation, American Journal of Agricultural Economics, 80, 1 , 64-75.
Adger, N., Brown, K., Cervigni, R. and Moran, D. Towards Estimating Total Economic Value of Forests in Mexico, Centre for
Social and Economic Research on the Global Environment, Working Paper GEC 94-21.
http://unstats.un.org/unsd/envAccounting/ceea/archive/Forest/TEV_Mexican_Forest.PDF
Bateman, I. J. 2003. The Economics of Non-Market Goods and Resources. A Primer on Nonmarket Valuation. Champ, P. A.,
Boyle, K. J., and Brown, T. C. (Eds), Kluwer Academic Publishers.
Englin, J., and Mendelsohn, R. 1991. A Hedonic Travel Cost Analysis for Valuation of Multiple Components of Site Quality:
The Recreation Value of Forest Management. Journal of Environmental Economics and Management, 21, 275-290.
Li, H., Gartner, D. I., Mou, P. and C. C. Trettin (2000) A Landscape Model (LEEMATH) to Evaluate Effects of Management
Impacts on Timber and Wildlife Habitat, Computers and Electronics in Agriculture, 7, 263-292.
Melville, N. P. (2010) Information Systems Innovation for Environmental Sustainability, MIS Quarterly, 34, 1, 1-21.
Mitchell, R. C. and Carson, R. T. (1989). Using Surveys to Value Public Goods: The Contingent Valuation Method, Washington,
DC: Resources for the Future.
Nute, D. et al. (2004) NED-2: an agent-based decision support system for forest ecosystem management, Environmental
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Pearce, D.W. (1993) Economic Values and the Natural World, Earthscan, London.
Rauscher, H. M. (1999) Ecosystem management decision support for federal forests in the United States: A review, Forest
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Rondeux, J. (1991) Management Information Systems: Emerging Tools for Integrated Forest Planning, Paper presented
international IUFRO Symposium on Integrated forest management information systems, October, Tsukuba, Japan.
Reynolds, K. M. (2005) Integrated Decision Support for Sustainable Forest Management in the United States: fact or fiction?
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Thomas, J.W. (1995). The forest service program for forest and rangeland resources: A long-term strategic plan, Draft 1995,
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