The Role of FMIS in Sustainable Forest Management Practices – comparisons and future direction

1. 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

2. Introduction – functions of the forest • Forests can provide • Wood and fiber • outdoor recreation • stream flow • erosion control • atmospheric CO2 absorption • habitat and biodiversity protection • Estuaries and adjacent upland provide services for • 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 • 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

3. Introduction – change in forest management paradigm • Forestry initially designed DSS for timber, cultivation and pest management (Reynolds, 2005) • 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)

4. Introduction – ecological, social and economic information • 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) • Non-economic values are important in environmental economics(Adamowicz et al. 1998), values needed by resource managersfor decision-making (Englin et al. 1991) • Regardless of the approach taken, CSR or stakeholder accountability, decision-makers 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

5. 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

6. Three levels of organization in ecosystem management decision-making process Decision Environment (goals, values, constraints) Organization and Decision-making Processes Decision Support System user DSS software (social, economic, political and legal context) 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 Adapted from Rauscher, 1999

7. The decision environment Private landowners Industrial landowners Special interest Public Scientist & specialist • Divided by management and ecological subsystems • Network of decision-makers and stakeholders • different values, goals and constraints • Decision-makers (managers, specialists) determine objectives, evaluate risks and value • social, economic, political pressures • Values, goals and constraints are group negotiated • most difficult part of social process • As goals and conditions change, so can value • Stakeholder, public preferences, negotiation conflict management skills, and economic valuation • inclusive for understanding ecosystem management Group negotiation process Decision support tools Ecological assessment Ecosystem management DSS Managerial decision-makers Management subsystem Ecological subsystem Resources Neutral biophysical (Adapted from Rauscher, 1999)

8. Total Economic Value Use Values Non-Use Values Future direct and indirect use values Value of leaving use- and non-use values for future generations Value of knowledge of continued existence Direct consumption Functional benefits Forests- water, fish, timber, carbon store Agriculture- food crops, biomass energy Regulating services- flood 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 All services- habitat support Irreversible change- Future damages from global warming Supporting services - endangered species (panda, blue whale, eagle No benefit expectation Direct Use Values Indirect Use Values Option Values Bequest Values Existence Values Values become increasingly intangible http://environmentaleconomics.wordpress.com/2010/05/02/valuation-http://www.slidefinder.net/v/valuation_the_contingent_valuation_method/3190400; (Pearce 1993; Bateman et al., 2003)

9. Economic Valuation Techniques Adapted from Mitchell and Carson (1989)

10. Economic Valuation Techniques • Direct Observational Methods • 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 • Direct Hypothetical Methods • 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 • 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 • 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

11. Results – comparisons of six forest ecosystem DSS 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

12. Conclusions • 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 • 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

13. Conclusions • 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 • 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 decision-making and stakeholder negotiation, and increase forest ecosystem sustainability

14. References • 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 Modelling & Software, 19, 831–843. • 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 Ecology and Management, 114, 173-197. • 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? Computers and Electronics in Agriculture, 49, 6–23. • Thomas, J.W. (1995). The forest service program for forest and rangeland resources: A long-term strategic plan, Draft 1995, RPA Program, USDA Forest Service, Washington, DC.