Modeling Biocomplexity - Actors, Landscapes and Alternative Futures

Envisioning Future Landscape TrajectoriesUsing Multiagent-based models to Simulate Dynamics of Landscape ChangeJohn BolteBiological & Ecological Engineering DepartmentOregon State University

Landscape Planning and Simulation ModelsThe future is uncertainThe future is certain to comeWe have little control over much of what will happenWe have substantial control over some aspects of what will happenThe choices we make today will affect the choices we have tomorrow

Simulation models that project the future outcomes of different possible actions are particularly useful when the system is complex, relationships are poorly understood, or uncertainties are highHow can we use simulation models in landscape planning to help people achieve desirable futures? Why models? Types and usesPhysical model a literal representation of something, generally in miniature, to show its construction or appearance.Conceptual model a simplified, abstract representation of a system or phenomena, typically of its components and the relationships among them. Commonly used to illustrate, explore or explain current understanding and gaps in understanding of a system and/or to generate hypotheses about how the system works.Quantitative model a model that uses numeric representations of system components and interactions among them to produce quantitative outcomes from quantitative inputs.In the most general sense, a model is anything used in any way to represent anything elseFIX4Quantitative Models Empirical model a quantitative model based on empirical observations rather than on mathematically describable relationships of the system modeled.Statistical model a quantitative formalization of relationships between variables in the form of mathematical equations.Mechanistic model a model that uses cause and effect logic to describe the behavior of a system.Simulation model a computer program which attempts to simulate the behavior of a particular system. May be used to project the outcomes of specified interactions and to test the consequences of different actions or scenariosSpatially explicit model a model that represents the behavior of a physical system, including the spatial relationships among its components. Multiagent-based model a model that represents the behaviors of one or more actors in a system.

FIX5Building ModelsThe essence of simulation models is to incorporate critical/dominant system features so that projections of the consequences of different scenarios can be made with some desired level of accuracy in representing likely real-world outcomes.All models are wrong, but some are useful.Box, G.E.P. 1976. Science and Statistics. Journal of the American Statistical Association 71: 791-799.

FIX6Alternative Futures ModelingExamine multiple scenarios of trends and assumptions about future conditions, generally using one or more models of change, Assist in incorporating stakeholder interactions to define goals, constraints, trajectories, drivers, outcomesAllow visualization of the results in a variety of types and formatsUltimately are intended to assist in improving land management decision-makingTrajectories of Change and Alternative Futures

Source: Hulse et al. (2008), modified from Shearer (2005)Some scenario concerns:Agency and the futureIdentifying possible futuresAspects of uncertaintyScenario logic

8Approach: Multi-agent ModelingBased on modeling behavior and actions of autonomous, adaptive agents (actors)Our approach: spatially explicit, represents land management decisions of entities (actors) with authority over parcels of landActor decisions implemented through policies that guide & constrain potential actionsAutonomous processes (e.g. succession) simultaneously modeledvalues attitudes actionA General Theory of Action(Parsons and Shils 1951)Systems

PersonalitySocialCultural values are abstract concepts, but not so abstract that they cannot motivate behavior. Hence, an important theme of values research has been to assess how well one can predict specific behavior knowing something about a persons values (Karp 2001:3213). Actorvalues attitudes behaviorbeliefs plan actionnorms desiresgoals intentionsComplex Theory of Action Systems

personalitysocialculturaleconomicbiophysical Iinformation/matter/energyContext = difficulty, time, expenseDriversEnvision Conceptual StructureLandscapeFeedbacksLandscapeFeedbacksActors Decision-makers managing the landscape by selecting policies responsive to their objectivesPolicies

Fundamental Descriptors of constraints and actions defining land use management decisionmakingScenarioDefinitionAutonomous Change ProcessesModels of Non-anthropogenic Landscape ChangeLandscape Production ModelsGenerating Landscape Metrics Reflecting Ecosystem Service ProductionsMultiagent Decision-makingSelect policies and generate land management decision affecting landscape pattern

Landscape Spatial Container in which landscape changes, ES Metrics are depictedENVISION Triad of RelationshipsPoliciesIntentionsActorsValuesLandscapesMetrics of ProductionProvide a common frame of referencefor actors, policies and landscape productionsGoalsEconomic ServicesEcosystem ServicesSocio-cultural ServicesPolicy DefinitionLandscape policies are decisions or plans of action for accomplishing desired outcomes.

from:Lackey, R.T. 2006. Axioms of ecological policy. Fisheries. 31(6): 286-290.

Policies in ENVISIONPolicies are a decision or plan of action for accomplishing a desired outcome; they are a fundamental unit of computation in EvolandDescribe actions available to actorsPrimary Characteristics:Applicable Site Attributes (Spatial Query)Effectiveness of the Policy (determined by evaluative models)Outcomes (possible multiple) associated with the selection and application of the PolicyExample: [Purchase conservations easement to allow revegetation of degraded riparian areas] in [areas with no built structures and high channel migration capacity] when [native fish habitat becomes scarce]Models in ENVISIONModels are plug-ins of two types:Autonomous Processes: Represent processes causing landscape changes independent of human decision-making e.g. climate change, vegetative succession, forest growth, fire, flooding, ??? Evaluative Models Generate production statistics and report back how well the landscape is doing a producing metrics of interest e.g. carbon sequestration, habitat production, land availability, risk, ???Actors in EnvisionActors are entities that make decisions about landscape changeAny number of actors can be defined ( 0-???)Actors can be defined in terms of A set of IDU attributesPrescribed areas on the landscapeRandomlyEach IDU is controlled by at most one Actor

Actors in Envision (continued)Actors have values that influence their decision-making behaviors. These values reflect landscape productions

Actors make choices about landscape management by selecting policies based on some combination of:Internal Values relative to Policy IntentionsLandscape Feedbacks/Emerging Scarcities (dynamically generated during a run)Global Policy Preferences (defined by scenario)Actor Decision-makingStep 1: For each location and each time step, collect all relevant policies based on site attributesStep 2: Score the policies with respect to:1) How well the policy intentions align with the actors on values (Self-interest)

2) How well the policies align with emerging landscape scarcities (Altruistic)3) a global preference for the policy that can be defined conditionally4) a scenario-specific preference for the policy5) where an lives on a Self-Interest/Altruism scaleStep 3: Stochastically select a policy based on a multicriteria score reflecting the above factorsActor Associations in EnvisionActor associations are collections of actors, defined in one of three ways, based on:a common landscape attribute or set of attributescommon valuesSpatial proximityAssociations influence an actors decision-making process by modifying the actors valuesIn theory, Envisionss actor decision-making can be influenced by their group affiliations, but in fact weve never done anything with this.ENVISION Actor Properties PropertyMeaningEnvisionReactiveResponds to environmentYesAutonomousControls own actionsYesSocialInteract with other actors Sort ofGoal-orientedMore than responsive to environment YesTemporally continuousAgent behavior continuousOnce/stepCommunicativeCommunicates with other agentsSort OfMobileCan transport self to other locationsNoFlexibleActions not scriptedYesLearningChanges based on experienceNoCharacterBelievable personality or emotionsNoAdapted from Benenson and Torrens (2004:156)Inferring Values from Actions: Votes on 1998 Environmental Ballot MeasuresBallot MeasureStatewideStatewide Percent YesLane County Percent YesYes VotesNo Votes56 (notification)874547212737807364 (timber)215491897535192166 (parks & salmon )7420383622476770Definition of value categories including descriptive terms and text examples.

Value CategoryDescriptive TermsEconomicreflecting economic production of the landscape, job activity, productivity, opportunities for capital production and revenue generation Property Rightsconcern is with the freedom to own and use private property as a landowner desiresEcosystem Healthecological health, diversity of the landscape, environmental protection and restorationNonmarket reflecting aesthetics, scenic integrity, beauty, spiritual, future generations, right thing to do, undiscovered utility, learning about and gaining connection with the environmentFairness refers to actor perceptions about economic justice, winners and losers, fears about litigation and its costs; unfair policies force an actor to do something she does not want to do Credibility refers to policies are justified by scientific or other expertise, or to policies that lack scientific or support by other expertiseSafetyconcerned with human safety in jobs and activites, from chemicals, from natural hazardsRecreationemphasis on any type of recreational activity that could be helped or hurt by passage of the ballot measure.MEASURENo Eco-nomic

%Pri-vate prop-ertyrightsEco-system health

%Non-mar-ket

%Fair-ness

%Credi-bility

%Safe-ty

%Recre-ation

%Notification967630151001500Timber - Pro20730935528307735Timber - Con29743552133851153Salmon & Parks218438452166371Value Frequencies in Ballot Measures

Integrated Decision Units (IDUs)

A spatial geometry to model both human decisions and successional processesEach IDU described in GIS by a set of attributes used to model climate effects, succession, wildfire and decisions

ENVISIONMean Age at HarvestCarbon SequestrationForest Products ExtractionHarvested AcreageFish Habitat (IBI)Resource Lands ProtectionEvaluative ModelsData SourcesAutonomous ProcessModelsParcels (IDUs)Rural Residential ExpansionPolicy Set(s)Agent DescriptorsVegetative Succession Climate ChangeEnvision Andrews ApplicationEnvision Andrews - ScenariosConservation - no Climate ChangeDevelopment - no Climate ChangeConservation - with Climate ChangeDevelopment - with Climate ChangeEnvision Andrews Study Area

Scenario Results Forest Carbon

Scenario Results Forest Product Extraction

Scenario Results Fish IBI

ENVISIONImpervious SurfacesWater Quality/Loading (SPARROW)Nearshore Habitat (Controlling Factors Model)Resource Lands ProtectionEvaluative ModelsData SourcesAutonomous ProcessModelsIDUs GSU/LULC/Rural/Urban DevelopmentPolicy Set(s)Agent DescriptorsExpansion of Nearshore ModificationsPopulation GrowthResidential Land SupplyINVEST Tier 1 CarbonEnvision Puget Sound ApplicationEnvision Puget Sound- ScenariosStatus Quo continue current trendsManaged Growth adopt a suite of additional policies aimed at conserving/restoring habitats, protecting resource lands, emphasizing denser development pattern near urban areasUnconstrained Growth allow lower density patterns, less habitat protection, less resource land protection

Puget Sound

South Sound

Bainbridge Island

Ferry Terminal Area

more info at:

http://envision.bioe.orst.edu