Adaptive Integrated Framework (AIF):Adaptive Integrated Framework (AIF):a new methodology for a new methodology for

managing impacts of multiple stressors in coastal managing impacts of multiple stressors in coastal ecosystemsecosystems

A bit more on AIF, A bit more on AIF, project componentsproject components

and timelinesand timelines

Solutions for adequately dealing with the impacts of multiple stressors will require novel approaches for understanding the dynamics of the ecosystem as well as appropriately assessing the costs and benefits of alternative management practices.

The complexity* and uncertainty of multiple interacting stressors makes planning and management very difficult for those tasked with balancing multiple and often competing stakeholder concerns in coastal ecosystems. *Complexity: Nonlinearities. Synergies. Alternative stable states

Anthropogenic stressors, especially “new” stressors such as invasive species, contaminants, land-use and global climate change, can cause unforeseen, devastating consequences even in ecosystems with well-defined management strategies to alleviate stressor impacts.

… managers are usually faced with limited resources to sample the ecosystem for maximum benefit to management decision making.

Project

Justificatio

n

Modeling synthesisModeling synthesis

Ecosystemdrivers

Ecosystemdrivers

Ecosystem characterization (data)

Scientific evaluation

&Stakeholderassessment

B) Guidance for future management actions

A) Guidance for future empirical efforts

Adaptive Integrative Framework (AIF) approach.

Project Goal

Modeling synthesisModeling synthesis

Ecosystemdrivers

Ecosystemdrivers

Ecosystem characterization (data)

Scientific evaluation

&Stakeholderassessment

B) Guidance for future management actions

A) Guidance for future empirical efforts

Adaptive Integrative Framework (AIF) approach.

• AIF incorporates a series of feedback loops between experimental scientists, modelers, agency managers, and the public for developing management tools and programs as well as monitoring impacts.• Multidirectional exchange of information between agency managers, modelers, experimental scientists, and interested stakeholders will improve and optimize management strategies, model development, and program monitoring. • Continuously evaluates the development and implementation of ecosystem models, experimental results, and management actions. • Includes individual models, experimental protocols, and human dimension research

AIF

Highlights

Adaptive Integrative Framework (AIF): Merging of Adaptive Management (AM) and Integrated Assessment (IA).

Adaptive ManagementSummary:• AM is based on the tenet that management actions in ecosystems may be

treated as ecosystem-scale experiments capable of generating new information for updating and improving management decisions

• AM uses an iterative approach with continuous feedback between management actions and scientific understanding of observed changes.

Gaps:• AM typically lacks a rigorous short-term framework for facilitating and

interpreting feedback, thereby confounding the true integration of scientific investigation and ecosystem management.

• integration is often complicated by divergent expectations and goals of multiple researchers and managers.

AIF: • Managers and researchers are both engaged in a mutually beneficial

process that allows for short-term assessment of specific environmental issues and long-term management of ecosystems.

Adaptive Integrative Framework (AIF): Merging of Adaptive Management (AM) and Integrated Assessment (IA).

Integrated Assessment Summary:• IA involves a multi-step process for assessing the status of key ecosystem

properties and characteristics; making and testing quantitative predictions (including an explicit assessment of uncertainty) of how ecosystems will respond to specific stressors; and developing technical guidance based upon such predictions

• IA is a linear approach which facilitates the integration and analyses of diverse ecosystem data and subsequent communication with key stakeholders.

Gaps:• IA alone fails to provide a rigorous framework for data synthesis and analysis

efforts to guide future data acquisition and adaptive management actions.• In most cases development and parameterization of ecosystem models are

based on ad hoc collections of data (i.e., data collected for some other purpose) which results in modeling syntheses that are linear processes--first, data collection and then modeling synthesis.

AIF: • AIF will incorporate adaptive process on IA so explicit uncertainty and

sensitivity of model outputs can provide the basis for future monitoring and experimental efforts.

Fishproduction

Regionaleconomics

Human

health

Predictions

Project Components

Land useInvasivespecies

Climate

change

Multiple

stressors

Project Components

Process-BasedSAGEM & SB-IBM

Bayesian

ProbabilityNeural Networks

Retrospective

Statistical Analysis

4 Modelingapproaches

Project Components

ModelUncertainty

Model

Comparison

Model

Feedback

Model

Evaluation

Project Components

Hydrodynamicmodel

Historical data

collection

Watershed

nutrient loading

Ecosystemcharacterization

Project Components

Project Components

Fieldmonitoring

Experiments

Data

reclamationField datacollection

EconomicAssessment

Public support

assessment

Management-

Research Workshops

Socio-EconomicFactors

Project Components

Process-BasedSAGEM & SB-IBM

Bayesian

ProbabilityNeural Networks

Retrospective

Statistical Analysis

4 Modelingapproaches

ModelUncertainty

Model

Comparison

Model

Feedback

Model

Evaluation

Hydrodynamicmodel

Historical data

collection

Watershed

nutrient loading

Ecosystemcharacterization

EconomicAssessment

Public support

assessment

Management-

Research Workshops

Socio-EconomicFactors

Land useInvasivespecies

Climate

change

Multiple

stressors

Fishproduction

Regionaleconomics

Human

health

Predictions

Project Components

Fieldmonitoring

Experiments

Data

reclamationField datacollection

Coupled bio-physical 3D

models

Empirically based

(Bayesian)

Empirically based

(Bayesian)

Simple statistical (e.g.

regression)

Simple statistical (e.g.

regression)

Artificial Neural

network

EcosystemStressors

Ecos

yste

m

Mod

els

Ecosystem Characterization

Fish community dynamics

Water quality &

Human health

Ecos

yste

m

endp

oint

s

• Land & Resource use

• Climate Change• Invasive Species

• Watershed model• Hydrodynamic model• Biophysical data and

processes

Recommendations for ecosystem characterization•Experimental•Monitoring•Synthesis

Socio-economic integration to guide management•Economic models•Public preference •Workshops

FLAVOR

• We don’t know what we are examining in the field a priori adaptive framework.

• The problems we examine will be guided by management/stakeholder input, and the factors we measure will be guided by modeling yet to be done.

Spring

Summer

Fall

Spring

Summer

Fall

Spring

Summer

Fall

Spring

Summer

Fall

Spring

Summer

2008

2009

2010

2011

2012

ModelingField

surveyField

ExperimentsData

Collection*

* Data collection: Hydrodynamics, historical data, hydrology, land use, human dimensions

Nov: Presentneeds

Nov: Presentneeds

Low level

Intense

Intermediate

Intense

No

Yes

No

Yes

Stakeholder workshops

Workshop

Workshop

Workshop

Workshop