Qualitative System Modeling
Sarah Hope, MS
2025-04-22
Why Model Systems?
“Next generation FEPs can advance EBFM in the United States.” (Marshall et al. 2018) - complex systems, limited data - explore structures and relationships - uncover indirect effects between components - co-produce knowledge across sectors - couple qualitative models with quantitative data
Why Model Systems?
Bennett et al. (2021)
Methods & Theory
- C. J. Puccia and R. Levins. 1986. Qualitative Modeling of Complex Systems: An Introduction to Loop Analysis and Time Averaging. Harvard University Press, Cambridge, MA.
- R. Levins. 1974. “The qualitative analysis of partially specified systems.” Annals of the New York Academy of Sciences, 231: 123–138.
- Levins, R. (1998). The internal and external in explanatory theories. Science as Culture, 7(4):557582.
Dambacher et al. (2003)
- Outlines methods for qualitative predictions in model ecosystems
- Introduces weighted predictions and sign determinacy
Melbourne-Thomas et al. (2012)
- Uses Bayesian framework to evaluate qualitative network model uncertainty
- Aims to address under-explored questions of model structure uncertainty
Fulton (2021)
- Highlights constraints from outdated fisheries paradigms
- Suggests a shift post-COVID-19 towards modern, behaviorally informed models
DePiper et al. (2021)
- Describes collaborative modeling with stakeholders for EBM
- Built conceptual model for Fluke
- Emphasized scoping and integrated management questions
Trade-offs of Qualitative Modeling
Benefits - investigate feedbacks within and between systems - no need for extensive ecosystem data - predict system repsonses to change - co-produce knowledge
Challenges - finding balance between robustness and functionality - complex systems can grow dramatically with small changes - takes time and willing collaboration
Tallis et al. (2010)
Breaks down EBM implementation using real-world case studies that start by asking: - What data is available to describe the system? - What kind of governance is at play in this system? - How much time do managers have to plan implementation?
Integrated Ecosystem Assessment (IEA)
Integrated Ecosystem Assessment (IEA)
- Scoping
- Defining Indicators
- Setting Thresholds
Integrated Ecosystem Assessment (IEA)
- Risk Analysis
- Management Strategy Evaluation
- Monitoring
- Evaluation
Wildermuth et al. (2018)
Model Alternatives & Responses - Model Complexity “sweet spot”
Washington CMAC Workshop (2021)
- Evaluated kelp forest and seafloor systems under new use/climate scenarios
- Assessed outcomes for aquaculture, wind farms, and seabed mining
- Identified key network elements and recommends monitoring strategies
Other Current Applications
- Haraldsson et al. (2020) {.small}
- Models social-ecological systems (SES) for wind farm impacts
- Shows the importance of social compensation
- Reum et al. (2015) {.small}
- Uses qualitative network models for shellfish aquaculture impact prediction
- Highlights trade-offs and indirect effects of ocean acidification
Markets into Models
![]()
Try it yourself!
- QPress Package in R
- (Snowshoe Hare Example)[https://swotherspoon.github.io/QPress/]
more theory & frameworks
- Stephenson & Hobday (2024)
- Offers a practical blueprint for blue economy implementation
- Winther et al. (2020)
- Reiterates need for Integrated Ocean Management (IOM)
- Rudolph et al. (2020)
- Applies transition theory to ocean governance reform
- Promotes niche innovations and systems adaptation
- Marasco et al. (2007)
- Provides actionable advice for implementing EBFM
more theory & frameworks
- Holsman et al. (2017)
- Presents an ecosystem-based risk assessment (ERA) framework
- Focuses on cumulative impacts, uncertainty, and data-poor contexts
- Stephenson et al. (2017)
- Recommends integrating social, economic, institutional factors
- Provides practical steps for multidisciplinary fisheries policy
- Winther et al. (2020)
- Advocates for Integrated Ocean Management
- Links sustainability goals with a unified management approach
