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that they can incorporate much more heterogeneity in the model, including differences in individuals and their behaviors.
Researchers define decision rules for particular subsets of agents (individuals)
and the proportion of agent types within a population. With environmental and
social conditions specified, the model simulates how agents react to changes in their
environments and the effects of their actions on the system. Behavioral heterogeneity can be incorporated by introducing multiple decision-making strategies, allowing for different responses by agents to changes in their environments. Interactions
between agents can also be modeled, allowing for agents’ behavior to be directly
impacted by the behaviors of other agents.
While the use of agent-based models to study behavior and adaptation in FEW
systems has allowed researchers to introduce different agent types with different
decision strategies, these models present additional challenges to researchers.
Because they are more flexible and allow for a greater variety of behaviors, the
amount and type of data needed to calibrate and verify these models is substantial
and may not always be available. In addition, the predicted outcomes of these models depend on the particular scenario, which may limit the generalizability of these
models and their usefulness for policy.
4.5 Case Studies: Key Adaptations and Their Implications
for FEW Systems
Two case studies are provided here as concrete examples of how accounting for
human behavior and adaptation can inform the study of FEW systems, and how
behavioral interventions can aid in FEW system management. The first case study
uses the example of eutrophication in the Great Lakes to demonstrate how behavioral heterogeneity can influence the adoption of fertilizer management strategies.
The second examines behavioral spillover, showing how the adoption of one FEWrelated behavior can lead households to engage in other FEW behaviors.
4.5.1 Case Study 1: Incorporating Behavioral Heterogeneity
into FEW System Models and Policies in the Lake Erie
Watershed
Harmful algal blooms (HABs) in Lake Erie provide an important example of how
misalignment of temporal and spatial scales may contribute to problems in FEW
systems (See Sect. 8.2.3 for material on HABs, and Sect. 12.3 for a discussion on
the spatial and temporal scales of FEW systems), and how they can be addressed by
interventions aimed at altering human behavior within these systems. HABs in Lake
Erie are a particularly negative example of eutrophication. They can be harmful to
animal and human health, and toxins from the algae have entered into cities’ water
M. Doidge et al.
that they can incorporate much more heterogeneity in the model, including differences in individuals and their behaviors.
Researchers define decision rules for particular subsets of agents (individuals)
and the proportion of agent types within a population. With environmental and
social conditions specified, the model simulates how agents react to changes in their
environments and the effects of their actions on the system. Behavioral heterogeneity can be incorporated by introducing multiple decision-making strategies, allowing for different responses by agents to changes in their environments. Interactions
between agents can also be modeled, allowing for agents’ behavior to be directly
impacted by the behaviors of other agents.
While the use of agent-based models to study behavior and adaptation in FEW
systems has allowed researchers to introduce different agent types with different
decision strategies, these models present additional challenges to researchers.
Because they are more flexible and allow for a greater variety of behaviors, the
amount and type of data needed to calibrate and verify these models is substantial
and may not always be available. In addition, the predicted outcomes of these models depend on the particular scenario, which may limit the generalizability of these
models and their usefulness for policy.
4.5 Case Studies: Key Adaptations and Their Implications
for FEW Systems
Two case studies are provided here as concrete examples of how accounting for
human behavior and adaptation can inform the study of FEW systems, and how
behavioral interventions can aid in FEW system management. The first case study
uses the example of eutrophication in the Great Lakes to demonstrate how behavioral heterogeneity can influence the adoption of fertilizer management strategies.
The second examines behavioral spillover, showing how the adoption of one FEWrelated behavior can lead households to engage in other FEW behaviors.
4.5.1 Case Study 1: Incorporating Behavioral Heterogeneity
into FEW System Models and Policies in the Lake Erie
Watershed
Harmful algal blooms (HABs) in Lake Erie provide an important example of how
misalignment of temporal and spatial scales may contribute to problems in FEW
systems (See Sect. 8.2.3 for material on HABs, and Sect. 12.3 for a discussion on
the spatial and temporal scales of FEW systems), and how they can be addressed by
interventions aimed at altering human behavior within these systems. HABs in Lake
Erie are a particularly negative example of eutrophication. They can be harmful to
animal and human health, and toxins from the algae have entered into cities’ water
M. Doidge et al.