Citation:

Fergus, E., P. Ringold, Ryan A Hill, J. Renee Brooks, Phil Kaufmann, A. Herlihy, AND R. Mitchell. Structural equation models: An analytic framework to connect aquatic resource data, management scenarios, & resource valuation? Joint Aquatic Sciences Meeting, Grand Rapids, Michigan, May 14 - 20, 2022.

Impact/Purpose:

Key to developing effective environmental policy is assessing how candidate policies affect human well-being and valuation. NCEE in collaboration with OW and ORD seek to examine these relationships as mediated through aquatic ecosystems. Disentangling these complex relationships is challenging without appropriate analytic frameworks. We propose using a structural equation modeling (SEM) framework to evaluate and quantify the pathways in which natural and anthropogenic factors affect aquatic condition. We applied SEM to evaluate hypothesized watershed, riparian, and in-stream factors in affecting stream biotic condition using the US EPA National Rivers and Streams Assessment and StreamCat datasets. This information is a necessary component to bridge the gap linking management actions to ecosystem condition, and future work will expand to incorporate human valuation. The SEM framework is a promising analytic approach to leverage broad-scale data to develop mechanistic understanding of management effects on ecosystem condition.

Description:

Aquatic resource management faces the challenge of developing ecologically relevant practices while managing diverse water bodies distributed across the landscape. Large-scale monitoring programs provide a wealth of information to assess aquatic ecosystem condition at broad spatial extents but converting this information into mechanistic understanding of the factors that drive ecosystem health can be challenging. Structural equation models (SEM) are a powerful analytic approach to evaluate and quantify the complex pathways in which natural and anthropogenic factors affect aquatic condition and offer promise to bridge the information gap between aquatic monitoring data and management needs. We applied an SEM framework to examine hypothesized watershed, riparian, and in-stream factors affecting macroinvertebrate integrity in US streams using the US EPA National Rivers and Streams Assessment and StreamCat datasets to support economic valuation analyses. We explore the potential for riparian best management practices to protect streams by quantifying the relative effects of riparian land cover on the condition of instream habitat and biota across different landscape settings. Model results showed ecoregional differences in the pathways by which hypothesized factors affected stream macroinvertebrate integrity. These findings illustrate the need for systems-level analytic approaches, like SEM, to disentangle the complex pathways in which natural and anthropogenic factors affect aquatic ecosystems from data collected at broad spatial scales. Although SEM provides a mechanistic framework to assess the effectiveness of management practices on aquatic ecosystem health, additional work will be needed to synthesize SEM models with management scenarios and economic valuation studies.

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