Atlantic menhaden (Brevoortia tyrannus) support the largest fishery by volume on the United States East Coast, while also playing an important role as a forage species. Managers’ and stakeholders’ increasing concerns about the impact of Atlantic menhaden harvest on ecosystem processes led to an evolution in the assessment and management of this species from a purely single-species approach to an ecosystem approach. The first coastwide stock assessment of Atlantic menhaden for management used a single-species virtual population analysis (VPA). Subsequent assessments used a forward projecting statistical catch-at-age framework that incorporated estimates of predation mortality from a multispecies VPA while analytical efforts continued toward the development of ecosystem models and explicit ecological reference points (ERPs) for Atlantic menhaden. As an interim step while ecosystem models were being developed, a series of ad hoc measures to preserve Atlantic menhaden biomass for predators were used by managers. In August 2020, the Atlantic States Marine Fisheries Commission formally adopted an ecological modeling framework as a tool to set reference points and harvest limits for the Atlantic menhaden that considers their role as a forage fish. This is the first example of a quantitative ecosystem approach to setting reference points on the United States Atlantic Coast and it represents a significant advance for forage fish management. This case study reviews the history of Atlantic menhaden stock assessments and management, outlines the progress on the current implementation of ERPs for this species, and highlights future research and management needs to improve and expand ecosystem-based fisheries management.

Atlantic menhaden is an important forage fish and the target of the largest fishery along the US East Coast by volume. Since 1999, managers at the Atlantic States Marine Fisheries Commission, stakeholders, and scientists have been interested in developing ecological reference points (ERPs) that account for menhaden’s role as a forage species. To accomplish this, we developed a suite of modeling approaches that incorporated predation on menhaden and changes in productivity over time and allowed for evaluation of trade-offs between menhaden harvest and ecosystem management objectives. These approaches ranged in complexity, from models with minimal data requirements and few assumptions to approaches with extensive data needs and detailed assumptions. This included a surplus production model with a time-varying intrinsic growth rate, a Steele-Henderson surplus production model, a multispecies statistical catch-at-age model, an Ecopath with Ecosim (EwE) model with a limited predator and prey field, and a full EwE model. We evaluated how each model could address managers’ objectives and compared outputs across the approaches, highlighting their strengths, weaknesses, and management utility. All models produced estimates of age-1 + biomass and exploitation rate that were similar in trend and magnitude to the single-species statistical catch-at-age model, especially in recent years. While the less complex models were relativity easy to implement and update, they lacked key elements needed to manage multiple species simultaneously. More complex models required a wider array of data and were more difficult to update within the current management time-frames, but produced a more useful framework for managers. Ultimately, an EwE model of intermediate complexity coupled with the existing single-species assessment model was recommended for use in management.

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Invasive species management can be a victim of its own success when decades of effective control cause memories of past harm to fade and raise questions of whether programs should continue. Economic analysis can be used to assess the efficiency of investing in invasive species control by comparing ecosystem service benefits to program costs, but only if appropriate data exist. We used a case study of water hyacinth (Eichhornia crassipes (Mart.) Solms), a nuisance floating aquatic plant, in Louisiana to demonstrate how comprehensive record-keeping supports economic analysis. Using long-term data sets, we developed empirical and spatio-temporal simulation models of intermediate complexity to project invasive species growth for control and no-control scenarios. For Louisiana, we estimated that peak plant cover would be 76% higher without the substantial growth rate suppression (84% reduction) that appeared due primarily to biological control agents. Our economic analysis revealed that combined biological and herbicide control programs, monitored over an unusually long time period (1975–2013), generated a benefit-cost ratio of about 34:1 derived from the relatively modest costs of $124 million ($2013) compared to the $4.2 billion ($2013) in benefits to anglers, waterfowl hunters, boating-dependent businesses, and water treatment facilities over the 38-year analysis period. This work adds to the literature by: (1) providing evidence of the effectiveness of water hyacinth biological control; (2) demonstrating use of parsimonious spatio-temporal models to estimate benefits of invasive species control; and (3) incorporating activity substitution into economic benefit transfer to avoid overstating benefits. Our study suggests that robust and cost-effective economic analysis is enabled by good record keeping and generalizable models that can demonstrate management effectiveness and promote social efficiency of invasive species control.