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Opportunity at National Oceanic & Atmospheric Administration (NOAA)

Ecosystem Indicators


National Marine Fisheries Service, Southwest Fisheries Science Center

RO# Location
26.03.37.C0316 La Jolla, CA 92038


Name E-mail Phone
Thompson, Andrew Richard 858-546-7132


Fish stocks do not live isolated from an ecosystem, but are part of it. Their productivity is intrinsically related to the dynamics of their predators and prey and environmental conditions as well as human pressures. This is particularly evident in the California Current where boom-bust cycles of forage fish species occur even in the absence of fishing, and where changes in forage dynamics lead to prey switching behavior in top predators, with unexpected consequences for target or protected species. Managers and stakeholders in the region now recognize that management actions taken at a single species level have ecosystem-level impacts. The Pacific Fishery Management Council (PFMC) has developed a Fishery Ecosystem Plan (FEP) that outlines the need for a more ecosystem-based approach to fisheries to answer questions such as how reductions of forage fish populations affect protected and target species that prey on them. Achieving such ecosystem-level objectives requires development of indicators for ecosystem status that may be different from the population status estimates routinely developed for actively managed fish stocks.

The NOAA’s California Current Integrated Ecosystem Assessment (CCIEA) Team produces an annual State of the California Current Report, which outlines status and trends of a variety of indicators, from ocean drivers to human wellbeing. However, such indicators have yet to be integrated into management decisions. Recently, the PFMC concluded a “Coordinated Ecosystem Indicator Review Initiative” to assess how these indicators can better inform management actions. Indicators need to be linked to decision rules to be of practical use to management. This project aims to build upon the CCIEA indicators and their Review Initiative and explore methods for integrating ecosystem indicators into the management process by developing experimental novel ecosystem-based decision rules for the California Current ecosystem. Uncertainty and natural variability associated with indicators also pose a challenge to their adoption in management frameworks, with the potential for overconfidence in their predictive power if uncertainty is not adequately quantified. Here, a management strategy evaluation (MSE) will be employed to formally assess the robustness of decision rules to a range of uncertainties, including process error due to natural variability. We define ecosystem indicators as measures of the state and trends of ecosystem attributes (e.g. sea lion productivity, community structure, labor returns) relevant to management objectives. These are separate from pressure indicators which specify the state of environmental drivers (e.g. upwelling) or human (e.g. fishing mortality) pressures on the ecosystem. The two types of indicators, however, are linked in the establishment of ecosystem-based decision rules, since an understanding of how and at what levels human pressures lead to significant changes in ecosystem indicators given particular environmental pressures is required to set trigger points for management actions. 

To better link ecosystem indicators to management, we anticipate the scholars will pursue the following objectives for their postdoctoral research:

1.           Define, in cooperation with stakeholders, a set of ecological and socioeconomic operational objectives for the California Current. These are a description of what we want to maximize, minimize or optimize. Examples may be trophic productivity, predator viability, or economic viability of coastal communities.

2.           Identify ecosystem indicators that would verify if the objectives defined above are met. Examples could be estimates of population status, indices of predation removals, energy flow to top predators, or availability of markets for new fishery products.

3.           For each indicator that can be developed using existing capabilities, develop triggers (e.g. reference points) for management action. These would specify index thresholds or trends that would prompt a management action.

4.           Develop novel ecosystem-based decision rules based on the proposed indicators and trigger points. Decision rules would have three parts to them: an assessment of the status of indicators, identification of the desired status, and a description of what corrective actions need to be taken to reach the desired status. Such action may be a change in total system catch, spatial allocation of catch, or in the exploitation of specific species groups. They may also incentivize development of new markets, reallocate capital, or introduce new fishing techniques.



Thompson AR, Harvey CJ, Sydeman WJ, Barcelo C, Bograd SJ, Brodeur RD, Fiechter J, Field JC, Garfield N, Good TP, Hazen EL, Hunsicker ME, Jacox MG, Leising A, Lindsay J, Melin SR, Santora JA, Schroeder ID, Thayer JA, Wells BK, and Williams GD 2019. Ecological indicators of the status and trends of the pelagic forage community in the California Current Large Marine Ecosystem, 1998-2016. Ecological Indicators 105: 215-228.

Thompson AR and 36 coauthors. 2018. State of the California Current 2017-18: Still not quite normal in the north and getting interesting in the south. CalCOFI Reports 59: 1-66.

Thompson AR, Chen DC, Guo LW, Hyde JR and Watson W. 2017. Larval abundances of rockfishes that were historically targeted by fishing has increased in a large marine protected area over 16 years. Royal Society Open Science 4:170639

Integrated ecosystem assessment; California Current Ecosystem; fisheries management; ecosystem management


Citizenship:  Open to U.S. citizens, permanent residents and non-U.S. citizens
Level:  Open to Postdoctoral and Senior applicants


Base Stipend Travel Allotment Supplementation
$56,000.00 $2,000.00

Experience Supplement:
Postdoctoral and Senior Associates will receive an appropriately higher stipend based on the number of years of experience past their PhD.

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