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What is Ecosystem Based
Fishery Management?

Marine Resource Education Program
Science Workshop, February 2024

Sarah Gaichas
NOAA Northeast Fisheries Science Center

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What do you think EBFM means?

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US Policy defines EBFM as:

A systematic approach to fisheries management in a geographically specified area that contributes to the resilience and sustainability of the ecosystem; recognizes the physical, biological, economic, and social interactions among the affected fishery-related components of the ecosystem, including humans; and seeks to optimize benefits among a diverse set of societal goals.

relating environment marine habitat and the marine community to human activities social systems and objectives

https://www.fisheries.noaa.gov/resource/document/ecosystem-based-fisheries-management-policy

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EBFM Guiding Principles

Five supporting EBFM steps to maintain resilient ecosystems

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What is ecosystem information?

An indicator tells us something about where we are relative to our goals or to limits, or about the context we are working within that may affect achieving our goals.

bank account balance, speedometer, weather warning

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as a big umbrella that can include many types of information A quick definition of ecosystem indicators, why they’re useful, and broad categories (e.g. climate, oceanographic, habitat, primary productivity, ecosystem services, human dimensions, etc.)

What is ecosystem information? Performance relative to objectives

An indicator tells us something about where we are relative to our goals or to limits, or about the context we are working within that may affect achieving our goals.

Stock status

Commercial Revenue and Recreational Effort

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What is ecosystem information? Context, risks to meeting objectives

An indicator tells us something about where we are relative to our goals or to limits, or about the context we are working within that may affect achieving our goals.

bottom temperatureblack sea bass survey distribution change over time from 2018 SOEoffshore wind

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Documenting and sharing ecosystem information

ecosystem reports, assessments, and overviews

SOE cover MAFMC

fishery overviews, cooperative research, working groups

Study Fleet

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Pathways for documenting and sharing ecosystem information ESRs and what they can do (e.g. synthesize, provide context, help formulate hypotheses and questions, support communication, potentially inform specific decisions) Other vehicles (e.g., some regions that don’t yet have regular ESRs have mentioned SAFE reports, fishery performance reports, and others). *Don’t worry about being comprehensive here – in the discussion that follows this talk we’ll be asking people how they receive ecosystem information.

(Jones, et al., 2022)

Entry points for ecosystem information: where to start?

Management decisions

  1. What are our issues and goals? Key question. Start here
  2. Current decisions
    • Stock assessments
    • Advice on catch levels
    • Harvest control rules
  3. New (current) decisions
    • Habitat change or restoration
    • Changing species distribution and interactions
    • Tradeoffs between fisheries
    • Tradeoffs between ocean use sectors

Methods and tools

  1. Stakeholder engagement, surveys, strategic planning
  2. Add information to current process
    • Ecosystem ToRs and overviews
    • Risk or uncertainty assessments
    • Management strategy evaluation
  3. Integrate across current processes
    • Risk assessment
    • Conceptual models
    • Scenario planning
    • Management strategy evaluation
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A basic orientation to ecosystem on-ramps – (however you would organize this) – e.g. assessments inputs, context for decision-making, risk assessment and identifying priorities, and less concrete pathways too – having a shared vocabulary, formulating questions or research priorities

Many options and entry points for a systematic ecosystem approach

Fishing icon made by EDAB       Fishing industry icon made by EDAB       Multiple drivers icon made by EDAB       Spiritual cultural icon made by EDAB       Protected species icon made by EDAB

Climate icon made by EDAB       Stock assessment icon made by EDAB       Ecosystem reorganization icon made by EDAB       Wind icon made by EDAB

Hydrography icon made by EDAB       Phytoplankon icon made by EDAB       Forage fish icon made by EDAB       Apex predators icon made by EDAB       Other human uses icon made by EDAB

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State of the Ecosystem (SOE) reporting

Improving ecosystem information and synthesis for fishery managers

  • Ecosystem indicators linked to management objectives

    • Contextual information
    • Report evolving since 2016
    • Fishery-relevant subset of full Ecosystem Status Reports

  • Open science emphasis

  • Used within Mid-Atlantic Fishery Management Council's Ecosystem Process

    • Risk assessment
    • Conceptual modeling
    • Management strategy evaluation (MSE)

2023 SOE Mid Atlantic Cover Page

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(DePiper, et al., 2017) (Bastille, et al., 2021) (Muffley, et al., 2021) (Gaichas, et al., 2018) (DePiper, et al., 2021)

State of the Ecosystem Summary 2023:

Performance relative to management objectives

Seafood production decreasing arrow icon, below average icon icon

Profits decreasing arrow icon, below average icon icon

Recreational opportunities: Effort increasing arrow icon above average icon icon; Effort diversity decreasing arrow icon below average icon icon

Stability: Fishery no trend icon near average icon icon; Ecological mixed trend icon near average icon icon

Social and cultural, trend not evaluated, status of:

  • Fishing engagement and reliance by community
  • Environmental Justice (EJ) Vulnerability by community

Protected species:

  • Maintain bycatch below thresholds mixed trend icon meeting objectives icon
  • Recover endangered populations (NARW) decreasing arrow icon below average icon icon
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State of the Ecosystem Summary 2023:

Risks to meeting fishery management objectives

Climate: warming and changing oceanography continue

  • Heat waves and Gulf Stream instability
  • Estuarine, coastal, and offshore habitats affected, with range of species responses
  • Distribution shifts complicate management
  • Multiple fish with poor condition, declining productivity

Other ocean uses: offshore wind development

  • Current revenue in proposed areas
    • 1-34% by port (some with EJ concerns)
    • up to 17% by managed species
  • Different development impacts for species preferring soft bottom vs. hard bottom
  • Overlap with important right whale foraging habitats, increased vessel strike and noise risks
  • Rapid buildout in patchwork of areas
  • Scientific survey mitigation required
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Implications: Climate change and managed species

Climate: 6 low, 3 low-mod, 4 mod-high, 1 high risk

Multiple drivers with different impacts by species

  • Seasonal estuarine conditions affect life stages of striped bass, blue crabs, summer flounder, black sea bass differently
    • Chesapeake summer hypoxia, temperature better than in past years, but worse in fall
    • Habitat improving in some areas (tidal fresh SAV, oyster reefs), but eelgrass declining
  • Ocean acidification impact on vulnerable surfclams
    • Areas of low pH identified in surfclam and scallop habitat
    • Lab work identified pH thresholds for surfclam growth
  • Warm core rings important to Illex availability. Fishing effort concentrates on the eastern edge of warm core rings, where upwelling and enhanced productivity ocurr

DistShift: 2 low, 9 mod-high, 3 high risk species

Shifting species distributions alter both species interactions, fishery interactions, and expected management outcomes from spatial allocations and bycatch measures based on historical fish and protected species distributions.

black sea bass survey distribution change over time from 2018 SOE

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Using ecosystem information at the stock level: Ecosystem Socioeconomic Profiles (ESPs)

GOA pcod ESP conceptual model

Pacific cod example from ASFC: https://www.fisheries.noaa.gov/alaska/2021-alaska-fisheries-science-center-year-review and https://apps-afsc.fisheries.noaa.gov/refm/docs/2021/GOApcod.pdf

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Looking across stocks for ecosystem signals

Indicator: fish condition

  • Stock level condition drivers --> decision on butterfish recruitment stanza for projections

Indicator: fish productivity anomaly

  • Related to multiple drivers
  • Multispecies projection and reference point implications
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(Perretti, et al., 2017)

State of the Ecosystem → MAFMC Risk assessent example: Commercial revenue

This element is applied at the ecosystem level. Revenue serves as a proxy for commercial profits.

Risk Level Definition
Low No trend and low variability in revenue
Low-Moderate Increasing or high variability in revenue
Moderate-High Significant long term revenue decrease
High Significant recent decrease in revenue

Ranked moderate-high risk due to the significant long term revenue decrease for all species (black points)

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State of the Ecosystem → MAFMC Risk assessent example: Commercial revenue

This element is applied at the ecosystem level. Revenue serves as a proxy for commercial profits.

Risk Level Definition
Low No trend and low variability in revenue
Low-Moderate Increasing or high variability in revenue
Moderate-High Significant long term revenue decrease
High Significant recent decrease in revenue

Ranked moderate-high risk due to the significant long term revenue decrease for all species (black points)

Risk element: CommRev, unchanged

SOE Implications: Recent change driven by benthos. Monitor changes in climate and landings drivers:

  • Climate risk element: Surfclams and ocean quahogs are sensitive to ocean warming and acidification.
  • pH in surfclam summer habitat is approaching, but not yet at, pH affecting surfclam growth
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EAFM Risk Assessment: 2023, Major Update In Progress

Species level risk elements

Species Assess Fstatus Bstatus FW1Pred FW1Prey FW2Prey Climate DistShift EstHabitat
Ocean Quahog lowest lowest lowest lowest lowest lowest highest modhigh lowest
Surfclam lowest lowest lowest lowest lowest lowest modhigh modhigh lowest
Summer flounder lowest lowest lowmod lowest lowest lowest lowmod modhigh highest
Scup lowest lowest lowest lowest lowest lowest lowmod modhigh highest
Black sea bass lowest lowest lowest lowest lowest lowest modhigh modhigh highest
Atl. mackerel lowest highest highest lowest lowest lowest lowmod modhigh lowest
Chub mackerel highest lowmod lowmod lowest lowest lowest na na lowest
Butterfish lowest lowest lowmod lowest lowest lowest lowest highest lowest
Longfin squid lowmod lowmod lowmod lowest lowest lowmod lowest modhigh lowest
Shortfin squid highest lowmod lowmod lowest lowest lowmod lowest highest lowest
Golden tilefish lowest lowest lowmod lowest lowest lowest modhigh lowest lowest
Blueline tilefish highest highest modhigh lowest lowest lowest modhigh lowest lowest
Bluefish lowest lowest lowmod lowest lowest lowest lowest modhigh highest
Spiny dogfish lowest highest lowmod lowest lowest lowest lowest highest lowest
Monkfish highest lowmod lowmod lowest lowest lowest lowest modhigh lowest
Unmanaged forage na na na lowest lowmod lowmod na na na
Deepsea corals na na na lowest lowest lowest na na na
  • RT assessment decreased Spiny dogfish Assess, risk to low and increased Fstatus risk to high
  • RT assessment decreased bluefish Bstatus risk from high to low-moderate
  • RT assessment increased Illex Assess risk from low-moderate to high

Ecosystem level risk elements

System EcoProd CommRev RecVal FishRes1 FishRes4 FleetDiv Social ComFood RecFood
Mid-Atlantic lowmod modhigh lowest lowest modhigh lowest lowmod highest modhigh
  • Recreational value risk decreased from low-moderate to low

Species and Sector level risk elements

Species MgtControl TecInteract OceanUse RegComplex Discards Allocation
Ocean Quahog-C lowest lowest lowmod lowest modhigh lowest
Surfclam-C lowest lowest lowmod lowest modhigh lowest
Summer flounder-R modhigh lowest lowmod modhigh highest highest
Summer flounder-C lowmod modhigh lowmod modhigh modhigh lowest
Scup-R lowmod lowest lowmod modhigh modhigh highest
Scup-C lowest lowmod modhigh modhigh modhigh lowest
Black sea bass-R highest lowest modhigh modhigh highest highest
Black sea bass-C highest lowmod highest modhigh highest lowest
Atl. mackerel-R lowmod lowest lowest lowmod lowest lowest
Atl. mackerel-C lowest lowmod modhigh highest lowmod highest
Butterfish-C lowest lowmod modhigh modhigh modhigh lowest
Longfin squid-C lowest modhigh highest modhigh highest lowest
Shortfin squid-C lowmod lowmod lowmod modhigh lowest highest
Golden tilefish-R na lowest lowest lowest lowest lowest
Golden tilefish-C lowest lowest lowest lowest lowest lowest
Blueline tilefish-R lowmod lowest lowest lowmod lowest lowest
Blueline tilefish-C lowmod lowest lowest lowmod lowest lowest
Bluefish-R lowmod lowest lowest lowmod modhigh highest
Bluefish-C lowest lowest lowmod lowmod lowmod lowest
Spiny dogfish-R lowest lowest lowest lowest lowest lowest
Spiny dogfish-C lowest modhigh modhigh modhigh lowmod lowest
Chub mackerel-C lowest lowmod lowmod lowmod lowest lowest
Unmanaged forage lowest lowest modhigh lowest lowest lowest
Deepsea corals na na modhigh na na na
  • Management section not updated--to be revised this year
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Comments on overall risk assessment for EOP to consider?

How is MAFMC using the risk assessment?

  • Prioritization: the Council selected summer flounder as high-risk fishery for conceptual modeling

Mid-Atlantic EAFM framework

  • Council proceeding with management strategy evaluation (MSE) addressing recreational fishery discards using information from conceptual modeling.
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In this interactive circular graph visualization, model elements identified as important by the Council (through risk assessment) and by the working group (through a range of experience and expertise) are at the perimeter of the circle. Elements are defined in detail in the last section of this page. Relationships between elements are represented as links across the center of the circle to other elements on the perimeter. Links from a model element that affect another element start wide at the base and are color coded to match the category of the element they affect.Hover over a perimeter section (an element) to see all relationships for that element, including links from other elements. Hover over a link to see what it connects. Links by default show text for the two elements and the direction of the relationship (1 for relationship, 0 for no relationship--most links are one direction).For example, hovering over the element "Total Landings" in the full model shows that the working group identified the elements affected by landings as Seafood Production, Recreational Value, and Commercial Profits (three links leading out from landings), and the elements affecting landings as Fluke SSB, Fluke Distributional Shift, Risk Buffering, Management Control, Total Discards, and Shoreside Support (6 links leading into Total Landings).

What is Management Strategy Evaluation?

  • Process to develop fishery management procedures

  • First used in S. Africa, Australia, and at International Whaling Commission late 1980s - early 1990s

Under this approach, management advice is based on a fully specified set of rules that have been tested in simulations of a wide variety of scenarios that specifically take uncertainty into account. The full procedure includes specifications for the data to be collected and how those data are to be used to provide management advice, in a manner that incorporates a feedback mechanism.

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MSE results: can improve on current management, but distribution shifts lower expectations

Results for 2 of 16 performance metrics:

Summer flounder MSE results by OM

August MAFMC briefing materials and full results on the web

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  • Linked recreational demand and population dynamics model
  • Alternative operating model included northward distribution shift as change in availability by state
  • Rank order of management options maintained, but degraded performance when considering ecosystem change

Participating in EBFM

Scientific concepts → management

  • Collaborative conceptual modeling
  • Management strategy evaluation

The IEA Loop1 IEA process from goal setting to assessment to strategy evaluation with feedbacks

[1] https://www.integratedecosystemassessment.noaa.gov/national/IEA-approach

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EBFM engagement: Conceptual modeling, from science- to stakeholder-driven

Mid-Atlantic conceptual model developed by a technical team and Council representatives

Collaborative conceptual modeling with stakeholders:

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(DePiper, et al., 2021) (Rosellon-Druker, et al., 2021) (Levin, et al., 2016) (Spooner, et al., 2021)

South Atlantic example: citizen science for data-poor migratory species

South Atlantic physical system https://safmc.net/citizen-science/dolphin-wahoo-participatory-workshops/

South Atlantic dolfin wahoo NC-VA conceptual model South Atlantic dolfin wahoo S Fl conceptual model

https://safmc-shinyapps.shinyapps.io/NCVA_DolphinWorkshops2020/
https://safmc-shinyapps.shinyapps.io/S_FL_DolphinWorkshops2021/

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Stakeholder engagement and Management Strategy Evaluation

Are any Atlantic herring harvest control rules good for both fisheries and predators?

Harvest control rules are:

  • plans for changing fishing based on stock status
  • pre-determined

"Which harvest control rules best consider herring's role as forage?"

  • DESIGN a harvest control rule (HCR):
    • balancing fishing benefits and ecological services
    • addressing diverse stakeholder interests
  • TRANSPARENTLY within management time frame!
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The Herring MSE process

First MSE within US Council
Scope: annual stockwide HCR Open stakeholder meetings (2)

  • ID objectives, uncertainties
  • ID acceptable performance
  • more diverse, interactive than "normal" process

Uncertainties identified

  • herring mortality (M)
  • environmental effects on herring
  • predator response to herring abundance
  • assessment uncertainty
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Linked models matching stakeholder-identified objectives

The Dream:1 Convert the effects of control rules on 4 user groups to dollars:

  1. Users of landed herring (Demand)
    • Lobster industry, aquariums
  2. Herring harvesters (Supply)
  3. Direct users of herring in the ocean (not people)
    • Terns and Whales
    • Striped Bass, Dogfish
  4. Indirect users of herring in the ocean (people, Derived Demand)
    • Bird- and whale-watchers
    • Recreational and Commercial Fishing
The Reality
  • 8 herring operating models linked to simple predator and economic models, developed in parallel
  • limited range of predator response
  • limited economic effects, directed fishery only

1 Credit: Min-Yang Lee

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(Deroba, et al., 2018)

Stakeholder process for Summer flounder recreational discards MSE

Broad online scoping results helped develop Core stakeholder group

MAFMC webcallMAFMC stakeholder comp MAFMC concerns

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Implementing the Ecosystem Approach: lessons learned

EBFM is flexible and iterative

  • Tools: ecosystem reporting, risk and vulnerability assessment
  • Many entry points for ecosystem information

EBFM is collaborative and participatory

Brandon Muffley, MAFMC staff

Collaborations needed:

  • Within the science community – diverse expertise is needed
  • Between science and management – understanding what information is needed and important to management, providing tools to management to understand ecosystem linkages and implications

EAFM Policy Guidance Doc Word Cloud

Word cloud based on Mid-Atlantic Fishery Management Council EAFM Guidance Document

  • Between science and stakeholders – need to build trust, open dialogue (everyone is heard), and sharing data and observations (on water and with information)
  • Between management and stakeholders – listening to/acting on stakeholder priorities and feedback, process not out to add more uncertainty but provide for more informed decisions
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Additional resources

National Ecosystem Based Fishery Management Websites

Northeast US Ecosystem Reporting and Indicators

Council Scientific and Statistical Committees

Council Ecosystem Approaches

Council Management Strategy Evaluations

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References

Bastille, K. et al. (2021). "Improving the IEA Approach Using Principles of Open Data Science". In: Coastal Management 49.1. Publisher: Taylor & Francis _ eprint: https://doi.org/10.1080/08920753.2021.1846155, pp. 72-89. ISSN: 0892-0753. DOI: 10.1080/08920753.2021.1846155. URL: https://doi.org/10.1080/08920753.2021.1846155 (visited on Apr. 16, 2021).

DePiper, G. S. et al. (2017). "Operationalizing integrated ecosystem assessments within a multidisciplinary team: lessons learned from a worked example". En. In: ICES Journal of Marine Science 74.8, pp. 2076-2086. ISSN: 1054-3139. DOI: 10.1093/icesjms/fsx038. URL: https://academic.oup.com/icesjms/article/74/8/2076/3094701 (visited on Mar. 09, 2018).

DePiper, G. et al. (2021). "Learning by doing: collaborative conceptual modelling as a path forward in ecosystem-based management". In: ICES Journal of Marine Science. ISSN: 1054-3139. DOI: 10.1093/icesjms/fsab054. URL: https://doi.org/10.1093/icesjms/fsab054 (visited on Apr. 15, 2021).

Deroba, J. J. et al. (2018). "The dream and the reality: meeting decision-making time frames while incorporating ecosystem and economic models into management strategy evaluation". In: Canadian Journal of Fisheries and Aquatic Sciences. ISSN: 0706-652X. DOI: 10.1139/cjfas-2018-0128. URL: http://www.nrcresearchpress.com/doi/10.1139/cjfas-2018-0128 (visited on Jul. 20, 2018).

Gaichas, S. K. et al. (2018). "Implementing Ecosystem Approaches to Fishery Management: Risk Assessment in the US Mid-Atlantic". In: Frontiers in Marine Science 5. ISSN: 2296-7745. DOI: 10.3389/fmars.2018.00442. URL: https://www.frontiersin.org/articles/10.3389/fmars.2018.00442/abstract (visited on Nov. 20, 2018).

Jones, A. W. et al. (2022). "Learning From the Study Fleet: Maintenance of a Large-Scale Reference Fleet for Northeast U.S. Fisheries". In: Frontiers in Marine Science 9. ISSN: 2296-7745. URL: https://www.frontiersin.org/articles/10.3389/fmars.2022.869560 (visited on Nov. 15, 2022).

Levin, P. S. et al. (2016). "Thirty-two essential questions for understanding the social–ecological system of forage fish: the case of pacific herring". In: Ecosystem Health and Sustainability 2.4. Publisher: Taylor & Francis _ eprint: https://doi.org/10.1002/ehs2.1213, p. e01213. ISSN: 2096-4129. DOI: 10.1002/ehs2.1213. URL: https://doi.org/10.1002/ehs2.1213 (visited on Jun. 22, 2020).

Muffley, B. et al. (2021). "There Is no I in EAFM Adapting Integrated Ecosystem Assessment for Mid-Atlantic Fisheries Management". In: Coastal Management 49.1. Publisher: Taylor & Francis _ eprint: https://doi.org/10.1080/08920753.2021.1846156, pp. 90-106. ISSN: 0892-0753. DOI: 10.1080/08920753.2021.1846156. URL: https://doi.org/10.1080/08920753.2021.1846156 (visited on Apr. 16, 2021).

Perretti, C. et al. (2017). "Regime shifts in fish recruitment on the Northeast US Continental Shelf". En. In: Marine Ecology Progress Series 574, pp. 1-11. ISSN: 0171-8630, 1616-1599. DOI: 10.3354/meps12183. URL: http://www.int-res.com/abstracts/meps/v574/p1-11/ (visited on Feb. 10, 2022).

Rosellon-Druker, J. et al. (2021). "Participatory place-based integrated ecosystem assessment in Sitka, Alaska: Constructing and operationalizing a socio-ecological conceptual model for sablefish (Anoplopoma fimbria)". En. In: Deep Sea Research Part II: Topical Studies in Oceanography 184-185, p. 104912. ISSN: 0967-0645. DOI: 10.1016/j.dsr2.2020.104912. URL: https://www.sciencedirect.com/science/article/pii/S0967064520301673 (visited on Mar. 10, 2022).

Spooner, E. et al. (2021). "Using Integrated Ecosystem Assessments to Build Resilient Ecosystems, Communities, and Economies". En. In: Coastal Management 49.1, pp. 26-45. ISSN: 0892-0753, 1521-0421. DOI: 10.1080/08920753.2021.1846152. URL: https://www.tandfonline.com/doi/full/10.1080/08920753.2021.1846152 (visited on Nov. 21, 2022).

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Questions?

Thank you

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What do you think EBFM means?

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