Risk Assessment used in a different context
Component of Ecosystem Approach to Fisheries Management
Tied to annual State of the Ecosystem Report
Used to prioritze issues for more detailed work
5 year update evolution towards more dynamic indicators
Mid Atlantic fishery management plans and species
Source: http://www.mafmc.org/fishery-management-plans
The Council’s EAFM framework has similarities to the IEA loop on slide 2. It uses risk assessment as a first step to prioritize combinations of managed species, fleets, and ecosystem interactions for consideration. Second, a conceptual model is developed identifying key environmental, ecological, social, economic, and management linkages for a high-priority fishery. Third, quantitative modeling addressing Council-specified questions and based on interactions identified in the conceptual model is applied to evaluate alternative management strategies that best balance management objectives. As strategies are implemented, outcomes are monitored and the process is adjusted, and/or another priority identified in risk assessment can be addressed.
(DePiper et al., 2017) (Bastille et al., 2021) (Muffley et al., 2021) (Gaichas et al., 2018) (DePiper et al., 2021) (Gaichas et al., 2016)
Ecosystem indicators linked to management objectives (DePiper et al., 2017)
Open science emphasis (Bastille et al., 2021)
Used within Mid-Atlantic Fishery Management Council's Ecosystem Process (Muffley et al., 2021)
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
Species level risk elements
Species | Assess | Fstatus | Bstatus | PreyA | PredP | FW2Prey | Climate | DistShift | EstHabitat | OffHab |
---|---|---|---|---|---|---|---|---|---|---|
Ocean Quahog | lowest | lowest | lowest | tbd | tbd | lowest | highest | modhigh | lowest | tbd |
Surfclam | lowest | lowest | lowest | tbd | tbd | lowest | modhigh | modhigh | lowest | tbd |
Summer flounder | lowest | highest | lowmod | tbd | tbd | lowest | lowmod | modhigh | highest | tbd |
Scup | lowest | lowest | lowest | tbd | tbd | lowest | lowmod | modhigh | highest | tbd |
Black sea bass | lowest | lowest | lowest | tbd | tbd | lowest | modhigh | modhigh | highest | tbd |
Atl. mackerel | lowest | lowest | highest | tbd | tbd | lowest | lowmod | modhigh | lowest | tbd |
Chub mackerel | highest | lowmod | lowmod | tbd | tbd | lowest | na | na | lowest | tbd |
Butterfish | lowest | lowest | lowmod | tbd | tbd | lowest | lowest | highest | lowest | tbd |
Longfin squid | lowmod | lowmod | lowmod | tbd | tbd | lowmod | lowest | modhigh | lowest | tbd |
Shortfin squid | highest | lowmod | lowmod | tbd | tbd | lowmod | lowest | highest | lowest | tbd |
Golden tilefish | lowest | lowest | lowmod | tbd | tbd | lowest | modhigh | lowest | lowest | tbd |
Blueline tilefish | highest | highest | modhigh | tbd | tbd | lowest | modhigh | lowest | lowest | tbd |
Bluefish | lowest | lowest | lowmod | tbd | tbd | lowest | lowest | modhigh | highest | tbd |
Spiny dogfish | lowest | highest | lowest | tbd | tbd | lowest | lowest | highest | lowest | tbd |
Monkfish | highest | lowmod | lowmod | tbd | tbd | lowest | lowest | modhigh | lowest | tbd |
Unmanaged forage | na | na | na | tbd | tbd | lowmod | na | na | na | tbd |
Deepsea corals | na | na | na | tbd | tbd | lowest | na | na | na | tbd |
Ecosystem level risk elements
System | EcoProd | CommVal | RecVal | FishRes1 | FishRes2 | ComDiv | RecDiv | Social | ComFood | RecFood |
---|---|---|---|---|---|---|---|---|---|---|
Mid-Atlantic | lowmod | modhigh | lowmod | lowest | modhigh | lowest | tbd | lowmod | modhigh | modhigh |
Species and Sector level risk elements
Species | FControl | Interact | OSW1 | OSW2 | OtherUse | RegComplex | Discards | Allocation |
---|---|---|---|---|---|---|---|---|
Ocean Quahog-C | lowest | lowest | tbd | tbd | tbd | lowest | modhigh | lowest |
Surfclam-C | lowest | lowest | tbd | tbd | tbd | lowest | modhigh | lowest |
Summer flounder-R | lowmod | lowest | tbd | tbd | tbd | highest | modhigh | highest |
Summer flounder-C | lowmod | lowmod | tbd | tbd | tbd | lowmod | modhigh | lowest |
Scup-R | highest | lowest | tbd | tbd | tbd | highest | modhigh | highest |
Scup-C | lowest | lowmod | tbd | tbd | tbd | lowmod | modhigh | lowest |
Black sea bass-R | highest | lowest | tbd | tbd | tbd | highest | modhigh | highest |
Black sea bass-C | lowmod | lowmod | tbd | tbd | tbd | lowmod | highest | lowest |
Atl. mackerel-R | lowmod | lowest | tbd | tbd | tbd | lowmod | lowmod | lowest |
Atl. mackerel-C | lowest | lowmod | tbd | tbd | tbd | highest | lowmod | lowest |
Butterfish-C | lowest | lowmod | tbd | tbd | tbd | modhigh | modhigh | lowest |
Longfin squid-C | lowest | modhigh | tbd | tbd | tbd | modhigh | modhigh | lowest |
Shortfin squid-C | lowmod | lowmod | tbd | tbd | tbd | modhigh | lowest | lowest |
Golden tilefish-R | na | lowest | tbd | tbd | tbd | lowest | lowest | lowest |
Golden tilefish-C | lowest | lowest | tbd | tbd | tbd | lowest | lowest | lowest |
Blueline tilefish-R | lowest | lowest | tbd | tbd | tbd | lowmod | lowest | lowest |
Blueline tilefish-C | lowmod | lowest | tbd | tbd | tbd | lowest | lowest | lowest |
Bluefish-R | lowmod | lowest | tbd | tbd | tbd | modhigh | lowmod | highest |
Bluefish-C | lowest | lowest | tbd | tbd | tbd | lowmod | lowmod | lowest |
Spiny dogfish-R | lowest | lowest | tbd | tbd | tbd | lowest | lowmod | lowest |
Spiny dogfish-C | lowest | modhigh | tbd | tbd | tbd | highest | lowmod | lowest |
Chub mackerel-C | lowest | lowmod | tbd | tbd | tbd | lowest | lowest | lowest |
Unmanaged forage | lowest | lowest | tbd | tbd | tbd | lowest | lowest | lowest |
Deepsea corals | na | na | tbd | tbd | tbd | na | na | na |
Risk based prioritization: the Council selected summer flounder for conceptual modeling
Council completed management strategy evaluation (MSE) addressing recreational fishery discards based on conceptual modeling
Stakeholder driven MSE coupled population and recreational demand models
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).
Example: Evaluate risks posed by prey availability to achieving OY for Council managed species
Council and Advisory Panel members recommended new elements addressing human dimensions (recreational access equity), new elements addressing cross-sectoral impacts (offshore wind impacts on biology and ecosystem as well as fishery access and scientific sampling), and transitions from static ecosystem indicators to time series indicators (prey availability, predation pressure, and fishing community vulnerability). New ecosystem science was required to support these requests. The process included development of new indicators of prey availability based on spatio-temporal modeling using ecological datasets (stomach contents, zooplankton), and new spatial analyses of habitat, revenue, and surveys relative to wind energy development areas. Development of potential risk criteria is ongoing; thresholds between low, moderate, and high risk that are essential to operational use are developed collaboratively with Council and Advisory Panel members.
The slide shows a higher risk example (black sea bass, low recent condition correlated with recently declining prey) and a lower risk example (bluefish, despite a long term decline in forage fish prey. recent condition has been good)
2016-2023 Reports: Climate Section
2024 Report: Climate/Ecosystem Risks
Risks to Spatial Management/Allocation
Risks to Seasonal Management/Timed Closures
Risks to Quota Management/Rebuilding
2024 Report: Days at stressful scallop temperature
Image courtesy Joseph Caracappa, NEFSC
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 78.4, pp. 1217-1228. ISSN: 1054-3139. DOI: 10.1093/icesjms/fsab054. URL: https://doi.org/10.1093/icesjms/fsab054 (visited on Aug. 08, 2022).
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).
Gaichas, S. K. et al. (2023). "Assessing small pelagic fish trends in space and time using piscivore stomach contents". En. In: Canadian Journal of Fisheries and Aquatic Sciences, pp. cjfas-2023-0093. ISSN: 0706-652X, 1205-7533. DOI: 10.1139/cjfas-2023-0093. URL: https://cdnsciencepub.com/doi/10.1139/cjfas-2023-0093 (visited on Feb. 15, 2024).
Gaichas, S. K. et al. (2016). "A Framework for Incorporating Species, Fleet, Habitat, and Climate Interactions into Fishery Management". In: Frontiers in Marine Science 3. ISSN: 2296-7745. DOI: 10.3389/fmars.2016.00105. URL: https://www.frontiersin.org/articles/10.3389/fmars.2016.00105/full (visited on Apr. 29, 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).
Risk Assessment used in a different context
Component of Ecosystem Approach to Fisheries Management
Tied to annual State of the Ecosystem Report
Used to prioritze issues for more detailed work
5 year update evolution towards more dynamic indicators
Mid Atlantic fishery management plans and species
Source: http://www.mafmc.org/fishery-management-plans
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