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ElementsNeedingDiscussion.Rmd
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---
title: "Risk Elements and Definitions Needing Discussion"
date: "`r Sys.Date()`"
output:
html_document:
df_print: paged
highlight: null
csl: frontiers.csl
bibliography: riskassess.bib
---
```{r setup, include=FALSE, echo=FALSE}
knitr::opts_chunk$set(echo = FALSE,
fig.asp=.45,
message = FALSE)
library(tidyverse)
library(ecodata)
```
```{r}
# Summarize response for element definitions in text
# once file has been downloaded use this
responses <- read.csv("EAFM Risk Assessment Review (Responses).csv",header=T)
# separate question number and element name? numbers are duplicates so just use name
names(responses) <- sub("^X.*\\.\\.\\.","",names(responses))
# take only the elements
elements <- responses[,4:46]
listdefs <- function(elname){
elements[elname] |>
map_df(str_squish) |> # removes whitespace
filter(.data[[elname]]!= "") |> # removes blank answers
distinct() |>
as.data.frame()
}
```
```{r, code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/macrofauna_MAB.Rmd-setup.R"), message=FALSE}
```
```{r, code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/LTL_MAB.Rmd-setup.R"), message=FALSE}
```
## Ecological elements
### Food web (Council-managed predators): change to "Food web: Prey availability"
This element is applied at the species level.
Fish stocks and protected species stocks are managed using single species approaches, but fish and protected species stocks exist within a food web of predator and prey interactions. This element is one of two separating food web risks to achieving OY for Council managed species from two sources. This first element assesses prey availability for each species, and the second food web risk element assesses predation pressure on each species (see next element).
Proposed definition:
Risk of not achieving OY for Council managed species due to availability of prey.
Indicators:
Indicators of prey availability for each Council managed species could be based on food habits information for the Council managed species combined with population trends for key prey species (if available). Prey could include all species (Council managed, other-managed, and non-managed) or a subset as determined by the EOP and Council.
Alternative indirect indicators of prey availability could include the fish condition indicators from the State of the Ecosystem report (shown below under Ecosystem Productivity). These would not rely on detailed diet information, instead reflecting the impact of environmental drivers including prey availability on fish growth.
Diet information was gathered from the Northeast Fisheries Science Center (NEFSC) food habits database and other sources [@smith_trophic_2010; @johnson_growth_2008].
Potential risk criteria:
```{r riskfw1, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | Prey availability high (not limiting) and/or good fish condition past 5 years |
| Low-Moderate | Aggregate prey available for this species has stable or increasing trend, moderate condition |
| Moderate-High | Aggregate prey available for this species has significant decreasing trend, poor condition |
| High | Managed species highly dependent on prey with limited and declining availability, poor condition |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
\newpage
### Food web (Council-managed prey): change to "Food web: Predation pressure"
This element is applied at the species level.
Fish stocks and protected species stocks are managed using single species approaches, but fish and protected species stocks exist within a food web of predator and prey interactions. This element is one of two separating food web risks to achieving OY for Council managed species from two sources. This second food web risk element assesses predation pressure on each species, and the first element assesses prey availability for each species (see element above).
Proposed definition:
Risk of not achieving OY for Council managed species due to predation pressure.
Indicators:
Indicators of predation pressure on a Council managed species could be based on food habits information for predators of the species combined with key predator trends. This could be derived from empirical information or food web/multispecies models. Predators could include all species (protected, HMS, Council managed, other-managed, and unmanaged) or a subset as determined by the EOP and Council.
Potential risk criteria:
```{r riskfw11, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | Predation pressure represents low proportion of overall mortality|
| Low-Moderate | Predation pressure moderate proportion of overall mortality, decreasing mortality trend |
| Moderate-High | Predation pressure moderate proportion of overall mortality, increasing mortality trend|
| High | Predation pressure represents high proportion of overall mortality, increasing mortality trend |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
\newpage
### Food web (protected species prey): clarify definition
This element is applied at the species level.
Fish stocks and protected species stocks are managed using single species approaches, but fish and protected species stocks exist within a food web of predator and prey interactions. The previous two elements focus on Council managed species OY, while this element focuses on protected species objectives (maintain or recover populations and minimize bycatch).
Proposed definitions:
1 - Risk of not achieving protected species objectives due to species interactions (not just MAFMC-managed species)
2 (current) - Risk of not achieving protected species objectives due to interactions with Council-managed species
If the Council is most interested in general food web risks to protected species, modified version 2 achieves this, leading to a broader set of indicators than currently used, but we may not be able to apply it at the species level.
If the Council is most interested in the food web risks to protected species that are most likely to be related to Council management decisions, the current version focused on Council managed species as prey achieves this.
This element ranks the risks of not achieving protected species objectives due to species interactions with Council managed species. In the US, protected species include marine mammals (under the Marine Mammal Protection Act), Endangered and Threatened species (under the Endangered Species Act), and migratory birds (under the Migratory Bird Treaty Act). In the Northeast US, endangered/threatened species include Atlantic salmon, Atlantic and shortnose sturgeon, all sea turtle species, and five whales.
Indicators (previously used):
As above, food web models and diet information can be used to establish thresholds of "importance" for predators and prey. Although monkfish occasionally ingest seabirds [@perry_predation_2013], there are no Council-managed species that are important predators of protected species [@smith_trophic_2010], so here we rank only risks where Council managed species represent prey of protected species. An important prey of protected species is defined here as individually comprising >30% of the predator's diet by weight. Critical prey warranting a high risk ranking would be a majority (>50%) of diet for an individual protected species.
Potential risk criteria:
```{r riskfw2, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | Few interactions with any protected species |
| Low-Moderate | Important prey of 1-2 protected species, or important prey of 3 or more protected species with management consideration of interaction |
| Moderate-High | Important prey of 3 or more protected species |
| High | Managed species is sole prey for a protected species |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
Previous risk discussion:
Risk ranking criteria for the multispecies protected species category were developed to address interactions across species. Low risk ranking criteria were few interactions with any protected species. Low risk was defined as few interactions with any protected species. Low-Moderate risk was a Council-managed species being important prey of 1-2 protected species, or important prey of 3 or more protected species with management consideration of the interaction. Moderate-High risk criteria was a Council-managed species being important prey of 3 or more protected species. Finally, High risk criteria was a Council-managed species being critical (>50%) prey for a protected species.
Diet information for protected species tends to be more uncertain than for fished species, and diet compositions are not reported to the species level, so we consider diet at the family level for these rankings. Atlantic salmon, both species of sturgeon, and sea turtles rarely if ever prey on Council managed species, as reviewed in the Council Forage Fish white paper [@savoy_prey_2007; @johnson_food_1997; @burke_diet_1993; @burke_diet_1994; @mcclellan_complexity_2007; @seney_historical_2007; @shoop_seasonal_1992]. We restrict further analysis to marine mammal and seabird prey. Longfin squids are estimated to comprise >30% of diet for one protected species, pilot whale, in the Northeast US [@smith_consumption_2015; @gannon_stomach_1997], therefore we rank this species low-moderate risk for this element. Shortfin squid were identified as important prey for two pelagic seabirds in the Northeast US [@powers_energy_1987], and therefore ranked low-moderate risk. Unmanaged forage fish such as sand lance and saury were identified as important prey for >3 seabird species in the Northeast US [@powers_energy_1987], as well as grey seals [@smith_consumption_2015]. The Council has enacted measures to restrict fishing on unmanaged forage species, such that they rank low-moderate risk for this element. All other Council-managed species do not meet the threshold of important prey of protected species based on available information for marine mammal diets in the Northeast US [@smith_consumption_2015], and seabird diets [@powers_pelagic_1983; @powers_energy_1987; @powers_seabirds_1987; @schneider_state_1996; @barrett_diet_2007; @bowser_puffins_2013], so they rank low risk for this element.
\newpage
### Ecosystem productivity: incorporate forage base indicators
Productivity at the base of the food web supports and ultimately limits the amount of managed species production in an ecosystem. This element is applied at the ecosystem level (the Mid-Atlantic Ecosystem Production Unit) and evaluates the risk of not achieving OY across all Council managed species due to broad changes in ecosystem productivity at the base of the food web.
Proposed definition:
Risk of not achieving OY due to changing system productivity at the base of the food web.
Indicators:
A combination of four indicators are currently used to assess risk of changing ecosystem productivity; the proposal is to add a fifth. We examine trends in total primary production, zooplankton abundance for a key Mid-Atlantic species, aggregate forage fish (new), and two aggregate fish productivity measures: condition factor (weight divided by length of individual fish) and a survey based “recruitment” (small fish to large fish) index. An assessment-based recruitment index was recently added to the State of the Ecosystem report as well. Because benthic crustaceans are important prey for many Council-managed species, we note a benthic production indicator is desirable but not yet available.
These indicators evaluate ecosystem productivity in aggregate, which may change due to drivers such as decreasing primary productivity, changes in spatial/temporal overlap at the base of the food web, or other factors.
For primary production and fish productivity, the spatial scale of analysis is the Mid-Atlantic Ecosystem Production Unit, as indicated in Figure \ref{EPUmap}.
#### Primary production
Primary production has fluctuated recently with current conditions near average. The observed stability in system productivity is in contrast to an apparent shift in the timing of the bloom cycle in the Mid-Atlantic. Comparing remote sensing information from the 1970-80s to 1997-2015 information suggests that winter productivity was historically higher in the MAB and that the spring bloom we see today was less prominent. Shifts in timing of low trophic level production can affect Council managed fish species through early life history stages that feed on zooplankton.
[add indicator]
#### Zooplankton abundance
Zooplankton provide a critical link between phytoplankton at the base of the food web, and higher trophic organisms such as fish, mammals, and birds. Changes in the species compostion and biomass of the zooplankton community have a great potential to affect recruitment success and fisheries productivity, and climate change may be the most important pathway for these changes to manifest. Therefore these indices are relevant to both productivity and trophic structure objectives.
The time series of zooplankton biovolume suggest that overall zooplankton production has not changed over time. However, the dominant species of zooplankton in the Mid-Atlantic, *Centropages typicus*, shows a seasonal shift in abundance. This suggests a change in timing of zooplankton reproductive cycles, which may impact fish species such as Atlantic mackerel.
[add indicator]
#### Incorporate Forage Base as new indicator
The amount of forage available is one important driver of fish productivity. Indicators of aggregate pelagic forage fish biomass and forage fish energy content are presented in the State of the Ecosystem report. Indicators of benthic forage are under development but not yet available. Food habits data from surveys and literature could be used to define the forage base common to all Council managed and protected species.
```{r , code=readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/macrofauna_MAB.Rmd-forage-index.R"), fig.asp=.6}
```
#### Fish condition
Fish condition is measured as the weight per length--a measure of "fatness". This information is from NEFSC bottom trawl surveys and shows a change in condition across all species at around 2000. Around 2010-2013 many species started to have better condition, though black sea bass remain thinner for their length on average.
```{r, out.width="120%"}
#knitr::include_graphics("https://github.com/NOAA-EDAB/presentations/raw/master/docs/EDAB_images//MAB_Condition_allsex_2022_viridis.jpg")
fishcond <- magick::image_read("https://github.com/NOAA-EDAB/ecodata/raw/master/docs/images/MAB_Condition_allsex_2023_viridis.jpg")
magick::image_trim(fishcond)
```
#### Fish productivity
The number of small fish relative to the biomass of larger fish of the same species, as derived from the NEFSC survey, is a simple measure of productivity intended to complement model-based stock assessment estimates of recruitment. There is a general decrease in this indicator when aggregated across managed and unmanaged species in the Mid-Atlantic. The plot includes black sea bass, butterfish, clearnose skate, fourspot flounder, little skate, scup, spiny dogfish, summer flounder, thorny skate, windowpane flounder, winter flounder, and winter skate.
```{r , code=readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/macrofauna_MAB.Rmd-productivity-anomaly.R"), fig.asp=.75}
```
```{r , code=readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/macrofauna_MAB.Rmd-productivity-assessment.R"), fig.asp=.75}
```
Potential risk criteria:
Low risk for this element was defined as no trends in ecosystem productivity across all five indicators. The Low-Moderate risk criterion was trend(s) in ecosystem productivity for 1-2 indicators, whether increasing or decreasing. The Moderate-High risk criterion was trends in ecosystem productivity (3+ measures, increase or decrease). The High risk criterion was decreasing trends across 4 or more indicators.
```{r riskecop, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No trends in ecosystem productivity |
| Low-Moderate | Trend in ecosystem productivity (1-2 measures, increase or decrease) |
| Moderate-High | Trend in ecosystem productivity (3+ measures, increase or decrease) |
| High | Decreasing trend in ecosystem productivity, all measures |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
Previous risk discussion:
To summarize, primary production shows no trend (although the seasonal timing of primary production may be changing). Similarly, there are no trends in overall zooplankton abundance, but a dominant Mid-Atlantic species shows different trends by season, possibly also indicating a shift in timing. Fish condition showed a drop across all species in the early 2000s, but most species appear to have recovered. There is a significant decreasing trend in aggregate numbers of small fish per large fish (Fig. \ref{ecoprod}). This one clear trend, along with changes in timing at lower trophic levels, suggest a low-moderate risk of changing ecosystem productivity in the Mid-Atlantic ecosystem.
\newpage
### Population diversity: new, prioritize species
This element is applied at the species level. Changes (particularly reduction) in diversity at the species/stock level (size, sex, reproductive). *Needs data workup by species, select priority species for age/size diversity*
Proposed definition:
Population Diversity - Risk of not achieving OY due to reduced species/stock diversity (size, sex, genetic, reproductive). Clarification of risk to OY over the short term or long term would be useful.
Indicators:
Stock specific indicators of size and age diversity could be derived from stock assessment information. Indicators of genetic and reproductive diversity would require investigation to determine availability by stock.
Potential risk criteria:
```{r riskpopdiv, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No trend in diversity measure |
| Low-Moderate | Significant long term trend (either direction) in diversity measure |
| Moderate-High | Significant recent increasing trend in diversity measure |
| High | Significant recent downward trend in diversity measure |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
\newpage
### Ecological Diversity: new
Diversity of species within ecosystems provides the capacity to adapt to change at the ecosystem level, stabilizing ecosystem structure and function for dependent fishing communities. This element would be applied at the ecosystem level.
Proposed Definition:
Ecological Diversity - Risk of not achieving OY due to reduced species diversity and altered ecosystem structure. Clarification of risk to OY over the short term or long term would be useful.
Indicators:
Ecological diversity indicators from surveys (adult fish, juvenile fish, and zooplankton) are included in the State of the Ecosystem reports.
```{r, code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/LTL_MAB.Rmd-zoo-diversity.R")}
```
```{r, code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/macrofauna_MAB.Rmd-ichthyo-diversity.R")}
```
```{r , code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/macrofauna_MAB.Rmd-exp-n.R")}
#exp-n, fig.cap = "Adult fish diversity the Mid-Atlantic Bight, based on expected number of species."
```
Potential risk criteria:
```{r riskecodiv, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No trend in diversity measure |
| Low-Moderate | Significant long term trend (either direction) in diversity measure |
| Moderate-High | Significant recent increasing trend in diversity measure |
| High | Significant recent downward trend in diversity measure |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
\newpage
### Offshore habitat: new
Offshore habitat supports all life stages of many Council managed species, and is changing in quality and quantity due to multiple stressors from climate to other ocean uses such as offshore wind development. This element is applied at the species level, and evaluates risk of achieving OY due to changes in offshore habitat quality and quantity.
Proposed definition:
Risk of not achieving OY due to changing offshore habitat. The rationale is that multiple drivers of offshore habitat change, including ocean industrialization, are included in this definition.
Indicators:
Indicators of offshore habitat trends are available from species-specific habitat modeling through the Northeast Regional Habitat Assessment and multiple other efforts throughout the region.
Potential risk criteria:
\newpage
### Invasive Species: new
Invasive species (defined as non-native to the ecosystem *and* likely to cause harm to the environment and or economy) are spread by human activity and have the potential to disrupt ecosystem structure and function.
This element would be applied at the ecosystem level, and would evaluate risks to OY across all Council managed species due to
invasive species interactions and impacts on stock productivity.
Proposed definition:
Risk of not achieving OY due to invasive species threats to managed species productivity.
Indicators:
Invasive species in the Northwest Atlantic would be identified through a combination of literature search, survey, and fishery data.
Potential risk criteria:
```{r, code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/human_dimensions_MAB.Rmd-setup.R")}
```
```{r, code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/human_dimensions_MAB.Rmd-GIS-setup.R")}
```
\newpage
## Economic elements
### Commercial revenue
This element is applied at the ecosystem level, and addresses the risk of not maximizing fishery value. Revenue serves as a proxy for commercial profits, which is the component of a fishery's value that this element is ultimately attempting to assess risk towards. Lack of cost information across all fleet segments precludes the assessment of risk to profitability itself at the ecosystem level.
Proposed definition:
Risk of not maximizing commercial fishery value.
Indicators:
Gross revenue is the current indicator for this element, and can be developed for all fishing activity within the Mid-Atlantic and for all Council managed species. Revenue serves as a proxy for commercial profits, which is the component of a fishery’s value that this element is ultimately attempting to assess risk towards. Currently this indicator is aggregated and presented at the ecosystem-level.
```{r , code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/human_dimensions_MAB.Rmd-comdat-comm-revenue.R")}
#, fig.width = 5, fig.asp = 0.45
#comm-revenue, fig.width = 4, fig.asp = 0.45, fig.cap = "Total revenue for the region (black) and revenue from MAFMC managed species (red)."
```
Net revenue (Gross revenue - trip costs) is a better proxy for trip value, in an economic context. However, this metric can be calculated only for trips by vessels holding federal licenses and submitting Vessel Trip Reports. This indicator would thus not capture all fishing within the region, and of potential interest to the Council.
Catch per unit effort has been suggested by the AP/Committee. However, clarity would be needed in terms of how this indicator should be calculated and interpreted in order to better inform Council decision-making.
Potentially, multiple indicators could be used to better proxy for commercial fishery value.
Proposed risk criteria:
Low risk was defined as no trend and low variability in revenue. Low-Moderate risk was increasing or overall high variability in revenue. Moderate-High risk was a significant long-term revenue decrease. High risk was a significant recent decrease in revenue.
```{r riskcomval, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| 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 |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
Previous risk discussion:
Aggregate commercial revenue for Council-managed species was calculated. Consistent with other published work (@gaichas_framework_2016, Figs 2-3) there is a long term significant decrease in revenue, indicating moderate-high risk to commercial fishery profit.
\newpage
### Commercial fishery resilience (revenue diversity)
This element is applied at the ecosystem level, and addresses the potential risk of reduced commercial fishery business resilience by evaluating species diversity of revenue at the permit level.
Proposed definition:
Commercial Fishery Resilience (Species Revenue Diversity) - Risk of reduced of commercial fishery business resilience (at permit level).
Indicators:
Currently the average effective Shannon index for species revenue at the permit level is used to calculate diversity for all permits landing any amount of Council-managed species within a year (including both monkfish and spiny dogfish). Although the exact value of the effective Shannon index is relatively uninformative in this context, the relative value identifies changes in diversity.
```{r, code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/human_dimensions_MAB.Rmd-commercial-div-species-div.R"), fig.asp=.4}
```
Other metrics for diversity exist. The Simpson index is a common measure of biodiversity, but has the undesirable attribute of being asymmetric and weighing more common types more heavily than the less common types. Although the Shannon index provides a measure proportional to each type’s relative frequency, the effective Shannon index has the added benefit of converting diversity measures onto a common scale, which is important when averaging across permits after calculation. As such, the effective Shannon index was selected as the preferred index of fishing diversity, consistent with the literature (Thunberg & Correia 2015).
Potential risk criteria:
```{r riskfrel1, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No trend in diversity measure |
| Low-Moderate | Increasing or high variability in diversity measure |
| Moderate-High | Significant long term downward trend in diversity measure
| High | Significant recent downward trend in diversity measure |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
Low risk was defined as no trend and low variability in the diversity measure. Low-Moderate risk was increasing or overall high variability in the diversity measure. Moderate-High risk was a significant long term decrease in the diversity measure. High risk was a significant recent decrease in the diversity measure.
\newpage
### Fishery Resilience (4,5,6): combine into Commercial fishery resilience (business and economic pressures)
This element is applied at the *??* level.
Proposed definition:
Risk of reduced fishery business resilience due to business and economic pressures.
Indicators:
Indicators capturing the risk envisioned by the Committee/AP could include access to capital, inflation, gas prices, insurance prices, etc. However, the Committee/AP would need to clarify how this differs from the other elements previously identified in order to ensure no double-counting occurs.
Potential risk criteria:
```{r riskfrel2, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No trend in access to capital |
| Low-Moderate | Increasing or high variability in access to capital |
| Moderate-High | Significant long term decrease in access to capital |
| High | Significant recent decrease in access to capital |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
```{r riskfrel3, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No trend in insurance availability |
| Low-Moderate | Increasing or high variability in insurance availability |
| Moderate-High | Significant long term decrease in insurance availability |
| High | Significant recent decrease in insurance availability |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
### Seafood Safety (merge into discussion of fishery resilience)
This element is applied at the ??? level. This element describes the risk to market access (e.g. spiny dogfish EU market; surfclam on GB and PSP) more than potential risks to human health.
```{r risksafe, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No current seafood safety advisory |
| Low-Moderate | Current seafood safety advisory for high risk individuals in some states |
| Moderate-High | Current seafood safety advisory for general population in some states |
| High | Current seafood safety advisory for general population in majority of states |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
\newpage
### Commercial fishery resilience (shoreside support)
This element is applied at the ecosystem level, and ranks the risk of reduced commercial fishery business resilience due to shoreside support infrastructure by examining the number of shoreside support businesses.
Proposed definition:
Risk of reduced commercial fishery business resilience due to loss of shoreside support infrastructure.
Indicators:
Current indicators include the number of shoreside support businesses. The number of shoreside support businesses were tallied for all Mid-Atlantic states in two categories: number of companies (Quarterly Census of Employment and Wages. Obtained September 27, 2017. US Department of Labor, Bureau of Labor Statistics. https://www.bls.gov/cew/home.htm) and number of non-employer entities Non-employer Statistics.” Obtained September 28, 2017. U.S. Census Bureau. https://www.census.gov/programs-surveys/nonemployer-statistics.html), which we consider separately. Non-employer entities are businesses that have no paid employees (i.e. entrepreneurs, or the owner is the workforce), while the shoreside support companies include all businesses with paid employees. Some state level data was not included due to confidentiality.
The number of shoreside support companies include seafood merchant wholesalers, seafood product preparation and packaging, and seafood markets across all Mid-Atlantic states. The indicator shows a significant long-term and short-term decrease, which represents moderate-high risk to fishery resilience. The number of non-employer entities, including seafood preparation and packaging and seafood markets, shows a long-term increase (Fig. , Lower right). Data from other shoreside fishery supporting businesses, such as gear manufacturers and welding companies, are not included here due to aggregation of the statistics across non-fishing industries (e.g. net manufacturers combined with all other businesses).
Potential risk criteria:
```{r riskfrel4, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No trend in shoreside support businesses |
| Low-Moderate | Increasing or high variability in shoreside support businesses |
| Moderate-High | Significant recent decrease in one measure of shoreside support businesses |
| High | Significant recent decrease in multiple measures of shoreside support businesses |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
Previous risk discussion:
Low risk was defined as no trend and low variability in the number of shoreside support businesses. Low-Moderate risk was increasing variability or overall high variability in shoreside support businesses. Moderate-High risk was a significant recent decrease in one measure of shoreside support businesses. High risk was a significant recent decrease in multiple measures of shoreside support businesses.
The number of shoreside support businesses were tallied for all Mid-Atlantic states in two categories: number of companies (Quarterly Census of Employment and Wages. Obtained September 27, 2017. US Department of Labor, Bureau of Labor Statistics. https://www.bls.gov/cew/home.htm) and number of non-employer entities Nonemployer Statistics.” Obtained September 28, 2017. U.S. Census Bureau.
https://www.census.gov/programs-surveys/nonemployer-statistics.html), which we consider separately. Nonemployer entities are businesses that have no paid employees (i.e. entrepreneurs, or the owner is the workforce), while the shoreside support companies include all businesses with paid employees. Some state level data was not included due to confidentiality.
The number of shoreside support companies include seafood merchant wholesalers, seafood product preparation and packaging, and seafood markets across all Mid-Atlantic states. The indicator shows a significant long-term and short-term decrease, which represents moderate-high risk to fishery resilience. The number of non-employer entities, including seafood preparation and packaging and seafood markets, shows a long-term increase (Fig. \ref{econinds}, Lower right). Data from other shoreside fishery supporting businesses, such as gear manufacturers and welding companies, are not included here due to aggregation of the statistics across non-fishing industries (e.g. net manufacturers combined with all other businesses).
\newpage
### Recreational Fishery Resilience (new)
This element ranks the risk of reduced fishery business resilience due to shoreside support infrastructure by examining the number of shoreside support businesses.
Proposed definition:
Risk of reduced fishery business resilience due to shoreside support infrastructure (marinas, bait and tackle shops, etc.).
Indicators:
Number of shoreside support businesses, including marinas and bait and tackle shops. Are there other businesses which should be tracked?
Potential risk criteria:
\newpage
## Social-cultural elements
### Commercial fleet diversity
This element is applied at the ecosystem level, and ranks the risk to maintaining equity in access to fishery resources. Beyond equity concerns, maintaining diversity can provide the capacity to adapt to change at the ecosystem level for dependent fishing communities, and can address objectives related to stability.
Proposed definition:
Risk of reduced fishery resilience (number and diversity of fleets).
Indicators:
Currently the diversity in revenue generated by different fleet segments, as well as a count of the number of active fleets, at the ecosystem level. A fleet is defined here as the combination of gear (Scallop Dredge, Other Dredge, Gillnet, Hand Gear, Longline, Bottom Trawl, Midwater Trawl, Pot, Purse Seine, or Clam Dredge) and vessel length category (Less than 30 ft, 30 to 50 ft, 50 to 75 feet, 75 ft and above). The effective Shannon index is used to calculate the diversity of revenue across these fleets. Although the exact value of the effective Shannon index is relatively uninformative in this context, the relative value identifies changes in diversity.
```{r, code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/human_dimensions_MAB.Rmd-commercial-div.R"), fig.asp=.85}
```
Other metrics for diversity exist. The Simpson index is a common measure of biodiversity, but has the undesirable attribute of being asymmetric and weighing more common types more heavily than the less common types. Although the Shannon index provides a measure proportional to each type’s relative frequency, the effective Shannon index has the added benefit of converting diversity measures onto a common scale. As such, the effective Shannon index was selected as the preferred index of fishing diversity, consistent with the literature and ensuring no differential treatment between large and small fleets (Thunberg & Correia 2015).
Potential risk criteria:
Low risk was defined as no trend and low variability in the diversity measure. Low-Moderate risk was increasing variability or overall high variability in the diversity measure. Moderate-High risk was a significant long-term decrease in the diversity measure. High risk was a significant recent decrease in the diversity measure.
```{r riskfltdiv, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No trend in diversity measure |
| Low-Moderate | Increasing or high variability in diversity measure |
| Moderate-High | Significant long term downward trend in diversity measure
| High | Significant recent downward trend in diversity measure |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
Previous risk discussion:
A declining trend in diversity indicates a less diverse fleet is currently active in Council-managed fisheries. However, it cannot distinguish whether specialization (by choice), or alternatively stovepiping (constrained choices), is occurring, rather merely that the fleet composition is changing, which might warrant additional scrutiny. There is a long term decrease in the fleet count metric (Fig. \ref{commrisk}, top panel). Therefore, this element ranks moderate-high risk. The number of fleets in the Mid-Atlantic seems to be negatively correlated to the revenue diversity metric in the most recent five years, which indicates that the latter results are being dominated by changes in the distribution of revenue across fleets, as opposed to the number of active fleets.
\newpage
### Recreational Fleet Diversity (new)
This element is applied at the ecosystem level, and ranks the risk to maintaining equity in recreational access to fishery resources. Beyond equity concerns, maintaining diversity can provide the capacity to adapt to change at the ecosystem level for dependent fishing communities, and can address objectives related to stability.
Proposed definition:
Risk of reduced recreational fishery business resilience.
Indicators:
Recreational fleet effort diversity is already presented in the Mid-Atlantic State of the Ecosystem Report. This indicator is an effective Shannon estimate of diversity of effort across mode (i.e. effort by shoreside, private boat, and for-hire anglers).
```{r , code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/human_dimensions_MAB.Rmd-recdat-diversity.R")}
#rec-div, fig.cap = paste0("Recreational fleet effort diversity in the ",region,".")
```
Other metrics for diversity exist. The Simpson index is a common measure of biodiversity, but has the undesirable attribute of being asymmetric and weighing more common types more heavily than the less common types. Although the Shannon index provides a measure proportional to each type’s relative frequency, the effective Shannon index has the added benefit of converting diversity measures onto a common scale. As such, the effective Shannon index was selected as the preferred index of fishing diversity, consistent with the literature and ensuring no differential treatment between large and small mode contributions (Thunberg & Correia 2015).
Potential risk criteria:
Similar criteria could be applied as for comercial diversity. Low risk was defined as no trend and low variability in the diversity measure. Low-Moderate risk was increasing variability or overall high variability in the diversity measure. Moderate-High risk was a significant long-term decrease in the diversity measure. High risk was a significant recent decrease in the diversity measure.
```{r riskrecfltdiv, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No trend in diversity measure |
| Low-Moderate | Increasing or high variability in diversity measure |
| Moderate-High | Significant long term downward trend in diversity measure
| High | Significant recent downward trend in diversity measure |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
\newpage
## Food production elements
### Recreational/subsistence food production
This element is applied at the ecosystem level, and describes the risk of not maintaining personal food production.
Proposed definition:
Risk of not maintaining personal food production (current)
Indicators:
Total recreational harvest (all species) and harvest per angler were evaluated indicators in the Mid-Atlantic region. Recreational seafood landings (as opposed to total catch which includes catch and release that are captured under other Risk Elements/indicators) were used to assess food use of recreationally caught fish.
```{r, code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/human_dimensions_MAB.Rmd-recdat-landings.R"), fig.asp=.4}
#, rec-landings, fig.cap = paste0("Total recreational seafood harvest (millions of fish) in the ",region," region.")
```
Potential risk criteria:
```{r riskrfood, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No trend or increase in recreational landings |
| Low-Moderate | Increasing or high variability in recreational landings |
| Moderate-High | Significant long term decrease in recreational landings |
| High | Significant recent decrease in recreational landings |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
Low risk was defined as no trend, or an increase in recreational seafood landings. Low-Moderate risk was increasing or high variability in recreational seafood landings. Moderate-High risk was a significant long-term decrease in recreational seafood landings. High risk was a significant recent decrease in recreational seafood landings.
Previous risk discussion:
This significant long term decrease in both recreational landings and recreational landings per angler represents a moderate-high risk to recreational food production.
\newpage
### Commercial Employment (left aside)
This element ranks the risk of not optimizing employment opportunities in the commercial sector. This objective should be refined if possible. What does optimized employment entail?
Proposed definition:
Risk of not optimizing commercial job creation and retention
Indicators:
Number of individuals employed by commercial fisheries. This indicator needs to be refined. For example, should this include solely those employed directly by fishing vessels, or should this include all employment (e.g. ice houses, gas, etc.)? Should it be estimated at the system level, state level, or something else?
Potential risk criteria:
\newpage
### Recreational Employment (left aside)
This element ranks the risk of not optimizing employment opportunities in the recreational sector. This objective should be refined if possible. What does optimized employment entail?
Proposed definition:
Risk of not optimizing recreational job creation and retention
Indicators:
Number of individuals employed by recreational fisheries. This indicator needs to be refined. For example, should this include solely those employed directly by charter/party fishing vessels, or should this include all employment (e.g. bait shops, marinas, etc.)? Should it be estimated at the system level, state level, or something else?
Potential risk criteria:
\newpage
## Management elements
### Other ocean uses: rename "Other Ocean Activities" and refine indicators, or separate into components following
Current description:
This element is applied at the species and sector (commercial and recreational) level, and addresses the risk of fishery displacement or damage of a fishery resource and/or supporting habitat as a result of non-fishing activities in the ocean (e.g., energy development/sand mining/other industrial uses, etc.). Many of these activities are in planning stages but not yet implemented in the region. It also includes evaluation of risk to Council fisheries from area-based measures outside of the control of the Council, including area closures implemented by other Councils to protect sensitive habitats, spawning areas, etc. and/or through marine monument or other types of area-based management designations.
Proposed definition:
Risk of not achieving OY due to fishery displacement or damage to resource/habitat from non-fishing ocean activities
Indicators:
There currently is no specific indicator for this element and expert judgment is used to determine impacts to fishery access and habitat quality and function due to other ocean uses. A more quantitative approach (similar to that done for offshore wind) could be applied with GIS mapping to determine the spatial footprint of current and future planned non-fishing activities could be calculated and qualify and spatial overlap with existing habitat and/or fishing ground locations. Could look to see what information and at what spatial scale is available from the NMFS Habitat Climate Vulnerability Assessment, the Mid-Atlantic Council NRHA data explorer, and the America the CCC Area-Based Management tool.
Current risk criteria:
```{r riskoou, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | No overlap; no impact on habitat |
| Low-Moderate | Low-moderate overlap; minor habitat impacts but transient |
| Moderate-High | Moderate-high overlap; minor habitat impacts but persistent |
| High | High overlap; other uses could seriously disrupt fishery prosecution; major permanent habitat impacts |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
Previous risk discussion:
Council staff used expert knowledge to determine impacts to fishery access and habitat quality and function due to other ocean uses, as quantitative evaluation of activities in early planning stages is not practical. Low risk ranking was defined as no overlap of the fishery with other ocean activities and/or no impact on habitat. Low-Moderate risk was defined as potential for fishery overlap and/or minor habitat impacts but transient. Moderate-High risk were potential loss of access to some fishing areas and/or minor habitat impacts but persistent. High risk were other ocean uses would restrict fishing in the prime fishing areas and/or result in major permanent habitat impacts. As the footprint of offshore energy development becomes clearer, this element could be evaluated through GIS analyses which quantify the degree of overlap ocean uses and quantitative risk criteria (e.g. 30% overlap) could also be used.
Recreational fisheries for Atlantic mackerel, golden and blueline tilefish, bluefish, and spiny dogfish and commercial fisheries for both tilefish were low risk due to no overlap with other ocean uses. Commercial fisheries for surfclams, ocean quahogs, shortfin squid, and bluefish, and both sectors for summer flounder and scup ranked low-moderate risk due to the potential for minor habitat or fishery impacts from other ocean uses; these will depend on extent of development of those activities (i.e., energy, aquaculture, etc.). Recreational black sea bass and commercial Atlantic mackerel, butterfish, and spiny dogfish ranked moderate-high risk due to potential for loss of access to fishing grounds (especially by mobile gear) and habitat loss due to offshore energy development in some prime fishing areas. However, it was noted for black sea bass that hard subsurface structures associated with energy production might provide some mitigation of habitat loss. Commercial black sea bass (mobile gear) and longfin squid ranked high risk due to potential for loss of access to fishing grounds and habitat loss due to offshore energy development in many prime fishing areas. Deepsea corals are also under management as protected habitat by the Council, and were ranked moderate-high risk for other ocean uses due to their sensitivity to benthic disturbance by offshore energy development, deep sea exploration, and mining.
\newpage
### Offshore Wind Biological/Ecosystem (new)
This element would be applied at the species level and considers the risks of offshore wind development on Council-managed fishery resources and/or the supporting habitat. Offshore wind development is expected to cover 2.4 million acres of ocean space by 2030 in the Greater Atlantic region (ME through NC). Within these lease areas, there are 3,400 foundations (i.e., wind turbines) with over 9,000 miles of interconnecting cable proposed for construction. Offshore wind siting, construction, and operation has the potential for a variety of biological impacts and associated risks for fisheries resources. Habitat alteration, local hydrodynamic changes, underwater noise, and electromagnetic fields (EMF) can affect stock productivity, food availability and migration patterns. However, these risks are likely different across species and habitat types and more research is needed to fully understand these impacts.
Proposed definition:
Risk of not achieving OY due to biological impacts to stock productivity, distribution, and ecosystem structure/function/interactions
Additional EOP/Council input is needed to identify a preference for either one Offshore Wind risk element that captures all potential risks or separate out risks into different risk elements. The risks associated with a biologically focused element are more likely to remain relatively stationary (i.e., the impacts for a particular species will be the same, but the scale may change as more offshore development changes), while scientific and access risks may be more dynamic and more tractable. Of the two biological/ecosystem focused definitions considered here, definition #1 seems to be more appropriate.
Indicators:
Information and relevant data at the species level available in the NOAA Tech Memo titled “Fisheries and Offshore Wind Interactions: Synthesis of Science”.
Species distribution overlap with offshore wind from a couple of potential data sources (e.g., https://apps-st.fisheries.noaa.gov/dismap/DisMAP.html). Translating exposure into a risk of impacts, which is likely to be different by species, may be challenging.

Potential risk criteria:
\newpage
### Offshore Wind Fishery Science and Access (new)
This element would be applied at the species and sector (commercial and recreational) level and considers the risks of offshore wind development on data and science quality and to fishery/fleet access for Council-managed fishery resources. Given the anticipated overlap between offshore wind lease areas and spatial coverage of many fishery-dependent survey strata, there are anticipated survey impacts through “preclusion, habitat change, changes in statistical design, and reduced sampling productivity” (Hogan et al. 2023). These impacts to the quality and quantity of the data could have implications for stock assessments, scientific uncertainty, and catch levels. As wind turbine construction and operation continues and expands, fishing fleet access, fishing operations, and revenue are anticipated to change.
Proposed definition:
Risk of not achieving OY due to fishery impacts to due access, stock availability, and scientific uncertainty
Similar to the comment under the Offshore Wind - Biological/Ecosystem risk element above, this is really how the EOP/Council wants to consider risks from offshore wind development - a comprehensive element or separate risk elements for different risks. Under this option, EOP Committee and AP feedback favored a more comprehensive risk element.
Indicators:
Indicators for the Mid-Atlantic State of the Ecosystem and socioeconomic impacts web site- Fishery revenue and party charter activity from within lease areas by species, fleet, or community, community vulnerability/engagement/EEJ, spatial overlap of lease areas and federal fisheries surveys.
```{r, code=readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/human_dimensions_MAB.Rmd-wea-spp-rev.R")}
#, fig.width=5, fig.asp=.4
#wea-spp-rev, fig.cap="Wind energy revenue in the Mid-Atlantic."
```
```{r, code = readLines("https://raw.githubusercontent.com/NOAA-EDAB/ecodata/master/chunk-scripts/human_dimensions_MAB.Rmd-wea-port-rev.R"), fig.asp=1.1}
```

Information and relevant data at the species level available in the NOAA Tech Memo titled “Fisheries and Offshore Wind Interactions: Synthesis of Science”
FishRules and FishBrain apps for recreational fishing spatial overlap information (work is still under review).
Potential risk criteria:
\newpage
### Offshore Energy Exclusive of Wind (new): combine with Other Ocean Activities
This element would be applied at the species and sector (commercial and recreational) level and considers the risks of non-wind related energy development offshore, which could include tidal energy turbines, oil and gas extraction, and other development of offshore energy infrastructure.
Proposed definition:
Additional EOP/Council input on this risk element is needed. There are other risk elements that consider other ocean uses (some with/without offshore wind considerations) and habitat condition which could address the risks associated with the proposed definitions included here. Clarity and additional feedback on the metric objectives and associated risks the EOP are interested in considering for this element would be beneficial.
Indicators:
Depends upon definition.
\newpage
### Aquaculture (new): combine with Other Ocean Activities
There is growing interest in the continued development and expansion of aquaculture production to support the increasing consumption of seafood and complement wild-caught fisheries. The Council does have an aquaculture policy, but does not have regulatory authority over aquaculture permitting, development, or operation. This element would be applied at the species level and would consider the biological and/or spatial risks of aquaculture development on Mid-Atlantic Council managed fisheries.
Proposed definition:
Additional feedback from the EOP/Council on this risk element would be beneficial.
Indicators:
Previous Mid-Atlantic State of the Ecosystem report have included an aquaculture indicator that provides information on total aquaculture production in the Mid-Atlantic. As offshore aquaculture develops, the spatial overlap and revenue impacts between aquaculture areas and existing fishing operations could be developed (similar to analyses conducted for offshore wind).
\newpage
### Regulatory complexity and stability
This element is applied at the species and sector (commercial and recreational) level. Constituents have frequently raised concerns about the complexity and continually changing fishery regulations and the need to simplify them to improve their efficacy. Complex and constantly changing regulations may lead to non-compliance and/or impact other fisheries. Non-compliance could have stock assessment, data quality, management, and fairness and equity implications.
This element could be evaluated by quantifying the number of regulations and/or the frequency of regulatory changes, based on evaluation of the Code of Federal Regulations. In terms of recreational fisheries, the magnitude and frequency of change in management measures (size and bag limits, seasons, etc.) could also be evaluated/quantified. For this assessment, Council staff used expert opinion to assess risk. Low risk rankings were simple/few regulations that rarely, if ever, change. Low-Moderate risk were low-moderate complexity regulations and/or occasional changes. Moderate-High risk were moderate-high complexity and occasional changes. High risk were highly complex or frequently changing regulations.
Proposed definitions:
1 - Regulatory Compliance - Risk of not achieving regulatory compliance due to complexity and modifications
2 (current) - Regulatory Complexity and Stability - Risk of not achieving compliance due to regulatory complexity and modifications
3 - Regulatory Complexity and Stability - Risk of not achieving OY due to regulatory complexity and modifications
Indicators:
This element could be evaluated by quantifying the number of regulations and/or the frequency of regulatory changes, based on evaluation of the Code of Federal Regulations. In terms of recreational fisheries, the magnitude and frequency of change in management measures (size and bag limits, seasons, etc.) could also be evaluated/quantified. To date, Council staff have considered the frequency of regulatory change over the last 5 years by fishery and sector. The number of law enforcement citations or warnings could be used determine compliance, but information at the fishery and sector level could be limited. For the recreational fishery, the proportion of non-compliant harvest relative to total harvest reported by MRIP could be used as a measure of compliance for each recreational fishery.
Potential risk criteria:
```{r riskcomplex, echo=FALSE, message=FALSE, warnings=FALSE, results='asis'}
tabl <- "
| Risk Level | Definition |
|:-------------------|:--------------------------------------------------------------------|
| Low | Simple/few regulations; rarely if ever change |
| Low-Moderate | Low-moderate complexity; occasional changes |
| Moderate-High | Moderate-high complexity; occasional changes |
| High | High complexity; frequently changed |
"
cat(tabl) # output the table in a format good for HTML/PDF/docx conversion
```
Previous risk discussion:
Surfclam, ocean quahog, recreational bluefish, Atlantic mackerel and spiny dogfish and both golden tilefish fisheries ranked low risk for complexity with only minor/no changes to regulations in recent years, relatively stable catch specifications and/or limited regulatory complexity. Commercial bluefish and shortfin squid ranked low-moderate risk with fairly complex regulations that have been stable over time, but may change in the near future. Both sectors for scup and commercial summer flounder and black sea bass fisheries ranked moderate-high risk with minimum size, commercial gear requirements, quota allocation systems, and reporting all very stable, but regulations can be complex, particularly at the state level with varying trip limits, permitting, and reporting systems. The moderate-high risk rankings for both recreational and commercial blueline tilefish and commercial spiny dogfish fisheries were based on recent and frequent changes in regulations. Recreational fisheries for summer flounder and black sea bass ranked high risk due to nearly annual changes in size, season, and possession limits, significant differences between states, reporting, and data estimation changes. Similarly, commercial fisheries for Atlantic mackerel, butterfish, and longfin squid regulations are highly complex and frequently changed, resulting in a high risk ranking.
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### Essential Fish Habitat (new)
The MSA requires federal fishery management councils and NOAA’s National Marine Fisheries Service to designate Essential Fish Habitat (EFH) for species managed under federal fishery management plans. EFH designation is important because it means those areas will be given additional consideration before any federal agencies are allowed to carry out activities in those areas. This element would be applied at the species level and would consider risks for not properly identifying and/or projecting EFH for Council-managed species.
Proposed definition:
Risk of not identifying and/or protecting essential fish habitat and implications for Council-managed species
Indicators:
The Northeast Habitat Climate Vulnerability Assessment and the Northeast Regional Habitat Assessment (https://www.mafmc.org/nrha) Data Explorer could be used to help identify EFH and critical habitats and potentially quantify changes in the total/spatial extent of these habitats over time. The Council is currently reviewing EFH designations for all Council-managed species and outcomes from that action could be applied here.
Potential risk criteria:
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## References