1 Descriptive Section

1.1 Indicator category

[1] “Fish”

1.2 Indicator name

Species Richness

Includes variable(s): lower-Richness, mean-Richness, median-Richness, Shannon, upper-Richness

1.3 Indicator brief description

Species richness is the number of unique species predicted to be captured in NEFSC bottom trawl survey tows, conducted within each of four ecological production units (EPUs) in each year between 2000 and 2019. This is based on simulations from a joint-species distribution model fitted to presence-absence data for 55 species routinely collected by spring and fall surveys during the corresponding time period. Vessel-specific differences in capture efficiency are estimated by the model, and then predictions are generated at the Albatross IV scale. See SOE Tech Doc for details of the model, species considered, and environmental covariates included.

1.4 Indicator visualization

An overall trend of declining richness can be seen in the more southerly Mid-Atlantic Bight (MAB) region during the modeled time period (2000-2019), while the more northerly regions (i.e., the Gulf of Maine and Georges Bank) are characterized by concurrent gains in richness. These patterns reflect the increasingly rare occurrence of cooler-water species (e.g., Atlantic cod, American plaice, and Atlantic pollock) in southern waters and the growing prevalence of warmer-water species (e.g., weakfish, spotted hake, and black sea bass) in the north, likely as a direct result of warming ocean temperatures.

2 SMART Attribute Section

2.1 Indicator documentation

2.1.1 Are indicators available for others to use (data downloadable)?

Yes

2.1.1.1 Where can indicators be found?

Data: https://noaa-edab.github.io/ecodata/index.html

Description: https://noaa-edab.github.io/catalog/habitat_diversity.html

Technical documentation: https://noaa-edab.github.io/tech-doc/habitat_diversity.html

2.1.1.2 How often are they updated? Are future updates likely?

[need sequential look at datasets for update frequency. Future requires judgement]

2.1.1.3 Who is the contact?

Chris Haak (chrishaak@gmail.com)

2.1.2 Gather indicator statistics

2.1.2.1 Units

Indicator	Units
lower-Richness	no Units field
mean-Richness	no Units field
median-Richness	no Units field
Shannon	no Units field
upper-Richness	no Units field

2.1.2.2 Length of time series, start and end date, periodicity

General overview: Spring (March-May) and fall (September-November) NEFSC bottom trawl surveys from 2000-2019

Indicator specifics:

Indicator	EPU	StartYear	EndYear	NumYears
lower-Richness	GB	2000	2019	20
lower-Richness	GOM	2000	2019	20
lower-Richness	MAB	2000	2019	20
lower-Richness	SS	2000	2019	20
mean-Richness	GB	2000	2019	20
mean-Richness	GOM	2000	2019	20
mean-Richness	MAB	2000	2019	20
mean-Richness	SS	2000	2019	20
median-Richness	GB	2000	2019	20
median-Richness	GOM	2000	2019	20
median-Richness	MAB	2000	2019	20
median-Richness	SS	2000	2019	20
Shannon	GB	2000	2019	20
Shannon	GOM	2000	2019	20
Shannon	MAB	2000	2019	20
Shannon	SS	2000	2019	20
upper-Richness	GB	2000	2019	20
upper-Richness	GOM	2000	2019	20
upper-Richness	MAB	2000	2019	20
upper-Richness	SS	2000	2019	20

2.1.2.3 Spatial location, scale and extent

General overview: Ecological production units (4) on the Northeast US continental shelf (as sampled by NEFSC spring and fall bottom trawl surveys)

Indicator specifics:

Indicator	EPU
lower-Richness	GB
lower-Richness	GOM
lower-Richness	MAB
lower-Richness	SS
mean-Richness	GB
mean-Richness	GOM
mean-Richness	MAB
mean-Richness	SS
median-Richness	GB
median-Richness	GOM
median-Richness	MAB
median-Richness	SS
Shannon	GB
Shannon	GOM
Shannon	MAB
Shannon	SS
upper-Richness	GB
upper-Richness	GOM
upper-Richness	MAB
upper-Richness	SS

2.1.2.4 Management scale: all species, FMP level, species level, can it be aggregated or separated to different scales?

[Classify by hand, note gridded data if available could be applied to different species ranges]

2.1.2.5 Uncertainty metrics

Uncertainty is captured in these variables:

[1] “lower-Richness” “upper-Richness”

2.1.3 Are methods clearly documented to obtain source data and calculate indicators?

Yes

2.1.3.1 Can the indicator be calculated from current documentation?

Estimated species richness is the number of unique species expected to be observed in NEFSC bottom trawl surveys conducted in a given ecological production unit (EPU) and year, based on a fitted joint-species distribution/habitat suitability model (considering only the 55 commonly-occurring species listed above). A spatiotemporal joint species distribution model was fitted to n=13231 observations of presence/absence in the Spring and Fall NEFSC bottom trawl surveys for the years 2000-2019, using the Community Level Basis Function Model (CBFM) framework with a binomial error distribution and logistic link function. The probability of presence was modeled as a function of environmental predictor variables (using smooth terms), a vessel effect (factor) to account for changes in sampling gear, as well as spatiotemporal (Lat, Lon, Month) and temporal (Year) random effects, which were estimated hierarchically through a set of species-common basis functions. The model thus controls for differences in capture efficiency across survey vessels, permitting predictions on a common scale (here calibrated to the RFV Albatross IV). Covariate values (i.e., environmental parameters) corresponding to the approximate location (and time, when applicable) of each observation (i.e., tow) were extracted from the following sources: Monthly mean surface and bottom temperature, surface and bottom salinity, and sea surface height anomaly were obtained from the GLORYS12V1 reanalysis (Jean-Michel et al. (2021)), as were annual minimum and maximum surface and bottom temperatures. Monthly mean underwater optical parameters, including the intensity (photosynthetically active radiation - PAR) and spectral composition (hue angle) of downwelling light at mid-water column, were estimated from remote sensing data, following the methods of Z.-P. Lee et al. (2005) and Z. Lee et al. (2022), respectively. Hydrodynamic stress near the seabed (95th quantile) was obtained from the USGS Sea Floor Stress and Sediment Mobility database (Dalyander et al. 2012). Annually-integrated chlorophyll was obtained from the Oceancolour-CCI (version 5) release (https://www.oceancolour.org/). Bathymetric position index (BPI), benthic structural complexity, and sediment type data were estimated following the methods described at: https://www.conservationgateway.org/ConservationByGeography/NorthAmerica/UnitedStates/edc/reportsdata/marine/namera/namera/Pages/default.aspx/ Simulating from the fitted model, we generated 100 random draws of “joint” predictions of the species assemblage observed in the survey, taking into account species residual covariances (see Wilkinson et al. (2021) for additional details). We used these to produce estimates of the mean species richness (and corresponding 95% prediction intervals) across all observations within each ecological production unit (EPU) for each modeled year (2000-2019).

2.1.3.2 Is code publicly available? up to date?

2.1.3.3 Have methods changed over time?

2.1.4 Are indicator underlying source data linked or easy to find?

This analysis is based on NEFSC bottom trawl survey data which are publicly available. Please reached out to nefsc.soe.leads@noaa.gov with questions.

2.1.4.1 Where are source data stored?

Abundance data were extracted from the NEFSC’s SVDBS database using Survdat for 55 fish species regularly sampled on spring and fall NEFSC bottom trawl surveys: Species included in NRHA Diversity Index: Data were converted to presence/absence for species richness modeling.

2.1.4.2 How/by whom are source data updated? Are future updates likely?

SOE Leads nefsc.soe.leads@noaa.gov

[likelihood of source data updates requires judgement, enter by hand]

2.1.4.3 How often are they updated?

[Update by hand, look for source, may require judgement]

2.2 Indicator analysis/testing or history of use

2.2.1 What decision or advice processes are the indicators currently used in?

Species richness can indicate the health of the ecosystem as a metric of biodiversity, and changes in richness over time may reflect distribution shifts or community reorganization. In the present context, richness in a given EPU is presented in terms of 55 commonly sampled fish species, as they are predicted to be observed (i.e., present or absent) in NEFSC spring and fall bottom trawl surveys each year over the modeled time period (conditional on a common level of gear efficiency across years).

2.2.2 What implications of the indicators are currently listed?

The contrasting EPU-specific trends displayed here highlight changes in the composition of marine fish assemblages that are consistent with expected species distribution shifts under warming water temperatures. It is important to note, however, that these estimates of richness consider only a certain (pre-specified) subset of community members, and are not representative of the entire fish community. For instance, it is probable that southerly (warmer-water) species not included in our analysis may be occurring in the MAB with increased frequency, effectively offsetting richness declines in that region. Still, decreases in the prevalence of cooler water taxa in the MAB may signal that fisheries in this region should reassess any reliance on stocks that are fished near the southern extents of their range, and/or shift fishing effort to more southerly species. Simultaneously, an apparent influx of southerly species in the GOM and GB may eventually necessitate the adjustment of management quotas across regions.

2.2.3 Do target, limit, or threshold values already exist for the indicator?

2.2.4 Have the indicators been tested to ensure they respond proportionally to a change in the underlying process?

2.2.5 Are the indicators sensitive to a small change in the process, or what is the threshold of change that is detectable?

Unknown

2.2.6 Is there a time lag between the process change and the indicator change? How long?