Marine-life Data and Analysis Team (MDAT) Marine-life data to support regional ocean planning and management.

Marine Geospatial Ecology Lab / Duke University

Marine Geospatial Ecology LaboratoryNOAA National Marine Fisheries ServiceNational Centers for Coastal Ocean ScienceThe Nature Conservancy

Contact:
marinelife_data@duke.edu
Updated

Abstract

In 2014, the Marine Geospatial Ecology Lab (MGEL) of Duke University began work with the Northeast Regional Ocean Council (NROC), the NOAA National Centers for Coastal Ocean Science (NCCOS), the NOAA Northeast Fisheries Science Center (NEFSC) and Loyola University Chicago, as part of the Marine-life Data and Analysis Team (MDAT), to characterize and map marine life in the Northeast region in support of regional ocean planning. In 2015, the Mid-Atlantic Regional Council on the Ocean (MARCO) contracted with MDAT to build upon and expand this effort into the Mid-Atlantic planning area. These research groups collaborated to produce “base layer” distribution products for cetacean, avian, and fish species. Cetacean and avian products are habitat-based density estimates, incorporating several physical or biological habitat parameters, and were created for the whole US east coast. Fish species products, based on recommendations from working groups and other experts, were kept closer to the original bottom trawl data, which exist from Cape Hatteras, NC to the Gulf of Maine. Base layer products are particularly relevant and useful in answering direct questions about specific species at certain times of year. Base products may be thought of as a reference library, with species-specific products available to be viewed and queried when detailed research is required for agency decision-making actions.

Because base layers total in the thousands, efforts to develop a general understanding of the overall richness or diversity in a particular area are not well served by the individual base products. To address this gap and other potential management applications, MDAT has created several types of summary map products from these base layers. Summary products are comprised of data layers from multiple species, and were created to allow quick access to map summaries about potential biological, management, or sensitivity groups of interest. Summary products provide a means to distill hundreds of data layer and time period combinations into more simplified maps that supplement the base layer reference library. These summary products include total abundance or biomass, species richness, diversity, and core area abundance or biomass richness for all modeled/sampled groups of species and are useful tools for seeing broad patterns in the underlying data or model results.

Careful consideration must be given when viewing and interpreting base layer and summary products. Section 2 of the MDAT Technical Report describes the methods and review processes for the base layer products, with caveats and considerations detailed for each taxa and product. Section 3 of the MDAT Technical Report describes the methods and review processes for the summary products, with caveats and considerations detailed for each taxa and each type of product.

All data MDAT products are hosted on the Northeast and Mid-Atlantic Data Ocean Portals.

Citation

Any use of these data should be accompanied by the following citation:

Curtice C., Cleary J., Shumchenia E., Halpin P.N. 2019. Marine-life Data and Analysis Team (MDAT) technical report on the methods and development of marine-life data to support regional ocean planning and management. Prepared on behalf of the Marine-life Data and Analysis Team (MDAT). Accessed at: http://seamap.env.duke.edu/models/MDAT/MDAT-Technical-Report.pdf

More information

Product Type Collection Level Metadata Download Package(s)
Avian base layer products metadata PDF Avian abundance ZIP
Avian summary products metadata PDF Avian summary ZIP
Fish base layer products metadata PDF NEFSC biomass ZIP
Fish summary products metadata PDF NEFSC fish summary ZIP
Fish Summary Products Time-Series metadata PDF NEFSC fish summary time-series ZIP
Marine mammal base layer products metadata PDF Mammal abundance ZIP
Marine mammal summary products metadata PDF Mammal summary ZIP
Sea turtle base layer products metadata PDF Sea Turtle density ZIP

Version change history

Periodic updates to the base layer models and data are produced by the individual institutions in the MDAT team based on schedules set by the funders of each modeling effort. MDAT summary products are updated as new models and data become available, as feasible.

2024 January

In January 2024, MDAT released an update to the marine mammal summary products to add four climate change vulnerability groups based on Lettrich et al. 2023. This release also changes the threshold used to convert the non-stratified species model layers to presence/absence for inclusion in the species richness summary products from 95% to 99%. For a full description of changes to the current release of marine mammal products, see the summary of changes.

2023 November

In November 2023 the leatherback sea turtle density predictions were updated to correct a problem where an incorrect perception bias estimate was used.

2023 August

In August of 2023, MDAT added base layer products for four sea turtle species provided by the Navy Undersea Warfare Center (NUWC) Division Newport. NUWC created spatial density models estimating long term averages of density, abundance, and distribution for green, Kemp's Ridley, leatherback and loggerhead turtles from line transect survey data from seven providers covering roughly 1.2 million linear kilometers of effort (shipboard and aerial surveys). Details on the source data, methods, and results are in the associated technical report.

2023 June

In June 2023, a fully updated set of marine mammal individual species models and corresponding updated summary products were released. The individual species products include new data and improved methods, while the summary products did not change the underlying methodology.

2022 April

NEFSC group summary products were updated to include a new set of summary products for species potentially vulnerable to electric and magnetic fields (EMF) from undersea power cables. Additionally, given the completion of the most recent decade of data for NEFSC (2010-2019) in the 2021 MDAT Fish update (v3.1_2021_09), a new time series was created to show increments in the total biomass from 1980-2019 for both Fall and Spring trawl surveys.

2022 March

North Atlantic Right Whale (NARW) individual species products were updated to an increased resolution, to include new survey data, to summarize the era from 2010-2018, to adjust predictions for Cape Cod Bay, and with new uncertainty layers that now account for interannual variability. All summary group products were updated with the new NARW individual model. The marine mammal sound sensitivity group summary products were modified following guidance from Southall et al., 2019

2021

Additional survey data were incorporated into the NEFSC Individual species layers to include data at each trawl site from 2010-2019 for Spring and Fall. The Summary products for each fish species group for Spring and Fall also now include data from 2010 through 2019.

2019

In 2019, MDAT published updates for the base layer products for fish and marine mammal species from the individual providers. Summary products were updated based on the new base-layer products, without changes to the methods. New MDAT partner TNC used independent trawl survey data from NEFSC, along with methods developed by OceanAdapt (a collaboration between the Pinsky Lab at Rutgers University and the National Marine Fisheries Service) to produce spatial data products for fish species from fall trawl surveys - updating the previous products - and added products from spring trawl surveys.

2018

In 2018, MDAT published updated products for all three taxa. Avian and marine mammal base-layer distribution products were updated by the individual providers, and summary products for all three taxa were updated by MDAT implementing improvements to the methods.

Summary Products

Total Abundance

Total abundance

For each group of species, total abundance maps are calculated in a Geographic Information System (GIS) by stacking the predicted annual abundance layers of each species that is a member of that group, and summing the values of the cell in each resulting “column”. The result is the total predicted abundance of all individuals (of the included species) in that cell. For cetaceans, this is total predicted abundance but for avian species groups this is total predicted relative abundance, and for fish species groups this is total biomass.

Species richness

For all species in a taxa together (i.e. all cetaceans) and for each group of species, species richness maps are calculated in a Geographic Information System (GIS) by stacking each individual species’ predicted presence or absence and counting the total number of species present in each cell. A species is considered present in a cell if the cell is included in the area containing 99% of the total predicted abundance or biomass for that species. Some mammal species were modeled as a guild to create the best available model at the guild level (e.g., beaked whales, pilot whales) when not enough data were available to create robust models at the individual species level. To better reflect true species counts in the richness map products, these guild density maps were counted as multiple species. For example, each beaked whale cell counts as four species (Blainville’s beaked whale, Sowerby’s beaked whale, and True’s beaked whale).

Diversity indices

To create maps showing areas of high and low biodiversity, two indices of diversity were considered: the Shannon diversity index (Shannon & Weaver, 1949) and the Gini-Simpson diversity index (Gini 1912, Simpson 1949, Greenberg 1956, Berger & Parker 1970). Each index has strengths and weaknesses, depending on the question that the user is hoping to answer. The Shannon index is most sensitive to changes in rare species, whereas the Gini-Simpson index is most sensitive to changes in abundant (e.g., dominant) species (Peet, 1974). Map products for both indices were created for each species group1. Different diversity indices have strengths and weaknesses, depending on the question that the user is hoping to answer.

Gini-Simpson index

The Simpson index is simply a probability that any two individuals will belong to the same species. As the Simpson index approaches a maximum of 1, it indicates a maximum probability that all individuals belong to the same species; in other words, diversity is very low. The index is calculated by taking the proportion of individuals in one species relative to the total number of species, and summing these across all species. This number is essentially a measure of dominance, and as dominance increases, total diversity decreases. Because values of the Simpson index are not intuitive to map (i.e., high values equal low diversity) MDAT uses the Gini-Simpson index, which is 1 minus the Simpson index. As a result, areas with high Gini-Simpson index scores (approaching 1) have higher diversity (low dominance by a single species). Areas with low Gini-Simpson index scores (approaching 0) have lower diversity (high dominance by a single species). A drawback of this index is that species with few numbers of individuals will not impact the Gini-Simpson score. The formula used to calculate the index, and the term definitions, are given below:

  • pi is the proportion of total individuals belonging to the ith species
  • R is richness, equal to the total number of species in the dataset

Shannon Diversity index

The Shannon index considers both abundance and evenness of species in an area in the calculation of diversity. Areas with high Shannon index scores have a large number of species (relative to the total number of species being considered in the area), as well as overall similar abundances (or biomass for fish) of these species. Areas that have a large number of species, but are dominated in abundance or biomass by only a few species, will not score as high on the Shannon index. The index approaches zero if the abundance is dominated by one species, regardless of how many other rare species occur in the area. The index is maximized when all the species evaluated have equal abundances, and it then equals the natural log of the species richness value (the number of species, or R). The formula used to calculate the index, and the term definitions, are given below:

  • pi is the proportion of total individuals belonging to the ith species
  • R is richness, equal to the total number of species in the dataset

1Because avian individual species model outputs are representations of relative abundance (not absolute), it would be inappropriate to calculate diversity metrics which rely on measures of absolute abundance.

Core abundance area richness

The purpose of a core abundance area map is to represent the smallest area containing 50% of the predicted abundance of each species. Summing all the cells (pixels) in the species distribution product gives the total predicted abundance. Core area is calculated by ranking cells by their abundance value from greatest to least, then summing cells with the highest abundance values until the total is equal to or greater than 50% of the total predicted abundance for the entire study area. Core abundance area richness is then calculated using the same methodology described above for “Species richness”, using the core abundance maps as input.

Core abundance area richness calculation

Acknowledgements

The Marine-life Data and Analysis Team developed and delivered the marine life base layer products and summary products as part of a collaboration with the Northeast Regional Ocean Council (NROC) and the Mid-Atlantic Regional Council on the Ocean (MARCO). Development of the summary products was guided by the Northeast Regional Planning Body (NE RPB), NE RPB expert work groups, the Mid-Atlantic Regional Planning Body, and the Mid-Atlantic Data Synthesis Work Group. Through NROC, this work was funded (in part) by cooperative agreement numbers NA12NOS4730010 and NA12NOS4730186 from the National Oceanic and Atmospheric Administration (NOAA). The views expressed herein are those of the author(s) and do not necessarily reflect the views of NOAA or any of its sub-agencies.

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