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, at the request of the Northeast Regional Planning Body (NE RPB) to support the Northeast Ocean Plan. These research groups collaborated to produce “base layer” predictive model products with associated uncertainty products for 29 marine mammal species or species guilds and 40 avian species, and three geospatial products for 82 fish species. Marine mammal 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.
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 as identified by the NE RPB and others, MDAT has created several types of “synthetic”, or 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. Species were grouped according to these three categories, resulting in approximately 27 avian groups, 12 fish groups, and nine mammal groups. 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.
In addition to being hosted on the Northeast and Mid-Atlantic Data Ocean Portals, the MarineCadastre.gov team has selected a subset of the summary products to include in the National Viewer. Learn how to combine these services with other MarineCadastre.gov data in their Tutorial: Using the MarineCadastre.gov Services in ArcMap (Version 10).
Any use of the data should be accompanied by the following citation:
Curtice, C., Cleary J., Shumchenia E., Halpin P.N. 2016. 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-v1_1.pdf
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 mammals, 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.
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. 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. Each beaked whale cell counts as five species (Blainville’s beaked whale, Cuvier’s beaked whale, Sowerby’s beaked whale, and True’s beaked whale)..
Gini-Simpson Diversity index
To create maps showing areas of high and low biodiversity, the Gini-Simpson diversity index (Gini 1912, Simpson 1949, Greenberg 1956, Berger & Parker 1970) was created for each species group1. Different diversity indices have strengths and weaknesses, depending on the question that the user is hoping to answer. The Gini-Simpson index is most sensitive to changes in abundant (e.g., dominant) species (Peet, 1974). 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:
- ni is the number of individuals belonging to the ith species
- N is the total number of individuals in the dataset
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.
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.