Abstract

A generalized additive modelling (GAM) approach is used to describe the abundance of 40 species groups (i.e. functional groups) across the Gulf of Mexico (GoM) using a large fisheries independent data set (SEAMAP) and climate scale oceanographic conditions. Predictor variables included in the model are chlorophyll a, sediment type, dissolved oxygen, temperature, and depth. The GAM approach was shown to be robust despite zero-inflated data. article: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0064458

Comments

Data and metadata is made available by the Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) through a CC0 license in compliance with the Gulf of Mexico Research Initiative (GoMRI). The original dataset landing pages may be accessed at GRIIDC’s dataset monitoring webpage.

Data users are encouraged to contact the originating investigator prior to data use and provide appropriate credit.

Purpose

These data provide continuous spatial coverage for fish and invertebrate abundance distributions needed to initialize the Gulf of Mexico Atlantis ecosystem model currently in development for the C-IMAGE project.

Keywords

species distribution, fish distribution, atlantis, ecosystem model, oil spill, Deepwater Horizon oil spill, fisheries

UDI

R1.x135.122:0002

Date

3-18-2016 12:00 AM

Point of Contact

Drexler, Michael
University of South Florida
College of Marine Science
140 7th Ave South
St. Petersburg , FL 33701
USA
mdrexler@mail.usf.edu

Funding Source

RFP-I

Start of Data Collection

1-1-2010

End of Data Collection

1-1-2010

DOI

https://doi.org/10.7266/N75H7D7W

Rights Information

Creative Commons License
This work is licensed under a Creative Commons Public Domain Dedication 1.0 License.

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