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. This dataset supports the publication: Drexler, M. and Ainsworth, C.H. 2013. Generalized Additive Models Used to Predict Species Abundance in the Gulf of Mexico: An Ecosystem Modeling Tool. PLOS ONE 8(5): e64458. doi: 10.1371/journal.pone.0064458 (http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0064458)

Suggested Citation:

Drexler, Michael. 2013. Spatial distributions of fish and invertebrates in the Gulf of Mexico for 2010-01-01 estimated using a statistical model. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N75H7D7W

Publications:

Drexler, M., & Ainsworth, C. H. (2013). Generalized Additive Models Used to Predict Species Abundance in the Gulf of Mexico: An Ecosystem Modeling Tool. PLoS ONE, 8(5), e64458. doi:10.1371/journal.pone.0064458

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.

Data Parameters and Units:

Abundance of fish and invertebrates (number of individuals per square kilometer)

Individual Files: