Use of multilinear regression for prediction of PH and aragonite saturation in the northwest Gulf of Mexico

dc.contributor.author	Jundt, EvaLynn
dc.contributor.author	Hu, Xinping
dc.contributor.author	Barbero, Leticia
dc.creator.orcid	https://orcid.org/0000-0002-0613-6545	en_US
dc.date.accessioned	2022-05-12T18:06:00Z
dc.date.available	2022-05-12T18:06:00Z
dc.date.issued	2022-04
dc.description.abstract	The Gulf of Mexico (GOM) is home to large shellfish populations, and the northernmost tropical coral reefs in the contiguous US. Despite this, the progression of Ocean Acidification (OA) in the GOM is still poorly understood as historical carbonate chemistry measurements are scarce. Based on carbonate chemistry and hydrographic data collected from 2007, 2017, and 2021, we derived multilinear regression models built upon relationships between commonly measured hydrographic properties (salinity, temperature, pressure, depth, or oxygen) and aragonite saturation state (Ωaragonite) and pH. The resulting models robustly predict Ωaragonite with R2>0.92, RMSE<0.07 and pH with R2>0.66, RMSE<0.30 for four different scenarios including different subsets of the data based on area and depth.	en_US
dc.identifier.uri	https://hdl.handle.net/1969.6/90592
dc.language.iso	en_US	en_US
dc.rights	Attribution-NonCommercial 4.0 International	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc/4.0/	*
dc.subject	Carbon cycle	en_US
dc.subject	mlr	en_US
dc.subject	data science	en_US
dc.title	Use of multilinear regression for prediction of PH and aragonite saturation in the northwest Gulf of Mexico	en_US
dc.type	Presentation	en_US

Files

Now showing 1 - 1 of 1

Now showing 1 - 1 of 1