Dataset: Kelp forest mooring DIC, TA, pCO2, and aragonite saturation state estimations inside the kelp canopy (36° 37.297’ N, 121° 54.102’ W.) at Hopkins Marine Station, recorded between June and October 2018.

ValidatedFinal no updates expectedDOI: 10.26008/1912/bco-dmo.823008.1Version 1 (2020-09-02)Dataset Type:Other Field Results

Principal Investigator, Project Coordinator: Kerry J. Nickols (California State University Northridge)

Co-Principal Investigator: Robert B. Dunbar (Stanford University)

Scientist, Contact: Heidi Hirsh (Stanford University)

Scientist: Stephen G. Monismith (Stanford University)

Scientist: David Mucciarone (Stanford University)

Scientist: Yuichiro Takeshita (Monterey Bay Aquarium Research Institute)

Scientist: Sarah Traiger (United States Geological Survey)

BCO-DMO Data Manager: Karen Soenen (Woods Hole Oceanographic Institution)

Project: Collaborative Research: RUI: Building a mechanistic understanding of water column chemistry alteration by kelp forests: emerging contributions of foundation species (Kelp forest biogeochemistry)

Abstract

Kelp forest mooring DIC, TA, pCO2, and aragonite saturation state estimations inside the kelp canopy (36° 37.297’ N, 121° 54.102’ W.) at Hopkins Marine Station, recorded between June and October 2018.

Cite Dataset

These data are published in Hirsh et al., see related publications section.

Related Datasets

IsDerivedFrom
Dataset: Inside and Outside Kelp Forest Mooring
Relationship Description: The derived carbonate system data comes from the kelp mooring data (pH, temperature, salinity)
Hirsh, H., Nickols, K. J., Takeshita, Y., Traiger, S., Monismith, S. G., Mucciarone, D., Dunbar, R. B. (2020) Data from moored instruments (pH, dissolved oxygen, temperature, salinity, PAR, pressure) at 9 depths outside and inside the kelp canopy at Hopkins Marine Station, recorded between June and October 2018. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2020-09-02 doi:10.26008/1912/bco-dmo.822549.1

Related Publications

Results
Hirsh, H. K., Nickols, K. J., Takeshita, Y., Traiger, S. B., Mucciarone, D. A., Monismith, S., & Dunbar, R. B. (2020). Drivers of Biogeochemical Variability in a Central California Kelp Forest: Implications for Local Amelioration of Ocean Acidification. Journal of Geophysical Research: Oceans, 125(11). Portico. https://doi.org/10.1029/2020jc016320
Methods
Alin, S. R., Feely, R. A., Dickson, A. G., Hernández-Ayón, J. M., Juranek, L. W., Ohman, M. D., & Goericke, R. (2012). Robust empirical relationships for estimating the carbonate system in the southern California Current System and application to CalCOFI hydrographic cruise data (2005-2011). Journal of Geophysical Research: Oceans, 117(C5), n/a–n/a. doi:10.1029/2011jc007511
Methods
Carter, B. R., Feely, R. A., Williams, N. L., Dickson, A. G., Fong, M. B., & Takeshita, Y. (2017). Updated methods for global locally interpolated estimation of alkalinity, pH, and nitrate. Limnology and Oceanography: Methods, 16(2), 119–131. doi:10.1002/lom3.10232
Methods
Lavigne H, Gattuso JP (2014) Seacarb: seawater carbonate chemistry with R, R package version 3.0. Available from http://CRAN.R-project.org/package=seacarb
Methods
Lueker, T. J., Dickson, A. G., & Keeling, C. D. (2000). Ocean pCO2 calculated from dissolved inorganic carbon, alkalinity, and equations for K1 and K2: validation based on laboratory measurements of CO2 in gas and seawater at equilibrium. Marine Chemistry, 70(1-3), 105–119. doi:10.1016/s0304-4203(00)00022-0

Hirsh, H., Nickols, K. J., Takeshita, Y., Traiger, S., Monismith, S. G., Mucciarone, D., Dunbar, R. B. (2020) Kelp forest mooring DIC, TA, pCO2, and aragonite saturation state estimations inside the kelp canopy (36° 37.297’ N, 121° 54.102’ W.) at Hopkins Marine Station, recorded between June and October 2018.. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2020-09-02 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.823008.1 [access date]

Terms of Use

This dataset is licensed under Creative Commons Attribution 4.0.


If you wish to use this dataset, it is highly recommended that you contact the original principal investigators (PI). Should the relevant PI be unavailable, please contact BCO-DMO (info@bco-dmo.org) for additional guidance. For general guidance please see the BCO-DMO Terms of Use document.

NSF Logo©2020 Biological and Chemical Oceanography Data Management Office.
Funded by the U.S. National Science Foundation