http://lod.bco-dmo.org/id/dataset/854787
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2021-06-29
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Model output of phytoplankton community composition variability as a function of intensity and duration of environmental disturbance at the Hawaii Ocean Time-series (HOT) location and nearby regions between 2003 and 2014
2021-06-29
publication
2021-06-29
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2021-07-01
publication
https://doi.org/10.26008/1912/bco-dmo.854787.1
Naomi M. Levine
University of Southern California
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Levine, N. M., Liu, X. (2021) Model output of phytoplankton community composition variability as a function of intensity and duration of environmental disturbance at the Hawaii Ocean Time-series (HOT) location and nearby regions between 2003 and 2014. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2021-06-29 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.854787.1 [access date]
Methods and Sampling: <p>Location:&nbsp; Hawaii Ocean Time-series (HOT) and nearby regions (5deg x 5deg centered at HOT)<br />
<br />
These data were generated from numerical model simulations.<br />
<br />
See Supplemental File "Liu_and_Levine_modelDescription.pdf" for a methodology summary including a physical model description, ecological model description, model configuration and simulations, and&nbsp;Appendix A. "Key ecosystem parameters used in the model. Parameters optimized for the HOT site are denoted with asterisks."<br />
<br />
Also, please refer to the associated publication&nbsp;Liu and Levine (2021)&nbsp;for additional details.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1538525 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1538525
Funding provided by NSF Ocean Sciences Research Initiation Grants (NSF OCE-RIG) Award Number: OCE-RIG-1323319 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1323319
completed
Naomi M. Levine
University of Southern California
213-821-0745
3616 Trousdale Parkway AHF 107
Los Angeles
CA
90089-0371
USA
n.levine@usc.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
How does intensity and frequency of environmental variability affect phytoplankton growth?
https://osprey.bco-dmo.org/project/668547
How does intensity and frequency of environmental variability affect phytoplankton growth?
<p><em>NSF Award Abstract:</em><br />
Microscopic plants called phytoplankton are key members of global oceanic ecosystems, since their photosynthesis supports the majority of the marine food chain and produces about as much oxygen as land plants. Because of this, oceanographers have often carried out experiments examining how factors such as temperature and carbon dioxide levels may affect phytoplankton growth. Most previous experiments have used constant levels of temperature and carbon dioxide, but it is clear from looking at measurements from real ocean ecosystems that these two factors often vary greatly over timescales of days to weeks. Using field and laboratory experiments along with computer modeling, this project will test how the growth of several major groups of phytoplankton differs under constant conditions of temperature and carbon dioxide, compared to conditions in which these factors fluctuate in intensity and frequency. This research will give marine scientists a better picture of how phytoplankton may respond to a varying natural environment today and in the future, and therefore help us to understand how ocean food webs function to support critical living resources such as fisheries. The project will train graduate and undergraduate students and a postdoctoral researcher, and the lead scientists will be involved in an ocean science education program for largely minority high school students from a downtown Los Angeles school district.</p>
<p>The goal of this project is to use laboratory culture and natural community experiments to understand how realistically fluctuating temperature and pCO2 conditions may affect globally important phytoplankton groups in ways that differ from the artificial constant exposures used in previous work. Culture experiments will test how the intensity and frequency of short-term thermal and carbonate fluctuations affects the growth responses of diazotrophic and picoplanktonic cyanobacteria, coccolithophores, and diatoms under both current and projected future environmental conditions. These lab results will be supported and extended by parallel experiments using mixed natural assemblages from the California upwelling regime, allowing us to test these same questions using phytoplankton communities that experience large seasonal shifts between highly dynamic thermal and carbonate system conditions during the spring upwelling season, and relatively much more static conditions during fall stratification events. These results will be synthesized using a new generation of numerical models that employ novel approaches to incorporating realistic environmental variations to allow more accurate predictions of phytoplankton responses to a dynamic environment in today's marine ecosystems, and in the future changing ocean.</p>
Enviro variability and phytoplankton growth
largerWorkCitation
project
OCE-RIG: The impact of submesoscale processes on oligotrophic carbon cycling and the sensitivity of this interaction to climatically driven changes
https://osprey.bco-dmo.org/project/718397
OCE-RIG: The impact of submesoscale processes on oligotrophic carbon cycling and the sensitivity of this interaction to climatically driven changes
<p><em>NSF Award Abstract:</em><br />
Overview: Anthropogenically induced warming has begun to change the global oceans and has the potential to alter the ocean carbon sink. Future changes in mixed layer depth and the delivery of nutrients into the surface ocean are hypothesized to be the primary processes that will impact primary production and carbon cycling in the ocean. Both of these processes are significantly impacted by submesoscale physical dynamics (1-10 km). However, current global climate models used to understand climate sensitivity do not resolve these important features, and so are missing a fundamental mechanism impacting ocean carbon cycling. In this project, the PI will develop a novel biogeochemical and ecosystem model that captures the impact of submesoscale processes on carbon cycling in a framework that is computationally tractable for large-scale simulations.</p>
<p>The Spatially Heterogeneous Dynamic Plankton (SHiP) model will represent a distribution of resource environments at the subgridscale and will include five phytoplankton functional groups, as well as light, nitrogen, and phosphorus limitation on phytoplankton growth. This research will focus on two oligotrophic sites, the Bermuda Atlantic Time-series Station (BATS) and the Hawaii Ocean Time-series (HOT). The SHiP model will be used to explore the impact of the observed submesoscale dynamics captured by the APEX/ISUS profiling nitrate floats on primary production, species dynamics, and carbon export flux. A suite of model simulations will also be conducted to investigate the sensitivity of carbon cycling at BATS and HOT to changes in the frequency and intensity of submesoscale front formation, such as might occur under future climate scenarios. Finally, the measurement-driven SHiP simulations will be compared against an idealized Regional Ocean Modeling System simulation that explicitly resolves submesoscale dynamics.</p>
<p>Intellectual Merit: Submesoscale processes have been shown to have a significant impact on ocean physics, however, the role that these processes play in carbon cycling remains unknown. This study will provide an observation-based analysis of the impact of submesoscale features on community composition and function in oligotrophic gyres and the sensitivity of this interaction to climatically driven changes. In addition, this work will validate a novel approach for mechanistically incorporating the impact of submesoscale dynamics into coarse-resolution models. This research will provide a computationally tractable framework for exploring the impact of changes in climate on global carbon cycling while including the impact of submesoscale processes.</p>
<p>Broader Impacts: The investigator and students associated with this project will collaborate with the Neighborhood Academic Initiative (NAI) at USC to develop an ocean sciences module including a field trip on an oceanographic research vessel. The NAI strives to improve high school graduation and college matriculation rates in the school district surrounding USC, which serves predominantly Latino/Hispanic and African-American communities. The module will also expose the students to oceanography, and help local high school teachers develop an ocean sciences lesson plan to incorporate into their curriculum.</p>
SHiP
largerWorkCitation
project
eng; USA
oceans
-160.5
-155.5
20.25
25.25
2003-01-01
2014-01-01
laboratory experiment
0
BCO-DMO catalogue of parameters from Model output of phytoplankton community composition variability as a function of intensity and duration of environmental disturbance at the Hawaii Ocean Time-series (HOT) location and nearby regions between 2003 and 2014
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2479005156
https://darchive.mblwhoilibrary.org/bitstream/1912/27302/1/Liu_Levine_PO_model_output.zip
download
https://doi.org/10.26008/1912/bco-dmo.854787.1
download
onLine
dataset
<p>Location:&nbsp; Hawaii Ocean Time-series (HOT) and nearby regions (5deg x 5deg centered at HOT)<br />
<br />
These data were generated from numerical model simulations.<br />
<br />
See Supplemental File "Liu_and_Levine_modelDescription.pdf" for a methodology summary including a physical model description, ecological model description, model configuration and simulations, and&nbsp;Appendix A. "Key ecosystem parameters used in the model. Parameters optimized for the HOT site are denoted with asterisks."<br />
<br />
Also, please refer to the associated publication&nbsp;Liu and Levine (2021)&nbsp;for additional details.</p>
Specified by the Principal Investigator(s)
<p>BCO-DMO data manager processing notes:<br />
* Bundled .mat files and attached to this dataset landing page as Data Files<br />
* Added model documentation as supplemental files.</p>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact