Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach
<p>The ability to constrain the mechanisms that transport organic carbon into the deep ocean is complicated by the multiple physical, chemical, and ecological processes that intersect to create, transform, and transport particles in the ocean. In this paper we develop and parameterize a data-a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-08-01
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| Series: | Biogeosciences |
| Online Access: | https://bg.copernicus.org/articles/19/3595/2022/bg-19-3595-2022.pdf |
| _version_ | 1818537119964987392 |
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| author | M. R. Stukel M. R. Stukel M. Décima M. R. Landry |
| author_facet | M. R. Stukel M. R. Stukel M. Décima M. R. Landry |
| author_sort | M. R. Stukel |
| collection | DOAJ |
| description | <p>The ability to constrain the mechanisms that transport organic
carbon into the deep ocean is complicated by the multiple physical,
chemical, and ecological processes that intersect to create, transform, and
transport particles in the ocean. In this paper we develop and
parameterize a data-assimilative model of the multiple pathways of the
biological carbon pump (NEMURO<span class="inline-formula"><sub>BCP</sub></span>). The mechanistic model is designed
to represent sinking particle flux, active transport by vertically migrating
zooplankton, and passive transport by subduction and vertical mixing, while
also explicitly representing multiple biological and chemical properties
measured directly in the field (including nutrients, phytoplankton and
zooplankton taxa, carbon dioxide and oxygen, nitrogen isotopes, and
<span class="inline-formula"><sup>234</sup></span>Thorium). Using 30 different data types (including standing stock
and rate measurements related to nutrients, phytoplankton, zooplankton, and
non-living organic matter) from Lagrangian experiments conducted on 11
cruises from four ocean regions, we conduct an objective statistical
parameterization of the model and generate 1 million different potential
parameter sets that are used for ensemble model simulations. The model
simulates in situ parameters that were assimilated (net primary production
and gravitational particle flux) and parameters that were withheld
(<span class="inline-formula"><sup>234</sup></span>Thorium and nitrogen isotopes) with reasonable accuracy. Model
results show that gravitational flux of sinking particles and vertical
mixing of organic matter from the euphotic zone are more important
biological pump pathways than active transport by vertically migrating
zooplankton. However, these processes are regionally variable, with sinking
particles most important in oligotrophic areas of the Gulf of Mexico and
California Current, sinking particles and vertical mixing roughly equivalent
in productive coastal upwelling regions and the subtropical front in the
Southern Ocean, and active transport an important contributor in the eastern
tropical Pacific. We further find that mortality at depth is an important
component of active transport when mesozooplankton biomass is high, but it
is negligible in regions with low mesozooplankton biomass. Our results also
highlight the high degree of uncertainty, particularly amongst
mesozooplankton functional groups, that is derived from uncertainty in model
parameters. Indeed, variability in BCP pathways between simulations for a
specific location using different parameter sets (all with approximately
equal misfit relative to observations) is comparable to variability in BCP
pathways between regions. We discuss the implications of these results for
other data-assimilation approaches and for studies that rely on non-ensemble
model outputs.</p> |
| first_indexed | 2024-12-11T18:46:39Z |
| format | Article |
| id | doaj.art-29aa842d5c1549c1b9a2b13b6c616d40 |
| institution | Directory Open Access Journal |
| issn | 1726-4170 1726-4189 |
| language | English |
| last_indexed | 2024-12-11T18:46:39Z |
| publishDate | 2022-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Biogeosciences |
| spelling | doaj.art-29aa842d5c1549c1b9a2b13b6c616d402022-12-22T00:54:27ZengCopernicus PublicationsBiogeosciences1726-41701726-41892022-08-01193595362410.5194/bg-19-3595-2022Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approachM. R. Stukel0M. R. Stukel1M. Décima2M. R. Landry3Department of Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, FL, USACenter for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, FL, USAScripps Institution of Oceanography, University of California San Diego, San Diego, CA, USAScripps Institution of Oceanography, University of California San Diego, San Diego, CA, USA<p>The ability to constrain the mechanisms that transport organic carbon into the deep ocean is complicated by the multiple physical, chemical, and ecological processes that intersect to create, transform, and transport particles in the ocean. In this paper we develop and parameterize a data-assimilative model of the multiple pathways of the biological carbon pump (NEMURO<span class="inline-formula"><sub>BCP</sub></span>). The mechanistic model is designed to represent sinking particle flux, active transport by vertically migrating zooplankton, and passive transport by subduction and vertical mixing, while also explicitly representing multiple biological and chemical properties measured directly in the field (including nutrients, phytoplankton and zooplankton taxa, carbon dioxide and oxygen, nitrogen isotopes, and <span class="inline-formula"><sup>234</sup></span>Thorium). Using 30 different data types (including standing stock and rate measurements related to nutrients, phytoplankton, zooplankton, and non-living organic matter) from Lagrangian experiments conducted on 11 cruises from four ocean regions, we conduct an objective statistical parameterization of the model and generate 1 million different potential parameter sets that are used for ensemble model simulations. The model simulates in situ parameters that were assimilated (net primary production and gravitational particle flux) and parameters that were withheld (<span class="inline-formula"><sup>234</sup></span>Thorium and nitrogen isotopes) with reasonable accuracy. Model results show that gravitational flux of sinking particles and vertical mixing of organic matter from the euphotic zone are more important biological pump pathways than active transport by vertically migrating zooplankton. However, these processes are regionally variable, with sinking particles most important in oligotrophic areas of the Gulf of Mexico and California Current, sinking particles and vertical mixing roughly equivalent in productive coastal upwelling regions and the subtropical front in the Southern Ocean, and active transport an important contributor in the eastern tropical Pacific. We further find that mortality at depth is an important component of active transport when mesozooplankton biomass is high, but it is negligible in regions with low mesozooplankton biomass. Our results also highlight the high degree of uncertainty, particularly amongst mesozooplankton functional groups, that is derived from uncertainty in model parameters. Indeed, variability in BCP pathways between simulations for a specific location using different parameter sets (all with approximately equal misfit relative to observations) is comparable to variability in BCP pathways between regions. We discuss the implications of these results for other data-assimilation approaches and for studies that rely on non-ensemble model outputs.</p>https://bg.copernicus.org/articles/19/3595/2022/bg-19-3595-2022.pdf |
| spellingShingle | M. R. Stukel M. R. Stukel M. Décima M. R. Landry Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach Biogeosciences |
| title | Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach |
| title_full | Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach |
| title_fullStr | Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach |
| title_full_unstemmed | Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach |
| title_short | Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach |
| title_sort | quantifying biological carbon pump pathways with a data constrained mechanistic model ensemble approach |
| url | https://bg.copernicus.org/articles/19/3595/2022/bg-19-3595-2022.pdf |
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