Using ecological partitions to assess zooplankton biogeography and seasonality
Zooplankton play a crucial role in marine ecosystems as the link between the primary producers and higher trophic levels, and as such they are key components of global biogeochemical and ecosystem models. While phytoplankton spatial-temporal dynamics can be tracked using satellite remote sensing, no...
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ftdoajarticles:oai:doaj.org/article:42a5f1314c594a48845ab4339fa81855 2023-06-11T04:15:02+02:00 Using ecological partitions to assess zooplankton biogeography and seasonality Niall McGinty Andrew J. Irwin Zoe V. Finkel Stephanie Dutkiewicz 2023-05-01T00:00:00Z https://doi.org/10.3389/fmars.2023.989770 https://doaj.org/article/42a5f1314c594a48845ab4339fa81855 EN eng Frontiers Media S.A. https://www.frontiersin.org/articles/10.3389/fmars.2023.989770/full https://doaj.org/toc/2296-7745 2296-7745 doi:10.3389/fmars.2023.989770 https://doaj.org/article/42a5f1314c594a48845ab4339fa81855 Frontiers in Marine Science, Vol 10 (2023) zooplankton biogeochemical model seasonality correlation biomass Science Q General. Including nature conservation geographical distribution QH1-199.5 article 2023 ftdoajarticles https://doi.org/10.3389/fmars.2023.989770 2023-05-07T00:35:40Z Zooplankton play a crucial role in marine ecosystems as the link between the primary producers and higher trophic levels, and as such they are key components of global biogeochemical and ecosystem models. While phytoplankton spatial-temporal dynamics can be tracked using satellite remote sensing, no analogous data product is available to validate zooplankton model output. We develop a procedure for linking irregular and sparse observations of mesozooplankton biomass with model output to assess regional seasonality of mesozooplankton. We use output from a global biogeochemical/ecosystem model to partition the ocean according to seasonal patterns of modeled mesozooplankton biomass. We compare the magnitude and temporal dynamics of the model biomass with in situ observations averaged within each partition. Our analysis shows strong correlations and little bias between model and data in temperate, strongly seasonally variable regions. Substantial discrepancies exist between model and observations within the tropical partitions. Correlations between model and data in the tropical partitions were not significant and in some cases negative. Seasonal changes in tropical mesozooplankton biomass were weak, driven primarily by local perturbations in the velocity and extent of currents. Microzooplankton composed a larger fraction of total zooplankton biomass in these regionsWe also examined the ability of the model to represent several dominant taxonomic groups. We identified several Calanus species in the North Atlantic partitions and Euphausiacea in the Southern Ocean partitions that were well represented by the model. This partition-scale comparison captures biogeochemically important matches and mismatches between data and models, suggesting that elaborating models by adding trait differences in larger zooplankton and mixotrophy may improve model-data comparisons. We propose that where model and data compare well, sparse observations can be averaged within partitions defined from model output to quantify zooplankton ... Article in Journal/Newspaper North Atlantic Southern Ocean Directory of Open Access Journals: DOAJ Articles Southern Ocean Frontiers in Marine Science 10 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
zooplankton biogeochemical model seasonality correlation biomass Science Q General. Including nature conservation geographical distribution QH1-199.5 |
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zooplankton biogeochemical model seasonality correlation biomass Science Q General. Including nature conservation geographical distribution QH1-199.5 Niall McGinty Andrew J. Irwin Zoe V. Finkel Stephanie Dutkiewicz Using ecological partitions to assess zooplankton biogeography and seasonality |
topic_facet |
zooplankton biogeochemical model seasonality correlation biomass Science Q General. Including nature conservation geographical distribution QH1-199.5 |
description |
Zooplankton play a crucial role in marine ecosystems as the link between the primary producers and higher trophic levels, and as such they are key components of global biogeochemical and ecosystem models. While phytoplankton spatial-temporal dynamics can be tracked using satellite remote sensing, no analogous data product is available to validate zooplankton model output. We develop a procedure for linking irregular and sparse observations of mesozooplankton biomass with model output to assess regional seasonality of mesozooplankton. We use output from a global biogeochemical/ecosystem model to partition the ocean according to seasonal patterns of modeled mesozooplankton biomass. We compare the magnitude and temporal dynamics of the model biomass with in situ observations averaged within each partition. Our analysis shows strong correlations and little bias between model and data in temperate, strongly seasonally variable regions. Substantial discrepancies exist between model and observations within the tropical partitions. Correlations between model and data in the tropical partitions were not significant and in some cases negative. Seasonal changes in tropical mesozooplankton biomass were weak, driven primarily by local perturbations in the velocity and extent of currents. Microzooplankton composed a larger fraction of total zooplankton biomass in these regionsWe also examined the ability of the model to represent several dominant taxonomic groups. We identified several Calanus species in the North Atlantic partitions and Euphausiacea in the Southern Ocean partitions that were well represented by the model. This partition-scale comparison captures biogeochemically important matches and mismatches between data and models, suggesting that elaborating models by adding trait differences in larger zooplankton and mixotrophy may improve model-data comparisons. We propose that where model and data compare well, sparse observations can be averaged within partitions defined from model output to quantify zooplankton ... |
format |
Article in Journal/Newspaper |
author |
Niall McGinty Andrew J. Irwin Zoe V. Finkel Stephanie Dutkiewicz |
author_facet |
Niall McGinty Andrew J. Irwin Zoe V. Finkel Stephanie Dutkiewicz |
author_sort |
Niall McGinty |
title |
Using ecological partitions to assess zooplankton biogeography and seasonality |
title_short |
Using ecological partitions to assess zooplankton biogeography and seasonality |
title_full |
Using ecological partitions to assess zooplankton biogeography and seasonality |
title_fullStr |
Using ecological partitions to assess zooplankton biogeography and seasonality |
title_full_unstemmed |
Using ecological partitions to assess zooplankton biogeography and seasonality |
title_sort |
using ecological partitions to assess zooplankton biogeography and seasonality |
publisher |
Frontiers Media S.A. |
publishDate |
2023 |
url |
https://doi.org/10.3389/fmars.2023.989770 https://doaj.org/article/42a5f1314c594a48845ab4339fa81855 |
geographic |
Southern Ocean |
geographic_facet |
Southern Ocean |
genre |
North Atlantic Southern Ocean |
genre_facet |
North Atlantic Southern Ocean |
op_source |
Frontiers in Marine Science, Vol 10 (2023) |
op_relation |
https://www.frontiersin.org/articles/10.3389/fmars.2023.989770/full https://doaj.org/toc/2296-7745 2296-7745 doi:10.3389/fmars.2023.989770 https://doaj.org/article/42a5f1314c594a48845ab4339fa81855 |
op_doi |
https://doi.org/10.3389/fmars.2023.989770 |
container_title |
Frontiers in Marine Science |
container_volume |
10 |
_version_ |
1768371511010263040 |