Effect of sampling bias on global estimates of ocean carbon export
Shipboard sampling of ocean biogeochemical properties is necessarily limited by logistical and practical constraints. As a result, the majority of observations are obtained for the spring/summer period and in regions relatively accessible from a major port. This limitation may bias the conceptual un...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2024-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ad1e7f |
| _version_ | 1797349066017865728 |
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| author | Stephanie Henson Kelsey Bisson Matthew L Hammond Adrian Martin Colleen Mouw Andrew Yool |
| author_facet | Stephanie Henson Kelsey Bisson Matthew L Hammond Adrian Martin Colleen Mouw Andrew Yool |
| author_sort | Stephanie Henson |
| collection | DOAJ |
| description | Shipboard sampling of ocean biogeochemical properties is necessarily limited by logistical and practical constraints. As a result, the majority of observations are obtained for the spring/summer period and in regions relatively accessible from a major port. This limitation may bias the conceptual understanding we have of the spatial and seasonal variability in important components of the Earth system. Here we examine the influence of sampling bias on global estimates of carbon export flux by sub-sampling a biogeochemical model to simulate real, realistic and random sampling. We find that both the sparseness and the ‘clumpy’ character of shipboard flux observations generate errors in estimates of globally extrapolated export flux of up to ∼ ± 20%. The use of autonomous technologies, such as the Biogeochemical-Argo network, will reduce the uncertainty in global flux estimates to ∼ ± 3% by both increasing the sample size and reducing clumpiness in the spatial distribution of observations. Nevertheless, determining the climate change-driven trend in global export flux may be hampered due to the uncertainty introduced by interannual variability in sampling patterns. |
| first_indexed | 2024-03-08T12:24:51Z |
| format | Article |
| id | doaj.art-fe0084295e0f472fbf752d656e4a4005 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-08T12:24:51Z |
| publishDate | 2024-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-fe0084295e0f472fbf752d656e4a40052024-01-22T11:50:35ZengIOP PublishingEnvironmental Research Letters1748-93262024-01-0119202400910.1088/1748-9326/ad1e7fEffect of sampling bias on global estimates of ocean carbon exportStephanie Henson0https://orcid.org/0000-0002-3875-6802Kelsey Bisson1Matthew L Hammond2Adrian Martin3Colleen Mouw4Andrew Yool5National Oceanography Centre , European Way, Southampton, United KingdomDepartment of Botany and Plant Pathology, Oregon State University , Corvallis, OR, United States of America; Ocean Biology and Biogeochemistry Program, NASA Headquarters, Science Mission Directorate, Earth Science Division , Washington, DC, United States of AmericaDepartamento de Biología Marina, Facultad de Ciencas del Mar, Universidad Católica del Norte , Coquimbo, Chile; Center for Ecology and Sustainable Management of Oceanic Islands (ESMOI), Facultad de Ciencias del Mar, Universidad Católica del Norte , Coquimbo, ChileNational Oceanography Centre , European Way, Southampton, United KingdomUniversity of Rhode Island, Graduate School of Oceanography , Narragansett, RI, United States of AmericaNational Oceanography Centre , European Way, Southampton, United KingdomShipboard sampling of ocean biogeochemical properties is necessarily limited by logistical and practical constraints. As a result, the majority of observations are obtained for the spring/summer period and in regions relatively accessible from a major port. This limitation may bias the conceptual understanding we have of the spatial and seasonal variability in important components of the Earth system. Here we examine the influence of sampling bias on global estimates of carbon export flux by sub-sampling a biogeochemical model to simulate real, realistic and random sampling. We find that both the sparseness and the ‘clumpy’ character of shipboard flux observations generate errors in estimates of globally extrapolated export flux of up to ∼ ± 20%. The use of autonomous technologies, such as the Biogeochemical-Argo network, will reduce the uncertainty in global flux estimates to ∼ ± 3% by both increasing the sample size and reducing clumpiness in the spatial distribution of observations. Nevertheless, determining the climate change-driven trend in global export flux may be hampered due to the uncertainty introduced by interannual variability in sampling patterns.https://doi.org/10.1088/1748-9326/ad1e7fcarbon exportBiogeochemical-Argothorium-derived fluxdata sparsitysampling strategy |
| spellingShingle | Stephanie Henson Kelsey Bisson Matthew L Hammond Adrian Martin Colleen Mouw Andrew Yool Effect of sampling bias on global estimates of ocean carbon export Environmental Research Letters carbon export Biogeochemical-Argo thorium-derived flux data sparsity sampling strategy |
| title | Effect of sampling bias on global estimates of ocean carbon export |
| title_full | Effect of sampling bias on global estimates of ocean carbon export |
| title_fullStr | Effect of sampling bias on global estimates of ocean carbon export |
| title_full_unstemmed | Effect of sampling bias on global estimates of ocean carbon export |
| title_short | Effect of sampling bias on global estimates of ocean carbon export |
| title_sort | effect of sampling bias on global estimates of ocean carbon export |
| topic | carbon export Biogeochemical-Argo thorium-derived flux data sparsity sampling strategy |
| url | https://doi.org/10.1088/1748-9326/ad1e7f |
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