 |
| Titel |
Modelling planktic foraminifer growth and distribution using an ecophysiological multi-species approach |
| VerfasserIn |
F. Lombard, L. Labeyrie, E. Michel, L. Bopp, E. Cortijo, S. Retailleau, H. Howa, F. Jorissen |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1726-4170
|
| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 8, no. 4 ; Nr. 8, no. 4 (2011-04-08), S.853-873 |
| Datensatznummer |
250005688
|
| Publikation (Nr.) |
 copernicus.org/bg-8-853-2011.pdf |
|
|
|
|
|
| Zusammenfassung |
| We present an eco-physiological model reproducing the growth of eight
foraminifer species (Neogloboquadrina pachyderma, Neogloboquadrina incompta,
Neogloboquadrina dutertrei, Globigerina bulloides, Globigerinoides ruber,
Globigerinoides sacculifer, Globigerinella siphonifera and Orbulina universa).
By using the main physiological rates of foraminifers (nutrition, respiration, symbiotic photosynthesis),
this model estimates their growth as a function of temperature, light
availability, and food concentration. Model parameters are directly derived
or calibrated from experimental observations and only the influence of food
concentration (estimated via Chlorophyll-a concentration) was calibrated against
field observations. Growth rates estimated from the model show positive
correlation with observed abundance from plankton net data suggesting close
coupling between individual growth and population abundance. This
observation was used to directly estimate potential abundance from the
model-derived growth. Using satellite data, the model simulate the dominant
foraminifer species with a 70.5% efficiency when compared to a data set of
576 field observations worldwide. Using outputs of a biogeochemical model of
the global ocean (PISCES) instead of satellite images as forcing variables
gives also good results, but with lower efficiency (58.9%). Compared to
core tops observations, the model also correctly reproduces the relative
worldwide abundance and the diversity of the eight species when using either
satellite data either PISCES results. This model allows prediction of the
season and water depth at which each species has its maximum abundance
potential. This offers promising perspectives for both an improved
quantification of paleoceanographic reconstructions and for a better
understanding of the foraminiferal role in the marine carbon cycle. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|