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Project properties |
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| Title | Assessing the significant of physical, geochemical and biological drivers of a Bivalves times series using modelling |
| Group | Marine Animal Ecology |
| Project type | thesis |
| Credits | 24-39 |
| Supervisor(s) | Dr. Katja Philippart
Léon Serre-Fredj Dr. Myron Peck |
| Examiner(s) | Tinka Murk, Reindert Nijland, Ronald Osinga, Rosa van der Ven, Diede Maas |
| Contact info | Diede Maas (diede.maas@wur.nl) for information leaflet
Myron Peck (myron.peck@nioz.nl) |
| Begin date | 2023/11/15 |
| End date | 2024/11/15 |
| Description | The Royal Netherlands Institute for Sea Research (NIOZ) located in Texel has at its disposal a
marine environmental time series that started as early as 1861 and is maintained until nowadays in the Wadden Sea (Philippart et al., 2010). With numerous environmental parameter, the series also measure the presence of larvae of bivalve species. Coupled with the SIBES (https://www.nioz.nl/en/research/projects/4126-20) database measuring size biomass and abundance of bivalves (Bijleveld et al., 2018) These species are at the utmost importance for the aquatic ecosystem (Vaughn and Hoellein, 2018) particularly on trophic web being used as food by numerous predator and grazing phytoplankton community. Numerous variables can affect this population's physical parameter (salinity, temperature), and biological (phytoplankton biomass, phytoplankton primary production, oxygen, fish biomass). Moreover, changes has already been pinpointed in the time series due to global warming strengthening the need to highlight the most important drivers of the zooplankton population to address future challenge. Also, web trophic modelling could allow us to perceive the consequence of potential change in this population on both lower and higher trophic levels. This work will first focus on identifying the main drivers of the bivalve larvae's presence or absence. Then the time dynamic of the bivalve biomass will be studied with a generalized additive model [GAM, (Hastie and Tibshirani, 2017)] using the phytoplankton and environmental parameters as descriptive variables. Finally, all previous information will be coupled to better asses the bivalve's recruitment. |
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