Shelf Sea Biogeochemistry Studentship - Identifying the nature of primary productivity variability in shelf sea systems

Identifying the nature of primary productivity variability in shelf sea systems

Marine primary productivity (PP) by phytoplankton drives the conversion of inorganic nutrients into organic matter to support key marine ecosystem services such as biogeochemical nutrient cycles and fisheries. In coastal waters, where many human populations are centered, PP is a key indicator of water quality and ecosystem health; however, the UK’s shelf seas are highly dynamic and it is unclear how current (and consequently future) environmental conditions influence PP. Characterising the spatial and temporal variability of PP in coastal seas and providing integrated values requires use of satellite remote sensing; however, the algorithms that are used with satellite ocean colour data and other variables to map PP in time and space are still constrained by our ability to obtain in situ "sea truth" measurements of PP. Current PP estimates are still largely based on approaches developed over 50 years ago where water samples are removed from natural conditions and incubated to measure O2 evolution or CO2 uptake; these approaches are time consuming and yield relatively few data. Fast Repetition Rate fluorescence (FRRf), is the only method which can be automated to produce in situ PP measurements with high spatial and temporal resolution at low cost required to circumvent the
historical PP measurements constraints. However, these estimates require knowledge of the environmental dependency of “the electron requirement for carbon fixation.”

Recent developments in FRRf technology and associated algorithms to estimate PP from FRRf data can increase the accuracy and resolution with which PP is examined in situ. Consequently, the aim of this studentship is to use these developments to address still unanswered questions for shelf seas: (i) How variable are key PP parameters, e.g. Pmax and α, spatially (location, depth) and temporally (diurnal, seasonal)? (ii) To what extent can these PP parameters be predicted from prevailing environmental factors, e.g. nutrients, mixing depth, irradiance? (iii) How well does the predicted physiological status of phytoplankton functional groups from biogeochemical models compare with data-rich FRRf-based estimates of photophysiology? (iv) How well do estimates of PP from ocean colour measurements and remote sensing algorithms compare with data-rich FRRf-based direct estimates of PP?

The studentship will be conducted in a partnership between the University of Essex, (where the student will be registered), the Centre for Environment, Fisheries & Aquaculture Science (CEFAS), Plymouth Marine Laboratory (PML) and the University of Southampton, and is funded through NERC’s Directed Program “Shelf Sea Biogeochemistry (SSB)” program (http://www.nerc.ac.uk/research/programmes/shelfsea/). Data will be collected in Irish, Celtic and North Seas primarily via participation in the Shelf Sea Biogeochemistry Programme (WP1) cruises throughout 2014 but also additional CEFAS led cruises throughout the program. Data collection will consist of FRRf-based observations along cruise tracks, and discrete water samples and nutrient enrichment experiments. Data evaluation will examine the relationship of FRRf-based PP to environmental (and phytoplankton community) conditions and subsequently investigate the use of high-resolution FRRf-based PP measurements for validating/developing remote sensing PP algorithms.

Candidates are expected to have knowledge of marine primary productivity and experience in a related discipline (with skills particularly in primary productivity techniques/approaches, numeracy and working with large data sets). Appropriate training and skill development will be provided in (i) biophysical properties of light and (FRR) fluorescence, experimental design, data analyses etc. (UoE), (ii) conceptual and computational models of PP (UoE, PML), and (iii) comparison of in situ data with ecosystem/remote sensing model outputs (CEFAS, PML). Sea-going experience and computer programming skills are also highly desirable, although not essential, as appropriate training can be provided. Interested candidates should apply on line through the University of Essex Graduate School (http://www.essex.ac.uk/bs/prospective_students/pg_research/default.aspx#apply). The project is embedded in NERC’s SSB program and students will participate in regular SSB meetings with the opportunity to engage with the SSB research network.

Further information can be obtained from Prof. Richard Geider (University of Essex),
[Email Address Removed].