Inferred support for disturbance‐recovery hypothesis of North Atlantic phytoplankton blooms. Issue 10 (31st October 2015)
- Record Type:
- Journal Article
- Title:
- Inferred support for disturbance‐recovery hypothesis of North Atlantic phytoplankton blooms. Issue 10 (31st October 2015)
- Main Title:
- Inferred support for disturbance‐recovery hypothesis of North Atlantic phytoplankton blooms
- Authors:
- Smith, Matthew J.
Tittensor, Derek P.
Lyutsarev, Vassily
Murphy, Eugene - Abstract:
- Abstract: Analyses of satellite‐derived chlorophyll data indicate that the phase of rapid phytoplankton population growth in the North Atlantic (the "spring bloom") is actually initiated in the winter rather than the spring, contradicting Sverdrup's critical depth hypothesis. An alternative disturbance‐recovery hypothesis (DRH) has been proposed to explain this discrepancy, in which the rapid deepening of the mixed layer reduces zooplankton grazing rates sufficiently to initiate the bloom. We use Bayesian parameter inference on a simple Nutrient‐Phytoplankton‐Zooplankton (NPZ) model to investigate the DRH and also investigate how well the model can capture the multiyear and spatial dynamics of phytoplankton concentrations and population growth rates. Every parameter in our NPZ model was inferred as a probability distribution given empirical constraints, which provides a more objective method to identify a model parameterization given available empirical evidence, rather than fixing or tuning individual parameter values. Our model explains around 75% of variation in the seasonal dynamics of phytoplankton concentrations, 30% of variation in their population rates of change, and correctly predicts the phases of population growth and decline. Our parameter‐inferred model supports the DRH, revealing the sustained reduction of grazing due to mixed‐layer deepening as the driving mechanism behind bloom initiation, with the relaxation of nutrient limitation being another contributoryAbstract: Analyses of satellite‐derived chlorophyll data indicate that the phase of rapid phytoplankton population growth in the North Atlantic (the "spring bloom") is actually initiated in the winter rather than the spring, contradicting Sverdrup's critical depth hypothesis. An alternative disturbance‐recovery hypothesis (DRH) has been proposed to explain this discrepancy, in which the rapid deepening of the mixed layer reduces zooplankton grazing rates sufficiently to initiate the bloom. We use Bayesian parameter inference on a simple Nutrient‐Phytoplankton‐Zooplankton (NPZ) model to investigate the DRH and also investigate how well the model can capture the multiyear and spatial dynamics of phytoplankton concentrations and population growth rates. Every parameter in our NPZ model was inferred as a probability distribution given empirical constraints, which provides a more objective method to identify a model parameterization given available empirical evidence, rather than fixing or tuning individual parameter values. Our model explains around 75% of variation in the seasonal dynamics of phytoplankton concentrations, 30% of variation in their population rates of change, and correctly predicts the phases of population growth and decline. Our parameter‐inferred model supports the DRH, revealing the sustained reduction of grazing due to mixed‐layer deepening as the driving mechanism behind bloom initiation, with the relaxation of nutrient limitation being another contributory mechanism. Our results also show that the continuation of the bloom is caused in part by the maintenance of phytoplankton concentrations below a level that can support positive zooplankton population growth. Our approach could be employed to formally assess alternative hypotheses for bloom formation. Key Points: Inferred parameter model supports disturbance‐recovery hypothesis for plankton blooms Bloom initiation occurs in winter when mixed layer deepens below euphotic zone depth Bloom prolonged by grazer population decline due to diluted phytoplankton concentrations … (more)
- Is Part Of:
- Journal of geophysical research. Volume 120:Issue 10(2015:Oct.)
- Journal:
- Journal of geophysical research
- Issue:
- Volume 120:Issue 10(2015:Oct.)
- Issue Display:
- Volume 120, Issue 10 (2015)
- Year:
- 2015
- Volume:
- 120
- Issue:
- 10
- Issue Sort Value:
- 2015-0120-0010-0000
- Page Start:
- 7067
- Page End:
- 7090
- Publication Date:
- 2015-10-31
- Subjects:
- inference -- productivity -- forecast -- NPZ -- parameter uncertainty -- structural uncertainty
Oceanography -- Periodicals
551.4605 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2169-9291 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/2015JC011080 ↗
- Languages:
- English
- ISSNs:
- 2169-9275
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4995.005000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 8816.xml