[2] It became prominent in 1953 when Harald Sverdrup published the "Critical Depth Hypothesis" based on observations he had made in the North Atlantic on the Weather Ship M.[3] Sverdrup provides a simple formula based on several assumptions that relates the critical depth to plankton growth and loss rates and light levels.
Semina (1960) found that SCD hypothesis does not apply well in the Bering Sea near Kamchatka, where the bloom is more limited by stability, nutrients, and grazing than by light.
Siegel et al. (2002) deduced that eastern North Atlantic Basin south of 40°N is likely limited by nutrients rather than light and hence is another region where SCD hypothesis would not be well applied.
[1] Most research used hydrographically defined mixed layer depth, which is not a good proxy for turbulence-driven movement of the phytoplankton and hence might not properly test the applicability of SCD hypothesis, as argued in Franks (2014).
As more becomes known about phytoplankton loss rate components (such as grazing, respiration, and vertical export of sinking particles),[1] Sverdrup’s hypothesis has come under increasing criticism.
Smetacek and Passow published a paper in 1990 that challenged the model on the basis that phytoplankton cellular respiration is not constant, but is a function of growth rate, depth, and other factors.
[10] They claimed that net growth depended on irradiation, species physiology, grazing, and parasitic pressures in addition to mixed layer depth.
Sverdrup himself offered criticism of his model when he stated that "a phytoplankton population may increase independently of the thickness of the mixed layer if the turbulence is moderate.
[12] Since its introduction, Sverdrup’s hypothesis has provided a framework for future research, facilitating a wide range of studies that address its assumptions.
With the advancement of interdisciplinary knowledge and technological capabilities, it has become easier to expand on Sverdrup’s basic theory for critical depth using methods that were not available at the time of its original publication.
Many studies seek to address the shortcomings of the theory by using modern observational and modeling approaches to explain how various biological and physical processes affect the initiation of spring blooms in addition to critical depth.
Theories involving the role of physiological characteristics, grazing, nutrient availability, and upper ocean physics are active areas of research on spring blooms.
He describes this relationship as being diluted (fewer interactions) in the winter, when the mixed layer is deep and stratification of the water column is minimal.
[11] When the atmospheric cooling becomes weak in the spring, turbulence subsides rapidly, but the mixed layer takes a longer time to react; restratification of the mixed layer occurs on timescales of weeks to months, while reduction of turbulence takes effect almost immediately after forcing stops (i.e. after atmospheric cooling shifts to warming).
This theory has been explored by Taylor & Ferrari (2011) using 3D Large eddy simulation (LES) turbulence modeling to study how the shutdown of thermal convection (i.e. convective overturning resulting from cooling of the ocean surface) can halt upper ocean turbulence and initiate a bloom before the mixed layer shoals to the critical depth.
[6] Their findings were further supported in Ferrari et al. (2015) by remote sensing of chlorophyll using ocean color measurements from the NASA MODIS Aqua satellite and air-sea heat flux measurements from ECMWF re-analysis ERA-interim data to correlate high chlorophyll concentrations to changes in surface heat flux.
In addition to abiotic factors, recent studies have also examined the role of individual phytoplankton traits that may lead to the initiation of the spring bloom.
Models have suggested that these variable, cell-specific parameters, previously fixed by Sverdrup, could play an important role in predicting the onset of a bloom.
Using decades of satellite data, Behrenfeld and Boss argued that physiological adaptations to the environment were not significantly linked to bloom initiation (measured via cell division rate).
[21] However, recent results from Hunter-Cevera et al. using an automated submersible flow cytometer over 13 years show a positive correlation between temperature and cell division rate in Synechococcus.