between entrainment of sinking phytoplankton into the surface layer during high tidal current speeds and settlement of sinking phytoplankton during tidal slacks. A periodicity of 12 hours 25 min indicates changes in phytoplankton concentration due to horizontal transport of different water masses. A 24 hour periodicity would signal environmental forcing by the day-night cycle (e.g., diurnal stratification), which would be very different from the 24 hour 50 min periodicity of a mixed semidiurnal tide. At longer time scales, the spring-neap cycle and apogee-perigee cycle generate variation in the intensity of tidal mixing that could affect phytoplankton populations. Furthermore, we hypothesize that the impact of environmental forcing on phytoplankton population dynamics will depend on the relative magnitude of intrinsic population growth versus environ- mental forcing. For instance, settling and resuspension of phytoplankton in shallow coastal waters depends on the vertical mixing intensity generated by wind action and tidal motion [23,24]. Hence, in case of strong tidal forcing in comparison to the phytoplankton growth rate, we hypothesize that phytoplankton concentrations will fluctuate in phase with the intensity of tidal mixing. Conversely, in case of weak tidal forcing, the phytoplank- ton dynamics may be largely governed by intrinsic population growth. Because light availability is often a limiting factor in turbid coastal waters [25], reduced turbidity during calm conditions at neap tide may provide suitable light conditions for phytoplankton growth. Hence, in this case, phytoplankton concentrations are more likely to fluctuate in anti-phase with the intensity of tidal mixing. To investigate these hypotheses, we analyze phytoplankton fluctuations in a high-resolution time series obtained from an automated mooring station in the coastal North Sea. The mooring measured chlorophyll fluorescence, suspended particulate matter (SPM), nitrate, salinity, temperature and irradiance at a high temporal resolution for a period of nine years. Earlier analysis of the first year of this time series showed that the phytoplankton spring bloom was initiated by an improved light availability in spring, due to a combination of enhanced solar radiation and reduced SPM concentrations [26]. This indicates that settlement of suspended particles may play an important role at this station. However, this earlier analysis focused on the seasonal dynamics, but did not investigate phytoplankton and SPM variability in relation to the tidal regime. We apply wavelet analysis [27–29], which is an advanced statistical technique ideally suited to quantify the time scales of the phytoplankton fluctuations and their coherence with SPM and the tidal cycle. Our results reveal how fluctuations of coastal phytoplankton are driven by different oscillatory components of the tidal cycle. Methods Automated Measurements We analyzed data of mooring station Warp, located in the coastal waters of the southern North Sea near the Thames Estuary (Fig. 1). The main characteristics of this mooring station are summarized in Table 1. The site has a water depth of 15 m, and an average tidal range of 4.3 m. Vertical profiles of water density measured at this station are generally uniform over depth, indicative of well-mixed waters without thermohaline stratification (Fig. S1). At the mooring station an automated measuring platform, called a ‘SmartBuoy’, has been deployed from 30 November 2000 onwards, as part of the United Kingdom’s eutrophication monitoring program [30]. The SmartBuoy measured chlorophyll fluorescence, optical backscatter, salinity, temperature and photo- Dancing with the Tides Figure 1. Map of the southern North Sea with the monitoring stations. Phytoplankton, SPM, nutrient, light, salinity and temperature were measured by a SmartBuoy (circle) at mooring station Warp. Tidal data were obtained from tide gauges (triangles) at station Sheerness and station K13A. doi:10.1371/journal.pone.0049319.g001 synthetically active radiation (PAR) at 1 m depth, using sampling intervals ranging from 12 to 30 min. The nitrate concentration was measured at sampling intervals ranging from 1 to 24 hours. We have analyzed SmartBuoy data from the years 2001–2009. The data can be downloaded from the website http://www.cefas. defra.gov.uk. More information on the methodology and applica- tion of SmartBuoys can be found in Kro¨ger et al. [31], Greenwood et al. [32] and Nechad et al. [33]. Seasonal phytoplankton bloom dynamics and biogeochemistry at this station in 2001 have been described by Weston et al. [26]. Chlorophyll fluorescence was measured with a Seapoint fluorometer (Seapoint Inc.). Fluorescence data were calibrated against chlorophyll concentrations in water samples taken during monthly service visits to the mooring stations. Chlorophyll concentrations were measured by filtering known sample volumes through glass fiber filters (GF/F; Whatman) in triplicate. Pigments were immediately extracted in 90% buffered acetone and refrigerated prior to analysis. A Turner Designs Model 10AU filter fluorometer was used to measure the fluorescence of extracted chlorophyll and phaeopigment before and after acidi- fication as described by Tett [34]. The filter fluorometer was calibrated using a solution of pure chlorophyll-a (Sigma-Aldrich) with known concentrations determined spectrophotometrically. Calibration curves of in situ Seapoint fluorometer measurements versus extracted chlorophyll concentrations in the water samples had a R2 of 0.86 when averaged over all monthly samples. Although chlorophyll fluorescence is a very convenient measure- ment technique, it is known that the fluorescence signal can be quenched when cells are exposed to high light [19,35]. This may cause a reduction in chlorophyll fluorescence during the daytime, especially in clear waters at sunny days. Optical backscatter was measured with a Seapoint turbidity meter (Seapoint Inc.), and converted to SPM concentration using calibration against monthly water samples. SPM concentrations in PLOS ONE | www.plosone.org 2 November 2012 | Volume 7 | Issue 11 | e49319