Shilin Tang

World's Largest Macroalgal Blooms Altered Phytoplankton Biomass in Summer in the Yellow Sea: Satellite Observations

Since 2008, the worlds largest blooms of the green macroalgae, Ulva prolifera, have occurred every summer in the Yellow Sea, posing the question of whether these macroalgal blooms (MABs) have changed the phytoplankton biomass due to their perturbations of nutrient dynamics. We have attempted to address this question using long-term Moderate Resolution Imaging Spectroradiometer (MODIS) observations. A new MODIS monthly time-series of chlorophyll-a concentrations (Chl-a, an index of phytoplankton biomass) was generated after removing the macroalgae-contaminated pixels that were characterized by unexpectedly high values in the daily Chl-a products. Compared with Chl-a during July of 2002-2006 (the pre-MAB period), Chl-a during July of 2008-2012 (the MAB period) exhibited significant increases in the offshore Yellow Sea waters (rich in macroalgae), with mean Chl-a increased by 98% from 0.64 mu g/L to 1.26 mu g/L in the study region. In contrast, no significant Chl-a changes were observed during June between the two periods. After analyzing sea surface temperature, photosynthetically available radiation, and nutrient availability, we speculate that the observed Chl-a changes are due to nutrient competition between macroalgae and phytoplankton: during the MAB period, the fast-growing macroalgae would uptake the increased nutrients from the origin of Jiangsu Shoal; thus, the nutrients available to phytoplankton were reduced, leading to no apparent increases in biomass in the offshore Yellow Sea in June.

Characterization and variability of particle size distributions in Hudson Bay, Canada

Particle size distribution (PSD) plays a significant role in many aspects of aquatic ecosystems, including phytoplankton dynamics, sediment fluxes, and optical scattering from particulates. As of yet, little is known on the variability of particle size distribution in marine ecosystems. In this study, we investigated the PSD properties and variability in Hudson Bay based on measurements from a laser diffractometer (LISST-100X Type-B) in concert with biogeochemical parameters collected during summer 2010. Results show that most power-law fitted PSD slopes ranged from 2.5 to 4.5, covering nearly the entire range observed for natural waters. Offshore waters showed a predominance of smaller particles while near the coast, the effect of riverine inputs on PSD were apparent. Particulate inorganic matter contributed more to total suspended matter in coastal waters leading to lower PSD slopes than offshore. The depth distribution of PSD slopes shows that larger particles were associated with the pycnocline. Below the pycnocline, smaller particles dominated the spectra. A comparison between a PSD slope-based method to derive phytoplankton size class (PSC) and pigment-based derived PSC showed the two methods agreed relatively well. This study provides valuable baseline information on particle size properties and phytoplankton composition estimates in a sub-arctic environment subject to rapid environmental change.

Beam attenuation, scattering and backscattering of marine particles in relation to particle size distribution and composition in Hudson Bay (Canada)

This study investigated the relationships between the concentration of biogeochemical parameters and particulate beam attenuation (cp), scattering (bp), and backscattering (bbp) in Hudson Bay. Results showed that most of the variability resulted from the presence of a deep chlorophyll maximum. cp, bp, and bbp were all adequate proxies to estimate total suspended matter (TSM) but were mostly sensitive to particulate inorganic matter (PIM) in the surface layer, and particulate organic matter (POM) at the chlorophyll maximum depth. The backscattering ratio b∼bp varied in the range of 0.005–0.05 and was inversely related to the POM : TSM ratio. According to the Twardowski et al. (2001) model, the PSD slope ξ well represented b∼bp and bulk refractive index n¯p in relation to particulate composition. For inorganic particulate dominated waters, both b∼bp and n¯p had a larger range and a higher mean value than at organic particulate dominated waters. This knowledge on the optical properties related to the PSD and particulate composition provides valuable information for further investigation and broadens our understanding of ocean optics in high latitude waters leading to potential improvements of regional scale remote sensing algorithms.

Regional algorithms for remote-sensing estimates of total suspended matter in the Beaufort Sea

The large and variable riverine inflow to Arctic continental shelves strongly influences their chemical, biological, and optical properties. The Beaufort Sea receives the largest amount of suspended sediments amongst all Arctic shelves, with sediment-laden Mackenzie river waters strongly influencing bio-optical properties on the shelf. Here, we developed two regional algorithms for the estimation of total suspended matter (TSM) concentration using Medium Resolution Imaging Spectrometer (MERIS) spectral bands, based on in situ optical and suspended particulate data collected in the summer during the Canadian Arctic Shelf Exchange Study (CASES) in 2004 and during the Arctic Coastal Ecosystem Study (ACES) in 2010. The band ratio (where R rs is remote-sensing reflectance) R rs,560/R rs,490 was best correlated with low TSM concentrations (less than 3.0 g m−3), while higher TSM concentrations were well correlated to R rs,681/R rs,560. An empirical piecewise algorithm is thus proposed with the switch between the ratios being triggered by R rs,681/R rs,560 at a threshold value of 0.6. The second algorithm made use of support vector machines (SVMs) as a nonlinear transfer function between TSM concentrations and remote-sensing reflectance ratios R rs,681/R rs,560, R rs,665/R rs,560, and R rs,560/R rs,490. Results show that both algorithms perform better (31% and 25%, respectively) than other published TSM algorithms including the MERIS Case 2 water processor (C2R) neural network algorithm in the study area.

Retrieval of suspended sediment concentration in the Pearl River Estuary from MERIS using support vector machines

With the rapid industrialization and urbanization, more and more solid have been emitted into the Pearl River Estuary. The suspended sediment concentration is one of the most important water quality parameters. With in-situ optical data and suspended sediment data collected on four cruises from 2004 to 2006 in the Pearl River Estuary, analysis shows that with the increasing of the total suspended sediment (TSM) concentration, the intensive bands which have the best correlation relationship with the TSM concentration shift from Rrs(620) to Rrs(778). When the mean suspended concentration is 14.5 g.m−3, the Rrs(620) has best correlation with the suspended concentration. However, when the mean suspended concentration becomes more than 40g.m−3, the most correlated band shifts to 778nm. It seems that all of the Rrs(620), Rrs(665), Rrs(681), Rrs(708), Rrs(753), Rrs(760), Rrs(778) may be the most sensitive band for the different TSM concentration. This work investigates the possibility of using a new universal approximator-support vector machines (SVMs)-as the nonlinear transfer function between TSM concentration and remote sensing reflectance in the Pearl River Estuary. Experimental results show that the SVM performs better result than general empirical algorithms or the piecewise algorithm. The correlation coefficient between the in-situ and modeled TSM of the test dataset is 0.91 and the root mean squared error (RMSE) is 0.145. The algorithm based on the SVM is applied to MERIS satellite data in January 31, 2007. The distribution of TSM concentration was obtained and it shows that the algorithm could be a useful tool for the study of TSM distribution in Pearl River estuary.

Retrieval of chlorophyll a concentration from a fluorescence enveloped area using hyperspectral data

It is acknowledged that fluorescence line height (FLH) algorithms are still hampered by the uncertainty of fluorescence peak position. The fluorescence peak moves to longer wavelengths with the increase of chlorophyll a concentration. In this article, the fluorescence enveloped area (FEA), which integrates the fluorescence height and the fluorescence peak position, was used to estimate the chlorophyll a concentration in the coastal waters of the Pearl River Estuary. The FEA algorithm was developed from in situ data of chlorophyll a concentration, total suspended matter (TSM) concentration and above-water remote sensing reflectance, which were collected at 37 sampling stations in the Pearl River Estuary during two cruises. The results showed that the FEA algorithm made a better estimation of chlorophyll a concentration compared with the widely used FLH algorithm and moving fluorescence line height (MFLH) algorithm. These three algorithms were applied to the Pearl River Estuary for retrieval of chlorophyll a concentration from Hyperion data acquired on 21 December 2006. Compared with the FLH and the MFLH, the FEA algorithm showed a rational distribution of the chlorophyll a concentration in the Pearl River Estuary.

A derivative spectrum algorithm for determination of chlorophyll-a concentration in the Pearl River estuary

Chlorophyll-a is the pigment presented in living plants or phytoplankton responsible for the photosynthesis, and it is a very important ecological and environmental parameter of waters, not only used for estimation of ocean primary productivity, but also for detection of red tides and for water quality. The chlorophyll-a concentration in coastal waters is generally overestimated from ocean color satellite data with common algorithm. In order to improve the remotely-sensed estimation of chlorophyll-a, many efforts have been made. In this study, six cruises for in situ data collection were conducted in lower reaches of the Pearl River and its estuary, the Lingdingyang, from 2003 to 2006. And the variables such as temperature, salinity, chlorophyll-a, total suspended matters (TSM), nutrients and gelbstoff absorption coefficient (Ag) were collected. The in situ remote sensing reflectance (Rrs) were measured from above waters with an ocean optics USB2000 spectrometer, which covers wavelength from 200 to 850 nm with spectral resolution of 0.38 nm. The original in situ Rrs data were processed to EO-1/hyperion bands (at resolution about 10 nm), and the derivative spectra with the different spectral resolutions were analyzed. The statistic analysis shows that the relative coefficient between derivative spectrum and chlorophyll-a is higher than that between original spectrum and chlorophyll-a. The band with highest relative coefficient to chlorophyll-a was employed for development of chlorophyll-a retrieval algorithm. A derivative spectrum algorithm was developed, and then applied to EO-1/hyperion data, which were acquired in December 16, 2006. The distribution image maps of chlorophyll-a concentration retrieved from EO-1/hyperion data were obtained. It shows that the derivative spectral method is an alternative approach for detection of water quality in coastal waters.

Using second-derivative spectrum to estimate Chlorophyll- a concentration in turbid estuarine waters

Hyperspectral technique is considered as one promising tool to solve the problems in monitoring optically-complex waters, which can be applied in optical sensors on board bouy, plane and satellite. In order to apply the technique in the in-situ chlorophyll monitoring of estuarine turbid waters, two cruises were carried out in May, 2004 and August, 2006, respectively, in Pearl River Estuary, China. In the cruises, water samples were collected at each sample station, a portable field spectroradiometer was used simultaneously to measure the downwelling sky radiance, and upwelling radiance of water and reference plaque, and the reflectance was calculated out. Further, the original reflectance spectra with 0.38 nm spectral resolution were resampled to 10 nm resolution, and then derivative spectra were processed. The results of correlation analysis between the chlorophyll-a concentrations and derivative spectra indicate that the second derivative spectra especially at 670 nm can be used to estimate chlorophyll-aconcentration of turbid estuarine waters, which suggests a new way for the in-situ chlorophyll measurement in the optically complex waters.

Seasonal and intraseasonal variability of surface chlorophyll a concentration in the South China Sea

Seasonal and intraseasonal variability of surface chlorophyll a concentration in the South China Sea is explored using the NASA standard Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) monthly and 8-day level-3 products from 1997 to 2007. The link between the seasonal and intraseasonal variability of the chlorophyll and physical forcing is revealed. Continuous wavelet transform indicates that chlorophyll in the South China Sea presents pronounced seasonal, as well as intraseasonal, variability. Chlorophyll a variability shows significant correlation with wind speed in all five sub-regions, while significant correlation with sea surface temperature only appears in the northern Sea. Intraseasonal variability of chlorophyll appears mainly in the winter, with spectral peaks around 32–64 days. It shows high commonalities for some periods in the intraseasonal cycle between chlorophyll a and sea surface temperature, wind stress curl or wind speed using cross wavelet transform.

Remotely-sensed estimation of the euphotic depth in the northern South China Sea

Euphotic layer of the sea refers to the layer where the phytoplankton can photosynthesize. Therefore the retrieval of the euphotic depth is in favor of estimating ocean primary productivity. This paper introduces an algorithm for retrieval of euphotic depth from ocean color remote sensing data, and dig out the relationship between the euphotic depth of the northern South China Sea (SCS) and the diffuse attenuation coefficient Kd (490) from theoretical deduction and in situ measurement data, then the remotely-sensed estimation of Kd (490) was used for computation of the euphotic depth of this area. A series of monthly and seasonal euphotic depth maps in the northern SCS were obtained and the seasonal variation of euphotic depth and its impact factors were analyzed.