New light for time series: international collaboration in ship-based ecosystem monitoring.

Ship-based biogeochemical and ecological time series are one of the most valuable tools to characterize and quantify ocean ecosystems. These programs continuously provided major breakthroughs in understanding ecosystem variability, allow quantification of the ocean carbon cycle, and help understand the processes that link biodiversity, food webs, and changes in services that benefit human societies. A quantum jump in regional and global ocean ecosystem science can be gained by aggregating observations from individual time series that are distributed across different oceans and which are managed by different countries. The collective value of these data is greater than that provided by each time series individually. However, maintaining time series requires a commitment by the science community and sponsor agencies.. Based on the success of existing initiatives, e.g. ICES and SCOR working groups, IOC-UNESCO launched the International Group for Marine Ecological Time Series (IGMETS, http://igmets.net) to promote collaborations across different individual projects, and jointly look at holistic changes within different ocean regions. The effort explores the reasons and connections for changes in phytoplankton and zooplankton at a global level and identifies locations where particularly large changes may be ocurring. This compilation will facilitate better coordination, communication, and data intercomparability among time series.IEO (RADIALES) IOC-UNESC

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Not AvailableThe in situ remote sensing reflectance (Rrs) and optically active substances (OAS) measured using hyperspectral radiometer, were used for optical classification of coastal waters in the southeastern Arabian Sea. The spectral Rrs showed three distinct water types, that were associated with the variability in OAS such as chlorophyll-a (chl-a), chromophoric dissolved organic matter (CDOM) and volume scattering function at 650 nm (β650). The water types were classified as Type-I, Type-II and Type-III respectively for the three Rrs spectra. The Type-I waters showed the peak Rrs in the blue band (470 nm), whereas in the case of Type-II and III waters the peak Rrs was at 560 and 570 nm respectively. The shifting of the peak Rrs at the longer wavelength was due to an increase in concentration of OAS. Further, we evaluated six bio-optical algorithms (OC3C, OC4O, OC4, OC4E, OC3M and OC4O2) used operationally to retrieve chl-a from Coastal Zone Colour Scanner (CZCS), Ocean Colour Temperature Scanner (OCTS), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), MEdium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS) and Ocean Colour Monitor (OCM2). For chl-a concentration greater than 1.0 mg m−3, algorithms based on the reference band ratios 488/510/520 nm to 547/550/555/560/565 nm have to be considered. The assessment of algorithms showed better performance of OC3M and OC4. All the algorithms exhibited better performance in Type-I waters. However, the performance was poor in Type-II and Type-III waters which could be attributed to the significant co-variance of chl-a with CDOM.Not Availabl

Satellite estimates of the long-term trend in phytoplankton size classes in the coastal waters of North-Western Bay of Bengal

The study presents long-term variability in satellite retrieved phytoplankton size classes (PSC) at two coastal sites, off Gopalpur and Visakhapatnam, in the north-western Bay of Bengal. The abundance-based models by Brewin et al. (2010) (B10) and Sahay et al. (2017) (S17), for retrieval of PSC (micro, nano, and picophytoplankton), from satellite data, were validated. Both the models performed well in the retrieval of nano and microphytoplankton. However, B10 performed poorly in retrieving picophytoplankton. The statistical analysis indicated better performance of the S17 model and hence was applied to Moderate Resolution Imaging Spectroradiometer onboard Aqua satellite (MODISA) data to understand the temporal (at monthly climatology) and spatial variability (from nearshore to offshore). The spatial distribution indicated nearshore dominance of micro and offshore dominance of picophytoplankton. In nearshore waters off Gopalpur, microphytoplankton dominated throughout the year except for months of south-west monsoon (June and July) where the dominance of picophytoplankton was observed. All PSC exhibited similar distribution at an annual scale with a primary peak during pre-monsoon (March and April) and a secondary peak during post-monsoon (September— November). However, microphytoplankton concentration during post-monsoon was higher off Gopalpur in comparison to Visakhapatnam. The higher microphytoplankton concentration during pre-monsoon was attributed to recurrent phytoplankton blooms. Whereas, post-monsoon increment could be attributed to enhanced phytoplankton growth by availing nutrients sourced from monsoonal precipitation induced terrigenous influx. The outcome of the present study recommends the use of the S17 model for satellite retrieval of PSC from the north-western Bay of Bengal

Chromophoric dissolved organic matter (CDOM) variability over the continental shelf of the Northern Bay of Bengal

The present paper dealt with the annual dynamics of the absorption coefficient of chromophoric dissolved organic matter at 440 nm {aCDOM(440)} during February 2015 to January 2016 in the continental shelf of northern Bay of Bengal (nBoB) for the first time. Sea surface salinity (SSS), chlorophyll-a (Chl-a), total suspended matter (TSM) were also analyzed. It was hypothesized that CDOM should exhibit significant spatial and temporal variability in this region. aCDOM(440) and spectral slope ranged between 0.1002 m1—0.6631 m1 and 0.0071 nm1— 0.0229 nm1 respectively during the entire study period. Higher values of aCDOM(440) were observed in the near shore stations and gradually decreased towards the offshore. Significant seasonal variability of aCDOM(440) was observed between the monsoon and non-monsoon seasons ( p < 0.05). Thus the framed hypothesis was successfully accepted by means of the present study. The CDOM was mainly found to be of allochthonous character in this region. aCDOM(440) portrayed a significant negative linear relationship with SSS (R2 = 0.80; p < 0.05) implying conservative mixing of marine and terrestrial end members. However, examining the spatial variability of the relationship, it was observed that this relationship was significant only in the nearshore stations. While examining the seasonal variability of this relationship, it was found to be most significant during the monsoon (R2 = 0.81; p < 0.05). Thus it was inferred that whenever the SSS gradient was higher, the relationship between aCDOM(440) and SSS was found to be most significant