Satellite-derived Chl Research Articles

Synergy of Sentinel-2A and Near-proximal sensor data for deriving biochemical parameters of paddy at different growth stages

The biochemical parameters (i.e. chlorophyll and nitrogen content) of crops are essential to evaluate the health status and to monitor crop growth. The incorporation of near-proximal sensor data with satellite data has offered a new angle for rapid, detailed, and reliable assessment of crop biochemical parameters. This study aimed to utilize the higher spatial and spectral resolution of Sentinel-2A multi-spectral instrument (MSI) satellite data in conjunction with near-proximal sensor data to derive the chlorophyll (Chl) content and nitrogen balance index (NBI) of paddy at different growth stages during the monsoon season (2017) in Ranchi district, Jharkhand. The key findings revealed that the satellite-derived Chl content and NBI of paddy were overestimated as compared to the field-based measurements. The correlations between satellite-derived and empirical model-based Chl content and NBI of paddy revealed a R2 of 0.92–0.99 (p < 0.001) at different growth stages. The Chl content was found higher (20–40 µg/cm2) during the peak growing stage of paddy and subsequently, it decreased (< 20 µg/cm2) by the start of the ripening stage. The root-mean-square error between the empirical model and satellite-based Chl content was from 7.7 to 8.5 µg/cm2. Thereby, it can be concluded that the MSI sensor with three red-edge bands along with visible and near-infrared has a virtuous capability to quantify the crop biochemical parameters. However, it needs a bias correction to derive Chl content/NBI accurately. The adopted methods of retrieving biochemical parameters at different growth stages would be beneficial for decision-makers in agriculture monitoring and can be incorporated in crop growth modelling and yield predictions.

Impact of physical and biogeochemical forcing on particle export in the South China Sea

This study examines temporal variations of 234Th-based particle export based on time-series observations conducted from 2004 to 2014 at the South-East Asian Time-series Study (SEATS) site in the basin area of the Northern South China Sea. It shows significant variability in particle export at both seasonal and interannual time scales. A significant feature of our data as observed by prior studies is that particle export was high during the NE monsoon in winter, but low during the inter-monsoon and SW monsoon. Particle flux increased with increasing mixed layer depth (MLD), primarily in winter due to the presence of a strong NE monsoon, in addition to influence by mesoscale features quantified by eddy kinetic energy values. Particle export was generally elevated when phytoplankton biomass was abundant, as shown by the significant correlation between particle fluxes and concentrations of chlorophyll (Chl) a and/or particulate organic carbon (POC) between 0 and 100 m. This is also supported by the negative correlation between 234Th residence time and Chl a concentration, suggesting that increased phytoplankton biomass accelerated downward particle sinking. The correlation disappeared however at Chl a values < 0.11 mg m−3, implicating other factors (e.g., phytoplankton community composition) as playing a more important role when biomass is relatively low. Satellite Chl a-based POC export estimated using various established algorithms agreed well with our measured fluxes when the export horizon was defined as the bottom of the mixed layer, but differed compared to estimated fluxes at 100 m depth. This is likely due to the fact that satellite-derived Chl a measurements only reflect surface values, suggesting that reliable algorithms must be used after considering the biological processes in subsurface waters.

Reconstruction of Ocean Color Data Using Machine Learning Techniques in Polar Regions: Focusing on Off Cape Hallett, Ross Sea

The most problematic issue in the ocean color application is the presence of heavy clouds, especially in polar regions. For that reason, the demand for the ocean color application in polar regions is increased. As a way to overcome such issues, we conducted the reconstruction of the chlorophyll-a concentration (CHL) data using the machine learning-based models to raise the usability of CHL data. This analysis was first conducted on a regional scale and focused on the biologically-valued Cape Hallett, Ross Sea, Antarctica. Environmental factors and geographical information associated with phytoplankton dynamics were considered as predictors for the CHL reconstruction, which were obtained from cloud-free microwave and reanalysis data. As the machine learning models used in the present study, the ensemble-based models such as Random forest (RF) and Extremely randomized tree (ET) were selected with 10-fold cross-validation. As a result, both CHL reconstructions from the two models showed significant agreement with the standard satellite-derived CHL data. In addition, the reconstructed CHLs were close to the actual CHL value even where it was not observed by the satellites. However, there is a slight difference between the CHL reconstruction results from the RF and the ET, which is likely caused by the difference in the contribution of each predictor. In addition, we examined the variable importance for the CHL reconstruction quantitatively. As such, the sea surface and atmospheric temperature, and the photosynthetically available radiation have high contributions to the model developments. Mostly, geographic information appears to have a lower contribution relative to environmental predictors. Lastly, we estimated the partial dependences for the predictors for further study on the variable contribution and investigated the contributions to the CHL reconstruction with changes in the predictors.

Estimation of Primary Production in the Northwestern Part of the Sea of Japan by Ship- and Satellite-Based Observations

The study analyzes data of ship-based observations on 45 stations performed aboard the R/V Akademik M.A. Lavrentyev on cruise 33 May 7–18, 2004, in the northwestern part of the Sea of Japan (35–44° N, 130–137° E). The following in situ data were used: CTD-data, assimilation number, concentrations of nutrients (nitrogen, phosphorus, and silicon compounds) and chlorophyll a (Сhl a). Satellite data on Сhl a concentration, diffuse attenuation coefficient at a wavelength of 490 nm, primary production (PP), and Photosynthetically Active Radiation (PAR) available from the Climate Change Initiative Ocean Colour (CCI-OC) and Ocean Productivity databases were also used for the same stations. The Chl a concentration in the first optical layer estimated from the results of ship-based measurements, was on average 0.55 ± 0.58 mg/m3, but the satellite-derived estimates were almost twice as high (0.95 ± 0.36 mg/m3). Ship assessments of PP were 1870 ± 900 mgC m–2 day–1; the value obtained using satellite data was 1.5 times smaller: 1226 ± 432 mgC m–2 day–1. Vertical Chl a profiles showed that the largest amount of Chl a was concentrated in the 20–45 m layer. Measurements of the assimilation number showed that most production occurs within the 0–55 m layer in the south of the study area and within the 0–30 m layer in the north. The weak correlation between ship- and satellite-derived Chl a and PP values can be explained by low accuracy of satellite-derived estimates.

Modelling ocean-colour-derived chlorophyll &amp;lt;i&amp;gt;a&amp;lt;/i&amp;gt;

Abstract. This article provides a proof of concept for using a biogeochemical/ecosystem/optical model with a radiative transfer component as a laboratory to explore aspects of ocean colour. We focus here on the satellite ocean colour chlorophyll a (Chl a) product provided by the often-used blue/green reflectance ratio algorithm. The model produces output that can be compared directly to the real-world ocean colour remotely sensed reflectance. This model output can then be used to produce an ocean colour satellite-like Chl a product using an algorithm linking the blue versus green reflectance similar to that used for the real world. Given that the model includes complete knowledge of the (model) water constituents, optics and reflectance, we can explore uncertainties and their causes in this proxy for Chl a (called derived Chl a in this paper). We compare the derived Chl a to the actual model Chl a field. In the model we find that the mean absolute bias due to the algorithm is 22 % between derived and actual Chl a. The real-world algorithm is found using concurrent in situ measurement of Chl a and radiometry. We ask whether increased in situ measurements to train the algorithm would improve the algorithm, and find a mixed result. There is a global overall improvement, but at the expense of some regions, especially in lower latitudes where the biases increase. Not surprisingly, we find that region-specific algorithms provide a significant improvement, at least in the annual mean. However, in the model, we find that no matter how the algorithm coefficients are found there can be a temporal mismatch between the derived Chl a and the actual Chl a. These mismatches stem from temporal decoupling between Chl a and other optically important water constituents (such as coloured dissolved organic matter and detrital matter). The degree of decoupling differs regionally and over time. For example, in many highly seasonal regions, the timing of initiation and peak of the spring bloom in the derived Chl a lags the actual Chl a by days and sometimes weeks. These results indicate that care should also be taken when studying phenology through satellite-derived products of Chl a. This study also reemphasizes that ocean-colour-derived Chl a is not the same as the real in situ Chl a. In fact the model derived Chl a compares better to real-world satellite-derived Chl a than the model actual Chl a. Modellers should keep this is mind when evaluating model output with ocean colour Chl a and in particular when assimilating this product. Our goal is to illustrate the use of a numerical laboratory that (a) helps users of ocean colour, particularly modellers, gain further understanding of the products they use and (b) helps the ocean colour community to explore other ocean colour products, their biases and uncertainties, as well as to aid in future algorithm development.

Modelling Kara Sea phytoplankton primary production: Development and skill assessment of regional algorithms

Empirical region-specific (RSM), depth-integrated (DIM) and depth-resolved (DRM) primary production models are developed based on data from the Kara Sea during the autumn (September–October 1993, 2007, 2011). The model is validated by using field and satellite (MODIS-Aqua) observations. Our findings suggest that RSM algorithms perform better than non-region-specific algorithms (NRSM) in terms of regression analysis, root-mean-square difference (RMSD) and model efficiency. In general, the RSM and NRSM underestimate or overestimate the in situ water column integrated primary production (IPP) by a factor of 2 and 2.8, respectively. Additionally, our results suggest that the model skill of the RSM increases when the chlorophyll specific carbon fixation rate, efficiency of photosynthesis and photosynthetically available radiation (PAR) are used as input variables. The parameterization of chlorophyll (chl a) vertical profiles is performed in Kara Sea waters with different trophic statuses. Model validation with field data suggests that the DIM and DRM algorithms perform equally (RMSD of 0.29 and 0.31, respectively). No changes in the performance of the DIM and DRM algorithms are observed (RMSD of 0.30 and 0.31, respectively) when satellite-derived chl a, PAR and the diffuse attenuation coefficient (Kd) are applied as input variables.

Can simple models predict large-scale surface ocean isoprene concentrations?

Abstract. We use isoprene and related field measurements from three different ocean data sets together with remotely sensed satellite data to model global marine isoprene emissions. We show that using monthly mean satellite-derived chl a concentrations to parameterize isoprene with a constant chl a normalized isoprene production rate underpredicts the measured oceanic isoprene concentration by a mean factor of 19 ± 12. Improving the model by using phytoplankton functional type dependent production values and by decreasing the bacterial degradation rate of isoprene in the water column results in only a slight underestimation (factor 1.7 ± 1.2). We calculate global isoprene emissions of 0.21 Tg C for 2014 using this improved model, which is twice the value calculated using the original model. Nonetheless, the sea-to-air fluxes have to be at least 1 order of magnitude higher to account for measured atmospheric isoprene mixing ratios. These findings suggest that there is at least one missing oceanic source of isoprene and, possibly, other unknown factors in the ocean or atmosphere influencing the atmospheric values. The discrepancy between calculated fluxes and atmospheric observations must be reconciled in order to fully understand the importance of marine-derived isoprene as a precursor to remote marine boundary layer particle formation.

Depth-integrated and depth-resolved models of Kara Sea primary production

Primary production (PP) models of the Kara Sea are developed based on data collected on fall expeditions (September–October 1993, 2007, and 2011) and their precision assessment utilizes the dataset collected in September 2013. The algorithms for different model types (depth-integrated and depth-resolved) are compared. The depth-resolved model performs slightly better than the depth-integrated one (the rootmean- square-difference (RMSD) are 0.29 and 0.31, respectively). These algorithms utilize the daily assimilation number (DAN) and photosynthetic efficiency (ψ) as the model coefficients, and surface chlorophyll a (chl a) and photosynthetically active radiation (PAR) as input variables. These algorithms perform better than the models that use chl a alone. Our results suggest that an increase in the performance of the Kara Sea PP models depends on the input of the photophysiological characteristics of phytoplankton (DAN and ψ) and PAR. To a lesser extent, this concerns the advantages of the depth-resolved model over the depth-integrated one. The constructed region-specific Kara Sea PP models combined with satellite-derived chl a and PAR can be used to estimate annual values and long-term variation of PP in hydrologically and hydrochemically similar waters of the Arctic Ocean.

Response patterns of phytoplankton growth to variations in resuspension in the German Bight revealed by daily MERIS data in 2003 and 2004

Chlorophyll (chl a) concentration in coastal seas exhibits variability on various spatial and temporal scales. Resuspension of particulate matter can somewhat limit algal growth, but can also enhance productivity because of the intrusion of nutrient-rich pore water from sediments or bottom water layers into the whole water column. This study investigates whether characteristic changes in net phytoplankton growth can be directly linked to resuspension events within the German Bight. Satellite-derived chl a were used to derive spatial patterns of net rates of chl a increase/decrease (NR) in 2003 and 2004. Spatial correlations between NR and mean water column irradiance were analysed. High correlations in space and time were found in most areas of the German Bight (R2 > 0.4), suggesting a tight coupling between light availability and algal growth during spring. These correlations were reduced within a distinct zone in the transition between shallow coastal areas and deeper offshore waters. In summer and autumn, a mismatch was found between phytoplankton blooms (chl a > 6 mg m−3) and spring-tidal induced resuspension events as indicated by bottom velocity, suggesting that there is no phytoplankton resuspension during spring tides. It is instead proposed here that frequent and recurrent spring-tidal resuspension events enhance algal growth by supplying remineralized nutrients. This hypothesis is corroborated by a lag correlation analysis between resuspension events and in-situ measured nutrient concentrations. This study outlines seasonally different patterns in phytoplankton productivity in response to variations in resuspension, which can serve as a reference for modelling coastal ecosystem dynamics.

A new method to generate a high-resolution global distribution map of lake chlorophyll

A new method was developed, evaluated, and applied to generate a global dataset of growing-season chlorophyll-a (chl) concentrations in 2011 for freshwater lakes. Chl observations from freshwater lakes are valuable for estimating lake productivity as well as assessing the role that these lakes play in carbon budgets. The standard 4 km NASA OceanColor L3 chlorophyll concentration products generated from MODIS and MERIS sensor data are not sufficiently representative of global chl values because these can only resolve larger lakes, which generally have lower chl concentrations than lakes of smaller surface area. Our new methodology utilizes the 300 m-resolution MERIS full-resolution full-swath (FRS) global dataset as input and does not rely on the land mask used to generate standard NASA products, which masks many lakes that are otherwise resolvable in MERIS imagery. The new method produced chl concentration values for 78,938 and 1,074 lakes in the northern and southern hemispheres, respectively. The mean chl for lakes visible in the MERIS composite was 19.2 ± 19.2, the median was 13.3, and the interquartile range was 3.90–28.6 mg m−3. The accuracy of the MERIS-derived values was assessed by comparison with temporally near-coincident and globally distributed in situ measurements from the literature (n = 185, RMSE = 9.39, R2 = 0.72). This represents the first global-scale dataset of satellite-derived chl estimates for medium to large lakes.

Satellite remote sensing of chlorophyll a in support of nutrient management in the Neuse and Tar–Pamlico River (North Carolina) estuaries

The North Carolina Environmental Management Commission (EMC) has adopted as a water quality standard that chlorophyll a concentration should not exceed 40μg/L in sounds, estuaries and other slow-moving waters. In 1996, nutrient load reductions were placed into North Carolina (NC) law to reduce the extent and duration of algal blooms in the Neuse and Tar River estuaries (Session Law 1995, Section 572). The chlorophyll a criterion was used as the endpoint to manage total nitrogen concentrations, and compliance would be achieved if chl a exceedances occurred in fewer than 10% of the samples collected in a specified area and time (known as the 10/40 criterion).In 2009, discussions were held between the North Carolina Department of Environmental and Natural Resources (NCDENR) and US Environmental Protection Agency (EPA) concerning the practicality of using satellite-derived chl a concentrations to monitor water quality, enforce water quality-related environmental regulations, and understand the environmental impacts of the watershed land-use practices on coastal waters.In this study, the MERIS chlorophyll a data product was used to conduct a retrospective analysis of the NC standard for water quality and Total Maximum Daily Load (TMDL) for total nitrogen in the Neuse and Tar–Pamlico River estuaries from 2006 to 2009. From daily MERIS images, compliance and chlorophyll exceedances in the Neuse and Tar–Pamlico River estuaries were assessed at daily and aggregated to annual time scales.

Ocean colour remote sensing in the southern Laptev Sea: evaluation and applications

Abstract. Enhanced permafrost warming and increased Arctic river discharges have heightened concern about the input of terrigenous matter into Arctic coastal waters. We used optical operational satellite data from the ocean colour sensor MERIS (Medium-Resolution Imaging Spectrometer) aboard the ENVISAT satellite mission for synoptic monitoring of the pathways of terrigenous matter on the shallow Laptev Sea shelf. Despite the high cloud coverage in summer that is inherent to this Arctic region, time series from MERIS satellite data from 2006 on to 2011 could be acquired and were processed using the Case-2 Regional Processor (C2R) for optically complex surface waters installed in the open-source software ESA BEAM-VISAT. Since optical remote sensing using ocean colour satellite data has seen little application in Siberian Arctic coastal and shelf waters, we assess the applicability of the calculated MERIS C2R parameters with surface water sampling data from the Russian–German ship expeditions LENA2008, LENA2010 and TRANSDRIFT-XVII taking place in August 2008 and August and September 2010 in the southern Laptev Sea. The shallow Siberian shelf waters are optically not comparable to the deeper, more transparent waters of the Arctic Ocean. The inner-shelf waters are characterized by low transparencies, due to turbid river water input, terrestrial input by coastal erosion, resuspension events and, therefore, high background concentrations of suspended particulate matter and coloured dissolved organic matter. We compared the field-based measurements with the satellite data that are closest in time. The match-up analyses related to LENA2008 and LENA2010 expedition data show the technical limits of matching in optically highly heterogeneous and dynamic shallow inner-shelf waters. The match-up analyses using the data from the marine TRANSDRIFT expedition were constrained by several days' difference between a match-up pair of satellite-derived and in situ parameters but are also based on the more stable hydrodynamic conditions of the deeper inner- and the outer-shelf waters. The relationship of satellite-derived turbidity-related parameters versus in situ suspended matter from TRANSDRIFT data shows that the backscattering coefficient C2R_bb_spm can be used to derive a Laptev-Sea-adapted SPM algorithm. Satellite-derived Chl a estimates are highly overestimated by a minimum factor of 10 if applied to the inner-shelf region due to elevated concentrations of terrestrial organic matter. To evaluate the applicability of ocean colour remote sensing, we include the visual analysis of lateral hydrographical features. The mapped turbidity-related MERIS C2R parameters show that the Laptev Sea is dominated by resuspension above submarine shallow banks and by frontal instabilities such as frontal meanders with amplitudes up to 30 km and eddies and filaments with horizontal scales up to 100 km that prevail throughout the sea-ice-free season. The widespread turbidity above submarine shallow banks indicates inner-shelf vertical mixing that seems frequently to reach down to submarine depths of a minimum of 10 m. The resuspension events and the frontal meanders, filaments and eddies indicate enhanced vertical mixing being widespread on the inner shelf. It is a new finding for the Laptev Sea that numerous frontal instabilities are made visible, and how highly time-dependent and turbulent the Laptev Sea shelf is. The meanders, filaments and eddies revealed by the ocean colour parameters indicate the lateral transportation pathways of terrestrial and living biological material in surface waters.

Acoustic characterization of pelagic fish distribution across the South Pacific Ocean

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 490:169-183 (2013) - DOI: https://doi.org/10.3354/meps10435 Acoustic characterization of pelagic fish distribution across the South Pacific Ocean Pablo Escobar-Flores1,*, Richard L. O’Driscoll2, John C. Montgomery1 1School of Biological Sciences, University Of Auckland, Private Bag 92019, Auckland 1142, New Zealand 2National Institute of Water and Atmospheric Research, Private Bag 14-901, Kilbirnie, Wellington 6241, New Zealand *Email: pesc003@aucklanduni.ac.nz ABSTRACT: Acoustic data can provide quantitative and qualitative information about the distribution and abundance of mid-trophic level functional groups in the marine ecosystem. Acoustic data, opportunistically collected on 2 return voyages between New Zealand and Chile, were used to describe the distribution patterns of pelagic fishes across the South Pacific Ocean. The area backscattering coefficient (sa in m2 m-2) at 38 kHz in the upper 600 m was used as the measure of fish abundance, and was assumed to be dominated by mesopelagic fishes. Consistent vertical and horizontal patterns of pelagic fish distribution were identified. Vertical (depth) patterns included diel migration and layering. Key horizontal (spatial) patterns were coastal intensification and oceanic patchiness. Boosted regression trees models were used to explain the relationship between sa and environmental and geographical variables. The key finding was that there was a strong correlation between satellite-derived chl a and distribution of acoustic backscatter. The incorporation of species composition information from biological sampling would improve the relevance of the results of this study. Nevertheless, these large-scale estimates provide an opportunity to validate model predictions of mid-trophic functional groups and to inform ecosystem-based fisheries management. KEY WORDS: Ecosystem · South Pacific Ocean · Acoustic · Mesopelagic fishes · Diel migration · Opportunistic data · Large-scale patterns · Boosted regression trees Full text in pdf format PreviousNextCite this article as: Escobar-Flores P, O’Driscoll RL, Montgomery JC (2013) Acoustic characterization of pelagic fish distribution across the South Pacific Ocean. Mar Ecol Prog Ser 490:169-183. https://doi.org/10.3354/meps10435 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 490. Online publication date: September 17, 2013 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2013 Inter-Research.

Satellite views of the seasonal and interannual variability of phytoplankton blooms in the eastern China seas over the past 14 yr (1998–2011)

Abstract. The eastern China seas are some of the largest marginal seas in the world, where high primary productivity and phytoplankton blooms are often observed. However, little is known about their systematic variation of phytoplankton blooms on large spatial and long temporal scales due to the difficulty of monitoring bloom events by field measurement. In this study, we investigated the seasonal and interannual variability and long-term changes in phytoplankton blooms in the eastern China seas using a 14 yr (1998–2011) time series of satellite ocean colour data. To ensure a proper satellite dataset to figure out the bloom events, we validated and corrected the satellite-derived chlorophyll concentration (chl a) using extensive in situ datasets from two large cruises. The correlation coefficients between the satellite retrieval data and the in situ chl a on the logarithmic scale were 0.85 and 0.72 for the SeaWiFS and Aqua/MODIS data, respectively. Although satellites generally overestimate the chl a, especially in highly turbid waters, both the in situ and satellite data show that the overestimation of satellite-derived chl a has an upper limit value (10 μg L−1), which can be used as a threshold for the identification of phytoplankton blooms to avoid the false blooms resulting from turbid waters. Taking 10 μg L−1 as the threshold, we present the spatial-temporal variability of phytoplankton blooms in the eastern China seas over the past 14 yr. Most blooms occur in the Changjiang Estuary and along the coasts of Zhejiang, with a maximal frequency of 20% (about 73 days per year). The coasts of the northern Yellow Sea and the Bohai Sea also have high-frequency blooms (up to 20%). The blooms show significant seasonal variation, with most occurring in spring (April–June) and summer (July–September). The study also revealed a doubling in bloom intensity in the Yellow Sea and Bohai Sea during the past 14 yr. The nutrient supply in the eastern China seas might be a major controlling factor in bloom variation. The time series in situ nutrient datasets show that both the nitrate and phosphate concentrations increased more than twofold between 1998 and 2005 in the Yellow Sea. This might be the reason for the doubling of the bloom intensity index in the Yellow Sea and Bohai Sea. In contrast, there has been no significant long-term increase or decrease in the Changjiang Estuary, which might be regulated by the Changjiang River discharge. These results offer a foundation for the study of the influence of phytoplankton blooms on the carbon flux estimation and biogeochemical processes in the eastern China seas.

Perspectives on empirical approaches for ocean color remote sensing of chlorophyll in a changing climate

Phytoplankton biomass and productivity have been continuously monitored from ocean color satellites for over a decade. Yet, the most widely used empirical approach for estimating chlorophyll a (Chl) from satellites can be in error by a factor of 5 or more. Such variability is due to differences in absorption and backscattering properties of phytoplankton and related concentrations of colored-dissolved organic matter (CDOM) and minerals. The empirical algorithms have built-in assumptions that follow the basic precept of biological oceanography--namely, oligotrophic regions with low phytoplankton biomass are populated with small phytoplankton, whereas more productive regions contain larger bloom-forming phytoplankton. With a changing world ocean, phytoplankton composition may shift in response to altered environmental forcing, and CDOM and mineral concentrations may become uncoupled from phytoplankton stocks, creating further uncertainty and error in the empirical approaches. Hence, caution is warranted when using empirically derived Chl to infer climate-related changes in ocean biology. The Southern Ocean is already experiencing climatic shifts and shows substantial errors in satellite-derived Chl for different phytoplankton assemblages. Accurate global assessments of phytoplankton will require improved technology and modeling, enhanced field observations, and ongoing validation of our "eyes in space."

Coherence of particulate beam attenuation and backscattering coefficients in diverse open ocean environments

We present an extensive data set of particle attenuation (c(p)), backscattering (b(bp)), and chlorophyll concentration (Chl) from a diverse set of open ocean environments. A consistent observation in the data set is the strong coherence between c(p) and b(bp) and the resulting constancy of the backscattering ratio (0.010 +/- 0.002). The strong covariability between c(p) and b(bp) must be rooted in one or both of two explanations, 1) the size distribution of particles in the ocean is remarkably conserved and particle types responsible for c(p) and b(bp) covary, 2) the same particle types exert influence on both quantities. Therefore, existing relationships between c(p) or Chl:c(p) and phytoplankton biomass and physiological indices can be conceptually extended to the use of b(bp). This finding lends support to use of satellite-derived Chl and b(bp) for investigation of phytoplankton biomass and physiology and broadens the applications of existing ocean color retrievals.

Global Distribution of the Random Uncertainty Associated With Satellite-Derived Chl a

The comparison of coincident daily records of the concentration of chlorophyll a (Chla) derived from the Sea-viewing Wide Field-of-view Sensor and the Moderate Resolution Imaging Spectroradiometer can provide the distribution of the standard deviation ? associated with the zero-mean random component of the uncertainty budget. The proposed approach does not quantify the bias characterizing the Chla satellite product, but it is spatially and temporally resolved and thus appears as a useful complement to validation exercises with in situ data. The global median of ? is equal to 0.074 for log-transformed Chla. The values of ? that are around or larger than 0.1 are found in a significant part of the ocean, including the centers of the subtropical gyres, some Arctic and Antarctic areas, or eastern boundary upwelling regions. In general, ? increases at the low and high ends of the Chla range, whereas it is lowest in the interval 0.1-0.3 mg ·m-3.

Seasonal and interannual correlations between right-whale distribution and calving success and chlorophyll concentrations in the Gulf of Maine, USA

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 394:289-302 (2009) - DOI: https://doi.org/10.3354/meps08267 Seasonal and interannual correlations between right-whale distribution and calving success and chlorophyll concentrations in the Gulf of Maine, USA Brittan L. Hlista1, Heidi M. Sosik1,*, Linda V. Martin Traykovski1, Robert D. Kenney2, Michael J. Moore1 1Biology Department, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02543, USA 2Graduate School of Oceanography, University of Rhode Island, Narragansett, Rhode Island 02882-1197, USA *Corresponding author. Email: hsosik@whoi.edu ABSTRACT: The North Atlantic right whale Eubalaena glacialis is one of the most endangered species of large whales. Although human-caused mortality is the primary factor contributing to poor recovery of E. glacialis, variability in reproductive success may also play a role. The present study evaluates the idea that seasonal distributions and reproductive success in E. glacialis are linked to food availability or related environmental conditions that can be assessed by treating satellite-derived sea-surface chlorophyll (chl) concentration as a proxy. Sea-surface chl time series in the major high-use feeding habitats and whale-sightings data were compared. Whale transition between habitats reflects a pattern in the seasonal distribution of peak concentration in satellite-derived chl. A regionally and seasonally weighted chl index was calculated to reflect aspects of average potential food condition. We found a significant correlation between the number of whale calves born and the weighted chl averaged over the prior 2 yr. These findings are consistent with the view that food availability during and just before the gestation period may be a critical factor regulating reproductive success, with low food years contributing to delays in conception. Longer time series are necessary to examine the predictive relationship between weighted chl concentration and calf production. Although ecological interactions and whale reproductive biology are certainly more complex than can be encompassed by emphasizing only food availability, analysis of satellite-derived surface chl concentrations provides a practical means to monitor a level of ecosystem variability that affects right-whale distributions and productivity. KEY WORDS: Right whale · Eubalaena glacialis · Calving · Seasonal patterns · Ocean color · SeaWiFS · Chlorophyll · Remote sensing Full text in pdf format PreviousCite this article as: Hlista BL, Sosik HM, Martin Traykovski LV, Kenney RD, Moore MJ (2009) Seasonal and interannual correlations between right-whale distribution and calving success and chlorophyll concentrations in the Gulf of Maine, USA. Mar Ecol Prog Ser 394:289-302. https://doi.org/10.3354/meps08267 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 394. Online publication date: November 18, 2009 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2009 Inter-Research.