scholarly journals Consistent Multi-Mission Measures of Inland Water Algal Bloom Spatial Extent Using MERIS, MODIS and OLCI

2021 ◽  
Vol 13 (17) ◽  
pp. 3349
Author(s):  
Chuiqing Zeng ◽  
Caren E. Binding
Keyword(s):  
Algal Blooms ◽  
Lake Erie ◽  
Algal Bloom ◽  
Spectral Band ◽  
Spatial Extent ◽  
Training Dataset ◽  
Western Basin ◽  
Time Period ◽  
Time Series Studies ◽  
The Impact

Envisat’s MERIS and its successor Sentinel OLCI have proven invaluable for documenting algal bloom conditions in coastal and inland waters. Observations over turbid eutrophic waters, in particular, have benefited from the band at 708 nm, which captures the reflectance peak associated with intense algal blooms and is key to line-height algorithms such as the Maximum Chlorophyll Index (MCI). With the MERIS mission ending in early 2012 and OLCI launched in 2016, however, time-series studies relying on these two sensors have to contend with an observation gap spanning four years. Alternate sensors, such as MODIS Aqua, offering neither the same spectral band configuration nor consistent spatial resolution, present challenges in ensuring continuity in derived bloom products. This study explores a neural network (NN) solution to fill the observation gap between MERIS and OLCI with MODIS Aqua data, delivering consistent algal bloom spatial extent products from 2002 to 2020 using these three sensors. With 14 bands of MODIS level 2 partially atmospherically corrected spectral reflectance as the NN input, the missing MERIS/OLCI band at 708 nm required for the MCI is simulated. The resulting NN-derived MODIS MCI (NNMCI) is shown to be in good agreement with MERIS and OLCI MCI in 2011 and 2017 respectively over the western basin of Lake Erie (R2 = 0.84, RMSE = 0.0032). To overcome the impact of MODIS sensor saturation over bright water targets, which otherwise renders pixels unusable for bloom detection using R-NIR wavebands, a variant NN model is employed which uses the 9 MODIS bands with the lowest probability of saturation to simulate the MCI. This variant NN predicts MCI with only a small increase in uncertainty (R2 = 0.73, RMSE = 0.005) allowing reliable estimates of bloom conditions in those previously unreported pixels. The NNMCI is shown to be robust when applied beyond the initial training dataset on Lake Erie, and when re-trained on different geographic areas (Lake Winnipeg and Lake of the Woods). Despite differences in spatial, temporal, and spectral resolution, MODIS algal bloom presence/absence was correctly classified in >92% of cases and bloom spatial extent derived within 25% uncertainty, allowing the application to the 2012–2015 time period to form a continuous and consistent multi-mission monitoring dataset from 2002 to 2020.

scholarly journals Metatranscriptomic Evidence for Co-Occurring Top-Down and Bottom-Up Controls on Toxic Cyanobacterial Communities

2015 ◽  
Vol 81 (9) ◽  
pp. 3268-3276 ◽  
Author(s):  
Morgan M. Steffen ◽  
B. Shafer Belisle ◽  
Sue B. Watson ◽  
Gregory L. Boyer ◽  
Richard A. Bourbonniere ◽  
...  
Keyword(s):  
Microbial Community ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Lake Erie ◽  
Sequence Data ◽  
Top Down ◽  
Western Basin ◽  
Bottom Up ◽  
Content Type ◽  
Cyanobacterial Harmful Algal Blooms

ABSTRACTLittle is known about the molecular and physiological function of co-occurring microbes within freshwater cyanobacterial harmful algal blooms (cHABs). To address this, community metatranscriptomes collected from the western basin of Lake Erie during August 2012 were examined. Using sequence data, we tested the hypothesis that the activity of the microbial community members is independent of community structure. Predicted metabolic and physiological functional profiles from spatially distinct metatranscriptomes were determined to be ≥90% similar between sites. Targeted analysis ofMicrocystis aeruginosa, the historical causative agent of cyanobacterial harmful algal blooms over the past ∼20 years, as well as analysis ofPlanktothrix agardhiiandAnabaena cylindrica, revealed ongoing transcription of genes involved in microcystin toxin synthesis as well as the acquisition of both nitrogen and phosphorus, nutrients often implicated as independent bottom-up drivers of eutrophication in aquatic systems. Transcription of genes involved in carbon dioxide (CO2) concentration and metabolism also provided support for the alternate hypothesis that high-pH conditions and dense algal biomass result in CO2-limiting conditions that further favor cyanobacterial dominance. Additionally, the presence ofMicrocystis-specific cyanophage sequences provided preliminary evidence of possible top-down virus-mediated control of cHAB populations. Overall, these data provide insight into the complex series of constraints associated withMicrocystisblooms that dominate the western basin of Lake Erie during summer months, demonstrating that multiple environmental factors work to shape the microbial community.

scholarly journals Satellite monitoring of harmful algal blooms in the Western Basin of Lake Erie: A 20-year time-series

2019 ◽  
Vol 45 (3) ◽  
pp. 508-521 ◽  
Author(s):  
Michael J. Sayers ◽  
Amanda G. Grimm ◽  
Robert A. Shuchman ◽  
Karl R. Bosse ◽  
Gary L. Fahnenstiel ◽  
...  
Keyword(s):  
Time Series ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Lake Erie ◽  
Satellite Monitoring ◽  
Western Basin

scholarly journals The Use of Sentinel-3 Imagery to Monitor Cyanobacterial Blooms

Environments ◽  
2019 ◽  
Vol 6 (6) ◽  
pp. 60 ◽  
Author(s):  
Igor Ogashawara
Keyword(s):  
Remote Sensing ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Lake Erie ◽  
Water Governance ◽  
Spectral Band ◽  
Cyanobacterial Blooms ◽  
Chl A ◽  
Cyanobacterial Harmful Algal Blooms ◽  
New Algorithms

Cyanobacterial harmful algal blooms (CHABs) have been a concern for aquatic systems, especially those used for water supply and recreation. Thus, the monitoring of CHABs is essential for the establishment of water governance policies. Recently, remote sensing has been used as a tool to monitor CHABs worldwide. Remote monitoring of CHABs relies on the optical properties of pigments, especially the phycocyanin (PC) and chlorophyll-a (chl-a). The goal of this study is to evaluate the potential of recent launch the Ocean and Land Color Instrument (OLCI) on-board the Sentinel-3 satellite to identify PC and chl-a. To do this, OLCI images were collected over the Western part of Lake Erie (U.S.A.) during the summer of 2016, 2017, and 2018. When comparing the use of traditional remote sensing algorithms to estimate PC and chl-a, none was able to accurately estimate both pigments. However, when single and band ratios were used to estimate these pigments, stronger correlations were found. These results indicate that spectral band selection should be re-evaluated for the development of new algorithms for OLCI images. Overall, Sentinel 3/OLCI has the potential to be used to identify PC and chl-a. However, algorithm development is needed.

scholarly journals Spatiotemporal Relationships of Phytoplankton Blooms, Drought, and Rainstorms in Freshwater Reservoirs

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 404
Author(s):  
Abigail S. Knapp ◽  
Adam M. Milewski
Keyword(s):  
United States ◽  
Statistical Modeling ◽  
Algal Blooms ◽  
Algal Bloom ◽  
Spatiotemporal Dynamics ◽  
Phytoplankton Blooms ◽  
Toxic Phytoplankton ◽  
Best Fitting ◽  
Global Threat ◽  
The Impact

Algal blooms, especially those composed of toxic phytoplankton, are a global threat to eutrophic and mesotrophic freshwater reservoirs. While extreme hydrologic events such as flooding and drought have been shown to control bloom onset and success, the spatiotemporal dynamics of these relationships are still unclear for mesotrophic reservoirs. In this study, the relationships between hydrologic events and phytoplankton in Lake Allatoona and Lake Lanier, Georgia, United States, were characterized using historical and satellite datasets from 2008 to 2017 and statistical modeling. Results showed that the impact of stormflow and rainstorm events varied systematically from riverine to lacustrine reaches of the two reservoirs on weekly and monthly scales. Precipitation duration and stormflow were the most significant and best-fitting predictors of algal bloom biomass in deeper reaches of the two reservoirs, suggesting that algal blooms in more lacustrine environments may be better equipped for wet and stormy regimes than has been previously hypothesized.

scholarly journals The impact of dreissenid mussels on growth of the fragile papershell (Leptodea fragilis), the most abundant unionid species in Lake Erie

2015 ◽  
Vol 93 (2) ◽  
pp. 143-148 ◽  
Author(s):  
Robert A. Krebs ◽  
Elizabeth M. Barkett ◽  
Matthew T. Begley
Keyword(s):  
Dreissena Polymorpha ◽  
Lake Erie ◽  
Freshwater Mussel ◽  
Species Competition ◽  
Western Basin ◽  
Dreissena Bugensis ◽  
Byssal Thread ◽  
Quagga Mussels ◽  
Dreissenid Mussels ◽  
The Impact

The arrival of zebra mussels (Dreissena polymorpha (Pallas, 1771)) and subsequently quagga mussels (Dreissena bugensis Andrusov, 1897) (Dreissenidae) in the Great Lakes in the 1980s induced many changes, most notably the devastation of native freshwater mussel species. Recently, empty shells of the fragile papershell (Leptodea fragilis (Rafinesque, 1820)) have become common, particularly in the western basin of Lake Erie, suggesting that this fast-growing species may be increasing in numbers in the lake. To examine continued competition with dreissenids, shell age and length of L. fragilis were used to contrast lifespan and growth rate, estimated as the slope of age on shell length, for shells from two beach localities where byssal threads were present on most shells and two sites where dreissenids were rare or absent. Few recent shells from Lake Erie beaches exceeded 5 years of age, and byssal thread counts were more numerous on older shells. Growth and lifespan were estimated to be significantly lower where dreissenid mussels remained numerous than when measured either from historic collections along Lake Erie or from protected populations. Therefore, even for this early-reproducing species, competition from dreissenids may continue to interfere with growth and shorten lifespan, which are effects few other unionid species can likely tolerate sufficiently to sustain population growth.

scholarly journals Landsat 8 Virtual Orange Band for Mapping Cyanobacterial Blooms

2020 ◽  
Vol 12 (5) ◽  
pp. 868 ◽  
Author(s):  
Abhishek Kumar ◽  
Deepak R. Mishra ◽  
Nirav Ilango
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Lake Erie ◽  
Cyanobacterial Bloom ◽  
Cyanobacterial Blooms ◽  
Landsat 8 ◽  
Western Basin ◽  
Accessory Pigment ◽  
Cyanobacterial Harmful Algal Blooms ◽  
Best Fit

The Landsat 8 Operational Land Imager (OLI) has a panchromatic band (503–676 nm) that can be used to derive a novel virtual orange band (590–635 nm) by using the multispectral green band and red band components. The orange band is useful for the accurate detection and quantification of phycocyanin (PC), an accessory pigment in toxin-producing cyanobacterial blooms, because of the specific light absorption characteristics of PC around 600–625 nm. In this study, we compared the Landsat 8 OLI’s and Sentinel-3 Ocean and Land Color Instrument’s (OLCI) derived orange band reflectance and PC products corresponding to a same-date overpass during a severe cyanobacterial bloom in Lake Erie, USA. The goal was to determine if the OLI’s virtual orange band can produce results equivalent to the OLCI’s actual orange band. Band-by-band match-ups used the OLI’s top-of-atmosphere (TOA) reflectance versus TOA reflectance from the OLCI, and surface reflectance (SR) from the OLI versus SR from the OLCI. A significant correlation was observed between the OLI’s and OLCI’s derived orange band TOA reflectance (R2 = 0.86; p < 0.001; NRMSE = 9.01%) and orange band SR (R2 = 0.93; p < 0.001; NRMSE = 20.23%). The PC map produced using the best-fit empirical models from both sensors showed similar PC spatial patterns and concentration levels in the western basin of Lake Erie. The results from this research are particularly important for the study of smaller inland waterbodies with the 30 m resolution of the OLI, which cannot be studied with the 300 m resolution of OLCI data, and for analyzing historical bloom events before the launch of the OLCI. Although more analysis and validation need to be conducted, this study opens up Landsat 8’s applicability in research on cyanobacterial harmful algal blooms (cyanoHABs).

scholarly journals Algal growth and weathering crust state drive variability in western Greenland Ice Sheet ice albedo

2020 ◽  
Vol 14 (2) ◽  
pp. 521-538 ◽  
Author(s):  
Andrew J. Tedstone ◽  
Joseph M. Cook ◽  
Christopher J. Williamson ◽  
Stefan Hofer ◽  
Jenine McCutcheon ◽  
...  
Keyword(s):  
Algal Blooms ◽  
Algal Bloom ◽  
Ice Sheet ◽  
Algal Growth ◽  
Greenland Ice Sheet ◽  
Weathering Crust ◽  
Near Surface ◽  
Ice Surfaces ◽  
Surface Ice ◽  
The Impact

Abstract. One of the primary controls upon the melting of the Greenland Ice Sheet (GrIS) is albedo, a measure of how much solar radiation that hits a surface is reflected without being absorbed. Lower-albedo snow and ice surfaces therefore warm more quickly. There is a major difference in the albedo of snow-covered versus bare-ice surfaces, but observations also show that there is substantial spatio-temporal variability of up to ∼0.4 in bare-ice albedo. Variability in bare-ice albedo has been attributed to a number of processes including the accumulation of light-absorbing impurities (LAIs) and the changing physical properties of the near-surface ice. However, the combined impact of these processes upon albedo remains poorly constrained. Here we use field observations to show that pigmented glacier algae are ubiquitous and cause surface darkening both within and outside the south-west GrIS “dark zone” but that other factors including modification of the ice surface by algal bloom presence, surface topography and weathering crust state are also important in determining patterns of daily albedo variability. We further use observations from an unmanned aerial system (UAS) to examine the scale gap in albedo between ground versus remotely sensed measurements made by Sentinel-2 (S-2) and MODIS. S-2 observations provide a highly conservative estimate of algal bloom presence because algal blooms occur in patches much smaller than the ground resolution of S-2 data. Nevertheless, the bare-ice albedo distribution at the scale of 20 m×20 m S-2 pixels is generally unimodal and unskewed. Conversely, bare-ice surfaces have a left-skewed albedo distribution at MODIS MOD10A1 scales. Thus, when MOD10A1 observations are used as input to energy balance modelling, meltwater production can be underestimated by ∼2 %. Our study highlights that (1) the impact of the weathering crust state is of similar importance to the direct darkening role of light-absorbing impurities upon ice albedo and (2) there is a spatial-scale dependency in albedo measurement which reduces detection of real changes at coarser resolutions.

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