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Using Hyperspectral Remote Sensing to Monitor Water Quality in Drinking Water Reservoirs
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At the Blankaart Water Production Center, a reservoir containing 3 million m3 of raw surface water acts as a first biologic treatment step before further processing to drinking water. Over the past decade, severe algal blooms have occurred in the reservoir, hampering the water production. Therefore, strategies (e.g., the injection of algaecide) have been looked at to prevent these from happening or try to control them. In this context, the HYperspectral Pointable System for Terrestrial and Aquatic Radiometry (HYPSTAR), installed since early 2021, helps in monitoring the effectiveness of these strategies. Indeed, the HYPSTAR provides, at a very high temporal resolution, bio-optical parameters related to the water quality, i.e., Chlorophyll-a (Chla) concentrations and suspended particulate matter (SPM). The present paper shows how the raw in situ hyperspectral data (a total of 8116 spectra recorded between 2021-02-03 and 2022-08-03, of which 2988 spectra passed the quality check) are processed to find the water-leaving reflectance and how SPM and Chla are derived from it. Based on a limited number of validation data, we also discuss the potential of retrieving phycocyanin (an accessory pigment unique to freshwater cyanobacteria). The results show the benefits of the high temporal resolution of the HYPSTAR to provide near real-time water quality indicators. The study confirms that, in conjunction with a few water sampling data used for validation, the HYPSTAR can be used as a quick and cost-effective method to detect and monitor phytoplankton blooms.
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RBINS Staff Publications 2022
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Monitoring of high biomass Phaeocystis globosa blooms in the Southern North Sea by in situ and future spaceborne hyperspectral radiometry
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Phaeocystis globosa (P. globosa hereafter) is a phytoplankton species which commonly blooms at high biomass in April–May in the Southern North Sea and forms undesirable foam which accumulates on the beaches. Monitoring of this species is required by EU directives. Measurement of phytoplankton species composition has historically been made by pigment or microscopic analysis of water samples, which is spatially sparse and temporally infrequent e.g. weekly/monthly. In-water instruments such as flow cytometers can provide very high frequency data but at high acquisition and maintenance cost. Automated in situ above water radiometry has the potential to provide very high frequency data at single locations but requires very careful design of processing algorithms in turbid waters with high non-algal absorption. Spaceborne radiometry could provide both very good spatial coverage and moderate/high frequency of data, e.g. daily/weekly, but accurate determination of phytoplankton species composition is considerably more difficult in turbid waters than in open ocean waters. Prior studies based on a limited number of shipborne reflectance measurements suggested feasibility of P. globosa detection in turbid waters from hyperspectral radiometry. The availability of a new autonomous above water hyperspectral radiometer system has enabled further refinement and intensive testing of these techniques. From a time-series of 4356 water reflectance spectra measured near Ostend harbour in Belgian coastal waters from 2020/04/01 to 2020/08/18, two existing algorithms for P. globosa detection were successfully applied. Results show a high biomass P. globosa bloom occurring in late-April/early-May as found every year in water sample analyses for Belgian coastal waters. The high temporal resolution of the radiometric data allows to capture the evolution of the bloom at time scales sufficiently short (hourly and daily) compared to growth/decay and tidal processes. The challenges of extending the methods to future spaceborne instruments are also tested by simulating the impact of errors in sensor inter-band calibration, atmospheric correction and radiometric noise. Results show that because of their spectral coherence, atmospheric correction errors impact only slightly P. globosa detection whereas inaccuracy in inter-band calibration and radiometric noise are much more problematic as they affect each spectral band independently. Because radiometric noise should be reduced in the new generation of hyperspectral sensors and can always be reduced by spatial binning, the inter-band relative calibration uncertainty appears to be the main challenge for spaceborne mission design. Indeed, it was demonstrated that inter-band calibration error should be 0.25\% and ideally 0.1\% at top of the atmosphere highlighting the need for particular attention to inter-band calibration in sensor design and post processing treatments including vicarious calibration.
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RBINS Staff Publications 2022
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Assessing the influences of bee’s (Hymnoptera: Apidae) floral preference on cashew (Anacardiacae) agronomics performances in Côte d’Ivoire.
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This study aimed to assess the influence of bees’ floral preference on cashew agronomics performances in Côte d’Ivoire. Therefore, a sampling design with a total of 40 cashew trees preferred by bees and 40 trees that were not preferred by bees was established in 4 main producing regions. In addition, bees’ foragers and agronomics performances of trees were sampled. As results, a total of 46 bee’ species with a foraging activity of 4±0.32 visits per minute were observed. Apis mellifera (60% of visits, with 2.27±0.17 of visitors per minute) followed by Meliponula bocandei (23% of visits with 0.91±0.18 of visits per minute) contributes significantly to the reproduction of cashew trees, compare to the 44 other bees’ species (17% of visits; with an activity of 0.69±0.03 of visitors per minute). The preferred trees recorded 40.54±0.57 kg of nuts per tree, with 18.39±0.48 fruits per inflorescence, including 37.12±0.4% of useful kernel per raw nut (yield ratio of 65.45±0.66 pound of useful kernel). Conversely, the non-preferred trees obtained 5.24±0.44kg of nuts per tree, with 1.7±0.21 fruits per inflorescence, including 28.69±0.65% of useful kernel per raw nut (50.6±1.15 pound of useful kernel). Hence, the foraging preference of these two Apidae significantly increased the fruiting rate (83.7±0.01%), the yields (87.08±0.0%), and the kernel rate (22.68±1.76%) in raw cashew nuts. Based in these results, we suggest the foraging preference of Apis mellifera as good indicator of high-yielding cashew plants. Moreover, we suggests combination of apicultural and meliponicultrual in cashew farming to boost the yields and farmers livelihoods.
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RBINS Staff Publications 2022
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The ants of the Galápagos Islands (Hymenoptera, Formicidae): a historical overview, checklist, and identification key
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The Galápagos ant fauna has long been understudied, with the last taxonomic summary being published almost a century ago. Here, a comprehensive and updated overview of the known ant species of the Galápagos Islands is provided with updated species distributions. The list is based on an extensive review of literature, the identification of more than 382,000 specimens deposited in different entomological collections, and recent expeditions to the islands. The ant fauna is composed of five subfamilies (Dolichoderinae, Dorylinae, Formicinae, Myrmicinae, and Ponerinae), 22 genera, 50 species, and 25 subspecies, although three species (Crematogaster crinosa Mayr, 1862, Camponotus senex (Smith, 1858), and Solenopsis saevissima (Smith, 1855)) are considered dubious records. Finally, an illustrated identification key of the species found in the archipelago is presented.
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RBINS Staff Publications 2023
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The HYPERMAQ dataset: bio-optical properties of moderately to extremely turbid waters
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Because of the large diversity of case 2 waters ranging from extremely absorbing to extremely scattering waters and the complexity of light transfer due to external terrestrial inputs, retrieving main biogeochemical parameters such as chlorophyll-a or suspended particulate matter concentration in these waters is still challenging. By providing optical and biogeochemical parameters for 180 sampling stations with turbidity and chlorophyll-a concentration ranging from 1 to 700 FNU and from 0.9 to 180 mg m−3 respectively, the HYPERMAQ dataset will contribute to a better description of marine optics in optically complex water bodies and can help the scientific community to develop algorithms. The HYPERMAQ dataset provides biogeochemical parameters (i.e. turbidity, pigment and chlorophyll-a concentration, suspended particulate matter), apparent optical properties (i.e. water reflectance from above water measurements) and inherent optical properties (i.e. absorption and attenuation coefficients) from six different study areas. These study areas include large estuaries (i.e. the Rio de la Plata in Argentina, the Yangtze estuary in China, and the Gironde estuary in France), inland (i.e. the Spuikom in Belgium and Chascomùs lake in Argentina), and coastal waters (Belgium). The dataset is available from Lavigne et al. (2022) at https://doi.org/10.1594/PANGAEA.944313.
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RBINS Staff Publications 2022
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On the Seasonal Dynamics of Phytoplankton Chlorophyll-a Concentration in Nearshore and Offshore Waters of Plymouth, in the English Channel: Enlisting the Help of a Surfer
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The role of phytoplankton as ocean primary producers and their influence on global biogeochemical cycles makes them arguably the most important living organisms in the sea. Like plants on land, phytoplankton exhibit seasonal cycles that are controlled by physical, chemical, and biological processes. Nearshore coastal waters often contain the highest levels of phytoplankton biomass. Yet, owing to difficulties in sampling this dynamic region, less is known about the seasonality of phytoplankton in the nearshore (e.g., surf zone) compared to offshore coastal, shelf and open ocean waters. Here, we analyse an annual dataset of chlorophyll-a concentration—a proxy of phytoplankton biomass—and sea surface temperature (SST) collected by a surfer at Bovisand Beach in Plymouth, UK on a near weekly basis between September 2017 and September 2018. By comparing this dataset with a complementary in-situ dataset collected 7 km offshore from the coastline (11 km from Bovisand Beach) at Station L4 of the Western Channel Observatory, and guided by satellite observations of light availability, we investigated differences in phytoplankton seasonal cycles between nearshore and offshore coastal waters. Whereas similarities in phytoplankton biomass were observed in autumn, winter and spring, we observed significant differences between sites during the summer months of July and August. Offshore (Station L4) chlorophyll-a concentrations dropped dramatically, whereas chlorophyll-a concentrations in the nearshore (Bovsiand Beach) remained high. We found chlorophyll-a in the nearshore to be significantly positively correlated with SST and PAR over the seasonal cycle, but no significant correlations were observed at the offshore location. However, offshore correlation coefficients were found to be more consistent with those observed in the nearshore when summer data (June–August 2018) were removed. Analysis of physical (temperature and density) and chemical variables (nutrients) suggest that the offshore site (Station L4) becomes stratified and nutrient limited at the surface during the summer, in contrast to the nearshore. However, we acknowledge that additional experiments are needed to verify this hypothesis. Considering predicted changes in ocean stratification, our findings may help understand how the spatial distribution of phytoplankton phenology within temperate coastal seas could be impacted by climate change. Additionally, this study emphasises the potential for using marine citizen science as a platform for acquiring environmental data in otherwise challenging regions of the ocean, for understanding ecological indicators such as phytoplankton abundance and phenology. We discuss the limitations of our study and future work needed to explore nearshore phytoplankton dynamics.
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RBINS Staff Publications 2022
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Validation of Landsat 8 high resolution Sea Surface Temperature using surfers
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Nearshore coastal waters are highly dynamic in both space and time. They can be difficult to sample using conventional methods due to their shallow depth, tidal variability, and the presence of strong currents and breaking waves. High resolution satellite sensors can be used to provide synoptic views of Surface Temperature (ST), but the performance of such ST products in the nearshore zone is poorly understood. Close to the shoreline, the ST pixels can be influenced by mixed composition of water and land, as a result of the sensor’s spatial resolution. This can cause thermal adjacency effects due to the highly different diurnal temperature cycles of water bodies and land. Previously, temperature data collected during surfing sessions has been proposed for validation of moderate resolution (1 km pixel size) satellite ST products. In this paper we use surfing temperature data to validate three high resolution (100 m resampled to 30 m pixel size) ST products derived from the Thermal InfraRed Sensor (TIRS) on board Landsat 8 (L8). ST was derived from Collection 1 and 2 Level 1 data (C1L1 and C2L1) using the Thermal Atmospheric Correction Tool (TACT), and was obtained from the standard Collection 2 Level 2 product (USGS C2L2). This study represents one of the first evaluations of the new C2 products, both L1 and L2, released by USGS at the end of 2020. Using automated matchup and image quality control, 88 matchups between L8/TIRS and surfers were identified, distributed across the North-Western semihemisphere. The unbiased Root Mean Squared Difference (uRMSD) between satellite and in situ measurements was generally ¡ 2 K, with warm biases (Mean Average Difference, MAD) of 1.7 K (USGS C2L2), 1.3 K (TACT C1L1) and 0.8 K (TACT C2L1). Large interquartile ranges of ST in 5 × 5 satellite pixels around the matchup location were found for several images, especially for the summer matchups around the Californian coast. By filtering on target stability the number of matchups reduced to 31, which halved the uRMSD across the three methods (to around 1.1K), MAD were much lower, i.e. 1.1 K (USGS C2L2), 0.6 K (TACT C1L1), and 0.2 K (TACT C2L1). The larger biases of the C2L2 product compared to TACT C2L1 are caused as a result of: (1) a lower emissivity value for water targets used in USGS C2L2, and (2) differences in atmospheric parameter retrieval, mainly from differences in upwelling atmospheric radiance and lower atmospheric transmittance retrieved by USGS C2L2. Additionally, tiling artefacts are present in the C2L2 product, which originate from a coarser atmospheric correction process. Overall, the L8/TIRS derived ST product compares well with in situ measurements made while surfing, and we found the best performing ST product for nearshore coastal waters to be the Collection 2 Level 1 data processed with TACT.
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Global satellite water classification data products over oceanic, coastal, and inland waters
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Satellites have generated extensive data of remote sensing reflectance spectra (Rrs(λ)) covering diverse water classes or types across global waters. Spectral classification of satellite Rrs(λ) data allows for the distinguishing and grouping of waters with characteristic bio-optical/biogeochemical features that may influence the productivity of a given water body. This study reports new satellite water class products (Level-2 and Level-3) from the Visible Infrared Imaging Radiometer Suite (VIIRS). We developed and implemented a hyperspectral scheme that accounts for the Rrs(λ) spectral shapes and globally resolves oceanic, coastal, and inland waters into 23 water classes. We characterized the light absorption and scattering coefficients, chlorophyll-a concentration, diffuse attenuation coefficient, and suspended particulate matter for individual water classes. It is shown that the water classes are separable by their distinct bio-optical and biogeochemical properties. Furthermore, validation result suggests that the VIIRS water class products are accurate globally. Finally, we examined the spatial and temporal variability of the water classes in case studies for a demonstration of applications. The water class data in open oceans reveal that the subtropical ocean gyres have experienced dramatic expansion over the last decade. In addition, the water class data appear to be a valuable (and qualitative) indicator for water quality in coastal and inland waters with compelling evidence. We stress that this new satellite product is an excellent addition to the aquatic science database, despite the need for continuous improvement toward perfection.
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RBINS Staff Publications 2022
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Comparing life history traits and tolerance to changing environments of two oyster species (Ostrea edulis and Crassostrea gigas) through Dynamic Energy Budget theory
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To predict the response of the European flat oyster (Ostrea edulis) and Pacific cupped oyster (Crassostrea gigas/Magallana gigas) populations to environmental changes, it is key to understand their life history traits. The Dynamic Energy Budget (DEB) theory is a mechanistic framework that enables the quantification of the bioenergetics of development, growth and reproduction from fertilization to death across different life stages. This study estimates the DEB parameters for the European flat oyster, based on a comprehensive dataset, while DEB parameters for the Pacific cupped oyster were extracted from the literature. The DEB parameters for both species were validated using growth rates from laboratory experiments at several constant temperatures and food levels as well as with collected aquaculture data from the Limfjorden, Denmark, and the German Bight. DEB parameters and the Arrhenius temperature parameters were compared to get insight in the life history traits of both species. It is expected that increasing water temperatures due to climate change will be beneficial for both species. Lower assimilation rates and high energy allocation to soma explain O. edulis’ slow growth and low reproductive output. Crassostrea gigas’ high assimilation rate, low investment in soma and extremely low reserve mobility explains the species’ fast growth, high tolerance to starvation and high reproductive output. Hence, the reproductive strategies of both species are considerably different. Flat oysters are especially susceptible to unfavourable environmental conditions during the brooding period, while Pacific oysters’ large investment in reproduction make it well adapted to highly diverse environments. Based on the life history traits, aquaculture and restoration of O. edulis should be executed in environments with suitable and stable conditions.
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RBINS Staff Publications 2022
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Organic Matter Composition of Biomineral Flocs and Its Influence on Suspended Particulate Matter Dynamics Along a Nearshore to Offshore Transect
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The seasonal variation in concentration of transparent exopolymer particles (TEPs), particulate organic carbon (POC) and particulate organic nitrogen (PON) were investigated together with floc size and the concentration of suspended particulate matter (SPM) along the cross-shore gradient, from the high turbid nearshore toward the low-turbid offshore waters in the Southern Bight of the North Sea. Our data demonstrate that biophysical flocculation cannot be explained by these heterogeneous parameters, but requires a distinction between a more reactive labile (“fresh”) and a less reactive refractory (“mineral-associated”) fraction. Based on all data, we separated the labile and mineral-associated POC, PON, and TEP using a semi-empirical model approach. The model's estimates of fresh and mineral-associated organic matter (OM) show that great parts of the POC, PON, and TEP are associated with suspended minerals, which are present in the water column throughout the year, whereas the occurrence of fresh TEP, POC, and PON is restricted to spring and summer months. In spite of a constantly high abundance of total TEP throughout the entire year, it is its fresh fraction that promotes the formation of larger and faster sinking biomineral flocs, thereby contributing to reducing the SPM concentration in the water column over spring and summer. Our results show that the different components of the SPM, such as minerals, extracellular OM and living organisms, form an integrated dynamic system with direct interactions and feedback controls.
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RBINS Staff Publications 2022
