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Current progress in developing a MARPOL Annex VI enforcement strategy in the Bonn Agreement through remote measurements.
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RBINS Staff Publications 2023
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Assessment of the Effect of International Maritime Regulations on Air Quality in the Southern North Sea.
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RBINS Staff Publications 2023
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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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Publishing data to support the fight against human vector-borne diseases
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Vector-borne diseases are responsible for more than 17% of human cases of infectious diseases. In most situations, effective control of debilitating and deadly vector-bone diseases (VBDs), such as malaria, dengue, chikungunya, yellow fever, Zika and Chagas requires up-to-date, robust and comprehensive information on the presence, diversity, ecology, bionomics and geographic spread of the organisms that carry and transmit the infectious agents. Huge gaps exist in the information related to these vectors, creating an essential need for campaigns to mobilise and share data. The publication of data papers is an effective tool for overcoming this challenge. These peer-reviewed articles provide scholarly credit for researchers whose vital work of assembling and publishing well-described, properly-formatted datasets often fails to receive appropriate recognition. To address this, GigaScience’s sister journal GigaByte partnered with the Global Biodiversity Information Facility (GBIF) to publish a series of data papers, with support from the Special Programme for Research and Training in Tropical Diseases (TDR), hosted by the World Health Organisation (WHO). Here we outline the initial results of this targeted approach to sharing data and describe its importance for controlling VBDs and improving public health.
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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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Suitability of multisensory satellites for long-term chlorophyll assessment in coastal waters: A case study in optically-complex waters of the temperate region
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We investigated the use of multisensory satellite data to determine long-term changes in surface chlorophyll concentrations using a 19-year (1998–2016) time series of chlorophyll data in the Danish Kattegat region of the Baltic Sea. Merged satellite estimates (SeaWiFS-MODIS/Aqua-MERIS-VIIRS) were compared with in situ ship based time series from four monitoring stations situated with increasing distance from land and nutrient sources. In situ and satellite derived estimates showed similar trend in chlorophyll with several fold higher values closer to land. Satellites aligned very well with in situ estimates in the open water stations but showed significant differences in magnitude and inter-annual variability, in particular in shallow coastal waters. Some systematic deviation was observed with satellite underestimating the growing season average for the earlier periods (1998–2002) and overestimating for the later period (2012–2016) compared to in situ estimates. Comparing growing season chlorophyll means over the 19 year period showed increasing magnitude and variability in nearshore and shallower areas, most pronounced for the satellite derived chlorophyll. Satellites overestimated chlorophyll in nearshore areas 2–4 fold, despite excluding shallow nearshore areas with possible benthic interferences from the analyses. This bias needs further validation and requires correction to improve the overall applicability of satellites for long-term monitoring of chlorophyll in the Kattegat region. From analysis of normalized data, we developed a simple correction model, which reduced deviations considerably between methods, underlying the importance of in situ data for application of satellite observations. While significant deviations were observed from in situ data, satellites are clearly advantageous in the much higher temporal and high spatial coverage they provide. Multisensory satellites can, however, not be used currently as a standalone technique for long-term assessment of chlorophyll. They require validation with in situ measurements, which provide essential data for calibration, validation and correction of satellite based estimates. A complementary use of multisensory satellite and in situ measurements therefore remains essential to assess trends in the ecological status of optically complex waters such as the Kattegat region of the Baltic Sea.
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RBINS Staff Publications 2022
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Quality-control tests for OC4, OC5 and NIR-red satellite chlorophyll-a algorithms applied to coastal waters
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Reliable satellite estimates of chlorophyll-a concentration (Chl-a) are needed in coastal waters for applications such as eutrophication monitoring. However, because of the optical complexity of coastal waters, retrieving accurate Chl-a is still challenging. Many algorithms exist and give quite different performance for different optical conditions but there is no clear definition of the limits of applicability of each algorithm and no clear basis for deciding which algorithm to apply to any given image pixel (reflectance spectrum). Poor quality satellite Chl-a data can easily reach end-users. To remedy this and provide a clear decision on when a specific Chl-a algorithm can be used, we propose simple quality control tests, based on MERIS water leaving reflectance (ρw) bands, to determine on a pixel-by-pixel basis if any of three popular and complementary algorithms can be used. The algorithms being tested are: 1. the OC4 blue-green band ratio algorithm which was designed for open ocean waters; 2. the OC5 algorithm which is based on look-up tables and corrects OC4 overestimation in moderately turbid waters and 3. a near infrared-red (NIR-red) band ratio algorithm designed for eutrophic waters. Using a dataset of 348 in situ Chl-a / MERIS matchups, the conditions for reliable performance of each of the selected algorithms are determined. The approach proposed here looks for the best compromise between the minimization of the relative difference between In situ measurements and satellite estimations and the number of pixels processed. Conditions for a reliable application of OC4 and OC5 depend on ρw412/ρw443 and ρw560, used as proxies of coloured dissolved organic matter and suspended particulate matter (SPM), as compared to ρw560/ρw490, used as a proxy for Chl-a. Conditions for reliable application of the NIR-red band ratio algorithm depend on Chl-a and SPM. These conditions are translated into pixel-based quality control (QC) tests with appropriately chosen thresholds. Results show that by removing data which do not pass QC, the performance of the three selected algorithms is significantly improved. After combining these algorithms, 70\% of the dataset could be processed with a median absolute percent difference of 30.5\%. The QC tests and algorithm merging methodology were then tested on four MERIS images of European waters. The OC5 algorithm was found to be suitable for most pixels, except in very turbid and eutrophic waters along the coasts where the NIR-red band ratio algorithm helps to fill the gap. Finally, a test was performed on an OLCI-S3A image. Although some validations of water reflectance are still needed for the OLCI sensors, results show similar behavior to the MERIS applications which suggests that when applied to OLCI data the present methodology will help to accurately estimate Chl-a in coastal waters for the next decade.
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Sand and Sustainability: 10 strategic recommendations to avert a crisis. GRID-Geneva, United Nations Environment Programme
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RBINS Staff Publications 2022 OA
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Tremadocian and Floian (Ordovician) linguliformean brachiopods from the Stavelot–Venn Massif (Avalonia; Belgium and Germany)
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RBINS Staff Publications 2022
