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Understanding and quantifying ES flows is essential for the sustainable management of social-ecological systems, as it directly captures the human-nature interactions within the system and not solely its individual elements. Especially in degrading marine systems, most ES assessments focus solely on either biophysical or socio-economic elements of these social-ecological systems, failing to directly capture the human-nature interactions. This systematic literature review aims to capture the state of the art of ES flow studies to improve the knowledge base on marine ES flows while highlighting knowledge gaps and discussing future research pathways. Within the review we extract information on: i) the ES flow definitions, classification systems, and indicators; ii) the scales of assessment and methods used to assess marine ES flows; and iii) the types of assessment outputs. 82% of the reviewed ES flow assessment methods were spatially explicit. 63% of the studies assess marine ES flows locally. Across-scale ES flows are rarely taken into account. We detect a broad range of conceptualizations within marine ES flow literature. We thus propose an updated definition for ES flows in which they are defined as a spectrum within the social-ecological system, within which different ES flow indicators are placed depending on the relative contributions of biophysical or socio-economic attributes. Based on the extracted information and detected literature gaps, we propose a set of four criteria that should be the minimum required information when referring to ES flows: i) the relative contributions of biophysical and socio-economic attributes present in ES flow indicators; ii) identification of the supplying and receiving systems; iii) the direction and branches of flows; and iv) the spatial and temporal scales across which ES flows occur.

On behalf of the Ministry of Agriculture, Nature and Food Quality (LNV), Wageningen Food Safety Research (WFSR) analyses samples of agricultural products of animal origin for dioxins, PCBs, brominated flame retardants (BFRs) and poly- and perfluorinated alkyl substances (PFASs). This includes meat, milk, eggs and fish. The samples are taken at the primary production or processing stage (e.g. in slaughterhouses or raw milk collection services). For dioxin-like compounds, 350 samples are screened first with the DR CALUX® method. Samples giving a signal indicating a level above the lowest action level are regarded as suspected. These samples are further examined using GC/HRMS as confirmatory method. Concerning fish, shellfish and crustaceans, approx. 25 samples are collected at sea by research vessels, at the fish auction, or from whole-sale traders (farmed fish).

Simple Summary In human papillomavirus (HPV) associated head and neck squamous cell carcinomas (HNSCC) s, the HPV genome is commonly found integrated in the human genome. The event of viral-human genome integration may act as a driver of carcinogenesis. Hence, it is vital to assess the viral integration status of a tumor. In this review, current and emerging techniques for integration detection are thoroughly discussed with their advantages and disadvantages. Additionally, the review also discusses the causes of HPV integration into the cellular genome, as well as its ramifications, impacting possible clinical implications. A constantly increasing incidence in high-risk Human Papillomaviruses (HPV)s driven head and neck squamous cell carcinomas (HNSCC)s, especially of oropharyngeal origin, is being observed. During persistent infections, viral DNA integration into the host genome may occur. Studies are examining if the physical status of the virus (episomal vs. integration) affects carcinogenesis and eventually has further-reaching consequences on disease progression and outcome. Here, we review the literature of the most recent five years focusing on the impact of HPV integration in HNSCCs, covering aspects of detection techniques used (from PCR up to NGS approaches), integration loci identified, and associations with genomic and clinical data. The consequences of HPV integration in the human genome, including the methylation status and deregulation of genes involved in cell signaling pathways, immune evasion, and response to therapy, are also summarized.

Several studies have suggested Indonesia to be among the top plastic polluting countries globally. Data on the presence and amounts of plastic pollution are required to help design effective plastic reduction and mitigation strategies. Research quantifying plastic pollution in Indonesia has picked up in recent years. However, a lack of central coordination in this research has led to research output with different goals, methods, and data formats. In this study we present a meta-analysis of studies published on plastic pollution in Indonesia to uncover gaps and biases in current research, and to use these insights to suggest ways to improve future research to fill these gaps. Research gaps and biases identified include a clear preference for marine research, and a bias toward certain environmental compartments within the marine, riverine, and terrestrial systems that have easy to apply methods. Units of measurement used to express results vary greatly between studies, making it difficult to compare data effectively. Nevertheless, we identify polypropylene (PP) and polyethylene variants (PE, HDPE, LDPE) to be among the most frequently found polymers in both macro- and microplastic pollution in Indonesia, though polymer identification is lacking in a large part of the studies. Plastic research is mostly done on Java (59% of the studies). We recommend research methods used to quantify plastic pollution to be harmonized. Moreover, we recommend a shift in focus of research toward the riverine and terrestrial environments and a shift of focus of environmental compartments analyzed within these systems, an increase in spatial coverage of research across Indonesia, and lastly, a larger focus on polymer characterization. With these changes we envision future research which can aid with the design of more effective and targeted reduction and mitigation strategies.

Original provider: Green Heritage Fund of Suriname Dataset credits: Monique Pool, Green Heritage Fund of Suriname Abstract: The Marine Spatial Planning (MSP) project in Suriname was initiated in 2017. Part of this EU-funded project focussed on collecting all the information regarding marine megafauna within the region (Suriname and Guyana). As part of the MSP project we searched for potential marine mammal data holders and different data-sets were found: (1) research data: published and unpublished data collected during dedicated (effort-related) marine fauna surveys (where a GPS track was available); (2) data collected by Marine Fauna Observers during geophysical seismic surveys (without an available GPS track); (3) Opportunistic data collected without keeping track of effort (e.g. website, social media and other sighting records collected by university students or citizens); and (4) Systematic land-based observations carried out during sea turtle surveys on Braamspunt. Here you can find all effort-related data regarding research data collected during boat-based surveys in Suriname. There are two types of boat-based data: (1) Small boat-based surveys by Green Heritage Fund Suriname in order to study the Guiana dolphin (Sotalia guianensis) in the Suriname River; and (2) Dedicated marine megafauna boat-based surveys at-sea carried out by M.N. de Boer and colleagues as part of a PhD study for the University of Wageningen. Purpose: The project aims to significantly enhance the governance and protection of marine and coastal resources of Guyana and Suriname through collaborative processes with all ocean stakeholders, improved knowledge of the coastal and marine environment, enhanced capacity of key stakeholders and informed marine spatial management. Upon completion of the marine Spatial planning project, we aim to continue to add new marine megafauna records to OBIS SEAMAP.

This dataset summarizes allometric measurements on zooplankton and nekton species performed in the framework of the Dutch and German ICEFLUX projects. Measurements were performed on 639 individuals of 15 species from the Southern Ocean and 2374 individuals of 14 species from the Arctic Ocean, including euphausiids, fish, pelagic and ice-associated amphipods, cnidarians, salps, siphonophores, chaetognaths and a copepod. Animals were collected during three expeditions in the Southern Ocean (winter and summer) and three expeditions in the Arctic Ocean (spring and summer). In addition to measurements on length and mass, the sizes of body parts were measured, such as carapaces, eyes, heads, telsons, tails and otoliths.

During the PhOxy cruise with R/V Pelagia in June 2013, sediments were collected with a multicorer in the eastern part of the Black Sea. The aim was to determine the geochemical siganture of sediments on the shelf and in the deep basin, and potentially track chemical changes to sediments that are transported into the sulfidic deep basin by turbidity currents. Sediment cores were cut at vertical resolution of 0.5-2.0 cm and the pore-water and solid-phase were separated by centrifugation. After filtration of the pore-water over 0.45 micrometer filter membranes, dissolved inorganic carbon (DIC), Fe, P, Mn, N (ammonium, nitrite, nitrate) and S (sulfate, sulfide) were measured in various sub-samples. After freeze drying and grinding, sub-samples of dry sediment were taken and solid-phase org-C, Al, Ca, Fe, Mn, Mo, P and S were determined by decalcification and combustion (org-C) or ICP-MS analysis of acid digest (other elements). Furthermore, various solid-phase Fe and P pools were determined using sequential chemical extraction protocols. From a second core, 10-mL wet sediment samples were taken at 5-cm resolution from a multicore with pre-drilled holes and transferred into glass vials with gas-tight, crimp-sealed rubber stoppers filled with N2-purged saturated NaCl (no headspace). Later, a N2 headspace was injected and the headspace was analyzed for CH4 by gas chromatography with a flame ionization detector (GC-FID, Thermo Finnigan).