FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2886291230> ?p ?o ?g. }

• W2886291230 endingPage "28898" @default.
• W2886291230 startingPage "28884" @default.
• W2886291230 abstract "To minimize the risk of negative consequences for public health from fecal pollution in lakes, the continuous surveillance of microbiological water quality parameters, alongside other environmental variables, is necessary at defined bathing sites. Such routine surveillance may prove insufficient to elucidate the main drivers of fecal pollution in a complex lake/watershed ecosystem, and it may be that more comprehensive monitoring activities are required. In this study, the aims were to identify the hotspots and main driving factors of fecal pollution in a large shallow Central European lake, the Neusiedler See, and to determine to what degree its current monitoring network can be considered representative spatially. A stochastic and geostatistical analysis of a huge data set of water quality data (~ 164,000 data points, representing a 22-year time-series) of standard fecal indicator bacteria (SFIB), water quality and meteorological variables sampled at 26 sampling sites was conducted. It revealed that the hotspots of fecal pollution are exclusively related to sites with elevated anthropogenic activity. Background pollution from wildlife or diffuse agricultural run-off at more remote sites was comparatively low. The analysis also showed that variability in the incidence of SFIB was driven mainly by meteorological phenomena, above all, temperature, number of sunny hours, and wind (direction and speed). Due to antagonistic effects and temporal undersampling, the influence of precipitation on SFIB variance could not be clearly determined. Geostatistical analysis did reveal that the current spatial sampling density is insufficient to cover SFIB variance over the whole lake, and that the sites are therefore in the most part representative of local phenomena. Suggestions for the future monitoring and managing of fecal pollution are offered. The applied statistical approach may also serve as a model for the study of other such areas, and in general indicate a method for dealing with similarly large and spatiotemporally heterogeneous datasets." @default.
• W2886291230 created "2018-08-22" @default.
• W2886291230 creator A5009976196 @default.
• W2886291230 creator A5030797817 @default.
• W2886291230 creator A5036381762 @default.
• W2886291230 creator A5048669599 @default.
• W2886291230 creator A5084320840 @default.
• W2886291230 date "2018-08-13" @default.
• W2886291230 modified "2023-10-16" @default.
• W2886291230 title "Hotspots and main drivers of fecal pollution in Neusiedler See, a large shallow lake in Central Europe" @default.
• W2886291230 cites W1495083471 @default.
• W2886291230 cites W1523030418 @default.
• W2886291230 cites W1531260672 @default.
• W2886291230 cites W1593051139 @default.
• W2886291230 cites W171723222 @default.
• W2886291230 cites W1963699226 @default.
• W2886291230 cites W1967732626 @default.
• W2886291230 cites W1969685288 @default.
• W2886291230 cites W1970519114 @default.
• W2886291230 cites W1985412822 @default.
• W2886291230 cites W1991155975 @default.
• W2886291230 cites W2008851722 @default.
• W2886291230 cites W2029278208 @default.
• W2886291230 cites W2034993426 @default.
• W2886291230 cites W2038416133 @default.
• W2886291230 cites W2041059001 @default.
• W2886291230 cites W2049825510 @default.
• W2886291230 cites W2050060085 @default.
• W2886291230 cites W2056652524 @default.
• W2886291230 cites W2063143100 @default.
• W2886291230 cites W2063246330 @default.
• W2886291230 cites W2065922432 @default.
• W2886291230 cites W2068400017 @default.
• W2886291230 cites W2074984119 @default.
• W2886291230 cites W2076449034 @default.
• W2886291230 cites W2081276335 @default.
• W2886291230 cites W2087350522 @default.
• W2886291230 cites W2087412483 @default.
• W2886291230 cites W2089580597 @default.
• W2886291230 cites W2133097426 @default.
• W2886291230 cites W2140017879 @default.
• W2886291230 cites W2160172778 @default.
• W2886291230 cites W2167040687 @default.
• W2886291230 cites W2199882078 @default.
• W2886291230 cites W2314798513 @default.
• W2886291230 cites W2474084290 @default.
• W2886291230 cites W2497973605 @default.
• W2886291230 cites W2512351845 @default.
• W2886291230 cites W2606713276 @default.
• W2886291230 cites W2738913988 @default.
• W2886291230 cites W2768172135 @default.
• W2886291230 cites W4229562638 @default.
• W2886291230 cites W4232329630 @default.
• W2886291230 cites W4252395563 @default.
• W2886291230 doi "https://doi.org/10.1007/s11356-018-2783-7" @default.
• W2886291230 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6153677" @default.
• W2886291230 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30105673" @default.
• W2886291230 hasPublicationYear "2018" @default.
• W2886291230 type Work @default.
• W2886291230 sameAs 2886291230 @default.
• W2886291230 citedByCount "17" @default.
• W2886291230 countsByYear W28862912302019 @default.
• W2886291230 countsByYear W28862912302020 @default.
• W2886291230 countsByYear W28862912302021 @default.
• W2886291230 countsByYear W28862912302022 @default.
• W2886291230 countsByYear W28862912302023 @default.
• W2886291230 crossrefType "journal-article" @default.
• W2886291230 hasAuthorship W2886291230A5009976196 @default.
• W2886291230 hasAuthorship W2886291230A5030797817 @default.
• W2886291230 hasAuthorship W2886291230A5036381762 @default.
• W2886291230 hasAuthorship W2886291230A5048669599 @default.
• W2886291230 hasAuthorship W2886291230A5084320840 @default.
• W2886291230 hasBestOaLocation W28862912302 @default.
• W2886291230 hasConcept C105795698 @default.
• W2886291230 hasConcept C106131492 @default.
• W2886291230 hasConcept C119857082 @default.
• W2886291230 hasConcept C124956284 @default.
• W2886291230 hasConcept C127413603 @default.
• W2886291230 hasConcept C140779682 @default.
• W2886291230 hasConcept C150547873 @default.
• W2886291230 hasConcept C187320778 @default.
• W2886291230 hasConcept C18903297 @default.
• W2886291230 hasConcept C2780797713 @default.
• W2886291230 hasConcept C31972630 @default.
• W2886291230 hasConcept C33923547 @default.
• W2886291230 hasConcept C39432304 @default.
• W2886291230 hasConcept C41008148 @default.
• W2886291230 hasConcept C521259446 @default.
• W2886291230 hasConcept C76886044 @default.
• W2886291230 hasConcept C81692654 @default.
• W2886291230 hasConcept C86803240 @default.
• W2886291230 hasConcept C94747663 @default.
• W2886291230 hasConceptScore W2886291230C105795698 @default.
• W2886291230 hasConceptScore W2886291230C106131492 @default.
• W2886291230 hasConceptScore W2886291230C119857082 @default.
• W2886291230 hasConceptScore W2886291230C124956284 @default.
• W2886291230 hasConceptScore W2886291230C127413603 @default.
• W2886291230 hasConceptScore W2886291230C140779682 @default.

• next