NIVA Open Access Archive
Not a member yet
8416 research outputs found
Sort by
Tiltaksrettet overvåking av Glomma ved Borregaard 2022
Get PDFProsjektleder: Maia Røst KileRapporten presenterer resultater fra undersøkelser av heterotrof begroing og fisk i Glomma ved Borregaard i 2022. Hensikten har vært å vurdere effekter av bedriftens utslipp på økologiske forhold i vassdraget, identifisere mulige tidstrender og undersøke rekruttering av laks. Prøver av heterotrof begroing antyder at bedriftens utslipp påvirker nedre Glomma, men da klassifiseringen ikke kunne utføres iht. veilederen, vurderes 2022-resultatene som usikre. Trenden fra tidligere år, der tilstanden er god oppstrøms Borregaards utslipp og hovedsakelig dårlig nedstrøms Borregaards utslipp, gjenspeiles likevel i årets resultater. Det ble fanget færre laks under el-fisket i 2022 enn i 2021. Estimerte tettheter var hhv. 17 og 23 ungfisk av laks pr. 100 m2 på nedre og øvre grusøre. Tettheten ved nedre grusøre var blant de høyeste observert i perioden 2013-2022, mens tettheten ved øvre grusøre var under medianen for perioden. Undersøkelse av fargemerking i et utvalg individer viste overtall av villfisk i 2022. Vi anbefaler å opprettholde overvåkingen på alle stasjonene i Glomma ved Borregaard, også på stasjonene lengst nede i vassdraget, for å få et mer presist bilde av vassdragets selvrensingsevne på den aktuelle strekningen.Borregaard AS, SarpsborgpublishedVersio
Plastid DNA sequences and oospore characters of some European taxa of Tolypella section Tolypella (Characeae) identify five clusters, including one new cryptic Tolypella taxon from Sardinia, but they do not coincide with current morphological descriptions
Get PDFIn Europe, the genus Tolypella (Characeae) comprises four to eight Tolypella taxa in sections Rothia and Tolypella that have been distinguished by vegetative morphology and gametangial characters such as antheridial size and oospore wall ornamentation. However, morphological differentiation is difficult in some cases due to overlapping and variable vegetative features, which in many cases are difficult to observe clearly. To clarify the taxonomic status of the five European taxa of Tolypella in section Tolypella, sequence data of the plastid genes atpB, rbcL and psbC for Tolypella glomerata (Desv.) Leonh., Tolypella hispanica Allen, Tolypella nidifica (O.F. Müll.) A. Braun, Tolypella normaniana (Nordst.) Nordst. and Tolypella salina Cor. were combined with data on oospore morphology, including oospore wall ornamentation. Gene sequence data identified five distinct clusters, but they were not consistent with the morphologically identified five taxa. T. glomerata consisted of some of the samples morphologically identified as T. glomerata and seven samples of T. normaniana, while the remaining T. glomerata samples clustered with specimens of unclear affiliation (Tolypella sp.). We identified two clusters of T. hispanica within the European material: cluster T. hispanica I consisted of samples from various locations, whereas the second cluster (T. hispanica II) consisted of samples of T. hispanica from Sardinia Island. The remaining cluster consisted of all the specimens that had been determined as T. salina or T. nidifica in addition to two specimens of T. normaniana. Oospore morphology was most clearly distinguishable for T. glomerata. Oospore characteristics for all other taxa were not as informative but showed some geographical and/or environmentally influenced differences, especially for T. nidifica and T. salina. Our results suggest the need to further check the different taxonomy of Tolypella sect. Tolypella in which specimens normally identified as T. glomerata might be two different taxa, T. glomerata and an unidentified taxon; T. nidifica and T. salina are not separate taxa; T. normaniana is a diminutive variant of two different Tolypella taxa; and T. hispanica comprises two different taxa, one from the Mediterranean island Sardinia.publishedVersio
Drivers of Perceived Nuisance Growth by Aquatic Plants
Get PDFMass developments of macrophytes occur frequently worldwide and are often considered a nuisance when interfering with human activities. It is crucial to understand the drivers of this perception if we are to develop effective management strategies for ecosystems with macrophyte mass developments. Using a comprehensive survey spanning five sites with different macrophyte species in four countries (Norway, France, Germany and South Africa), we quantified the perception of macrophyte growth as a nuisance among residents and visitors, and for different recreational activities (swimming, boating, angling, appreciation of biodiversity, appreciation of landscape and birdwatching). We then used a Bayesian network approach to integrate the perception of nuisance with the consequences of plant removal. From the 1234 responses collected from the five sites, a range of 73–93% of the respondents across the sites considered macrophyte growth a nuisance at each site. Residents perceived macrophytes up to 23% more problematic than visitors. Environmental mindedness of respondents did not influence the perception of nuisance. Perceived nuisance of macrophytes was relatively similar for different recreational activities that were possible in each case study site, although we found some site-specific variation. Finally, we illustrate how Bayesian networks can be used to choose the best management option by balancing people’s perception of macrophyte growth with the potential consequences of macrophyte removal.publishedVersio
Comparison of piecewise structural equation modeling and Bayesian network for de novo construction of a quantitative adverse outcome pathway network
Get PDFQuantitative adverse outcome pathway network (qAOPN) is gaining momentum due to the predictive nature, alignment with quantitative risk assessment and great potential as a computational new approach methodology (NAM) to reduce laboratory animal tests. The present work aimed to demonstrate two advanced modeling approaches, piecewise structural equation modeling (PSEM) and Bayesian network (BN), for de novo qAOPN model construction based on routine ecotoxicological data. A previously published AOP network comprised of four linear AOPs linking excessive reactive oxygen species production to mortality in aquatic organisms was employed as a case study. The demonstrative case study intended to answer: Which linear AOP in the network contributed the most to the AO? Can any of the upstream KEs accurately predict the AO? What are the advantages and limitations of PSEM or BN in qAOPN development? The outcomes from the two approaches showed that both PSEM and Bayesian network were suitable for constructing a complex qAOPN based on limited experimental data. Besides quantification of response-response relationships, both approaches were capable of identifying the most influencing linear AOP in a complex network and evaluating the predictive ability of the AOP, albeit some discrepancies in predictive ability were identified for the two approaches using this specific dataset. The PROs and CONs of the two approaches for qAOPN construction were discussed in detail and suggestions on optimal workflows of PSEM and BN were provided to guide future qAOPN development.publishedVersio
Land-use change in a Nordic future towards bioeconomy: A methodological framework to compare and merge stakeholder and expert opinions on qualitative scenarios
Get PDFFuture development of bioeconomy is expected to change land use in the Nordic countries in agriculture and forestry. The changes are likely to affect water quality due to changes in nutrient run-off. To explore possible future land-use changes and their environmental impact, stakeholders and experts from four Nordic countries (Denmark, Finland, Norway and Sweden) were consulted. The methodological framework for the consultation was to identify a set of relevant land-use attributes for agriculture and forestry, e.g. tillage conservation effort, fertiliser use, animal husbandry, biogas production from manure, forestry management options, and implementation of mitigation measures, including protection of sensitive areas. The stakeholders and experts provided their opinions on how these attributes might change in terms of their environmental impacts on water quality given five Nordic bioeconomic scenarios (sustainability, business as usual, self-sufficiency, cities first and maximizing economic growth). A compilation methodology was developed to allow comparing and merging the stakeholder and expert opinions for each attribute and scenario. The compiled opinions for agriculture and forestry suggest that the business-as-usual scenario may slightly decrease the current environmental impact for most attributes due to new technologies, but that the sustainability scenario would be the only option to achieve a clear environmental improvement. In contrast, for the self-sufficiency scenario, as well as the maximum growth scenario, a deterioration of the environment and water quality was expected for most of the attributes. The results from the stakeholder consultations are used as inputs to models for estimating the impact of the land-use attributes and scenarios on nutrient run-off from catchments in the Nordic countries (as reported in other papers in this special issue). Furthermore, these results will facilitate policy level discussions concerning how to facilitate the shift to bioeconomy with increasing biomass exploitation without deteriorating water quality and ecological status in Nordic rivers and lakes.publishedVersio
Study of various machine learning approaches for Sentinel-2 derived bathymetry
Get PDFIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it became possible to develop bathymetry estimation algorithms that can predict seabed depth and utilize them systematically. Since there are a number of theoretical approaches, physical models, and empirical techniques to use satellite observations in order to estimate depth in the coastal zone, the presented article compares the performance and precision of the most common one to modern machine learning algorithms. More specifically, the models based on shallow neural networks, decision trees and Random Forest algorithms have been proposed, investigated and confronted with the performance of pure analytical models. The particular proposed machine learning models differ also in a set of satellite data bands used as an input as well as in applying or not geographical weighting in the learning process. The obtained results point towards the best performance of the regression tree algorithm that incorporated as inputs information about data localization, raw reflectance data from four satellite data bands and a quotient of logarithms of B2 and B3 bands. The study for the paper was performed in relatively optically difficult and spatially variant conditions of the south Baltic coastline starting at Szczecin, Poland on the west (53°26’17’’ N, 14°32’32’’ E) to Hel peninsula (54°43’04,3774’’ N 18°37’56,9175’’ E). The reference bathymetry data was acquired from Polish Marine Administration. It was obtained through profile probing with single-beam sonar or direct in-situ probing.publishedVersio
Monitoring of environmental contaminants in freshwater food webs (MILFERSK) 2022
Get PDFProsjektleder: Morten JartunSamples of a benthic food chain in Lake Mjøsa have been collected, and the concentrations of emerging contaminants such as Siloxanes, PFAS, UV-compounds, Quaternary Ammonium Compounds, Musks, Benzothiazoles and Chlorinated paraffins in addition to legacy contaminants such as Mercury, other Metals and PBDEs have been determined. For comparison, samples of the top predator brown trout have been collected and analysed from Lake Femunden, a rural counterpart to the more urban Lake Mjøsa.MiljødirektoratetpublishedVersio
Passive-Sampler-Derived PCB and OCP Concentrations in the Waters of the World─First Results from the AQUA-GAPS/MONET Network
No full textPersistent organic pollutants (POPs) are recognized as pollutants of global concern, but so far, information on the trends of legacy POPs in the waters of the world has been missing due to logistical, analytical, and financial reasons. Passive samplers have emerged as an attractive alternative to active water sampling methods as they accumulate POPs, represent time-weighted average concentrations, and can easily be shipped and deployed. As part of the AQUA-GAPS/MONET, passive samplers were deployed at 40 globally distributed sites between 2016 and 2020, for a total of 21 freshwater and 40 marine deployments. Results from silicone passive samplers showed α-hexachlorocyclohexane (HCH) and γ-HCH displaying the greatest concentrations in the northern latitudes/Arctic Ocean, in stark contrast to the more persistent penta (PeCB)- and hexachlorobenzene (HCB), which approached equilibrium across sampling sites. Geospatial patterns of polychlorinated biphenyl (PCB) aqueous concentrations closely matched original estimates of production and use, implying limited global transport. Positive correlations between log-transformed concentrations of Σ7PCB, ΣDDTs, Σendosulfan, and Σchlordane, but not ΣHCH, and the log of population density (p < 0.05) within 5 and 10 km of the sampling sites also supported limited transport from used sites. These results help to understand the extent of global distribution, and eventually time-trends, of organic pollutants in aquatic systems, such as across freshwaters and oceans. Future deployments will aim to establish time-trends at selected sites while adding to the geographical coverage.acceptedVersio
The impact of rainfall events on dissolved oxygen concentrations in a subtropical urban reservoir
Get PDFUnderstanding controls of dissolved oxygen (DO) concentrations in reservoirs is important as they are important for fisheries and a significant driver of greenhouse gas emissions. The latter is of global significance as IPCC inventories now require greenhouse gas emissions from artificial reservoirs to be included. Declines in dissolved oxygen (DO) concentrations in lakes and reservoirs have been linked to climate change and human activity. However, these effects can vary widely in any given region under various meteorological conditions. There is a clear need to know how changes in weather patterns affect DO in reservoirs by changing internal processes. Based on a six-year (2016–2021) high-frequency (twice a week) dataset from a shallow urban reservoir (Xinglinwan Reservoir) in subtropical China, the long-term (six years) and short-term (8–72-h) drivers of DO concentrations in surface waters were evaluated. Over the past six years, the concentration of DO has gradually decreased in the reservoir from 2016 to 2021. Multivariate adaptive regression spline (MARS) models were developed to identify the key factors explaining variability in DO and partial least squares path models (PLS-PM) were used to explore the short-term relationships between DO and environmental variables in rainy and dry (non-rain) periods, separately. We identified three key drivers operating on different time scales. First, the long-term decline of DO in Xinglinwan Reservoir from 2016 to 2021 was best explained by anthropogenic nutrient inputs. Second, rainy periods prior to sampling reduced DO concentrations indirectly by affecting the algal biomass and nutrient concentrations. This effect varied in complexity with the duration of the rainfall period. Third, water temperature best explained DO concentrations during dry periods, while wind reduced DO by reducing algal biomass. We conclude that anthropogenic nutrient and organic matter inputs drive long-term oxygen declines in urban subtropical reservoirs, while meteorological factors determine short-term variability in DO concentrations.acceptedVersio
Deepwater dissolved oxygen shows little ecological memory between lake phenological seasons
Get PDFDepletion of deepwater dissolved oxygen (DO) in lakes has become increasingly prevalent and severe because of many external stressors, potentially threatening human-derived ecosystem services ranging from drinking water quality to fisheries. Using year-round, high-frequency DO data from 12 dimictic lakes, we compared 3 measures of deepwater DO depletion during winter and summer: DO depletion rate, DO minimum, and hypoxia duration. Hypoxia (DO 65%) regardless of the previous summer’s DO depletion severity. This lack of ecological memory in deepwater DO depletion across seasons suggests that deepwater DO largely resets during spring and fall mixing periods in most years in these dimictic lakes. Understanding the patterns and drivers in deepwater DO depletion in both winter and summer is a key step forward for predicting future chemical and biological consequences of seasonal DO depletion and managing lake ecosystem health, as well as the effects that climate change may have on these patterns.acceptedVersio