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  • 1
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    People need freshwater biodiversity (2023)
    John Wiley & Sons, Inc. | Hoboken, USA
    Details
    Publication Date: 2023-07-21
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Freshwater biodiversity, from fish to frogs and microbes to macrophytes, provides a vast array of services to people. Mounting concerns focus on the accelerating pace of biodiversity loss and declining ecological function within freshwater ecosystems that continue to threaten these natural benefits. Here, we catalog nine fundamental ecosystem services that the biotic components of indigenous freshwater biodiversity provide to people, organized into three categories: material (food; health and genetic resources; material goods), non‐material (culture; education and science; recreation), and regulating (catchment integrity; climate regulation; water purification and nutrient cycling). If freshwater biodiversity is protected, conserved, and restored in an integrated manner, as well as more broadly appreciated by humanity, it will continue to contribute to human well‐being and our sustainable future via this wide range of services and associated nature‐based solutions to our sustainable future.〈/p〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉
    Description: María de Maeztu excellence accreditation 2018‐2022
    Description: Ministerio de Ciencia e Innovación (MCIN) http://dx.doi.org/10.13039/501100004837
    Description: Leibniz Competition: Freshwater Megafauna Futures
    Description: CGIAR Initiative on NEXUS Gains
    Keywords: ddc:333.9 ; ecosystem services ; freshwater biodiversity ; freshwater ecosystems ; freshwater life
    Language: English
    Type: doc-type:article
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    CITATION GEO-LEO
  • 2
    Electronic Resource
    Electronic Resource
    A comparison of statistical approaches for modelling fish species distributions (2002)
    Oxford, UK : Blackwell Science Ltd
    Freshwater biology 47 (2002), S. 0 
    Details
    ISSN: 1365-2427
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology
    Notes: SUMMARY 1. The prediction of species distributions is of primary importance in ecology and conservation biology. Statistical models play an important role in this regard; however, researchers have little guidance when choosing between competing methodologies because few comparative studies have been conducted.2. We provide a comprehensive comparison of traditional and alternative techniques for predicting species distributions using logistic regression analysis, linear discriminant analysis, classification trees and artificial neural networks to model: (1) the presence/absence of 27 fish species as a function of habitat conditions in 286 temperate lakes located in south-central Ontario, Canada and (2) simulated data sets exhibiting deterministic, linear and non-linear species response curves.3. Detailed evaluation of model predictive power showed that approaches produced species models that differed in overall correct classification, specificity (i.e. ability to correctly predict species absence) and sensitivity (i.e. ability to correctly predict speciespresence) and in terms of which of the study lakes they correctly classified. Onaverage, neural networks outperformed the other modelling approaches, although all approaches predicted species presence/absence with moderate to excellent success.4. Based on simulated non-linear data, classification trees and neural networks greatly outperformed traditional approaches, whereas all approaches exhibited similar correct classification rates when modelling simulated linear data.5. Detailed evaluation of model explanatory insight showed that the relative importance of the habitat variables in the species models varied among the approaches, where habitat variable importance was similar among approaches for some species and very different for others.6. In general, differences in predictive power (both correct classification rate and identity of the lakes correctly classified) among the approaches corresponded with differences in habitat variable importance, suggesting that non-linear modelling approaches (i.e. classification trees and neural networks) are better able to capture and model complex, non-linear patterns found in ecological data. The results from the comparisons using simulated data further support this notion.7. By employing parallel modelling approaches with the same set of data and focusing on comparing multiple metrics of predictive performance, researchers can begin to choose predictive models that not only provide the greatest predictive power, but also best fit the proposed application.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1046/j.1365-2427.2002.00945.x
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    Paper (German National Licenses)
    Fulltext
  • 3
    Electronic Resource
    Electronic Resource
    An artificial neural network approach for studying phytoplankton succession (2000)
    Springer
    Hydrobiologia 436 (2000), S. 131-143 
    Details
    ISSN: 1573-5117
    Keywords: bottom-up ; top-down ; trophic ; zooplankton ; randomization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract Artificial neural networks are used to model phytoplankton succession and gain insight into the relative strengths of bottom-up and top-down forces shaping seasonal patterns in phytoplankton biomass and community composition. Model comparisons indicate that patterns in chlorophyll aconcentrations response instantaneously to patterns in nutrient concentrations (phosphorous (P), nitrite and nitrate (NO2/NO3–N) and ammonium (NH4–H) concentrations) and zooplankton biomass (daphnid cladocera and copepoda biomass); whereas lagged responses in an index of algal community composition are evident. A randomization approach to neural networks is employed to reveal individual and interacting contributions of nutrient concentrations and zooplankton biomass to predictions of phytoplankton biomass and community composition. The results show that patterns in chlorophyll aconcentrations are directly associated with P, NO2/NO3–N and daphnid cladocera biomass, as well as related to interactions between daphnid cladocera biomass, and NO2/NO3–N and P. Similarly, patterns in phytoplankton community composition are associated with NO2/NO3–N and daphnid cladocera biomass; however show contrasting patterns in nutrient– zooplankton and zooplankton–zooplankton interactions. Together, the results provide correlative evidence for the importance of nutrient limitation, zooplankton grazing and nutrient regeneration in shaping phytoplankton community dynamics. This study shows that artificial neural networks can provide a powerful tool for studying phytoplankton succession by aiding in the quantification and interpretation of the individual and interacting contributions of nutrient limitation and zooplankton herbivory on phytoplankton biomass and community composition under natural conditions.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1026575418649
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    Paper (German National Licenses)
    Fulltext
  • 4
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    Arsenic speciation in aquatic organisms collected from south-central Puget Sound urban lakes in 2018 and 2019 (2021)
    PANGAEA
    Details
    Publication Date: 2023-10-28
    Description: Between 2 and 6 littoral sediment samples were collected in 2018 and 2019 from nearshore (1-2 m depth) in each lake using a dredge (Wildco Petite Ponar Stainless Steel Grab) and dried at 60 °C overnight and homogenized using a porcelain mortar and pestle. Oven-dried sediment samples were digested using a microwave-assisted (CEM MARS 5) total digestion protocol (modified EPA method 3015a). Concentrations of total arsenic in digested sediment samples were determined by inductively-coupled plasma mass spectrometry (ICP-MS) on an Agilent 7900 at the University of Washington Tacoma.
    Keywords: (Trimethylarsaniumyl)acetate, per dry mass, tissue; 2-Hydroxyethyl-trimethylarsonium, per dry mass, tissue; Arsenate, per dry mass, tissue; arsenic; Arsenite, per dry mass, tissue; crayfish; DATE/TIME; Dimethylarsinic acid, per dry mass, tissue; Event label; fish; ICP-MS Agilent 7900; Inductively coupled plasma mass spectrometer (Agilent 7900); Lake_Killarney; LATITUDE; littoral sediment; LONGITUDE; Methylarsonic acid, per dry mass, tissue; MULT; Multiple investigations; Registration number of species; snail; Species; Steel_Lake; Sum; Tissue, sampling; Uniform resource locator/link to reference; United States; water column
    Type: Dataset
    Format: text/tab-separated-values, 176 data points
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    DATA PANGAEA
  • 5
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    Dissolved oxygen and arsenic concentrations in the water column of south-central Puget Sound urban lakes from June 2019 (2021)
    PANGAEA
    Details
    Publication Date: 2023-10-28
    Description: Dissolved oxygen measurements and water samples for dissolved arsenic were taken from a boat at approximately the deepest point in each lake in June 2019. Dissolved oxygen was measured every half meter using an In-Situ smarTROLL MP equipped with an optical Rugged Dissolved Oxygen (RDO) sensor. Water samples were collected using a peristaltic pump, filtered (0.45 µm Geotech cartridge filter), and then acidified with 1% HNO3 (v/v) in the laboratory. Concentrations of total arsenic in water samples were determined by inductively-coupled plasma mass spectrometry (ICP-MS) on an Agilent 7900 at the University of Washington Tacoma.
    Keywords: Angle_Lake; arsenic; Arsenic, dissolved; Bonney_Lake; crayfish; DATE/TIME; DEPTH, water; Event label; fish; ICP-MS Agilent 7900; Inductively coupled plasma mass spectrometer (Agilent 7900); Lake_Killarney; LATITUDE; littoral sediment; LONGITUDE; MULT; Multi-parameter water quality probe (In-Situ smarTROLL MP); Multiple investigations; Oxygen, dissolved; snail; Steel_Lake; United States; water column
    Type: Dataset
    Format: text/tab-separated-values, 40 data points
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    DATA PANGAEA
  • 6
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    Total arsenic in littoral sediments in south-central Puget Sound urban lakes from 2018 and 2019 (2021)
    PANGAEA
    Details
    Publication Date: 2023-10-28
    Description: Between 2 and 6 littoral sediment samples were collected in 2018 and 2019 from nearshore (1-2 m depth) in each lake using a dredge (Wildco Petite Ponar Stainless Steel Grab) and dried at 60 °C overnight and homogenized using a porcelain mortar and pestle. Oven-dried sediment samples were digested using a microwave-assisted (CEM MARS 5) total digestion protocol (modified EPA method 3015a). Concentrations of total arsenic in digested sediment samples were determined by inductively-coupled plasma mass spectrometry (ICP-MS) on an Agilent 7900 at the University of Washington Tacoma.
    Keywords: Angle_Lake; arsenic; Arsenic, total, per sediment dry mass; Bonney_Lake; crayfish; DATE/TIME; Event label; fish; ICP-MS Agilent 7900; Inductively coupled plasma mass spectrometer (Agilent 7900); Lake_Killarney; LATITUDE; littoral sediment; LONGITUDE; MULT; Multiple investigations; Pine_Lake; snail; Steel_Lake; United States; water column
    Type: Dataset
    Format: text/tab-separated-values, 19 data points
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    DATA PANGAEA
  • 7
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    Total arsenic in aquatic organisms collected from south-central Puget Sound urban lakes between 2004 and 2019 (2021)
    PANGAEA
    Details
    Publication Date: 2023-10-28
    Description: Snail (Bellamya chinensis), crayfish (Pacifastacus leniusculus; Procambarus clarkii), and sunfish (Lepomis gibbosus; L. macrochirus) sampling occurred primarily over four dates in June 2019 in the entire nearshore (〈 2 m depth) area of each lake. Additional frozen crayfish samples from Killarney, Steel, and Pine Lakes collected in 2004, 2009, 2017, and 2018 were also analyzed. All crayfish were captured using minnow traps set overnight and baited with dog kibble. Snails were collected by hand via snorkeling or with a dip net from a boat. Sunfish were collected using beach seining. Snails, crayfish, and fish were euthanized and dissected for edible tissues (whole snail, excluding shell, crayfish tail meat, and fish muscle tissue (fillet)). Duplicate portions of each edible tissue of snail, crayfish, or fish specimen were dried at 60 °C overnight. Dried samples were homogenized using a porcelain mortar and pestle. Oven-dried animal tissues were digested using a microwave-assisted (CEM MARS 5) total digestion protocol (modified EPA method 3015a). Concentrations of total arsenic in digested animal tissue samples were determined by inductively-coupled plasma mass spectrometry (ICP-MS) on an Agilent 7900 at the University of Washington Tacoma.
    Keywords: Angle_Lake; arsenic; Arsenic, total, per dry mass, tissue; Bonney_Lake; crayfish; DATE/TIME; Event label; fish; ICP-MS Agilent 7900; Inductively coupled plasma mass spectrometer (Agilent 7900); Lake_Killarney; LATITUDE; littoral sediment; LONGITUDE; MULT; Multiple investigations; Pine_Lake; Registration number of species; snail; Species; Steel_Lake; Tissue, sampling; Uniform resource locator/link to reference; United States; water column
    Type: Dataset
    Format: text/tab-separated-values, 525 data points
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    DATA PANGAEA
  • 8
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    Opinion: Lay summaries needed to enhance science communication (2015)
    National Academy of Sciences
    Details
    Publication Date: 2015-03-24
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
    Published by National Academy of Sciences
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    PAPER CURRENT
  • 9
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    Integrated assessment of biological invasions (2014)
    Wiley
    Details
    Publication Date: 2014-01-01
    Description: As the main witnesses of the ecological and economic impacts of invasions on ecosystems around the world, ecologists seek to provide the relevant science that informs managers about the potential for invasion of specific organisms in their region(s) of interest. Yet, the assorted literature that could inform such forecasts is rarely integrated to do so, and further, the diverse nature of the data available complicates synthesis and quantitative prediction. Here we present a set of analytical tools for synthesizing different levels of distributional and/or demographic data to produce meaningful assessments of invasion potential that can guide management at multiple phases of ongoing invasions, from dispersal to colonization to proliferation. We illustrate the utility of data-synthesis and data-model assimilation approaches with case studies of three well-known invasive species?a vine, a marine mussel, and a freshwater crayfish?under current and projected future climatic conditions. Results from the integrated assessments reflect the complexity of the invasion process and show that the most relevant climatic variables can have contrasting effects or operate at different intensities across habitat types. As a consequence, for two of the study species climate trends will increase the likelihood of invasion in some habitats and decrease it in others. Our results identified and quantified both bottlenecks and windows of opportunity for invasion, mainly related to the role of human uses of the landscape or to disruption of the flow of resources. The approach we describe has a high potential to enhance model realism, explanatory insight, and predictive capability, generating information that can inform management decisions and optimize phase-specific prevention and control efforts for a wide range of biological invasions. # doi:10.1890/13-0776.1
    Print ISSN: 1051-0761
    Electronic ISSN: 1939-5582
    Topics: Biology
    Published by Wiley on behalf of The Ecological Society of America (ESA).
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    PAPER CURRENT
  • 10
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    The interactive effects of climate change, riparian management, and a nonnative predator on stream-rearing salmon (2014)
    Wiley
    Details
    Publication Date: 2014-06-01
    Description: Predicting how climate change is likely to interact with myriad other stressors that threaten species of conservation concern is an essential challenge in aquatic ecosystems. This study provides a framework to accomplish this task in salmon-bearing streams of the northwestern United States, where land-use-related reductions in riparian shading have caused changes in stream thermal regimes, and additional warming from projected climate change may result in significant losses of coldwater fish habitat over the next century. Predatory, nonnative smallmouth bass have also been introduced into many northwestern streams, and their range is likely to expand as streams warm, presenting an additional challenge to the persistence of threatened Pacific salmon. The goal of this work was to forecast the interactive effects of climate change, riparian management, and nonnative species on stream-rearing salmon and to evaluate the capacity of restoration to mitigate these effects. We intersected downscaled global climate forecasts with a local-scale water temperature model to predict mid- and end-of-century temperatures in streams in the Columbia River basin. We compared one stream that is thermally impaired due to the loss of riparian vegetation and another that is cooler and has a largely intact riparian corridor. Using the forecasted stream temperatures in conjunction with fish?habitat models, we predicted how stream-rearing chinook salmon and bass distributions would change as each stream warmed. In the highly modified stream, end-of-century warming may cause near total loss of chinook salmon-rearing habitat and a complete invasion of the upper watershed by bass. In the less modified stream, bass were thermally restricted from the upstream-most areas. In both systems, temperature increases resulted in higher predicted spatial overlap between stream-rearing chinook salmon and potentially predatory bass in the early summer (two- to fourfold increase) and greater abundance of bass. We found that riparian restoration could prevent the extirpation of chinook salmon from the more altered stream and could also restrict bass from occupying the upper 31 km of salmon-rearing habitat. The proposed methodology and model predictions are critical for prioritizing climate-change adaptation strategies before salmonids are exposed to both warmer water and greater predation risk by nonnative species. # doi:10.1890/13-0753.1
    Print ISSN: 1051-0761
    Electronic ISSN: 1939-5582
    Topics: Biology
    Published by Wiley on behalf of The Ecological Society of America (ESA).
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    PAPER CURRENT
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