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84 results for “Freshwater ecosystems”
Data from: Spatial, temporal, and experimental: three study design cornerstones for establishing defensible numeric criteria in freshwater ecosystems
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Data from: Bottom-up regulation of parasite population densities in freshwater ecosystems
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Data from: Sustainability management of short-lived freshwater fish in human-altered ecosystems should focus on adult survival
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Data from: Fine tuning for the tropics: application of eDNA technology for invasive fish detection in tropical freshwater ecosystems.
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Data from: Species turnover and invasion of dominant freshwater invertebrates alter biodiversity-ecosystem function relationship
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Data from: Dispersal syndromes can impact ecosystem functioning in spatially structured freshwater populations
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Data from: Damming, lost connectivity and the historical role of anadromous fish in freshwater ecosystem dynamics
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Data from: Size-based hydroacoustic measures of within-season fish abundance in a boreal freshwater ecosystem
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Data from: Application of ancient DNA to the reconstruction of past microbial assemblages and for the detection of toxic cyanobacteria in subtropical freshwater ecosystems
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Fig. 4 in A new species of freshwater flatworm (Platyhelminthes, Tricladida, Dendrocoelidae) inhabiting a chemoautotrophic groundwater ecosystem in Romania
Fig. 4. Dendrocoelum obstinatum Stocchino & Sluys, sp. nov., holotype (ZMA V.Pl. 7264.1). A. Microphotograph of the copulatory apparatus. B. Microphotograph of the anterior adhesive organ with the associated ventral muscles. C. Microphotograph of the cervix-like protrusion of the male atrium, with the opening of the common oviduct.
Figure 5 in Fauna of microcrustaceans (Cladocera: Copepoda) of shallow freshwater ecosystems of Wrangel Island (Russian Far East)
Figure 5. The percentage ratio of the species number of different crustaceans (Cladocera, Copepoda: Cyclopoida, Calanoida, Harpacticoida) from different arctic regions.
Figure 4 in Fauna of microcrustaceans (Cladocera: Copepoda) of shallow freshwater ecosystems of Wrangel Island (Russian Far East)
Figure 4. Dendrogram for hierarchical clustering (group average) of faunas of different arctic regions.
Figure 2 in Fauna of microcrustaceans (Cladocera: Copepoda) of shallow freshwater ecosystems of Wrangel Island (Russian Far East)
Figure 2. Species number of Cladocera and Copepoda in different areas along a latitude gradient following average summer temperatures, based on literature sources and original data.
Data from: Review on the effects of toxicants on freshwater ecosystem functions
We reviewed 122 peer-reviewed studies on the effects of organic toxicants and heavy metals on three fundamental ecosystem functions in freshwater ecosystems, i.e. leaf litter breakdown, primary production and community respiration. From each study meeting the inclusion criteria, the concentration resulting in a reduction of at least 20% in an ecosystem function was standardized based on median effect concentrations of standard test organisms (i.e. algae and daphnids). For pesticides, more than one third of observations indicated reductions in ecosystem functions at concentrations that are assumed being protective in regulation. Moreover, the reduction in leaf litter breakdown was more pronounced in the presence of invertebrate decomposers compared to studies where only microorganisms were involved in this function. High variability within and between studies hampered the derivation of a concentration–effect relationship. Hence, if ecosystem functions are to be included as protection goal in chemical risk assessment standardized methods are required.
Measurements in flowing freshwater ecosystems taken in Ohio (US)
<p>Knowledge of ecological responses to changes in the environment is vital to design appropriate measures for conserving biodiversity. Experimental studies are the standard to identify ecological cause-effect relationships, but their results do not necessarily translate to field situations. Deriving ecological cause-effect relationships from observational field data is, however, challenging due to potential confounding influences of unmeasured variables. Here, we present a causal discovery algorithm designed to reveal ecological relationships in rivers and streams from observational data. Our algorithm (a) takes into account the spatial structure of the river network, (b) reveals the complete network of ecological relationships, and (c) shows the directions of these relationships. We apply our algorithm to data collected in the US state of Ohio to better understand causes of reductions in fish and invertebrate community integrity. We found that nitrogen is a key variable underlying fish and invertebrate community integrity in Ohio, likely negatively impacting both. We also found that fish and community integrity are each linked to one physical habitat quality variable. Our algorithm further revealed a split between physical habitat quality and water quality variables, indicating that causal relations between these groups of variables are likely absent. Our approach is able to reveal networks of ecological relationships in rivers and streams based on observational data, without the need to formulate a priori hypotheses. This is an asset particularly for diagnostic assessments of the ecological state and potential causes of biodiversity impairment in rivers and streams.</p>
Supporting Data for: Assessing the potential of amino acid δ13C and δ15N analysis in terrestrial and freshwater ecosystems
<p>Understanding the structure and dynamics of food webs requires accurate estimates of energy flow among organisms. Bulk tissue carbon (<em>δ</em><sup>13</sup>C) and nitrogen (<em>δ</em><sup>15</sup>N) isotope analysis is often used to this end, however, the limitations of this technique can outweigh the benefits. The isotope analysis of individual amino acids is being increasingly employed to trace energy flow and estimate consumer trophic level. Central to this compound-specific approach are the concepts of essential amino acid (AA<sub>ESS</sub>) <em>δ</em><sup>13</sup>C fingerprinting and amino acid (AA) <em>δ</em><sup>15</sup>N beta-values, both of which have been understudied and are poorly constrained in terrestrial and freshwater producers.</p> <p>We present AA<sub>ESS</sub> <em>δ</em><sup>13</sup>C data for 112 terrestrial and freshwater producers collected from two aridland habitats in the northern Chihuahuan Desert (New Mexico, USA) and AA <em>δ</em><sup>15</sup>N data for a subset (n=28) of these samples. We characterized AA<sub>ESS</sub> <em>δ</em><sup>13</sup>C fingerprints by performing linear discriminant analysis on the <em>δ</em><sup>13</sup>C values of isoleucine, leucine, lysine, phenylalanine, threonine, and valine for four producer groups – C<sub>3</sub> plants, C<sub>4</sub> plants, CAM plants, and filamentous green algae. We explored potential biochemical mechanisms underlying these AA<sub>ESS</sub> <em>δ</em><sup>13</sup>C fingerprints by calculating differences between the <em>δ</em><sup>13</sup>C values of AA<sub>ESS</sub> products and their AA precursors. This allowed us to estimate and compare isotopic discrimination for specific AA<sub>ESS</sub> synthesis pathways across producer groups.</p> <p>We found near perfect separation of AA<sub>ESS</sub> <em>δ</em><sup>13</sup>C fingerprints among producer groups; all groups reclassified with >95% success within our multivariate framework. We also found varied isotopic discrimination for specific AA<sub>ESS</sub> synthesis pathways among producer groups. Contrary to previous studies, we found no differences in beta-values between terrestrial C<sub>3</sub> and C<sub>4</sub> plants for any trophic-source AA pairing. Furthermore, we found that Lys <em>δ</em><sup>15</sup>N values were less variable and more closely related to bulk tissue <em>δ</em><sup>15</sup>N values than Phe <em>δ</em><sup>15</sup>N values in terrestrial and freshwater producers.</p> <p><span><span><span><span><span>We conclude that AA<sub>ESS</sub> <em>δ</em></span></span></span></span></span><sup>13</sup><span><span><span><span><span>C fingerprints are a higher-resolution tracer for freshwater food webs where instream algae have overlapping bulk tissue <em>δ</em></span></span></span></span></span><sup>13</sup><span><span><span><span><span>C values with terrestrial C<sub>3</sub> plants. Additionally, </span></span></span></span></span><span><span><span><span><span>beta</span></span></span></span></span><sub>Glx-Lys</sub><span><span><span><span><span> and </span></span></span></span></span><span><span><span><span><span>beta</span></span></span></span></span><sub>Pro-Lys</sub><span><span><span><span><span> are the best for AA <em>δ</em></span></span></span></span></span><sup>15</sup><span><span><span><span><span>N-based consumer trophic level estimates in freshwater food webs containing both terrestrial and aquatic resources.</span></span></span></span></span></p>
Supporting Data for: Assessing the potential of amino acid δ13C and δ15N analysis in terrestrial and freshwater ecosystems
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Data from: Review on the effects of toxicants on freshwater ecosystem functions
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Data from: Exploring the effects of salinization on trophic diversity in freshwater ecosystems: a quantitative review
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Measurements in flowing freshwater ecosystems taken in Ohio (US)
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.