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53 results for “Dreissena”
In-depth characterization revealed polymer type and chemical content specific effects of microplastic on Dreissena bugensis
<p>The files contain datasets that were generated during laboratory-based real-time valvometry, and laser doppler anemometry measurements. The article was published in Journal of Hazardous Materials (accepted June 8, 2022).</p>
Figure 5 in A simplistic water body-specific risk assessment model for zebra mussel (Dreissena polymorpha) establishment based on physicochemical characteristics
Figure 5. Overall zebra mussel establishment risk categorization of 133 Texas water bodies based on calcium, pH, salinity, and temperature. Major water bodies not included in this study due to lack of TCEQ water quality data are shown for context of the study extent. The Whittier et. al. low calcium/low risk zone delineation is shown to demonstrate level of agreement with that study, which is relatively high with some noteworthy exceptions. The Cypress, Sabine, and Neches River basins referenced in the text are the three East Texas basins with predominantly minimal risk water body categorizations.
Figure 2 in A simplistic water body-specific risk assessment model for zebra mussel (Dreissena polymorpha) establishment based on physicochemical characteristics
Figure 2. pH-based zebra mussel establishment risk categorization of 133 Texas water bodies. Major water bodies not included in this study due to lack of TCEQ water quality data are shown for context of the study extent.
Figure 4 in A simplistic water body-specific risk assessment model for zebra mussel (Dreissena polymorpha) establishment based on physicochemical characteristics
Figure 4. Temperature-based zebra mussel establishment risk categorization of 126 Texas water bodies. Major water bodies not included in this study due to lack of TCEQ water quality data are shown for context of the study extent.
Figure 3 in A simplistic water body-specific risk assessment model for zebra mussel (Dreissena polymorpha) establishment based on physicochemical characteristics
Figure 3. Salinity-based zebra mussel establishment risk categorization of 133 Texas water bodies. Major water bodies not included in this study due to lack of TCEQ water quality data are shown for context of the study extent.
Figure 1 in A simplistic water body-specific risk assessment model for zebra mussel (Dreissena polymorpha) establishment based on physicochemical characteristics
Figure 1. Calcium-based zebra mussel establishment risk categorization of 85 Texas water bodies. Areas to the east of the Whittier et al. (2008) calcium risk delineation were predicted by that study to have ≤ 12 mg/l calcium (i.e., minimal establishment risk); this delineation is shown to demonstrate level of agreement with that study. Major water bodies not included in this study due to lack of TCEQ water quality data are shown for context of the study extent. The Cypress, Sabine, and Neches River basins referenced in the text are the three East Texas basins with predominantly minimal risk water body categorizations.
Figure 3 in Effects of temperature on mortality of quagga mussels (Dreissena bugensis) exposed to potassium chloride and copper-based molluscicides in high conductivity waters
Figure 3. Comparison of measured mortality for adult mussels exposed to copper at 10 °C and copper concentrations over time for Experiment 1b (A), which had 50% less biomass and lower mean specific conductivity than Experiment 4 (C) with log-logistic dose-response model fits. Colored bands are 95% confidence intervals and points are mortality values from replicate bioboxes. Measured copper concentrations in bioboxes for B) Experiment 1b and D) Experiment 4. Solid horizontal lines are target concentrations, dashed horizontal lines are mean concentration over the entire experiment duration.
Figure 2 in Effects of temperature on mortality of quagga mussels (Dreissena bugensis) exposed to potassium chloride and copper-based molluscicides in high conductivity waters
Figure 2. Measured mortality for adult mussels exposed to KCl at A) 10 °C, B) 18 °C, and C) 22 °C with log-logistic doseresponse model fits. Colored bands are 95% confidence intervals and points are mortality values from replicate bioboxes.
Figure 1 in Effects of temperature on mortality of quagga mussels (Dreissena bugensis) exposed to potassium chloride and copper-based molluscicides in high conductivity waters
Figure 1. Variation in specific conductivity in A) Lake Piru and B) control bioboxes within experimental periods. Specific conductivity from moderate conductivity Lake Ontario and Minnesota lakes (≈ 300 µS/cm; Moffitt et al. 2016; Luoma et al. 2018) is provided for reference.
Figure 5 in Effects of temperature on mortality of quagga mussels (Dreissena bugensis) exposed to potassium chloride and copper-based molluscicides in high conductivity waters
Figure 5. Comparison of measured mortality for adult mussels exposed to copper at 10 °C and copper concentrations over time for Experiment 1a (A), which received only a single dose of copper and Experiment 1b, which included refreshed copper treatments (C) with log-logistic dose-response model fits. Colored bands are 95% confidence intervals and points are mortality values from replicate bioboxes. Measured copper concentrations in bioboxes for B) Experiment 1a (without refresh) and D) Experiment 1b (with refresh). Solid horizontal lines are target concentrations, dashed horizontal lines are mean concentration over the entire experiment duration.
Figure 4 in Effects of temperature on mortality of quagga mussels (Dreissena bugensis) exposed to potassium chloride and copper-based molluscicides in high conductivity waters
Figure 4. Measured mortality for adult mussels exposed to copper (Earthtec QZ®) at A) 10 °C, C) 18 °C, and E) 22 °C with loglogistic dose-response model fits. Colored bands are 95% confidence intervals and points are mortality values from replicate bioboxes. Measured copper concentrations in bioboxes at B) 10 °C, D) 18 °C, and F) 22 °C. Solid horizontal lines are target concentrations, dashed horizontal lines are mean concentration over the entire experiment duration.
Figure 2 in Environmental DNA as a tool to help inform zebra mussel, Dreissena polymorpha, management in inland lakes
Figure 2. The mean number of cycles needed to detect DNA of zebra mussels from water samples collected at the surface, mid-column and bottom of Lake Minnetonka directly above a known zebra mussel population. A lower number of cycles indicates a greater amount of DNA. Bars represent the 95% confidence intervals.
Figure 3 in Environmental DNA as a tool to help inform zebra mussel, Dreissena polymorpha, management in inland lakes
Figure 3. Structural Equation Model for zebra mussels in two lakes near Alexandria, Minnesota: Lake Le Homme Dieu (A) and Maple Lake (B). Nodes are environmental DNA copy numbers of zebra mussel DNA (eDNA), habitat, depth, lake and ash-free dry weight (AFDW). AFDW is log(AFDW + 0.1). eDNA is log(copy number eDNA + 0.1). Numbers next to a line between two nodes represents the correlation between the two nodes. The r2 values in boxes correspond % variance of dependent variable explained by the independent variable. Values with an asterisk (*) indicate significant correlation between nodes. Our significance level was established at α ≤ 0.05.
Fig. 1 in Towards a ground pattern reconstruction of bivalve nervous systems: neurogenesis in the zebra mussel Dreissena polymorpha
Fig. 1 Development of Dreissena polymorpha from gastrula to early veliger stage. a, g, h, and i Scanning electron micrographs. b, c Confocal microscope Zprojection images. d, e, and f Single optical sections of c. Acetylated α-tubulin-lir (green), HCS CellMask (pink), and cell nuclei counter staining (blue). Apical is always up. Lateral views. Scale bars are 15 μm. a Ciliated gastrula stage (16 h post fertilization, hpf) with blastopore (bp) on the vegetal pole. b Elongated early trochophore (22 hpf) with prominent apical tuft (at) and prototroch (pt). c Early-trochophore (23 hpf) with apical tuft (at), prototroch (pt), and telotroch (tt). d Early trochophore (23 hpf). e, f Early trochophore (23 hpf) in different optical planes with foregut (fg) and shell field (sf) invagination. g Early veliger (39 hpf) with embryonic shell (s) and expanded velum (ve). h 46 hpf old veliger. i Late veliger larva (188 hpf)
Fig. 1 in A report of Zebra Mussel Dreissena polymorpha (Pallas, 1771) (Bivalvia: Dreissenidae) in the middle sector of Iskar River, Bulgaria
Fig. 1. Study sector of the Iskar River: white circles marked macrozoobenthos sampling sites, dark circles marked microreservoirs of SHPPs.
Fig. 2 in A report of Zebra Mussel Dreissena polymorpha (Pallas, 1771) (Bivalvia: Dreissenidae) in the middle sector of Iskar River, Bulgaria
Fig. 2. Zebra Mussels from Iskar River near Tserovo village. Left: first recorded individual, 2016 September 29. Right: location (yellow arrow) of single specimens in the border (red lines) between ripal zone (0-0.5m depth) and medial river zone (over 1.5m depth). Photos: Ivaylo Yotinov.
Fig. 1 in The Study Of Age-Related Variability Of Pigmentation Patterns Of The Shells Of Dreissena Polymorpha (Bivalvia, Dreissenidae) From Different Parts Of It'S Range
Fig. 1. Change of pattern types on zebra mussel shell. The present shell has four age zones (0+, 1+, 2+, 3+). The pattern sequence is С–АС–А–А.
Figure 1 in Molecular data on Phyllodistomum macrocotyle (Digenea: Gorgoderidae) from an intermediate host Dreissena polymorpha (Bivalvia: Dreissenidae) in the Northern Dvina River Basin, Northwest Russia
Figure 1. Map of the study area: A) Geographic position of the research area (red color frame and red color point); B) The Northern Dvina River Basin (red color flags indicate points where zebra mussels infected with Phyllodistomum macrocotyle were found); C) Habitat of zebra mussel, the Yuras River; D) Trematode sporocysts located within the gills of Dreissena polymorpha.
Figure 2 in Molecular data on Phyllodistomum macrocotyle (Digenea: Gorgoderidae) from an intermediate host Dreissena polymorpha (Bivalvia: Dreissenidae) in the Northern Dvina River Basin, Northwest Russia
Figure 2. Maximum likelihood phylogeny of Phyllodistomum macrocotyle based on the nuclear dataset (28S rDNA gene fragment). Numbers near nodes are bootstrap support (BS) values of IQ-TREE. Scale bar indicates the branch lengths. The red color indicates our sequence from Northwest Russia.
Figure 2 in First record of metacercariae trematodes Opisthioglyphe ranae (Digenea: Telorchiidae) and Echinostoma bolschewense (Digenea: Echinostomatidae) in Dreissena polymorpha (Bivalvia: Dreissenidae) from the Don and Volga river basins, Russia
Figure 2. Maximum likelihood phylogeny of Echinostoma genus based on the nuclear dataset (28S rDNA gene fragment). Numbers near nodes are bootstrap support (BS) values of IQ-TREE. Scale bar indicates the branch lengths. Red color indicates our sequence from the Sokolovskoe Reservoir (Don River basin).
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International Brain Laboratory public data
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OpenNeuro
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