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227 results for “lake morphology”
Modeling the effects of lake morphology on chloride retention and salt-driven stratification in two urban lakes in St. Paul, MN
Road salt inputs have caused widespread salinization of urban lakes in northern temperate regions. Watershed characteristics are known to be important drivers of lake chloride concentrations, but there has been less focus on how lake morphometry influences seasonal and interannual dynamics in lake chloride, and how these chloride levels may alter mixing in the water column. We analyzed chloride retention for two urban lakes (Como Lake and Lake McCarrons) in Saint Paul, Minnesota, that are in adjacent watersheds and have similar surface areas, but differ in depth and water residence time. Summer chloride concentrations were negatively related to total summer precipitation for Como Lake (maximum depth 2.2 m), but the relationship was less strong for Lake McCarrons (maximum depth 7.6 m). We used a zero-dimensional model to simulate chloride dynamics in both lakes and tracked the fate of chloride over time. In Como Lake, the mass of chloride in the lake turns over within three years, whereas chloride inputs are retained for >10 years in Lake McCarrons. We then used a one-dimensional hydrodynamic lake model (GLM-AED) to examine how lake depth affects how current chloride loading rates alter lake mixing. Salt inputs significantly extended the duration of summer stratification for simulated lakes with depths of 8 m or more, and salt inputs increased the number of days of hypoxia and anoxia across all depths. These results underscore the importance of considering lake morphometry in understanding the effects of salt inputs on lake ecosystems.
Density-dependent effects of exotic brook trout on aquatic communities in mountain lakes revealed by environmental DNA and morphological taxonomy
Invasion of non-native fishes threatens freshwater biodiversity worldwide. Yet, detailed estimates of population demography for invasive species, that estimate population size and body size of the invasive species, are rarely integrated in evaluating aquatic community responses. Our study capitalized on detailed brook trout population demographic data collected for a replicated whole lake ecosystem experiment involving experimental harvesting of exotic brook trout in nine mountain lakes. We applied environmental DNA (eDNA) metabarcoding and morphological taxonomy to examine the response of crustacean zooplankton and macroinvertebrate communities to gradients in brook trout effective density and lake elevation. Density-dependent effects of brook trout on crustacean zooplankton and macroinvertebrate communities were detected even decades after their first introductions (between 1926 and 1980). However, they were moderated by environmental factors such as elevation, lake maximum depth and dissolved organic carbon. Elevation was important in structuring crustacean zooplankton and macroinvertebrate community composition. While there were differences in explanatory variables when describing communities characterized by eDNA metabarcoding and morphological taxonomy, the principal environmental factors that structured the communities were similar. Our paper highlights persisting density-dependent impacts of exotic trout on invertebrate communities even decades after first introduction, and it considers the conservation implications for lake restoration.
FIGURE 3 in Morphological and molecular species boundaries in the Hyalella species Flock of Lake Titicaca (Crustacea: Amphipoda)
FIGURE 3 Bayesian phylogeny and molecular species delimitation of South American Hyalella based on currently available cox1 mitochondrial data (present work and Barcode of Life DATA Systems (BOLD) repository project TTKK). Nodes with maximum nodal support are remarked with circles. Purple dots on branch tips indicate haplotypes exclusively sampled in South America outside the Altiplano area (see supplementary fig S1 for details). See main text for details on molecular species delimitation methods and results.
FIGURE 1 A in Morphological and molecular species boundaries in the Hyalella species Flock of Lake Titicaca (Crustacea: Amphipoda)
FIGURE 1 A, map of South America showing location of the Andean Altiplano; B, approximate area of the Altiplano showing placement of its main water bodies; C, sampling sites placed outside Lake Titicaca; D, sampling sites at Lake Titicaca itself. Numbers identify sampling stations. See supplementary tables S1 and S2 for precise information on sampling sites. Maps were produced using R ggmap (Kahle & Wickham, 2013) and Google Maps (Google Inc., Mountain View Downloaded, CA). from Brill.com 12/12/2023 03:08:26PM via Open Access. This is an open access article distributed under the terms of the CC BY 4.0 license. https://creativecommons.org/licenses/by/4.0/
FIGURE 2 in Morphological and molecular species boundaries in the Hyalella species Flock of Lake Titicaca (Crustacea: Amphipoda)
FIGURE 2 Morphological disparity within the Hyalella species-flock of Lake Titicaca. A, H. robusta; B, H. longipalma; C, H. montforti; D-E, H. crawfordi; F, H. neveulemairei; G-H, H. armata; I, H. knickerbockeri; J, Hyalella n. sp. 1; K, H. lucifugax. See key to species for descriptionDownloadedof precisefrom Brill armature.com 12/12 arrangement /2023 03:08:26PM on each species. [A-C, E: after via ChevreuxOpen (1907 Access);. D, This E: after is an Coleman open & accessGonzález article(2006); distributedG, H: after under the terms González & Coleman (2002); I: modified from Weckel (1910); K: modified from Faxonof(the 1876)] CC BY 4.0 license. https://creativecommons.org/licenses/by/4.0/
FIGURE 4 in Morphological and molecular species boundaries in the Hyalella species Flock of Lake Titicaca (Crustacea: Amphipoda)
FIGURE 4 Multidimensional scaling plot based on Kimura 2-parameters genetic distances of the 560 unique cox1 haplotypes detected in Hyalella. Dot colours refer to the main Hyalella lineages inferred in the molecular species delimitation analyses. Dots have been numbered according to their MOTU assignment.
Figure 1 in Morphological, histological and molecular characteristics of Myxobolus spp. (Cnidaria: Myxozoa) infecting the kidney of silver carp in Lake Taihu
Figure 1. Spores of Myxobolus lieni (Nie & Li, 1973) (A–B) and M. varius (Achmerov, 1960) (C–D) from Hypophthalmichthys molitrix, line drawings. Scale bars = 2 μm.
Figure 2 in Morphological, histological and molecular characteristics of Myxobolus spp. (Cnidaria: Myxozoa) infecting the kidney of silver carp in Lake Taihu
Figure 2. Spores of Myxobolus lieni (Nie & Li, 1973) (A–B) and M. varius (Achmerov, 1960) (C–D) from Hypophthalmichthys molitrix, digitized images. Scale bars = 10 μm.
Figure 3 in Morphological, histological and molecular characteristics of Myxobolus spp. (Cnidaria: Myxozoa) infecting the kidney of silver carp in Lake Taihu
Figure 3. Histopathological sections of Hypophthalmichthys molitrix kidney infected by Myxobolus spp. A–C. M. lieni (Nie & Li, 1973), in the renal tubules; D. M. varius (Achmerov, 1960), in the renal interstitium. Arrows indicate the plasmodia which contains 2–4 mature myxospores. Scale bars = 10 μm.
Figure 4 in Morphological, histological and molecular characteristics of Myxobolus spp. (Cnidaria: Myxozoa) infecting the kidney of silver carp in Lake Taihu
Figure 4. Bayesian inference trees constructed with the SSU rDNA sequences. Numbers near the nodes shows the posterior probability and bootstrap values of BI and maximum likelihood (ML), respectively. Information of GenBank accession number, infection site, host and locality follows the species name. Abbreviations: B—brain; E—encephalocoele; F—fin; G—gills; GA—gill arch; GL— capillary network of the gill lamellae; H—heart; I—intestine; K—kidney; M—mesentery; MP- palate of the mouse; MC—muscle cells; SB—swim bladder; UB—urinary bladder.
Рис. 2. Крючки глохидиев Colletopterum anatinum: А – оЗ. Красное; B – оЗ. Арахлей. МасШтабные линейки 20 мкм. Fig. 2. Hooks of glochidia of Colletopterum anatinum: А – Lake Krasnoye; B – Lake Arakhley. Scale bars – 20 µm. in Morphology of glochidia of the anodontine bivalves of the genus Colletopterum (Unionidae) inhabiting water basins of Khakasia Republic and Chitinskaya Territory
Рис. 2. Крючки глохидиев Colletopterum anatinum: А – оЗ. Красное; B – оЗ. Арахлей. МасШтабные линейки 20 мкм. Fig. 2. Hooks of glochidia of Colletopterum anatinum: А – Lake Krasnoye; B – Lake Arakhley. Scale bars – 20 µm.
Рис. 1. Створки глохидиев Colletopterum piscinale: А – вид снаружи, оЗ. ШакШинское; B – вид иЗнутри, оЗ. Новомихайловское. МасШтабные линейки 50 мкм. Fig. 1. Valves of glochidia of Colletopterum piscinale: A – exterior view, Lake Shakshinskoye; B – interior view, Lake Novomikhailovskoye. Scale bars –50 µm. in Morphology of glochidia of the anodontine bivalves of the genus Colletopterum (Unionidae) inhabiting water basins of Khakasia Republic and Chitinskaya Territory
Рис. 1. Створки глохидиев Colletopterum piscinale: А – вид снаружи, оЗ. ШакШинское; B – вид иЗнутри, оЗ. Новомихайловское. МасШтабные линейки 50 мкм. Fig. 1. Valves of glochidia of Colletopterum piscinale: A – exterior view, Lake Shakshinskoye; B – interior view, Lake Novomikhailovskoye. Scale bars –50 µm.
Рис. 3. Микроскульптура наружной (А, B) и внутренней (C, D) поверхностей глохидиальных створок Colletopterum piscinale, оЗ. ШакШинское. МасШтабные линейки 2 мкм. Fig. 3. Microsculpture of the outer (А, B) and inner (C, D) surfaces of glochidial valves of Colletopterum piscinale, Lake Shakshinskoye. Scale bars – 2 µm. in Morphology of glochidia of the anodontine bivalves of the genus Colletopterum (Unionidae) inhabiting water basins of Khakasia Republic and Chitinskaya Territory
Рис. 3. Микроскульптура наружной (А, B) и внутренней (C, D) поверхностей глохидиальных створок Colletopterum piscinale, оЗ. ШакШинское. МасШтабные линейки 2 мкм. Fig. 3. Microsculpture of the outer (А, B) and inner (C, D) surfaces of glochidial valves of Colletopterum piscinale, Lake Shakshinskoye. Scale bars – 2 µm.
Fig. 3. Correlation coefficients estimated between water quality indicators and morphological Fig. 4 in Investigation Of Common Reed Regrowth On The Shores Of Recreational Lakes
Fig. 3. Correlation coefficients estimated between water quality indicators and morphological Fig. 4. The number of holidaymakers near parameters of common reeds on the shores of Bridvaisis, Gaustvinis and Gilius lakes (in the Bridvaisis, Gaustvinis and Gilius Lakes. The order from the bottom to the top) and differences boundary of the continuous line side indicates in morphological parameters of plants after the cases where p <0.01; dashed lines, where p <0.05. holidaymakers' visits.
Fig.5 in Genetic And Morphological Variability Of Small Vendace (Coregonus Albula (Linnaeus, 1758)) Population In Three Latvian Lakes
Fig.5. Principal component analysis (PCA) plot of the genetic structuring among the three vendace populations. A). PC1 and PC2 explain 25.50% and 21.88% of the total variation, respectively (by allozyme markers); B). PC1 and PC2 explain 19.52% and 13.73% of the total variation, respectively (by RAPD markers).
Fig. 4 in Genetic And Morphological Variability Of Small Vendace (Coregonus Albula (Linnaeus, 1758)) Population In Three Latvian Lakes
Fig. 4. Number of RAPD loci and gene diversity of Coregonus albula in three Latvian lakes, based on RAPD markers.
Fig.3 in Genetic And Morphological Variability Of Small Vendace (Coregonus Albula (Linnaeus, 1758)) Population In Three Latvian Lakes
Fig.3. Allelic richness and polymorphism in Coregonus albula populations in studied lakes based on allozyme markers.
Рис. 2. Ментум Λичинок роΑа Chironomus из озера Кенон Fig. 2. Mentum of the Chironomus genus larvae from Lake Kenon in Toxic pollution assessment of Chita TPP-1 cooling reservoir by applying the method of head capsule morphological deformations in chironomid larvae
Рис. 2. Ментум Λичинок роΑа Chironomus из озера Кенон Fig. 2. Mentum of the Chironomus genus larvae from Lake Kenon
Рис. 1. Схема мониторинговых станций на озере Кенон: 1–1.6 — ТЭЦ; 2–2.1 — КСК; 3 — Нефтебаза; 4 — Центр озера; 5 — КаΑаΛинка Fig. 1. Diagram of monitoring stations on Kenon lake: 1–1.6 — TPP; 2–2.1 — KSK; 3 — Tank farm; 4 — Lake Center; 5 — Kadalinka in Toxic pollution assessment of Chita TPP-1 cooling reservoir by applying the method of head capsule morphological deformations in chironomid larvae
Рис. 1. Схема мониторинговых станций на озере Кенон: 1–1.6 — ТЭЦ; 2–2.1 — КСК; 3 — Нефтебаза; 4 — Центр озера; 5 — КаΑаΛинка Fig. 1. Diagram of monitoring stations on Kenon lake: 1–1.6 — TPP; 2–2.1 — KSK; 3 — Tank farm; 4 — Lake Center; 5 — Kadalinka
Fig. 2a, b in Morphological, ecological and toxicological aspects of Raphidiopsis raciborskii (Cyanobacteria) in a eutrophic urban subtropical lake in southern Brazil
Fig. 2a, b. Bar graphs indicating the relative percentages of different phytoplankton groups in the lake inflow (a) and outflow (b), sampled every month from November 2009 to November 2010.
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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.