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High-resolution (10-meter) Dynamic Water body map of the Hindu Kush Himalaya region (DWH10) for the year 2022
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Fig. 3 in Investigation of Ichthyophthirius multifiliis infection in fish from natural water bodies in the Lhasa and Nagqu regions of Tibet
Fig. 3. Prevalence of I. mutlifillis infection in Schizopygopsis at locations of differing salinity.
Assessing environmental DNA metabarcoding and camera trap surveys as complementary tools for biomonitoring of remote desert water bodies
<p>Biodiversity assessments are indispensable tools for planning and monitoring conservation strategies. Camera traps (CT) are widely used to monitor wildlife and have proven their usefulness. Environmental DNA (eDNA)-based approaches are increasingly implemented for biomonitoring, combining sensitivity, high taxonomic coverage and resolution, non-invasiveness and easiness of sampling, but remain challenging for terrestrial fauna. However, in remote desert areas where scattered water bodies attract terrestrial species, which release their DNA into the water, this method presents a unique opportunity for their detection. In order to identify the most efficient method for a given study system, comparative studies are needed. Here, we compare CT and DNA metabarcoding of water samples collected from two desert ecosystems, the Trans-Altai Gobi in Mongolia and the Kalahari in Botswana. We recorded with CT the visiting patterns of wildlife and studied the correlation with the biodiversity captured with the eDNA approach. The aim of the present study was threefold: a) to investigate how well waterborne eDNA captures signals of terrestrial fauna in remote desert environments, which have been so far neglected in terms of biomonitoring efforts; b) to compare two distinct approaches for biomonitoring in such environments and c) to draw recommendations for future eDNA-based biomonitoring. We found significant correlations between the two methodologies and describe a detectability score based on variables extracted from CT data and the visiting patterns of wildlife. This supports the use of eDNA-based biomonitoring in these ecosystems and encourages further research to integrate the methodology in the planning and monitoring of conservation strategies.</p>
Fig.1 in Changes In Liver Parenchyma Of Green Frogs (Pelophylax Esculentus Complex) Under Conditions Of Anthropogenic Pollution And Their Use In Monitoring Of Water Bodies
Fig.1. Alteration in the liver of the frog collected in the urban sprawl and in agrocenosis: A — fatty degeneration turning into necrosis; B — inFLammation; C — degradation of the connective tissue; D — necrosis and the beginning of the anisocytosis in "emergency regeneration" (the bright pink cells with large nuclei); E — anisocytosis and abundance of small hepatocytes not forming a typical structure; F — protein dystrophy. Staining: hematoxylin-eosin (A, B, D, E, F) and Mallory (C). ×200.
Fig. 1 in Finding Of Gyrodactylus Perccotti (Plathelminthes, Gyrodactylidae) In Water Bodies Of Kyiv Region
Fig. 1. Gyrodactylus perccotti detected in Chinese sleeper from Shaparnja lake; a — general view; b — anchor; c — marginal hook.
HLWATER V1.0 water bodies - Western Nunavik (Subarctic Canada)
<p>This dataset consists of a Very High Resolution water body delineation dataset computed with the <a href="https://doi.org/10.5281/zenodo.10203553">HLWATER V1.0 model</a> (<a href="https://doi.org/10.1016/j.rse.2024.114047">Freitas et al., 2024</a>) over PlanetScope-Dove imagery (3-m spatial resolution) for Western Nunavik (Eastern Hudson Bay), Subarctic Canada. It covers a total area of 41,832 km2 within the latitudes 54° to 58° N and the longitudes 74° to 78° W.</p> <p>The dataset is composed of 335,281 water bodies. Additionally, 1 km2 hexagonal grids are provided with the calculation of the limnicity (water fraction of land surface) and limnodensity (density of water bodies considering their centroids). Outputs are provided in shapefile and geodatabase formats.</p> <p>The manuscript detailing these outputs has been submitted to GIScience and Remote Sensing.</p>
Figure 11 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 11. Temporal trend of the Pianka mean niche overlap indexes deviation from random alternatives (1998–2018). The abscissa axis – years, the ordinate axis – the Pianka mean niche overlap indexes deviation from random alternatives, line – the linear approximation of the temporal trend (R2 = 0.32, p <0.001).
Figure 9 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 9. Dynamics of the spawning start and end of fish in the "Dnipro-Orilskiy" nature reserve. The abscissa axis – years; the ordinate axis – spawning start and end, days of the year (black dot – spawning start time, red dot – spawning end time); lines – linear trend approximation
Figure 8 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 8. Dependence of the coefficient of variation of the spawning start time from the average time of the spawning onset and the coefficient of variation of the end of the spawning from the average time of the end of the spawning. The abscissa axis – days of the year; the ordinate axis – coefficient of variation (blue dot – spawning start time, red dot – spawning end time); lines – second order approximation polynomials.
Figure 7. Fine-scale components RDA 1-3 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 7. Fine-scale components RDA 1-3 of the annual temperature variation. Black line – the original data, colored lines – smoothed data. The abscissa axis – the number of days from 1 July of the previous year to June 31 of the next year.
Figure 3 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 3. Annual course of the temperature (A) and residuals of the trend line (B). The abscissa axis – the number of days from 1 July of the previous year to June 31 of the next year, the ordinate axis – the average temperature for the period 1998–2018 (A). Line indicates the graph of the polynomial of the fourth degree.
Figure 2 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 2. The dynamics of air temperature from 1998 to 2018. The line indicates an approximation of the average annual temperature trend Temp = 8.81 + 0.059 t, where Temp – average annual temperature, t – the order of year: 1 – 1998, 2 – 1999, etc.
Figure 6. Medium-scale components RDA 1-3 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 6. Medium-scale components RDA 1-3 of the annual temperature variation. Black line – the original data, colored lines – smoothed data. The abscissa axis – the number of days from 1 July of the previous year to June 31 of the next year.
Figure 1 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 1. Map of the "Dnipro-Orilskiy»Nature Reserve and spawning locations. I – Nikolayev system of water bodies; II – river Protoch system and Obukhov floodplain; III – the channel of the river Dnipro; IV – water bodies of the Taromske ledge.
Рис. 3. Theristus securus sp. nov., гоΛотип самца (a, c, d), паратип самки (b). a, b — общий виΔ; c — гоΛова; d — спикуΛярный аппарат. Масштаб: a — 150 мкм; b — 250 мкм; c, d — 30 мкм Fig. 3. Theristus securus sp. nov., male holotype (a, c, d) and female paratype (b). a, b — general view; c — head; d — spicular apparatus. Scale bars: a — 150 µm; b — 250 µm; c, d — 30 µm in Two New Species Of The Family Xyalidae Chitwood, 1951 (Nematoda, Monhysterida) From The Water Bodies Of Vietnam
Рис. 3. Theristus securus sp. nov., гоΛотип самца (a, c, d), паратип самки (b). a, b — общий виΔ; c — гоΛова; d — спикуΛярный аппарат. Масштаб: a — 150 мкм; b — 250 мкм; c, d — 30 мкм Fig. 3. Theristus securus sp. nov., male holotype (a, c, d) and female paratype (b). a, b — general view; c — head; d — spicular apparatus. Scale bars: a — 150 µm; b — 250 µm; c, d — 30 µm
Рис. 2. Фотографии Metadesmolaimus longicaudatus sp. nov., гоΛотип самца (a, c, d, g, h) и паратип самки (b, e, f, j). a, b — общий виΔ; c — переΔний конец теΛа; d, e — гоΛова; f — теΛо в обΛасти вуΛьвы; g — теΛо в обΛасти кΛоаки; h, j — заΔний конец теΛа. Масштаб: a, b — 100 мкм; c — 50 мкм; f, h, j — 20 мкм; d, e, g — 10 мкм Fig. 2. Light micrograph of Metadesmolaimus longicaudatus sp. nov., male holotype (a, c, d, g, h) and female paratype (b, e, f, j), a, b — general view; c — anterior body end; d, e — head; f — vulvar region; g — cloaca region; h, j — posterior body end;. Scale bars: a, b — 100 μm; c — 50 μm; h, j — 20 μm; d, e, g — 10 μm in Two New Species Of The Family Xyalidae Chitwood, 1951 (Nematoda, Monhysterida) From The Water Bodies Of Vietnam
Рис. 2. Фотографии Metadesmolaimus longicaudatus sp. nov., гоΛотип самца (a, c, d, g, h) и паратип самки (b, e, f, j). a, b — общий виΔ; c — переΔний конец теΛа; d, e — гоΛова; f — теΛо в обΛасти вуΛьвы; g — теΛо в обΛасти кΛоаки; h, j — заΔний конец теΛа. Масштаб: a, b — 100 мкм; c — 50 мкм; f, h, j — 20 мкм; d, e, g — 10 мкм Fig. 2. Light micrograph of Metadesmolaimus longicaudatus sp. nov., male holotype (a, c, d, g, h) and female paratype (b, e, f, j), a, b — general view; c — anterior body end; d, e — head; f — vulvar region; g — cloaca region; h, j — posterior body end;. Scale bars: a, b — 100 μm; c — 50 μm; h, j — 20 μm; d, e, g — 10 μm
Fig. 2. Pleuronema grolierei after protargol impregnation. A, C. Ventral views showing a typical body shape and infraciliature. B. Dorsal view showing somatic kineties. D. Nuclear apparatus, arrow denotes a in Taxonomy of four scuticociliates (Protozoa: Ciliophora) from coastal waters of South Korea
Fig. 2. Pleuronema grolierei after protargol impregnation. A, C. Ventral views showing a typical body shape and infraciliature. B. Dorsal view showing somatic kineties. D. Nuclear apparatus, arrow denotes a micronucleus. CC, caudal cilia; Ma, macronucleus; M1, 3, membranelles 1, 3; M2a, anterior part of membranelle 2; M2b, posterior part of membranelle 2; PM, paroral membrane; PK; preoral kineties; PoK, postoral kinety; SK, somatic kineties. Scale bar = 30 μm.
FIGURE 7 in Archaeodiacyclops, new genus with "archaic" features (Crustacea, Copepoda, Cyclopoida), with description of new species from water bodies of northern Sakhalin Island
FIGURE 7. Distribution of the genus Archaeodiacyclops gen. nov. (made with Google Earth).
Figure 1 in Macrobenthic communities in water bodies and streams of Svalbard, Norway
Figure 1. Map of sampling sites.
Non-biodegradable objects may boost microbial growth in water bodies by harnessing bubbles
<p><span><span><span><span><span><span><span><span><span><span><span>Given the ubiquity of bubbles and non-biodegradable wastes in aqueous environments, their transport through bubbles should be widely extant in water bodies. In this study, we investigate the effect of bubble-induced waste transport on microbial growth by using yeasts as model microbes and a silicone rubber object as a model waste. Noteworthily, this object repeatedly rises and sinks in fluid through fluctuations in bubble acquired buoyant forces produced by cyclic nucleation, growth and release of bubbles from object's surface. The rise-sink movement of object gives rise to a strong bulk mixing and an enhanced resuspension of cells from the floor. Such spatially dynamic contaminant inside a nutrient-rich medium also leads to an increment in the total microbe concentration in the fluid. The enhanced concentration is caused by strong nutrient mixing generated by the object's movement which increases the nutrient supply to growing microbes and thereby, prolonging their growth phases. We confirm these findings through a theoretical model for cell concentration and nutrient distribution in fluid medium. The model is based on the continuum hypothesis and it uses the general conservation law which takes an advection-diffusion-growth form. We conclude the study with demonstration of bubble-induced digging of objects from model sand.</span></span></span></span></span></span></span></span></span></span></span></p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.