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304 results for “scale pattern”
Figure 9 in Spatiotemporal patterns in marine fish and cephalopods communities across scales: using an autoregressive spatiotemporal clustering model. A study of fish and cephalopods of the Eastern English Channel
Figure 9. – Eastern English Channel absolute spatiotemporal community from low (blue) to high (red) median densities of numbers/ km2 in log scale for communities, AST522c1 (A), AST522c2 (B).
Figure 8 in Spatiotemporal patterns in marine fish and cephalopods communities across scales: using an autoregressive spatiotemporal clustering model. A study of fish and cephalopods of the Eastern English Channel
Figure 8. – Eastern English Channel spatiotemporal community from low (blue) to high (red) median densities of numbers/ km2 in log scale for communities ST522c1 (A), ST522c2 (B).
Figure S6 in Spatiotemporal patterns in marine fish and cephalopods communities across scales: using an autoregressive spatiotemporal clustering model. A study of fish and cephalopods of the Eastern English Channel
Figure S6. – Eastern English Channel spatiotemporal community from low (blue) to high (red) median densities of numbers/ km2 in log scale for communities ST782c1 (A), ST782c2 (B), ST1043c1 (C), ST1043c2 (D).
Figure S1 in Spatiotemporal patterns in marine fish and cephalopods communities across scales: using an autoregressive spatiotemporal clustering model. A study of fish and cephalopods of the Eastern English Channel
Figure S1. – Spatial correlation matrix at a 782 km2 (A) and 1043 km2 (B) scale displaying correlation from strongly negative (dark blue) to strongly positive (dark red).
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 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.
◂Fig. 3 Historically described phenotypical variations and yet undiscovered deviations in the plate pattern of P. volzii. b–c, f, i, l–m Light microscopy, a, d–e, g–h, k scanning electron microscopy. a–f Newly identified deviations a–b plate 4′′ pentagonal in strains a GeoM*793; b GeoM*788; c plate 2a split (strain GeoK*024); d plates 2′′ and 3′′ fused (strain GeoM*866); e plates 1′′′ and 1′′′′ fused (strain GeoM*788); f plates 1a and 3′ fused (strain GeoM*788). g–m Historic infraspecific taxa; g P. guestrowiense forma lineatum (strain GeoM*866); h P. guestrowiense forma compressum (strain GeoM*866); i P. guestrowiense subvar. originale (strain GeoK*024); k P. volzii var. cinctiforme (strain GeoM*793); l P. volzii var. simplex (strain GeoM*789); m P. volzii forma complexum (strain GeoM*793). Abbreviations: n′: apical plate, n′′: precingular plate, n′′′: postcingular plate, n′′′′: antapical plate, na: anterior intercalary plate, nC: cingular plate, split or fused plates are indicated by asterisks. Scale bar= 10 µm. U A= 15 kV in Morphological and molecular variability of Peridinium volzii Lemmerm. (Peridiniaceae, Dinophyceae) and its relevance for infraspecific taxonomy
◂Fig. 3 Historically described phenotypical variations and yet undiscovered deviations in the plate pattern of P. volzii. b–c, f, i, l–m Light microscopy, a, d–e, g–h, k scanning electron microscopy. a–f Newly identified deviations a–b plate 4′′ pentagonal in strains a GeoM*793; b GeoM*788; c plate 2a split (strain GeoK*024); d plates 2′′ and 3′′ fused (strain GeoM*866); e plates 1′′′ and 1′′′′ fused (strain GeoM*788); f plates 1a and 3′ fused (strain GeoM*788). g–m Historic infraspecific taxa; g P. guestrowiense forma lineatum (strain GeoM*866); h P. guestrowiense forma compressum (strain GeoM*866); i P. guestrowiense subvar. originale (strain GeoK*024); k P. volzii var. cinctiforme (strain GeoM*793); l P. volzii var. simplex (strain GeoM*789); m P. volzii forma complexum (strain GeoM*793). Abbreviations: n′: apical plate, n′′: precingular plate, n′′′: postcingular plate, n′′′′: antapical plate, na: anterior intercalary plate, nC: cingular plate, split or fused plates are indicated by asterisks. Scale bar= 10 µm. U A= 15 kV
Dataset used for the paper entitled: Large-scale water quality patterns across Portugal using a long-term nationwide dataset (1970-2024)
<p>This repository contains the dataset and plots generated for the paper described above, which are listed below</p> <ol> <li>Dataset: <ol> <li>Folder: dataset.zip</li> <li>File format: NPY (standard binary file format in NumPy/Python for NumPy arrays) </li> </ol> </li> <li>Plots: <ol> <li>Folder: HTML_plots.zip</li> <li>File format: HTML (for interactive exploring and broad accessibility)</li> </ol> </li> <li>Basins interception with Landuse: <ol> <li>Folder: basin_LU_intersect.zip</li> <li>File format: NPY (standard binary file format in NumPy/Python for NumPy arrays) </li> </ol> </li> </ol>
Figure 10 in Can hair width and scale pattern and direction of dorsal scapular mammalian hair be a relatively simple means to identify species?
Figure 10. Boxplot of 30 guard hair widths for each species including quartile ranges.
Figure 5 in Variation in elasmoid fish scale patterns is informative with regard to taxon and swimming mode
Figure 5. Principal components analysis (PC1 and PC2) of mean scale shapes in each area: A1, A2, A3, C1, C2, C3, P1, P2, P3 as defined in Fig. 1. A, Mugil cephalus; B, Mugil curema; C, Dicentrarchus labrax.
Figure 7 in Variation in elasmoid fish scale patterns is informative with regard to taxon and swimming mode
Figure 7. Specific swimming modes identified within body/caudal fin propulsion, based on the extended classification scheme (Lindsey, 1978) proposed by Breder (1926). Reprinted from Lindsey CC. Form, function and locomotory habits in Fish. Pages. 9 & 10, Figs 1 and 2. In: Hoar D, Randall DJ, eds. Fish Physiology. Vol. VII New York: Academic Press, Copyright (1978), with permission from Elsevier.
Figures 14-19 from: Simon E (2013) Preliminary study of wing interference patterns (WIPs) in some species of soft scale (Hemiptera, Sternorrhyncha, Coccoidea, Coccidae). ZooKeys 319: 269-281. https://doi.org/10.3897/zookeys.319.4219
Figures 14-19 - Males with "eliptical" patterns of WIPs, subfamily Eriopeltinae: 14, 15 WIP of Luzulaspis frontalis Green 16–17 WIP of Luzulaspis nemorosa Koteja. 18–19 WIP of Eriopeltis lichtensteini Signoret.
Figures 1-5 from: Simon E (2013) Preliminary study of wing interference patterns (WIPs) in some species of soft scale (Hemiptera, Sternorrhyncha, Coccoidea, Coccidae). ZooKeys 319: 269-281. https://doi.org/10.3897/zookeys.319.4219
Figures 1-5 - 1 General scheme of the fore wing (after Koteja 2008) acp-alar cupolae, afx-anterior flexing patch, alf-alar fold, alp-alar lobe, asfd-anterior subcostal field, ast-alar setae, clfd-claval (anal) field, cofd-costal field or thickening, cufd-cubital field, cur-cubital ridge, mat-macrotrichia, mit-microtrichia, pfx-posterior flexing patch, psfd-posterior subcostal field, ptst-pterostigma, rs-"radial sector", scr-subcostal ridge 2, 3 Pulvinaria vitis (Linnaeus): scanning electron microphotographs of the wing, showing its microsculpture 4, 5 Male of Pulvinaria vitis (Linnaeus) on white background, with invisible WIPs, and 2 on a black background, showing WIPs.
Figures 6-13 from: Simon E (2013) Preliminary study of wing interference patterns (WIPs) in some species of soft scale (Hemiptera, Sternorrhyncha, Coccoidea, Coccidae). ZooKeys 319: 269-281. https://doi.org/10.3897/zookeys.319.4219
Figures 6-13 - Males with "horizontally striped patterns" of WIPs, subfamilies Eulacaninae and Coccinae: 6–7 WIP of Sphaerolecanium prunastri (Boyer de Fonscolombe) 8–9 WIP of Eulecanium tiliae (Linnaeus) 10, 11 WIP of Pulvinaria vitis 12–13 WIP of Parthenolecanium corni (Bouché).
Data for: Properties of wing scales on butterflies with different distribution patterns
<p><span>Butterflies play a crucial role in understanding the spread of life due to their complex thermal adaptations. </span><span>The cooling capacity provided by wing scales</span><span> is a dominant factor associated with the ambient temperature of their habitats. </span><span>However, it remains unclear how the wing scale structure of butterflies varies to regulate cooling capacity and participate in shaping distribution patterns.</span></p> <p><span>Based on data acquired from quantitative measurements, rank sum and ANOVA tests were used to test whether the structure and cooling capacity of wing scales responded to butterfly distribution. Virtual simulations and Spearman tests were used to confirm the correlation between the structure and cooling capacity of wing scales. The response was first resolved using three representative species with gradient differences in distribution, and then macroscopically validated using 99 species</span><span> within</span><span> their phylogenetic framework, with a presampling control to exclude potential effects of taxonomic position, body size, and migratory behaviour.</span> <span>Both optical and thermal properties were used to measure the cooling capacity. Thermal data generated from specimens in different states were used to exclude the effects of other thermoregulatory pathways.</span></p> <p><span>The results show that the cooling capacity of butterfly wings decreases and becomes more homogeneous as the temperature of their habitat decreases. The decrease in cooling capacity is due to the decrease in maximum emissivity, while the homogenisation is due to both the decrease in maximum emissivity and the increase in minimum emissivity. Variation in cooling capacity is due to changes in the structure of wing scale, which homogenises as the habitat becomes colder. As butterflies generally spread from the tropics to temperate zones, it is inferred that the generation of a low overall cooling capacity through structural homogenisation of wing scales has supported the dispersal of butterflies.</span></p> <p><span>For the first time, we provide cascading evidence for the links between butterfly distribution, thermal adaptation, and functional morphology. We also highlight the role of structural homogenisation on the poikilothermic body surface in the adaptive process for dispersal. Further investigation using genetic information would be beneficial to resolve the mechanism behind thermal adaptation at a deeper level.</span></p>
Data from: Life history determines biogeographical patterns of soil bacterial communities over multiple spatial scales
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Data from: A theoretical foundation for multi-scale regular vegetation patterns
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Data from: Fine-scale vertical stratification and guild composition of saproxylic beetles in lowland and montane forests: similar patterns despite low faunal overlap
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Data for: Properties of wing scales on butterflies with different distribution patterns
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Data from: Using functional trait diversity patterns to disentangle the scale-dependent ecological processes in a subtropical forest
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Allen Brain Atlas
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International Brain Laboratory public data
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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.