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304 results for “scale pattern”
Emergence of a geometric pattern of cell fates from tissue-scale mechanics in the Drosophila eye
<p>Pattern formation of biological structures involves the arrangement of different types of cells in an ordered spatial configuration. In this study, we investigate the mechanism of patterning the <em>Drosophila</em> eye into a precise triangular grid of photoreceptor clusters called ommatidia. Previous studies had led to a long-standing biochemical model whereby a reaction-diffusion process is templated by recently formed ommatidia to propagate a molecular prepattern across the eye epithelium. Here, we find that the templating mechanism is instead, mechanical in origin; newly born columns of ommatidia serve as a template to spatially pattern cell flows that move the cells in the epithelium into position to form each new column of ommatidia. Cell flow is generated by a pressure gradient that is caused by a narrow zone of cell dilation precisely positioned behind the growing wavefront of ommatidia. The newly formed lattice grid of ommatidia cells are immobile, deflecting and focusing the flow of other cells. Thus, the self-organization of a regular pattern of cell fates in an epithelium is mechanically driven.</p>
FIG. 2 in Analysis of the diversity and distributional patterns of coleopteran families on a global scale
FIG. 2. Cluster analyses and corresponding regionalisation schemata based on (a) a streamlined but nevertheless fairly comprehensive dataset excluding very widespread families and family-poor ecoregions; (b) endemic-rich ecoregions only.
FIG. 1 in Analysis of the diversity and distributional patterns of coleopteran families on a global scale
FIG. 1. Global patterns of coleopteran family diversity and endemism. (a) family richness; (b) weighted endemism.
The first comprehensive revision of all the species attributed to Melomys led J. I. Menzies in 1996 to resurrect the genus Paramelomys and to redefine its morphologicallimits and species content. Menzies created P. gressitti as a new species belonging to a group displaying morphological similarities and including also P. lorentzii and P. moncktoni. Monotypic Distribution. E New Guinea. Descriptive notes. Head-body 135-162 mm, hindfoot 30-34 mm; no specific data are available for body weight. Gressitt's Mosaic-tailed Rat is a medium-sized Paramelomys with a soft, thick and woolly pelage, a long narrow foot, and a tail with three hairs per scale. It exhibits a medium-sepia dorsal pelage and a gray-buff ventral one. Tail is slightly shorter (99%) than head-body length. The skull has a narrow zygomatic plate. Habitat. Moist tropical mountain forest between 2300 m and 2400 m. Food and Feeding. No information. Breeding. No information. Activity patterns. Gressitt's Mosaic-tailed Rat is terrestrial. Movements, Home range and Social organization. No information. Status and Conservation. Classified as Endangered on The IUCN Red List owing to its small geographic range (less than 3500 km?*) and the destruction ofits habitat by mining and logging activities. The major threat to Gressitt's Mosaic-tailed Rat is ongoing habitat degradation caused by nearby human populations; habitat on Mount Kandy has been destroyed by gold-miners and wood-cutters. Bibliography. Menzies (1996). in Muridae
The first comprehensive revision of all the species attributed to Melomys led J. I. Menzies in 1996 to resurrect the genus Paramelomys and to redefine its morphologicallimits and species content. Menzies created P. gressitti as a new species belonging to a group displaying morphological similarities and including also P. lorentzii and P. moncktoni. Monotypic Distribution. E New Guinea. Descriptive notes. Head-body 135-162 mm, hindfoot 30-34 mm; no specific data are available for body weight. Gressitt's Mosaic-tailed Rat is a medium-sized Paramelomys with a soft, thick and woolly pelage, a long narrow foot, and a tail with three hairs per scale. It exhibits a medium-sepia dorsal pelage and a gray-buff ventral one. Tail is slightly shorter (99%) than head-body length. The skull has a narrow zygomatic plate. Habitat. Moist tropical mountain forest between 2300 m and 2400 m. Food and Feeding. No information. Breeding. No information. Activity patterns. Gressitt's Mosaic-tailed Rat is terrestrial. Movements, Home range and Social organization. No information. Status and Conservation. Classified as Endangered on The IUCN Red List owing to its small geographic range (less than 3500 km?*) and the destruction ofits habitat by mining and logging activities. The major threat to Gressitt's Mosaic-tailed Rat is ongoing habitat degradation caused by nearby human populations; habitat on Mount Kandy has been destroyed by gold-miners and wood-cutters. Bibliography. Menzies (1996).
How to enhance the inverse distance weighting method to detect the precipitation pattern in a large-scale watershed
<p>These datasets provide precipitation data over Central Plateau watershed of Iran. Four different variants of the Inverse Distance Weighting (IDW) method are utilized to create these datasets. Two out of four IDW variants are proposed and developed by the authors to enhance the performance of the available standard models.</p> <p> </p> <p>Data Format: xlsx</p> <p>Spatial Resolution: ~0.08˚ & 0.25˚</p> <p>Spatial Coverage: Central Plateau watershed, Iran (48˚07'E to 61˚25'E - 26˚33'N to 37˚27'N)</p> <p>Temporal Resolution: Monthly</p> <p>Temporal Coverage: 2005 - 2015 (Inclusively)</p> <p> </p> <p><strong>How to cite:</strong></p> <p><strong>Arash Ghomlaghi, Mohsen Nasseri & Bardia Bayat (2022): How to enhance the inverse distance weighting method to detect the precipitation pattern in a large-scale watershed, Hydrological Sciences Journal, DOI: 10.1080/02626667.2022.2124874</strong></p>
Continental scale α- and β-diversity patterns of terrestrial eukaryotic microbes: effect of climate and microhabitat on testate amoeba assemblages in Eurasian peatlands
Open the record for dataset details and reuse information.
Fig. 4 in Variability on microevolutionary and macroevolutionary scales: a review on patterns of morphological variation in Cnidaria Medusozoa
Fig. 4 Schematic summary of levels of morphological variation found in medusozoans, including the absence of variation (cryptic species). Clades indicate different lineages, colors and shades represent the phenotype in current time, and the circles represent individuals. Note that there is individual variation (arrows) and it can parallel intraspecific variation. The same occurs with interspecific variation, which can parallel intraspecific variation in b
Fig. 1 in Variability on microevolutionary and macroevolutionary scales: a review on patterns of morphological variation in Cnidaria Medusozoa
Fig. 1 Intracolony variation in Orthopyxis sargassicola (Nutting, 1915) based on three polyps randomly sampled from a single colony (MZUSP4079, see Online Resource 1). a Measurements (in μm) of total length of trophosome (Tr), length of pedicel (Pd), hydrothecal length (Hd), and diameter at margin (Diam); b measurements (in μm) of maximum perisarc (Ps) thickness (Thick) of hydrotheca and pedicel at medial portion, as well as maximum number of sinuosities (NS) in pedicel and number of hydrothecal cusps (NC); c, d polyps of O. sargassicola from a single colony (both polyps are at the same position of maximum perisarc thickness). Note the differences in size and shape of the pedicels (Pd) and hydrotheca (Hd), as well as the perisarc thickness (Ps) and sinuosities of the pedicel (S)
FIGURE 2. A–C. Austroblechnum lehmannii. A. Habit. B. Pinna and venation pattern. C. Rhizome scale. D–F. Austroblechnum organense. D. Habit. E. Pinna pair showing venation. F in The family Blechnaceae (Polypodiopsida) in Brazil: key to the genera and taxonomic treatment of Austroblechnum, Cranfillia, Lomaridium, Neoblechnum and Telmatoblechnum for southern and southeastern Brazil
FIGURE 2. A–C. Austroblechnum lehmannii. A. Habit. B. Pinna and venation pattern. C. Rhizome scale. D–F. Austroblechnum organense. D. Habit. E. Pinna pair showing venation. F. Rhizome scale. (A–C from A. Salino et al. 14054, BHCB; D–F from A.L. Gasper et al. 2658, BHCB).
FIGURE 5. A–C. Lomaridium plumieri. A. Habit. B. Basal pinnae showing venation pattern. C. Rhizome scale. D–F. Neoblechnum brasiliense. D. Habit. E in The family Blechnaceae (Polypodiopsida) in Brazil: key to the genera and taxonomic treatment of Austroblechnum, Cranfillia, Lomaridium, Neoblechnum and Telmatoblechnum for southern and southeastern Brazil
FIGURE 5. A–C. Lomaridium plumieri. A. Habit. B. Basal pinnae showing venation pattern. C. Rhizome scale. D–F. Neoblechnum brasiliense. D. Habit. E. Pair of basal pinnae showing venation. F. Rhizome scale. (A–C from F.S. Souza et al. 613, CESJ0052285; D–F from C. Kozera 3992, CESJ0062336, CESJ0062336_01).
FIGURE 4. A–C. Cranfillia mucronata. A. Habit. B. Pinna and venation pattern. C. Rhizome scale. D–F. Cranfillia caudata. D. Habit. E in The family Blechnaceae (Polypodiopsida) in Brazil: key to the genera and taxonomic treatment of Austroblechnum, Cranfillia, Lomaridium, Neoblechnum and Telmatoblechnum for southern and southeastern Brazil
FIGURE 4. A–C. Cranfillia mucronata. A. Habit. B. Pinna and venation pattern. C. Rhizome scale. D–F. Cranfillia caudata. D. Habit. E. Pair of basal pinnae showing venation. F. Rhizome scale. (A–C from F.S. Souza et al. 1482, BHCB; D–F from L.L. Giacomin et al. 1350, CESJ).
FIGURE 3. A–C. Austroblechnum penna-marina. A. Habit. B. Pinnae and venation pattern. C. Rhizome scale. D–F. Austroblechnum squamipes. D. Habit. E in The family Blechnaceae (Polypodiopsida) in Brazil: key to the genera and taxonomic treatment of Austroblechnum, Cranfillia, Lomaridium, Neoblechnum and Telmatoblechnum for southern and southeastern Brazil
FIGURE 3. A–C. Austroblechnum penna-marina. A. Habit. B. Pinnae and venation pattern. C. Rhizome scale. D–F. Austroblechnum squamipes. D. Habit. E. Base of blade showing pinnae and venation. F. Rhizome scale. (A–C from A. Salino et al. 14745, BHCB; D–F from A. Salino et al. 12036, CESJ).
Supplement to "Hydro-Meteorological Drivers of Event Runoff Characteristics Under Analogous Soil Moisture Patterns in Three Small-Scale Headwater Catchments"
<p>The dataset is a supplement to the manuscript "Hydro-Meteorological Drivers of Event Runoff Characteristics Under Analogous Soil Moisture Patterns in Three Small-Scale Headwater Catchments" and contains the processed time series data of the Wüstebach, Rollesbroich, and Petzenkirchen catchments. Hydro-metorological variables include precipitation, runoff, soil moisture, and groundwater level.</p>
Data from: Large scale patterns of marine diatom richness: drivers and trends in a changing ocean.
Aim Plankton diversity is a pivotal element of marine ecosystem stability and functioning. A major obstacle in the assessment of diversity is the lack of consistency between patterns assessed by molecular and morphological data. This work aims to reconcile the two in a single richness measure, to investigate the environmental drivers affecting such measure, and finally to predict its spatio-temporal patterns. Location & Time period This is a global-scale study, based on data collected within the 2009-2013 interval during the Tara Oceans expedition. Major taxa studied The focus of this study is diatoms. They play an important role in several biogeochemical cycles and within marine food webs, while displaying a high taxonomic and functional richness. Methods We integrate measures of diatom richness across the global ocean using molecular and morphological approaches, giving particular attention to the rare biosphere. We then perform a machine-learning-based analysis of these reconciled patterns to extrapolate diatom richness at the global scale and to identify the main environmental processes governing it. Finally, we model the response of diatom richness to climate change. Results By filtering out 0.3% of the rarest operational taxonomic units, molecular-based richness patterns show the best possible match with the morphological approach. Temperature, phosphate, chlorophyll a and the Lyapunov exponent are the major explainers of these reconciled patterns. Global scale predictions provide a first approximation of the global geography of diatom richness and of the possible impacts of climate change. Main conclusion Our models suggest that diatom richness is controlled by different processes characteristic of distinct environmental scenarios: lateral mixing in highly dynamic regions, and both nutrient availability and temperature elsewhere. We present herein the implications of these processes on richness and how these same implications differ from other diversity indices because of the main component of richness: the rare biosphere.
Figure 2 in Multi-scale patterns in the host specificity of plant-dwelling arthropods: the influence of host plant and temporal variation on species richness and assemblage composition of true bugs (Hemiptera)
Figure 2. Non-metric multi-dimensional scaling (MDS) ordination showing hemipteran composition for all sampling periods with selected plant species superimposed.
Figure 5 in Multi-scale patterns in the host specificity of plant-dwelling arthropods: the influence of host plant and temporal variation on species richness and assemblage composition of true bugs (Hemiptera)
Figure 5. Annual cyclic pattern of the proportion of the effectively specialized fauna (squares) and singleton species (circles) for the total number of hemipteran species from each sampling period.
Figure 3 in Multi-scale patterns in the host specificity of plant-dwelling arthropods: the influence of host plant and temporal variation on species richness and assemblage composition of true bugs (Hemiptera)
Figure 3. Mean number of individuals (from SIMPER analysis) of dominant hemipteran species, during each sampling period, for most plant species.
Figure 1 in Multi-scale patterns in the host specificity of plant-dwelling arthropods: the influence of host plant and temporal variation on species richness and assemblage composition of true bugs (Hemiptera)
Figure 1. Interactions between plant species sampled and sampling period for (A) abundance (number of individuals) per plant and (B) species richness per plant (standard error bars are shown).
Figure 6 in Multi-scale patterns in the host specificity of plant-dwelling arthropods: the influence of host plant and temporal variation on species richness and assemblage composition of true bugs (Hemiptera)
Figure 6. Relationship between the effectively specialized fauna (squares) and singleton species (circles) for the number of hemipteran species from each sampling period and for the entire collection. An exponential decay equation is fitted for effectively specialized fauna, y = 2.973∗ exp (−0.00575∗ x) + (−1.478), R2 = 0.7598, and for singleton species, y = 22.53∗exp (−0.08466∗x) + 0.2614, R2 = 0.9873.
Figure 5 in Landscape-scale surveys reveal patterns of floral visitation by species of Scarabaeidae (Coleoptera) in the Kruger National Park, South Africa
Figure 5. Adult of Pedinorrhina trivittata (Schaum) on flowers of Peltophorum africanum Sonder (Kruger National Park, South Africa).
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.