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9,882 results for “Scale”
Data for "Plant trait-environment relationships in tundra are consistent across spatial scales"
<p>These data and code are associated with the publication Rissanen et al. (2023) "<strong>Plant trait-environment relationships in tundra are consistent across spatial scales</strong>" published in Ecography (doi:10.1111/ecog.06397). Modelling data are provided separately for each scale and contain community weighted mean traits and environmental variables. Raster stacks of the spatially continuous environmental predictors were used to produce spatial predictions of trait variation at each scale. </p> <p>Provided R codes were used to model trait-environment relationships at the local (LOC), regional (REG) and subcontinental (SUB) scale. The data and analyses are described in the linked publication. The data should be sited properly.</p> <p> </p>
Improving rainfall forecast at the district scale over the eastern Indian region using deep neural network
<p>The code contains ANN and CNN models.</p>
FIG. 4 in Small scale habitat preferences of Myotis daubentonii, Pipistrellus pipistrellus, and potential aerial prey in an upland river valley
FIG. 4. Relationship between aerial insect number (pooled for altitude and all habitat types) with air temperature (r² = 0.092)
F. 7 in Small scale habitat preferences of Myotis daubentonii, Pipistrellus pipistrellus, and potential aerial prey in an upland river valley
F. 7. Bat activity expressed as 0 ± SD bat passes hr-1 in relation to habitat type (water state) of both M. daubentonii and IG P. pipistrellus, pooled for all four altitudes
FIG. 6 in Small scale habitat preferences of Myotis daubentonii, Pipistrellus pipistrellus, and potential aerial prey in an upland river valley
FIG. 6. Percentage of most prevalent aerial insects found during the 40 nights of sweep net sampling along river Wharfe. Samples been pooled for altitude and habitat type. Insect families represented by <0.1 % not shown
FIG. 3 in Small scale habitat preferences of Myotis daubentonii, Pipistrellus pipistrellus, and potential aerial prey in an upland river valley
FIG. 3. Mean ± SD of number of aerial insects caught with sweep net above water surface (and over grass = control), pooled for all four altitudes (n = 40 nights)
FIG. 5 in Small scale habitat preferences of Myotis daubentonii, Pipistrellus pipistrellus, and potential aerial prey in an upland river valley
FIG. 5. Relationship between numbers of aerial insects caught with a sweep net (pooled for all altitudes and habitat types) above the water surface with minimum wind speed
FIG. 2 in Small scale habitat preferences of Myotis daubentonii, Pipistrellus pipistrellus, and potential aerial prey in an upland river valley
FIG. 2. Wind direction (degrees) expressed as windroses at for 10 nights from highest (a) to lowest (d) altitudes along river Wharfe
Trait-based and multi-scale approach provides insight on responses of freshwater mussels to environmental heterogeneity
<p>Our understanding of the factors driving the distribution of metacommunities at different scales can be obscured by high variation in species composition between sites and a lack of fine-scale distribution data. Trait-based approaches have long been used to better identify and examine ecological patterns. Most recent studies of riverine metacommunities examining trait-based patterns have focused on shorter-lived organisms. Here we focused on a group of longer-lived, sedentary riverine organisms, unionid freshwater mussels. The objective of this study was to examine how (1) the distribution of mussels with different life history strategies (trait-based approach) and (2) the relative importance of environmental and spatial factors (as a proxy for dispersal) would differ with spatial scale and position in the river; and to (3) further compare this with patterns derived from a taxonomic approach. Fine-scale distribution data of mussels and environmental factors were collected every 100 m in spatially extensive surveys in an up- and downstream segment (200 sites/20 km-segment) of a semi-arid river, making them some of the most spatially intensive surveys documented to date. A combination of redundancy analysis, asymmetric eigenvector mapping, and variation partitioning analyses revealed that more variation was explained by environmental factors where more environmental differences occur between sites. Where environmental heterogeneity was lower the amount of variation explained by smaller-scale spatial factors was higher, likely mostly associated with stochastic rather than dispersal processes. A higher amount of unexplained variation at the taxonomic level suggests that stochasticity may also play an important role in determining species composition. In contrast, different life history groups had a highly predictable distribution pattern driven by environmental heterogeneity, especially between river segments and mesohabitat, which was associated with different flow conditions. The role we predict for environmental heterogeneity and stochasticity in shaping the distribution of mussels in our study river likely also applies to other taxa and ecosystems at a spatial scale at which neither dispersal limitation nor mass effects occur. Thus, understanding the magnitude and extent of dispersal relative to the amount of environmental heterogeneity may be key for predicting metacommunity structure and dynamics for different organisms.</p>
Fig. 3.—Nonmetric multidimensional scaling ordination for the 4 in Effects of fire on small mammal communities in frequent-fire forests in California
Fig. 3.—Nonmetric multidimensional scaling ordination for the 4 habitat variables (overstory cover, oak tree cover, shrub cover, and fire severity index) and elevation and the 11 most commonly captured mammal species in 10 burned and 10 unburned sites from April to July 2004 and 2005 in Yosemite National Park, California. Only variables with a r ≥ 0.7 or the environmental variable with the highest r for that axis (i.e., fire severity r = −0.41 and oak tree cover r = 0.51) are listed on each axis. The R2 was 0.09 and 0.77 for axis 1 and 2, respectively, for a cumulative total of 0.86. The mammal species codes represent the following: CALA, Callospermophilus lateralis; GLSA, Glaucomys sabrinus (r = 0.73 on axis 1); MIXX, Microtus sp.; NEQU, Neotamias quadrimaculatus (r = −0.71 on axis 2); NESP, N. speciosus (r = −0.67 on axis 1); OTBE, Otospermophilus beecheyi; PEBO, Peromyscus boylii; PEMA; P. maniculatus (r = −0.88 on axis 2); SCGR, Sciurus griseus (r = 0.68 on axis 1); SOXX, Sorex sp.; TADO, Tamiasciurus douglasii.
FIGURE 6 in A new genus and species of the scale insect family Qinococcidae (Hemiptera: Coccomorpha) from China
FIGURE 6. Third-instar nymph of Abrococcus cunninghamia Zheng & Wu sp. n.: A. Antenna; B. Clypeolabral shield and labium; C. Labium; D. Sclerotized apodeme; E. Thoracic spiracle; F. Sieve-like multilocular disc pores; G. Abdominal spiracles; H. Tube-like spiracles; I. Anal ring; J. Simple pores; K. Multilocular disc pores; L. Short spine.
FIGURE 3 in A new genus and species of the scale insect family Qinococcidae (Hemiptera: Coccomorpha) from China
FIGURE 3. Adult female of Abrococcus cunninghamia Zheng & Wu sp. n.: A. Antenna; B. Dorsum of antennal segments I and II; C. Campaniform sensillum; D. Sensory seta; E. Distal segment of antenna; F. Eye; G. Clypeolabral shield and labium; H. Fore leg; I. Capitate seta; J. Claw; K. Thoracic spiracle; L. Abdominal spiracles; M. Sieve-like multilocular disc pore; N. Tubelike spiracles; O. Anal ring; P. Vulva; Q. Cicatrix; R. Multilocular disc pores; S. Large simple pore; T. Short hair-like seta; U. Small simple pore; V. Convergent small simple pores; W. Bilocular pore; X. Long hair-like seta; Y. Short spine.
FIGURE 4 in A new genus and species of the scale insect family Qinococcidae (Hemiptera: Coccomorpha) from China
FIGURE 4. First-instar nymph of Abrococcus cunninghamia Zheng & Wu sp. n.: A. Antenna; B. Clypeolabral shield and labium; C. Labium; D. Fore leg with an apodemal sclerotized bar; E. Thinner bar on dorsum; F. Thoracic spiracle; G. Abdominal spiracle; H. Multilocular disc pore with 7 central loculi; I. Multilocular disc pores, each with 3–5 central loculi; J. Sieve-like multilocular disc pores; K. Quadrilocular and trilocular pores; L. Short spine.
FIGURE 5 in A new genus and species of the scale insect family Qinococcidae (Hemiptera: Coccomorpha) from China
FIGURE 5. Second-instar nymph of Abrococcus cunninghamia Zheng & Wu sp. n.: A. Antenna; B. Clypeolabral shield and labium; C. Sclerotized apodeme; D. Thoracic spiracle; E. Abdominal spiracles; F. Tube-like spiracle; G. Simple pores; H. Multilocular disc pores, each with 4 or 5 central loculi; I. Short spine.
FIGURE 2 in A new genus and species of the scale insect family Qinococcidae (Hemiptera: Coccomorpha) from China
FIGURE 2. Adult female of Abrococcus cunninghamia Zheng & Wu sp. n.: A. Dorsum; B. Venter. Scale bars all = 1 mm.
FIGURE 1 in A new genus and species of the scale insect family Qinococcidae (Hemiptera: Coccomorpha) from China
FIGURE 1. Habitus photograph of Abrococcus cunninghamia Zheng & Wu sp. n.: A. Adult female; B. First-instar nymph, scale bar = 0.5 mm; C. Live third-instar female nymphs; D. Ventral view of third-instar female nymph; E. Part of fore wing of adult male, arrows indicate circular sensoria; F. Cuticular reticulum on fore wing; G. Habitat; H. Third-instar nymphs under the bark.
Distributive plural/singular cross-linguistic data – Likert-scale and forced-choice data
<p>Forced-choice: Our survey contains 15 pairs of sentences to be compared (languages: English, Czech, German, Polish). The sentences are indicated in the initial row (full case in A2, short notation in next columns). In each pair of sentences, we asked the participant to indicate the variant that seemed "better" or "more natural" to them. The following rows contain the choices made by each of the 30 participants. Rarely have both variants been chosen by a single participant.</p> <p>Likert scale: 50 participants were asked to rate the sentences given in column 2. The participants were explicitly asked to not evaluate the content or reliability of the sentences. Answers of the participants are given in the following rows. The answers mean: 1 (very unnatural/unacceptable); 2 (somewhat unnatural/weird); 3 (hard to say); 4 (quite natural/acceptable); 5 (fully natural/acceptable). The columns marked purple contain the test sentences, whereas the sentences in blue columns contain filler sentences. </p>
Viral genomes, functional genes, and microbial genomes of 144 activated sludge samples taken from 54 WWTPs across 13 countries on a global scale
<p>The study dataset contains 85,114 viral genomes, 1,115,185 viral functional genes, and 3,823 microbial genomes obtained from 54 WWTPs across 13 countries. </p><p>If this study dataset is useful, please cite: Fan, X., Ji, M., Mu, D. <i>et al.</i> Global diversity and biogeography of DNA viral communities in activated sludge systems. <i>Microbiome</i> <strong>11</strong>, 234 (2023). https://doi.org/10.1186/s40168-023-01672-1</p>
Diversity of Expertise is Key to Scientific Impact: a Large Scale Analysis in the Field of Computer Science
<p><strong>This repository is companion to a research paper with the following abstract:</strong></p> <p>Understanding the relationship between the composition of a research team and the potential impact of their research papers is crucial as it can steer the development of new science policies for improving the research enterprise. Numerous studies assess how the characteristics and diversity of research teams can influence their performance across several dimensions: ethnicity, internationality, size, and others. In this paper, we explore the impact of diversity in terms of the authors’ expertise and skills. To this purpose, we retrieved 114K papers in the field of Computer Science and analysed how the diversity of research fields within a research team relates to the number of citations their papers received in the upcoming 5 years. The results show that two different metrics reflecting the diversity of expertise are directly associated with the number of citations. This suggests that, at least in Computer Science, diversity of expertise is key to scientific impact.</p>
Supplementary data to "Small-scale variation prevails in the cell shape patterning of green microalgae belonging to the genus Micrasterias (Zygnematophyceae, Viridiplantae)"
<p>The supplementary data consist of 24 TPS files including the landmark coordinates of 12 Micrasterias datasets (two separate digitisations for each dataset). In addition, the R script used for the analyses described in the paper submitted to "Evolutionary Biology" and the utility file with factors for Procrustes ANOVA are also included.</p> <p> </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.