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4,563 results for “correlations”
Melanin-based ornament darkness positively correlates with across-season nutritional condition
Sexually dimorphic ornamental traits are widely regarded as indicators of nutritional condition. However, variation of nutritional condition outside the reproductive and the ornament production seasons has rarely been considered, although it affects the generality of information content, especially for ornaments that may be used across the year. We measured several indicators of migratory and moult condition in male and female blackcaps (Sylvia atricapilla) during their autumn migration, and quantified their crown reflectance. We detected robust correlations between migratory and moult condition indices, and the correlation structure was similar in the two sexes. Furthermore, the across-season measure of body condition was positively related to the darkness of the black crown in males, while being unrelated to reflectance traits of the reddish crown in females. Our results reinforce the possibility that some melanin-based ornaments may be year-round indicators of individual quality via their dependence on nutritional condition.
Figure 4 from: Caterino MS, Tishechkin AK (2016) Spatial and environmental correlates of species richness and turnover patterns in European cryptocephaline and chrysomeline beetles. ZooKeys 557: 59-77. https://doi.org/10.3897/zookeys.557.7087
Figure 4 - Female genitalia, Megalocraerus rubricatus. A 8th tergite, dorsal view B 8th sternite, ventral view C Bursa copulatrix (bc), common oviduct (co), spermatheca (st) and attached spermathecal gland (stg) D Ovipositor.
Figure 3 from: Caterino MS, Tishechkin AK (2016) Spatial and environmental correlates of species richness and turnover patterns in European cryptocephaline and chrysomeline beetles. ZooKeys 557: 59-77. https://doi.org/10.3897/zookeys.557.7087
Figure 3 - Male genitalia, Megalocraerus rubricatus. A 8th tergite, dorsal view B 8th sternite, dorsal view C 8th tergite and sternite, lateral view, in situ D 9th and 10th tergites, dorsal view E 9th sternite, dorsal view F Aedeagus, dorsal view G Tegmen, lateral view.
Figure 6 from: Caterino MS, Tishechkin AK (2016) Spatial and environmental correlates of species richness and turnover patterns in European cryptocephaline and chrysomeline beetles. ZooKeys 557: 59-77. https://doi.org/10.3897/zookeys.557.7087
Figure 6 - Aedeagi of Megalocraerus spp. A Megalocraerus mandibularis, dorsal view B Megalocraerus mandibularis, lateral view C Megalocraerus chico, dorsal view D Megalocraerus chico, lateral view E Megalocraerus madrededios, dorsal view F Megalocraerus madrededios, lateral view G unnamed Megalocraerus sp. from Rio de Janeiro, dorsal view H unnamed Megalocraerus sp. from Rio de Janeiro, lateral view.
Figure 1 from: Caterino MS, Tishechkin AK (2016) Spatial and environmental correlates of species richness and turnover patterns in European cryptocephaline and chrysomeline beetles. ZooKeys 557: 59-77. https://doi.org/10.3897/zookeys.557.7087
Figure 1 - Generic characters of Megalocraerus. A Frons B Antenna C Mouthparts, ventral view (one maxilla and labial palpus omitted for clarity).
Figure 5 from: Caterino MS, Tishechkin AK (2016) Spatial and environmental correlates of species richness and turnover patterns in European cryptocephaline and chrysomeline beetles. ZooKeys 557: 59-77. https://doi.org/10.3897/zookeys.557.7087
Figure 5 - A Dorsal habitus Megalocraerus mandibularis B Mandibles male Megalocraerus mandibularis C Dorsal habitus Megalocraerus chico.
Figure 2 from: Freijeiro A, Baselga A (2016) Spatial and environmental correlates of species richness and turnover patterns in European cryptocephaline and chrysomeline beetles. In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Research on Chrysomelidae 6. ZooKeys 597: 81–99. https://doi.org/10.3897/zookeys.597.6792
Figure 2 - Partitioning of the variation (%) in species richness (a, b) and species composition (c, d) among groups of explanatory sets (A=area, E=environment and S=spatial variables) for European Cryptocephalinae (left column: a, c) and Chrysomelinae (right column: b, d).
Figure 1 from: Freijeiro A, Baselga A (2016) Spatial and environmental correlates of species richness and turnover patterns in European cryptocephaline and chrysomeline beetles. In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Research on Chrysomelidae 6. ZooKeys 597: 81–99. https://doi.org/10.3897/zookeys.597.6792
Figure 1 - Patterns of variation in species richness (a, b), hierarchical clustering based in βsim (c, d) and mapping of 4 major clusters (e, f) for cryptocephalines (left column: a, c, e) and chrysomelines (right column: b, d, f). Colours correspond to the 4 major clusters. Countries' abbreviations follow those of Löbl and Smetana (2010).
Figure 3 from: Freijeiro A, Baselga A (2016) Spatial and environmental correlates of species richness and turnover patterns in European cryptocephaline and chrysomeline beetles. In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Research on Chrysomelidae 6. ZooKeys 597: 81–99. https://doi.org/10.3897/zookeys.597.6792
Figure 3 - Distance decay of similarity with spatial distance in Northern Europe (solid dots, solid line) and southern Europe (hollow dots, dashed line) for cryptocephalines (a, blue), chrysomelines (b, red) and longhorn beetles (c, green). The density plots in (d) show the distribution of 1000 bootstrap replicates of the distance decay slopes (solid lines: northern Europe, dashed lines: southern Europe, colours corresponding to a, b, and c).
Table S2. Enhancer-gene correlation framework
<p>Outcome of all enhancer-gene correlations with FDR < 0.05</p>
Data files for "Stripe correlations in the two-dimensional Hubbard-Holstein model" by S. Karakuzu et al.
<p>Data files for the manuscript "Stripe correlations in the two-dimensional Hubbard-Holstein model" by S. Karakuzu et al. To appear in Communications Physics. Preprint available at https://arxiv.org/abs/2205.15464 (2022).</p> <p>This work was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Award Number<br> DE-SC0022311.</p>
Correlation analysis between TGF-beta signaling-related score and cancer hallmarks
<p>Correlation analysis between TGF-beta signaling-related score and cancer hallmarks</p>
The data of COVID-19 and their correlation with wind speed
<p>In 2020 the world was presently burdened with the COVID-19 pandemic. World Health Organization confirms 34,874,744 cases with 1,097,497 deaths (case fatality rate (CFR) 3.1%) were reported in 216 countries. In Indonesia, the number of people who have been infected and the number who have died are approximately 287,008 and 10,740 (CFR 3.7%), respectively, with the most predominant regions being Jakarta (73,700), East Java (43,536) and Central Java (22,440). Many factors can increase the transmission of COVID-19. One of them is wind speed. This data set contains covid-19 data in DKI Jakarta from June 2020 until August 2022 and wind speed in daily power point form. This data can be analyzed to see the correlation between wind speed and the COVID-19 cases.</p>
Thesis: Morphological disparity across clades: Correlates, limitations and alternatives – Chapter 6: What determines disparity in avian clades?
<p><span>Morphological disparity is an aspect of avian evolution that remains understudied and has rarely been quantified explicitly, despite its importance for inferring patterns of avian evolution. </span><span>Morphological and molecular data are now routinely used both in combination and in isolation to infer phylogeny and to study evolutionary rates. Similarly, parallel studies of phylogeny, diversity and morphological disparity are now commonplace in both the neontological and palaeontological literature </span><span>(Giribet, 2015; Bromham et al., 2002; Hopkins and Gerber, 2017; Deline et al., 2018; Prum et al., 2015)</span><span>. </span><span>Most recently, the concept of molecular disparity has been introduced as an analogue of morphological disparity</span>, alt<span>hough there are few studies that attempt to deploy it </span><span>(Deline et al., 2018; van den Ende et al., 2022)</span><span>. This chapter addresses ten related questions using the largest available morphological and molecular data set for birds. </span></p>
Data for: Ground nesting in passerine birds: Evolution, biogeography and life history correlates
<p>Nest location is one of the key components of avian reproduction and sharp transitions between different nest location strategies may have profound ecological and evolutionary consequences. Here, we used a phylogenetically-informed comparative framework to reconstruct the evolution of ground nesting behaviour in passerine birds, quantify its biogeographical and habitat variation, and test for its associations with life history traits. Our dataset comprised over 1600 species distributed worldwide and representing ca. 90% of all extant passerine families. Our analyses revealed a scattered phylogenetic distribution and moderate phylogenetic signal in the occurrence of ground nesting in passerines. We also found relatively high forward and backward transitions rates between character states of ground and non-ground nesting, indicating strong evolutionary lability. Non-ground nesting was identified as a likely ancestral state at the root of passerine phylogeny. Occurrence of ground nesting was clearly associated with habitat variation, as open habitats generally supported greater proportion of ground nesting species than non-open habitats (forests). Within the major habitat categories we found greater proportion of ground nesters in boreal and temperate than subtropical and tropical zones. This reflected a general latitudinal gradient in the occurrence of ground nesting, with higher proportion of ground nesting species at higher latitudes (especially at the northern hemisphere). Ground nesting was also associated with fast life histories, as ground nesters had larger clutches, shorter incubation periods and faster chick development rates than non-ground nesters. This variation was possibly driven by higher predation rates on nestlings and adult birds in ground nesting species. Our study lays a foundation for a comprehensive understanding of mechanisms and processes that have driven macroevolution of ground nesting behaviour in the most species-rich extant avian lineage.</p>
SNS Feature Correlations for Personality Identification
<p>blinded for review</p>
Figs 17, 18 in Scorpions of the Brandberg Massif, Namibia: Species richness inversely correlated with altitude
Figs 17, 18. Adult males, habitus in life: (17) Hadogenes tityrus (Simon, 1888); (18) Opistophthalmus carinatus (Peters, 1861).
Figs 19, 20 in Scorpions of the Brandberg Massif, Namibia: Species richness inversely correlated with altitude
Figs 19, 20. Opistophthalmus adult males, habitus in life: (19) O. lamorali Prendini, 2000; (20) O. jenseni (Lamoral, 1972).
Correlations between monthly values for fungal CFU and air pollutants.
<p>Correlations between monthly values for fungal CFU and air pollutants.</p>
SPRS Total Correlation clustering
<p>Total Correlation calculated using the Total Correlation Explanation algorithm<a href="https://www.zotero.org/google-docs/?FBcmlE"> </a>(CorEx), which is an optimization technique that identifies latent variables to explain the dependence in the data.</p>
ScienceDex guides
Understand access before you commit
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.