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DATASET: Facet-Dependent Formation and Adhesion of Au Oxide and Nanoporous Au on Poly-Oriented Au Single Crystals
<p>This project contains all the data shown in the manuscript or SI titled 'Facet-Dependent Formation and Adhesion of Au Oxide and Nanoporous Au on Poly-Oriented Au Single Crystals' (doi:10.26434/chemrxiv-2023-nf7v3). For each figure, a folder was created in which the corresponding data can be found.</p>
Fig 5 in Species Diversity Of Wetland Birds, Depending On Area, Overgrowth Of Water Bodies On The Example Of Sovskie Ponds (Ukraine)
Fig 5. Percentage of species under conditions of overgrowth of a reservoir with macrophytes, a - 5% overgrowth, b - 90% overgrowth, c - 45% overgrowth, d - 55% overgrowth, e - 65% overgrowth.
FIGURE 12 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 12. Three-dimensional models visualizing the sequence of the wear stages (A-E) for the m1 of Pliospalax. Occlusal view. (1) anterosinusid, (2) protosinusid, (3) sinusid, (4) posterosinusid, (5) mesosinusid.
FIGURE 11 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 11. Three-dimensional model visualizing the sequence of the wear stages (11.1-11.9) for the left m1 of Spalax microphthalmus (REG 22729) from Hungary. Labial and occlusal view. The scale bars apply to all panels of the figure.
FIGURE 6 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 6. Three-dimensional model visualizing the sequence of the wear stages (6.1-6.12) for the m1 of Pliospalax tourkobouniensis (TB1-901), from the locality of Tourkobounia-1 in Greece (De Bruijn and Van der Meulen, 1975). Labial and occlusal view. The scale bars apply to all panels of the figure.
FIGURE 5 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 5. Three-dimensional model visualizing the sequence of the wear stages (5.1-5.9) for the holotype (m1) of Pliospalax tourkobouniensis (TB1 481), from the locality of Tourkobounia-1 in Greece (De Bruijn and Van der Meulen, 1975). Labial and occlusal view. The scale bars apply to all panels of the figure.
FIGURE 2 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 2. Three-dimensional model visualizing the sequence of the wear stages (2.1-2.12) for the m1 of Pliospalax macoveii (ACA 859) from the locality of Çalta in Turkey (Şen, 1977). Labial and occlusal view. Inverted figure of the specimen. The scale bars apply to all panels of the figure.
FIGURE 3 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 3. Three-dimensional model visualizing the sequence of the wear stages (3.1-3.12) for the right m1 of Pliospalax macoveii (ACA 881) from the locality of Çalta in Turkey (Şen, 1977). Labial and occlusal view. Inverted figure of the specimen. The scale bars apply to all panels of the figure.
FIGURE 8 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 8. Three-dimensional model visualizing the sequence of the wear stages (8.1-8.9) for the right m1 of Spalax microphthalmus (REG 22726) from Romania. Labial and occlusal view. Inverted figure of the specimen. The scale bars apply to all panels of the figure.
FIGURE 10 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 10. Three-dimensional model visualizing the sequence of the wear stages (10.1-10.12) for the right m1 of Spalax microphthalmus (REG 22729) from Hungary. Labial and occlusal view. Inverted figure of the specimen. The scale bars apply to all panels of the figure.
FIGURE 9 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 9. Three-dimensional model visualizing the sequence of the wear stages (9.1-9.9) for the left m1 of Spalax microphthalmus (REG 22726) from Romania. Labial and occlusal view. The scale bars apply to all panels of the figure.
FIGURE 4 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 4. Three-dimensional model visualizing the sequence of the wear stages (4.1-4.12) for the left m1 of Pliospalax macoveii (ACA 881) from the locality of Çalta in Turkey (Şen, 1977). Labial and occlusal view. The scale bars apply to all panels of the figure.
FIGURE 7 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 7. Three-dimensional model visualizing the sequence of the wear stages (7.1-7.12) for holotype (m1) of Pliospalax sotirisi (MR 1286) from Maritsa, in Greece (De Bruijn et al., 1970). Inverted figure of the specimen. The scale bars apply to all panels of the figure.
FIGURE 1 in Wear-dependent molar morphology in hypsodont rodents: The case of the spalacine Pliospalax
FIGURE 1. Three-dimensional model visualizing the sequence of the wear stages (1.1-1.15) for the m1 of Pliospalax macoveii (ACA 858), from the locality of Çalta in Turkey (Şen, 1977). Labial and occlusal view. The scale bars apply to all panels of the figure.
Data for: Environment-dependent relationships between corticosterone and energy expenditure during reproduction: insights from seabirds in the context of climate change
<p>We studied the relationship between baseline levels of the steroid hormone corticosterone and daily energy expenditure (DEE) in the little auk (<em>Alle alle</em>), an Arctic sea bird that is experiencing mounting energetic challenges due to climate change. We specifically investigated the hypothesis that there might be environment-dependent relationships between baseline corticosterone, DEE, time activity budgets, diving behavior and fitness-related traits (chick provisioning rate, adult body condition). Furthermore, we also examined whether mercury (Hg) contamination might interfere with corticosterone production, and hence potentially the capacity to upregulate DEE. In addition, we performed a phylogenetically controlled analysis across breeding seabird species to assess the relationship between baseline corticosterone and DEE, which we estimated via <span>a model derived from a phylogenetically controlled meta-analysis, </span><span>available within a <span>web-based app (‘Seabird FMR Calculator’, </span></span><span><a href="https://ruthedunn.shinyapps.io/seabird_fmr_calculator/"><span>https://ruthedunn.shinyapps.io/seabird_fmr_calculator/</span></a></span><span>) (Dunn et al. 2018). These datasets contain information on corticosterone levels, DEE, TABs and Hg in little auks, and the data used in our phylogenetically controlled analysis. Please see the READ me file for details.</span></p>
Data from: The importance of biotic interactions in distribution models of wild bees depends on the type of ecological relations, spatial scale and range
<p>Studies have found that biotic information can play an important role in shaping the distribution of species even at large scales. However, results from species distribution models are not always consistent among studies, and the underlying factors that influence the importance of biotic information to distribution models, are unclear. 2. We studied wild bees and plants, and cleptoparasite bees and their hosts in the Netherlands to evaluate how the inclusion of their biotic interactions affects the performance of species distribution models. We assessed model performance through spatial block cross-validation and by comparing models with interactions to models where the interacting species were randomized. Finally, we evaluated how, (i) spatial resolution, (ii) taxonomic rank (genus or species), (iii) degree of specialization, (iv) distribution of the biotic factor, (v) bee body size and (vi) type of biotic interaction, affect the importance of biotic interactions in shaping the distribution of wild bee species using generalized linear models. 3. We found that the models of wild bees improved when the biotic factor was included. The model performance improved the most for parasitic bees. Spatial resolution, taxonomic rank, distribution range of the biotic factor, and degree of specialization of the modelled species all influenced the importance of the biotic interaction to the models. 4. We encourage researchers to include biotic interactions in species distribution models, especially for specialized species and when the biotic factor has a limited distribution range. However, before adding the biotic factor we suggest considering different spatial resolutions and taxonomic ranks of the biotic factor. We recommend using single species or genus data as a biotic factor in the models of specialist species and for the generalist species, we recommend using an approximate measure of interactions, such as flower richness.</p>
Density dependence maintains long-term stability despite increased isolation and inbreeding in the Florida Scrub-Jay
<p>Isolation caused by anthropogenic habitat fragmentation can destabilize populations. Populations relying on the inflow of immigrants can face reduced fitness due to inbreeding depression as fewer new individuals arrive. Empirical studies of the demographic consequences of isolation are critical to understanding how populations persist through changing conditions. We used a 34-year demographic and environmental dataset from a population of cooperatively-breeding Florida Scrub-Jays (<em>Aphelocoma coerulescens</em>) to create mechanistic models linking environmental and demographic factors to population growth rates. We found that the population has not declined despite both declining immigration and increasing inbreeding, owing to a coinciding response in breeder survival. We find evidence of density-dependent immigration, breeder survival, and fecundity, indicating that interactions between vital rates and local density play a role in buffering the population against change. Our study elucidates the impacts of isolation on demography and how long-term stability is maintained via demographic responses.</p>
Figure 3 in Size-dependent sex allocation in Solanum lycocarpum St. Hil. (Solanaceae)
Figure 3. Proportion of male and hermaphrodite flowers as a function of plant size (small group versus large group).
Figure 2 in Size-dependent sex allocation in Solanum lycocarpum St. Hil. (Solanaceae)
Figure 2. Number of flowers per plant as a function of the plant size. The number of flowers in smaller group (minimum = 0.000; maximum = 36.00; mean = 5; median = 10.6; standard error = 2.54) versus in larger group (minimum = 3.00; maximum = 54.00; mean = 29.00; median = 30.00; standard error = 3.51).
Figure 4 in Size-dependent sex allocation in Solanum lycocarpum St. Hil. (Solanaceae)
Figure 4. Interaction between the floral attributes according to the flowers gender. The circles represent hermaphrodite flowers and the squares represent male flowers. (A) Corolla diameter (cm) versus anther size (cm); (B) Flower Biomass versus anther size (cm).
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.