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FIG. 3 in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 3. — Phylogram generated by Maximum Likelihood analysis based on combined sequence data of nrLSU, mtSSU and rpb2 for Russula boddingii Hembrom, D.Chakr., A.Ghosh & K.Das, sp. nov., R. pseudoflavida A.Ghosh, Hembrom, I.Bera & Buyck, sp. nov. and R. shoreae D.Chakr., A.Ghosh, K.Das & Buyck, sp. nov. and their allied species. Maximum Likelihood bootstrap support values (MLbs) ≥ 70% are shown on the left of "/" and Bayesian Posterior Probabilities (BPP) ≥ 0.95 are shown on the right above or below the branches at nodes. The new species are placed in red font to highlight their phylogenetic positions in the tree.
FIG. 5 in Three new species of genus Russula Pers. from Sal dominated forests of tropical India based on morphotaxonomy and multigene phylogenetic analysis
FIG. 5. — Russula boddingii Hembrom, D.Chakr., A.Ghosh & K.Das, sp. nov. (from holotype): A-D, fresh and dissected basidiomata in the field and basecamp; E, F, transverse section through pileipellis showing elements; G, transverse section through lamellae showing hymenial gloeocystidia near the lamellae edges; H, I, transverse section through lamellae showing hymenial gloeocystidia near the lamellae sides; J, transverse section through lamellae showing basidia. Scale bars: A, 40 mm; E, 100 μm; F-J, 10 μm.
Top-of-the-atmosphere radiative forcing by aerosol due to continuous OCS injection near the tropical tropopause simulated by EMAC
<p>This dataset was prepared for a publication by von Hobe et al. (2023):</p> <p><strong>Comment on “An approach to sulfate geoengineering with surface emissions of carbonyl sulfide” by Quaglia et al. (2022)</strong></p> <p>In that publication, the data are displayed in Figure 4.</p> <p>The dataset contains additional stratospheric aerosol forcing for injections of 6 Tg S a<sup>-1</sup> OCS for several years over 5 tropical cities at the tropopause (97 hPa) calculated with the EMAC (ECHAM5/MESSy Atmospheric Chemistry) CCM (e.g. Brühl et al., 2018; Schallock et al., 2023). Data are given for a four year time series starting in January 2017.</p> <p>- - - - - - - - - - - -</p> <p>File format:</p> <p> netCDF</p> <p>Index Variables:</p> <p> time, 10 hourly, as 'day since 1997-01-01' (note that the two variables named time4 and time6 are identical)</p> <p>Parameters:</p> <p> SOLFORCCSO: instantaneous solar radiative forcing at the top of the atmosphere by aerosol due to continuous OCS injection near the tropical tropopause with surface mixing ratios of OCS were fixed to observations</p> <p> TOTFORCCSO: instantaneous total radiative forcing at the top of the atmosphere by aerosol due to continuous OCS injection near the tropical tropopause with surface mixing ratios of OCS were fixed to observations</p> <p> SOLFORCCSO_FREE: instantaneous solar radiative forcing at the top of the atmosphere by aerosol due to continuous OCS injection near the tropical tropopause with surface mixing ratios of OCS allowed to increase from downward transport</p> <p> TOTFORCCSO_FREE: instantaneous total radiative forcing at the top of the atmosphere by aerosol due to continuous OCS injection near the tropical tropopause with surface mixing ratios of OCS allowed to increase from downward transport</p> <p>- - - - - - - - - - - -</p> <p><strong>References:</strong></p> <p>Brühl, C., Schallock, J., Klingmüller, K., Robert, C., Bingen, C., Clarisse, L., Heckel, A., North, P., and Rieger, L.: Stratospheric aerosol radiative forcing simulated by the chemistry climate model EMAC using Aerosol CCI satellite data, Atmos. Chem. Phys., 18, 12845-12857, 10.5194/acp-18-12845-2018, 2018</p> <p>Quaglia, I., Visioni, D., Pitari, G., and Kravitz, B.: An approach to sulfate geoengineering with surface emissions of carbonyl<br> sulfide, Atmos. Chem. Phys., 22, 5757-5773, 10.5194/acp-22-5757-2022, 2022.</p> <p>Schallock, J., Brühl, C., Bingen, C., Höpfner, M., Rieger, L., and Lelieveld, J.: Reconstructing volcanic radiative forcing since 1990, using a comprehensive emission inventory and spatially resolved sulfur injections from satellite data in a chemistry climate model, Atmos. Chem. Phys., 23, 1169-1207, 10.5194/acp-23-1169-2023, 2023.</p> <p>von Hobe, M., Brühl, C., Lennartz, S. T., Whelan, M. E., and Kaushik, A.: Comment on “An approach to sulfate geoengineering with surface emissions of carbonyl sulfide” by Quaglia et al. (2022) , EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-268, 2023.</p>
"Breath holding" as a thermoregulation strategy in the scalloped hammerhead, a deep-diving tropical ectothermic shark
<p>Fish moving between different thermal environments experience heat exchange via conduction through the body wall and convection from blood flow across the gills. Here we report a strategy of preventing convective heat loss at the gills during excursions into deep cold water by the tropical scalloped hammerhead shark (<em>Sphryna lewini</em>). Adult scalloped hammerhead sharks dive rapidly and repeatedly from warm (~26ºC) surface waters to depths exceeding 800 meters and temperatures as low as 5°C. Biologgers attached to adult sharks show that warm muscle temperatures were maintained throughout the deepest portion of each dive. Substantive cooling only occurred during the latter stages of the ascent phase, and once initiated, was rapid. Heat transfer coefficient modeling indicated that convective heat transfer was suspended, probably by suppressing gill function during deep dives. This previously unobserved strategy has broad similarities to marine mammal "breath hold" diving.</p>
Figure S50 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S50. Optimisation of tropical and temperate niches across the Mimosoid phylogeny. Ancestral niches were estimated using a complete metachronogram for Caesalpinioideae, including non-Mimosoid Caesalpinioideae taxa, but only the Mimosoid clade is shown here.
Figure S48 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S48. Speciation rates estimated across the Caesalpinioideae metachronogram under eight scenarios with different fixed extinction rates. Extinction rates are shown above each subfigure, while speciation rates are indicated by branch colours.
Figure S49 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S49. Top: Speciation rates in the Mimosoid clade through time, estimated under different extinction rate scenarios using BAMM. Middle: Paleotemperature inferred from delta O18 measurements, using data from Zachos et al. (179). Bottom: Phenogram of mean annual precipitation in the Mimosoid clade through time. Coloured lines with dots show the median, wettest, and driest reconstructed rainfall niche of all nodes in the phylogeny per time bin of one million years.
Figure S47 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S47. Ancestral range estimation of Caesalpinioideae, performed using BioGeoBEARS with the best-fitting model (i.e., DEC+J). Trans-oceanic dispersal events in the Mimosoid clade, based on a model with seven regions, are indicated with numbered green circles.
Figure S46 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S46. Optimisation of dry season length across the Mimosoid phylogeny. Inset shows the fraction of dry season length niche shifs per speciation event through time. See caption Figure 1 for explanation.
Figure S45 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S45. Variation partitioning results obtained using the genus-level Mimosoid phylogeny (rather than the metachronogram). See caption Figure 2 for explanation.
Figure S42 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S42. Phyloregionalization per continent using the metachronogram, showing global distribution of isohyets. Caption otherwise as for Figure 3.
Figure S30 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S30 (right). Conflict and concordance among the 821 single-copy gene trees for each bipartition mapped onto the single-copy genes ASTRAL species tree (Figure S14). Pie charts show the fraction of gene trees supporting that bipartition in blue, the fraction of gene trees supporting the most likely alternative configuration in green, the fraction of gene trees supporting additional conflicting configurations in red, and the fraction of uninformative gene trees in grey. Numbers above and below the pie charts indicate the total number of gene trees supporting and conflicting the bipartition, respectively. Branch lengths are set equal for easier visualisation.
Figure S22 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S22. Phylogeny of Caesalpinioideae. RAxML species tree based on the amino acid alignment of all genes with orthology assessment. Bootstrap support values are only shown for nodes with <100% bootstrap support.
Figure S27 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S27. Tanglegram comparing the PhyloBayes phylogeny (Figure S23) with the RAxML amino acid single-copy genes phylogeny (Figure S20).
Figure S37 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S37. Phyloregionalization of South America using the metachronogram. Subfigures show clustering results with two to eight phyloregions, as well as the results of phyloregionalization analyses using the geographic residuals of phylogenetic turnover, and ancient phylogenetic turnover with a cut-off of 5, 10, and 20 million years.
Figure S21 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S21. Phylogeny of Caesalpinioideae. RAxML species tree based on the amino acid alignment of all genes without orthology assessment. Bootstrap support values are only shown for nodes with <100% bootstrap support.
Figure S38 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S38. Phyloregionalization of Africa using the metachronogram. Subfigures show clustering results with two to eight phyloregions, as well as the results of phyloregionalization analyses using the geographic residuals of phylogenetic turnover, and ancient phylogenetic turnover with a cut-off of 5, 10, and 20 million years.
Figure S43 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S43. Climatic distinctiveness of phyloregions. Each subplot shows, for phyloregionalization analyses with two to eight phyloregions performed using the metachronogram, how many of the resulting phyloregions have statistically significant different climatic values from the other regions based on mean annual precipitation (P), precipitation seasonality (Pseas), and dry season length.
Figure S34 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S34. Metachronogram with the names and locations of all subtrees (coloured branches) that were grafed onto the phylogenomic backbone (black branches).
Figure S19 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S19. Phylogeny of Caesalpinioideae. RAxML species tree based on the nucleotide alignment of all genes with orthology assessment. Bootstrap support values are only shown for nodes with <100% bootstrap support.
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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)
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DANDI Archive for NWB datasets
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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.
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