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opencc-by-4.0Oct 2024View details →

MESA (r11701) models with convective turnover times

$\texttt{MESA r11701}$ (<a title="r11701 release paper" href="https://ui.adsabs.harvard.edu/abs/2019ApJS..243...10P/abstract" target="_blank" rel="noopener">Paxton et al. 2019</a>) stellar models in the range 0.08 - 1.3 $\rm M_{\odot}$ with a metallicity of $\rm Z_{\odot}$ (as according to <a href="https://ui.adsabs.harvard.edu/abs/2009ARA%26A..47..481A/abstract" target="_blank" rel="noopener">Asplund et al. 2009</a>) and no rotation. These models are part of a study on convective turnover times accepted to ApJ and available to read here: <a href="https://ui.adsabs.harvard.edu/abs/2024arXiv241020000G/abstract" target="_blank" rel="noopener">Gossage et al. 2024</a>.   <ul> <li>$\texttt{MESA r11701}$ may be downloaded here: <a href="https://zenodo.org/records/2665077" target="_blank" rel="noopener">https://zenodo.org/records/2665077</a></li> <li>The associated $\texttt{MESA SDK}$ may be found here: <a href="http://user.astro.wisc.edu/~townsend/static.php?ref=mesasdk-old#linux-download" target="_blank" rel="noopener">old release archive</a> (compiled under $\texttt{GCC version 8.3.0}$)</li> </ul>   <h3>Models and inlists</h3> The compressed archive files $\texttt{MESA_run_directories_to_XGyr.tar.gz}$ contain run directories for our models evolved up to $\texttt{X}$ Gyrs (1, 5, or 14). Each directory within has a name corresponding to the model's initial mass (e.g., with $\texttt{00101M_dir}$ corresponding to a 1.01 $\rm M_{\odot}$ model) and contains the inlist (called $\texttt{inlist_project}$) used for that run. Each directory contains a subdirectory called $\texttt{LOGS}$ that contains the run's output (stellar profiles and histories in this case). The stellar profiles are available at approximately 1 Myr, 1 Gyr, 5 Gyr and 14 Gyr, when possible. Every $\texttt{LOGS}$ directory should contain a $\texttt{final_profile.data}$ file which is the stellar profile at the final simulation step of that run. These models were produced to study the variation of the convective turnover time, according to mixing length theory (as according to <a href="https://ui.adsabs.harvard.edu/abs/1965ApJ...142..841H/abstract" target="_blank" rel="noopener">Henyey et al. 1965</a>) in 1D stellar evolution. In the history files, the convective turnover times provided are (in units of seconds): <ol> <li>$\texttt{conv_env_turnover_time_l_hp}$, calculated one half of a (local) pressure scale height from the bottom of the convection zone (BCZ), or core in fully convective stars. This calculation corresponds to the values cited in <a href="https://arxiv.org/abs/2410.20000" target="_blank" rel="noopener">Gossage et al. 2024</a>.</li> <li>$\texttt{conv_env_turnover_time_l_hp_mid}$ at one pressure scale height from the BCZ</li> <li>$\texttt{conv_env_turnover_time_l_hp_hi}$ at two pressure scale heights from the BCZ</li> <li>$\texttt{conv_env_turnover_time_l_hp_hi2}$ at four pressure scale heights from the BCZ</li> <li>$\texttt{conv_env_turnover_time_l_hp_hi3}$ at eight pressure scale heights from the BCZ</li> <li>$\texttt{conv_env_turnover_time_l_b}$ at half pressure scale height from the BCZ, as calculated and adopted in <a href="https://ui.adsabs.harvard.edu/abs/1985ApJ...299..286G/abstract" target="_blank" rel="noopener">Giliand et al. 1985</a></li> <li>$\texttt{conv_env_turnover_time_l_t}$ at one pressure scale height from the BCZ (calculated in same manner as <a href="https://ui.adsabs.harvard.edu/abs/1985ApJ...299..286G/abstract" target="_blank" rel="noopener">Giliand et al. 1985</a>)</li> <li>$\texttt{conv_env_turnover_time_g}$ a "global" convective turnover time, calculated as a running sum of local distances divided by convective velocities (computed cell-wise)  through the outer convection zone of the model</li> </ol> The quantities 1-5 above are scaled by the $\texttt{inlist}$ parameter $\texttt{x_ctrl(15)}$, which is set to 0.5 by default. <h3>$\texttt{MESA src (run_star_extras.f90)}$ and other files </h3> Our $\texttt{run_star_extras.f90}$ file is provided as well. Several additional files may be needed, such as reaction networks (these are as in $\texttt{MIST v1.2}$, <a href="https://ui.adsabs.harvard.edu/abs/2016ApJ...823..102C/abstract" target="_blank" rel="noopener">Choi et al. 2016</a>) that may be downloaded here: <a href="https://waps.cfa.harvard.edu/MIST/resources.html" target="_blank" rel="noopener">https://waps.cfa.harvard.edu/MIST/resources.html</a>. Our $\texttt{run_star_extras.f90}$ file is also based on that used in the $\texttt{MIST v1.2}$ models, but with some additions.  <h3>Observational Data</h3> The compiled observational data used in our study is recorded in literature_sample.csv. This data is comprised of observations from several sources: <ul> <li><a href="https://ui.adsabs.harvard.edu/abs/2024ApJ...967L..36S/abstract" target="_blank" rel="noopener">Stassun & Kounkel 2024</a></li> <li><a href="https://ui.adsabs.harvard.edu/abs/2011ApJ...743...48W/abstract" target="_blank" rel="noopener">Wright et al. 2011</a></li> <li><a href="https://ui.adsabs.harvard.edu/abs/2022ApJ...931...45N/abstract" target="_blank" rel="noopener">Nunez et al. 2022</a></li> <li><a href="https://ui.adsabs.harvard.edu/abs/2024A%26A...684A...9S/abstract" target="_blank" rel="noopener">Shan et al. 2024</a></li> <li><a href="https://ui.adsabs.harvard.edu/abs/2019A%26A...628A..41P/abstract" target="_blank" rel="noopener">Pizzocaro et al. 2019</a></li> <li><a href="https://ui.adsabs.harvard.edu/abs/2022AN....34320049M/abstract" target="_blank" rel="noopener">Magaudda et al. 2022</a></li> <li><a href="https://ui.adsabs.harvard.edu/abs/2012A%26A...546A.117G/abstract" target="_blank" rel="noopener">Gondoin 2012</a></li> <li><a href="https://ui.adsabs.harvard.edu/abs/2018MNRAS.479.2351W/abstract" target="_blank" rel="noopener">Wright et al. 2018</a></li> <li><a href="https://ui.adsabs.harvard.edu/abs/2013A%26A...556A..14G/abstract" target="_blank" rel="noopener">Gondoin 2013</a></li> <li><a href="https://ui.adsabs.harvard.edu/abs/2016Natur.535..526W/abstract" target="_blank" rel="noopener">Wright & Drake 2016</a></li> </ul> The csv contains the cross-match with Gaia DR3 (<a href="https://ui.adsabs.harvard.edu/abs/2016A%26A...595A...1G/abstract" target="_blank" rel="noopener">Gaia Collaboration et al. 2016</a>; <a href="https://ui.adsabs.harvard.edu/abs/2023A%26A...674A...1G/abstract" target="_blank" rel="noopener">Gaia Collaboration et al. 2023</a>), and we removed duplicated sources which had the same X-ray measurement.

opencc-zeroNov 2023View details →

Data from: The mechanism of promoting rhizosphere nutrient turnover for arbuscular mycorrhizal fungi attribute to recruited functional bacterial assembly

Symbiosis with arbuscular mycorrhizal (AM) fungi improves plant nutrient capture from the soil, yet there is limited knowledge about the diversity, structure, functioning, and assembly processes of AM fungi-related microbial communities. Here, 16S rRNA gene sequencing and metagenomic sequencing were used to detect bacteria in the rhizosphere of Lotus japonicus inoculated with and without AM fungi, and the L. japonicus mutant ljcbx (defective in symbiosis) inoculated with AM fungi in southern grassland soil. Our results show that AM symbiosis significantly increased bacterial diversity and promoted deterministic processes of bacterial community construction, suggesting that mycorrhizal symbiosis resulted in the directional enrichment of bacterial communities and established a stable rhizosphere bacterial community. AM fungi promoted the enrichment of nine bacteria, including Ohtaekwangia, Niastella, Gemmatimonas, Devosia, Sphingomonas, Novosphingobium, Opitutus, Lysobacter, Brevundimonas, which are positively correlated with NPK-related parameters. Through a functional identification experiment, we found that six of these genera, including Brevundimonas, Lysobacter, Ohtaekwangia, Sphingomonas, Devosia, and Gemmatimonas, demonstrated the ability to mineralize organophosphate and dissolve inorganic phosphorus, nitrogen, and potassium. Our study revealed that AM fungi can regulate rhizosphere bacterial community assembly and attract specific rhizosphere bacteria to promote soil nutrient turnover in southern grasslands.

opencc-zeroDec 2023View details →

Rates of species turnover across elevation vary with vertical stratum in rainforest ant assemblages

Climatic variation at local scales can influence both exposure and sensitivity of organisms and thereby scale up to influence population persistence and community composition across broader geographic extents. Tropical forest canopies are more climatically dynamic than the understorey. Consequently, the niche space of forest canopies has higher overlap in thermal conditions along elevation gradients, which imposes less of a climatic barrier to arboreal species than their ground-dwelling counterparts. We use ant communities of the Australian Wet Tropics to test the prediction that ground communities should have higher rates of species turnover over elevation compared to arboreal communities. We sampled ground and arboreal ants along elevation gradients at a bioregional scale that includes four mountain sub-regions. We assessed community composition at three spatial resolutions (regional, elevation, vertical) and then calculated beta diversity (species turnover) over elevation for ground and arboreal communities using null modelling procedures to compare different-sized species pools. Vertical niche affinity was a strong contributor to overall biogeographic patterns; indicated by a strong interaction between vertical niche and elevation in beta diversity models. On average, the ground community exhibited a pronounced elevational distance-decay pattern while the arboreal community showed no pattern. Mean species turnover was 36% higher in ground than arboreal communities. Our findings suggest that the vertical niche has a pronounced effect on biogeographic patterns which has important implications for understanding the role of local scale climate conditions in shaping communities and for potential responses to future climate change.

opencc-zeroFeb 2024View details →

Data from: Rapid turnover of a pea aphid superclone mediated by thermal endurance in central Chile

Global change drivers are imposing novel conditions on Earth's ecosystems at an unprecedented rate. Among them, biological invasions and climate change are of critical concern. It is generally thought that strictly asexual populations will be more susceptible to rapid environmental alterations due to their lack of genetic variability and, thus, of adaptive responses. In this study, we evaluated the persistence of a widely distributed asexual lineage of the alfalfa race of the pea aphid, Acyrthosiphon pisum, along a latitudinal transect of approximately 600 Km in central Chile after facing environmental change for a decade. Based on microsatellite markers, we found an almost total replacement of the original aphid superclone by a new variant. Considering the unprecedented warming that this region has experienced in recent years, we experimentally evaluated the reproductive performance of these two A. pisum lineages at different thermal regimes. The new variant exhibits higher rates of population increase at warmer temperatures, and computer simulations employing a representative temperature dataset suggest that it might competitively displace the original superclone. These results support the idea of a superclone turnover mediated by differential reproductive performance under changing temperatures.

opencc-zeroFeb 2024View details →

Data from: The effect of drainage on the fine root biomass, production, and turnover in hemiboreal old-growth forests on organic soils

Information on the capacity of organic soils to capture and store carbon in old-growth forests in the hemiboreal forest zone is scarce and fragmented. However, fine root data can provide valuable insights into soil carbon fluxes. Thus, the aim of the current study was to provide estimates of the fine root biomass (FRB), fine root production (FRP), and fine root turnover (FRT) rate by tree species and other functional groups in old-growth (stand age 131–179 years) forests on mesotrophic organic soils dominated by Scots pine (Pinus sylvestris L.), with (drained mesotrophic organic soil) and without (undrained mesotrophic organic soil) the effects of forest drainage. The sequential soil coring method was used to estimate the FRB and FRP. The total FRB (sum of the FRB of all functional groups) was significantly higher in the undrained sites (6.8±0.3 t ha 1) than in the drained sites (3.97±0.1 t ha 1). The FRB of Scots pine in the undrained forest was significantly higher (1.7±0.1 t ha 1) than in the drained forest (0.5±0.1 t ha 1), supporting an extensive foraging strategy. The significantly higher mean FRB of Norway spruce (Picea abies [L.] Karst.) (1.4±0.1 t ha 1) in the drained sites than the undrained sites (0.7±0.2 t ha-1) can be explained by there being a higher proportion of spruce in the stand compositions, thus a higher standing volume (cubic meters per hectare) of this species and an increased FRB. The FRB of dwarf shrubs (2.43±0.2 t ha-1) formed the largest part of the total FRB in the undrained sites and the second largest (1.16±0.1 t ha-1), following Norway spruce, in the drained sites. The total FRP was similar between the undrained (2.05±0.31 t ha-1 yr-1) and drained (1.82±0.26 t ha-1 yr-1) stands. However, considerable variability in the FRP was observed between different sites of the same forest site type. The FRT rate of Scots pine was twice as high in the drained sites than the undrained sites, suggesting faster nutrient and carbon input into the drained soil compared to the undrained soil. Estimates of FRB, FRP, and FRT rate for different functional groups can be used in carbon-cycle modeling and in further calculations to estimate the carbon budget (balance) in forests on organic soils.

opencc-by-4.0Nov 2024View details →

Dataset of the publication: Accelerating water oxidation - a mixed Co/Fe polyoxometalate with improved turnover characteristics

Dataset of the publication: Accelerating water oxidation - a mixed Co/Fe polyoxometalate with improved turnover characteristics DOI: 10.1039/d3sc04002j J. Soriano-López, F.W. Steuber, M. Mulahmetovci, M. Besora, J.M. Clemente-Juan, M. O'Doherty, N.-Y. Zhu, C.L Hill, E. Coronado, J.M. Poblet, W. Schmitt Chem. Sci. 14, 47, 13722-13733 (2023)

opencc-zeroNov 2021View details →

Data from: Drivers of global pre-industrial patterns of species turnover in planktonic foraminifera

Anthropogenic climate change is altering global biogeographical patterns. However, it remains difficult to quantify how bioregions are changing because pre-industrial records of species distributions are rare. Marine microfossils, such as planktonic foraminifera, are preserved in seafloor sediments and allow the quantification of bioregions in the past. Using a recently compiled data set of pre-industrial species composition of planktonic foraminifera in 3802 worldwide seafloor sediments, we employed multivariate and statistical model-based approaches to study spatial turnover in order to 1) quantify planktonic foraminifera bioregions and 2) understand the environmental drivers of species turnover. Four latitudinally banded bioregions emerge from the global assemblage data. The polar and temperate bioregions are bi-hemispheric, supporting the idea that planktonic foraminifera species are not limited by dispersal. The equatorial bioregion shows complex longitudinal patterns and overlaps in sea surface temperature (SST) range with the tropical bioregion. Compositional-turnover models (Bayesian bootstrap generalised dissimilarity models) identify SST as the strongest driver of species turnover. The turnover rate is constant across most of the SST gradient, showing no SST threshold values with rapid shifts in species composition, but decelerates above 25°C, suggesting SST is less predictive of species composition in warmer waters. Other environmental predictors affect species turnover non-linearly, and their importance differs across regions. In the Pacific ocean, net primary productivity below 500 mgC m−2 day−1 drives fast compositional change. Water depth values below 3000 m (which affect calcareous microfossil preservation) increasingly drive changes in species composition among death assemblages in the Pacific and Indian oceans. Together, our results suggest that the dynamics of planktonic foraminifera bioregions are expected to be highly responsive to climate change; however, at lower latitudes, environmental drivers other than SST may affect these dynamics.

opencc-by-4.0Dec 2013View details →

Fig. 1 MapshowingtherangeofthestudypopulationofEasternImperialEaglesinHungaryandthelocationofsampledandnotsampledterritoriesin 2003 in High Turnover Rate Revealed By Non-Invasive Genetic Analyses In An Expanding Eastern Imperial Eagle Population

Fig. 1 MapshowingtherangeofthestudypopulationofEasternImperialEaglesinHungaryandthelocationofsampledandnotsampledterritoriesin 2003 (35 ofthe 61 nesting

opencc-by-4.0Dec 2013View details →

Fig. 2 in High Turnover Rate Revealed By Non-Invasive Genetic Analyses In An Expanding Eastern Imperial Eagle Population

Fig. 2. Firstidentification (1999, territorycodeBS-02) andre-identification (2003, BS-03) of afemale. Theterritorieswereapproximately 10 kmawayfromeachotherandtheoriginal BS-02 territorywasvacantin 2001-2002, butitwasoccupiedbyapairwithanewfemale in 2003; differentmarkingsrepresentdifferentgeneticallytaggedfemales, blackmarkings representthenestsfromtheBS-02 territory, greymarkingsrepresentnestsfromtheBS-03 territory; yearsinitalic (nestsmarkedbycircles) representnestingsiteswithoutsamples.

opencc-by-4.0Oct 2021View details →

Input data and Supplementary Results for "Turnover in life-strategies recapitulates marine microbial succession colonizing model particles"

README This page contains processed input data used for downstream analysis and some Supplementary Results for the paper: Pascual-García, A., Schwartzman, J., Enke, T.N., Iffland-Stettner, A., Cordero, O.X., Bonhoeffer, S., Turnover in life-strategies recapitulates marine microbial succession colonizing model particles (2022).   Input data   <ul> <li> File “count_table.ESV.biom”: Table containing the abundance of each Exact Sequence Variant (ESV) in the different samples (biom format). </li> <li> File “count-table_metagenomes_KEGGs.L3.spf”. Table containing the abundances of genes found in the shotgun metagenomics experiments annotated in KEGG and then aggregated into classes according to the finest classification in KEGG's hierarchy (level 3). This is a tsv-formatted file that can be directly used in STAMP to perform statistical analysis (spf format). </li> <li> File “count-table_PICRUST2_KEGGs.L3.spf”. Table containing the abundances of genes predicted with PICRUSt v2. These genes were annotated in KEGG and aggregated into classes according to the finest hierarchy in KEGG (level 3). This is a tsv-formatted file that can be directly used in STAMP to perform statistical analysis (spf format). </li> <li> File “count-table_Isolates_KEGGs.L3.spf”. Table containing the abundances of genes found in the isolates genomes that were annotated in KEGG and aggregated into classes according to the finest classification in KEGG's hierarchy (level 3). This is a tsv-formatted file that can be directly used in STAMP to perform statistical analysis (spf format). </li> <li> File “samples_metadata.tsv”. Metadata table describing the samples. </li> <li> File “isolates_metadata.tsv”. Metadata table describing the isolates, it includes shallow phylogenetic levels and a categorical identifier describing the environmental preference estimated for the ESV having a 100% sequence identity with a ZINB-GLM. </li> <li> File “sequences.ESV.fasta”. File containing the Exact Sequence Variants fasta. </li> </ul> Supplementary Materials   <ul> <li> File “qiime2_visualizations.zip”. A file containing visualizations compatible with the qiime2 viewer (simply drag and drop the file in <a href="https://view.qiime2.org/">https://view.qiime2.org/</a>) for each sample or combination of samples, labelled as `$substrate.$medium.$replicate`, where `$medium = {Beads, Seawater}`  and `$replicate = {A,B,C}`. If the label is not present for one field, it means that all samples are aggregated for that field e.g.: <ul> <li> “count_table.ESV.Chitosan.Beads.A.bar-plots.qzv” Contains the replicate experiment A for communities on the synthetic beads in chitosan. </li> <li> “count_table.ESV.Chitosan.bar-plots.qzv” Contains all samples in chitosan (both seawater communities and the three replicates of communities on the beads). </li> </ul> </li> <li> File “README.odt”. This readme in libreoffice format. </li> <li> File “Genome_deposition_information.xlsx”. NCBI identifiers for the isolates’ genomes. </li> <li> File "barcodes_to_samples_MGRAST.xlsx". Contains the barcodes of each sample and its metadata as it was deposited in MG-RAST. In a second tab, there is a subset of samples with a low number of reads that MG-RAST analyzed together, generating a single entry (termed "mixed"). </li> <li> Access to raw an processed metagenomes and analysis are provided through MG-RAST following [this link](<a href="https://www.mg-rast.org/mgmain.html?mgpage=project&project=mgp85635">https://www.mg-rast.org/mgmain.html?mgpage=project&project=mgp85635</a>). <ul> <li> As of May 30th, 2022, there are two issues with the dataset in MG-RAST which are out of our scope to solve. We will report any update here. The first problem is related to the entry TCCTGAGC-GTAAGGAG-s_2_, which does not load in MG-RAST. These are very low samples and were discarded in most analyses. In addition, you will find in the metadata 17 metagenomes that do not belong to our project. </li> </ul> </li> </ul>

FIG. 35. — A in Vertebrate paleobiodiversity of the Early Cretaceous (Berriasian) Angeac-Charente Lagerstätte (southwestern France): implications for continental faunal turnover at the J/K boundary

FIG. 35. — A, Relative abundance of Angeac-Charente large vertebrate taxa based on identified macroremains collected from 2010 to 2017. White numbers indicate the Minimum Number of Individuals (MNI) (after Rozada et al. 2021); B, Relative abundance of Angeac-Charente taxa, based on microremains collected in 2017, by water screen-washing (diameter of mesh = 0.8 mm), at the base of the unit 3, of the R3 plot.

FIG. 31 in Vertebrate paleobiodiversity of the Early Cretaceous (Berriasian) Angeac-Charente Lagerstätte (southwestern France): implications for continental faunal turnover at the J/K boundary

FIG. 31. — Reconstruction of the Angeac Ornithomimosaur, based on 3D surface scans of 232 bones. All the bones of the 3D reconstruction were scaled on the basis of a 40 cm long femur.

FIG. 34 in Vertebrate paleobiodiversity of the Early Cretaceous (Berriasian) Angeac-Charente Lagerstätte (southwestern France): implications for continental faunal turnover at the J/K boundary

FIG. 34. — Trechnotherian mammal teeth from the Berriasian of Angeac-Charente: A, B, left lower molar of Spalacotherium evansae Ensom & Sigogneau-Russell, 2000 (ANG M-26) in occlusal (A) and lingual (B) views; C, D, left lower molar (m1 or?m2) of Dryolestidae indet. (ANG M-05) in occlusal (C) and linguodistal (D) views; E, F, left lower molar (m6 or?m7) of Dryolestidae indet. (ANG M-01) in occlusal (E) and mesial (F) views; G-I, left lower molar (m3?) of Peramus sp. (ANG M-25) in occlusal (G) labial (H) and lingual (I) views. Scale bars: 400 µm.

FIG. 33 in Vertebrate paleobiodiversity of the Early Cretaceous (Berriasian) Angeac-Charente Lagerstätte (southwestern France): implications for continental faunal turnover at the J/K boundary

FIG. 33. — Multituberculate mammal teeth from Angeac-Charente: A, B, left p4 of Pinheirodontidae indet. (ANG M-72) in lingual (A) and labial (B) views; C, D, left P1 of Pinheirodontidae indet. (ANG M-03) in occlusal (C) and distolingual (D) views; E, F, right P2 of Pinheirodontidae indet. (ANG M-06) in occlusal (E) and lingual (F) views; G, H, left P3 of Pinheirodontidae indet. (ANG M-22) in occlusal (G) and lingual (H) views; I, J, left?P4 of Sunnyodon sp. (ANG M-04) in occlusal (I) and labial (J) views; K, L, left?P5 of Multituberculata indet. (ANG M-106) in mesio-occlusal (K) and occluso-labial (L) views; M, N, left?m2 of Pinheirodontidae indet. (ANG M- 105) in occlusal (M) and labial (N) views; O, P, right M2 of Pinheirodontidae indet. (ANG M-32) in occlusal (O) and lingual (P) views. Scale bar: A, B, 1 mm; C, D, 750 µm; E-P, 500 µm.

FIG. 28 in Vertebrate paleobiodiversity of the Early Cretaceous (Berriasian) Angeac-Charente Lagerstätte (southwestern France): implications for continental faunal turnover at the J/K boundary

FIG. 28. — Theropod teeth from Angeac-Charente: A-C, Archaeopterygid tooth (ANG M-09) in lingual (A) and labial (B, C) views; D, Archaeopterygid tooth (ANG M-08) in lingual view; E, F, cf. Nuthetes sp. (ANG M-45) in lingual (E) and distal (F) views; G, cf. Nuthetes sp. (ANG M-61) in lingual view; H, tooth of Tyrannosauroidea indet. (ANG17-5342) in lingual view; I, J, tooth of Tyrannosauroidea indet. (ANG M-73) in lingual (I) and distal (J) views; K, Megalosauridae? indet. (ANG17 R-1748) in lingual view (J); L, M, Megalosauridae? indet. (ANG17-5650) in labial (L) and (M) lingual views; N, Megalosauridae? indet. (ANG M-121) in lingual view. Scale bar: A, B, 1 mm; C-F, 400 µm; G, 5 mm; H-N, 1 cm.

FIG. 23 in Vertebrate paleobiodiversity of the Early Cretaceous (Berriasian) Angeac-Charente Lagerstätte (southwestern France): implications for continental faunal turnover at the J/K boundary

FIG. 23. — Thyreophoran remains from Angeac-Charente: A, B, ankylosaur maxillary tooth (ANG15-3980) in lingual (A) and labial (B) views; C, ankylosaur osteoderm (ANG18-6585) in dorsal view; D, E, dentary tooth of Dacentrurus sp. (ANG M-14) in labial (D) and lingual (E) views; F, axis of Dacentrurus sp. (ANG18-6203) in ventral view; G, anterior cervical vertebra of Dacentrurus sp. (ANG12-1878) in ventral view; H, reconstructed cervical series of Dacentrurus sp. (ANG16-6748, ANG16-4660, ANG12-1749, ANG14-3202, ANG14-2912, ANG14-3094) in ventral view; I, J, dorsal vertebra of Dacentrurus sp. (ANG18-6548) in anterior (I) and right lateral (J) views. Scale bars: A, B, 5 mm; C, D, 2.5 mm; E, 2.5 cm; F-J, 5 cm.

FIG. 32 in Vertebrate paleobiodiversity of the Early Cretaceous (Berriasian) Angeac-Charente Lagerstätte (southwestern France): implications for continental faunal turnover at the J/K boundary

FIG. 32. — Mammal teeth from Angeac-Charente: A, B, premolariform or molariform tooth of Gobiconodon? sp. (ANG M-21) in occlusal (A) and labial (B) views; C, D, premolariform tooth of Mammalia indet. (ANG M-34) in lingual (C) and labial (D) views; E, F, left lower molar of Triconodon sp. (ANG M-02) in lingual (E) and occlusal (F) views; G-I, left upper molar of Thereuodon cf. taraktes (ANG M-23) in labial (G), lingual (H) and occlusal (I) views. Scale bar: 500 µm.

FIG. 19 in Vertebrate paleobiodiversity of the Early Cretaceous (Berriasian) Angeac-Charente Lagerstätte (southwestern France): implications for continental faunal turnover at the J/K boundary

FIG. 19. — Crocodyliform remains from Angeac-Charente: A, B, tooth of Bernissartiidae indet. (ANG10-268) in lingual/labial (A) and occlusal (B) views; C, tooth of Bernissartiidae indet. (ANG10-76) in lingual/labial view; D, osteoderm of Atoposauridae? (ANG 10-167) in dorsal view; E, F, tooth of Pholidosaurus sp. (ANG11- 960) in labial (E) and mesial/distal (F) views; G, H, tooth of Pholidosaurus sp. (ANG11-883) in labial (G) and mesial/distal (H) views I, J, tooth of Pholidosaurus sp. (ANG10-369) in labial (I) and mesial/distal (J) views. Scale bar represents: A-C, 2 mm; D-J, 8 mm.

FIG. 18 in Vertebrate paleobiodiversity of the Early Cretaceous (Berriasian) Angeac-Charente Lagerstätte (southwestern France): implications for continental faunal turnover at the J/K boundary

FIG. 18. — Goniopholidid crocodyliform Angeac-Charente: A, D, left dentary of Goniopholis sp. (ANG18-5925) in dorsal (A) and ventral (D) views; B, C, skull of Goniopholis sp. (ANG18-5914, ANG18-5920, ANG18-5921) in dorsal (B) and ventral (C) views. Scale bar: 10 cm.

FIG. 15 in Vertebrate paleobiodiversity of the Early Cretaceous (Berriasian) Angeac-Charente Lagerstätte (southwestern France): implications for continental faunal turnover at the J/K boundary

FIG. 15. — Scincomorph lizard remains from Angeac-Charente: A-C, fragment of left dentary of cf. Paramacellodus sp. (ANG M-20) in lingual (A), labial (B) and distal (C) views; D-F, osteoderms of Scincomorpha indet., ANG M-46 (D), ANG M-49 (E), ANG M-58 (F) in dorsal view. Scale bar: 500 µm.