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Fig. 4 in Biodiversity of museum and bulk field samples compared: The Chiampo sponge fauna (Eocene, Lessini Mountains, Italy)

Fig. 4. Rarefaction curve (line in the middle) of the Chiampo sponge fauna at Lovara. Grey area demarcate 95% confidence intervals of diversity estimates.

Fig. 12 in Biodiversity of museum and bulk field samples compared: The Chiampo sponge fauna (Eocene, Lessini Mountains, Italy)

Fig. 12. In situ Eocene specimen of Laocoetis patula from Lovara Quarry, Italy; showing its characteristic morphology with canal openings in quadrate arrangement, indicated by the white arrow. Coin for scale is 22 mm in diameter.

Fig. 10 in Biodiversity of museum and bulk field samples compared: The Chiampo sponge fauna (Eocene, Lessini Mountains, Italy)

Fig. 10. Percent similarity (A) and Jaccard similarity (B) measurements between bulk and museum collection material at different taxonomic levels.

Fig. 3 in Biodiversity of museum and bulk field samples compared: The Chiampo sponge fauna (Eocene, Lessini Mountains, Italy)

Fig. 3. Bulk collection of Eocene sponges at Lovara Quarry. Some of the sponge specimens are indicated by white arrows.

Fig. 1 in Biodiversity of museum and bulk field samples compared: The Chiampo sponge fauna (Eocene, Lessini Mountains, Italy)

Fig. 1. Sponge fossils from the Eocene of Chiampo. A. The lyssacinosid Stauractinella eocenica Frisone, Pisera, and Preto, 2016. B. The lychniscosid Callicylix eocenicus Pisera and Busquets, 2002. C. The lithistid demosponge Platychonia sp. D. The hexactinosid Laocoetis patula Pomel, 1872. Scale bars 10 mm. Photos S. Castelli.

Fig. 6 in Using abundance data to assess the relative role of sampling biases and evolutionary radiations in Upper Muschelkalk ammonoids

Fig. 6. Percent similarity among bins averaged to 1 degree bins. A. om7 interval. B. om8 interval. C. om9 interval. The thicker the line, the greater the similarity between the two cells connected by the line.

Fig. 4 in Using abundance data to assess the relative role of sampling biases and evolutionary radiations in Upper Muschelkalk ammonoids

Fig. 4. Correlations between richness per map and number of localities. A. om7 interval. B. om8 interval. C. om9 interval. The gap in the distribution of points for the om8 interval highlights the discontinuity between a group of maps with few taxa at a few localities and other maps with a large number of localities and high richness.

Fig. 5 in Using abundance data to assess the relative role of sampling biases and evolutionary radiations in Upper Muschelkalk ammonoids

Fig. 5. Rarefaction curves for each interval, based on number of occurrences. The confidence envelope of the species richness for om9 departs significantly from those of om7 and om8 above 50 occurrences, but the significantly higher species−richness of om8 only becomes apparent at sample sizes of around 250 specimens, indicating that a few, rare taxa are boosting richness in the om8 interval.

Fig. 2 in Using abundance data to assess the relative role of sampling biases and evolutionary radiations in Upper Muschelkalk ammonoids

Fig. 2. Distribution of Muschelkalk ammonoid localities used in this study plotted on a map of modern Germany. The overall geographic spread of localities does not change greatly over time.

Fig. 3 in Using abundance data to assess the relative role of sampling biases and evolutionary radiations in Upper Muschelkalk ammonoids

Fig. 3. Correlations between richness per map and number of occurrences. A. om7 interval. B. om8 interval. C. om9 interval.

Fig. 1 in Using abundance data to assess the relative role of sampling biases and evolutionary radiations in Upper Muschelkalk ammonoids

Fig. 1. Chart of stratigraphic interval names and durations for the Muschelkalk of the Germanic Basin with ammonoid immigration events marked (simplified from Klug et al. 2005: fig. 1).

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Fig. 1 in A novel supermatrix approach improves resolution of phylogenetic relationships in a comprehensive sample of danthonioid grasses

Fig. 1. Geologic map of Florissant Fossil Beds National Monument in central Colorado, USA, modified from Evanoff et al. (2001: fig. 1). Areal extent of the Monument is outlined by thick gray line.

opencc-by-4.0Dec 2008View details →

Fig. 2 in A novel supermatrix approach improves resolution of phylogenetic relationships in a comprehensive sample of danthonioid grasses

Fig. 2. Talpid mammal Oreotalpa florissantensis gen. et sp. nov., FLFO 5813 (holotype), right dentary with m1–m3 from UCM locality 92179, Florissant Formation, Florissant Fossil Beds National Monument, Colorado, USA; latest Eocene (Chadronian). SEM micrographs; in lingual (A), labial (B), and occlusal (C) views, and explanatory drawing of occlusal view (D). Anterior is to the right. Original drawing by Leigh Anne McConnaughey. For B, C, and D, anterior is to the right.

opencc-by-4.0Dec 2022View details →

Fig. 1. Maps indicating the sampling locality within South Africa. A in Camallanid nematodes from Clarias gariepinus (Burchell, 1822) in the Crocodile River, Gauteng, South Africa: Exploring diversity and divergence in an acid-mine drainage impacted environment

Fig. 1. Maps indicating the sampling locality within South Africa. A- Map of Africa. B- Map of South Africa; red square highlighting area of interest. C- Map of Crocodile River flowing from Lake Heritage (sampling site) to Hartbeespoort Dam further downstream.

opencc-by-4.0Aug 2024View details →

Fig. 4. Goods coverage index for each sample using the OTUs. Retained 330,000 in Bacterial community of ticks (Acari: Ixodidae) and mammals from Arauca, Colombian Orinoquia

Fig. 4. Goods coverage index for each sample using the OTUs. Retained 330,000 (49.90%) features in 15 (93.75%) samples at the specified sampling depth (22,000).

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resource metadata sample: resource_metadata

For registration on https://opentraits.org/ of all branch painting datasets as of Aug 30, 2022

opencc-by-4.0Dec 2017View details →

FIGURE 4 in Overcoming sampling issues in dental tribology: Insights from an experimentation on sheep

FIGURE 4. Mean and standard error of the mean for complexity (Asfc) and anisotropy (epLsar) of the dental microwear textures for each ewe sample and for each molar of the tooth row.

opencc-by-4.0Dec 2017View details →

FIGURE 3 in Overcoming sampling issues in dental tribology: Insights from an experimentation on sheep

FIGURE 3. Mean and standard error of the mean for complexity (Asfc) and anisotropy (epLsar) of the dental microwear textures for dental facets from upper and lower molars and for each dietary sample. 1, Comparison of the disto-labial protoconid facet of the second lower molar and the mesio-lingual paracone facet of the second upper molar. 2, Comparison of the disto-labial protoconid facet of the second lower molar and mesio-lingual protocone facet of the second upper molar.

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FIGURE 5 in Overcoming sampling issues in dental tribology: Insights from an experimentation on sheep

FIGURE 5. Mean and standard error of the mean for complexity (Asfc) and anisotropy (epLsar) of the dental microwear textures for the simulations of fossil data using random sampling of the ewe dataset. Ellipses represent 95% of the means for each iteration. Mean and standard error of the mean for each sample (lower second molars) are also represented for comparison. 1, Simulation with 10 individuals per dietary category and 1000 iterations. 2, Simulation with 20 individuals per dietary category and 1000 iterations. 3, Simulation with 30 individuals per dietary category and 1000 iterations.