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Fig. 4 in Multispecies leatherback turtle assemblage from the Oligocene Chandler Bridge and Ashley formations of South Carolina, USA
Fig. 4. Ossicle of leatherback turtle cf. Egyptemys sp. (CCNHM 4289) from Oligocene of South Carolina, USA, in dorsal (A1), visceral (A2), and sutural A3) views.
Fig. 2 in Multispecies leatherback turtle assemblage from the Oligocene Chandler Bridge and Ashley formations of South Carolina, USA
Fig. 2. Ossicles of leatherback turtle Natemys sp. 1 from Oligocene of South Carolina, USA. CCNHM 5542 (A), CCNHM 5540 (B), CCNHM 4405.1– 4405.5 (C–G, respectively), CCNHM 4288 (H), and CCNHM 5541 (I), in dorsal (A1–I1), visceral (A2–I2), and sutural (A3–I3) views.
Fig. 1 in Multispecies leatherback turtle assemblage from the Oligocene Chandler Bridge and Ashley formations of South Carolina, USA
Fig. 1. The Ashley and Chandler Bridge formations and geologic context of CCNHM ossicles. A. Map of the southeastern United States. B. Map of Ashley and Chandler Bridge formation exposures on the coast of South Carolina. Stars denote Oligocene dermochelyid localities. C. Stratigraphic column of the Ashley and Chandler Bridge formations.
Figure 2 in Shallow-water polychaete assemblages in the northwestern Mediterranean Sea and its possible use in the evaluation of good environmental state
Figure 2. Cluster analysis of polychaete fauna for the Gulf of Lions region (France; upper graph) and the Northern Mediterranean Spanish coast (Spain; lower graph). Asterisk observed in lower graph indicates stations associated with the Detritic Sand Community (DS)
Fig. 1 - A in Decapod assemblage from the late Miocene (early-middle Messinian) of the Romagna Apennines nearby Brisighella, Emilia-Romagna (N Italy)
Fig. 1 - A) Callianassa cf. C. subterranea (Montagu, 1808), MSF 2302 (x 6.5). B) Calliax sp., MSF 1157 (x 7.7).
Fig. 3 in Assessment of coastal fish assemblages before the establishment of a new marine protected area in the central Mediterranean: its role in formulating a zoning proposal Abstract
Fig. 3: Species richness (mean number of species ± S.E.) of fishes recorded along the random courses at each (a) sector, (b) habitat type (POM=Posidonia oceanica meadow; RAR=rockyalgal reef; SOB=soft bottom) and (c) depth range.
Fig. 7 in Fibrocapsa japonica (Raphidophyceae) occurrence and ecological features within the phytoplankton assemblage of a cyclonic eddy, offshore the Eastern Alboran Sea
Fig. 7: A) Dinophyceae, and B) "other plankton" (Cryptophyceae, Chrysophyceae, Haptophyta excluding coccolithophores, Prasinophyceae, <10 mm flagellates and incertae sedis cells) cell number map (x 103 cells l-1) overlapped to isohalines (bold lines) as in Fig. 4.
Fig. 2 in Fibrocapsa japonica (Raphidophyceae) occurrence and ecological features within the phytoplankton assemblage of a cyclonic eddy, offshore the Eastern Alboran Sea
Fig. 2: Seawater A) salinity and B) temperature along the 2 transects. Bold lines denote the A) 37.0 and 37.5 isohaline and the B) 15 °C and 20 °C isotherms, respectively.
Fig. 2 in Dipteran Assemblages In Red-Footed Falcon (Falco Vespertinus) Nest Boxes
Fig. 2. Phenology of emergence of Carnus hemapterus imagoes from three years old accumulated nest material (collected in 2009), grouped by the last breeding bird species (n =
Fig. 3 in Effects of the interannual variations in the flood pulse mediated by hypoxia tolerance: the case of the fish assemblages in the upper Paraná River floodplain
Fig. 3. Interannual variation of the absolute and mean ± s.e. values of dissolved oxygen (a, c) and water transparency (b, d) in lakes (circle) and river channels (square) of the upper Paraná River floodplain, in years of short (2000 and 2001) and moderate (2002 and 2003) floods. Numbers 1-6 are codes of the sampling stations (see Fig. 1).
FIGURE 10 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies
FIGURE 10. Percentage of DCA-1 values obtained from simulations that fall within a 95% envelope of three DCA-1 values: (A) 0.0 (B) 1.0 and (C) 2.0. These values were selected as example observations from a hypothetical empirical data set and are marked by a green line in each subfigure. The bounds of the 95% confidence envelope were calculated by repeatedly simulating assemblages at the indicated empirical DCA-1 value and finding the two-tailed 95% quantile on the DCA-1 values obtained from those simulated assemblages. In the mixed assemblage simulations, background assemblages are simulated at a DCA-1 value of -0.5 and are mixed with an event assemblage with a DCA-1 value as given on the horizontal axis, with the proportion of mixing indicated on the vertical axis. In all three cases, the region the target DCA-1 value is observed in the simulations is a narrow ridge in probability space.
Fig. 4 in Patterns in fish species composition and assemblage structure in the upper Salado River lakes, Pampa Plain, Argentina
Fig. 4. Relationship between dominance of fish species and gradients in water conductivity and the NO3:NH 4 ratio.
Figure 1 in Assessing structure and seasonal variations of a temperate shallow water fish assemblage through Snorkel Visual Census
Figure 1. – Model data for temperature and salinity at the two study sites during the survey period.
Figure 4 in Species richness of urban and rural fish assemblages in the Grijalva Basin floodplain, southern Gulf of Mexico
Figure 4. – Fish distributed in the Villahermosa city and rural areas in the Grijalva floodplain. 1 – Dorosoma anale, 2 – D. petenense, 3 – Astyanax finitimus, 4 – Pterygoplichthys spp., 5 – Cathorops aguadulce, 6 – Rhamdia guatemalensis, 7 – Cincelichthys pearsei, 8 – Cribroheros robertsoni, 9 – Mayaheros urophthalmus, 10 – Oreochromis niloticus. 11 – Oscura heterospila, 12 – Parachromis friedrichsthalii, 13 – Parachromis managuensis, 14 – Vieja bifasciata, 15 – V. melanurus, 16 – Hyporhamphus mexicanus, 17 – Strongylura hubbsi, 18 – Ophisternon aenigmaticum, 19 – Centropomus undecimalis, 20 – Diapterus auratus, and 21 – Eugerres mexicanus.
Figure 2 in Species richness of urban and rural fish assemblages in the Grijalva Basin floodplain, southern Gulf of Mexico
Figure 2. – Fish distributed in the Villahermosa city and rural areas in the Grijalva floodplain. 1 – Atractosteus tropicus, 2 – Megalops atlanticus, 3 – Ctenopharyngodon idella, 4 – Cyprinus carpio, 5 – Brycon guatemalensis, and 6 – Petenia splendida.
Figure 3 in Species richness of urban and rural fish assemblages in the Grijalva Basin floodplain, southern Gulf of Mexico
Figure 3. – Fish distributed in the Villahermosa city and rural areas in the Grijalva floodplain. 1 – Anchoa mitchilli, 2 – Brevoortia gunteri, 3 – Hyphessobrycon compressus, 4 – Batrachoides goldmani, 5 – Dormitator maculatus, 6 – Eleotris amblyopsis, 7 – Gobiomorus dormitor, 8 – Oreochromis aureus, 9 – Rocio octofasciata, 10 – Thorichthys helleri, 11 – T. meeki, 12 – T. pasionis, 13 – Trichromis salvini, 14 – Atherinella alvarezi, 15 – Cynodonichthys tenuis, 16 – Belonesox belizanus, 17 – Carlhubbsia kidderi, 18 – Gambusia sexradiata, 19 – G. yucatana, 20 – Pseudoxiphophorus bimaculatus, 21 – Heterophallus echeagarayi, 22 – Phallichthys fairweatheri, 23 – Poecilia kykesis, 24 – P. mexicana. 25 – Xiphophorus maculatus, 26 – Achirus lineatus, and 27 – Microphis lineatus.
FIGURE 14. Taeniopteris leaves. 1. Taenopteris spatulata, LX1097 in Middle-Late Jurassic plant assemblages of the Catlins coast, New Zealand
FIGURE 14. Taeniopteris leaves. 1. Taenopteris spatulata, LX1097, Curio Bay; 2. Taeniopteris crassinervis, LX2365, Curio Bay; 3. Taeniopteris sp. 'narrow', LX2365, Little Bay-03. All scale bars equal 10 mm.
FIGURE 1 in Middle-Late Jurassic plant assemblages of the Catlins coast, New Zealand
FIGURE 1. Catlins Coast fossil locality map. Arrow in the upper inset map points to a rectangle that delineates the general region along the southern coast of New Zealand's South Island. The upper map indicates the whole area regarded as 'Catlins Coast' in this work, and shows the Owaka and Chasm localities, which are a little distant from the others, and it delineates a rectangular area, which is shown in detail in the lower map.
FIGURE 4. Cladophlebis patagonica pinnules. 1. LX1498 in Middle-Late Jurassic plant assemblages of the Catlins coast, New Zealand
FIGURE 4. Cladophlebis patagonica pinnules. 1. LX1498, Black Point (Note the distinct apical broadening of the pinnule base); 2. LX1074, Curio Bay; 3. LX1197, Slope-02; 4. LX1069, The Boat Harbour; 5. LX1076, Curio Bay (Note that some of the veins dichotomise twice.); 6. LX2070, The Boat Harbour (Note the pronounced apical broadening of the pinnule base which continues to the adjacent pinnule as a 'wing'. All scale bars equal 10 mm).
FIGURE 16. Elatocladus confertus 1. LX1060 in Middle-Late Jurassic plant assemblages of the Catlins coast, New Zealand
FIGURE 16. Elatocladus confertus 1. LX1060, Little Bay-01; 2. LX0674, Little Bay-01; 3. LX1050, Little Bay-01; 4. LX1057, Little Bay-01; 5. LX1107, Curio Bay; 6. LX1147, Blue Cod Bay; 7. LX1090, Curio Bay. All scale bars equal 10 mm.
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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)
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.