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Fig. 6 in The Frasnian-Famennian events in a deep-shelf succession, Subpolar Urals: biotic, depositional, and geochemical records
Fig. 6. Various upper Frasnian spongiolitic microfacies, Syv'yu River section. A. Sponge boundstone(?); note large growth cavities, and complex and diverse, peloidal to bioclastic geopetal fill up, as well as preserved spicular network; sample Syv96−58. B, C. Sponge relics (Sp) distinguished by a variety of grumeous fabric, pyrite−rich marginal rims, and partly chertified interstitial mudstone matrix (Ch); samples CB99−224 (B) and CB99−314 (C).
Fig. 1 in The Frasnian-Famennian events in a deep-shelf succession, Subpolar Urals: biotic, depositional, and geochemical records
Fig. 1. Location of the studied area in Russia (A) and Timan−Pechora region (B, modified from Becker et al. 2000: fig. 1A), and location of the Kozhym River basin (C) and locality map of studied outcrops along the Syv'yu River section (D), western slopes of the Subpolar Urals; C1t, Tournaisian. D1, Lower Devonian; D2tk,?Middle Devonian, Takata Suite; D2ef−gv, Eifelian–Givetian; D3fr, Frasnian; D3fm, Famennian.
Fig. 4 in The Frasnian-Famennian events in a deep-shelf succession, Subpolar Urals: biotic, depositional, and geochemical records
Fig. 4. Upper Frasnian and lower Famennian lithologic column of the Syv'yu River section (upper Vorota Fm.), sampling pattern and conodont succession across the F–F boundary, with emphasis on principal biotic events and alleged Kellwasser levels (see also Figs. 7, 8); figures in the lithological column refer to microfacies photos (Figs. 5, 6).
Fig. 2. F–F in The Frasnian-Famennian events in a deep-shelf succession, Subpolar Urals: biotic, depositional, and geochemical records
Fig. 2. F–F boundary beds exposed along the right bank of Syv'yu River, outcrop 2 (line marks F–F boundary; for location see Fig. 1D).
Fig. 8 in The Frasnian-Famennian events in a deep-shelf succession, Subpolar Urals: biotic, depositional, and geochemical records
Fig. 8. Stable isotope geochemistry for the Upper Frasnian and lower Famennian in the Syv'yu River section, F–F background values taken from Joachimski and Buggisch (1996: fig. 1); for explanations see Fig. 4.
FIGURE 6 in Biting midges (Diptera: Ceratopogonidae) in Fushun amber reveal further biotic links between Asia and Europe during the Eocene
FIGURE 6. Palaeogeographic locations of early Eocene insect faunas in (approximately 50 Ma) Baltic amber (B) from Europe and Fushun amber (F) from China (modified after Blakey, 2015).
FIGURE 1 in Biting midges (Diptera: Ceratopogonidae) in Fushun amber reveal further biotic links between Asia and Europe during the Eocene
FIGURE 1. Photograph of Mantohelea sinica n. sp. from lower Eocene Fushun amber. 1. Mantohelea sinica n. sp., Holotype female NIGP156996. 2. Mantohelea sinica n. sp., head.
FIGURE 2. Mantohelea sinica n in Biting midges (Diptera: Ceratopogonidae) in Fushun amber reveal further biotic links between Asia and Europe during the Eocene
FIGURE 2. Mantohelea sinica n. sp., Holotype female NIGP156996. 1. Antenna. 2. Wing. 3. Palpus. 4. Fore tibia. 5. Fore femur. 6. Tarsus of foreleg. 7. Tarsus of mid leg. 8. Tarsus of hind leg.
FIGURE 5. Gedanohelea liaoningensis n in Biting midges (Diptera: Ceratopogonidae) in Fushun amber reveal further biotic links between Asia and Europe during the Eocene
FIGURE 5. Gedanohelea liaoningensis n. sp., Holotype female NIGP156998. 1. Flagellum. 2. Wing. 3. Palpal segments 3-5. 4. Tarsus of foreleg. 5. Tarsus of mid leg. 6. Tarsus of hind leg.
FIGURE 3 in Biting midges (Diptera: Ceratopogonidae) in Fushun amber reveal further biotic links between Asia and Europe during the Eocene
FIGURE 3. Photograph of Gedanohelea fushunensis n. sp. and Gedanohelea liaoningensis n. sp. from lower Eocene Fushun amber 1. Gedanohelea liaoningensis n. sp., Holotype female NIGP156998. 2. Gedanohelea fushunensis n. sp., Holotype female NIGP156997. 3. Detail of wing of Gedanohelea liaoningensis n. sp. with tips of veins M1 and M2 marked. 4. Detail of wing of Gedanohelea fushunensis n. sp. with tips of veins M1 and M2 marked.
FIGURE 4. Gedanohelea fushunensis n in Biting midges (Diptera: Ceratopogonidae) in Fushun amber reveal further biotic links between Asia and Europe during the Eocene
FIGURE 4. Gedanohelea fushunensis n. sp., Holotype female NIGP156997. 1. Flagellum. 2. Wing. 3. Palpal segments 3-5. 4. Tarsomeres 4, 5 and claw of foreleg. 5. Tarsomeres 4, 5 and claw of mid leg. 6. Tarsomeres 4, 5 and claw of hind leg.
FIGURE 4 in Biotic differentiation in headwater creeks after the massive introduction of non-native freshwater aquarium fish in the Paraíba do Sul River basin, Brazil
FIGURE 4 | Contamination Index (CI) in each headwater creek in the Muriaé Ornamental Aquaculture Center, Brazil. Headwater creeks: LO = Lopes; QU = Queiroga; BS = Boa Sorte; RO = Rochedo; VA = Varginha; SL = São Luís.
FIGURE 3 in Biotic differentiation in headwater creeks after the massive introduction of non-native freshwater aquarium fish in the Paraíba do Sul River basin, Brazil
FIGURE 3 | The 10 most widespread non-native exotic fish in the studied headwater creeks located in the Muriaé Ornamental Aquaculture Center, Brazil. Only non-native species with at least 50% of occurrence were listed.
FIGURE 2 in Biotic differentiation in headwater creeks after the massive introduction of non-native freshwater aquarium fish in the Paraíba do Sul River basin, Brazil
FIGURE 2 | Richness of native (blue) and non-native species [translocated (yellow) and exotic (red)], in each headwater creek in the Muriaé Ornamental Aquaculture Center, Brazil. Headwater creeks: LO = Lopes; QU = Queiroga; BS = Boa Sorte; RO = Rochedo; VA = Varginha; SL = São Luís.
FIGURE 1 in Biotic differentiation in headwater creeks after the massive introduction of non-native freshwater aquarium fish in the Paraíba do Sul River basin, Brazil
FIGURE 1 | Sampling sites in the area affected by the Muriaé Ornamental Aquaculture Center in Brazil. Municipalities: Muriaé, Miradouro, Vieiras, and São Francisco do Glória (Total area of 1,419 km2; IBGE, 2020). Headwater creeks: LO = Lopes; QU = Queiroga; BS = Boa Sorte; RO = Rochedo; VA = Varginha; SL = São Luís.
FIGURE 5 in Biotic differentiation in headwater creeks after the massive introduction of non-native freshwater aquarium fish in the Paraíba do Sul River basin, Brazil
FIGURE 5 | Distances to the centroid obtained from the two main Principal Coordinate Analysis – PCoA axis (see Anderson et al., 2006 for further details) of fish community Jaccard dissimilarities in six headwater creeks (LO = Lopes; QU = Queiroga; BS = Boa Sorte; RO = Rochedo; VA = Varginha; SL = São Luís) sampled in historical (only native species) and in contemporary (native + non-natives) periods, in the Muriaé Ornamental Aquaculture Center, Brazil.
FIGURE 6 in Biotic differentiation in headwater creeks after the massive introduction of non-native freshwater aquarium fish in the Paraíba do Sul River basin, Brazil
FIGURE 6 | Position of six headwater creeks (LO = Lopes; QU = Queiroga; BS = Boa Sorte; RO = Rochedo; VA = Varginha; SL = São Luís), scaled by temperature (Temp, blue gradient colours), and number of ponds (Np, circle size) used to raise fish species in the nearest fish farm (i.e., anthropogenic proxy of propagule pressure) in the Muriaé Ornamental Aquaculture Center, Brazil.
Forest resilience to global warming is strongly modulated by local-scale topographic, microclimatic and biotic conditions
<p>Resilience of endangered rear edge populations of cold-adapted forests in the Mediterranean basin is increasingly altered by extreme heatwave and drought pressures. It remains unknown, however, whether microclimatic variation in these isolated forests could ultimately result in large intra-population variability in the demographic responses, allowing the coexistence of contrasting declining and resilient trends across small topographic gradients. Multiple key drivers promoting spatial variability in the resilience of rear edge forests remain largely unassessed, including amplified and buffered thermal exposure induced by heat waves along topographic gradients, and increased herbivory pressure on tree saplings in defaunated areas lacking efficient apex predators. Here we analysed whether indicators of forest resilience to global warming are strongly modulated by local-scale topographic, microclimatic and biotic conditions.</p> <p>We studied a protected rear edge forest of sessile oak (<em>Q. petraea</em>), applying a suite of 20 indicators of resilience of tree secondary growth, including multidecadal and short-term indices. We also analysed sapling recruitment success, recruit/adult ratios and sapling thermal exposure across topographic gradients. We found large within population variation in secondary growth resilience, in recruitment success and in thermal exposure of tree saplings to heatwaves, and this variability was spatially structured along small-scale topographical gradients. Multidecadal resilience indices and curves provide useful descriptors of forest vulnerability to climate warming, complementing assessments based in the analysis of short-term resilience indicators. Species-specific associations of trees with microclimatic variability are reported.</p> <p>Biotic factors are key in determining long-term resilience in climatically-stressed rear edge forests, with strong limitation of sapling recruitment by increased roe deer and wild boar herbivory. Our results also support non-stationary effects of climate determining forest growth responses and resilience, showing increased negative effects of warming and drought over the last decades in declining stands.</p> <p>Our findings do not support scenarios predicting spatially homogeneous distributional shifts and limited resilience in rear-edge populations, and are more supportive of scenarios including spatially heterogeneous responses, characterised with contrasting intra-population trends of forest resilience. We conclude that forest resilience responses to climate warming are strongly modulated by local-scale microclimatic, topographic and biotic factors. Accurate predictions of forest responses to changes in climate would therefore largely benefit from the integration of local-scale abiotic and biotic factors.</p>
Fig. 1 in The Singscore: a macroinvertebrate biotic index for assessing the health of Singapore's streams and canals
Fig. 1. Map of Singapore showing the 47 study sites (black circles) located in 33 concrete canals, and 14 forested streams. Note that all forested streams were located within the Central Catchment Nature Reserve (CCNR; dark grey area in centre of the map). Inset shows forested study sites within the CCNR.
Fig. 2 in The Singscore: a macroinvertebrate biotic index for assessing the health of Singapore's streams and canals
Fig. 2. Partial canonical correspondence analysis (pCCA) ordination showing differences in macroinvertebrate community composition in the 33 urban canals (open circles) and the 14 reference streams (closed triangles). The main environmental drivers (pH and copper) of community dissimilarity are depicted as solid arrows.
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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.