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62 results for “linearis”
FIGURE 4. Tamaulipan Acanthaceae IV. A. Justicia brandegeeana. B. Justicia leonardii. C. Justicia salviiflora. D. Justicia linearis. E. Justicia fulvicoma. F. Justicia pilosella. G. Justicia canbyi. H in Taxonomic and Photographic Guide to the Acanthaceae of Tamaulipas, Mexico
FIGURE 4. Tamaulipan Acanthaceae IV. A. Justicia brandegeeana. B. Justicia leonardii. C. Justicia salviiflora. D. Justicia linearis. E. Justicia fulvicoma. F. Justicia pilosella. G. Justicia canbyi. H. Justicia sp. I. Justicia pacifica. Photos by T. Daniel (A–C, E) and L. García-Morales (D, F–I).
Fig. 1 in New data and notes on the distribution of Lioderina linearis (Hampe, 1870) (Cerambycidae: Callidiini) in Bulgaria
Fig. 1. Lioderina linearis (Hampe, 1870). A: Male, Sredna Gora Mts., NE Strelcha, 29.VII.2012; B: Female, Pirin Mts., NE Sugarevo Vill., 21.VII.2012. Scale bars: 1 mm.
Fig. 2 in New data and notes on the distribution of Lioderina linearis (Hampe, 1870) (Cerambycidae: Callidiini) in Bulgaria
Fig. 2. Localities of Lioderina linearis (Hampe, 1870) in Bulgaria. Legend: ▲ after Sabol (2000); ● after Migliaccio et al. (2007); ♦ new data, Gradinarov & Sivilov (present study).
Figure 2 in First record of Sitophilus linearis (Herbst, 1795) (Coleoptera: Curculionidae) from East African copal
Figure 2. Sitophilus linearis, East African copal: a – rostrum, head and prosternum, ventral view; b – metaventrite and abdomen, ventral view.
Figure 1 in First record of Sitophilus linearis (Herbst, 1795) (Coleoptera: Curculionidae) from East African copal
Figure 1. Sitophilus linearis, habitus, East African copal: a – ventro-lateral view, right; b – lateral view, left; c – dorsal view.
Fig. 17. Species distribution. A. Canthon septemmaculatus linearis Schmidt, 1920. B in The dung beetles of Venezuela (Coleoptera: Scarabaeidae: Scarabaeinae): catalogue and updated distribution
Fig. 17. Species distribution. A. Canthon septemmaculatus linearis Schmidt, 1920. B. Canthon septemmaculatus septemmaculatus (Latreille, 1807). Green diamond = CEMT collection data; black circle = literature data.
Drosera linearis (Droseraceae) - whole plant - juvenile
Image of Drosera linearis (Droseraceae) - whole plant - juvenile
The evolution of C4 photosynthesis in Flaveria (Asteraceae): Insights from the Flaveria linearis complex
<p>Flaveria is a leading model for C4 plant evolution due to the presence of a dozen C3-C4 intermediate species, many of which are associated with a phylogenetic complex centered around F. linearis. To investigate C4 evolution in Flaveria, we updated the Flaveria phylogeny and evaluated gas exchange, starch δ13C, and activity of C4 cycle enzymes in 19 Flaveria species and 28 populations within the F. linearis complex. A principal component analysis identified six functional clusters: i) C3, ii) sub-C2, iii) full C2, iv) enriched C2, v) sub-C4, and vi) fully C4 species. The sub-C2 species lacked a functional C4 cycle, while a gradient was present in the C2 clusters from little to modest C4 cycle activity as indicated by δ13C and enzyme activities. Three Yucatan populations of F. linearis had photosynthetic CO2 compensation points equivalent to C4 plants but showed little evidence for an enhanced C4 cycle, indicating they have an optimized C2 pathway that recaptures all photorespired CO2 in the bundle sheath (BS) tissue. All C2 species had enhanced aspartate aminotransferase activity relative to C3 species and most had enhanced alanine aminotransferase activity. These aminotransferases form aspartate and alanine from glutamate and in doing so help return photorespiratory nitrogen (N) from BS to mesophyll cells, preventing glutamate feedback onto photorespiratory N assimilation. Their use requires upregulation of parts of the C4 metabolic cycle to generate carbon skeletons to sustain N return to the mesophyll, and thus could facilitate the evolution of the full C4 photosynthetic pathway.</p>
Figure 3 in First record of Sitophilus linearis (Herbst, 1795) (Coleoptera: Curculionidae) from East African copal
Figure 3. Copal piece.
The evolution of C4 photosynthesis in Flaveria (Asteraceae): Insights from the Flaveria linearis complex
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Simulated impacts of harvesting Chamaedorea linearis and C.pinnatifrons (Arecaceae): Implications for conservation
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Shortgrass Steppe site, station Treatment 1 (control) for ESA study, study of plant density of Mirabilis linearis in units of numberPerMeterSquared on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Shortgrass Steppe (SGS) contains plant density of Mirabilis linearis measurements in numberPerMeterSquared units and were aggregated to a yearly timescale.
Shortgrass Steppe site, station Treatment 2 (water addition) for ESA study, study of plant density of Mirabilis linearis in units of numberPerMeterSquared on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Shortgrass Steppe (SGS) contains plant density of Mirabilis linearis measurements in numberPerMeterSquared units and were aggregated to a yearly timescale.
Shortgrass Steppe site, station Treatment 3 (nitrogen addition) for ESA study, study of plant density of Mirabilis linearis in units of numberPerMeterSquared on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Shortgrass Steppe (SGS) contains plant density of Mirabilis linearis measurements in numberPerMeterSquared units and were aggregated to a yearly timescale.
Shortgrass Steppe site, station Treatment 4 (water and nitrogen addition) for ESA study, study of plant density of Mirabilis linearis in units of numberPerMeterSquared on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Shortgrass Steppe (SGS) contains plant density of Mirabilis linearis measurements in numberPerMeterSquared units and were aggregated to a yearly timescale.
Data from: Distribution of the invasive Caprella mutica Schurin, 1935 and native Caprella linearis (Linnaeus, 1767) on artificial hard substrates in the North Sea: separation by habitat
Studying offshore natural and artificial hard substrates in the southern North Sea (51ºN–57ºN/1ºW–9ºE), the invasive introduced Japanese skeleton shrimp Caprella mutica Schurin, 1935 was found to co-exist with the native Caprella linearis (Linnaeus, 1767) only on near-shore locations that had an intertidal zone (e.g., wind farm foundations). In contrast, on far offshore and strictly subtidal locations, such as shipwrecks and rocky reefs, only C. linearis was found. Based on these exploratory observations, we hypothesised that artificial structures that are only subtidal are inhabited exclusively by C. linearis, and never by C. mutica. To test this hypothesis and understand factors driving each species' habitat preferences, habitat suitability models were constructed using generalised additive models, based on samples collected in 2013–2015 from offshore gas platforms, buoys, shipwrecks, and rocky reefs and combined with data from other published and unpublished surveys (2001–2014). The models showed that the presence of C. mutica is explained by the availability of intertidal and floating hard substrates, suspended particulate matter density (SPM), mean annual sea surface temperature, salinity, and current velocity. The C. linearis model included subtidal hard substrates, SPM, salinity, temperature, and current velocity. The modelled distributions showed a significant difference, demonstrating that C. linearis' habitat preference does not fully overlap with that of C. mutica. Thus, the native and alien Caprella species are likely to be able to co-exist in the North Sea.
FIGURES 24–28 in Redescription of Pseudoparomius linearis (Stål), and descriptions of three new species of Pseudoparomius Harrington (Rhyparochromidae: Heteroptera)
FIGURES 24–28: Pseudoparomius slateri, male genitalia. 24— pygophore, dorsal view. 25— pygophore, lateral view. 26— right paramere, inner view. 27— right paramere, outer view. 28aphallus, 28b— schematic drawing of serrated projections
FIGURES 19–23 in Redescription of Pseudoparomius linearis (Stål), and descriptions of three new species of Pseudoparomius Harrington (Rhyparochromidae: Heteroptera)
FIGURES 19–23: Pseudoparomius brailovskyi, male genitalia. 19— pygophore, dorsal view. 20— pygophore, lateral view. 21— right paramere, inner view. 22— right paramere, outer view. 23aphallus, 23b— schematic drawing of serrated projections.
FIGURES 15–18 in Redescription of Pseudoparomius linearis (Stål), and descriptions of three new species of Pseudoparomius Harrington (Rhyparochromidae: Heteroptera)
FIGURES 15–18: Pseudoparomius brailovskyi. 15— anterior pronotal lobe, transverse sulci, and posterior pronotal lobe (X200). 16— details of anterior pronotal lobe (X3500). 17— details of posterior pronotal lobe (X1000). 18— scutellum and hemelytra (sc: scutellum; cla: clavus) (X750).
FIGURES 10–14 in Redescription of Pseudoparomius linearis (Stål), and descriptions of three new species of Pseudoparomius Harrington (Rhyparochromidae: Heteroptera)
FIGURES 10–14: Pseudoparomius bimaculatus, male genitalia. 10— pygophore, dorsal view. 11— pygophore, lateral view. 12— right paramere, inner view. 13— right paramere, outer view. 14a— phallus, 14b— schematic drawing of serrated projections.
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DANDI Archive for NWB datasets
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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.