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Fig. 31 in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 31. Glyptapanteles drioplanetus Fagan-Jeffries & Austin, 2021, holotype, ♀ (WAM WAME10965). A. Dorsal habitus. B. Fore wing. C. Lateral habitus. D. Dorsal head. E. Anterior head. F. Scutellar disk and propodeum. Images from Fagan-Jeffries & Austin (2021: fig. 5).
Fig. 32 in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 32. Glyptapanteles eburneus Fagan-Jeffries, Bird & Austin sp. nov., holotype, ♀ (AM K.517935). A. Lateral body. B. Dorsal mesosoma. C. Dorsal head. D. Anterior head. E. Lateral head. F. Dorsal metasoma. G. Lateral habitus.
Fig. 45 in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 45. Glyptapanteles mouldsi Fagan-Jeffries, Bird & Austin sp. nov., paratypes, ♀. A–F. QM T250978. G. QM T250979. A. Lateral habitus. B. Fore wing. C. Dorsal mesosoma. D. Anterior head. E. Lateral head. F. Dorsal metasoma. G. Dorsal head.
Fig. 44. Glyptapanteles mnesampela Austin, 2000 in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 44. Glyptapanteles mnesampela Austin, 2000 holotype, ♀ (ANIC 32-141445). A. Lateral habitus. B. Dorsal propodeum and metasoma. C. Anterior head. Images courtesy of O. Evangelista (ANIC).
Fig. 36 in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 36. Glyptapanteles goodwinnoakes Fagan-Jeffries, Bird & Austin sp. nov., paratype, ♀ (QM T250956). A. Lateral habitus. B. Dorsal head. C. Anterior head. D. Dorsal habitus. E. Fore wing. F. Lateral head.
Fig. 29 in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 29. Glyptapanteles doreyi Fagan-Jeffries, Bird & Austin sp. nov., paratype, ♀ (ANIC 32 130330), 'clade B'. A. Lateral habitus. B. Fore wing. C. Dorsal head. D. Dorsal metasoma. E. Anterior head. F. Lateral head. G. Dorsal mesosoma.
Fig. 7. A in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 7. A. Glyptapanteles harveyi Fagan-Jeffries, Bird & Austin sp. nov., paratype, ♀ (WAM E109889), arrow indicating faint median carina at the posterior end of the propodeum. B. G. kittelae Fagan-Jeffries, Bird & Austin sp. nov., holotype, ♀ (SAMA 32-46156), propodeum with median carina completely absent.
Fig. 8. A in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 8. A. Glyptapanteles andamookaensis Fagan-Jeffries, Bird & Austin sp. nov., holotype, ♀ (SAMA 32-035451), hind femur mostly dark. B. G. kittelae Fagan-Jeffries, Bird & Austin sp. nov., holotype, ♀ (SAMA 32-46156), hind femur mostly light brown.
Fig. 6. A. Glyptapanteles mnesampela Austin, 2000 in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 6. A. Glyptapanteles mnesampela Austin, 2000, holotype, ♀ (ANIC 32-141445), T1 and T2 pale. B. G. eburneus Fagan-Jeffries, Bird & Austin sp. nov., holotype, ♀ (AM K.517935), T1 and T2 pale. C. G. rixi Fagan-Jeffries, Bird & Austin sp. nov., holotype, ♀ (QM T250981), T2 pale, T1 darker than T2. D. G. mouldsi Fagan-Jeffries, Bird & Austin sp. nov., paratype, ♀, (QM T250978), T1 dark, T2 pale. E. G. dowtoni Fagan-Jeffries, Bird & Austin sp. nov., paratype, ♀ (QM T250953), T1 dark, T2 pale. F. G. harveyi Fagan-Jeffries, Bird & Austin sp. nov., paratype, ♀ (WAM E109889), T1 dark, T2 dark.
Fig. 5. A in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 5. A. Glyptapanteles albigena Fagan-Jeffries, Bird & Austin sp. nov., holotype, ♀ (ANIC 32 130334), arrow indicating a large pale gena spot. B. G. sanniopolus Fagan-Jeffries, Bird & Austin sp. nov., holotype, ♀ (ANIC 32 130370), arrow indicating a large pale gena spot. C. G. kittelae Fagan- Jeffries, Bird & Austin sp. nov., holotype, ♀ (SAMA 32-46156) arrow indicating small (clearly visible) pale gena spot. D. G. harveyi Fagan-Jeffries, Bird & Austin sp. nov., paratype, ♀ (WAM E109889), arrow indicating small (faint, barely visible) pale gena spot. E. G. baylessi Fagan-Jeffries, Bird & Austin sp. nov. paratype, ♀ (AM K.517936), gena without a pale spot.
Fig. 2 in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 2. Maximum likelihood phylogeny constructed using IQ-TREE ver. 1.6.12 of a concatenated COI and wingless alignment including Glyptapanteles Ashmead, 1904 from Australia, Papua New Guinea and Fiji, with specimens of Cotesia Cameron, 1891 from Australia included for contextual placement of the genus. Branch support values are given as SH-aLRT support (%) / ultrafast bootstrap support (%), with symbols representing value ranges as follows: * = 96–100; • = 91–95; ^ = 85–90; - = <85.
Fig. 3 in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 3. Known distribution of the described species of Glyptapanteles Ashmead, 1904 from Australia, represented by coloured circles or part circles, with each species represented by a different colour (see key to colours below map).
Fig. 4 in Systematic revision of the parasitoid wasp genus Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) for Australia results in a ten-fold increase in species
Fig. 4. Distribution of species groups of Glyptapanteles Ashmead, 1904 in Australia. A. G. albigena species group. B. G. arcanus species group. C. G. austini species group. D. G. eburneus species group. E. G. mouldsi species group. F. G. niveus species group. G. Unplaced species of Glyptapanteles in Australia.
A high-resolution gridded inventory of coal mine methane emissions for India and Australia
<p>The dataset contains the high-resolution gridded coal mine methane emissions file (.csv) for India and Australia. The emissions are estimated for the year 2018 at a resolution of 0.1° × 0.1°. The emission unit is ton/grid/year.</p>
Fig. 1 in On The Biodiversity Hotspot Of Large Branchiopods (Crustacea, Branchiopoda) In The Central Paroo In Semiarid Australia
Fig. 1. Map of Bloodwood, Tregeda, and Muella Stations, central Paroo, northwestern NSW. Code to symbols: SL — Salt Lake; L — Freshwater Lake; C — Claypan; G — Grassy swamp; S — Samphire swamp; X — Poplar Box flat; short line, creek pool; dot — Black Box swamp.
Fig. 3. Four representative branchiopods from the central Paroo. A in On The Biodiversity Hotspot Of Large Branchiopods (Crustacea, Branchiopoda) In The Central Paroo In Semiarid Australia
Fig. 3. Four representative branchiopods from the central Paroo. A — Anostracan Branchinella australiensis; B — Notostracan Triops sp.; C — Spinicaudatan Limnadopsis tatei; D — Spinicaudatan Ozestheria lutraria.
Fig. 2 in On The Biodiversity Hotspot Of Large Branchiopods (Crustacea, Branchiopoda) In The Central Paroo In Semiarid Australia
Fig. 2. Images of seven types of wetlands in the central Paroo., northwestern New South Wales: A — Gidgee Salt Lake; B — Ski Freshwater Lake; C — Melaleuca claypan; D — Beverley's grassy pool (dry); E — Reedy Black Box swamp; F — Utah Poplar Box flat; G — Lower Crescent creek pool. Not to scale.
Population connectivity and genetic offset in the spawning coral Acropora digitifera in Western Australia
<p><span>Anthropogenic </span>climate change has caused widespread loss of species biodiversity and ecosystem productivity across the globe, particularly on tropical coral reefs. Predicting the future vulnerability of reef-building corals, the foundation species of coral reef ecosystems, is crucial for cost-effective conservation planning in the Anthropocene. In this study, we combine regional population genetic connectivity and seascape analyses to explore patterns of genetic offset (the mismatch of gene-environmental associations under future climate conditions) in <em>Acropora digitifera</em> across 12 degrees of latitude in Western Australia. Our data revealed a pattern of restricted gene flow and limited genetic connectivity among geographically distant reef systems. Environmental association analyses identified a suite of loci strongly associated with the regional temperature variation. These loci helped forecasting future genetic offset in random forest and generalised dissimilarity models. These analyses predicted pronounced differences in the response of different reef systems in Western Australia to rising temperatures. Under the most optimistic future warming predictions (RCP 2.6), we observed a general pattern of increasing genetic offset with latitude. Under the most extreme climate scenario (RCP 8.5 in 2090-2100), coral populations at the Ningaloo World Heritage Area were predicted to experience a higher mismatch in genetic composition, compared to populations in the inshore Kimberley region. The study suggest complex and spatially heterogeneous patterns of climate-change vulnerability in coral populations across Western Australia, reinforcing the notion that regionally tailored conservation efforts will be most effective at managing coral reef resilience into the future.</p>
Satellite-derived chlorophyll-a concentrations for Lake Hume (Australia) using Mixture Density Networks and Sentinel-2 and Landsat 8 imagery
<p>This dataset contains satellite-derived chlorophyll-a data of Lake Hume (Australia) for the period 21 Mar. 2013 - 01 Feb. 2021. Chlorophyll-a concentrations have been calculated using Mixture Density Networks and Sentinel-2 and Landsat 8 imagery.</p> <p>Mixture Density Networks are a class of neural networks that tackle the inverse problem by modelling the multimodal distribution of target variables using a mixture of Gaussians. For more information, please refer to the following:</p> <ul> <li>Pahlevan, N., Smith, B., Alikas, K., Anstee, J., et al. (2022). Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3. <em>Remote Sensing of Environment, 270</em>, 112860</li> <li>Smith, B., Pahlevan, N., Schalles, J., et al. (2021). A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks. <em>Frontiers in Remote Sensing, 1</em></li> <li>Pahlevan, N., Smith, B., Schalles, J., et al. (2020). Seamless retrievals of chlorophyll-a from Sentinel-2 (MSI) and Sentinel-3 (OLCI) in inland and coastal waters: A machine-learning approach. <em>Remote Sensing of Environment, 240</em>, 111604</li> </ul>
Satellite-derived chlorophyll-a concentrations for Western Water Treatment Plant (Melbourne, Australia) using Mixture Density Networks and Sentinel-2 and Landsat 8 imagery
<p>This dataset contains satellite-derived chlorophyll-a data of the Western Water Treatment Plant (Melbourne, Australia) for the period 21 Mar. 2013 - 01 Feb. 2021. Chlorophyll-a concentrations have been calculated using Mixture Density Networks and Sentinel-2 and Landsat 8 imagery.</p> <p>Mixture Density Networks are a class of neural networks that tackle the inverse problem by modelling the multimodal distribution of target variables using a mixture of Gaussians. For more information, please refer to the following:</p> <ul> <li>Pahlevan, N., Smith, B., Alikas, K., Anstee, J., et al. (2022). Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3. <em>Remote Sensing of Environment, 270</em>, 112860</li> <li>Smith, B., Pahlevan, N., Schalles, J., et al. (2021). A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks. <em>Frontiers in Remote Sensing, 1</em></li> <li>Pahlevan, N., Smith, B., Schalles, J., et al. (2020). Seamless retrievals of chlorophyll-a from Sentinel-2 (MSI) and Sentinel-3 (OLCI) in inland and coastal waters: A machine-learning approach. <em>Remote Sensing of Environment, 240</em>, 111604</li> </ul>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.