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162 results for “continental scale”
FIGURE 3 in Towards the identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 1. Identification of the families
FIGURE 3. Monophlebidae adult female morphology, from Williams & Watson (1990: 24, Fig. 5), © CABI, Wallingford, U.K. Note well-spaced antennae with basal segments only moderately enlarged, and each antenna with 8‒11 segments; ovisac band composed of pores; anal opening often distinctly dorsal, simple, not sclerotised; and well-developed mouthparts.
FIGURE 12 in Towards the identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 1. Identification of the families
FIGURE 12. Coccidae adult female morphology, from Gill (1993: 7, Fig. 4), © California Department of Food & Agriculture, Sacramento, California, U.S.A. Note well-developed anal cleft, paired triangular anal plates with inner margins usually contiguous, and tubular ducts with cup-shaped inner ends.
FIGURE 11 in Towards the identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 1. Identification of the families
FIGURE 11. Stictococcidae adult female morphology, from Williams et al. (2010: 25, Fig. 10), © Magnolia Press, www. mapress.com/j/zt, reproduced with permission. Note anal complex situated at centre of dorsum, with anal opening between anterior and posterior anal plates.
FIGURE 7 in Towards the identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 1. Identification of the families
FIGURE 7. Putoidae adult female morphology, from Danzig & Gavrilov-Zimin (2014: 160, Fig. 2.1.1-8). Note dorsal ostiole (A); trochanter with 3 or 4 campaniform sensilla on each surface (B), and claw with plantar denticle (C). Note also that Putoidae often have a pair of denticles on the claw base, and have 9-segmented antennae; 18 pairs of cerarii-like marginal groups of setae; and have trilocular pores, a circulus and ostioles.
FIGURE 14 in Towards the identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 1. Identification of the families
FIGURE 14. Aclerdidae adult female morphology, from Gill (1993: 8, Fig. 5), © California Department of Food & Agriculture, Sacramento, California, U.S.A. Note posterior margin with furrows and ridges; legs usually absent; short anal cleft usually present, with a single triangular or oval anal plate situated at anterior end; anal opening leading to an eversible anal tube, inner end with an anal ring bearing 10 or more setae. Mostly found on grasses.
Figure 7 in Integrative taxonomic analysis of new collections from the central Angolan highlands resolves the taxonomy of African pipistrelloid bats on a continental scale
Figure 7. Lateral photograph of the alcohol-preserved head and anterior portion of the forearm and thumb of the holotype of N. hlandzeni, DM 8423 (left) and close-up photographs of the thumb and proximal forearm of the holotype, DM 8423 (centre) and paratype, DM 8422 (right) showing a distinct white marking at the base to the thumb. The thumb (encircled) is slightly longer than that of a typical pipistrelloid bat.
Figure 6 in Integrative taxonomic analysis of new collections from the central Angolan highlands resolves the taxonomy of African pipistrelloid bats on a continental scale
Figure 6. Dorsal, ventral, lateral cranial and lateral mandibular views of DM 8423 (holotype) and DM 8422 (paratype) of N. hlandzeni sp. nov. Scale bar represents 1 mm.
Figure 5 in Integrative taxonomic analysis of new collections from the central Angolan highlands resolves the taxonomy of African pipistrelloid bats on a continental scale
Figure 5. Photographs and drawings of bacula of N. hlandzeni sp. nov. from Eswatini (DM 8423, 8422), KwaZulu-Natal Province, South Africa (DM 2269, 8787, 5353, 5358), together with N. anchietae from Botswana (TM 48489), Angola (FWC 7521), and Zambia (NHM 70.2632; from Hill & Harrison, 1987). In the top row, D=dorsal, L=lateral and V=ventral view. Images in the lower row are of the ventral view, except for the far right image which is of the lateral view. Abbreviations of museums as follows: DM = Durban Natural Science Museum; TM = Ditsong National Museum of Natural History; NHM = The Natural History Museum, London. FWC indicates the field number of Fenton (Woody) Cotterill. The vertical scale bar on the bottom right indicates 1 mm.
Figure 4 in Integrative taxonomic analysis of new collections from the central Angolan highlands resolves the taxonomy of African pipistrelloid bats on a continental scale
Figure 4. PCA of 12 log-transformed cranial and dental length variables (a) and plots of forearm length and mass (b) and forearm and condylobasal skull length (c) in Angolan small vespertilionid bats with anterior premolar absent (open squares: N. zuluensis; dots: L. capensis). Species identification based on DNA barcoding of the cytb, CO1 and 12S genes.
Figure 3 in Integrative taxonomic analysis of new collections from the central Angolan highlands resolves the taxonomy of African pipistrelloid bats on a continental scale
Figure 3. PCA of components 1 and 2 (a) and components 1 and 3 (b) from 12 log-transformed cranial and dental variables in DNA barcoded Angolan small vespertilionid bats with anterior upper premolar present, in comparison with positively identified samples from South Africa and Eswatini. Species identification based on DNA barcoding of the cytb, CO1 and 12S genes for P. rusticus (open squares) and N. anchietae (dots) from Angola and on either sequences or baculum photographs for N. hlandzeni (open circles) from South Africa and Eswatini and P. hesperidus (crosses) from Eswatini and South Africa.
Figure 1. Maps showing A, 19 in Integrative taxonomic analysis of new collections from the central Angolan highlands resolves the taxonomy of African pipistrelloid bats on a continental scale
Figure 1. Maps showing A, 19 localities in southern Africa of all pipistrelloid bat specimens examined by this study (numbers correspond with locality numbers given in Supporting Information, Table S1; duplicate numbers represent closely spaced GPS points classified as the same locality) and B, seven localities of six species of pipistrelloid bats collected in central Angola by the National Geographic Okavango Wilderness project (in the area demarcated by the dashed lines) between 2016 and 2019. Species identifications based on CO1, 12S RNA and cytb genes. Shaded regions represent elevations of 1200 m a.s.l. and greater. The star represents the holotype locality of N. anchietae in the western Angolan highlands.
Climate and geology overwrite land use effects on soil organic nitrogen cycling on a continental scale
<p><strong>Abstract.</strong> Soil fertility and plant productivity are globally constrained by N availability. Proteins are the largest N reservoir in soils and the cleavage of proteins into small peptides and amino acids has been shown to be the rate limiting step in the terrestrial N cycle. However, we are still lacking a profound understanding of the environmental controls of this process. Here we show that integrated effects of climate and soil geochemistry drive protein cleavage across large scales. We measured gross protein depolymerization rates in mineral and organic soils sampled across a 4000-km-long European transect covering a wide range of climates, geologies and land uses. Based on structural equation models we identified that soil organic N cycling was strongly controlled by substrate availability, e.g. by soil protein content. Soil geochemistry was a secondary predictor, by controlling protein stabilization mechanisms and protein availability. Precipitation was identified as the main climatic control on protein depolymerization, by affecting soil weathering and soil organic matter accumulation. In contrast, land use was a poor predictor of protein depolymerization. Our results highlight the need to consider geology and precipitation effects on soil geochemistry when estimating and predicting soil N cycling at large scales.</p>
A robust estimate of continental-scale terrestrial carbon sinks using GOSAT XCO2 retrievals
<p>The dataset contains monthly terrestrial ecosystem carbon fluxes (NEE) for 51 terrestrial regions from 2011-2014. We used simulations from 12 terrestrial biosphere models (TBMs) as the prior carbon fluxes, therefore the posterior carbon fluxes correspond to the 12 TBMs.</p>
Scaling up experimental stress responses of grass invasion to predictions of continental-level range suitability
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Data from: Genetic structure and effective population sizes in European red deer (Cervus elaphus) at a continental scale: insights from microsatellite DNA
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Data from: A generalizable energetics-based model of avian migration to facilitate continental-scale waterbird conservation
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Data from: Continental-scale biogeographic variation: provinces versus gradients in the Upper Ordovician of Laurentia
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Data from: Continental-scale patterns reveal potential for warming-induced shifts in cattle diet
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Data from: Population genetic structure and its implications for adaptive variation in memory and the hippocampus on a continental scale in food-caching black-capped chickadees
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Evolutionary constraints and adaptation shape the size and colour of rain forest fruits and flowers at continental scale
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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)
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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.