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163 results for “Localization Relations”
The relative influence of history, climate, topography and vegetation structure on local animal richness varies among taxa and spatial grains
<p>Understanding the spatial scales at which environmental factors drive species richness patterns is a major challenge in ecology. Due to the trade-off between spatial grain and extent, studies tend to focus on a single spatial scale, and the effects of multiple environmental variables operating across spatial scales on the pattern of local species richness have rarely been investigated.</p> <p>Here, we related variation in local species richness of ground beetles, landbirds, and small mammals to variation in vegetation structure and topography, regional climate, biome diversity, and glaciation history for 27 sites across the USA at two different spatial grains.</p> <p>We studied the relative influence of broad-scale (landscape) environmental conditions using variables estimated at the site level (climate, productivity, biome diversity, and glacial era ice cover) and fine-scale (local) environmental conditions using variables estimated at the plot level (topography and vegetation structure) to explain local species richness. We also examined whether plot-level factors scale up to drive continental scale richness patterns. We used Bayesian hierarchical models and quantified the amount of variance in observed richness that was explained by environmental factors at different spatial scales.</p> <p>For all three animal groups, our models explained much of the variation in local species richness (85-89%), but site-level variables explained a greater proportion of richness variance than plot-level variables. Temperature was the most important site-level predictor for explaining variance in landbirds and ground beetles richness. Some aspects of vegetation structure were the main plot-level predictors of landbird richness. Environmental predictors generally had poor explanatory power for small mammal richness, while glacial era ice cover was the most important site-level predictor.</p> <p>Relationships between plot-level factors and richness varied greatly among geographical regions and spatial grains, and most relationships did not hold when predictors were scaled up to continental scale. Our results suggest that the factors that determine richness may be highly dependent on spatial grain, geography, and animal group. We demonstrate that instead of artificially manipulating the resolution to study multi-scale effects, a hierarchical approach that uses fine grain data at broad extents could help solve the issue of scale selection in environment-richness studies. </p>
Distribution. Brazilian Amazon, S of the Rio Amazonas, between the rios Xingu and Iriri in the states of Para and Mato Grosso. Only three widely separated localities are known, one is relatively close to the type locality and another on the right (S) bank of the Rio Iriri in Para. in Phitheciidae
Distribution. Brazilian Amazon, S of the Rio Amazonas, between the rios Xingu and Iriri in the states of Para and Mato Grosso. Only three widely separated localities are known, one is relatively close to the type locality and another on the right (S) bank of the Rio Iriri in Para.
Distribution. Known only from type locality on S coast of Seram I, Indonesia. Descriptive notes. Head-body 123 mm, tail 128 mm, ear 14-6 mm, hindfoot 26-2 mm; weight 65 g (all mensural data are from holotype). Pavel's Seram Mosaic-tailed Rat is very small-bodied, with dorsal pelage soft and brightly colored rufescent reddish brown, hairs with graybases, and venter contrastingly pure white; tail is slightly longer than head-body length, all black in color, tail scales raised, one hair per scale, scale hairs very short. Upper surfaces of feet are dark gray; hindfeet broad, with first digit long. Cranium is relatively narrow, with nasal profile flat; teeth very small. Single known specimen (the holotype), a pregnant female, has four mammae. in Muridae
Distribution. Known only from type locality on S coast of Seram I, Indonesia. Descriptive notes. Head-body 123 mm, tail 128 mm, ear 14-6 mm, hindfoot 26-2 mm; weight 65 g (all mensural data are from holotype). Pavel's Seram Mosaic-tailed Rat is very small-bodied, with dorsal pelage soft and brightly colored rufescent reddish brown, hairs with graybases, and venter contrastingly pure white; tail is slightly longer than head-body length, all black in color, tail scales raised, one hair per scale, scale hairs very short. Upper surfaces of feet are dark gray; hindfeet broad, with first digit long. Cranium is relatively narrow, with nasal profile flat; teeth very small. Single known specimen (the holotype), a pregnant female, has four mammae.
FIGURE 11 in The return of the Duke - locality data for Megadytes ducalis Sharp, 1882, the world's largest diving beetle, with notes on related species (Coleoptera: Dytiscidae)
FIGURE 11. Distribution of the subgenus Bifurcitus in Central and South America: White line: distribution of M. lherminieri; black line: distribution of M. magnus; red spot: only known locality for M. ducalis.
FIGURE 7 in The return of the Duke - locality data for Megadytes ducalis Sharp, 1882, the world's largest diving beetle, with notes on related species (Coleoptera: Dytiscidae)
FIGURE 7. Megadytes ducalis, male from collection Guignot: A) frontal view, B) ventral view of head and protarsus, C) left middle leg, D) dorso-lateral view of left side of head, pronotum and elytral base, E) ventro-lateral view of left hind leg. Scale bars = 5 mm.
FIGURE 3 in The return of the Duke - locality data for Megadytes ducalis Sharp, 1882, the world's largest diving beetle, with notes on related species (Coleoptera: Dytiscidae)
FIGURE 3. Female of M. ducalis from collection Régimbart in MNHN [TL = 47.4 mm], the largest known diving beetle specimen in the world: "San Antônio da Barra, Prov. de Bahia, Brésil".
FIGURE 6 in The return of the Duke - locality data for Megadytes ducalis Sharp, 1882, the world's largest diving beetle, with notes on related species (Coleoptera: Dytiscidae)
FIGURE 6. Megadytes magnus: A) median lobe with parameres in ventral view, B) tip of median lobe in lateral view, C) median lobe in ventro-apical view to show the long nose-like tip. Scale bars = 1.5 mm.
FIGURE 1 in The return of the Duke - locality data for Megadytes ducalis Sharp, 1882, the world's largest diving beetle, with notes on related species (Coleoptera: Dytiscidae)
FIGURE 1. Habitus in dorsal view of: A) M. ducalis, B) M. lherminieri, C) M. magnus; habitus in ventral view of: D) M. ducalis, E) M. lherminieri (Ecuador, Esmeraldas), F) M. magnus (Paraguay, Cerro Lambaré).
FIGURE 5 in The return of the Duke - locality data for Megadytes ducalis Sharp, 1882, the world's largest diving beetle, with notes on related species (Coleoptera: Dytiscidae)
FIGURE 5. Megadytes lherminieri: A) median lobe with parameres in ventral view, B) tip of median lobe in lateral view, C) median lobe in ventro-apical view to show the flat tongue-like tip. Scale bars = 1.5 mm.
FIGURE 8 in The return of the Duke - locality data for Megadytes ducalis Sharp, 1882, the world's largest diving beetle, with notes on related species (Coleoptera: Dytiscidae)
FIGURE 8. Megadytes lherminieri, male, Ecuador, Esmeraldas: A) ventral view of head, left protarsus and left middle leg, B) dorsal view of left protarsus, C) ventro-lateral view of left hind leg; M. magnus, male, Paraguay, cerro Lambaré: D) ventral view of head, right protarsus and right middle leg, E) dorsal view of left protarsus, F) ventro-lateral view of left hind leg. Scale bars = 5 mm.
FIGURE 9 in The return of the Duke - locality data for Megadytes ducalis Sharp, 1882, the world's largest diving beetle, with notes on related species (Coleoptera: Dytiscidae)
FIGURE 9. Habitat of M. lherminieri in Guadeloupe: (A) Pond in Savane Desrosière, Anse Bertrand, Grande-Terre, Guadeloupe, 27.VIII. 2013, N16°30'09" W61°28'25"; (B) Pond near Sainte Anne, Grande-Terre, Guadeloupe, 17.VIII. 2013, N16°14'19"/W61°21'03.6" (Photos: M. Manuel).
X-ray Binary Luminosity Function Scaling Relations for Local Galaxies Based on Subgalactic Modeling
<p>Property maps (SFR and M*) and processed Chandra images for the 38 galaxies from Lehmer et al. (2019).</p>
Data related to the manuscript "Visualizing endogenous Rho activity with an improved localization-based, genetically encoded biosensor"
<p>These are the data that are related to the manuscript "Visualizing endogenous Rho activity with an improved localization-based, genetically encoded biosensor" by </p> <p>Eike K. Mahlandt<sup>1,*</sup>, Janine J. G. Arts<sup>1,2</sup>,Werner J. van der Meer<sup>1</sup>, Franka H. van der Linden<sup>1</sup>, Simon Tol<sup>2</sup>, Jaap D. van Buul<sup>1,2</sup>, Theodorus W. J. Gadella Jr.<sup>1</sup>, Joachim Goedhart<sup>1,*</sup></p> <p><sup>1</sup> Swammerdam Institute for Life Sciences, Section of Molecular Cytology, van Leeuwenhoek Centre for Advanced Microscopy, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands</p> <p><sup>2</sup> Molecular Cell Biology Lab at Dept. Molecular Hematology, Sanquin Research and Landsteiner Laboratory, Amsterdam, The Netherlands</p>
Global and local drivers of the relative importance of allochthonous and autochthonous energy sources to freshwater food webs
<p>Resource quantity (i.e., organic matter; OM) is a main driver of the prevailing energy pathway in freshwater food webs. The OM pool is mainly composed of allochthonous material, a primary resource for freshwater consumers. Contrastingly, small amounts of autochthonous OM (i.e., algae) can subsidize aquatic communities due to its higher nutritional quality. To date, there is no consensus about the relative importance of allochthonous and autochthonous OMs for freshwater food webs or the environmental factors driving their relative importance. We fill this gap by evaluating the relative importance of allochthonous and autochthonous OM sources for freshwater food webs on a global scale through a meta-analytical approach. We gathered the outcome of stable isotope mixing models of 2,789 cases from 58 published studies and calculated a response ratio between the mean contributions of allochthonous and autochthonous OM for freshwater consumers. Using mixed-effect models and a multimodel inference approach, we tested the influence of latitude, habitat type, ecosystem size, climate, and terrestrial productivity over the response ratio. The relative contribution of autochthonous was higher in lotic systems. In lentic systems, increasing terrestrial productivity increased the relative contribution of autochthonous OM, while increasing precipitation and temperature seasonality reduced this relative contribution. We suggested that factors increasing terrestrial productivity might also boost autochthonous OM in these systems, while precipitation increases the transport of allochthonous OM to freshwater habitats. We did not find any relationship between environmental factors and the relative contribution of autochthonous OM for lotic systems. We concluded that the relative contribution of allochthonous and autochthonous energy sources to freshwater food webs differs between lotic and lentic ecosystems and it is dependent on multiple environmental factors.</p>
Fig. 5 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 5. DESI-MS/MSI of OPDA and OPC-8 in the developing Phaseolus vulgaris seeds. (a) Optical image of the seed section for OPDA analysis. (b) MS/MS spectrum of precursor ion at m/z 291.1966 ± 1 Da obtained at the target enhanced mode for m/z 165.1. (c) Ion image at m/z 165.1300. (d) Optical image of the seed section for OPC-8:0 analysis. (e) MS/MS spectrum of precursor ion at m/z 293.2122 ± 1 Da obtained at the target enhanced mode for m/z 225.1. Ion images at m/z (f) 223.1400 and (g) 231.2142. Scale bar = 2 mm. Compound names are defined in Table 1.
Fig. 4 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 4. LC-ESI-MS/MS analysis of JA-related compounds in the extracts from the radicle and seed coat of developing Phaseolus vulgaris seeds. MS/MS spectra of peaks at (a) 5.3 min in Fig. 3c, (b) 5.3 min in Fig. 3d, (c) 6.5 min in Fig. 3c and (d) 6.5 min in Fig. 3d and (e) 6.3 min in Fig. 3e and (f) 6.3 min in Fig. 3f and (g) 6.4 min in Fig. 3e, (h) 6.4 min in Fig. 3f, (i) 6.7 min in Fig. 3e, and (j) 6.7 min in Fig. 3f. Compound names are defined in Table 1.
Fig. 2 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 2. LC-ESI-MS/MS analysis of JA-related compound standards. Spectra of (a) OPDA, (b) OPC-8:0, and (c) JA standards. Compound names are defined in Table 1.
Fig. 1 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 1. DESI-MSI analysis of JA-related compounds in the developing Phaseolus vulgaris seeds. (a) Optical image of the section. (b) Mass spectrum obtained from the section. Ion images of m/z (c) 277.2172, (d) 291.1953, and (e) 293.2117. Three different developing seeds were analyzed, and the results from one are shown as representative data. Scale bar = 2 mm. Compound names are defined in Table 1.
Fig. 3 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 3. LC-ESI-MS analysis of JA-related compounds in the extracts from the radicle and seed coat of developing Phaseolus vulgaris seeds. Base peak chromatogram of m/z 277.2173 ±10 ppm for (a) radicle and (b) seed coat, m/z 291.1966 ± 10 ppm for (c) radicle and (d) seed coat, and m/z 293.2122 ± 10 ppm for (e) radicle and seed coat, respectively. Peaks with arrow indicates JA-related compounds: (a) and (b) αLA, (c) and (d) OPDA, and (e) and (f) OPC-8:0. Compound names are defined in Table 1.
Fig. 8 in Relative contribution of LOX10, green leaf volatiles and JA to woundinduced local and systemic oxylipin and hormone signature in Zea mays (maize)
Fig. 8. Volatiles emitted in wounded leaves of WT, lox10 and opr7opr8. (A) GLVs; (B) 13-LOX-derived C5 volatiles; (C) Volatile terpenes and indole. Volatiles were collected for 1 h after wounding. Values are mean ± standard error (n = 6). Different letters show significant differences (one-way ANOVA, S–N–K, P <0.05).
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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.