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2,021 results for “valley”
InSAR data from 2016 to 2018 for the Tulare Basin in California's Central Valley
<p>This file contains InSAR range change observations for the Tulare basin in California's Central Valley. The values are cumulative range change from January 1, 2016 to January 1, 2018. The range change estimates were provided by Tom Farr of CalTech's Jet Propulsion Laboratory.</p>
Nitrogen publications in the Yaqui Valley (1990-2020)
<p>This database contains categorized publications based on an organized search of scientific literature published in Springer (https://www.springer.com/la), Science Direct (https://www.sciencedirect.com/), sciElo (https://scielo.org/), Redalyc (https://www.redalyc.org/), International Maize and Wheat Improvement Center (CIMMYT) Repository (https://www.cimmyt.org/) and Sonora Institute of Technology (ITSON) library (http://sib2.itson.mx/cgi-bin/koha/opac-main.pl) databases. The Google Scholar search was also used to retrieve as many publications as possible; however, we considered the database origin for the analysis. The search was limited in terms of the used databases, since they were chosen for being among the most complete on national and international publications related to the research topic</p>
USGSG16AP00094: Developing a seismic velocity model of the central valley, northern California: model SSJD2016
<p>Seismic velocity model SSJD2016 uses earthquake travel-time, ambient noise group velocity and gravity data to update Thurber NC2009, for northern California.</p>
Figs 45-50 in New data on the Oriental Xantholinini. XXIV. Nine new taxa of Paratesba from Danum Valley, Sabah, and dichotomic key of the bornean species (Coleoptera, Staphylinidae). 221° contribution to the knowledge of the Staphylinidae
Figs 45-50: Aedeagus, tergite and sternite of male genital segment of Paratesba fluvialis nov.sp. (45-47); P. lithocarpi nov.sp. (48-50).
Figs 11-18 in New data on the Oriental Xantholinini. XXIV. Nine new taxa of Paratesba from Danum Valley, Sabah, and dichotomic key of the bornean species (Coleoptera, Staphylinidae). 221° contribution to the knowledge of the Staphylinidae
Figs 11-18: Head and pronotum (right half omitted) of Paratesba minuta nov.sp. (11-12); head (right half omitted) and anterior angle of pronotum of Paratesba rougemonti nov.sp. (13-14); P. rubescens nov.sp. (15-16); P. silvestris nov.sp. (17-18).
Figs 27-30 in New data on the Oriental Xantholinini. XXIV. Nine new taxa of Paratesba from Danum Valley, Sabah, and dichotomic key of the bornean species (Coleoptera, Staphylinidae). 221° contribution to the knowledge of the Staphylinidae
Figs 27-30: Head and pronotum (right half omitted) of Paratesba lithocarapi nov.sp. (27-28); head (right half omitted) and anterior angle of pronotum of Paratesba differens nov.sp. (29-30).
Figs 19-26 in New data on the Oriental Xantholinini. XXIV. Nine new taxa of Paratesba from Danum Valley, Sabah, and dichotomic key of the bornean species (Coleoptera, Staphylinidae). 221° contribution to the knowledge of the Staphylinidae
Figs 19-26: Head (right half omitted) and anterior angle of pronotum of Paratesba danum BORDONI (19-20); P. sabahensis nov.sp. (21-22); P. confusa nov.sp. (23-24); P. fluvialis nov.sp. (25-26).
Figs 39-44 in New data on the Oriental Xantholinini. XXIV. Nine new taxa of Paratesba from Danum Valley, Sabah, and dichotomic key of the bornean species (Coleoptera, Staphylinidae). 221° contribution to the knowledge of the Staphylinidae
Figs 39-44: Aedeagus, tergite and sternite of male genital segment of Paratesba sabahensis nov.sp. (39-41); P. confusa nov.sp. (42-44).
Fig. 1 in The aquatic malacofauna (Gastropoda et Bivalvia) in the Bluntau Valley in the Federal State of Salzburg (Austria)
Fig. 1: (a) View into the Bluntau Valley with its larger lake positioned in the center; (b) Geographic map exhibiting the main water bodies of the Bluntau Valley as well as the 20 sampling locations defined for this study.
FIG. 9 in Charophyte flora from the Miocene of Zahle (Beeka Valley, Lebanon). Biostratigraphic, palaeoenvironmental and palaeobiogeographical implications
FIG. 9. — Neogene chronostratigraphy. Suggested age of the base of the lacustrine deposits of Zahle according to the charophyte assemblage. European charophyte biozonations and distribution of species are after Riveline et al. (1996).
Supplementary material (part 2) for "On the effect of tributary valleys on thermally driven winds in the main valley: a case study in the Inn Valley"
<p>Part 2 of the supplementary material for the master's thesis "On the effect of tributary valleys on thermally driven winds in the main valley: a case study in the Inn Valley." (Deidda 2023, available at <a href="https://resolver.obvsg.at/urn:nbn:at:at-ubi:1-134436">https://resolver.obvsg.at/urn:nbn:at:at-ubi:1-134436</a>). The supplementary material consists in two parts: part 1 includes scripts, datasets, model setup files and figures (available at <a href="https://zenodo.org/records/8089010">https://zenodo.org/records/8089010</a>), while part 2 includes the model output needed to create the figures (see description below).</p><p>This directory contains part of the model output used for the thesis. The model used is WRF-ARW version 4.4 (Skamarock et al. 2021). Information on the model setup is available in the thesis, Section 2.2. For storage limitations, only the files needed to create the graphs presented in the thesis are available.</p><p>The file format is <i>type_domain_date.nc </i>where <i>domain</i> is "d01" or "d02" (respectively for the outer or inner domain, see Section 2.2 in the thesis), while <i>type</i> is "wrfout", "mean_out", or "Averaged", where:</p><ul><li>"wrfout" is the instantaneous WRF output;</li><li>"mean_out" is the time-averaged WRF output, computed using the fork <a href="https://github.com/matzegoebel/WRFlux">WRFlux</a>.</li><li>"Averaged" is a combination of time-averaged and instantaneous outputs. These files were created using the the script <i>Create_intermediate_files.py, </i>available in the <a href="https://zenodo.org/records/8089010">software directory </a>(in Scripts.zip). These files were computed to have a lighter and WRF-like formatted data containing the averaged fields needed for the analysis.</li></ul>
Land use and land cover scenarios for the Maurienne valley (French Alps) at 2085 horizon produced using CLUMPY model
<p>We built three contrasted future LULC scenarios from 2020 to 2085 with the CLUMPY model (Mazy and Longaretti, 2022). The CLUMPY model is an innovative model of land use and land cover change comprising a calibration-estimation module separate from a non-biased allocation module. It is calibrated by using time series of past LULC maps (Mazy and Longaretti, 2022). The model then calculates transition probabilities for each LULC class according to relevant spatial explanatory variables. Next, the model can produce maps of future LULC distributions according to information it learned during the calibration-estimation phase. This model has the benefits of being easy to use, proposing nonbiased allocation methods and producing scenarios of future LULC change either by adjusting manually the matrix of LULC transitions probabilities (used for the Conservation and Tourism scenarios) or by training the model on specific areas of the past time series (only used for the Conservation scenario).</p>
Biomass production at 2085 horizon for the Maurienne valley (French Alps) estimated using a Bayesian Belief Network
<p>In mountains, grasslands managed for livestock production sustain local economies, culture and identity. However, their future fodder production is highly uncertain under climate change: while an extended growing season may be beneficial, more frequent and intense summer droughts could also reduce fodder quantity and quality. Land use and land cover (LULC) changes are another major driver of regional grassland biomass production, but combined effects of future land use transitions and climate change are rarely quantified.</p> <p>We modelled combined climate and LULC scenarios for grassland production of the Maurienne Valley (French Alps) by 2100. We built a Bayesian Belief Network (BBN) from long-term grassland production monitoring data complemented with expert knowledge. We assessed the potential of two candidate adaptations, intensification as an incremental solution, and silvopastoralism as a transformative solution to compensate combined impacts of two climate scenarios and three land use change scenarios.</p> <p>Total biomass production was far more sensitive to LULC than to climate scenarios. Production losses were largest under the Conservation LULC scenario (-28% on average between 2020 and 2085), followed by the Tourism development scenario (-7%) and the Business-as-Usual scenario (+3%). Climate change under RCP 8.5 altered the seasonality of production by increasing potential production from May to July while decreasing summer regrowth. Intensification somewhat compensated effects of climate and LULC changes on biomass production, whereas silvopastoralism offered only marginal gains. The Bayesian network model explicitly captured a future increase in interannual variability in biomass production.</p> <p>Synthesis and application: Changes in LULC are more decisive for global biomass production than climate change. However, under the most extreme climate change scenario (RCP8.5), the seasonal shift in production and increased interannnual variability threaten the current grass-based Protected Designation of Origin production system. Only the intensification adaptation solution showed significant gains in total biomass production. Still, the silvopastoralism would require less investment compared to the intensification and have a similar efficiency when assessing the gains of biomass by the surface concerned with adaptation solutions. </p>
Figure 1 in Acanthodian fauna from the Early Devonian (Emsian) of Death Valley, California
Figure 1. Map showing the position and geology of the fossil locality (Elliott and Ilyes 1996, fig. 1).
Figure 2. Ischnacanthiform acanthodian dermal elements. A in Acanthodian fauna from the Early Devonian (Emsian) of Death Valley, California
Figure 2. Ischnacanthiform acanthodian dermal elements. A, fin spine FMNH-PF14560; B, fin spine fragment FMNH-PF14561. C, D, dentigerous jaw bone FMNH-PF14562, labial view; boxed area in C is enlarged in D. Scale bars=0.5 mm in A–C, 0.1 mm in D. Arrow indicates rostral direction.
Figure 3. Acanthodian fin spines and scapulocoracoid. A-C in Acanthodian fauna from the Early Devonian (Emsian) of Death Valley, California
Figure 3. Acanthodian fin spines and scapulocoracoid. A-C, Bryantonchus peracutus: A, B complete spine FMNH-PF14564; C, proximal end of spine FMNH-PF14568. D, E, Machaeracanthus sp.: D, incomplete spine FMNH-PF14573, lateral view; E, abraded spine FMNH-PF14574, dorsoventrally compressed. F-H, acanthodian indet. scapulocoracoid: F, counterpart FMNH-PF14575; G, part FMNH-PF14576; H, outline sketch. Abbreviations: IEB, insertion-exsertion boundary; k/w, worn keel or wing; plac, placoderm plate; le, leading edge; te, trailing edge; teg, trailing edge groove. Scale bars=0.5 mm in A, C–E, 0.1 mm in B, F–H.
Vulnerability tools - Drôme Valley (France)
<p>The MOVING project has developed accessible <strong>tools </strong>designed to assess susceptibility and vulnerability within the region, ready to be used by both experts and the general audience. This document synthesises crucial information for the Drôme Valley Region, particularly focusing on the Participatory Vulnerability Matrix and the Spatial Vulnerability Map. Furthermore, it includes <strong>supplementary maps and figures </strong>detailing various aspects such as the delineation of Reference Landscape, distribution of land systems, areas affected by wildfires, susceptibility to floods across different return periods, severity of forest disturbances, rainfall erosivity, and more.</p>
Plate 2. Figures 11-20. Chimarra spp. Male genitalia.11-15. Chimarra nepalensis. 11. Lateral view, 12 in Genus Chimarra Stephens, 1829 (Insecta: Trichoptera: Philopotamidae) from Suntalekhola Biodiversity Camp, Neora Valley, National Park, West Bengal
Plate 2. Figures 11-20. Chimarra spp. Male genitalia.11-15. Chimarra nepalensis. 11. Lateral view, 12. Dorsal view,
Plate 5. Figures 34-44. Chimarra spp. Adult.34-35. C. biungulata. 34. Dorsal view, 35 in Genus Chimarra Stephens, 1829 (Insecta: Trichoptera: Philopotamidae) from Suntalekhola Biodiversity Camp, Neora Valley, National Park, West Bengal
Plate 5. Figures 34-44. Chimarra spp. Adult.34-35. C. biungulata. 34. Dorsal view, 35. Ventral view.
Plate 1. Figures 1-10. Chimarra spp. Male genitalia. 1-5. Chimarra sikkimensis. 1. Lateral view, 2. Dorsal view, 3. Inferior appendage Ventral view, 4. Phallic apparatus lateral view, 5. Phallic apparatus ventral view. 6-10. C in Genus Chimarra Stephens, 1829 (Insecta: Trichoptera: Philopotamidae) from Suntalekhola Biodiversity Camp, Neora Valley, National Park, West Bengal
Plate 1. Figures 1-10. Chimarra spp. Male genitalia. 1-5. Chimarra sikkimensis. 1. Lateral view, 2. Dorsal view, 3. Inferior appendage Ventral view, 4. Phallic apparatus lateral view, 5. Phallic apparatus ventral view. 6-10. C. rifati.
ScienceDex guides
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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.