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1,188 results for “Deltas”
Strategic basin and delta planning increases the resilience of the Mekong Delta under future uncertainty
<p># Geospatial data and analysis results for:</p> <p>Schmitt R. J. P., Giuliani, M., Bizzi, S., Kondolf, G. M., Daily, G. C., Castelletti, A. (2021). Strategic basin and delta planning increases the resilience of the Mekong Delta under future uncertainty (accepted for publication in the Proceedings of the National Academy of Sciences). </p> <p><br> # Prepared by R. Schmitt (rschmitt@stanford.edu), July 2021. </p> <p># Abstract: </p> <p>The climate resilience of river deltas is threatened by rising sea levels, accelerated land subsidence, and reduced sediment supply from contributing river basins. Yet, these uncertain and rapidly changing threats are rarely considered in conjunction. Here we provide an integrated assessment, on basin- and delta-scales, to identify key planning levers for increasing the climate resilience of the Mekong Delta. We find, first, that 23 % to 90 % of this unusually productive delta might fall below the sea level by 2100, with the large uncertainty driven mainly by future management of groundwater pumping and associated land subsidence. Second, maintaining sediment supply from the basin is crucial, under all scenarios, to maintaining delta land and enhancing the climate resilience of the system. We then use a bottom-up approach to identify basin development scenarios that are compatible with maintaining sediment supply at current levels. This analysis highlights, third, that strategic placement of hydropower dams will be more important for maintaining sediment supply than either projected increases in sediment yields or sediment management at individual dams. Our results demonstrate (1) the needs for integrated planning across basin and delta scales, (2) the role of river sediment management as a nature-based solution to increase delta resilience, and (3) global benefits from strategic basin management to maintain resilient deltas, especially under uncertain and changing conditions.</p> <p> </p> <p># Contents:<br> Mekong_Basin_geomorphic provinces.gpkg: location of geomorphic provinces and the associated sediment load. Digtized and modified from Kondolf et al., 2014<br> Schmitt_et_al_PNAS_2020-26127P.m: Script demonstrating the robust analysis and the derivation of decision surfaces (e.g., Fig. 3, f, g and Figure 4)<br> Data PNAS_2020-26127P.mat: Resimulation data (i.e., sediment yield and dam sediment trapping multipliers and the response in terms of sediment delivery to the delta) </p>
Comparing the Influence of Global Warming and Urban Anthropogenic Heat on Extreme Precipitation in Urbanized Pearl River Delta Area Based on WRF Dynamical Downscaling
<p>The simulation outputs from the Weather Research and Forecasting (WRF) v3.8.1 coupled with single layer urban canopy model from three experiments (HIST_AH300, HIST_AH0, and RCP85_AH300).</p> <p>Variables include hourly precipitation, wind, specific humidity, relative humidity, convective available potential energy, convective inhibition, temperature, model height, land use land cover, and topography.</p> <p> </p>
Figure 4 in Stranded humpback whale (Megaptera novaeangliae) (Cetacea: Balaenopteridae) in Paraná River Delta, Buenos Aires Province, Argentina. Comments on the occurrence of marine
Figure 4. Median-joining network based on the cytochrome c oxidase subunit I mtDNA haplotypes of Megaptera novaeangliae. Haplotypes are represented with discs and colors that indicate geographical locations. Mutational steps are indicated with stripes.
Figure 1 in Stranded humpback whale (Megaptera novaeangliae) (Cetacea: Balaenopteridae) in Paraná River Delta, Buenos Aires Province, Argentina. Comments on the occurrence of marine
Figure 1. Paraná River delta map were Megaptera novaeangliae (CFA-MA-13084) was found dead (exact location is indicated with a black dot).
Fig. 5 in Nematode morphometry and biomass patterns in relation to community characteristics and environmental variables in the Mekong Delta, Vietnam
Fig. 5. Frequency distribution of L/W ratios at the mouth stations (a) and Co Chien estuary (b).
Guadiana river delta bathymetry surveys from 1944 to 1992 (digitalization)
<p>Digitalization of Guadiana river delta bathymetry.</p> <p>Data consists of vector points and lines (shapefile) with bathymetric values (z) as reference to Hydrographic Zero (Z.H.): 2 m bellow mean sea level, observed in Cascais tidal gauge, Portugal.</p> <p>It also has *.csv files (zxy) of the point data.</p> <p>Data was manually digitized from paper charts regarding the following surveys (month/year):</p> <p>?/1944; may, june/1958; june/1967; may, june/1969; march, april/1973; april/1977; july/1982; april, may/1986; april/ 1988; july/august/ 1992.</p> <p>Original map scale is 1:5000.</p> <p>Digitalization o paper charts produced 0.67 m x 0.65 m cell size raster files.</p> <p>All data is projected to ESPG: 3763 (ETRS89 / Portugal TM06).</p> <p>Surveys were originally performed by Portuguese hydrographic authorities:</p> <p>Brigada Hidrográfica 4; MOPTC - DSF - DCME</p> <p> </p>
pyDeltaRCM sample data -- Golf Delta
<p>This model run was created to generate sample data.<br> Model was run on 10/14/2021, at the University of Texas at Austin.</p> <p>Run was computed with pyDeltaRCM v2.1.0. See log file for complete information<br> on system and model configuration.</p> <p>Data available at Zenodo, version 1.1: 10.5281/zenodo.5570962.</p> <p>Version history:<br> v1.1: 10.5281/zenodo.5570962<br> v1.0: 10.5281/zenodo.4456144<br> </p>
two-slope Gilbert and hyperpycnal deltas - dataset
<p>Experimental images, measured profiles and parameter values used for two-slope Gilbert and hyperpycnal deltas</p>
Supplementary Dataset for "Synthetic Witherite for Standardization of Clumped Isotope (Delta 47) Analyses"
<p>This supplementary dataset contains raw clumped isotopic data used to generate figures in the article "Synthetic Witherite for Standardization of Clumped Isotope (Delta 47) Analyses" by Kong et al. </p>
Maps of predicted carbon dioxide and methane fluxes from waterbodies in the Yukon-Kuskokwim Delta, Alaska
<p>In the Arctic, waterbodies are abundant, and rapid thaw of permafrost is destabilizing the carbon cycle and changing hydrology. It is particularly important to quantify and accurately scale aquatic carbon emissions in arctic ecosystems. Recently available high-resolution remote sensing datasets capture the physical characteristics of arctic landscapes at unprecedented spatial resolution. We demonstrate how machine learning models can capitalize on these spatial datasets to greatly improve accuracy when scaling waterbody CO<sub>2</sub> and CH<sub>4</sub> fluxes across the Yukon-Kuskokwim (YK) Delta of south-west AK. These datasets include carbon dioxide and methane dissolved concentrations and diffusive fluxes from a research watershed in the central YK Delta. </p>
Landcover map for the central region of the Yukon-Kuskokwim Delta, Alaska
<p>Climate change is causing an intensification in tundra fires across the Arctic, including the unprecedented 2015 fires in the Yukon-Kuskokwim (YK) Delta. The YK Delta contains extensive surface waters (∼33% cover) and significant quantities of organic carbon, much of which is stored in vulnerable permafrost. Inland aquatic ecosystems act as hot-spots for landscape CO<sub>2</sub> and CH<sub>4</sub> emissions and likely represent a significant component of the Arctic carbon balance, yet aquatic fluxes of CO<sub>2</sub> and CH<sub>4</sub> are also some of the most uncertain. We measured dissolved CH<sub>4 </sub>and CO<sub>2</sub> concentrations (n = 364), in surface waters from different types of waterbodies during summers from 2016 to 2019. We used Sentinel-2 multispectral imagery to classify landcover types and area burned in contributing watersheds. We develop a model using machine learning to assess how waterbody properties (size, shape, and landscape properties), environmental conditions (O<sub>2</sub>, temperature), and surface water chemistry (dissolved organic carbon composition, nutrient concentrations) help predict in situ observations of CH<sub>4 </sub>and CO<sub>2</sub> concentrations across deltaic waterbodies. CO<sub>2</sub> concentrations were negatively related to waterbody size and positively related to waterbody edge effects. CH<sub>4</sub> concentrations were primarily related to organic matter quantity and composition. Waterbodies in burned watersheds appeared to be less carbon limited and had longer soil water residence times than in unburned watersheds. Our results illustrate the importance of small lakes for regional carbon emissions and demonstrate the need for a mechanistic understanding of the drivers of greenhouse gasses in small waterbodies.</p>
Sea turtle relative abundance in nearshore waters adjacent to the Mississippi River delta, Gulf of Mexico, United States
<p><span>We measured the relative abundance of sea turtles using standardized transect surveys conducted during the summer and fall of 2013 in neritic waters surrounding the Mississippi River delta in Louisiana, USA. Data comprise sea turtle locations, observation circumstances, and environmental covariates recorded at the beginning of each transect and at the time of each turtle observation. Turtles were recorded by species and size class, as well as location in the water column and the distance the turtle was from the transect line. Transects were performed on an 8.2-meter vessel with two observers atop a 4.5-meter elevated platform, with vessel speed standardized at ~15 km/hr. These data are the first to describe relative abundance of sea turtles observed from small vessels in this region. Detection of turtles <45 cm SSCL and data detail are greater than aerial surveys. The data serve to inform resource managers and researchers regarding these protected marine species. </span></p>
Biomarker indices and concentrations and biomarker-based temperature estimates from the Iberian Margin core MD95-2042, composite atmospheric temperature record from Greenland, and stacks of delta 18Oice and atmospheric temperature records from three Antarctic sites
<p>Core MD95-2042 alkenone and GDGT data: This dataset provides the following information for core MD95-2042: depth, age, summed OH-GDGT, iGDGT, and di-unsaturated and tri-unsaturated C<sub>37</sub> alkenone concentrations, OH-GDGT-based, iGDGT-based, and alkenone-based paleothermometric indices, GDGT-2/GDGT-3 ratio, and biomarker-based sea surface temperature (SST) and 0‐ to 200‐m sea temperature (subT; gamma function probability distribution for target temperatures with a = 4.5 and b = 15) estimates. Sediment samples were taken every 5 cm from core MD95-2042 and homogenized before lipid extraction. The lipid extracts were splitted into two fractions: one for alkenone analysis by gas chromatography coupled to a flame ionization detector, and the other for GDGT analysis by high-performance liquid chromatography coupled to mass spectrometry. All GDGT analyses were done in duplicate. The 1σ analytical uncertainties from 37 replicate analyses of the core catcher sample from core MD95-2042 are 0.007 (0.4 °C) for RI-OH, 0.008 (0.2 °C) for RI-OH′, 0.003 (0.2 °C) for TEX<sub>86</sub>, 0.238 for GDGT-2/GDGT-3, and 0.010 (0.26 °C) for U<sup>K′</sup><sub>37</sub>. RI-OH′-SST estimates are from the following global calibration: SST = (RI-OH′ + 0.029)/0.0422 (Fietz et al., 2020). RI-OH-SST estimates are from the following global calibration: SST = (RI-OH − 1.11)/0.018 (Lü et al., 2015). TEX<sub>86</sub><sup>H</sup>-SST estimates are from the following regional paleocalibration: SST = 68.4 × TEX<sub>86</sub><sup>H</sup> + 33.0 (Darfeuil et al., 2016). U<sup>K′</sup><sub>37</sub>-SST estimates are from the following global calibration: SST = 29.876 × U<sup>K′</sup><sub>37</sub> − 1.334 (Conte et al., 2006). Bayesian calibrations were also used for TEX<sub>86</sub>-SST and TEX<sub>86</sub>-subT estimates (BAYSPAR; Tierney & Tingley, 2014, 2015) and for U<sup>K′</sup><sub>37</sub>-SST estimates (BAYSPLINE; Tierney & Tingley, 2018). Alkenone data covering the 160–70 and 70–0 ka BP periods are from Davtian et al. (2021) and Darfeuil et al. (2016), respectively. GDGT data covering the 160–45 ka BP period are from Davtian et al. (2021). The age model of core MD95-2042 for the 160–43 and 43–0 ka BP periods was obtained by tuning to Chinese speleothems (Cheng et al., 2016) and by recalibrating existing <sup>14</sup>C ages with the Marine20 calibration curve (Heaton et al., 2020), respectively. MIS, Marine Isotope Stage; GDGT, glycerol dialkyl glycerol tetraether; and N/A, not available.</p> <p>Greenland atmospheric temperature record: This dataset consists in a composite Greenland atmospheric temperature record, which was built with the following records: the GISP2 atmospheric temperature record by Kobashi et al. (2017) for the 10–0 ka BP period, the NGRIP atmospheric temperature record by Kindler et al. (2014) for the 120–10 ka BP period, and the NEEM atmospheric temperature record by NEEM community members (2013) for the 129–120 ka BP period. The NEEM temperature anomalies obtained by NEEM community members (2013) were shifted by –31 °C to obtain absolute air temperatures. The employed age model is the one of Davtian and Bard (2023) for Greenland and Antarctic ice-core records.</p> <p>Antarctic δ<sup>18</sup>O<sub>ice</sub> and atmospheric temperature stacks: This dataset consists in two stacks of three Antarctic records (EDC, EDML, and WD), one for δ<sup>18</sup>O<sub>ice</sub> and the other for atmospheric temperature: both stacks are provided with their stacking uncertainties. To build the Antarctic δ<sup>18</sup>O<sub>ice</sub> stack, the Antarctic δ<sup>18</sup>O<sub>ice</sub> records were resampled every 10 years before centering to zero means and normalization to unit standard deviations over the 140–0 ka BP period (68–0 ka BP for WD). To optimize the continuity between the portions with and without the WD ice core, the Antarctic δ<sup>18</sup>O<sub>ice</sub> records were centered to zero means over the 68–67 ka BP period. The resulting Antarctic δ<sup>18</sup>O<sub>ice</sub> records were then averaged and stacking uncertainties were calculated as the pooled standard deviation of the stacked Antarctic δ<sup>18</sup>O<sub>ice</sub> records divided by the square root of the number of stacked Antarctic δ<sup>18</sup>O<sub>ice</sub> records. The final Antarctic δ<sup>18</sup>O<sub>ice</sub> stack, expressed in ‰, has the same standard deviation as the δ<sup>18</sup>O<sub>ice</sub> record from EDML over the 140–0 ka BP period, and has a zero mean over the 1–0 ka BP. The Antarctic atmospheric temperature stack was built like the Antarctic δ<sup>18</sup>O<sub>ice</sub> stack, except that the Antarctic δ<sup>18</sup>O<sub>ice</sub> records were corrected for seawater δ<sup>18</sup>O<sub>ice</sub> variations before conversion into atmospheric temperature. The employed age model is the one of Davtian and Bard (2023) for Greenland and Antarctic ice-core records.</p>
Electronic supplemental material for Mann et al. "Multi-decadal records of shoreline erosion reveal the roles of river delta dynamics, hard protection measures, and other interventions in Eastern Ghana"
<p>Electronic supplemental material for Mann et al. "Multi-decadal records of shoreline erosion reveal the roles of river delta dynamics, hard protection measures, and other interventions in Eastern Ghana"</p> <p><br> The supplemental material comprises the database "Geodatabase Ghana.mdb" and the MSc thesis by Aleksandra Serwa (Serwa 2017), the results of which built the foundation for the paper.</p> <p>The database contains one layer with all digitized shorelines (HWL_END) as indicated in table 1 of the manuscript, and additional baseline and transect layers that are necessary for the shoreline change analyses with DSAS (Thieler & Danforth 1994). Further information can be found in Serwa (2017).</p> <p>References:</p> <p>Serwa, A., 2017. Shoreline changes in the Keta Municipal District (Ghana): Evidence from multi-decadal records. Master Thesis, Department of Geosciences, University of Bremen, 88 p.</p> <p><br> Thieler, E.R. & Danforth, W.W., 1994. Historical Shoreline Mapping ( II ): Application of the Digital Shoreline Mapping and Analysis Systems ( DSMS / DSAS ) to Shoreline Change Mapping in Puerto Rico. Journal of Coastal Research, 10(3), pp.600–620.</p>
DeLTA 2.0: A deep learning pipeline for quantifying single-cell spatial and temporal dynamics
<p>Datasets associated with https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009797</p>
Evaluations on numerical simulations of ozone dry deposition over the Yangtze River Delta
<p>Regional simulation of ozone dry deposition is an important tool for understanding ozone pollution threats and quantifying the ozone impact on terrestrial ecosystems. In this study, we evaluate ozone dry deposition in the Yangtze River Delta (YRD) region using two different dry deposition schemes. The WRF-Chem model, Wesely dry deposition scheme, and revised Surfatm dry deposition scheme were used to simulate the ozone dry deposition process in the YRD region, and results are compared with the observation over a winter wheat field. The results show that the simulated ozone concentrations (<em>c</em><sub>O3</sub>) of the two dry deposition schemes were good and lower than the measurements. The simulated ozone dry deposition velocity (<em>V</em><sub>d</sub>) in the Surfatm dry deposition scheme was more close to the measurements. The mean value of <em>c</em><sub>O3 </sub>and <em>V</em><sub>d</sub> in the YRD region ranged from 30 to 50 nL·L<sup>−1</sup> and from 0.2 to 0.5 cm·s<sup>−1 </sup>in the daytime, respectively. To improve the simulation results of the ozone dry deposition process, the simulation errors due to different land use types, the meteorological factors on dry deposition resistance functions, and the influence of chemical reactions must all be considered.</p>
SARS-CoV-2 vaccine breakthrough infections by Omicron and Delta variants in healthcare workers
<p>An observational prospective cohort study was conducted in vaccinated employees with acute SARS-CoV-2 infection between October 2021 and February 2022. Serological and molecular testing was performed to determine SARS-CoV-2 viral load, lineage, antibody levels, and neutral-ising antibody titres. A total of 571 (9.7%) employees experienced SARS-CoV-2 breakthrough infections during the enrolment period, of which 81 were included. The majority (n=79, 97.5%) was symptomatic and most (n=75, 92.6%) showed Ct-values < 30 in RT-PCR assays. Twenty-four (30%) remained PCR-positive for > 15 days. Neutralizing antibody titres were strongest for the wildtype, intermediate for Delta and lowest for Omicron variants. Omicron infections occurred at higher anti-RBD-IgG serum levels (p= 0.00001) and showed a trend for higher viral loads (p=0.14, median Ct-difference 4.3, 95% CI [-2.5-10.5]). For both variants, viral loads were signifi-cantly higher in participants with lower anti-RBD-IgG serum levels (p=0.02). </p>
Dataset for a study:Clinical characteristics of SARS-CoV-2 delta variant infection in Xiamen
<p>This retrospective study aims to identify the clinical and demographic features of patients infected with the SARS-CoV-2 delta variant at a single institution in Xiamen, China.</p>
Abb. 1 in Kurzbeitrag Ungewöhnlicher Nestbau von Delta unguiculatum (Villers, 1789) (Hymenoptera, Vespidae)
Abb. 1. Einzelliges Nest im Bau, aufgenommen in Solothurn am 31.7.2006. (Foto Felix Amiet)
Abb. 2 in Kurzbeitrag Ungewöhnlicher Nestbau von Delta unguiculatum (Villers, 1789) (Hymenoptera, Vespidae)
Abb. 2. Altes mehrzelliges Nest in Solothurn am 13.12.2018. (Foto Felix Amiet)
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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)
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.