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1,806 results for “CA”
Triptych of the Descent from the Cross. Dieric Bouts. Ca 1450-1458.
<u>File Name</u>: PM_152222_E_Granada <br><u>Sublocation</u>: Cabildo de la Capilla Real <br><u>Location</u>: Granada <br><u>Province</u>: Andalucía, Granada <br><u>Country</u>: Spain <br><u>Header</u>: Triptico de la descenso cruzado/triptiek van de kruisafneming, Dieric Bouts, ca 1450-1458 <br><u>Description</u>: Triptych of the Descent from the Cross. Dieric Bouts. Ca 1450-1458. <br><u>Author</u>: Dieric Bouts (ca 1410/1415-1475) <br><u>Author Mail</u>: pmrmaeyaert@gmail.com <br><u>Copyright</u>: © Paul M.R. Maeyaert <br><u>Keywords</u>: Cultural heritage|Techniques|Painting; Cultural heritage|Techniques; Cultural heritage; Cultural heritage|Museum/private collection; Europe|Spain; Europe|Spain|Andalucía; Europe|Spain|Andalucía|Granada; Europe|Spain|Andalucía|Granada|Granada <br><u>Date of Generation</u>: 2023-12-24T14:46:58.045+02:00
Tapestry. Antependium with the monogram of Christ. Ca 1550-1600. Detail.
<u>File Name</u>: PM_152131_B_Leuven <br><u>Sublocation</u>: M Leuven <br><u>Location</u>: Leuven <br><u>Province</u>: Vlaams Brabant <br><u>Country</u>: Belgium <br><u>Header</u>: Tapijt/antependium met christusmonogram, Leuven (?), ca 1550-1600; detail <br><u>Description</u>: Tapestry. Antependium with the monogram of Christ. Ca 1550-1600. Detail. <br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Author Mail</u>: pmrmaeyaert@gmail.com <br><u>Copyright</u>: © Paul M.R. Maeyaert <br><u>Keywords</u>: Cultural heritage; Cultural heritage|Techniques|Tapestry; Cultural heritage|Techniques; Europe|Belgium; Europe|Belgium|Vlaams-Brabant; Europe|Belgium|Vlaams-Brabant|Leuven; Cultural heritage|Museum/private collection <br><u>Date of Generation</u>: 2023-12-24T13:38:44.029+02:00
CA-discharge data set, scripts and raw data
<p>Gauge locations of 295 gauges in Central Asia, including long-term norm discharge, basin outlines and basin characteristics compiled from 3rd-party data. Discharge time series for 135 gauge locations collected from the hydrological yearbooks of Hydrometeorological Organisations in Central Asia. </p> <p>Instructions of how to use the data can be found in the readme document in the folder CA-data-paper-scripts. </p> <p>! Important note: Please do not use the glacier thinning rates extracted from Hugonnet et al., 2021 (https://doi.org/10.1038/s41586-021-03436-z), i.e. features gl_dmdt_km3a and gl_dmdtda_mma. The ice density is not accounted for in our averages. </p>
Lower American River dissolved oxygen monitoring, CA (2022 - 2024)
The purpose of the Lower American River (LAR) dissolved oxygen monitoring is to provide timely information to better understand how dissolved oxygen levels in the LAR fluctuate over time and space, particularly in relation to Folsom and Nimbus Dam operations, and if conditions are stressful to adult Chinook salmon in Nimbus Basin during the fall spawning period. This information has been collected from summer 2022 to present (winter 2024) used to inform resource managers about a biologically important water quality parameter during a key period in Chinook Salmon life history so they can take action to address poor water quality using water releases from dam gates or other means. Reports are provided to the American River Group as needed, generally on a monthly basis, to support water quality management discussions.
Repeated vegetation monitoring for riparian forest restoration project, Santa Clara River, CA, 2015-2023.
We implemented a spatially-patterned methodology to restore 87 ha of riparian forest habitat, selectively applying multiple restoration approaches based on localized differences in degradation severity throughout the project area. This work was conducted as part of a large, collaborative effort to control invasive Arundo donax and reestablish contiguous natural habitat throughout the Santa Clara River floodplain in southern California.
UC Davis Suisun Marsh Fish Study, CA,1980-2024
Suisun Marsh, at the geographic center of the northern San Francisco Estuary, provides important habitat for native and non-native fishes, as well as many valued and endangered plants, reptiles, mammals, and birds. The University of California, Davis, Suisun Marsh Fish Study, in partnership with the California Department of Water Resources (DWR), has systematically monitored the marsh's fish populations since January 1980 (O'Rear et al. 2023). The study’s main purpose has been to determine natural and human-caused factors affecting fish and invertebrate distribution and abundance. All sampling has occurred in Suisun Marsh, mostly in subtidal sloughs. Sampling began in 1979, but standardized methods and stations were not implemented until 1980. Sampling has occurred monthly from January 1980 to the present at geographically fixed stations. Fixed stations have been necessary because snags preclude uninterrupted trawls in many sections of smaller sloughs. Originally, 48 stations were selected haphazardly that could be easily and safely sampled by boat and covered the breadth of Suisun Marsh to ensure capture of all variability in fish populations. However, the emphasis has been on sampling smaller sloughs because they exhibit greater variability in a smaller space than the marsh's two big sloughs (Suisun and Montezuma), and because only the big sloughs are sampled by other long-term monitoring projects such as California Fish and Wildlife's Fall Midwater Trawl. The 48 stations were sampled in 1980 and 1981. Water quality and catches were then compared across these stations to locate redundancies and thereby improve logistical efficiency while maximizing capture of variation by eliminating uninformative stations (Brown et al. 1981). Seventeen stations were then chosen and were continuously sampled from 1980 through 1993. Geographic scope was reassessed in 1994, when sampling was reinitiated in the northeast marsh in Denverton and Nurse sloughs at four stations (DV2, DV3
Soil Sampling at the Cienega Springs Ecological Reserve, Santa Clara River Watershed, CA 2020
Soil samples were collected throughout the 283-acre Cienega Springs Ecological Reserve to plan an Arundo donax removal and restoration project. Data on soil characteristics were used to model habitat suitability and plant species selection for revegetation efforts.
Chinook Salmon genetic assignments for the Central Valley Project (CVP) and State Water Projects (SWP), Sacramento and San Joaquin Delta Waters, CA, 2024-25
Central Valley Chinook Salmon populations differ in their Endangered Species Act listing status. It is difficult to visually distinguish individuals from the different Evolutionarily Significant Units. As such, many of the salmon monitoring and evaluation efforts in the Central Valley and San Francisco Bay-Delta are hampered by uncertainty about population (stock) identification and proportional effects of management actions (Dekar et al. 2013; IEP 2019). Studies have identified that the current identification method (length-at-date models) of juvenile Chinook salmon (Fisher 1992) captured in the watershed vary in their accuracy, particularly for spring-run (NMFS 2013; Harvey et al. 2014; Merz et al. 2014). The inaccuracy of the size-based methods is likely due to differences in fish distribution during early rearing, habitat-specific growth rates, and inter-annual variability in temperatures and food availability that lead to overlap in size ranges among stocks. The primary objective of this project was the genetic classification (to genetic lineage; Evolutionary Significant Unit) of Chinook Salmon captured from State Water Project and Central Valley Project fish protection facilities and Interagency Ecological Program compliance monitoring programs. The genetic lineage was determined for sampled fish by comparing their genotypes to reference genetic baselines. Genetic methods, having less statistical uncertainty that size-based models for population identification, were intended to directly target (and reduce) one source of uncertainty in the estimation of loss (take) from water diversions (operations) and develop the information necessary for understanding stock-specific distribution, habitat utilization, abundance, and life history variation. This project supports recommendations from the Interagency Ecological Program’s Salmon and Sturgeon Assessment of Indicators by Life Stage and Interagency Ecological Program Science Agenda efforts to improve Central Valley
Delta Smelt Enclosure Studies, North Delta Arc of the upper San Francisco Estuary, CA, 2019 - 2024
This dataset comprises data from seven different enclosure studies, each of which used Delta Smelt reared by the UC Davis Fish Conservation and Culture Laboratory (FCCL). Each study had unique study questions and utilized slightly different methods. Enclosure Prototype (Rio Vista (RV) and Sacramento Deep Water Ship Channel (SDWSC)) – these studies, conducted January through February (RV) and March (SDWSC) of 2019, were designed to test different enclosure mesh sizes to assess their effects on Delta Smelt growth, survival, and feeding efficacy over a period of four weeks. Three different enclosure designs were deployed at two locations (Rio Vista and the Sacramento Deep Water Ship Channel), with 60 to 64 fish per enclosure and a control group of 30 fish at FCCL. See Baerwald et al, 2023 for details. - https://doi.org/10.1371/journal.pone.0286027 North Delta Pilot – This study, conducted in July and August of 2019, was implemented to test the feasibility of using enclosures to evaluate a flow action designed to improve food for Delta Smelt in the Yolo Bypass, and test upper thermal limits in field conditions for cultured Delta Smelt. Three enclosures were placed at Rio Vista and one enclosure was placed in the Yolo Bypass. Each enclosure held 60 fish. A control group of 90 fish was held at FCCL. The study lasted for four weeks; however, the Yolo Bypass enclosures were removed after three weeks following a heat wave that was lethal to all enclosure fish at that site. Suisun Marsh Pilot – This study, conducted in October and November of 2019, tested the feasibility of using enclosures to evaluate a flow action designed to improve low salinity habitat for Delta Smelt in Suisun Marsh. Three enclosures per site were placed at three locations (Suisun Marsh, Rio Vista, and the Yolo Bypass). Each enclosure held 60 fish, and a control group of 90 fish was held at FCCL. The study lasted for four weeks. Domestication/Behavior – This study, conducted in January and February of 20
Salmonid habitat use monitoring used to determine effectiveness of habitat improvement projects in the Sacramento River, CA
Overview The Central Valley Project Improvement Act (CVPIA) funds habitat improvement work in the Central Valley of California to increase salmonid populations in furtherance of meeting CVPIA fish doubling goals. This data package contains five datasets. Enclosure Study – Growth Data This dataset covers enclosure studies that examined salmonid growth rates in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Data was collected in July and August 2019 from project sites, constructed habitat project sites, and control sites where no treatment is planned. Six enclosures with juvenile Fall Run Chinook salmon from Coleman National Fish Hatchery were placed in each habitat type. Fish growth was tracked for approximately 6.5 weeks. Annual reports summarize the survey findings. Enclosure Study – Gut Contents Data This dataset covers enclosure studies that examined salmonid growth rates in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Data was collected in July and August 2019 from project sites, constructed habitat project sites, and control sites where no treatment is planned. Six enclosures with juvenile Fall Run Chinook salmon from Coleman National Fish Hatchery were placed in each habitat type. Enclosures remained in the river for approximately 6.5 weeks. At the end of the study, fish were euthanized, and we dissected their guts and enumerated the taxa found. Annual reports summarize the survey findings. Microhabitat Use Data This dataset covers salmonid microhabitat use conducted in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Surveys are conducted roughly monthly and include pre-project sites, constructed habitat project sites, and control sites where no treatment is planned. Based upon habitat inventory data, annually identify which habitat units within each side channel will be selected for the collectio
Fishery impacts - CA commercial lobster catch and effort, and trap distribution around marine reserves
These data describe landings and fishing effort for the CA commercial spiny lobster fishery. Data are contained in two tables: 1) a time series collected by the California Fish and Wildlife (CDFW) of lobster catch (kg) and effort (lobster trap pulls) by year (1998-2020) and location (geographic fishery blocks). Catch is recorded and reported to CDFW by fish processors (buyers) with “fish tickets”. Trap pulls are recorded and reported by fishermen with logbooks. 2) The number of traps counted in the water at increasing distances from the boundary of marine reserves, three reserves located in the northern region of the fishery and three from the southern region of the fishery, in November 2022.
SBC LTER: Reef: Geospatial structure of microsatellite markers for the giant kelp, Macrocystis pyrifera, Santa Barbara CA, 2009
Data package includes data and R code for the examination of geospatial genetic structure (SGS) and simulation of inbreeding in giant kelp (Macrocystis pyrifera) from the Santa Barbara Channel, California. Data are reported for microsatellite markers from individual giant kelp plants from Carpinteria Reef, Mohawk Reef and Goleta Bay, collected during September 2009. Relative X and Y coordinates (meters) were recorded for each specimen sampled. R code consists of two scripts, a) to calculate mean number of alleles per locus, and observed and expected heterozygosity, and b) to simulate self-fertilization and sibling/cousin relationships. These data were presented in: Johansson, Mattias L, Raimondi, Peter T, Reed, Daniel C, Coelho, Nelson C, Serrão, Ester A, Alberto, Filipe A. In press. Looking into the black box: simulating the role of self-fertilization and mortality in the genetic structure of Macrocystis pyrifera. Molecular Ecology, 22:4842–4854. These data are also available from: Johansson ML, Raimondi PT, Reed DC, Coelho NC, Serrão EA, Alberto FA (2013) Data from: Looking into the black box: simulating the role of self-fertilization and mortality in the genetic structure of Macrocystis pyrifera. Dryad Digital Repository. doi:10.5061/dryad.s1b07.
Wikipedia: wikipedia-ca (Catalan)
Wikipedia is a multilingual, web-based, free-content encyclopedia project supported by the Wikimedia Foundation and based on a model of openly editable content. EOL harvests articles from wikipedia that are indexed as species or higher taxa.<p></p>
CA-TIMS U-Pb analysis of IGSN samples IEMM10001, IEMM10002, IEMM10003, IEM10004
<p>Single zircon U-Pb analyses were performed at the Berkeley Geochronology Center. The samples were crushed and mineral concentrates were then purified using standard mineral separation techniques, including sieves, magnetic separation and density separation. If present, euhedral, clear grains devoid of optically recognizable cores were chosen for analysis. All zircons were pretreated using thermal annealing at 850°C for 48 hrs, followed by chemical abrasion with concentrated HF in pressurized dissolution capsules at 220°C for 6-8 hrs. Prior to dissolution the crystals were cleaned in ultrasonically agitated aqua regia followed by multiple steps of rinsing in clean HNO<sub>3</sub>. Zircon crystals were then spiked with <sup>205</sup>Pb-<sup>233</sup>U- <sup>235</sup>U tracer solution mixed and calibrated at BGC, and dissolved by vapor transfer in HF using miniature PTFE capsules at 220°C for 6 days. After dissolution, large crystals were loaded in 2 to 3 aliquots (see table) to optimize beam stability (which typically is significantly decreased for large, unextracted zircon samples) and test reproducibility. Isotope ratios were determined on a Micromass Sector 54 mass spectrometer using a Daly-type ion counter positioned behind a WARP filter. Pb (as Pb<sup>+</sup>) and U (as UO<sup>2+</sup>) were run sequentially on the same filament. The accuracy of the used mixed tracer was tested repeatedly against solutions derived from certified standards of isotopically pure <sup>206</sup>Pb and natural U (NIST SRM-991 and CRM-145, respectively), as well as age solutions distributed by the Earthtime initiative (agreement was found to be <0.1%, additional details regarding tracer calibration are in Irmis et al., 2011; Mundil et al., 2004; Black et al., 2004). An additional subset of 5 zircons of the KHB01 sample was analyzed using the Earthtime 535 tracer solution. The resulting mean age of 97.80 ± 0.19 Ma (MSWD 2.0) from this batch is slightly younger, but within uncertainty, compared to our reported age of 98.00 ± 0.14 Ma, even without taking into account an augmented uncertainty resulting from U/Pb in the tracer solutions. The elevated MSWD may be a result of excess scatter from true age dispersion within the zircon population of KHB01. Repeat measurements of the total procedural blank averaged 0.82 ± 0.36 pg Pb (U blanks were indistinguishable from zero), with <sup>206</sup>Pb/<sup>204</sup>Pb = 18.40 ± 0.46, <sup>207</sup>Pb/<sup>204</sup>Pb = 15.64 ± 0.25, <sup>208</sup>Pb/<sup>204</sup>Pb = 38.04 ± 0.75 (all 2σ of population), and a <sup>206</sup>Pb/<sup>204</sup>Pb-<sup>207</sup>Pb/<sup>204</sup> Pb correlation of +0.47 (ratios and uncertainties were propagated into the age and age-error calculations). The total procedural blank including ion exchange chemistry is also as low as 1 pg but scatter in total common Pb concentration and possibly common Pb composition suggests that results from unextracted analyses of zircon yield better reproducibility. Deficient radiogenic <sup>206</sup>Pb in zircon due to initial deficit of <sup>230</sup>Th is accounted for by assuming a partition coefficient ratio DTh/DU of 0.2 (as applied in Wotzlaw et al., 2014), or by assuming Th/U in the parent magma to be 3.5 where the ET535 tracer solution was used (the resulting difference in age from either approach is negligible). Mass fractionation of U during analysis was controlled by the U double spike, whereas Pb mass fractionation was corrected by 0.15 ± 0.6 %/AMU (based on multiple analyses of NBS 981).</p> <p>The photo-micrograph shows crystals extracted from KHB03 and illustrates that the zircon population is homogeneous. </p>
Copernicus Digital Elevation Model (DEM) for Europe at 3 arc seconds (ca. 90 meter) resolution derived from Copernicus Global 30 meter DEM dataset
<p>Overview:<br> The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters.</p> <p>The Copernicus DEM for Europe at 3 arcsec (0:00:03 = 0.00083333333 ~ 90 meter) in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/).</p> <p>Processing steps:<br> The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in <a href="https://gdal.org/drivers/raster/vrt.html">VRT</a> format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized:</p> <p><code>gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt </code></p> <p>In order to reduce the spatial resolution to 3 arc seconds, weighted resampling was performed in GRASS GIS (using <code>r.resamp.stats -w</code> and the pixel values were scaled with 1000 (storing the pixels as integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using <code>r.relief</code>, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files.</p> <p>Projection + EPSG code:<br> Latitude-Longitude/WGS84 (EPSG: 4326)</p> <p>Spatial extent:<br> north: 82:00:30N<br> south: 18N<br> west: 32:00:30W<br> east: 70E</p> <p>Spatial resolution:<br> 3 arc seconds (approx. 90 m)</p> <p>Pixel values:<br> meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.)</p> <p>Software used:<br> GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief)</p> <p>Original dataset license:<br> <a href="https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf">https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf</a></p> <p>Processed by:<br> mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p>
Copernicus Digital Elevation Model (DEM) for Europe at 30 arc seconds (ca. 1000 meter) resolution derived from Copernicus Global 30 meter DEM dataset
<p>Overview:<br> The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters.</p> <p>The Copernicus DEM for Europe at 30 arcsec (0:00:30 = 0.0083333333 ~ 1000 meter) in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/).</p> <p>Processing steps:<br> The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in <a href="https://gdal.org/drivers/raster/vrt.html">VRT</a> format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized:</p> <p><code>gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt </code></p> <p>In order to reduce the spatial resolution to 30 arc seconds, weighted resampling was performed in GRASS GIS (using <code>r.resamp.stats -w</code> and the pixel values were scaled with 1000 (storing the pixels as integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using <code>r.relief</code>, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files.</p> <p>Projection + EPSG code:<br> Latitude-Longitude/WGS84 (EPSG: 4326)</p> <p>Spatial extent:<br> north: 82:00:30N<br> south: 18N<br> west: 32:00:30W<br> east: 70E</p> <p>Spatial resolution:<br> 30 arc seconds (approx. 1000 m)</p> <p>Pixel values:<br> meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.)</p> <p>Software used:<br> GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief)</p> <p>Original dataset license:<br> <a href="https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf">https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf</a></p> <p>Processed by:<br> mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p> <p> </p>
Model results and observation data in Zhang et al. modeling of wave interference at Ocean Beach, CA
<p>The dataset contains modeling results and observation data supporting the manuscript of Phase-resolved modeling of wave interference and its effects on nearshore circulation in a large ebb shoal-beach system by Yu Zhang, Fengyan Shi, Jim Kirby, Xi Feng.</p>
SETDB1 knock-out and reexpression of a WT, a catalytic-dead variant (CA) or a NLS-tagged SETDB1 protein
<p>In order to generate the Setdb1 cKO allele, exons 15 and 16, which encode the core amino acids of the catalytic domain, have been flanked with two lox-P sites recognized by Cre recombinase enzyme. Cre-oestrogen receptor fusion gene Mer-Cre-Mer has been introduced to induce acute Setdb1 KO after Tamoxifen treatment. Setdb1 cKO mESCs where Setdb1 expression is stably rescued by wild type 3xFlag-Setdb1 (WT) or by the catalytic dead mutant 3xFlag-Setdb1 (CA) were generously given by Pr Yoichi Shinkai. The catalytic dead mutant was obtained with a single lysine mutation. In the lab, Setdb1 cKO mESCs, where Setdb1 expression is stably rescued by NLS-3xFlag-Setdb1 which localizes only in the nucleus, have been established (3 NLS sequences have been added in order to retain Setdb1 in the nucleus).</p> <p>The quality of the RNA was determined on the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, USA), the RNA integrity number was above 8 for all the samples. To construct libraries, 1 mg of high-quality total RNA sample was processed using Truseq® stranded total RNA kit (Illumina®). After the removal of ribosomal RNAs (using Ribo-zero® rRNA), confirmed by QC control on pico chipTM on the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, USA), total RNA molecules are fragmented and reverse-transcribed using random primers. Replacement of dTTP by dUTP during the second strand synthesis will permit to achieve the strand specificity. Addition of a single A base to the cDNA is followed by ligation of adapters. Libraries were quantified by qPCR using the KAPA Library Quantification Kit for Illumina Libraries (KapaBiosystems) and library profiles were assessed using the DNA High SensitivityTMHS kit on an Agilent Bioanalyzer 2100. Libraries were sequenced on an Illumina® Nextseq 500 instrument using 75 base-lengths read V2 chemistry in a paired-end mode.</p>
CLMS Water Bodies monthly time series for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023)
<p>Water Bodies from Copernicus Land Monitoring Service (CLMS) as monthly time series for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023)</p> <p>Source data:<br>- CLMS: Water Bodies 2014-2020 (raster 300 m), global, 10-daily – version 1: <a href="https://land.copernicus.eu/en/products/water-bodies/water-bodies-global-v1-0-300m">https://land.copernicus.eu/en/products/water-bodies/water-bodies-global-v1-0-300m</a> <br>- CLMS: Water Bodies 2020-present (raster 300 m), global, monthly – version 2: <a href="https://land.copernicus.eu/en/products/water-bodies/water-bodies-global-v2-0-300m">https://land.copernicus.eu/en/products/water-bodies/water-bodies-global-v2-0-300m</a></p> <p>Water is fundamental to life on Earth. Water quality, including aspects like turbidity and trophic state, is vital for assessing a water body's ecological well-being and its suitability for drinking. Understanding the water's surface temperature is key for monitoring climate change and can influence weather patterns. Tracking water levels in lakes and rivers helps in flood prediction, irrigation planning, and hydroelectric power generation. The presence and extent of ice on lakes and rivers can have significant implications for regional climates, ecosystems, and human activities. Moreover, the surface extent of water bodies, whether permanent or ephemeral, informs land management across various sectors. In an era marked by environmental change, these metrics offer insights into sustainable water resource management.<br>The Water Bodies product group aims to address these critical issues by providing tailored datasets to users which are applicable across a wide array of sectors. It includes Lake Surface Water Temperature, providing real-time and historical data; Lake Water Quality in various resolutions; Water Bodies datasets for surface extent; Lake and River Water Level information; the River and Lake Ice Extent product for ice presence; and the Aggregated River and Lake Ice Extent product, showing percent ice coverage. These products support applications like food security, public health safeguarding, climate studies, and responsible water management practices.</p> <p>Processing steps:<br>To cover the complete time period from 2019 to 2023 two data products of the Water Bodies product group are processed. Up to December of 2020 the Water Bodies at 10-daily resolution have been used, from January 2021 the Water Bodies at monthly resolution have been used. Both original datasets have been downloaded for the area of Mauritania (NUTS MR) within Latitude-Longitude/WGS84 spatial reference system. Then both datasets have been downsampled to 30 arc seconds (ca. 1000 meter) using the most frequent occuring value. The 10-daily data have been aggregated to monthly resolution using the most frequent occurring value.</p> <p>File naming:<br>Until December 2020: <code>c_gls_WB300_GLOBE_PROBAV_V1.0.1_MR_WB_res_YYYY_MM_01T00_00_00.tif</code> <br>e.g.: <code>c_gls_WB300_GLOBE_PROBAV_V1.0.1_MR_WB_res_2020_12_01T00_00_00.tif</code> <br>From January 2021 on: <code>c_gls_WB300_GLOBE_S2_V2.0.1_MR_WB_res_YYYY_MM_01T00_00_00.tif</code> <br>e.g.: <code>c_gls_WB300_GLOBE_S2_V2.0.1_MR_WB_res_2023_12_01T00_00_00.tif</code></p> <p>The date within the filename is year and month of aggregated timestamp.<br>NOTE: data for 2023-04 are missing, since they are not available from CLMS</p> <p>Pixel values:<br>0: Sea<br>70: Water<br>255: No water</p> <p>Projection + EPSG code:<br>Latitude-Longitude/WGS84 (EPSG: 4326)</p> <p>Spatial extent:<br>north: 27:17:30N<br>south: 14:43:30N<br>west: 17:04:30W<br>east: 04:48:00W</p> <p>Temporal extent:<br>January 2019 - December 2023 (except: April 2023)</p> <p>Spatial resolution:<br>30 arc seconds (approx. 1000 m)</p> <p>Temporal resolution:<br>monthly</p> <p>Software used:<br>GRASS GIS 8.3.2</p> <p>Format: GeoTIFF</p> <p>Original dataset license:<br>Generated using European Union's Copernicus Land Monitoring Service information</p> <p>Processed by:<br>mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p> <p>Contact: <br>mundialis GmbH & Co. KG, info@mundialis.de</p> <p> </p>
MODIS NDVI, monthly aggregated time series for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023)
<p>Normalized Difference Vegetation Index (NDVI) from MODIS data for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023).</p> <p>Source data:<br>- MODIS/Terra Vegetation Indices 16-Day L3 Global 1 km SIN Grid (MOD13A2 v061): <a href="https://lpdaac.usgs.gov/products/mod13a2v061/">https://lpdaac.usgs.gov/products/mod13a2v061/</a></p> <p><br>The Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Indices 16-Day (MOD13A2) Version 6.1 product provides Vegetation Index (VI) values at a per pixel basis at 1 kilometer (km) spatial resolution. There are two primary vegetation layers. The first is the Normalized Difference Vegetation Index (NDVI), which is referred to as the continuity index to the existing National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) derived NDVI. The second vegetation layer is the Enhanced Vegetation Index (EVI), which has improved sensitivity over high biomass regions. The algorithm for this product chooses the best available pixel value from all the acquisitions from the 16 day period. The criteria used is low clouds, low view angle and the highest NDVI/EVI value.</p> <p>For the time period January 2019 - December 2023, the NDVI layer of the original data has been processed. Bad quality pixels or pixels with snow/ice and/or cloud cover have been masked using the provided quality assurance (QA) layers and appear as "no data". These 16-Day data are then aggregated to monthly temporal resolution using the maximum and reprojected to Latitude-Longitude/WGS84.</p> <p>File naming:<br><code>ndvi_filt_YYYY_MM_01T00_00_00.tif</code><br>e.g.: <code>ndvi_filt_2023_12_01T00_00_00.tif</code></p> <p>The date within the filename is year and month of aggregated timestamp.</p> <p>Pixel values:<br>NDVI * 10000 Scaled to Integer, example: value 6473 = 0.6473</p> <p>Projection + EPSG code:<br>Latitude-Longitude/WGS84 (EPSG: 4326)</p> <p>Spatial extent:<br>north: 28N<br>south: 14N<br>west: 18W<br>east: 4W</p> <p>Temporal extent:<br>January 2019 - December 2023</p> <p>Spatial resolution:<br>30 arc seconds (approx. 1000 m)</p> <p>Temporal resolution:<br>monthly</p> <p>Software used:<br>GRASS GIS 8.3.2</p> <p>Format: GeoTIFF</p> <p>Original dataset license:<br>All data products distributed by NASA's Land Processes Distributed Active Archive Center (LP DAAC) are available at no charge. The LP DAAC requests that any author using NASA data products in their work provide credit for the data, and any assistance provided by the LP DAAC, in the data section of the paper, the acknowledgement section, and/or as a reference. The recommended citation for each data product is available on its Digital Object Identifier (DOI) Landing page, which can be accessed through the Search Data Catalog interface. For more information see: <a href="https://lpdaac.usgs.gov/products/mod13a2v061/">https://lpdaac.usgs.gov/products/mod13a2v061/</a></p> <p>Processed by:<br>mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p> <p>Contact: <br>mundialis GmbH & Co. KG, info@mundialis.de</p> <p> </p>
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