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168 results for “water conservation”
Areas of global importance for conserving terrestrial biodiversity, carbon, and water
<p><strong>Content:</strong><br> This data repository contains the results of the NatureMap ( naturemap.earth/) conservation prioritization effort. The maps were created by jointly optimizing biodiversity and NCPs such as carbon and/or water.</p> <p><strong>Usage notes:</strong><br> Maps are supplied at both 10km and 50km resolution unless specified differently in the manuscript.<br> All maps that aim to find priority areas for all species considered in the analysis, utilize a series of representative sets.<br> The ranks for each layer are area-specific and can be used to extract summary statistics by simple subsetting.<br> For example:<br> To obtain the top 30% of land area for biodiversity and carbon, one needs to create a mask of all areas lower than a value of 30 from the respective ranked layers.</p> <p>For convenience two files are supplied that contain the fraction of land area per grid cell times 1000. Multiplying those with the cell area (100km2, respectively 2500km2) gives the exact amount of land area in a given grid cell.<br> These are labelled " globalgrid_mollweide_**km.tif " can be used to create masks for the priority maps.</p> <p><strong>Spatial resolution:</strong></p> <p>10 and 50 km</p> <p><strong>Geographic projection:</strong><br> World Mollweide Equal Area projection<br> PROJ4 ( +proj=moll +lon_0=0 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs )</p> <p><strong>Filename suffix description:</strong></p> <p><em>'minshort_speciestargets'</em><br> =- Problem formulation where targets were achieved by minimzing a shortfall</p> <p><em>'repruns10'</em><br> =- The number of representative that were used to create the ranked layer</p> <p><em>'biome.id'</em><br> =- Species distribution were split by biome, thus creating separate targets for subpopulation</p> <p><em>'withPA'</em><br> =- Fractions of current protected areas (Date: WDPA 2019) were locked in as baseline and starting budget. Approximately 15% of the globe. Note that not entire grid cells, but fractions were locked in and build opon!</p> <p><em>'carbon'</em><br> =- Carbon was included in the prioritization and jointly optimized together with the other assets by giving it equal weighting (see manuscript)</p> <p><em>'water'</em><br> =- Water was included in the prioritization and jointly optimized together with the other assets by giving it equal weighting (see manuscript)</p> <p><strong>License:</strong><br> CC-BY-SA 4.0</p> <p><strong>Citation:</strong><br> Jung, Martin, Andy Arnell, Xavier De Lamo, Shaenandhoa Garcia-Rangel, Matthew Lewis, Jennifer Mark, Cory Merow et al. (2021) "Areas of global importance for terrestrial biodiversity, carbon, and water." Nature Ecology & Evolution</p>
An Innovative Scheme to Confront the Trade‐Off Between Water Conservation and Heat Alleviation With Environmental Justice for Urban Sustainability: The Case of Phoenix, Arizona
<p><em><strong>The manuscript for this dataset is accepted by AGU Advances and can be accessed here: <a href="https://doi.org/10.1029/2022AV000816">link</a>. Please cite the literature when using the datasets.</strong></em></p> <p><strong>How to cite this article: Yuanhui Zhu, Soe Myint, Xin Feng, Yubin Li. An Innovative Scheme to Confront the Trade‐Off Between Water Conservation and Heat Alleviation With Environmental Justice for Urban Sustainability: The Case of Phoenix, Arizona. AGU Advances, 4, e2022AV000816. <a href="https://doi.org/10.1029/2022AV000816">https://doi.org/10.1029/2022AV000816</a></strong></p> <p>This study aims to develop a practical and integrated framework to tackle the tradeoff between land surface temperature (LST) reduction and water conservation for heat mitigation and resilience planning in Phoenix, Arizona. We developed a multi-objective framework of spatial optimization for priority areas that considers environmental justice. We employed the priority areas (i.e., residential districts, socio-economically disadvantaged neighborhoods, hotspot regions, and opportunity areas), ECOSTRESS-based LST, actual evapotranspiration (ETa, as a proxy to water use), Landsat-based LST and ETa changes (2000–2020), and the evaporative stress index (ESI). These datasets are used to identify the priority areas in which environmental conditions need to be improved seriously and (2) spatially optimize the placement of new green space (tree %, grass %) in the priority areas to realize the most significant LST reduction and minimum OWU. We provide the results of the new green space configurations with the scenarios for the percentage of new vegetation coverage (including trees and grass) overall increased to 25%, 35%, and 45% within the entire study areas, residential districts, socio-economically disadvantaged neighborhoods, and hotspot regions.</p> <table> <caption>The dataset summarization</caption> <tbody> <tr> <td>Category</td> <td>Dataset</td> <td>Resolution</td> <td>Source/method</td> <td>Time</td> </tr> <tr> <td>Environmental database</td> <td>Summer daytime LST</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental database</td> <td>Summer nighttime LST</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental database</td> <td>Summer ETa</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental database</td> <td>Summer ESI</td> <td>70m</td> <td>ECOSTRESS</td> <td>2019</td> </tr> <tr> <td>Environmental change database</td> <td>Trends of summer LST changes</td> <td>30m</td> <td>Landsat-based Statistical Mono-Window algorithm</td> <td>2000-2020</td> </tr> <tr> <td>Environmental change database</td> <td>Trends of summer ETa changes</td> <td>30m</td> <td>Landsat-based Simplified Surface Energy Balance</td> <td>2000-2020</td> </tr> <tr> <td>The results of new green space configurations</td> <td>The spatial distributions of new green space</td> <td>--</td> <td>Spatial optimization</td> <td>--</td> </tr> </tbody> </table> <p>note: LULC: Land use and land cover; LST: Land Surface Temperature; ETa: Actual Evapotranspiration; ESI: Evaporative Stress Index</p> <p>We provide the different scenarios in shapefile format for spatial distributions of new space configurations. The naming convention for attribute tables in shapefile is :</p> <p>VV_new_perNN_LSTWW</p> <p>where:</p> <ul> <li>VV = New vegetation for tree or grass</li> <li>NN = The scenarios with new vegetation increased to 25%, 35%, or 45% (unit: %)</li> <li>WW = The weight values of land surface temperature range from 0 to 1 (unit: %) when executing spatial optimization for the tradeoff between land surface temperature reduction and outdoor water use conservation with vegetation coverage. The weight of 0 represents that our spatial optimization models only focus on outdoor water use conservation, and the weight of 1 denotes that we only consider land surface temperature reduction. </li> </ul> <p>Example: grass_new_per25_LST65 means -- new vegetation for grass; the scenario is set up by new vegetation increased to 25%; the weight of land surface temperature is 0.65. </p> <p> </p>
Stable isotope and conservative tracer data used to estimate uptake of stream water dissolved organic carbon (DOC) through a whole-stream addition of a ¹³C-DOC tracer coupled with laboratory measurements of bioavailability of the tracer and stream water DOC using lability profiling with bioreactors
We performed a whole-stream addition of a ¹³C-DOC tracer and made laboratory measurements of the biological availability of the tracer as well as stream water DOC. The study was performed in October 2002 in a 1.27 km stretch of the third-order White Clay Creek in southeastern Pennsylvania. The tracer was prepared as a cold-water leachate of ¹³C-labeled tulip poplar saplings and it was added to the stream along with sodium bromide, a conservative tracer, over a 2-h period. Stream water samples were collected at 8 downstream stations over an 8-h period, filtered, and analyzed for concentrations of bromide and DOC. DOC was measured by Pt-catalyzed, persulfate oxidation, Br- was analyzed by ion chromatography, and C isotope samples were rotary evaporated, acidified, lyophilized, combusted, and the CO₂ analyzed with an elemental analyzer interfaced with an isotope ratio mass spectrometer. Lability profiling of the ¹³C-DOC tracer and stream water DOC were performed with a series of plug-flow bioreactors of increasing empty-bed contact times with the concentration of biodegradable DOC operationally defined as the difference between the DOC concentrations in the influent and effluent waters of the bioreactors. The bioreactor measurements were performed 2 days after the whole-stream release. Data were analyzed to estimate the uptake of stream water DOC associated with labile and semi-labile fraction of biodegradable DOC. These data have been previously used in a 2008 publication in Freshwater Biology, doi:10.1111/j.1365-2427.2007.01941.x.
Throw trap and Electrofishing Data from Water Conservation Area 3B, Florida, USA, 2019-2022 for the Decompartmentalization Physical Model Project
This dataset includes densities and biomass of fishes and macroinvertebrates collected using throw traps or an airboat-mounted electrofisher in the study region of the Decompartmentalization Physical Model (DPM) located in Water Conservation Area (WCA) 3B. Some sites in this region experienced seasonal increases in water flow due to the operations of the S-152 structure. The sites sampled for this dataset were either located along a gradient of water flow (downstream the S-152) or were in a reference area that had ambient flow conditions. The purpose of this dataset was to quantify community responses of consumers groups to flowing water and how it may interact with local nutrient conditions at the site level. Hydrological, floc nutrient and periphyton volume data used in the analyses are included. This data package includes the R script that was used to run the statistical models for the manuscript titled "Discharge and nutrients interact to determine trophic structure in a wetland: evidence from a landscape-scale manipulation". The data collection for this data package is complete.
Data for "Water (or the Lack Thereof), Management, and Conservation of an Endangered Desert Wetland Obligate, Lilaeopsis schaffneriana var. recurva"
<p>Raw and RData forms of data for "Water (or the Lack Thereof), Management, and Conservation of an Endangered Desert Wetland Obligate, <em>Lilaeopsis schaffneriana </em>var. <em>recurva". </em>Consists of six Excel files, with names corresponding to the type of data.</p> <ol> <li>field_ecology_data.xlsx </li> <li>experiment_randomization.xlsx </li> <li>experiment_entered_data.xlsx </li> <li>resilience_days_to_critical.xlsx </li> <li>resilience_experiment_data.xlsx </li> <li>resilience_leaf_density_data.xlsx </li> </ol> <p>Four RData files of the loaded Excel data, and one text file to explain the coding of the drought experiment data.</p>
Figure 7 in An update note on diversity and conservation of the endemic fishes in Iranian inland waters
Figure 7. Endemicity in the Iranian cyprinodontids: (A) Aphanius arakensis; (B) A. farsicus; (C) A. isfahanensis; (D) A. mesopotamicus; (E) A. pluristriatus; (F) A. shirini; (G) A. sophiae; (H) A. vladykovi; (I) A. furcatus. For photos of two recently described new endemic Aphanius species from Iran (A. kavirensis and A. darabensis), see Esmaeili et al. (2014).
Figure 6 in An update note on diversity and conservation of the endemic fishes in Iranian inland waters
Figure 6. Some Iranian endemic fishes: (A) Alburnoides qanati (Cyprinidae); (B) Acanthobrama persidis (Cyprinidae); (C) Alburnoides qanati (Cyprinidae); (D) Iranocypris typhlops (Cyprinidae); (E) Oxynoemacheilus persa (Nemacheilidae); (F) Cobitis linea (Cobitidae); (G) Oxynoemacheilus tongiorgii (Nemacheilidae); (H) Turcionemacheilus hafezi (Nemacheilidae).
Figure 5 in An update note on diversity and conservation of the endemic fishes in Iranian inland waters
Figure 5. The human-induced disturbance of ichthyofauna of Iran: (A and B) unusual methods of fishing by local people in the Mond River basin; (C) water pollution in the Pirbanow spring system, habitat of a vulnerable endemic species, Aphanius farsicus, and recently drought-stricken; (D) habitat alteration and reconstruction of the endemic and endangered species Aphanius ginaonis, the only known habitat for this species; (E and F) habitat alteration of the only endemic cichlid species in Iran and the Middle East, Iranocichla hormuzensis.
Figure 3 in An update note on diversity and conservation of the endemic fishes in Iranian inland waters
Figure 3. Unusual habitats for Iranian endemic fishes: (A) qanat system; (B) the qanat outlet opening; (C) cave system in Zagros Mountains, habitat of the only blind cyprinid fish and the only blind loach fish in Iran, which are respectively Iranocypris typhlops and Paracobitis smithi; and (D) hot sulfuric spring— Genow hot sulfuric spring—the only known habitat of the endangered Aphanius ginaonis in southern Iran.
Fig. 5 in Evidence for cryptic diversity in the Neotropical water snake, Helicops angulatus (Linnaeus, 1758) (Dipsadidae, Hydropsini), with comments on its ecology, facultative reproductive mode, and conservation
Fig. 5. Illustration of the holotype of Coluber surinamensis Shaw. From Sebae (1735, Vol. 2, pl. 59, Fig. 2).
Fig. 3 in Evidence for cryptic diversity in the Neotropical water snake, Helicops angulatus (Linnaeus, 1758) (Dipsadidae, Hydropsini), with comments on its ecology, facultative reproductive mode, and conservation
Fig. 3. Best Maximum Likelihood tree based on the data set of concatenated 12S and 16S rDNA, and c-mos sequences. The red clade depicts the Helicops angulatus group. On the left and right sides of a slash (/) are values indicated at nodes for Maximum Likelihood bootstraps (> 75%) and Bayesian Posterior probability values (> 95%), respectively. Green clades represent the paraphyly of Helicops angulatus. The name Helicops pictiventris is currently a junior synonym of H. infrataeniatus, but it appears in the tree exactly as the pertinent sequences appear in the GenBank dataset.
Fig. 1 in Evidence for cryptic diversity in the Neotropical water snake, Helicops angulatus (Linnaeus, 1758) (Dipsadidae, Hydropsini), with comments on its ecology, facultative reproductive mode, and conservation
Fig. 1. The distribution of Helicops angulatus in the Neotropics. Locality data is from the VertNet and GBIF databases, as well as the literature. Diamonds (green oviparous, yellow viviparous): specimens reported in Appendix B of Braz et al. (2016); red stars represent localities where Helicops was sampled for DNA; small black markers: localities from Helicops angulatus map in Nogueira et al. (2019). As currently defined Helicops angulatus occurs in Freshwater Ecoregions: 301 North Andean Pacific Slopes, Rio Atrato; 302 Magdalena, Sinu; 304 South America Caribbean Drainages, Trinidad; 307 Orinoco Llanos; 308 Orinoco Guiana Shield; 311 Guianas; 313 Western Amazon Piedmont; 317 Ucayali, Urubamba Piedmont; 318 Mamore, Madre de Dios Piedmont; 319 Guapore, Itenez; 320 Tapajos, Juruena; 321 Madeira Brazilian Shield; 323 Amazonas Estuary and Coastal Drainages; 324 Tocantins, Araguaia; 325 Parnaiba; and 328 Northeastern Mata Atlantica.
Fig. 1 in The ecology, distribution, status, threats, and conservation of the Common Water Monitor (Varanus salvator) in the Dhaleswari River of Assam, India
Fig. 1. (A) Map of India, highlighting Assam. (B) Map of Assam, highlighting Hailakandi district. (C) Map of Hailakandi district showing the two rivers, Dhaleswari River and Katakhal River, with distribution of the Common Water Monitor (Varanus salvator). Dots represent sighting locations during the present survey; current distribution in the Dhaleswari River is shown in green. Further downstream, despite no present records, occurrence in the past (1970s–1980s) was reported by several interviewees (shown in yellow). No reports on present occurrence in the Katakhal River (shown in red) could be found. Map by A.S. Choudhury.
Fig. 2 in The ecology, distribution, status, threats, and conservation of the Common Water Monitor (Varanus salvator) in the Dhaleswari River of Assam, India
Fig. 2. Photographs relevant to the habitat and threats of the Common Water Monitor (Varanus salvator) in the Dhaleswari River, Assam, India. (A) Research team interacting with the locals at Rongpur 5, Hailakandi. (B) Habitat of the Common Water Monitor in the Dhaleswari River, showing bushes and other features on the banks. (C) The sandy bank of the Katakhal River, prone to erosion and landslides, is the habitat not preferred by the Common Water Monitor. (D) The sluice gate at the mouth of Dhaleswari River at Shahabad, which prevents water flow into it and diverts the water to the Katakhal River. (E) Encroachment and conversion of the Dhaleswari River into fisheries by the locals building dikes at Rongpur 2. Photos by A.S. Choudhury.
Fig. 3. A in The ecology, distribution, status, threats, and conservation of the Common Water Monitor (Varanus salvator) in the Dhaleswari River of Assam, India
Fig. 3. A Common Water Monitor (Varanus salvator) killed for venturing into a human habitation at Rongpur 6, Hailakandi. It was subsequently buried. Photo by R.A. Barbhuiya.
FIG. 3 in The water mites of Madagascar (Acari, Hydrachnidia): a revised list completed by original material conserved at the Muséum national d'Histoire naturelle, Paris
FIG. 3. — Sigthoria nilotica (Nordenskiöld, 1905),; A, dorsal shield; B, ventral shield; C, region of lateral eyes. Scale bar: 100 µm.
FIG. 6. — Moramangabates pauliani n. gen., n in The water mites of Madagascar (Acari, Hydrachnidia): a revised list completed by original material conserved at the Muséum national d'Histoire naturelle, Paris
FIG. 6. — Moramangabates pauliani n. gen., n. sp.; A, first leg; B, segments 4 and 5 of third leg; C, fourth leg. Scale bar: 100 µm.
FIG. 2 in The water mites of Madagascar (Acari, Hydrachnidia): a revised list completed by original material conserved at the Muséum national d'Histoire naturelle, Paris
FIG. 2. — Hydrachna (Bargena) mirifica Koenike, 1893; A-C,; A, genital field (damaged); B, palpus; C, chelicera; D,, genital field. Scale bars: 100 µm.
FIG. 1 in The water mites of Madagascar (Acari, Hydrachnidia): a revised list completed by original material conserved at the Muséum national d'Histoire naturelle, Paris
FIG. 1. — Hydrachna amplexa Koenike, 1898; A-D, (MNHN B 15 A); A, frontal shield; B, palp; C, gnathosoma in lateral view; D, genital field; E, (MNHN E 14 M), genital field. Scale bars: 100 µm.
FIG. 8. — Wuria milloti n in The water mites of Madagascar (Acari, Hydrachnidia): a revised list completed by original material conserved at the Muséum national d'Histoire naturelle, Paris
FIG. 8. — Wuria milloti n. sp.,; A, gnathosoma, chelicera and palp in medial view; B, fourth leg. Scale bar: 100 µm.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.