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1,133 results for “wetlands”
Figure 8 in Ecological Features And Anthropogenic Transformation Of Wetlands As Part Of Urban Floras Of Ukraine
Figure 8. Proportion of number of wetland plant species by hemerobia in studied territories.
Figure 5 in Ecological Features And Anthropogenic Transformation Of Wetlands As Part Of Urban Floras Of Ukraine
Figure 5. Proportion of number of plant species within light ecogroups in studied territories.
Dataset: Participatory surveillance reveals marsh deer mortality event during an extraordinary flood in Ibera wetlands, Argentina
<p>This is the dataset for the paper titled: <span>Participatory surveillance reveals marsh deer mortality event during an extraordinary flood in Ibera wetlands, Argentina.</span></p>
Data-base for : 'Partitioning carbon sources between wetland and well-drained ecosystems to a tropical first-order stream - Implications to carbon cycling at the watershed scale (Nyong, Cameroon)'
<p>Dataset of carbon (pCO2, TA, DIC, DOC, POC) and ancillary parameters (water temperature, oxygen saturation, pH, specific conducitivity) in ground and surface waters of the Nyong watershed (Cameroon). The dataset covers one entire year (in 2016) and thus allows describing the varability of carbon and ancillary paramaters concentrations induced by seasons.</p>
Fig. 1 in Impact Of Coastal Wetland Restoration Strategies In The Chongming Dongtan Wetlands, China: Waterbird Community Composition As An Indicator
Fig. 1. Locationofthestudysites (A–D).
Fig. 1 in Waterbird Distribution Patterns And Environmentally Impacted Factors In Reclaimed Coastal Wetlands Of The Eastern End Of Nanhui County, Shanghai, China
Fig. 1. LocationofstudysitesinNanhuiCounty, Shanghai.
Carbon sequestration of a forested wetland receiving nutrient inputs - soil, tree and greenhouse gas data
<p><span><span><span><span><span><span><span><span><span><span><span>Here we describe a pilot wetland carbon project located 30 km west of New Orleans where measurements were taken in 2013 and 2018, and applied to the carbon offset methodology, "Restoration of Degraded Deltaic Wetlands of the Mississippi Delta" ("the ACR Methodology") published by the American Carbon Registry (ACR). Baseline emissions were modeled using values derived from scientific literature. Results indicate net sequestration rate of 619,727 tons carbon dioxide equivalent (CO<sub>2</sub>e) over the 40 year project duration, which equates to 16,527 t CO2-e/yr, if wetland greenhouse gases (GHGs) are included, and 200,143 t CO<sub>2</sub>e over 40 years, or 5,003 t CO2-e/yr, if wetland greenhouse gasses were conservatively omitted. A kriging exercise was carried out that modeled the tree and soil pools, which resulted in net sequestration of 723,375 t CO2-e over 40 years (annual mean 18,084 t CO2-e/yr) with greenhouse gases, and 262,472 t CO2-e over 40 years (annual mean rate 6,560 t CO2-e/yr) if greenhouse gases were omitted. Unfortunately, the project was withdrawn, prohibiting the issuance and eventual transaction of carbon credits, due to very large uncertainty estimates mostly associated with GHG emissions and the kriging approach as in situ sampling could not be conducted as required by the methodology.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Better together? Assessing different remote sensing products for predicting habitat suitability of wetland birds
<p>This data repository contains the processed and extracted metrics from the Dutch land cover, country wide airborne laser scanning and Sentinel-1 and 2 datasets used as input predictor variables in the species distribution modelling step. The study area within the Netherlands comprised five Dutch provinces (Groningen, Drenthe, Overijssel, Gelderland, and Flevoland) for which both ALS and Sentinel data were available for the same year. The land cover metrics were derived using the Dutch land cover map from 2018 (LGN2018 or LGN8). The country-wide LiDAR point clouds were derived from the third Dutch national ALS flight campaign (AHN3, Actueel Hoogtebestand Nederland). The AHN3 dataset is openly accessible data available from (<a href="https://ahn.arcgisonline.nl/ahnviewer/">https://ahn.arcgisonline.nl/ahnviewer/</a>). The Sentinel datasets were processed using Google Earth Engine. </p>
Baliles Center (Hull Springs) Wetland Data 2021-10-28 to 2021-12-04
<p>General Metadata for Hull Springs Restored Wetland Sampling Station</p> <p>Files</p> <p>Specific metadata for each deployment and sensor can be found as text files with the file format of:</p> <pre><code>HS_wetland_DO_YYYY-MM-DD_metadata.txt HS_wetland_Depth_YYYY-MM-DD_metadata.txt HS_wetland_CT_YYYY-MM-DD_metadata.txt</code></pre> <p> </p> <p>Where YYYY-MM-DD is the date that the sampling period ended.</p> <p>NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab <a href="https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts">https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts</a>.</p> <p>File Created</p> <ul> <li>2021-06-16 by KF</li> </ul> <p>File Modified</p> <ul> <li>2021-07-22 by KF - added general metadata for the pressure transducer and the CT sensor.</li> <li>2021-11-10 by KF - updated to include the depth calculations from the water level logger.</li> </ul> <p>Description</p> <p>These data are from the sampling station in the restored wetland at the Baliles Center for Environmetal Education at Hull Springs. The sensors are in the NE corner of the shallow pond portion of the restored wetland (38.119289, -76.667252).</p> <p>All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a></p> <p>Station Specifics</p> <p>The specific at each site are:</p> <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> <p> </p> <p>The sensors are sampled every 15 minutes</p> <p>Measurement Parameters, units, and Variable Names</p> <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT, .press, or .BP - the temperature (dC) from the DO, conductivity, water pressure, or barometric pressure sensor. * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
A framework to identify priority wetland habitats and movement corridors for urban amphibian conservation
<p>Core corridors: derived from Circuitscape modeling results -top 50% of wood frog, boreal chorus frog and tiger salamander results converted to binary value and summed to produce core corridors (probable movement for 2-3 amphibian species). <br> <br> To derive core corridors, we summed connectivity models for three amphibian species. For each species we derived focal nodes from high habitat value (based on HSI modelling), used three resistance scenarios and summed the three scenarios for each species to represent probable movement pathways between focal nodes. Species connectivity models were then classified to top 50% of the model, and converted to a binary value of 0 to 1. The three species were summed where by values 0-3 represent number of amphibian species the corridor probably supports movement. </p>
A framework to identify priority wetland habitats and movement corridors for urban amphibian conservation - Raw Data
<p>Call of the Wetland Program observation data reported by citizen scientists at wetlands in the City of Calgary during three amphibian seasons from 2017 to 2019. Wetlands were surveyed up to 11 times per season and participants reported observations to a smartphone application – where they documented species, and type of observation (eggs, adult, juvenile, tadpole or call). Participants also recorded when they participated in a survey and there were no observations. Observations associated without a site ID represent opportunistic observations at non-survey wetlands. This data was used to validate habitat suitability models derived from the occupancy modeling results. <br> <br> Survey wetland location shapefile (centroid point of wetland) also included. </p>
Data: Human pressure effect on biodiversity-multifunctionality relationship in large Neotropical wetlands
<p>Data from manuscript Human pressure drives biodiversity–multifunctionality relationships in neotropical wetlands.<br> Moi et al.</p> <p>This is a dataset compiled from 72 lakes distributed across four neotropical wetlands of Brazil (Amazon, Araguaia, Pantanal, and Paraná). Dataset included single ecosystem functions: nutrient concentrations (in situ measurements of N and P water concentrations), metabolism (daily changes in water O2 concentration), biomass at multiple trophic levels (algae, herbivores, carnivores, detritivores, and omnivores), microorganism abundance (bacterial cell densities), availability of photosynthetically active radiation (light availability underwater), and variation in habitat complexity under water (variation in plant above-bottom cover). Dataset also included measures of aquatic biodiversity, including species richness and functional diversity of seven organismal groups (fish, aquatic macrophytes, microcrustaceans, rotifers, phytoplankton, ciliates, and testate amoebae). Finally, the dataset includes measures of ecosystem multifunctionality, human pressure (Human Footprint), and local environmental covariates (depth, conductivity, pH, precipitation, temperature). All data came from standardized samples. </p>
Fig. 1 in The Amount And Distribution Of The Red Data Book Bird Wetland Species In The Azov-Black Sea Region Of Ukraine According To The Results Of August Counts 2004-2015
Fig. 1. Number of August Counts in the different wetlands of Azov-Black Sea coast of Ukraine.
Nestedness theory suggests wetland fragments with large areas and macrophyte diversity benefit waterbirds
<p>Many artificial wetland constructions are currently underway worldwide to compensate for the degradation of natural wetland systems. Researchers face the responsibility of proposing wetland management and species protection strategies to ensure that constructed wetlands positively impact waterbird diversity. Nestedness is a commonly occurring pattern for biotas in fragmented habitats with important implications for conservation; however, only a few studies have focused on seasonal waterbird communities in current artificial wetlands. In this study, we used the nestedness theory for analyzing the annual and seasonal community structures of waterbirds in artificial wetlands at Lake Dianchi (China) to suggest artificial wetland management and waterbird conservation strategies. We carried out three waterbird surveys per month for one year to observe the annual, spring, summer, autumn, and winter waterbird assemblages in 27 lakeside artificial wetland fragments. We used the NeD program to quantify nestedness patterns of waterbirds at the annual and seasonal levels. We also determined Spearman partial correlations to examine the associations of nestedness rank and habitat variables to explore the factors underlying nestedness patterns. We found that annual and all four seasonal waterbird compositions were nested, and selective extinction and habitat nestedness were the main factors governing nestedness. Further, selective colonization was the key driver of nestedness in autumn and winter waterbirds. We suggest that the area of wetland fragments should be as large as possible and that habitat heterogeneity should be maximized to fulfill the conservation needs of different seasonal waterbirds. Furthermore, we suggest that future studies should focus on the least area criterion, and that vegetation management of artificial wetland construction should be based on the notion of sustainable development for humans and wildlife. </p>
A novel trophic cascade between cougars and feral donkeys shapes desert wetlands
<p>Introduced large herbivores have partly filled ecological gaps formed in the late Pleistocene, when many of the Earth's megafauna were driven extinct. However, extant predators are generally considered incapable of exerting top-down influences on introduced megafauna, leading to unusually strong disturbance and herbivory relative to native herbivores.</p> <p>We report on the first documented predation of juvenile feral donkeys (<em>Equus africanus asinus</em>) by cougars (<em>Puma concolor</em>) in the Mojave and Sonoran Deserts of North America. We then investigated how cougar predation corresponds with differences in feral donkey behavior and associated effects on desert wetlands.</p> <p>Focusing on a feral donkey population in Death Valley National Park, we compared donkey activity patterns and impacts between wetlands with and without cougar predation.</p> <p>Donkeys were primarily diurnal at wetlands with cougar predation, thereby avoiding cougars. However, donkeys were active throughout the day and night at sites without predation. Donkeys were ~87% less active (measured as hours of activity a day) at wetlands with predation (p<0.0001). Sites with predation had reduced donkey disturbance and herbivory, including ~46% fewer access trails, 43% less trampled bare ground, and 192% more canopy cover (PERMANOVA, R<sup>2</sup> = 0.22, p=0.0003).</p> <p>Our study is the first to reveal a trophic cascade involving cougars, feral equids, and vegetation. Cougar predation appears to rewire an ancient food web, with diverse implications for modern ecosystems. Our results suggest that protecting apex predators could have important implications for the ecological effects of introduced megafauna.</p>
To a charismatic rescue: Designing a blueprint to steer fishing cat conservation for safeguarding Indian wetlands
<p>Wetland conservation in the Indo-tropics can benefit from the protection of the charismatic Fishing Cat. India, supporting ∼ 40% of its known range, is a stronghold for the species. Here, using multiple information sources we outline a framework to safeguard fishing cats in India. Specifically, we a) estimated district-level Conservation priority scores (using presence records, and habitat suitability and habitat connectivity) to identify ecologically important habitats, b) estimated state-level Conservation likelihood scores assessing the success potential of any conservation intervention, c) collated district-level Conservation initiative information identifying ongoing efforts for species and/or habitat conservation. We consecutively assessed the spatial congruence between (a), (b) and (c) to delineate species' conservation areas and corresponding action goals (blueprint). Using information on habitat suitability, we also delineated survey landscapes. Although Fishing Cat records were found in 12 Indian states, only a small proportion of the state area was identified harbouring optimal habitat for the species. Three broad habitat clusters - Terai arc, Eastern coast, and Brahmaputra floodplains - were identified, with overall high habitat connectivity. Most districts ranking high in Conservation priority scored low in Conservation likelihood. Districts with Fishing Cat presence (n = 60) were delineated into four tiers of action landscapes and the majority of districts classified as survey landscapes (n = 156) were found in the Terai arc. We use our results to recommend and discuss conservation actions for districts identified in our blueprint. Flagship species conservation approach has substantial potential to enrich wetland conservation, for which our blueprint can act as a baseline.</p>
Intraspecific variation and economics spectrum of Phragmites australis in lakeshore wetland of (semi-) arid regions
<p><em>Phragmites australis</em>, as a widely distributed species, has a high degree of intraspecific variation in functional traits and is able to respond to external climatic and environmental changes and adjust its adaptation strategies on time. The plant economic spectrum can reflect the adaptation strategies of resource acquisition and storage of plants in different climatic regions, and provide a scientific basis for understanding the ecological differentiation of plants in different habitats and their adaptation mechanisms. In this study, the morphological traits, nutrient contents and stoichiometric ratios of <em>P. australis</em> in lakes and lakeshore wetlands of semi-arid and arid climatic regions from east to west in Inner Mongolia Plateau were investigated to reveal the variability of plant functional traits at different regional scales and the influencing factors, and to reveal the ecological adaptation strategies of <em>P. australis</em> in different regions through plant economic spectrum. The results showed that soil moisture gradient, geographic location and regional scale effected the intraspecific variation of functional traits of <em>P. australis</em>. At the local scale, soil moisture gradients had opposite effects on the response to functional traits of <em>P. australis</em> in the arid and semi-arid regions. At the regional scale, climatic factors dominated the variation of reed functional traits across the latitudinal gradient, while the correlation with soil properties was not significant (<em>P</em> > 0.05). Plant economic spectrum theory is also applicable to the functional traits of various organs and whole plants of <em>P. australis</em> populations at different regional scales, and the acquisition and assimilation of resources is conservative in arid regions, while in semi-arid regions it is an acquisition strategy. This study provides a new understanding of the ecological niche differentiation and drivers of plant populations and ecological adaptation strategies of species at the regional scale, and provides a theoretical basis for the restoration and reconstruction of degraded wetland ecosystems.</p>
Global wetland CH4 emissions estimated by LPJ-wsl model for 1980-2021
<p>This dataset contains two files that summarize the regional wetland methane emissions simulated by LPJ-wsl model for the period of 2000-2021. two estimates based on two climate forcing datasets, ground-based CRU and reanalysis-based MERRA2. The ground-based input dataset is a monthly climatic observation based on meteorological stations developed by Climatic Research Unit, University of East Anglia. The reanalysis-based climate dataset is a daily climatic dataset from 1 hourly reanalysis Modern-Era Retrospective analysis for Research and Applications Version 2. For more details about LPJ-wsl model, see Zhang et al., (2017, 2018).</p> <p>References:</p> <p>Zhang, Z., Zimmermann, N.E., Stenke, A., Li, X., Hodson, E.L., Zhu, G., Huang, C., Poulter, B., 2017. Emerging role of wetland methane emissions in driving 21st century climate change. Proceedings of the National Academy of Sciences 114, 9647–9652. <a href="https://doi.org/10.1073/pnas.1618765114">https://doi.org/10.1073/pnas.1618765114</a></p> <p>Zhang, Z., Zimmermann, N.E., Calle, L., Hurtt, G., Chatterjee, A., Poulter, B., 2018. Enhanced response of global wetland methane emissions to the 2015–2016 El Niño-Southern Oscillation event. Environmental Research Letters 13, 074009. <a href="https://doi.org/10.1088/1748-9326/aac939">https://doi.org/10.1088/1748-9326/aac939</a></p>
The detailed wetland data of Haikou and Yinchuan in 2015 and 2020
<p>2015年和2020年银川和海口14种湿地类型和6种非湿地类型数据</p>
Figure 45. Immature Cosmophasis umbratica from Singapore. 1-2, Penultimate male from Sugei Buloh Wetland Reserve. 3-6 in Three new jumping spiders of the genus Cosmophasis from Wallacea (Araneae: Salticidae: Chrysillini)
Figure 45. Immature Cosmophasis umbratica from Singapore. 1-2, Penultimate male from Sugei Buloh Wetland Reserve. 3-6, Immature or penultimate female. Photographs © Nicky Bay, used with permission.
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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.