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78 results for “river network”
Modelling riparian forest distribution and composition to entire river networks
<p><strong>Aim: </strong>Developing a methodology to map the distribution of riparian forests to entire river networks and determining the main environmental factors controlling their spatial patterns.</p> <p><strong>Location: </strong>Cantabrian region, northern Spain.</p> <p><strong>Methods: </strong>We mapped the riparian forests at a physiognomic and phytosociological levels by delimiting riparian zones and generating vegetation distribution models based on remote sensing data (Landsat 8 OLI and LiDAR PNOA). We built virtual watersheds to define a spatial framework where the catchment environmental information can be routed to each river reach, jointly with the vegetation map. In order to determine the drivers playing a significant role on the observed spatial patterns in the riparian forest we modelled interactions between these datasets of environmental information and riparian vegetation by using the Random Forest algorithm.</p> <p><strong>Results: </strong>The modelling results obtained reproduced a reliable variation of riparian forest structure and composition across Cantabrian watersheds. The produced maps were highly accurate, with more than a 70% overall accuracy for the forest occurrence. A clear differentiation between Eurosiberian (91E0 and 9160 habitats) and Mediterranean (92E0) riparian forests was shown on both sides of the mountain range. Topography and land use were the main drivers defining the distribution of riparian forest as a physiognomic unit. In turn, altitude, climate and percentage of pasture were the most relevant factors determining their composition (phytosociological approach).</p> <p><strong>Conclusions: </strong>Our study confirms that the anthropic control ultimately defines the distribution of the vegetation in the riparian area at a regional to local scale. Human disturbances constrain the extension of forest patches across their potential distribution defined by topoclimatic boundaries, which establish a clear limit between Mediterranean and Eurosiberian biogeographical regions.</p>
Supporting data ocean model GMD submission: From Weather Data to River Runoff: Leveraging Spatiotemporal Convolutional Networks for Comprehensive Discharge Forecasting
<p>Ocean model salinity data used for the comparison of the ConvLSTM river runoff model and the original E-HYPE based model simulations.</p>
In-situ monitoring of the Seine River based on the MeSeine network
<p>In Europe, the management of freshwater ecosystem is governed by the Water Framework Directive (2000/60/CE) and its transposing legislation in France (2006-1772 of December 2006). The good ecological status of water are evaluated using a combination of several indicators such as biological and physico-chemical parameters. The Seine River crosses several important urbanized areas of France, including the Parisian conurbation (9 millions inhabitants). To ensure the good ecological status of the Seine River, the Greater Paris Conurbation Sanitation Authority (SIAAP), has constructed and operated the MeSeine network since 1990. MeSeine constitutes a tool for evaluating the quality of the Seine river and its tributaries (Marne, Oise) in terms of physico-chemistry, bacteriology, micro-contamination and faunal diversity.</p> <p>The MeSeine network extends along 125 km of the Seine River (from Choisy to Méricourt) and over 13 km along the Marne River (frome Champigny to Alfortville). It is structured around tree pillars:</p> <ul> <li>Real time monitoring of the physico-chemical composition of the Seine river using in situ sensor, in particular dissolved oxygen and temperature sensors</li> <li>Sampling and laboratory analysis campaigns to monitor watercourses quality and comply with the quality standards as defined by the Water Framework Directive (good ecological and chemical parameters)</li> <li>Biota monitoring to appreciate the diversity of fish populations, macro-invertebrates and diatoms.</li> </ul> <p>The aim of this work is to provide dissolved oxygen and temperature data of the Seine, generated by the in-situ sensors of the MeSeine network, via the open platform Zenodo.</p>
Monitoring of the physico-chemical composition of the Seine River based on the MeSeine network
<p>In Europe, the management of freshwater ecosystem is governed by the Water Framework Directive (2000/60/CE) and its transposing legislation in France (2006-1772 of December 2006). The good ecological status of water are evaluated using a combination of several indicators such as biological and physico-chemical parameters. The Seine River crosses several important urbanized areas of France, including the Parisian conurbation (9 millions inhabitants). To ensure the good ecological status of the Seine River, the Greater Paris Conurbation Sanitation Authority (SIAAP), has constructed and operated the MeSeine network since 1990. MeSeine constitutes a tool for evaluating the quality of the Seine river and its tributaries (Marne, Oise) in terms of physico-chemistry, bacteriology, micro-contamination and faunal diversity.</p> <p>The MeSeine network extends along 125 km of the Seine River (from Choisy to Méricourt) and over 13 km along the Marne River (frome Champigny to Alfortville). It is structured around tree pillars:</p> <ul> <li>Real time monitoring of the physico-chemical composition of the Seine river using in situ sensor, in particular dissolved oxygen and temperature sensors</li> <li>Sampling and laboratory analysis campaigns to monitor watercourses quality and comply with the quality standards as defined by the Water Framework Directive (good ecological and chemical parameters)</li> <li>Biota monitoring to appreciate the diversity of fish populations, macro-invertebrates and diatoms.</li> </ul> <p>The aim of this work is to provide data on the physico-chemical quality of the Seine generated by the MeSeine observatory via the open platform Zenodo.</p>
Functional and taxonomic diversity indices of riparian plants in river networks
<p>1. The River Continuum Concept (RCC) predicts a gradual shift of organisms' functional adaptations along the longitudinal (upstream-downstream) gradient, as well as the maximization of the biotic diversity in mid-reaches. Although this theoretical framework was originally developed for stream macroinvertebrates, we tested whether such a pattern can be also observed in riparian plant communities.</p> <p>2. We studied the cover of plant species in riparian forests across two river networks. We analyzed the taxonomic and functional diversity indices, as well as community-weighted means of functional traits in relation to the plots' position in the catchments.</p> <p>3. The observed patterns were largely in line with the predictions of RCC. We discovered a significant decrease in the specific leaf area and an increase in the herbaceous plants' height in communities along a river gradient. There was also a shift in the dispersal syndromes, towards a higher importance of zoochory in the lower reaches.</p> <p>4. The functional richness and divergence displayed unimodal patterns of increasing values in the mid-reaches. The patterns of taxonomic diversity were similar, but some plots in the lowest reaches were more diverse than expected, forming an additional increase in diversity.</p> <p>5. The study shows that plant communities in natural riparian forests show high connectivity along the longitudinal gradient, which along with the environmental gradients creates patterns that are known from theoretical predictions.</p>
Data from: Thermal springs and active fault network of the central Colca River basin, Western Cordillera, Peru, published in Journal of Volcanology and Geothermal Research
<p>We used hydrogeochemical analysis of 35 water samples from springs and geysers, together with isotopic (δ<sup>18</sup>O and δD) analysis, chemical and mineral studies of precipitates collected in the field around these outflows, and field observations to study the thermal system of the Colca River basin in S Peru. We aimed to determine the geochemistry of thermal waters, identify fluid sources and their origin, estimate reservoir temperature, and discuss the regional tectonic and volcanic framework. Our findings presented in Tyc et al. (2022; https://doi.org/10.1016/j.jvolgeores.2022.107513) corroborate a heterogeneous and complex geothermal system in the central region of the Colca River basin. This system exhibits contrasting hydrogeochemical and physical characteristics, variable isotope compositions, distinct reservoir temperatures, and associated precipitates near thermal springs. The control of water chemistry in this area is closely linked to the activity of the Ampato-Sabancaya magmatic chamber and the presence of tectonic structures, which enable intricate interactions between meteoric waters, magmatic fluids, and gases.</p> <p>Here, we present datasets used in the article (Tyc et al., 2022; https://doi.org/10.1016/j.jvolgeores.2022.107513), including:</p> <p>- Physicochemical characteristics of water samples collected by authors in the field in September 2012 and August–September 2017 (Table 1)</p> <p>- Chemical and isotopic composition of water samples collected by authors in the field in September 2012 and August–September 2017 (Table 2) and those monitored by INGEMMET in years 2013-2018 (Table 3)</p> <p>- Chosen molecular ratios discussed in Tyc et al., 2022 (Table 4)</p> <p>- Calculated reservoir temperature with the use of different Na/K geothermometers (Table 5)</p> <p>- Mineral phases in efflorescences precipitating at the water sampling sites (Table 6).</p> <p>Thirty-five sets of water samples were collected in the field in September 2012 and August–September 2017 using polyethylene bottles of high density (Table 1). Consequently, these were analyzed in the Water Analysis Laboratory at the University of Silesia in Katowice (Poland; Table 2). Water temperatures, pH, and electrical conductivity were measured in the field using portable pH meter CP-315 and conductivity meter CC-315, both with temperature sensors, with an accuracy of ±0.1 °C, ±0.01 pH, and ± 0.1% (up to 19.999 mS/cm) or ± 0.25% (above 20.00 mS/cm), respectively. Discharge of springs was estimated if possible (Table 1). Both cations and anions were analyzed by ion chromatography using Methron 850 Professional Ion Chromatograph with separate Metrosept C4–150 and A-supp 7–250 columns for cations and anions, respectively (Tables 2 and 4). Analysis of water analyses collected by INGEMMET in years 2013-2018 was performed at the INGEMMET Chemical Laboratory in Lima with the use of ion chromatography (Dionex ICS 5000) for the determination of anions and inductively coupled plasma optical emission spectrometry (ICP-OES) – VARIAN for cations (Table 3). Isotopic analyses (δ<sup>2</sup>H, δ<sup>18</sup>O) of 17 water samples collected in 2017 were performed at the Stable Isotope Laboratory Institute of Geological Sciences Polish Academy of Sciences (Table 2). The δ<sup>2</sup>H values of studied H<sub>2</sub>O were measured using the H-Device peripheral coupled to MAT 253 IRMS (Thermo Scientific) in a dual inlet system. For the determination of δ<sup>18</sup>O in H<sub>2</sub>O, an equilibration technique was used. The analysis used the GasBench II peripheral device (Thermo Scientific) coupled to MAT 253 IRMS with a continuous He flow. The AquaChem 4.0.284 software was used to evaluate the water samples' geochemical properties and calculate reservoir temperature for thermal waters (Table 5). Precipitates found at the water sampling sites were collected separately into plastic bags with strings and sealed boxes. These samples were subsequently analyzed at the Institute of Earth Sciences, University of Silesia in Katowice. The qualitative chemical composition and mineral characteristics were examined using a Philips XL 30 ESEM/TMP scanning electron microscope coupled with an energy-dispersive spectrometer (EDS; EDAX type Sapphire). The phase composition of the precipitates was determined through X-ray diffraction (XRD) using a Philips PW 3710 diffractometer. The XRD data were analyzed and interpreted using the X'Pert HIGHScore Plus software (Table 6).</p>
Estimating drivers and identifying uncertainties in smallmouth bass population dynamics in an invaded river network
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Data from: As time goes by: 20 years of changes in the aquatic macroinvertebrate metacommunity of Mediterranean river networks
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Functional and taxonomic diversity indices of riparian plants in river networks
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Drying and fragmentation drive the dynamics of resources, consumers and ecosystem functions across aquatic-terrestrial habitats in a river network
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Stream Order for drainage to streams in the Ipswich or Parker River Network - ASCII Raster File
This datalayer is a gridded data set that identifies for each pixel the stream order that drainage from the pixel initially enters into the river network. The resolution is 120 m x 120 m. Based on the flow direction in: WAT-RGIS-120m-FlowDirection.asc. First order streams at the 120m resolution are equivalent to third order when calculated at the pixel level from the drainage direction grid (i.e. 3rd order pixels are equivalent to 1st order streams, 4th order pixels are second order streams, etc). Idenitify the distribution of inputs from land to streams of different sizes.
10Be concentrations constraining surface age and valley growth rate in a seepage-derived drainage network in the Apalachicola River basin, Florida
<p class="Head1"><span><span>Measuring rates of valley head migration and determining the timing of canyon-opening are insightful quantifications for the history and evolution of planetary surfaces. Horizontal spatial gradients of <em>in situ-</em>produced cosmogenic nuclide concentrations provide a framework for assessing the migration of these and similar topographic features. We developed a theoretical model for the concentration of <em>in situ</em> produced cosmogenic radionuclides in valley walls during retreat of a valley head. The retreat rate is inversely proportional to the magnitude of the spatial concentration gradient and proportional to local nuclide accumulation rates. By solving for a spatial gradient in concentration along a valley parallel transect, we created an expression for the explicit determination of valley head retreat, termed unzipping. We applied this theory to a developing seepage-derived drainage network along the Apalachicola River, Florida, USA. Sample concentrations along a valley margin transect vary systematically from 2.9 x 10<sup>5</sup> atoms/g to 3.5 x 10<sup>5</sup> atoms/g resulting in a gradient of 160 atoms/g/m, and from this value a valley head retreat rate of 0.025 m/y is found. The discrepancy between overall network age and current rates of valley head migration suggests intermittent network growth which is consistent with glacial-interglacial precipitation variations during the Pleistocene. This method can be applied to a wide range of Earth-surface environments. For the <sup>10</sup>Be system, this method should be sensitive to unzipping rates bounded between 10<sup>-6</sup> m/y and 10<sup>0</sup> m/y.</span></span></p>
ClimateNet Dataset as used in "Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data"
<p>ClimateNet dataset as it was used by us for the study: "Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data" (https://gmd.copernicus.org/preprints/gmd-2024-60/).</p> <p> </p> <p>For the original dataset refer to: https://portal.nersc.gov/project/ClimateNet/</p>
Monthly pCO2, gas transfer velocity and CO2 efflux rate in global streams and rivers (the GRADES river networks)
<p>The datasets contain monthly partial pressure of dissolved CO<sub>2</sub> (<em>p</em>CO<sub>2</sub>, µatm), gas transfer velocity (<em>k</em>, m d<sup>-1</sup>), and CO<sub>2</sub> efflux rate (g C m<sup>-2</sup> d<sup>-1</sup>) estimates for global streams and rivers in both comma separated values (csv) and GeoTIFF formats. These datasets served as the base for monthly CO<sub>2</sub> emission estimates for global streams and rivers and can be used to support regional terrestrial carbon balances. Original vector-version of products is based on the Global Reach–level A priori Discharge Estimates for SWOT or GRADES river networks, which have ~ 3 million individual reaches of global streams and rivers. The GeoTIFF version has a spatial resolution of approximately 0.0083º (1 km). The datasets also contain direct CO<sub>2</sub> measurements compiled from the literature (Supplementary Data 1).</p>
Fish abundance data in forest steppe and grassland river networks in Mongolia
<p>Fish abundance data (fish per m) collected during the MACRO project in Mongolia. We collected fish assemblages in river networks of two different ecoregions, the Forest Steppe (FS) and Grassland (G), in 2017 and 2019.</p>
Pulse, Shunt and Storage: Hydrological Contraction Shapes Processing and Export of Particulate Organic Matter in River Networks
<p>This repository hosts the code to run the analysis presented in </p> <p>"Pulse, Shunt and Storage: Hydrological Contraction Shapes Processing and Export of Particulate Organic Matter in River Networks" <br> by Catalan et al., Ecosystems, 2022.<br> DOI: https://doi.org/10.1007/s10021-022-00802-4</p> <p>The code has been tested on Matlab R2019b.</p> <p>Run the Main.m code to produce the results of Figure 3 and 4 of the paper.<br> Each simulation takes about 8 hours on a standard Desktop computer.</p>
Data from: Evaluating the sensitivity of process domains for logjams to spatial and temporal sample size in river networks of the Southern Rockies, USA
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Data from: A comprehensive examination of the network position hypothesis across multiple river metacommunities
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10Be concentrations constraining surface age and valley growth rate in a seepage-derived drainage network in the Apalachicola River basin, Florida
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Data from: River network architecture, genetic effective size and distributional patterns predict differences in genetic structure across species in a dryland stream fish community
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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)
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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.