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2,691 results for “streams”
Dataset of nitrogen in rivers and streams in sub-Saharan Africa
<p>This is a dataset on concentrations and export of all nitrogen compounds in rivers and streams in sub-Saharan Africa reported in scientific literature (<em>n</em>=254) until July 2024. Data are aggregated by site and, where possible, data are reported for the dry and wet season separately. In addition to concentrations and export of nitrogen compounds, data on ancillary parameters, such as pH, electrical conductivity and dissolved oxygen area also included. Each site for which (approximate) coordinates could be extracted from the original study was assigned to a land cover class based on open source data on tree cover and the extent of cropland, settlement and wetlands across Africa (see second tab in the file 'Dataset.xlsx' for land cover classes and corresponding classification conditions as well as data sources). The third tab in the file 'Dataset.xlsx' contains links to the individual studies and full references are provided in the file 'Reference list.pdf'.</p>
Hydrological, physicochemical and metabolic activity data for streams in the Japanese Alps
<p>A series of files with hydrological, physicochemical and metabolic activity data from a study investigating the environmental dynamics of six stream systems in the Japanese Alps.</p>
Indicative distribution map for Ecosystem Functional Group F1.1 Permanent upland streams
<p>This archive contains indicative distribution maps and profiles for <strong>F1.1 Permanent upland streams</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group F1.4 Seasonal upland streams
<p>This archive contains indicative distribution maps and profiles for <strong>F1.4 Seasonal upland streams</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group SF1.1 Underground streams and pools
<p>This archive contains indicative distribution maps and profiles for <strong>SF1.1 Underground streams and pools</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Accepted Artifact for Profiling and Optimizing Java Streams
<p>The accepted artifact for the journal article "Profiling and Optimizing Java Streams" published in Volume 7, Issue 3 of <a href="https://programming-journal.org/"><em>The Art, Science, and Engineering of Programming</em></a>.</p> <p>Please refer to the README.md to work with the artifact and reproduce results from the article.</p>
Dataset of a 5G RTSP video streaming use case
<p><strong>About the project: monitoring 5G RTSP video streaming</strong></p> <p>This dataset collects data from a 5G video streaming use case. A video is streamed by a cvlc server (realized as a Kubernetes pod) through RTSP to a variable number of 5G UE clients that activate according to a daily traffic pattern. The values of the 4 dataset features (number of active UEs, gNB's downlink bit rate, pod's outbound traffic, and pod's CPU usage) are collected by a custom monitoring system deployed in the context of the MONB5G project.</p> <p><strong>Setup/Equipment</strong></p> <p>The Kubernetes cluster, including the server pod, runs in a COTS server. The 5G core and gNB is realized through Amarisoft Callbox Ultimate. The UEs are emulated through Amarisoft Simbox. In order to display the video in ffplay clients, we use the Remote UE from Amarisoft, so traffic from Simbox is forwarded to an external VM with GUI.</p> <p><strong>Video</strong></p> <p>The streamed video is Big Buck Bunny at 30 FPS from <a href="https://peach.blender.org/">https://peach.blender.org/</a>.</p> <table> <tbody> <tr> <td> <p>Video codec </p> </td> <td> <p>Advanced Video Codec (AVC) </p> </td> </tr> <tr> <td> <p>Width </p> </td> <td> <p>1920 pixels </p> </td> </tr> <tr> <td> <p>Height </p> </td> <td> <p>1080 pixels </p> </td> </tr> <tr> <td> <p>Display aspect radio </p> </td> <td> <p>16:9 </p> </td> </tr> <tr> <td> <p>Duration </p> </td> <td> <p>10 min 34 s </p> </td> </tr> <tr> <td> <p>Max Bitrate </p> </td> <td> <p>16.7 Mb/s </p> </td> </tr> <tr> <td> <p>Frame rate </p> </td> <td> <p>30 FPS </p> </td> </tr> </tbody> </table> <p><strong>What does this Zenodo project contain?</strong></p> <ol> <li>The csv file of the dataset (dataset.csv)</li> <li>A picture displaying an overview of the setup (overview.png)</li> <li>A picture displaying Grafana charts for each featuer (grafana.png)</li> <li>A picture displaying a screenshot of the Remote UE VM with multiple UEs playing the video (ues.png)</li> </ol> <p><strong>Dataset</strong></p> <p>The dataset has 5 columns (time + 4 features). Features:</p> <ol> <li><em>Time</em>: timestamp in epoch format.</li> <li><em>Number of active UEs (N)</em>: number of UEs that are currently downloading more than 100 kbps. No unit.</li> <li><em>gNB's downlink bit rate (R)</em>: aggregate downlinkg bitrate from the gNB to all the UEs. In Mbps.</li> <li><em>Outbound traffic (O)</em>: outboun traffic at the pod's interface, transmitting the video(s) packets. In Mbps.</li> <li><em>CPU (C)</em>: CPU usage at the server pod. In millicores (mc). Each iteration represents a whole day, composed of 24 "demand periods". Each demand period takes 2 minutes and is given by the number of active UEs consuming the video stream (N). N is included for informative reasons. Sampling rate is 10 seconds, but some parameters are refreshed at a lower frequency given monitoring limitations. This means that some parameters repeat the same value in consecutive measurements.</li> </ol>
Datasets for "Mass-stream trajectories with non-synchronously rotating donors"
<p>Datasets to accompany the publication of the paper "Mass-stream trajectories with non-synchronously rotating donors" by David Hendriks and Rob Izzard (<a href="https://doi.org/10.1093/mnras/stad2077">https://doi.org/10.1093/mnras/stad2077</a>).</p> <p>Below follows an explanation of the contents of this repository:</p> <ul> <li>Hendriks2023_ballistic_stream_datafile.csv: Data file containing the ballistic trajectory data for a ranges of initial stream velocity, donor synchronicity and mass ratio. This file contains a header with extra information.</li> <li>Hendriks2023_ballistic_stream_metadata.json: Settings file containing the configuration for the ballistic stream integration simulations and other meta data.</li> <li>Hendriks2023_binary_populations_exploration_data_Z0.02.csv: Data file containing the binary population data at Z=0.02. This file contains a header with extra information.</li> <li>Hendriks2023_binary_populations_exploration_metadata.json: Settings file containing the configuration for the binary population synthesis simulations, including binary_c-python settings, binary_c information and other meta data.</li> <li>RLOF_Hendriks2023_roche_lobe_interpolation_table.csv: Data file containing Roche-lobe radius data for a range of donor synchronicity and mass ratio (q=M_acc/M_don).</li> <li> readme.md: readme file.</li> </ul>
Simulation results of adaptive multicast streaming for videoconferences in software-defined networks
<p>Real-time applications, such as video conferences, have strong Quality of Service requirements for ensuring a decent Quality of Experience. Nowadays, most of these conferences are performed over wireless devices. Thus, an appropriate management of both heterogeneous mobile devices and network dynamics is necessary. Software Defined Networking enables the use of multicasting and stream layering inside the network nodes, two techniques able to enhance the quality of live video streams. In this paper, we propose two algorithms for building and maintaining multicast sessions in a software-defined network. The first algorithm sets up the initial multicast trees for a given call. It optimally places the stream layer adaptation function inside the core network in order to minimize the bandwidth consumption. This algorithm has two versions: the first one, based on shortest path trees is minimizing the latency, while the second one, based on spanning trees is minimizing the bandwidth consumption. The second algorithm adapts the multicast trees according to the network changes occurring during a call. It does not recompute the trees, but only relocates the stream layer adaptation functions. It requires very low computation at the controller, thus making our proposal fast and highly reactive. Extensive simulation results confirm the efficiency of our solution in terms of processing time and bandwidth savings compared to existing solutions such as multiple unicast connections, Multipoint Control Unit solutions and application layer multicast.</p>
Food-chain length in desert streams of central and southern Arizona, USA
## overview Food chain length (FCL) is a key measure of the vertical structure of food webs that determines energy flow through ecosystems, carbon exchange between freshwater ecosystems and the atmosphere, and rates of nutrient cycling. FCL also has a strong bearing on the biomass of green plants in ecosystems and hence on water quality in aquatic ecosystems. Broad-scale syntheses of controls on FCL in stream ecosystems indicate that FCL declines with discharge variation but, counter to theory, does not vary significantly with energy supply. The mechanisms linking discharge and energy to FCL are largely unresolved in streams. We propose that lack of a relationship between energy supply and FCL may be due to variation in efficiency of energy transfer caused by constraints of food quality, or to a temporal mismatch between measures of energy inputs and FCL. Alternatively, the effects of flow variation on FCL may simply be paramount to energy supply, but potential mechanisms linking flow to FCL remain untested. Regime shifts—punctuated change between strings of high- and low-flow events—may cause comprehensive faunal replacement across trophic levels and collapse of the vertical structure of food webs. FCL may change as a result of loss (or gain) of an apex predator, or as a result of changes in feeding relationships leading to apex predators that eat higher on the food chain. Finally, flow variation may indirectly influence FCL through inputs of limiting nutrients during floods. In desert streams, algae typically provide the primary source of energy, and algal production is limited by nitrogen (N). N loading from terrestrial ecosystems is strongly related to flow variation, particularly to the inter-flood interval (IFI) or duration of baseflow between floods. Long IFI leads to larger N pulses and potentially greater net ecosystem production (NEP), thereby providing an indirect effect of flow variation on FCL. Specific aims of the research include: 1) Quantify the effe
Survey of Odonata Abundance in Two Streams at El Yunque Rainforest (2018-2019)
The focus of this research was to study the natural history of odonate species in headwater montane streams following major hurricane impacts in Puerto Rico. We monitored assemblages from August 2018 to July 2019 in two headwater streams within El Yunque National Forest, Puerto Rico. Data contains information on abundance of adult and larvae of different species of Odonata, as well as head width and body length of larvae. Data a product of: Ashley Mariani-Ríos, Norman Maldonado-Benítez & Alonso Ramírez (2022) Natural history of Odonata assemblages in tropical streams in Puerto Rico, Neotropical Biodiversity, 8:1, 112-123, DOI: 10.1080/23766808.2022.2043699
Freshwater connectivity clusters for lakes, wetlands, and streams at the Hydrologic Unit 12 scale in the Midwest and Northeast U.S.A. – freshwater metric variables and K-means cluster assignment
This dataset includes freshwater connectivity cluster output and principal component scores for lakes, wetlands, and streams measured at the Hydrologic Unit 12 (HU12) scale in 17 U.S. states in the Midwest and Northeast regions (appr. 1,800,000 km2). The intent of the cluster analysis is to characterize the macroscale patterns of freshwater connectivity attributes. We define freshwater connectivity as the permanent surface hydrologic connections that link lakes, wetlands, and streams and measure connectivity as the landscape position of systems within stream networks. Geographic data used in the analysis are in LAGOS-NE-GEO database v. 1.03 (Lake multi-scaled geospatial and temporal database), an integrated, multi-thematic geographic database (Soranno et al. 2015). Freshwater connectivity clusters were created separately for lakes, wetlands, and streams through a multi-step process as follows: 1) we quantified multiple freshwater connectivity metrics, 2) we performed principal components analysis (PCA) on the connectivity metric values for each freshwater type to reduce collinearity, and 3) we performed k-means cluster analysis to group spatial units with similar freshwater connectivity characteristics. The resulting freshwater clusters are representations of the macroscale patterns of lake, wetland, and stream connectivity in the landscape.
Data from: Heterogeneity in habitat and nutrient availability facilitate the co-occurrence of N2 fixation and denitrification across wetland - stream - lake ecotones of Lakes Superior and Huron
Great Lakes coastlines are mosaics of wetland, stream, and lake habitats, characterized by a high degree of spatial heterogeneity that may facilitate the co-occurrence of seemingly incompatible biogeochemical processes due to variation in environmental factors that favor each process. We measured nutrient limitation and rates of N2 fixation and denitrification along transects in 5 wetland - stream - lake ecotones with different nutrient loading in Lakes Superior and Huron and hypothesized that rates of both processes would be related to nutrient limitation status, habitat type, and environmental characteristics including temperature, nutrient concentrations, and organic matter quality. This data package includes information on sampling sites, dates and locations; rates of N fixation and denitrification measured at each site, date and transect location; and biomass information from nutrient diffusing substrates deployed on the study transects.
Snail Shell Strength and Total Crush Force of a Northern Michigan Snail as a Function of Predation Risk at the University of Michigan Biological Station Stream Research Facility (5/31/23-8/1/23)
Many prey organisms respond to the non-consumptive effects of predators by altering their physiology, morphology, and behavior. These inducible defenses can create refuges for prey by decreasing the likelihood of consumption by predators. Some prey, as in marine mollusks, have been shown to alter their morphology in response to the presence of size-limited predation. To extend this work into the freshwater realm, we presented pointed campeloma snails (Campeloma decisum) to chemical cues from a natural predator, the rusty crayfish (Faxonius rusticus), to better understand how snail morphology changes under the threat of predation. The total force needed to crush shells, total shell length, aperture width, and total weight, along with changes to these three body measurements were recorded for each individual and used to quantify morphological changes as a function of risk. Snails exposed to crayfish chemical cues needed significantly more force to crush their shells than controls (p = 0.002). Total shell length was greater in crayfish exposed snails than control snails (p = 0.002), and snails in the crayfish treatment also showed significantly more change in shell length than control snails (p = 0.003). Similarly, aperture width was significantly greater in exposed snails (p = 0.002). However, exposed snails exhibited significantly less change in aperture width than controls (p = 0.017). Finally, we found that snails exposed to crayfish weighed significantly more than snails in the control (p = 0.0009). Thus, the results of this study show that morphology of gastropods is altered in the presence of predators, and this may be an antipredator tactic directly related to risk.
Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 01, Highlands Biological Station, Highlands, NC, USA, 2022-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Betula alleghanensis and formerly Tsuga canadensis, the latter of which has mostly succombed to the Hemlock Woolly Adelgid.
Daily Summary of Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 01, Highlands Biological Station, Highlands, NC
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Betula alleghanensis and formerly Tsuga canadensis, the latter of which has mostly succombed to the Hemlock Woolly Adelgid.
Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 02, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in a remnant old-growth Canada Hemlock Forest (typic subtype) community dominated by an understory of Rhododendron maximum and an overstory of Tsuga canadensis, the majority of which are still alive and have been treated with systemic insecticides to protect against infestations of the Hemlock Woolly Adelgid. Other trees include Betula alleghanensis, Acer rubrum, and Quercus rubra. The pressure transducer is located in the thalweg of Coker Creek, a second order stream that flows into Lindenwood Lake.
Daily Summary of Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 02, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in a remnant old-growth Canada Hemlock Forest (typic subtype) community dominated by an understory of Rhododendron maximum and an overstory of Tsuga canadensis, the majority of which are still alive and have been treated with systemic insecticides to protect against infestations of the Hemlock Woolly Adelgid. Other trees include Betula alleghanensis, Acer rubrum, and Quercus rubra. The pressure transducer is located in the thalweg of Coker Creek, a second order stream that flows into Lindenwood Lake.
Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 03, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Liriodendron tulipifera, Betula alleghanensis, and Tsuga canadensis, the latter of which has several trees that have succombed to the Hemlock Woolly Adelgid, though living trees have been treated with a systemic insecticide. The pressure transducer is located in a second order stream known as Station Branch.
Daily Summary of Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 03, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Liriodendron tulipifera, Betula alleghanensis, and Tsuga canadensis, the latter of which has several trees that have succombed to the Hemlock Woolly Adelgid, though living trees have been treated with a systemic insecticide. The pressure transducer is located in a second order stream known as Station Branch.
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