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205 results for “Ohio”
Pelagic, epilimnetic production estimates in Sparkling, Trout (Wisconsin), Acton (Ohio), and Castle (California) Lakes (USA) calculated using 14C and free-water O2 metabolism methods, 2007 - 2017
Concurrent daily estimates of pelagic, eplilimnetic production (mmol C m3 d) generated from 14C incubations and diel changes in high frequency dissolved oxygen data (free-water). Original data derived from the North Temperate Lakes Long Term Ecological Research program (Sparkling [2007-2013], Trout [2007-2012] Lakes), Castle Lake Research Station (Castle Lake [2014-2017]), and Center for Aquatic and Watershed Sciences (Acton Lake [2010-2014]). 14C production estimates were generated as part of each research programs core data collection. Free-water production estimates generated using high frequency sensor data provided by research programs and Phillips (2020) time-varying, Bayesian metabolism model.
H2Ohio Wetland Monitoring Program Surface Water and Soil Nutrient Content from Wetlands across Ohio, USA (2021–2022).
This data package contains surface water and soil nutrient concentration datasets from wetland projects across Ohio, USA monitored by the H2Ohio Wetland Monitoring Program. Monitoring began in May 2021 and is ongoing. This data package will be updated yearly. In general, surface water samples are collected to measure concentrations of major nutrients, including inorganic nitrogen, ammonium-nitrogen, total nitrogen, dissolved reactive phosphorus, and total phosphorus. Sampling from major inflows and outflows is prioritized at flow-through wetland projects to support the calculation of nutrient filtration estimates using mass balance approaches. Surface water samples may also be collected from representative zones or hydrologic features with sufficient standing water (i.e., vernal pools, vegetated areas, interconnected smaller pond-like areas, etc.) to assess nutrient conditions and processes within the wetland system. The majority of surface water sampling (~monthly) occurs from March through December, with opportunistic sampling in January and February. Every effort is made to collect samples during hydrologic events (i.e., storms) as well as baseflow conditions. Concurrent with surface water sampling, hand-held multiparameter sensors are used to measure snapshots of physicochemical characteristics including dissolved oxygen, temperature, specific conductance, turbidity, and pH. Soil samples (0-5 cm) are collected in saturated and unsaturated zones at each identified soil "patch" determined from expert opinion, soil maps (Natural Resources Conservation Service), and/or hydrogeophysical assessment. Additionally, soil samples may be collected along major visible hydrologic or elevation gradients. Soil sampling occurs 1-3 times a year in select wetland projects.
H2Ohio Wetland Monitoring Program Vegetation Community Composition, Biomass, and Nutrient Content across Ohio, USA (2021-2022)
This data package includes vegetation community composition, percent cover, biomass, and nutrient concentration data from wetland projects across Ohio, USA, monitored by the H2Ohio Wetland Monitoring Program. Monitoring began in July 2021 and is ongoing, with annual updates planned. While data collection varies by site, most wetlands are surveyed to characterize vegetation and estimate nutrient stocks through community composition assessments and biomass sampling. Sampling points are randomly generated within and up to 5 meters outside the approximated wetland boundary. Surveys are conducted at points where wetland species (FAC–OBL) are present using a 1×1 meter quadrat to record species composition and percent cover. At approximately half of these locations, a 0.25×0.25 meter quadrat is placed outside the northeast corner to collect vegetation samples for nutrient analysis. In these smaller quadrats, community composition and percent cover are recorded prior to sampling aboveground biomass and, at approximately one third of those sites, belowground biomass. Datasets collected by the H2Ohio Wetland Monitoring Program containing surface water and soil nutrient concentration from samples collected at Ohio wetlands during the 2021–2022 sampling period can be found in an accompanying data package (edi.2087) at https://doi.org/10.6073/pasta/297bd6d93b4fcc8416e4225834db380e.
Bird Communities in Fragmented, Non-Native Pine Plantations in the Oak Openings Region of Northwest Ohio
Comprehensive surveys, while preferred, are not always feasible due to time, logistical, and funding constraints. However, limited surveys of focal taxa, such as birds, coupled with vegetation surveys, can provide critical information to guide land management. In the 1930s non-native conifers were planted in the Oak Openings Region of northwestern Ohio, a biodiversity hotspot. The stands are declining, and management is needed, but restoration to native habitat is time consuming and expensive. Our research utilized an avian perspective of ecological function of introduced pine plantations versus native remnants to guide management. We surveyed bird activity May through July 2020 with point-counts in nine sites (1.3-2.3 ha) with three each of white pine, red pine, and oak forest sites. At each site, we estimated bird richness, abundance, and diversity, as well as structural characteristics (e.g., canopy cover), composition (e.g., vegetation types), and landscape context (e.g., landcover). Superficially, the pine sites appear to be beneficial as pine habitat for breeding birds, with high Simpson’s indices (up to 0.89) and high species richness compared to oak sites. However, our results reveal that the pines are not truly functioning as pine habitat for birds based on the limited occurrence of pine specialist species, proportion of generalists to pine specialists, and landscape context. Simple measures of diversity with no consideration as to species identity and without the environmental context fail to provide reliable measures of ecological value. Instead, we recommend selective sampling and consideration of landscape context, vegetation structure, and species classification to guide management.
Dust geochemistry and lead isotopes along an urban-rural transect in central Ohio, 2021
This data package contains geochemical concentrations and stable lead isotope ratios for dust samples collected along an urban-rural land use gradient in central Ohio during 2021. The purpose of the study was to characterize the geochemical and isotopic signatures of dust in relation to different land uses, to see how much dust varies across land use and by season. At four sites along an urban-rural transect in central Ohio, we collected weekly bulk deposition samples and analyzed the geochemical composition (47 elements including major elements, trace metals, and rare earth elements) and stable lead isotopes (208Pb, 207Pb, 206Pb, and 204Pb) of the particulate matter. This study demonstrates the tight connection between land use and anthropogenic dust composition in a region where land use is changing rapidly as development encroaches into farmland. This dataset is complete and will not be updated.
Air mass back-trajectory modeling output along an urban-rural transect in central Ohio, 2021
This data package contains modeled air parcel back-trajectories generated using the Stochastic Time-Inverted Lagrangian Transport model (STILT) via the R interface. The purpose of the study was to characterize the geochemical and isotopic signatures of dust in relation to different land uses, and to connect the geochemistry of deposited dust to air mass trajectories. Back-trajectories are three-dimensional paths of air parcels from a receptor site (the dust collection site) backwards in time and space for the duration of the tracking interval, calculated iteratively using wind fields from high-resolution gridded meteorological data. To calculate a probability of potential pathways, rather than a single back-trajectory, STILT introduces small random perturbations into the wind fields during each time step. For four sites along an urban-rural transect in central Ohio for June-July 2021, we generated weekly footprints of potential sources for the dust deposited at each site. These back-trajectories can be paired with geochemical data to establish a connection between land use and anthropogenic dust composition. This dataset is complete and will not be updated.
Long term limnological measurements in Acton Lake, a southwest Ohio reservoir, and its inflow streams: 1992-2023
Long-term data were collected from Acton Lake and its inflow streams on a suite of physical, chemical and biological variables. The data are collected as part of long-term research investigating how Acton Lake, a eutrophic reservoir, responds to changes in ecosystem subsidies of detritus (sediments) and nutrients. Our data span 31 years, from 1992-2023, although for some parameters the data set spans a shorter time frame within this period. In three of Acton Lake’s inflow streams, collectively constituting ~86% of the lake’s watershed, we include data on hourly stream discharge, as well as concentrations of suspended sediments, ammonium-N, nitrate+nitrite-N, and soluble reactive phosphorus (P). Data on the concentrations of these constituents were collected at various time scales depending on stream discharge (usually every 6-8 hours during storms, every 1-3 days during baseflow). In Acton Lake, we collected data on several parameters from an “outflow” site, at the deepest part of the lake where the water column is usually thermally stratified in summer. Vertical profile data were collected for temperature, dissolved oxygen, photosynthetically active radiation (PAR), and chlorophyll. Depth profile data were collected at 0.5 or 1 m intervals (depending on depth and year), usually weekly from April or May until September or October. In addition, data for several parameters were obtained from “integrated samples” that collect water from the lake surface to the bottom of the euphotic zone (defined as the depth at which PAR equals 1% of surface PAR) with a tube or pump. Parameters for which integrated data are presented include chlorophyll; suspended solids; non-volatile suspended solids; particulate (seston) carbon, nitrogen and phosphorus; and total nitrogen and total phosphorus. We also collected Secchi depth data, using standard methods. Larval fish were collected in the top 1-3 meter stratum of the water column with a metered net to generate estimates of lake-wide l
Sediment, C, N, and P Concentrations and Burial Rates in Three Southwestern Ohio Retention Ponds: 2006-2019
These datasets correspond to Rogers et al (2022) “Temporal patterns in sediment, carbon, and nutrient burial in ponds associated with changing agricultural tillage” published in Biogeochemistry (DOI: 10.1007/s10533-022-00916-w). We sampled three retention ponds in southwest Ohio in 2019 to compare sediment, carbon, nitrogen, and phosphorous burial rates to those calculated in 2006 to see the effect a watershed-wide shift to conservation tillage and to estimate the value of the ecosystem services these ponds provide via sequestration. Two methods were used to calculate burial rates: simple mean and spatially explicit. All datasets use simple mean except for the data set named “Spatially Explicit Sediment C N P Burial in SW OH Retention Ponds 2019”, which uses the spatially explicit method. For more information, please refer to our paper.
A Comparison of Recreational and Survey-Grade Side-Scan Sonar Systems in Mapping Reservoir Fish Habitat in 3 Southwest Ohio Reservoirs
Littoral zone aquatic habitat is thought to play an important driver of aquatic organism population dynamics, but historically has been difficult to obtain at the whole waterbody scale because it is costly and time-consuming to collect with traditional aquatic habitat sampling methods. Here we used side-scan sonar to quantification of habitat features over large areas using two levels of equipment: recreational (consumer-grade) and professional (survey-grade). Our goal was to compare performance of the different side-scan sonars by analyzing their ability to map shoreline habitat features (wood, vegetation, and substrate) in three southwest Ohio reservoirs that contain the range of habitat features of interest to fisheries biologists. We used a low-cost Lowrance Active Imaging 3-in-1 system (≈$2,000 USD) recreational sonar and an EdgeTech 6205 system (≈$150,000 USD) survey-grade sonar to collect imagery along the shoreline of three reservoirs in Ohio. Using imagery from each system, We manually delineated patches of submerged woody debris, standing timber, aquatic vegetation, and benthic substrate in GIS. We also compared the size of uniquely identifiable submerged wood from paired imagery to understand potential biases between the systems.
Satellite derived chlorophyll-a of the Ohio and Illinois Rivers (CHOIR), 1984-2022
Chlorophyll-a is a vital water quality parameter used to quantify concentrations of algal biomass in freshwater systems. However, insufficient field data in the Ohio River Basin has resulted in limited understanding of the development of algal blooms. We built a 38-year (1984 – 2022) dataset of satellite derived chlorophyll-a predictions to support research efforts which aim to quantify the frequency and intensity of river algal blooms. We developed our model by leveraging coinciding in situ chlorophyll-a data and surface reflectance extracted from Landsat Collection 2 Tier 1, referred to as matchups. Matchups were used to train and test our machine learning model. We also extracted Landsat surface reflectance over 6,116 NHD river reaches using similar methods. We then applied our model to this reach-level data to create a comprehensive dataset of chlorophyll-a predictions. This dataset includes the following files: 1) data used to train and test the model (matchups), 2) the model infrastructure, 3) satellite derived chlorophyll-a predictions aggregated over NHD river reaches, and 4) a shapefile of NHD river reaches.
Chlorophyll data from experiments testing for nitrogen, phosphorus, and thiamine limitation of phytoplankton in 39 Ohio lakes of varying trophic status during the growing seasons (April – October) of 2008–2009
Although nitrogen and phosphorus deficiency of algal blooms have been the focus of substantial attention, organic nutrients can limit algal growth in aquatic systems. Growing evidence indicates thiamine (vitamin B1) can influence the community of primary producers in marine systems, but comparatively little is known about the effect of thiamine on freshwater algal productivity. We conducted 106 nutrient deficiency experiments with water from 39 Ohio lakes of varying trophic status during the growing seasons (April – October) of 2008–2009. Specifically, we tested the response of phytoplankton biomass (as chlorophyll a, chl-a) relative to controls to added nitrogen (N), phosphorus (P), thiamine (Th), or combinations of N+P and N+P+Th in integrated surface water collected from the inflow and outflow of each lake. The data presented here show the average chl-a of two replicate samples of each treatment (control, N, P, Th, N+P, N+P+Th), ratio of treatment/control response, and growth response ratio as ln(treatment chl-a/control chl-a). Each entry also includes lake surface water pH at time of collection and the initial chl-a concentration at time of experiment start.
Witness Tree Database for 4 Survey Districts in Southeastern Ohio, Level 0
This database is a collation and digitization of witness tree attributes at PLS corners in four survey districts in southeastern Ohio: Old Seven Ranges, North of the Seven Ranges, United States Military Tract, Ohio Land Company.
Supplementary data for "ENGINEERED ADAPTATION MECHANISMS BETWEEN MARINE AND FRESHWATER ENVIRONMENTS IN FISH AFTER THE FLOOD" for the ICC 2023 in Cedarville, Ohio
<p>Supplementary data for "ENGINEERED ADAPTATION MECHANISMS BETWEEN MARINE AND FRESHWATER ENVIRONMENTS IN FISH AFTER THE FLOOD" for the ICC 2023 in Cedarville, Ohio.</p> <p>These include FishBase annotation, mtDNA sequence similarity matrixes, clustering, and statistics for nine fish orders:</p> <p>1. Acipenseriformes</p> <p>2. Angulliformes</p> <p>3. Beloniformes</p> <p>4. Characiformes</p> <p>5. Clupeiformes</p> <p>6. Cyprinodontiformes</p> <p>7. Elasmobranchii</p> <p>8. Pleuronectiformes</p> <p>9. Salmoniformes</p>
Dataset: Ohio Valley Banc Corp. (OVBC) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Fig. 1 in Predicting Baylisascaris procyonis roundworm prevalence, presence and abundance in raccoons (Procyon lotor) of southwestern Ohio using landscape features
Fig. 1. Map of the townships of Greene and Clark Counties Ohio. The data represent the proportion of raccoons from an individual township that had raccoon roundworms when necropsied. This map also demonstrates the mean patch size, proportion of landscape modified by urbanization and the proportion of landscape modified by agriculture for the nine townships.
Linked collectors and determiners for: Ohio State Acarology Laboratory (OSAL), Ohio State University.
Natural history specimen data linked to collectors and determiners held within, "Ohio State Acarology Laboratory (OSAL), Ohio State University". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/96b54e8c-f762-11e1-a439-00145eb45e9a">https://bionomia.net/dataset/96b54e8c-f762-11e1-a439-00145eb45e9a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/96b54e8c-f762-11e1-a439-00145eb45e9a">https://gbif.org/dataset/96b54e8c-f762-11e1-a439-00145eb45e9a</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Ohio State University Tetrapod Division - Bird Collection (OSUM).
Natural history specimen data linked to collectors and determiners held within, "Ohio State University Tetrapod Division - Bird Collection (OSUM)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/91aa5e23-9cad-4751-86e0-241da77d7407">https://bionomia.net/dataset/91aa5e23-9cad-4751-86e0-241da77d7407</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/91aa5e23-9cad-4751-86e0-241da77d7407">https://gbif.org/dataset/91aa5e23-9cad-4751-86e0-241da77d7407</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: C.A. Triplehorn Insect Collection (OSUC), Ohio State University.
Natural history specimen data linked to collectors and determiners held within, "C.A. Triplehorn Insect Collection (OSUC), Ohio State University". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/84ab7b76-f762-11e1-a439-00145eb45e9a">https://bionomia.net/dataset/84ab7b76-f762-11e1-a439-00145eb45e9a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/84ab7b76-f762-11e1-a439-00145eb45e9a">https://gbif.org/dataset/84ab7b76-f762-11e1-a439-00145eb45e9a</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Ohio State University Tetrapod Division - Mammal Collection (OSUM).
Natural history specimen data linked to collectors and determiners held within, "Ohio State University Tetrapod Division - Mammal Collection (OSUM)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/78dcfcbd-03c4-4d47-8618-830aac6f2ee5">https://bionomia.net/dataset/78dcfcbd-03c4-4d47-8618-830aac6f2ee5</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/78dcfcbd-03c4-4d47-8618-830aac6f2ee5">https://gbif.org/dataset/78dcfcbd-03c4-4d47-8618-830aac6f2ee5</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Ohio State University Tetrapod Division - Reptile Collection (OSUM).
Natural history specimen data linked to collectors and determiners held within, "Ohio State University Tetrapod Division - Reptile Collection (OSUM)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/51fa0155-a545-4154-ac20-b89dbb2c312b">https://bionomia.net/dataset/51fa0155-a545-4154-ac20-b89dbb2c312b</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/51fa0155-a545-4154-ac20-b89dbb2c312b">https://gbif.org/dataset/51fa0155-a545-4154-ac20-b89dbb2c312b</a>. Formatted as a Frictionless Data package.
ScienceDex guides
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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.