Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,606
datasets available to search
ShareScore release 0.9.0
Dataset results
1,606 results for “Prairie”
ASR01 Short-term assessment of effects of burning on infiltration, runoff, and sediment and nutrient loss on Tallgrass Prairie using rainfall simulation, 1989
Rainfall simulation and overland flow experiments were performed on four plots at a single site on Konza from May to August, 1989. Two plots were treated with a late spring burn and two plots were left unburned. Five simulations were performed on burned plots and three simulatons on unburned plots. Each simulation consisted of a “dry run” followed 24 hours later by a 'wet run'. The dry run consisted of rainfall applied at an intesity of approximately 60 mm/hour. The wet run was the same as a dry run, except when the rainfall was complete, overland flow was applied directly at the top of the plots to simulate run off coming from upslope. Measurements taken include overland flow velocity, water application rate, runoff, hydrograph, water flow depth, sediment content, nitrogen and phosphorus content and percent ground cover (See A.B. Duell, Effects of burning on infiltration, overland flow, and sediment loss on tallgrass prairie, M.S. thesis, Kansas State University, 82pp. for further details).
PBG06 Cattle grazing and cattle performance in the Patch-Burn Grazing experiment at Konza Prairie
PBG datasets are associated with a long-term, large-scale study that is addressing the effects of fire-grazing interactions in the context of a Patch-Burn Grazing management system designed to promote grassland heterogeneity. Effects of patch-burn grazing management on plant and animal diversity and the nature and variety of wildlife habitat are being assessed in two replicate management units, each consisting of three pastures (watersheds) designated C03A/C03B/C03C and C3SA/C3SB/C3SC. In each patch-burn grazing unit, one watershed is burned and two that are left unburned in a given year. The burning treatments are rotated annually so that each pasture is burned every third year. Each patch-burn grazing unit is paired with an annually-burned pasture for comparison with traditional grazing systems (C01A and C1SB). All grazing units are stocked with cow/calf pairs from approximately 1 May until 1 Oct at a stocking density equal to 3.2 ha per cow/calf. To examine the impact of patch burning and grazing in all 8 units, we monitor changes in plant species composition, residual biomass, grassland bird populations, insect populations, small mammal populations, soil nutrients, and stream water quality1 (1C3SA/C3SB/C3SC unit only). The KSU Department of Animal Science monitors cattle performance, including weight gain and body condition to assess the economic feasibility of using patch-burn management on a widespread basis. This data set focuses on monitoring (1) the dynamics of cattle grazing on each of two sets of three pastures burned each year on a rotating basis and (2) cattle performance including cow weight gain, body condition, and reproductive performance and calf weight gains.
PBG07 Grasshopper species abundances in the Patch-Burn Grazing experiment at Konza Prairie
‘PBG’ datasets are associated with a long-term, large-scale study that is addressing the effects of fire-grazing interactions in the context of a Patch-Burn Grazing management system designed to promote grassland heterogeneity. Effects of patch-burn grazing management on plant and animal diversity and the nature and variety of wildlife habitat are being assessed in two replicate management units, each consisting of three pastures (watersheds) designated C03A/C03B/C03C and C3SA/C3SB/C3SC. In each patch-burn grazing unit, one watershed is burned and two that are left unburned in a given year. The burning treatments are rotated annually so that each pasture is burned every third year. Each patch-burn grazing unit is paired with an annually-burned pasture for comparison with traditional grazing systems (C01A and C1SB). All grazing units are stocked with cow/calf pairs from approximately 1 May until 1 Oct at a stocking density equal to 3.2 ha per cow/calf. To examine the impact of patch burning and grazing in all 8 units, we monitor changes in plant species composition, residual biomass, grassland bird populations, insect populations, small mammal populations, soil nutrients, and stream water quality1(1C3SA/C3SB/C3SC unit only). The KSU Department of Animal Science monitors cattle performance, including weight gain and body condition to assess the economic feasibility of using patch-burn management on a widespread basis.
PBG08 Grasshopper density survey in the Patch-Burn Grazing experiment at Konza Prairie
PBG datasets are associated with a long-term, large-scale study that is addressing the effects of fire-grazing interactions in the context of a Patch-Burn Grazing management system designed to promote grassland heterogeneity. Effects of patch-burn grazing management on plant and animal diversity and the nature and variety of wildlife habitat are being assessed in two replicate management units, each consisting of three pastures (watersheds) designated C03A/C03B/C03C and C3SA/C3SB/C3SC. In each patch-burn grazing unit, one watershed is burned and two that are left unburned in a given year. The burning treatments are rotated annually so that each pasture is burned every third year. Each patch-burn grazing unit is paired with an annually-burned pasture for comparison with traditional grazing systems (C01A and C1SB). All grazing units are stocked with cow/calf pairs from approximately 1 May until 1 Oct at a stocking density equal to 3.2 ha per cow/calf. To examine the impact of patch burning and grazing in all 8 units, we monitor changes in plant species composition, residual biomass, grassland bird populations, insect populations, small mammal populations, soil nutrients, and stream water quality1 (1C3SA/C3SB/C3SC unit only). The KSU Department of Animal Science monitors cattle performance, including weight gain and body condition to assess the economic feasibility of using patch-burn management on a widespread basis. This data set focuses on measuring grasshopper density using ring count method (Onsager 1977*) at watersheds C03A, C03B, C03C, C01A, C3SA, C3SB, C3SC, and C01B. Grazing intensity is estimated (Joern 2005) at each site at time of density measurements to model how grasshopper populations respond to grazing.
PBG10 Soil physical and chemical characteristics in the Patch-Burn Grazing experiment at Konza Prairie
PBG datasets are associated with a long-term, large-scale study that is addressing the effects of fire-grazing interactions in the context of a Patch-Burn Grazing management system designed to promote grassland heterogeneity. Effects of patch-burn grazing management on plant and animal diversity and the nature and variety of wildlife habitat are being assessed in two replicate management units, each consisting of three pastures (watersheds) designated C03A/C03B/C03C and C3SA/C3SB/C3SC. In each patch-burn grazing unit, one watershed is burned and two that are left unburned in a given year. The burning treatments are rotated annually so that each pasture is burned every third year. Each patch-burn grazing unit is paired with an annually-burned pasture for comparison with traditional grazing systems (C01A and C1SB). All grazing units are stocked with cow/calf pairs from approximately 1 May until 1 Oct at a stocking density equal to 3.2 ha per cow/calf. To examine the impact of patch burning and grazing in all 8 units, we monitor changes in plant species composition, residual biomass, grassland bird populations, insect populations, small mammal populations, soil nutrients, and stream water quality1 (1C3SA/C3SB/C3SC unit only). The KSU Department of Animal Science monitors cattle performance, including weight gain and body condition to assess the economic feasibility of using patch-burn management on a widespread basis. This data set focuses on measuring bulk density, soil organic matter, pH, cation exchange capacity, soil cations (Ca++, Mg++, Na+), phosphorous and total Kjeldahl nitrogen of soils at the vegetation transects in C3SA, C3SB, C3SC. C1SB, C3A, C3B, C3C, and C1A.
PBG11 Stream water chemistry for the Shane Creek drainage basin in the Patch-Burn Grazing experiment at Konza Prairie
PBG datasets are associated with a long-term, large-scale study that is addressing the effects of fire-grazing interactions in the context of a Patch-Burn Grazing management system designed to promote grassland heterogeneity. Effects of patch-burn grazing management on plant and animal diversity and the nature and variety of wildlife habitat are being assessed in two replicate management units, each consisting of three pastures (watersheds) designated C03A/C03B/C03C and C3SA/C3SB/C3SC. In each patch-burn grazing unit, one watershed is burned and two that are left unburned in a given year. The burning treatments are rotated annually so that each pasture is burned every third year. Each patch-burn grazing unit is paired with an annually-burned pasture for comparison with traditional grazing systems (C01A and C1SB). All grazing units are stocked with cow/calf pairs from approximately 1 May until 1 Oct at a stocking density equal to 3.2 ha per cow/calf. To examine the impact of patch burning and grazing in all 8 units, we monitor changes in plant species composition, residual biomass, grassland bird populations, insect populations, small mammal populations, soil nutrients, and stream water quality1 (1C3SA/C3SB/C3SC unit only). The KSU Department of Animal Science monitors cattle performance, including weight gain and body condition to assess the economic feasibility of using patch-burn management on a widespread basis. This data set focuses on measuring Nitrate, ammonium, total N, soluble reactive P, total P, and dissolved organic C in four streams draining watersheds with 1 (N01B), 2 (N02B), 4 (N04D), and 20 (N20B) year target burn frequencies.
PPL01 Konza prairie long-term phosphorus plots experiment
Increased nutrient inputs is one of many global change factors predicted to affect the composition and ecosystem function of plant communities. In general, nitrogen deposition decreases diversity and increases productivity. The effects of phosphorus addition have received less attention, however, and the interactive effect of both nutrients is likely to exacerbate diversity loss over time. Here we addressed whether chronic nutrient additions changed community structure and ecosystem productivity of a native tallgrass prairie. This study took place in an ungrazed watershed that is burned every two years. Two N treatments, 0 and 10 g m-2, and four P treatments, 0, 2.5, 5 and 10 g m-2 were crossed in a fully factorial experimental design. The experiment was initiated in 2002 and starting in 2003 nutrients were added at the beginning of each growing season. Plant species composition was surveyed both in the spring and late summer each year, and aboveground biomass was harvested at the end of each summer to estimate aboveground net primary productivity (ANPP).
CEE01 The Climate Extremes Experiment (CEE): Assessing ecosystem resistance and resilience to repeated climate extremes at Konza Prairie
Climate extremes, such as drought, are increasing in frequency and intensity, and the ecological consequences of these extreme events can be substantial and widespread. Yet, little is known about the factors that determine recovery (or resilience) of ecosystem function post-drought. Such knowledge is particularly important because post-drought recovery periods can be protracted depending on drought legacy effects (e.g., loss key plant populations, altered community structure and/or biogeochemical processes). These drought legacies may alter ecosystem function for many years post-drought and may impact future sensitivity (both resistance and resilience) to climate extremes. With forecasts of more frequent drought, there is an imperative to understand whether and how post-drought legacies will affect ecosystem response to future drought events. To address this knowledge gap, we experimentally imposed over an eight year period two extreme growing season droughts, each two years in duration followed by a two-year recovery period, in annually burned tallgrass prairie.
AST01 Soil temperature measured in burned, burned-clipped, and unburned plots at Konza Prairie
Soil temperature was measured using temperature probes and dataloggers at selected depths in small plots tht were either burned annually, burned and clipped to remove aboveground biomass, or left unburned. Raw data was summarized into hourly readings and daily minimum, maximum, and mean temperatures.
CFC01 Kings Creek long-term fish and crayfish community sampling at Konza Prairie
Prairie stream fish communities have been monitored seasonally at multiple sites within the Kings Creek watershed since 1995. The objective of this sampling is to evaluate how these communities respond to seasonal and annual variation in environmental conditions. Specifically, we are interesting in testing the resistance and resilience of stream communities in response to flood and drought disturbances. One site in a downstream perennial reach of the watershed has been sampled since 1995. Five sites have been sampled in smaller tributaries in the watershed, two were discontinued due to often lack of flow, two have been sampled since 1995 and one was added in 2008. Sampling is conducted with backpack electrofishing with at least one person dip netting. At each site, multiple habitats (pools and riffles) are sampled. Length of all fish and crayfish are measured.
KKE01 The Konza-Kruger Experiment: A cross-continental fire and grazing experiment at Konza Prairie
For more than a decade, we have compared responses of mesic (subhumid) savanna grasslands (>500 mm MAP in the tropics and >600 mm MAP outside the tropics) in North America and South Africa to alterations in both fire and grazing regimes. The long-term, comparative experiment that forms the centerpiece of this cross-continental research program is located in tallgrass prairie at the Konza Prairie Biological Station (Kansas, USA) and in knob-thorn marula savanna at the Kruger National Park (Limpopo and Mpumalanga provinces, South Africa). We refer to this study as the Konza-Kruger (K-K) Experiment. At both sites, we have been manipulating grazing by removing all large herbivores (>5 kg) from research plots with permanent exclosures (each with a paired plot that grazers can freely access). These exclosures were established in replicated fire frequency experiments ongoing at each site (treatments range from >25-50 yrs of annual burning, burning every 3-4 yrs, or complete fire exclusion).
RCS01 Recovery and relative influence of root, microbial, and structural properties of soil on physically sequestered carbon stocks in restored grassland at Konza Prairie
Managing soil to sequester C can help mitigate increasing CO2 in the atmosphere. To maximize this ecosystem service, more knowledge of factors influencing C sequestration is needed. The objectives of this study were to (i) quantify recovery of the roots, microbial biomass and composition, and soil structure across a chronosequence of grassland restorations and (ii) use a structural equation model to develop a data-based hypothesis on the relative influence of physical and biological soil properties on the soil C aggregate fraction diagnostic of sequestered C. We hypothesized measured variables would recover with restoration age. Belowground plant biomass and tissue quality (C/N ratio), soil microbial biomass C, phospholipid fatty acid (PLFA) concentrations, soil structure, and soil C stocks in the bulk soil and each aggregate fraction were quantified from a cultivated field, prairies restored for 1 to 35-yr (n = 6), and a never-cultivated (native) prairie. Root biomass, microbial biomass C, arbuscular mycorrhizal fungi (AMF) PLFA biomass across the chronosequence increase to resemble native prairie following 35 yr of restoration. Many aspects of soil structure (i.e., bulk density, proportional mass of aggre- gate fractions, and aggregate mean weighted diameter) and the distribution C among soil fractions, including C in the micro-within-macro aggregate fraction (sequestered C), also became representative of native prairie within 35 yr of restoration. Total soil C stock and physically protected C increased at a similar rate (23 and 27 g C m-2 yr-1) respectively, across the chronosequence. After 35 yr of restoration, 50% of the total C pool was physically protected. The structural equation modeling developed by these data hypothesizes that microbial biomass C and AMF biomass (microbial composition) have the strongest causal influence on physically protected C. This model needs to be tested using independent sites to achieve greater inference.
ESM01 Fire and grazing modulate the structure and resistance of plant-floral visitor networks in a tallgrass prairie
Data from the study: Welti, E.A.R. and Joern, A. 2017. Fire and Grazing modulate the structure and resistance of plant-floral visitor networks in a tallgrass prairie. Oecologia 186: 447-458. EMS011 dataset contains counts of blooming inflorescences of plant species on 12 Konza watersheds in June-July of 2014; ESM012 dataset contains associations between flower-visiting insects and insect-pollinated flowering plants on 12 Konza watersheds collected in May-July of 2014; ESM013 dataset describes insects belonging to the orders of Coleoptera, Diptera, Lepidoptera and Hymenoptera collected in pantrap transects on 12 Konza watersheds collected in June - July of 2014.
PPS01 Konza prairie plant species list
The dataset (Key for Plant Species Codes in Konza Prairie Community Composition Datasets) contains a numeric code for each vascular plant species that has been recorded in any Konza Prairie LTER plant community composition dataset (e.g. PVC02, PBG01, WAT01, BGPVC). Each code designates a vasular plant taxon (species level). Variables include: family, genus, specific epithet, lifespan, growth form, origin, photosynthetic pathway (for grasses).
GIS68 GIS Coverages of Konza Prairie Research Experiments in 2020
These data show locations for some experiments at Konza Prairie including: Chronic Addition of Nitrogen Gradient Experiment (ChANGE), Ghost Fire, Shrub Rainfall Manipulation Plots (ShRaMPs), sampling locations for ingrowth cores collected as part of the ShRaMPs experiment, Climate Extremes Experiment, Drought-Net, the Experimental Streams Experiment, the Nutrient Network Experiment, Phosphorous Plots experiment, the Vert-Invert experiment, and restoration areas.GIS680 defines the locations where the ChANGE experiment occurs on Konza Prairie. These data are to be used in conjunction with the NGE01 dataset.GIS681 defines the locations where the Ghost Fire experiment occurs on Konza Prairie. These data are to be used in conjunction with the GFE01.GIS682 defines locations where the ShRaMPs shelters occur on Konza Prairie.GIS683 defines locations where ingrowth cores were installed as part of the ShRaMPs experiment.GIS684 defines the locations where the Climate Extremes experiment occurs on Konza Prairie. These data are to be used in conjunction with the CEE01 dataset.GIS685 defines the locations where the Drought-Net experiment occurs on Konza Prairie.GIS686 defines the site where the Experimental Streams experiments occur on Konza Prairie.GIS687 defines the locations where the Nutrient Network experiment occurs on Konza Prairie. These data are to be used in conjunction with the NUT01 dataset.GIS688 defines the locations where the Phosphorous Plots experiment occurs on Konza Prairie. These data are to be used in conjunction with the PPL01 dataset.GIS689 defines the locations where the Vert-Invert experiment occurs on Konza Prairie. These data are to be used in conjunction with the VIR01 dataset.GIS690 contains locations of restoration areas. These data are to be used in conjunction with the HRE01, SPR01, and PRP01 datasets. These data are available to download as zipped shapefiles (.zip), and compressed Google Earth KML layers (.kmz).
GIS70 Konza Prairie Woody Plant Mapping in Core Watersheds (1D, 20B, and 4B) in 2019
This dataset contains the point and polygon boundaries of shrubs and trees mapped in watersheds 1D, 4B, and 20B from May to August 2019. Datatype one (GIS700) defines the point locations of all trees mapped in these watersheds. Datatype two (GIS701) defines the point locations of all shrubs less than one meter wide in these watersheds. Datatype three (GIS702) defines the boundaries of select shrub species greater than one meter wide in these watersheds. These data are available to download as zipped shapefiles (.zip), and compressed Google Earth KML layers (.kmz).
SMR01 Konza Prairie grassland soil microbial responses to long-term management of N availability
Anthropogenic actions have significantly increased biological nitrogen (N) availability on a global scale. In tallgrass prairies, this phenomenon is exacerbated by land management changes, such as fire suppression. Historically, tallgrass prairie fire removed N through volatilization, but fire suppression has contributed to increased soil N availability as well as woody encroachment. Because soil microbes respond to N availability and plant growth, these changes may alter microbial composition and important microbially-mediated functions. Grassland management affects the soil environment on multiple time scales including short (fertilization or fire event), seasonal (growing vs. non-growing season), and long-term (decadal plant turnover and nutrient accumulation), therefore my goal was to understand community variability at different time scales affecting the population and community dynamics of soil microbes. I predicted soil microbes would be sensitive to environmental changes at all time scales, seasonal variation would reflect increased plant rhizodeposit-supported populations during summer and decomposers during winter, and long-term fire suppression and chronic fertilization would drive soil microbial community turnover associated with accumulation of plant litter and N. Soil microbial responses to short-term fire/fertilization events were minimal, while microbial population sizes fluctuate seasonally and synchronously, and microbial community composition varied more with management history than at shorter time scales. Bacterial populations increased 10x during growing-season plant rhizodeposition, while fungal populations were less dynamic, but decreased in fall, possibly reflecting a shift to subsistence on soil organic matter. In contrast, microbial community composition was seasonally stable, but distinct between long-term management treatments, which may indicate accumulation of niche-defining plant or soil properties over decades. Prokaryotic communities
PEC01 Elemental chemistry of plant tissue collected for the Konza LTER aboveground plant biomass on Konza Prairie core watersheds
Dataset contains elemental chemistry (N, C, Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, P, Pb, S, Si, Ti, V, and Zn) of dried and ground, end-of-season, above-ground live tissue from grasses, forbs, and woody plants collected on Tully soils in the watersheds 001d, 004b, and 020b. N and C are provided as percentages; all other elements are provided as parts per million (ppm). Within plant growth type (grasses, forbs, and woody) and year, elemental concentrations were measured on one pooled (2g) sample containing four (0.5g) subsamples of ground and dried plant tissue (subsamples included from recent years were named TA2, TB2, TC2, and TD2; subsamples included from older years were named: TA2, TA4, TB2, TB4). For more information on plant sampling see the description of the Konza LTER PAB01 aboveground plant biomass dataset (Blair & Nippert). Elemental chemistry was analyzed using combustion analysis for percent N and using hot plate digestion and inductively coupled plasma atomic emission spectroscopy (ICP-AES) for concentrations of metals (ppm) at the Cornell Nutrient Analysis Laboratory (https://cnal.cals.cornell.edu/).
SIC01 Isotopic composition of select archived soil cores from Konza Prairie
The concentration and isotopic composition of soil carbon and nitrogen were measured from select archived soil cores originally collected for the NSC01 dataset using an isotope ratio mass spectrometer coupled with an elemental analyzer. These soil cores were collected from the lowlands (25 cm depth) of four experimental watersheds in 1982, 1987, 2002, 2010, and 2015. The four experimental watersheds are 001d, n01b, 020b, and n20b.
CME01 The Consumer Size Manipulation Experiment (ConSME) at Konza Prairie
Herbivores of varying size classes exist with the grassland biome (large mammals, small mammals, insects), however their independent and interactive effects on grassland plant species composition and function are understudied. Here we aim to tease apart the effects of three size classes of herbivores within the Konza Prairie system, and whether these effects vary across fire regimes.
ScienceDex guides
Understand access before you commit
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.