Estimated evapotranspiration from a hypothetical short grass with a height of 0.12 m, a surface resistance of 70 s m-1, and an albedo of 0.23 (no water stress). Dataset contains daily total estimated evapotranspiration.
Dates of records of occurrence for all bird species reported on Konza Prairie.
Dates by species of documented records of breeding - either nests or dependent, fledged young - with contents of nest, nest placement information and location on Konza Prairie recorded by grid square.
Konza Prairie Terrestrial Arthropods Species List. This species list has been modified since 1977, last modified by Ellen Welti and Anthony Joern in 2014.
Litterfall is collected monthly (more frequently during peak litterfall in October and November) at permanent sampling sites in the mixed deciduous gallery forest located along the lower reaches of Kings Creek at the Konza Prairie Biological Station. Thirty litterfall traps, 50 x 50 cm (.25 m2) are located along the north fork of Kings Creek, and two are located on the south fork of Kings Creek. The north fork boxes are numbered 31 to 60 and the south fork boxes are numbered 1 and 2.
The experiment is a randomized complete block design with four whole plot hetereogeneity treatments replicated within each of four blocks (n=16 whole plots). The whole plot treatments were created using different combinations of soil depth and nutrient manipulations. The control plots contained no depth or nutrient manipulations. The 'maximum hetereogeneity' plots contained three 2 m x 8 m vertical strips assigned to ambient, enriched and reduced N treatments and four 2 m x 6 m horizontal strips assigned to deep and shallow soil to result in six treatment combinations.
The objectives of this project are to quantify the seasonably variable timing among meteoric precipitation, groundwater recharge, and groundwater temperature. Hypotheses are: 1. Because of the karst-like characteristics of the aquifers in N04d (and by extension, the entire region), recharge will be rapid during moderately large precipitation events where fractures are enlarged by dissolution and therefore highly conductive, except during the most active part of the growing season. 2.
Long-term monitoring of bird presence is performed on Konza Prairie. The purpose was to determine bird species phenology of occurrence on entire Konza Prairie. Data on the presence, including documented nesting, of all bird species is recorded weekly in five-year periods e.g. 1980-1984, 1985-1989, 1990-1994.
Frequent burning is a common land practice in many grasslands worldwide, and this land use strategy has large impacts on a wide variety of ecosystem functions and services. Fire in tallgrass prairie, in the absence of grazing, alters plant community composition, decreases richness, and increases plant production. Proposed mechanisms for the changes in community composition and function are that fire decreases N availability (through volatilization) and removes litter (thereby increasing light availability and decreasing soil moisture).
These data depict the elevation features of Konza Prairie. Record type 1 is a 2 meter resolution digital elevation model (DEM) of Konza Prairie, generated from 2006 LiDAR DEM data collected to standard USGS specifications (GIS200). Record type 3 is a 2010 10 meter (1/3 arc second) resolution National Elevation Dataset (NED) DEM of Konza Prairie (GIS202). Record type 4 is a 10 meter resolution NED DEM of Konza Prairie with a modified 3 kilometer buffer (GIS203). Record type 5 is a USGS topographic map of Konza Prairie (GIS204).
This dataset contains the boundary polygon of the Konza Prairie Biological Station (KPBS). Data type one (GIS000) defines the original KPBS boundary used from 1977 until 1982, type two contains the extended boundary from 1982 (GIS001) to 1997, and type three (GIS002) contains the boundary since 1997. These data are available as zipped (.zip) shapefiles (.shp).
This dataset defines the internal boundaries of the Konza Prairie Biological Station (KPBS). Data type one (GIS010) is a record of all fenced areas on KPBS with GIS011 providing locations for all gates and type of gate (exterior, bison, and cattle). Data type three (GIS012) represents various large-scale research areas on Konza including bison grazed, cattle grazed, fire reversal, etc. These data are available as zipped (.zip) shapefiles (.shp).
This dataset defines the experimental watershed treatments for the Konza Prairie Biological Station (KPBS). These treatments have changed over time to represent changes in both physical boundaries as well as changes in watershed treatments.
These data are available to download as zipped shapefiles (.zip), compressed Google Earth KML layers (.kmz).
This dataset contains a comprehensive record of burn histories for the Konza Prairie Biological Station (KPBS) dating from 1972. Burn history data contains date burned, area burned and type of treatment (prescribed burns, complete and partial burns, and wildfires). These data are available as zipped (.zip) shapefiles (.shp).
This Coverage Contains the Locations of Streams (GIS210) and Waterbodies (GIS211) within the Konza Prairie Biological Station.
These data are available to download as zipped shapefiles (.zip), compressed Google Earth KML layers (.kmz), and associated EML metadata (.xml).
The Konza Prairie soils dataset is derived from the USDA NRCS SSURGO soils definitions for Riley and Geary Counties (variant ca. 2012; soildatamart.nrcs.usda.gov/). The coverage contains MUSYM and Soil Names that correspond to the code. Additional and current SSURGO data is available from (soildatamart.nrcs.usda.gov/SSURGOMetadata.aspx) Associated metadata derived from NRCS SSURGO Metadata for: Riley County SSURGO Data - soildatamart.nrcs.usda.gov/Metadata.aspx?Survey=KS161&UseState=KS Geary County SSURGO Data -soildatamart.nrcs.usda.gov/Metadata.aspx?Survey=KS061&UseState=KS.
This dataset defines the roads in and around the Konza Prairie Biological Station (KPBS). The road data shows locations of Konza maintained and county/state/federal access roads as well as defining gravel or paved.
These data are available to download as zipped shapefiles (.zip), compressed Google Earth KML layers (.kmz).
This dataset defines the nature trails found at Konza Prairie Biological Station (KPBS). The trails data shows locations of the different Konza maintained walking trails including leg distances and loop names.
These data are available to download as zipped shapefiles (.zip), compressed Google Earth KML layers (.kmz).
This dataset contains a comprehensive record of supplemental burns, wildfires, wildfire cleanup burns for the Konza Prairie Biological Station (KPBS) dating from 1972. Burn history data contains date burned, area burned and type of treatment (wildfires, wildfire cleanup, and supplemental burns). Burn histories for planned, prescribed burns are available in dataset GIS05.
These data are available to download as zipped shapefiles (.zip), and compressed Google Earth KML layers (.kmz).
This dataset defines the permanent buildings located on the Konza Prairie Biological Station (KBPS). The data include building names and addresses. These data are available as zipped (.zip) shapefiles (.shp).
These data show sample locations for various abiotic data collected on Konza Prairie (rain gauges, soil moisture, and stream data). Included in these data are the locations for 12 rain gauges (GIS300) on Konza Prairie. The Konza headquarters weather station formerly consisted of two gauges which were operated year-round. The Konza headquarters weather station currently consists of one Otto-Pluvio2 gauge which is operated year-round. The remaining Konza-operated gauges run from April 1 to November 1. These data are to be used in conjunction with the APT01 (precipitation) dataset.
These data show the locations of research conducted at the below ground plots near Konza Headquarters. Record type 1 (GIS350) describes the 64 belowground plots receiving a variety of nutrient, burn, and mowing treatments. Data for BMS01, BMS02, and BNS01 are collected on these plots. Record type 6 (GIS355) describes the locations of the Micro-Rhizotrons. Two spatial datasets lie on the belowground plots, but are classified separately. These are the Lysimeters on belowground plots (GIS455) and Aboveground biomass on belowground plots (GIS505) datasets.
These data show the sampling locations for the consumer datasets at Konza Prairie. GIS400 defines the starting points for sweep samples of grasshoppers across Konza Prairie. These data may be used in conjunction with the sweep sample datasets (CGR02). GIS401 defines the starting points for sweep samples of grasshoppers across Konza Prairie, focusing on grazing impact. These data may be used in conjunction with the sweep sample datasets (CGR02Z). GIS405 defines the trap locations for small mammal sampling across Konza Prairie. These data may be used in conjunction with CSM0X.
These data show the sample locations for soil bulk density and chemical characteristics along LTER vegetation plots. This dataset contains the transect lines (GIS450) and sample locations(GIS451) at which the soil cores are sampled. These data may be used in conjunction with the Soil Chemistry and Bulk Density (NSC01) datasets. GIS455 contains the locations of the lysimeters used to measure soil water chemistry on the belowground plots. These data may be used in conjunction with the NBS01 dataset. GIS460 contains the locations of the bulk precipitation collectors on Konza Prairie.
These data show locations of samples and research areas at Konza that do not fit under our standard classifications. GIS 600 contains the locations of the Hulbert plots on Konza Prairie. GIS605 contains locations for rainfall shelters, ramps, experimental streams, restoration plots, the weather station, grasshopper cages, the climate extremes project. Currently no associated LTER datasets exist for these locations. GIS 610 provides a record of the historic Konza gridded location system. Older datasets may reference these locations with a column letter and row number.
These data show the sample locations for datasets pertaining to primary production at Konza Prairie. These data reference various treatments across Konza including varying burn frequencies, belowground plots, patch burn, exclosures, etc.Record type one (GIS500) contains sample locations for estimated standing crop biomass in various burning-grazing treatments (PABXX).
These data show the components of the irrigation system near Konza Prairie HQ. Record types 1, 2, 3 and 4 demarcate the locations of the study plots heads (GIS550), transect lines (GIS551), irrigation lines (GIS552), and irrigation line joints (GIS553). Record types 4 and 5 describe the location of the storage piles (GIS554) and the irrigation reservoir (GIS555). This data may be used in conjunction with the Irrigation Transect Studies (WATXX) data.
Annual aboveground net primary productivity (ANPP) from the Sequential Prairie Restoration Experiment at the Konza Prairie Long-Term Ecological Research site in Manhattan, KS USA. The data (SRP011) include ANPP from the first three years of restoration in each of three restoration sequences initiated in different years. Data correspond to subplot and whole-plot analyses.
We manipulated key resources that influence plant diversity in tallgrass prairie (i.e., soil depth and nitrogen availability) to increase environmental heterogeneity prior to sowing native prairie species into a former agricultural field.
Recent models suggest that herbivores optimize nutrient intake by selecting patches of low to intermediate vegetation biomass. We assessed the application of this hypothesis to plains bison (Bison bison) in an experimental grassland managed with fire by estimating daily rates of nutrient intake in relation to grass biomass and by measuring patch selection in experimental watersheds in which grass biomass was manipulated by prescribed burning.
Rainfall Manipulation Plots facility (RaMPs) is a unique experimental infrastructure that allows us to manipulate precipitation events and temperature, and assess population community, and ecosystem responses in native grassland. This facility allows us to manipulate the amount and timing of individual precipitation events in replicated field plots at the Konza Prairie Long-Term Ecological Research (LTER) site.
This GPS-collar data set was used to evaluate the factors that influence where bison choose to graze and how grazing and space use patterns affect ecosystem function and structure. Our objectives were to quantify space use and movement patterns of adult female Plains bison in the context of selection for specific prescribed burn frequencies and topographical features in the bison-grazed watersheds 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.
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).
The distribution, structure and function of mesic savanna grasslands are strongly driven by fire regimes, grazing by large herbivores, and their interactions. This research addresses a general question about our understanding of savanna grasslands globally: Is our knowledge of fire and grazing sufficiently general to enable us to make accurate predictions of how these ecosystems will respond to changes in these drivers over time? Some evidence suggests that fire and grazing influence savanna grassland structure and function differently in South Africa (SA) compared to North America (NA).
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.
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.
Understanding spatial and temporal variation in plant traits is needed to accurately predict how communities and ecosystems will respond to global change. The National Observatory Ecological Network (NEON) Airborne Observation Platform (AOP) provides hyperspectral images and associated data products at numerous field sites at 1 m spatial resolution, allowing high-resolution trait mapping. However, the reliability of these data depend on establishing rigorous links with in-situ field measurements.
Woody plants are increasing prevalence and dominance in many rangelands around the world. The reason for their increase is various but two common drivers that have changed are an increase in CO2 concentrations and alteration to precipitation dynamics. We asked what the physiological growth dynamics of four juvenile woody plant species (Cornus drummondii, Rhus glabra, Gleditsia triacanthos and Juniperus osteosperma) when grown in elevated CO2 and chronically water stressed.
Climate variability and periodic droughts have complex effects on carbon (C) fluxes, with uncertain implications for ecosystem C balance under a changing climate. Responses to climate change can be modulated by persistent effects of climate history on plant communities, soil microbial activity, and nutrient cycling (i.e., legacies). To assess how legacies of past precipitation regimes influence tallgrass prairie C cycling under new precipitation regimes, we modified a long-term irrigation experiment that simulated a wetter climate for >25 years.
Climate change is expected to shift precipitation regimes in the North American Central Plains with likely impacts on ecosystem functioning. In tallgrass prairies, water and nitrogen (N) can co-limit ecosystem processes, so changes in precipitation may have complex effects on carbon (C) and N cycling. Rates of N supply such as N mineralization and nitrification respond differently to short- and long-term patterns in water availability, and previous climate patterns may exert legacy effects on current N cycling that could alter ecosystem sensitivity to current precipitation regimes.
In fall of 2010 in watershed N2B ( 39.088976°, -96.588599°), we established plant community plots to assess the potential ability of the riparian zone to shift to a grassland state based on cutting alone and cutting with replanting. The three treatments were 1) naturally open riparian grassland before the removal, 2) areas cleared of woody vegetation, and 3) areas cleared of woody vegetation and seeded with prairie plant species. The addition of the seeded treatment was designed to address if recovery of grassland vegetation is hindered by propagule limitation.
Woody encroachment, or invasion of woody plants, is rapidly shifting tallgrass prairie into shrub and evergreen dominated ecosystems, mainly due to exclusion of fire. Tracking the pace and extent of woody encroachment is difficult because shrubs and small trees are much smaller than the coarse resolution (>10m2) of common remote sensed images.
Purpose: Litter decomposition is an important component of carbon (C) and nitrogen (N) cycling, and rates of mass loss and nutrient release are sensitive to current climate conditions. Growing evidence suggests that past climate conditions can exert legacies on soil C and N cycling, but little is known about how belowground decomposition dynamics relate to these climate legacies.
Evolutionary history plays a key role driving patterns of trait variation across plant species. For scaling and modeling purposes, grass species are typically organized into C3 versus C4 plant functional types (PFTs). PFT groupings may obscure important functional differences among species. Rather, grouping grasses by evolutionary lineage may better represent grass functional diversity.
Losses in freshwater fish diversity might produce a loss in important ecological services provided by fishes in particular habitats. An important gap in our understanding of ecosystem services by fishes is the influence of individuals from different size classes, which is predicted based on known ontogenetic shifts in habitat and diet. I used twenty experimental stream mesocosms located on Konza Prairie Biological Station (KPBS), KS, USA to assess the influence of fish size on ecosystem properties.
