Prairie dogs (Cynomys spp.) are burrowing rodents considered to be ecosystem engineers and keystone species of the central grasslands of North America. Yet, prairie dog populations have declined by an estimated 98% throughout their historic range. This dramatic decline has resulted in the widespread loss of their important ecological role throughout this grassland system. The 92,060 ha Sevilleta NWR in central New Mexico includes more than 54,000 ha of native grassland. Gunnison’s prairie dogs (C. gunnisoni) were reported to occupy ~15,000 ha of what is now the SNWR during the 1960’s, prior to their systematic eradication. In 2010, we collaborated with local agencies and conservation organizations to restore the functional role of prairie dogs to the grassland system. Gunnison’s prairie dogs were reintroduced to a site that was occupied by prairie dogs 40 years ago. This work is part of a larger, long-term study where we are studying the ecological effects of prairie dogs as they re-colonize the grassland ecosystem.
Two replicate paired 16 ha plots were established in spring 2010. Each pair consists of a treatment plot with prairie dogs (reintroduced), which are plots B and D and a control plot with no prairie dogs (plots A and C). There are 4 other plots (E,F,G, and H) but they are not set up to do vegetation sampling.
Baseline vegetation sampling occurred at the end of April 2010. A second sampling was done at the end of September 2011. There was no other vegetation sampling until September 2013, at which time it will be collected consistently every spring and fall.
Percent live plant canopy cover and height of live foliage of all plant species are measured using 0.25 m2 vegetation sampling quadrats at the end of the growing season each spring (late April) and late summer (early September). The 50x50 cm vegetation measurement frame has a string grid which partitions the frame into 25, 10x10 cm squares. One quarter of a 10x10 cm grid cell equals 1% cover. Therefore each 10x10 cm cell has a 4% cover value. Vegetation measurements range from 0.1 to 100%. A cover of 0.1 represents a plant species trace occurrence on the quad. The next smallest measurement is 1%, or ¼ of a 10x10 cm grid cell. Cover is measured to the nearest 1% for 1-10% cover and to the nearest 5% for 10-100% cover. Total cover for a particular plant species is measured by counting the number of 10x10 cm cells occupied by the foliage canopy, multiplying that value by 4 and rounding to the nearest 5% for total cover greater than 10%. Typical maximum plant canopy height for each species is also measured to the nearest centimeter.
More information about who is involved with the samples/data:
Terri Koontz 2010
Amaris Swann 2011
John Mulhouse 2011
Stephanie Baker 2011-present
Megan McClung 2013-present
Chandra Tucker 2014-present
Study Site Information:
The SevLTER Prairie Dog Project 16 ha study plots are located east of the Blue Grama Core site at the foothill of the Los Pinos Mountains and along Test Well Road. It is a grassland dominated by blue grama grass, with associated grass species consisting of black grama, galleta, purple three-awn, sand muhly, and dropseed. Yucca and Cholla cactus are the dominant shrubs at the site.
In the southwestern United States two important seasons influence stream flow: snowmelt in spring and summer monsoonal rainfall events. Flow patterns exhibit peak discharge from snowmelt runoff in the spring followed by pulsed increases in stream discharge during late summer monsoons. Molles and Dahm showed the intensity of the snowmelt discharge is linked to El Nino-Southern Oscillation (ENSO) conditions in the tropical Pacific. El Nino and La Nina climate patterns also may affect late summer monsoonal precipitation in New Mexico by intensifying the monsoon during La Nina years and weakening monsoons during El Nino years. Stage gage data show seasonal and interannual variability in the intensity of snowmelt and monsoonal runoof events in montane catchments in New Mexico. Further, in-situ YSI sonde, Satlantic Submersible Ultraviolet Nitrate Analyzer (SUNA) and CycleP instrumentation show physical and chemical constituents respond to higher flow events driven by climate variability, and the constituents these instruments measure can be used as a proxy to estimate whole stream metabolism and nutrient cycling processes.
Data Selection: Historical flux tower data from 2007 to 2011 was provided by UNM Marcy Litvak for two locations near our study site on the EFJR. Los Alamos National Lab provided flux data from 2005 to 2006. Flux towers provided photosynthetic active radiation (PAR) and barometric pressure in 30 minute time intervals. In-stream YSI sondes continuously monitored the Jemez and East Fork Jemez Rivers in 15 minute time intervals collecting water quality data (dissolved oxygen, pH, turbidity, specific conductance, water temperature).
Instrument Name: YSI Sonde Manufacturer: YSI IncorporatedModel Number: 6920V2-0
Sonde and flux data were QAQC'd using Aquarius software to delete suspicious data (or outliers) and to correct for drift from biofouling on probes.
Study Area Name: East Fork Jemez River
Study Area Location: Valles Caldera National Preserve, New Mexico
Study Area Description:
Elevation: 2582 meters
Landform: Montane grassland, caldera
Soils: Rich organic soils; Mollisols
Hydrology: snowpack(winter) and monsoonal rainfall (summer)
Vegetation: grassland, meadow
Site history: Domestic grazing of sheep from mid-1800's to 1940's, then cattle by 1940's.
Single Point: EFJR at Hidden Valley (from VCNP)
North Coordinate: 35.83666667
West Coordinate: -106.5013833
Climate models predict that water limited regions around the world will become drier and warmer in the near future, including southwestern North America. We developed a large-scale experimental system that allows testing of the ecosystem impacts of precipitation changes. Four treatments were applied to 1600 m2 plots (40 m × 40 m), each with three replicates in a piñon pine (Pinus edulis) and juniper (Juniper monosperma) ecosystem. These species have extensive root systems, requiring large-scale manipulation to effectively alter soil water availability. Treatments consisted of: 1) irrigation plots that receive supplemental water additions, 2) drought plots that receive 55% of ambient rainfall, 3) cover-control plots that receive ambient precipitation, but allow determination of treatment infrastructure artifacts, and 4) ambient control plots. Our drought structures effectively reduced soil water potential and volumetric water content compared to the ambient, cover-control, and water addition plots. Drought and cover control plots experienced an average increase in maximum soil and air temperature at ground level of 1-4° C during the growing season compared to ambient plots, and concurrent short-term diurnal increases in maximum air temperature were also observed directly above and below plastic structures. Our drought and irrigation treatments significantly influenced tree predawn water potential, sap-flow, and net photosynthesis, with drought treatment trees exhibiting significant decreases in physiological function compared to ambient and irrigated trees. Supplemental irrigation resulted in a significant increase in both plant water potential and xylem sap-flow compared to trees in the other treatments. This experimental design effectively allows manipulation of plant water stress at the ecosystem scale, permits a wide range of drought conditions, and provides prolonged drought conditions comparable to historical droughts in the past – drought events for which wide-spread mortality in both these species was observed.
Water potential measurements were used to monitor the water stress of the two target species across the four treatment regimes. Sampling for water potentials occurred twice daily. One set of samples was collected hours before dawn and another set was collected at mid-day. The predawn readings provided the “least-stressed” tree water content values as they were collected after the trees had returned to equilibrium over the evening and had yet to start transpiring. The mid-day values, collected after tree-level respiration had been occurring for hours and when the daily temperatures were highest, represented the opposite “most-stressed” scenario. To gauge the effect of the irrigation treatment on the water content of the trees, we sampled water potentials just before and just after irrigation events.
In total, our study site consisted of 12 experimental plots located in three replicate blocks that varied in slope % and aspect. Slope varied from 0-2% in experimental plots situated in level portions of the site, with steeper grades ranging from 6-18% for plots established on hill-slopes. Soil depth across the site ranged from 20 to ≥ 100 cm, with shallower soil depths occurring on hill-slopes where depth to caliche and/or bed-rock was only 20-30 cm in some instances.
The study utilized four different experimental treatments applied in three replicate blocks. The four experimental treatments included 1) un-manipulated, ambient control plots, 2) drought plots, 3) supplemental irrigation plots, and 4) cover-control plots that have a similar infrastructure to the drought plots, but remove no precipitation. The three replicated blocks differed in their slope and aspect. One block of four plots was located on south facing slopes, one on north facing slopes, and one in a flat area of the landscape.
Experimental Treatment Design
To effectively reduce water availability to trees, we installed treatments of sufficient size to minimize tree water uptake from outside of the plot. Thus, we constructed three replicated drought structures that were 40 m × 40 m (1600 m2). We targeted a 50% reduction in ambient precipitation through water removal troughs that covered ~50% of the land surface area. Drought plot infrastructure was positioned to insure that targeted Piñon pine and juniper were centrally located within each drought plot to provide the maximum distance between tree stems and the nearest plot boundary. Each drought and cover-control plot consists of 27 parallel troughs running across the 40 m plot. Each trough was constructed with overlapping 3ft ×10 ft (0.91 m × 3.05 m) pieces of thermoplastic polymer sheets (Makloron SL Polycarbonate Sheet, Sheffield Plastics Inc, Sheffield, MA) fixed with self-tapping metal screws to horizontal rails that are approximately waist height and are supported by vertical posts every 2.5-3.5 m. The plastic sheets were bent into a concave shape to collect and divert the precipitation off of the plot. The bending and spacing of the plastic resulted in 0.81 m (32 in) troughs separated by 0.56 m (22 in) walkways.
Individual troughs often intersected the canopy of trees because of their height. The troughs were installed as close to the bole of the tree as possible without damaging branches in order to maximize the area covered by the plastic across the entire plot. An end-cap was attached to the downstream edge of the trough to prevent water from falling onto the base of the tree. The end-caps were 81 cm × 30 cm and made with the same plastic as the troughs. Each end-cap was fixed to the trough with a 75 cm piece of 20 gauge angle iron cut to match the curve of the bottom of the trough and held in place with self-tapping screws. The plastic junctures were then sealed with acrylic cement (Weld-On #3 epoxy, IPS Corp., Compton, CA). The middle of the end-cap was fitted with a 3 in (7.62 cm) PVC collar to allow water to flow through. A piece of 3 in (7.62 cm) PVC pipe or suction hose (used when the bole of a tree was directly below trough) was then attached to the downstream side of the end-cap, enabling water to flow into the trough on the other side of a tree. End-caps were also placed at the downhill end of the troughs on the edge of the plot and fitted with 90o fittings to divert water down into a 30 cm2 gutter (open on top) that ran perpendicular to the plot. Collected water was then channeled from the gutter into adjacent arroyos for drainage away from the study area.
We built cover-control infrastructures to investigate the impact of the plastic drought structures independent of changes in precipitation. This was necessary because of the high radiation environment in central New Mexico, in which the clear plastic troughs can effectively act as a greenhouse structure. The cover-control treatment had the same dimensions as the drought plots with one key difference. The plastic was attached to the rails in a convex orientation so precipitation would fall on top of the plastic and then drain directly down onto the plot. The cover-control plots were designed to receive the same amount of precipitation as un-manipulated ambient plots, with the precipitation falling and draining into the walkways between the rows of troughs. Cover-control plots were constructed between June-21-07 and July-24-07; drought plots were constructed between August-09-07 and August-27-07. The total plastic coverage in each plot is 45% ± 1% of the 1600 m2 plot area due to the variable terrain and canopy cover. A direct test of the amount of precipitation excluded via the plastic troughs was performed over a 2-week period during the summer monsoon season of 2008. Two rainfall collection gutters (7.6 cm width, 6.1 m length) were installed in a perpendicular arrangement across four plastic drought structures and four intervening open walkways. One gutter was located below the troughs (~0.6 m above ground), and the other was located just above (~1.35 m) and offset, to determine the interception of rainfall by the troughs. Rainfall totals collected via the perpendicular gutters were measured using Series 525 tipping bucket rain gauges (Texas Electronics, Dallas, TX).
Our irrigation system consisted of above-canopy sprinkler nozzles configured to deliver supplemental rainstorm event(s) at a rate of 19 mm hr-1. Our irrigation system is a modified design of the above-canopy irrigation system outlined by Munster et al. (2006). Each of the three irrigation plots has three 2750 gal (10.41 m3) water storage tanks connected in parallel. These tanks were filled with filtered reverse osmosis (RO) water brought to the site with multiple tractor-trailer trucks. During irrigation events, water is pumped from the tanks through a series of hoses that decrease from 7.62 cm (3 in) main lines out of the tank to 2.54 cm (1 in) hoses attached to 16 equally-spaced sprinklers within the plot. Each sprinkler is 6.1 m (20 ft) tall (2-3 m higher than mean tree height), and fitted with a sprinkler nozzle that creates an even circular distribution of water with a radius of 5 m on the ground. Due to the varying topography, sprinklers located downslope (if unregulated) would receive more pressure than those at the top of a hill and thus spray more water. To mitigate this problem, each sprinkler line was fitted with a pressure gauge and variable globe valve (inline water spigot with precise regulation) equidistant from the top of the sprinkler. Each sprinkler line was then set so that the pressure gauges were equal, thus ensuring equal distribution of water throughout the plot, regardless of elevational differences. The irrigation systems were tested in October 2007 (2 mm supplemental), and full applications (19 mm) were applied in 2008 on 24-June, 15-July, and 26-August. During the 24-June event, we deployed six ~1 m2 circular trays across one of the irrigation plots to test the spatial variation of the wetting. Data from this test indicated that on average, collection trays received 19.5 (± 2.5) mm of water.
Plant Physiological Response
Multiple physiological characteristics of ten target trees (five piñon and five juniper) within each of the intensive measurement plots were continually monitored by automated sensors or periodic manual measurements. Predawn (PD) and mid-day (MD) plant water potentials were measured with multiple Scholander-type pressure chambers (PMS Instrument Co, Albany, OR) on all target trees. When possible, PD was measured both before and after supplemental irrigation events.
Data processing and QA-QC were performed using either Matlab (The Mathworks, Inc.) or Microsoft Office 2010 Excel (Microsoft Corporation) software. All raw and/or processed data traces were visually plotted and inspected for noisy, erroneous, or out of range data points or sensors traces. All removed data points had a “NaN” value assigned. Despite this QA-QC review and data cleaning, all data sets should still be evaluated for outliers, etc., as standard outlier statistical tests were not performed.
Additional notes: The water potential data-set contains periodic tree level water potential data from 2006 thru 2012. Measurements were made at either predawn or midday. Data Qa/Qc has been performed on these files. PJ day refers to days since start of project (i.e., 1/1/2006). The treatment classes provided in the file are as follows; ambient (1), drought (2), cover-control (3), and irrigation (4). The experiment used plot aspect as the blocking factor. There are 3 different replicate blocks and block classifications designated in the files; flat aspect (1), north aspect (2), and south aspect (3). This will be obvious when viewing the files.Tree numbers are always grouped by species as follows (regardless of plot); Trees 1-5 are original Pinus edulis, Trees 6-10 are original Juniper monosperma. When one of these original trees died, an additional tree in the plot was added to retain an adequate sample size over time (i.e., multiple years+). These additional trees are grouped as follows; Trees 11-15 are “replacement” Pinus edulis, Trees 16-20 are “replacement” Juniper monosperma. “Replacement” is used here in a more restricted sense, as these additional trees have their separate and unique tree designation number.So, in differing plots you will have differing numbers of trees depending on; 1) the number of trees for which data was collected, and 2) how many additional “replacement trees” had to be designated due to mortality (or partial mortality) of original trees. Many plots have n=10 trees, based on the original T1-T5 & T6-10 designation, as these particular plots did not experience mortality. However, a plot like P10 has a total of n=16 trees. In P10, the original T1-5 & T6-T10 trees are listed, a replacement Pinon (T11) is listed, and five additional/replacement junipers (T16-T20). In some cases you will see data present at the same time for both original and replacement junipers (plots 6 & 10). This is fine, as juniper experiences a slow/partial canopy dieback, so we monitored the original and replacement trees at the same time in these two plots. Finally, we only provide data on trees for which data was collected (so for example, in some instances you may only have n=4 cols of data for a particular species in a particular plot).
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 differences have been attributed to the contingent factors of greater biome age, longer evolutionary history with fire and grazing, reduced soil fertility, and greater diversity of plants and large herbivores in SA. An alternative hypothesis is that differences in methods and approaches used to study these systems have led to differing perspectives on the role of these drivers. If the impacts of shared ecosystem drivers truly differ between NA and SA, this calls into question the generality of our understanding of these ecosystems and our ability to forecast how changes in key drivers will affect savanna grasslands globally. Since 2006, an explicitly comparative research program has been conducted to determine the degree of convergence in ecosystem (productivity, N and C cycling) and plant community (composition, diversity, dynamics) responses to fire and grazing in SA and NA.
Thus far, initial support has been found for convergence at the ecosystem level and divergence at the community level in response to alterations in both fire regimes and grazing. However, there have also been two unexpected findings (1) the ways in which fire and grazing interact differed between NA and SA, and (2) the rate of change in communities when grazers were removed was much greater in NA than in SA. These unexpected findings raise a number of important new questions: (Q1) Will exclusion of grazing eventually affect community structure and composition across all fire regimes in SA? (Q2) Will these effects differ from those observed in NA? (Q3) What are the determinants of the different rates of community change? (Q4) How will these determinants influence future trajectories of change? (Q5) Will the different rates and trajectories of community change be mirrored by responses in ecosystem function over time? This project is based on a large herbivore exclusion study established within the context of long-term (25-50+ yr) experimental manipulations of fire frequency at the Konza Prairie Biological Station (KPBS) in NA and the Kruger National Park (KNP) in SA. The suite of core studies and measurements include plant community composition, ANPP, and herbivore abundance and distribution at both study sites to answer these research questions.
Konza-Ukulinga fire by nitrogen project: We used comparable experimental designs and sampling procedures at both URF and KPBS (Figure 1). At URF we used three replicate plots (not hayed or mowed) that have been burned every 1 and 3 years in the spring, and those left unburned (N=9 plots). At KPBS, we established replicate plots in experimental watersheds burned every 1 and 4 years in the spring, and those left unburned (N=9 plots). Thus, the only difference in design between NA and SA was the intermediate burn frequency. In 2005 at both sites we established four 2x2m areas in each replicate of the 1-yr, 3-4 yr burned, and unburned plots (N=36 subplots). We then randomly selected two of the subplots for the fertilization treatment and the other two subplots served as controls (Fig. 1). Starting in 2006 at KPBS and 2007 at URF, we began adding 10 gN/m2/yr as NH4+NO3- to assess the interactive effects of fire frequency and nitrogen limitation on plant community composition, structure and dynamics.
Fig. 1. Experimental design and sampling for the proposed studies: A) the role of long-term fire regimes (without megaherbivores), B) the importance of grazing and grazing/fire interactions, and C) the role of megaherbivore diversity. Moveable exclosures (3/plot) will be used to estimate ANPP in the grazed plots. N addition subplots (2 x 2 m) will be divided into 4 1 x 1 plots, with two designated for plant species composition sampling and the other two for destructive sampling. Soil samples will be collected from areas not designated for ANPP or plant composition sampling. Note that the same annually and infrequently burned plots at Kruger and Konza will be used in (B) and (C). In addition, similar plots will be established minus the N addition subplots in the 1-yr and 4-yr burned blocks of the Buffalo enclosure for (C).
Each of the 2x2m subplots was divided into four 1x1m quadrats. Annually since 2005 (prior to nitrogen addition) canopy cover of each species rooted in each quadrat was visually estimated twice during the growing season to sample early and late season species. As a surrogate for aboveground production, we measured light availability at the end of the growing season above the canopy at the ground surface in each quadrat (N=4 per subplot) using a Decagon ceptometer.
Konza-Kruger fire by grazing project: For this study, we are utilizing the long-term experiments at KPBS and KNP in which native megaherbivore grazers are present and fire frequency is directly manipulated. To assess the effects of grazing and fire-grazing interactions, we constructed seven sets of permanent exclosures and adjacent control plots in three blocks at both sites. The exclosures and matching paired open plots were established in 2005 in the Satara EBPs that are burned every 1 and 3 years in the spring or left unburned and at KPBS in watersheds that are burned every 1 and 4 years or left unburned. (N=63 exclosures/site; Fig. 1). Within each exclosure and paired open plot, we sample plant community composition and light availability in permanent 2x2 m subplots. We collect ANPP at the end of each growing season from each exclosure, and throughout the growing season in grazed areas adjacent to the unexclosed plots using 1x1 m moveable exclosures (Fig. 1).
Net primary production measurements: Prior to the 2005 growing season we established plots (13.7 m by 18.3 m) in ungrazed areas burned annually, at 3–4-year intervals, and unburned (n = 3 per fire treatment) at both KBPS and URF. Areas with trees or large shrubs were avoided as our main goal was to evaluate responses in the herbaceous plant community. ANPP was estimated from end-of-season harvests starting in 2005 (September for KBPS, April for URF). In 10, 0.1-m2 (20 cm by 50 cm) quadrats randomly located in each plot (n = 30/treatment/site), we harvested the vegetation at ground level and separated it into grass, forb, and previous year’s dead biomass. Samples were dried at 60C to a constant weight. For annually burned plots, total biomass harvested represents ANPP. For the intermediate and unburned sites, we calculated ANPP by summing all but the previous year’s dead component.
To assess the impacts of fire on ANPP in grazed areas, we established herbivore exclusion treatments in KBPS in North America and KNP in South Africa. Herbivore exclosures in grazed areas in KPBS and KNP were erected prior to the 2006 growing season. The exclosures were 7 m in diameter, 2 m tall, and constructed of diamond mesh (5-cm diameter). Seven exclosures were established in each of three blocks of the three fire treatments— annually burned, intermediate burn (3- years for KNP or 4-years for KPBS), and unburned (n = 21 exclosures/treatment/site). As our focus was on ANPP responses of the herbaceous layer, exclosures were not located beneath trees or where dense shrub patches were present. Additionally, in the Satara region of KNP is a 900-ha permanent enclosure containing 80–90 adult African buffalo (S. caffer). This enclosure was erected in 2000 and was divided into six areas (100–200 ha each), with these burned on a rotational basis including plots burned annually and plots that were unburned. We used the unburned and annually burned areas in the buffalo enclosure to provide a direct comparison for determining the effects of a single-species large grazer in KNP and KPBS, and to assess the effects of large herbivore diversity at adjacent sites in KNP. Similar exclosures were built in the African buffalo enclosure at KNP. We placed 7 exclosures in the three blocks of each fire treatment (annually burned and unburned) resulting in 21 exclosures/treatment. We sampled ANPP by harvesting plant biomass from three 0.1 m2 quadrats per herbivore exclosure at the end of the growing season starting in 2006.
Data are collected twice each year at each site. Sample periods are equivalent to spring and late summer at each study site (December/January and March/April in South Africa, May and September in North America.
Where the Data were Collected:
Ukulinga Research Farm, Pietermaritzburg, South Africa; Satara Region of Kruger National Park, South Africa; Konza Prairie Biological Station, North America
Additional Geographic Metadata:
Ukulinga Research Farm (URF), South Africa. The URF of the University of KwaZulu-Natal is located in Pietermaritzburg, in southeastern South Africa (30o 24’ S, 29o 24’ E). The site is dominated by native perennial C4 grasses, such as Themeda triandra and Heteropogon contortus, that account for much of the herbaceous aboveground net primary production (ANPP). Mean annual precipitation is 790 mm, coming mostly as convective storms during summer (Oct-Apr). Summers are warm with a mean monthly maximum of 26.4oC in February, and winters are mild with occasional frost. Soils are fine-textured and derived from shales. There has been no grazing at this site for >60 years. Long-term experimental plots were established at URF in 1950 with the objective of determining the optimal fire and/or summer cutting regime to maximize hay production. The experiment is a randomized block (three replicates) split-plot design with four whole-plot haying treatments and 11 subplot fire or mowing treatments. Subplot sizes are 13.7 x 18.3 m.
Kruger National Park (KNP), South Africa. The KNP is a 2 million ha protected area of savanna grassland that includes many of the large herbivores common to southern Africa (22º 25' to 25º 2 32' S, 30º 50' to 32º 2' E). The extant abundance and grazing intensity of herbivores in KNP is considered moderate for regional savanna grasslands. In the south-central region of KNP where our research takes place, average rainfall is 537 mm with most falling during the growing season (Oct-Apr). The dormant season is mild, dry and frost free, and summers are warm with mean monthly maximum air temperature of 28.9oC in January. Because of the importance of fire in savanna grassland ecosystems, the Experimental Burn Plot (EBP) experiment was initiated in 1954 to examine the effects of fire frequency (control-no fire, 1-, 2-, 3-, 4- and 6-yr return interval) and season [early spring (Aug), spring (Oct), mid-summer (Dec), late summer (Feb), and fall (Apr)] on vegetation communities in the park. Four blocks of 12 plots (two were later split for the 4- and 6-yr trts), each ~7 ha (370 x 180 m) in size, were established in four primary vegetation types covering the two major soil types (granites and basalts) and spanning the precipitation gradient in the park. Each plot has 50+ years of known fire history, and native herbivores have had unrestricted access, thus fire and grazing effects are combined. This research focuses on the EBPs located near Satara where precipitation, soil type, and the mix of herbaceous and woody plants are similar to KPBS. Vegetation on the blocks is co-dominated by C4 grasses, such as Bothriochloa radicans, Panicum coloratum and Digiteria eriantha, and woody plants, such as Acacia nigrescens and Sclerocarya birrea. Soils are fine-textured and derived from basalts. Adjacent to one of the Satara blocks is the Cape buffalo enclosure, erected in 2000 for veterinary purposes. The 200 ha permanent enclosure contains 65-80 animals and is divided into 4 blocks burned on a rotational basis. The grazing intensity inside is comparable to the moderate levels imposed in the park and at KPBS. Two blocks are burned annually while others are burned infrequently (approximately once every 4-yr).
Konza Prairie Biological Station (KPBS), North America. The KPBS is a 3,487 ha savanna grassland in northeastern Kansas, USA (39o 05’ N, 96o 35’ W) dominated by native perennial C4 grasses such as Andropogon gerardii and Sorghastrum nutans that account for the majority of ANPP. Scattered shrub and tree species include Cornus drummondii, Gleditsia triacanthos, and Prunus spp. Numerous sub-dominant grasses and forbs contribute to the floristic diversity of the site. The climate is continental, with mean July air temperature of 27°C. Annual precipitation is ca. 820 mm/year, with 75% falling as rain during the Apr-Oct growing season. Soils are fine textured, silty clay loams derived from limestone and shales. KPBS includes fully replicated watershed-level fire and fire/grazing treatments, in place since 1977 and 1987, respectively. Replicate watersheds (mean size ~60ha) are burned at 1-, 2-, 4-, 10- and 20-yr intervals, mainly in April, to encompass a range of likely natural fire frequencies and management practices. A subset of watersheds has not been grazed for more than 30 years. To address the role of native grazers and fire/grazing interactions, bison (~260 individuals) were reintroduced to KPBS in a 1000-ha fenced area that includes replicate watersheds burned in the spring at 1-, 2-, 4- and 20-year intervals. The overall grazing intensity is considered moderate.
Study Area 1:
Study Area Name: Ukulinga Research Farm
Study Area Location: Near Pietermaritzburg, South Africa
Elevation: 840 m above sea level
Landform: Colluvium fan
Geology: Marine shales and dolerite colluvium
Soils: Dystric leptosols, Chromic luvisols, Haplic plinthisols
Vegetation: Native grassland
Climate: Mean annual precipitation is 844 mm, Mean annual temperature 17.6C
Site history: Ungrazed since 1950
Single Point: 29o 40’ S / 30o 20’ E
Study Area 2: Kruger National Park, South Africa
Study Area Name: Satara Experimental Burn Plots and Cape Buffalo Exclosure
Study Area Location: Near Satara rest camp
Elevation: 240-320 meters above sea level
Landform: Level Upland
Soils: Rhodic nitisols, Haplic luvisols, Leptic phaeozems
Climate: Mean annual precipitation 544 mm; mean annual temperature 21.2–23.3C
Site history: Grazed by native herbivores
Single Point: 23–25o S /30-31o E
Study Area 3: Konza Prairie Biological Station
Study Area Name: Konza Prairie
Study Area Location: Watersheds N20B, N4D, N1B, N4B; 1D, 4F, 20B
Elevation: 320-444 meters above sea level
Landform: Alluvial terrace
Geology: Cherty limestone and shale
Soils: Udic argiustolls
Climate: Mean annual precipitation 835 mm; mean annual temperature 12.7C
Site history: Ungrazed watersheds (since 1971), watersheds grazed by native herbivores (since 1987)
Single Point: 39o 05.48’ N / 96o 34.12’ W
Shrub expansion into grasslands can cause abrupt changes in ecosystem processes. Creosote (Larrea tridentata) is a native shrub in warm, arid deserts of the southwestern US and has taken over C4 grasslands. A limited freeze tolerance is thought to dictate the northern boundary of creosote and the Sevilleta National Wildlife Refuge occurs near to the northern extent of creosote. Cold temperatures are known to damage creosote. In laboratory trials, temperatures of -25 for 1 hour lead to xylem damaging embolism in nearly 100% of stems and temperatures of -24 C lead to seedling death in the lab. Sevilleta LTER meteorological data from a station located within creosote shrublands indicated a low temperature of -20 C between 1999 and 2010. On February 3, 2011 temperatures hit record lows in central New Mexico, reaching -30 C at shrublands within the SNWR. To address how creosote responds to a natural extreme cold events, plots were established to monitor creosote initial response and regrowth following the cold event. Initial surveys will determine canopy death and subsequent surveys of the same individuals will allow us to determine how creosote responds to record cold temperatures.
Plots were established at 6 locations across SNWR. Criteria for site selection included the presence of L. tridentata, flat terrain to limit microtopographic impacts, close proximity to existing meteorological stations, and variation in shrub density between sites. At each site, approximately 200 shrubs were evaluated within circular plots (20m in diameter) with the number of plots at each site varying in shrub density. Initial surveys to determine canopy death were conducted in early April 2011. These surveys consisted of tagging each shrub with an unique ID, estimating canopy death, and measuring maximum canopy height, maximum width and the perpendicular width to max width.
Study Area 1:
Study Area Name: South Gate
Study Area Location: Located across the road from the met station located at South Gate.
North Coordinate: 34.42
South Coordinate: 34.19
East Coordinate: -106.513
West Coordinate: -107.08
Study Area 2:
Study Area Name: Microwave shrubland
Study Area Location: Located near the Microwave tower on the West side of the SNWR. Plots are located 100 to 200 m down the road just East of the tower towards Red Tank. Plots are on the West side of the road.
North Coordinate: 34.42
East Coordinate: -106.518
Study Area 3:
Study Area Name: BurnX shrubland site
Study Area Location: Located near Met station 52b, established near the burn enclosure (BurnX) Black Grama site.
This file contains 1997 daily lightning activity data for the state of New Mexico. These data were collected by a network of lightning detection stations scattered throughout the western United States. More information regarding the LLP Lightning Locating System can be found in Maier et al. (1983).
This file contains 1997 daily lightning activity data for the state of New Mexico. These data were collected by a network of lightning detection stations scattered throughout the western United States. More information regarding the LLP Lightning Locating System can be found in Maier, et.al. (1983).
Only data on cloud-to-ground lightning flashes are recorded in this file. Note that each cloud-to-ground lightning flash is composed of one or more highly energetic discharges known as return strokes. Thus each lightning observation found in this file contains a column showing the number of return strokes associated with each flash. In addition, each observation includes information on the time of the flash, location (latitude/longitude), polarity, and signal amplitude. The lightning flash location is determined by triangulation. The accuracy of the flash location is dependent on the number of stations detecting the flash, the flash location with respect to the detecting stations (i.e., poor accuracy if on the baseline between two stations), and the distance between the detecting stations. When the detecting stations are 50 miles apart, estimated strike locations are usually within 1/2 to 1 kilometer of the actual location.
The local lightning detection stations are located at:
LOCATION LATITUDE LONGITUDE
Albuquerque 34.9475 -106.5590
Socorro 34.0682 -106.9139
Roswell 33.3076 -104.5274
Gallup 35.5126 -108.7768
These data are bounded by the following coordinates:
Latitude: 31.335 to 36.999 degrees
Longitude: -109.048 to -103.006 degrees
This file contains 1998 daily lightning activity data for the state of New Mexico. These data were collected by a network of lightning detection stations scattered throughout the western United States. More information regarding the LLP Lightning Locating System can be found in Maier et al. (1983).
This file contains 1998 daily lightning activity data for the state of New Mexico. These data were collected by a network of lightning detection stations scattered throughout the western United States. More information regarding the LLP Lightning Locating System can be found in Maier, et.al. (1983).
This file contains 1999 daily lightning activity data for the state of New Mexico. These data were collected by a network of lightning detection stations scattered throughout the western United States. More information regarding the LLP Lightning Locating System can be found in Maier et al. (1983).
This file contains 1996 daily lightning activity data for the state of New Mexico. These data were collected by a network of lightning detection stations scattered throughout the western United States. More information regarding the LLP Lightning Locating System can be found in Maier, et.al. (1983).
This study originated with the objective of parameterizing riparian evapotranspiration (ET) in the water budget of the Middle Rio Grande. We hypothesized that flooding and invasions of non-native species would strongly impact ecosystem water use. Our objectives were to measure and compare water use of native (Rio Grande cottonwood, Populus deltoides ssp. wizleni) and non-native (saltcedar, Tamarix chinensis & Russian olive, Eleagnus angustifolia) vegetation and to evaluate how water use is affected by climatic variability resulting in high river flows and flooding as well as drought conditions and deep water tables. Eddy covariance flux towers to measure ET and shallow wells to monitor water tables were instrumented in 1999. Active sites in their second decade of monitoring include a xeroriparian, non-flooding salt cedar woodland within Sevilleta National Wildlife Refuge (NWR) and a dense, monotypic salt cedar stand at Bosque del Apache NWR, which is subject to flood pulses associated with high river flows.
Three-dimensional eddy covariance: Measures fluxes of latent heat, sensible heat, and momentum, integrated over an area such as a vegetation canopy. High frequency measurements are made of vertical wind speed and water vapor, and their covariance over thirty minutes is used to compute latent heat flux, the heat absorbed by evaporation, from the canopy surface. Latent heat flux (LE) is converted to a direct measurement of evapotranspiration (ET). Simultaneous, high frequency measurements of temperature are used with vertical wind speed to compute the sensible heat flux (H), the heat transfer due to vertical temperature gradients. Measuring net radiation (Rn) and ground heat flux (G), allows the energy balance to be calculated (Rn = LE + H + G), providing a self-check for accuracy and closure error.
Sites: Two Rio Grande riparian locations in P. deltoides forests, two in T. chinensis forests. In each forest type, one of the two sites is prone to flooding from elevated Rio Grande flows, and the other site does not flood. A fifth site was located in a mix of non-native Eleagnus angustifolia (Russian olive) and native Salix exigua (coyote willow) prone to flooding.
Design: Eddy covariance systems were mounted on towers in the turbulent surface layer 2-2.5 m above the canopy. Measurement period was 10 Hz and the covariance period was 30 minutes. Additional energy fluxes were made at 1 Hz and averaged over 30 minutes.
Water table fluctuations were monitored at the sights with groundwater wells installed ~ 1 m below baseflow water table. Wells were constructed of 5 cm inner diameter PVC pipe with approximately 1 m screen lengths. Automated pressure transducers were deployed to measure water table elevations at 30-minute intervals.
Precision: Thirty minute average or total (e.g., precipitation) core data from field instruments and processed field data (thirty minute or daily average or total. Data are programmed for IEEE4 4 byte floating point output (~ 7 digits), but actual precision values are not apparent in the program or in many instrument manuals.
Missing Data: Direct-from-field data time stamps are excluded if data are missing.
Instrument Name: 3-D Sonic Anemometer
Manufacturer: Campbell Scientific, Inc. (Logan, UT)
Model Number: CSAT3
Instrument Name: CO2/H2O Analyzer
Manufacturer: Li-Cor, Inc. (Lincoln, NE)
Model Number: LI-7500
Instrument Name: Net Radiometer
Manufacturer: Kipp & Zonen (Delft, The Netherlands)
Model Number: CNR1
Instrument Name: Barometric Pressure Sensor
Manufacturer: Vaisala (Helsinki, Finland)
Model Number: CS105
Instrument Name: Temperature and Relative Humidity Probe
Model Number: HMP45C
Instrument Name: Wind Sentry (Anemometer and Vane)
Manufacturer: R.M. Young (Traverse City, MI)
Model Number: 03001
Instrument Name: Tipping Bucket Rain Gage
Manufacturer: Texas Electronics, Inc. (Dallas, TX)
Model Number: TE525
Instrument Name: Quantum Sensor (PAR)
Model Number: LI-190
Instrument Name: Water Content Reflectometer
Model Number: CS616
Instrument Name: Soil Heat Flux Plate
Manufacturer: Radiation and Energy Balance Systems, Inc. (Bellevue, WA)
Model Number: HFT3
Instrument Name: Averaging Soil Thermocouple Probe
Model Number: TCAV
Instrument Name: Measurement and Control System (Datalogger)
Model Number: CR5000
Instrument Name: Levelogger and Barologger (Water Table)
Manufacturer: Solinst Canada Ltd. (Georgetown, ON, Canada)
Model Number: 3001 LT M10 and 3001 LT M1.5
Instrument Name: Mini-Diver, Cera-Diver, and Baro-Diver (Water Table)
Manufacturer: Van Essen Instruments ((Delft, The Netherlands)
Model Number: DI501, DI701, and DI500
Instrument Name: Krypton Hygrometer
Model Number: KH2O
Model Number: Q-7.1
Instrument Name: Pyranometer
Model Number: CM3
Instrument Name: Micrologger
Model Number: CR23X
Instrument Name: Submersible Sensor Pressure Transducer (Water Table)
Manufacturer: Electronic Engineering Innovations (Las Cruces, NM)
Model Number: 2.0 (2 m) and 5.0 (4 m)
a] Before ET is computed from LE, various standard corrections are applied. These include: coordinate rotation to align the wind vector with the sonic anemometer, corrections developed from frequency response relationships that incorporate sensor line averaging and separation (Massman corrections), and corrections to account for flux effects on vapor density as opposed to mixing ratio measurements. Corrections are made in a data analysis (Perl) program. See Cleverly, et al., Hydrological Processes 20: 3207-3225, 2006 for more detail and references.
b] On days in which 1-4 of the 30 min LE values are missing, a general linear regression model between LE and Rn is used to estimate missing data whenever the regression coefficient was significantly different from 0 (i.e. p > 0.5). ET is not calculated from LE on days that do not match the above criteria.
c] Other missing data required for derived data values, as well as out of range data are filtered out in data analysis (Perl) programs.
d] Closure of the energy balance is achieved by adding the measured Bowen Ration (H/LE) components to H and LE. Closure represents the error introduced when applying the energy balance method to estimate ET: closure = Rn - LE - H - G. The measured Bowen Ratio, H / LE, is used to parse the closure value into component H and LE values.
e] Soil water content data are calibrated with soil water content (% vol) values measured from field samples by linear regression in a data analysis (Perl) program.
f] Well loggers are pressure transducers that measure absolute pressure (barometric plus water column pressures). An on-site barometric pressure transducer suspended above the water table is calibrated to quantify pressure in units of elevation head, which is subtracted from absolute head to arrive at the actual water level.
g] Well data are calibrated using periodic manual measurements of water table elevations.
Prairie dogs are keystone species that impact both animals and plants in grassland habitats. They are a food resource for secondary consumers such as badgers, foxes, and raptors. Also, the mounds that they construct are home to many arthropod and reptile species that otherwise might not survive in grasslands. Both Gunnison’s and black-tailed prairie dogs can increase the number of plant species in grasslands and landscape heterogeneity with their ecosystem engineering that creates disturbed patches on the landscape. Gunnison’s prairie dogs, which were native herbivores at the Sevilleta National Wildlife Refuge (NWR) before their populations disappeared, were reintroduced at the Sevilleta NWR in 1997, 2005, and 2008. In 1998, a Gunnison’s prairie dog colony naturally established along the northern border on the east side of the Refuge. The naturally occurring colony and the colony that was reintroduced in 1997 have since then severely declined or gone locally extinct. Still, with the removal of cattle from the Sevilleta in 1973, the reintroductions of Gunnison’s prairie dogs in 2005 and 2008 provides an interesting opportunity to study how a native keystone herbivore affects a grassland habitat without the pressures and competition from livestock.
Three psuedo-replicates in a paired plot design: 1)plots where prairie dogs have been reintroduced and 2)control plots.Sampling Design
Each 100 x 100m plot contains 36 sample units (quads) that are 20m apart in a 6 x 6 grid. These quads are numbered in a zig zag pattern starting in the NE corner of the plot where the first six quads go north to south, the next six plots that are west of the first quads go south to north, and so on for the remaining quads on the plot. These quads are marked by a numbered rebar stake.Field/laboratory Procedures
A 50 x 50 cm quadrat separated into twenty-five 10 x 10 cm squares are placed southeast of a small white pvc pipe that marks permanent subplots. Then, percent covers and highest height are estimated for each plant species into palmtop computers. Species occupying less than 1%, a quarter of a 10 x 10 cm square, are recorded 0.1 %. When estimating plant species percent covers yellow and green plant material are included in the measurement. Individual plants that are completely gray, containing no yellow or green foliage, are not assessed in the percent cover estimate. For highest height, the ‘average’ height of the foliage for perennialspecies is recorded and for annual plant species the height to the top of the inflorescence, flowers and fruits,is recorded. The estimate of percent cover of disturbance from prairie dogs is the same as the plant cover estimates. Finally, all prairie dog fecal pellets that are in the quadrat, subplot, are counted.
Data were qa/qced and obvious errors were corrected. A column for height was added to the data since we added to the protocol a height measurement in 2009. We also added in 2008 prairie dog fecal counts and in 2009 prairie dog disturbance measurements. Previous data were explored to renter past height measurements along with adding disturbance and prairie dog fecal pellet counts to the data. These measurements were not recorded for all years. 11 January 2010 tlk
More information about who is involved with the samples/data: Mike Friggens 1999-September 2001Karen Wetherill February 7, 2000-Augst 2009Terri Koontz February 2000-August 2003 August 2006-PresentShana Pennington February 2000-August 2000Heather Simpson August 2000-August 2002Chris Roberts September 2001-August 2002Caleb Hickman September 9, 2002-November 15, 2004Seth Munson September 9, 2002-June 2004Maya Kapoor August 9, 2003-January 21, 2005 March 2010-March 2011Tessa Edelen August 15, 2004-August 15, 2005Charity Hall January 31, 2005-January 3, 2006Yang Xia January 31, 2005-PresentMichell Thomey September 3, 2005-August 2008Jay McLeod January 2006-August 2006Amaris Swann August 25, 2008-Jan 2013John Mulhouse August 2009-PresentAmanda Boutz August 2009-May 2010Stephanie Baker October 2010-PresentMegan McClung April 2013-Present
Additional Study Area Information
Study Area Name: Prairie Dog Town
Study Area Location: The study area is about 655 ha (~2.5 sq mi) in size and approximately1 km due west from the foothills of the Los Pinos Mountains. The study is also just north of the Blue Grama Core Site.Elevation: 1670 mSoils: sandy loam and sandy clay loamSite history: historically large prairie dog colonies inhabited the study area