Net primary production is a fundamental ecological variable that quantifies rates of carbon consumption and fixation. Estimates of NPP are important in understanding energy flow at a community level as well as spatial and temporal responses to a range of ecological processes. While measures of both below- and above-ground biomass are important in estimating total NPP, this study focuses on above-ground net primary production (ANPP). Above-ground net primary production is the change in plant biomass, including loss to death and decomposition, over a given period of time. Volumetric measurements are made using vegetation data from permanent plots collected in SEV297, "Extreme Drought in Grassland Ecosystems (EDGE) Net Primary Production Quadrat Data" and regressions correlating biomass and volume constructed using seasonal harvest weights from SEV157, "Net Primary Productivity (NPP) Weight Data."
Derivation of Biomass and Net primary Production:
Data from SEV297 and SEV157 are used to calculate the seasonal and annual production (i.e., biomass) of each species in each quadrat for a given year. Allometric equations derived from harvested samples of each species for each season are applied to the measured cover, height, and count of each species in each quadrat. This provides seasonal biomass for winter, spring, and fall.
Seasonal net primary production (NPP) is derived by subtracting the previous season's biomass from the biomass for the current season. For example, spring NPP is calculated by subtracting the winter weight from the spring weight for each species in a given quadrat. Negative differences are considered to be 0. Likewise, fall production is computed by subtracting spring biomass from fall biomass. Annual biomass is taken as the sum of spring and fall NPP.
The bounding box coordinates for the corners of the polygon which encompasses the full EDGE black site are:NW: -106.729227 34.337913 Decimal DegreesNE: -106.728434 34.337937 Decimal DegreesSW: -106.729144 34.337298 Decimal DegreesSE: -106.728392 34.337310 Decimal DegreesEDGE blue:NW: -106.622610 34.342141 Decimal DegreesNE: -106.621689 34.342079 Decimal DegreesSW: -106.623365 34.341518 Decimal DegreesSE: -106.622711 34.341015 Decimal Degrees
EDGE is located at six grassland sites that encompass a range of ecosystems in the Central US - from desert grasslands to short-, mixed-, and tallgrass prairie. We envision EDGE as a research platform that will not only advance our understanding of patterns and mechanisms of ecosystem sensitivity to climate change, but also will benefit the broader scientific community. Identical infrastructure for manipulating growing season precipitation will be deployed at all sites. Within the relatively large treatment plots (36 m2), we will measure with comparable methods, a broad spectrum of ecological responses particularly related to the interaction between carbon fluxes (NPP, soil respiration) and species response traits, as well as environmental parameters that are critical for the integrated experiment-modeling framework, as well as for site-based analyses. By designing EDGE as a research platform open to the broader scientific community, with subplots in all replicates (n = 180 plots) set-aside for additional studies, and by making data available to the broader ecological community EDGE will have value beyond what we envision here.
The six sites were selected to capture the key environmental and ecological gradients of Central US grasslands and represent the major grassland ecosystem types (desert, shortgrass, mixedgrass, and tallgrass) of the region. Site selection criteria included: site characteristics (mean annual precipitation and temperature, dominant vegetation), access and site security, permission to build experimental infrastructure, participation in an existing or future network (e.g., LTER, NEON), and available site support and supporting data (e.g., LTER, USFWS or ARS).
Experimental Treatments and Plots
Our approach will be to impose a significant reduction in growing season precipitation (-66 % of ambient) over a 4-yr period. This is the equivalent of a ca. 50% reduction in annual precipitation because at all sites about 60-75% of annual precipitation falls in the growing season. We will impose this long-term drought either by reducing the size of each rainfall event (event size reduction, E) or by reducing the number of events (delayed rainfall treatment, D).
The control (C) treatment is included for comparison. At each site, the ambient (C) rainfall pattern will be reduced in two ways to impose a severe drought over a 4-yr period.
For the event size reduction treatment (E), each rainfall event will be passively reduced by a fixed proportion. Note that rain event number and the average number of days between events does not differ from ambient treatment.
For the reduced event number (D) treatment, shelters roofs will be removable to permit periods of complete rain exclusion alternating with periods of ambient rainfall inputs. Here, a + 10 mm rule is used to determine when roofs are on or off. When the cumulative precipitation amount in this D treatment falls 10 mm below the E treatment, the roofs are removed until the cumulative precipitation total is 10 mm greater than the E treatment. In this way, total precipitation amounts will be similar at the end of the growing season, but event number will be reduced and the average number of days between events increased, with no change in event size compared to the C treatment.
At each site, we will establish replicate 6 x 6 m experimental plots (n = 10 per treatment, including the control treatment) in a relatively homogeneous area (similar soils, vegetation, etc.) that is representative of the overall site. Plots will be arrayed such that each treatment will be co-located in a single block (n=10 blocks per site), with each block located at least 5 m apart.
The blocking will help control for environmental gradients if present. For each site, all plots within a block (including the control) will be located at least 2 m apart and trenched to 1-1.5 m and surrounded by a 6 mil plastic barrier to hydrologically isolate them from the adjacent soil, and each plot will be covered by the rainfall manipulation infrastructure. The 6 x 6 m plot size includes a 0.5 m external buffer to allow access to the plots and minimize edge effects associated with the infrastructure. The resulting 5 x 5 m area will be divided into 4 2.5 x 2.5 m subplots. One subplot will be designated for plant species composition sampling, two will for destructive sampling (ANPP, belowground productivity, soil sampling, etc.), and the fourth set aside for opportunistic studies.
Rainfall Manipulation Infrastructure
We will passively alter rainfall reaching the plots by using a version of a rainfall reduction shelter (Fig. 6) designed by Yahdjian and Sala (2002). Versions of these shelters (ranging from ~2 to 100 m2 ) are being used by the co-PIs at the Sevilleta, Konza Prairie and Shortgrass Steppe LTERs, as well as by many other ecologists, and thus, they are proven technology. The most significant environmental artifacts of these shelters are a 5- 10% reduction in light due to the acrylic Vshaped shingles and a ~ 20 cm edge effect (Yahdjian and Sala 2002). Shelters will consist of a steel frame that supports a roof. To cover the 36 m2 plots, the shelters will be constructed as modular 3 x 3 m units, with four units per plot. The roof of each modular unit will be slanted at 15° toward the edge of the plot, creating a 6 m long peak along the mid-line of the plot, with two lower 6 m long edges with gutters to move rainwater away from the plots. The peaked roof will facilitate run-off of rainfall and access to the plot, and the lower edge will be oriented to the prevailing wind direction to minimize blow-in. Average leaf canopy height varies among the desert/short-, midand tallgrass prairie sites (~0.2 to 0.6 m), and to maintain a consistent roof-to-canopy distance, peak height of the shelters will be 1.3, 1.55 and 1.8 m, with lower edges of the shelters at 0.5, 0.75 and 1.0 m, respectively, for the four grassland types. Construction of the shelters will begin in Yr 1 (after pretreatment measurements are taken) and treatments will be operational by the early spring of YR 2. For the ESR treatment, the roof will consist of clear acrylic (high light transmission, low yellowness index, UV transparent) v-shaped shingles arrayed at a density to passively reducing each rainfall event by ~66% (Fig. 6). For the REN treatment, the roof will consist of clear, corrugated polycarbonate (high light transmission, low yellowness index, UV transparent) to completely exclude rainfall. For both treatments, the roofs will be constructed to facilitate easy removal via a clamping system. The REN treatment roofs will then be manually deployed and removed at intermittent intervals (see Fig. 6 for more detail). Ambient plots will have a deer netting roof to achieve an average reduction in light similar to the rainfall reduction roofs.
Plant species composition, species traits, stem density, and light availability
In the subplot designated for species composition, we will establish a permanent 2 x 2 m sampling plots, which will be divided into four 1 x 1m quadrats in which canopy cover of each species will be visually estimated to the nearest 1%. For each site, these measures will be repeated at least twice during the growing season of each year to sample early and late season species. Maximum cover values of each species will be used to determine richness, diversity and dominance and changes in composition, species turnover, and species associations over time.
Collecting the Data:
Net primary production data is collected twice each year, spring and fall, for both sites. Spring measurements are taken in April or May when shrubs and spring annuals have reached peak biomass. Fall measurements are taken in either September or October when summer annuals have reached peak biomass but prior to killing frosts. Winter measurements are taken in February before the onset of spring growth.
Vegetation data is collected on a palm top computer. A 1-m2 PVC-frame is placed over the fiberglass stakes that mark the diagonal corners of each quadrat. When measuring cover it is important to stay centered over the vegetation in the quadrat to prevent errors caused by angle of view (parallax). Each PVC-frame is divided into 100 squares with nylon string. The dimensions of each square are 10cm x 10cm and represent 1 percent of the total area.
The cover (area) and height of each individual live (green) vegetative unit that falls within the one square meter quadrat is measured. A vegetative unit consists of an individual size class (as defined by a unique cover and height) of a particular species within a quadrat. Cover is quantified by counting the number of 10cm x 10cm squares filled by each vegetative unit.
Niners and plexidecs are additional tools that help accurately determine the cover a vegetative unit. A niner is a small, hand-held PVC frame that can be used to measure canopies. Like the larger PVC frame it is divided into 10cm x 10cm squares, each square representing 1% of the total cover. However, there are only nine squares within the frame, hence the name “niner.” A plexidec can help determine the cover of vegetative units with covers less than 1%. Plexidecs are clear plastic squares that are held above vegetation. Each plexidec represents a cover of 0.5% and has smaller dimensions etched onto the surface that correspond to 0.01%, 0.05%, 0.1%, and 0.25% cover.
It is extremely important that cover and height measurements remain consistent over time to ensure that regressions based on this data remain valid. Field crew members should calibrate with each other to ensure that observer bias does not influence data collection.
Grasses-To determine the cover of a grass clump, envision a perimeter around the central mass or densest portion of the plant, excluding individual long leaves, wispy ends, or more open upper regions of the plant. Live foliage is frequently mixed with dead foliage in grass clumps and this must be kept in mind during measurement as our goal is to measure only plant biomass for the current season. In general, recently dead foliage is yellow and dead foliage is gray. Within reason, try to include only yellow or green portions of the plant in cover measurement while excluding portions of the plant that are gray. This is particularly important for measurements made in the winter when there is little or no green foliage present. In winter, sometimes measurements will be based mainly on yellow foliage. Stoloniferous stems of grasses that are not rooted should be ignored. If a stem is rooted it should be recorded as a separate observation from the parent plant.
Forbs, shrubs and sub-shrubs (non-creosote)-The cover of forbs, shrubs and sub-shrubs is measured as the horizontal area of the plant. If the species is an annual it is acceptable to include the inflorescence in this measurement if it increases cover. If the species is a perennial, do not include the inflorescence as part of the cover measurement. Measure all foliage that was produced during the current season, including any recently dead (yellow) foliage. Avoid measuring gray foliage that died in a previous season.
Cacti-For cacti that consist of a series of pads or jointed stems (Opuntia phaecantha, Opuntia imbricata) measure the length and width of each pad to the nearest cm instead of cover and height. Cacti that occur as a dense ball/clump of stems (Opuntia leptocaulis) are measured using the same protocol as shrubs. Pincushion or hedgehog cacti (Escobaria vivipara, Schlerocactus intertextus, Echinocereus fendleri) that occur as single (or clustered) cylindrical stems are measured as a single cover.
Yuccas-Make separate observations for the leaves and caudex (thick basal stem). Break the observations into sections of leaves that are approximately the same height and record the cover as the perimeter around this group of leaf blades. The caudex is measured as a single cover. The thick leaves of yuccas make it difficult to make a cover measurement by centering yourself over the caudex of the plant. The cover of the caudex may be estimated by holding a niner next to it or using a tape measure to measure to approximate the area.
Height is recorded as a whole number in centimeters. All heights are vertical heights but they are not necessarily perpendicular to the ground if the ground is sloping.
Annual grasses and all forbs-Measure the height from the base of the plant to the top of the inflorescence (if present). Otherwise, measure to the top of the green foliage.
Perennial grasses-Measure the height from the base of the plant to the top of the live green foliage. Do not include the inflorescence in the height measurement. The presence of live green foliage may be difficult to see in the winter. Check carefully at the base of the plant for the presence of green foliage. If none is found it may be necessary to pull the leaf sheaths off of several plants outside the quadrat. From this you may be able to make some observations about where green foliage is likely to occur.
Perennial shrubs and sub-shrubs (non-creosote)-Measure the height from the base of the green foliage to the top of the green foliage, ignoring all bare stems. Do not measure to the ground unless the foliage reaches the ground.
Plants rooted outside but hanging into a quadrat-Do not measure the height from the ground. Measure only the height of the portion of the plant that is within the quadrat.
Additional Information on the personnel associated with the Data Collection / Data Processing
Nathan Gehres 2014-present; Michell Thomey 2012-2014
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
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.
We used comparable experimental designs and sampling procedures at both URF and KPBS. 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.
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
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.
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).
Global climate change processes, especially prolonged droughts and increasingly high temperatures, are significantly affecting numerous arid ecosystems across the state of New Mexico. One of the more adversely affected ecosystems in New Mexico is piñon-juniper woodland (PJ), which includes areas near Mountainair, New Mexico, USA. Because changes in ambient temperature and decreases in water availability show pervasive effects on the above-ground status of existing PJ woodlands in New Mexico, it seems likely that the effects of changes in these two master variables will manifest themselves within soil processes such as soil organic matter (SOM) decomposition rates and soil respiration rates, as well as nutrient cycling rates and availabilities to both plants and soil microbial communities.
We conducted analyses of soil physicochemical properties and soil fungal biomass via soil ergosterol content, as well as evaluating the activity rates of multiple hydrolytic exoenzymes, which are indicative of fungal activity in soils. Samples were collected from multiple tree-to-tree competition gradients that were identified in May/June of 2011. These gradients were established based on the type of mycorrhizal fungus types expected to occupy the soil community established beneath the canopy of a focal tree, with there being two focal trees in each gradient. Gradients were established between two live piñon trees (Pinus edulis), two juniper trees (Juniperus monosperma), a live piñon and live juniper, and a dead piñon and live juniper. We only sampled from under live trees at the control site.
In order to obtain these samples, we collected soil samples from two different sites in a PJ woodland located within the boundaries of the Deer Canyon ranch. Changes in soil conditions were captured by sampling from the two sites at multiple times throughout the summer of 2011. We collected samples from Dr. Marcy Litvak’s girdled PJ woodland eddy-flux tower site in June, July, August and finally in late September. We also collected samples from Dr. Litvak’s control PJ woodland tower site in June and September of 2011. Significant differences in the activity rates of the hydrolytic exoenzymes alanine aminopeptidase, alkaline phosphatase, β-d-glucosidase, and β-N-acetyl glucosaminidase were observed within soils collected at multiple times from June through September when comparing the observed rates of activities under the trees in the live piñon to live piñon gradients vs. the juniper to juniper gradients. These differences were observed in samples from multiple dates at the girdled site without there being significant differences in soil fungal biomass across seasons or study sites. Continued work with the established sites on a year-to-year basis could provide an insight into how the fungal communities within New Mexican PJ woodlands will respond to future changes in soil conditions as global climate change processes advance in New Mexico.
Experimental design: Randomized complete block design was established at 2 different study sites, girdled piñon-juniper (PJ) woodland and non-girdled (control) PJ woodland. In late May, 2011, we set-up each study site to contain six complete blocks (plots), each with multiple tree-to-tree gradients. At the girdled PJ site, each plot included five different tree-to-tree gradients: Live pine to live pine, live pine to dead pine, live pine to live juniper, dead pine to live juniper, and live juniper to live juniper. At the control PJ site we also established 6 blocks (plots); however, at this site there were only three gradients: Live pine to live juniper, dead pine to live juniper, and live juniper to live juniper.
Setting up plots: Plots and gradients were established by marking sampling locations with orange flagging tape and pin-flags by Daniel Warnock and Kimberly Elsenbroek on May 19 and 23, 2011.
Sample collection, allocation and storage: Soil samples were collected monthly from the girdled PJ woodland to establish two pre-monsoonal (dry) season time points, with samples collected on June 6, 2011 and June 15, 2011 considered as being from single time point. Soil samples collected on July 20, 2011 represented our second dry season time point. Soil samples for our two post-monsoon moisture time points were collected on August 15, 2011 and September 28, 2011. As with the girdled site, soils sample from the control PJ woodland site were collected both before and after the onset of the monsoon season. However, unlike the girdled PJ woodland site, we only have one pre-monsoon time point June 29, 2011 and one post monsoon time point, September 15, 2011.
All soil samples were collected by combining three 0-10cm sub-samples into the same zipper-locking plastic storage bag. Samples were collected from three different locations within each tree-to tree gradient. Two of the three samples were collected from locations within 30cm of the trunk of each of the two focal trees within a gradient. The other sample for each gradient was collected from a point at the center of a zone formed by the edges of the canopies from the two competing focal trees. All samples were then transported to the lab for refrigeration.
Within 24-72 hours of sample collection, 5mL sub-samples were taken from each bulked soil sample and placed into individual Corning 15mL screw-cap centrifuge tubes. Each tube was then filled to the 10mL mark with an 0.8% KOH in Methanol solution. These tubes were placed in the fridge for storage until analyzed for ergosterol content. After preparation of the samples for ergosterol analyses, 1g samples were placed into 125mL round Nalgene bottles for analyses of fungal exoenzyme actitity (EEA) rates from each sample. All enzyme activity assays were performed within 1 to 5 days after collection. Further, for all but the final post-monsoonal time points, assays were performed within 2 to 3 days of sample collection.
After all of the fresh, refrigerated samples were alloquated for ergosterol and EEA analyses we placed the remaining quantities of soil for each sample into labeled paper bags for air-drying on a lab bench. After 1-2 weeks, 30g of each sample was placed into a labeled plastic bag for shipping to Ithaca, New York, USA for analyses of soil-physicochemical properties. While taking the 30g sub-samples, a separate 5g sub-sample from the air-dried sample was placed into a labeled, no. 1 coin-envelope for storage until analysis of soil hyphal abundance. After all sub-sampling was completed any remaining soil was kept in its sample bag and stored in the lab.
Hydrolytic exoenzyme activity (EEA) assays: All hydrolytic EEA assays were performed as follows: Each 125mL sample bottle was partially filled with 50mM sodium bicarbonate buffer solution and homogenized using a Kinematica Polytron CH 6010 (Lucerne, Switzerland). Upon homogenization, sample bottles were filled to 125mL with buffer solution. Sample bottles were then set aside until placement in black, 96-well, micro-plates. At the time of placement, each sample suspension was poured into a glass crystalizing dish where it was stirred at high speed into the appropriate columns within each micro-plate. These columns included a quench control (200 uL sample suspension + 50uL MUB or methylcoumrin substrate control), a sample control (200uL sample suspension + 50uL 50mM bicarbonate buffer) and an assay column (200uL suspension + 50ul 200mM substrate). Samples were pipetted into four sets of plates with each set analyzing the activity rates of a single hydrolytic enzyme. These enzymes included alanine amino peptidase, alkaline phosphatase, β-d-glucosidase, and N-acetyl-β-d-glucosiminidase. Further, all three samples from a single gradient within a single plot were added to the same plate (e.g., all samples from the live-pine-to-live-pine gradient from plot one were pipetted into a single plate for analyzing the activity of the enzyme alkaline-phospotase.
Ultimately our plate layout was completed as follows usingt two other columns for substrate controls: In column one, we added 200uL buffer and 50uL of a substrate standard, which accounts for the fluorescence emitted by either the MUB, or the methylcoumarin group that is a component of the substrate solution added to the assay wells. In column six of each plate was a substrate control, which is a solution of 200uL buffer and 50uL of one the four different substrates used in our hydrolytic EEA assays. Columns 3-5 were our quench controls, which accounts for the quantity of fluorescence emitted by the MUB or methylcoumarin molecule absorbed by the particles in the soil suspension itself. Columns 7-9 were the sample controls and account for the amount of fluorescence emitted by the soil suspension + buffer solution added to each well. Finally, columns 10-12 were our assay wells. From these wells we could determine enzyme activity by measuring the fluorescence emitted by the MUB or methylcoumarin molecules cleaved off of the substrates initially added to each well. The substrates included in these assays included: 7-amino-4-methylcoumarin (Sigma-Aldrich), 4-MUB-phosphate (Sigma-Aldrich), 4-MUB-β-d-glucoside (Sigma-Aldrich), and 4-MUB-N-acetyl-β-d-glucosiminide (Sigma-Aldrich).
Because the intrinsic EEA rates varied across our targeted exoenzymes, assay plates were scanned for flourscence in sets of two. Alanine aminopeptidase plates and alkaline phosphatase plates were scanned twice, first at 30-40 minutes after substrate addion and again at 50-80 minutes after substrate addition. β-d-glucosidase, and N-acetyl-β-d-glucosiminidase plates were all scanned at 3-4 hours after substrate addition. The timing of the second enzyme activity time point depended on expected soil moisture conditions. Here, the post monsoon soils were allowed to incubate for a total of 5-6 hours prior to the second scan and the pre-monsoon plates were incubated for a total of 7-9 hours.
Fungal biomass measurements: Fungal biomass was quantified by measuring the concentration of ergosterol in a sub-sample taken from each soil sample collected from June to September. Within 24-72 hours of sample collection, 5mL sub-samples were taken from each bulked soil sample and placed into individual Corning 15mL screw-cap centrifuge tubes. Each tube was filled to the 10mL mark with an 0.8% KOH in methanol solution. Tubes were refrigerated for storage until analyzed for fungal biomass by measuring the ergosterol content within each sample. Ergosterol concentration for each sample was determined using HPLC with 100% methanol as the solvent at a flow rate of 1.5mL/ minute and a c-18 column. Ergosterol was quantified by measuring the peak height that passed through a detector set to measure absorbance at 282nm, at 3.7min after the sample was injected into the column. The height of each peak was then converted into μg ergosterol/g soil and finally converted to mg fungal biomass/ g soil by applying a conversion factor.
* Instrument Name: Polytron
* Manufacturer: Kinematica
* Model Number: CH 6010
* Instrument Name: GeoXT
* Manufacturer: Trimble
* Model Number: GeoExplorer 3000 series
* Instrument Name: fmax
* Manufacturer: Molecular devices
* Model Number: type 374
* Instrument Name: versamax tunable micro-plate reader
* Manufacturer: molecular devices
* Model Number: ?
* Instrument Name: SSI 222D isocratic HPLC pump
* Manufacturer: SSI
* Model Number: 222D
* Instrument Name: Thermo Seperation Products AS 1000 autosampler
* Manufacturer: Thermo Seperation Products
* Model Number: AS 1000
* Instrument Name: Acutect 500 UV/Vis Wavelength detector
* Manufacturer: Acutect
* Model Number: 500
* Instrument Name: HP 3396 series iii integrator
* Manufacturer: Hewlitt Packard
* Model Number: 3396
Girdled and control PJ woodland: 34.36N, 106.27W.
Girdled PJ woodland sampled: 6/June/2011, 15/June/2011, 20/July/2011, 15/Aug/2011, 28/Sept/2011.
Control PJ woodland sampled: 29/June/2011, 15/Sept/2011.
Plant species can differentially shape soil biota and abiotic conditions. In some grasslands, edaphic factors are more influential on microbial communities than biotic interactions. Arid grasses are intimately linked with a hyphal network that delivers substantial water and nutrients to plant roots. Examining microbial activities associated with dominant grasses determines how individual plant species shape ecosystem processes and how these processes may be affected as plant communities change. If microbial activity is consistent between different plant species, then microbial activity is largely controlled by edaphic factors, and microbial mediated ecosystem processes may not be affected if plant communities change. If microbial activity varies between plant species, it is controlled by differential plant properties and microbial mediated ecosystem processes would presumably change as plant communities change. The main research questions for this project were 1) does microbial activity vary between dominant semiarid grasses, and 2) is microbial activity driven mainly by edaphic or plant species-specific attributes?
There are five monocultures of each of seven grasses (35 plots) for total of 95 plot. There are 55 plots that have two species: Each of the five non-blue and black species will be planted with blue grama and black grama. Blue and black grama will also be planted together, for a total of 11 species interaction treatments, which will also be replicated five times. The plots will be 2 x 2.5 meters to allow the 0.5 meter strip on one side of the plot to be used in invasion future experiments.
The seven species planted:
Reseeded four species in July 2008. The species planted in each plot can be found in the plot treatment are: Sporobolus cryptandrus, sand_dropseed, Bouteloua gracilis, Blue gramaOryzopsis hymenoides, Indian_ricegrass, Hilaria jamesii, galleta, Aristida purpurea, purple_threeawn, Bouteloua eriopoda, Black gramma, Bouteloua curtipendula, Side oats grama. We reseeded four species in July of 2008.
Only monoculture plots of Bouteloua eriopoda, Bouteloua gracilis and Aristida Purpurea were utilized for this project. Soil samples were collected from the rhizosphere and interspaces between plants. Four soil cores (1cm wide, 3 cm deep) were taken across the plot and mixed together for each sample. Enzyme activity in the rhizosphere and interspace were analyzed separately. Samples were refrigerated and processed within 48 hours of collection to prevent enzyme degradation. Soils were subsampled for organic matter and water content. Field soil moisture was calculated by comparing weights of freshly collected soil and soil dried at 60 °C. A subsample was also burned at 500 °C for 4 hours to determine percent organic matter. The potential activity levels of beta-glucosidase, beta-N-acetylglucosaminidase, alanine aminopeptidase, alkaline phosphatase, and phenol oxidase were measured in the lab following the methods of Stursova et al. (2006).
The varied topography and large elevation gradients that characterize the arid and semi-arid Southwest create a wide range of climatic conditions - and associated biomes - within relatively short distances. This creates an ideal experimental system in which to study the effects of climate on ecosystems. Such studies are critical givien that the Southwestern U.S. has already experienced changes in climate that have altered precipitation patterns (Mote et al. 2005), and stands to experience dramatic climate change in the coming decades (Seager et al. 2007; Ting et al. 2007). Climate models currently predict an imminent transition to a warmer, more arid climate in the Southwest (Seager et al. 2007; Ting et al. 2007). Thus, high elevation ecosystems, which currently experience relatively cool and mesic climates, will likely resemble their lower elevation counterparts, which experience a hotter and drier climate. In order to predict regional changes in carbon storage, hydrologic partitioning and water resources in response to these potential shifts, it is critical to understand how both temperature and soil moisture affect processes such as evaportranspiration (ET), total carbon uptake through gross primary production (GPP), ecosystem respiration (Reco), and net ecosystem exchange of carbon, water and energy across elevational gradients.
We are using a sequence of six widespread biomes along an elevational gradient in New Mexico -- ranging from hot, arid ecosystems at low elevations to cool, mesic ecosystems at high elevation to test specific hypotheses related to how climatic controls over ecosystem processes change across this gradient. We have an eddy covariance tower and associated meteorological instruments in each biome which we are using to directly measure the exchange of carbon, water and energy between the ecosystem and the atmosphere. This gradient offers us a unique opportunity to test the interactive effects of temperature and soil moisture on ecosystem processes, as temperature decreases and soil moisture increases markedly along the gradient and varies through time within sites.
Data for this project can be found on the website: http://ameriflux.ornl.gov/
Data collection follows Ameriflux protocols.
Seasonal environments experience cyclical or unpredictable pulses in plant growth that provide important resources for animal populations, and may affect the diversity and persistence of animal communities that utilize these resources. The timing of breeding cycles and other biological activities must be compatible with the availability of critical resources for animal species to exploit these resource pulses; failure to match animal needs with available energy can cause population declines. Adult Gunnison’s prairie dogs emerge from hibernation and breed in early spring, when plant growth is linked to cool-season precipitation and is primarily represented by the more nutritious and digestible plants that utilize the C3 photosynthetic pathway. In contrast, summer rainfall stimulates growth of less nutritious plants using the C4 photosynthetic pathway. Prairie dogs should therefore produce young during times of increased productivity from C3 plants, while pre-hibernation accumulation of body fat should rely more heavily upon C4 plants. If seasonal availability of high-quality food sources is important to Gunnison’s prairie dog population growth, projected changes in climate that alter the intensity or timing of these resource pulses could result in loss or decline of prairie dog populations. This project will test the hypothesis that population characteristics of Gunnison's prairie dog, an imperiled grassland herbivore, are associated with climate-based influences on pulses of plant growth.
Gunnison’s prairie dogs will be monitored at 6 colonies, with 3 colonies each occurring with the range of prairie and montane populations. Colonies for study within the prairie populations occur at Sevilleta National Wildlife Refuge (n = 3 prairie populations) and at Vermejo Park Ranch (n = 3 montane populations). Live-trapping of prairie dogs will be conducted during 3 periods of the active seasons—following emergence (April), after juveniles have risen to the surface (mid-to-late June), and pre-immergence (beginning in August). Trapping will occur for 3-day periods, following pre-baiting with open traps. At capture, sex and body mass of each individual will be recorded. Blood and subcutaneous body fat samples will be collected nondestructively for analysis of isotopic composition. Prairie dogs will be marked with dye, and released on site immediately following processing. After trapping periods at each site have concluded, population counts will be conducted during 2-3 re-sighting (or recapture) periods for each prairie dog colony. Resighting observation periods will be ~3 hours in length, and consist of 2-6 systematic scans of the entire colony, beginning and ending from marked points outside of the colony boundary. During each observation period, prairie dogs will be counted, recorded as marked or unmarked, and location on the colony noted.
Vegetation cover and composition measurements will be collected (or obtained at Sevilleta, where such data is already being collected) during pre- and post-monsoon periods of the active season. Total cover will be measured by plant species (or to genus if species is indeterminable). Total cover will be measured at 12 grid points per colony using Daubenmire frames (0.5 m x 0.5 m), and at 12 grid locations 200-800 m outside of each colony boundary. Adjacent to each Daubenmire frame, a 20 cm x 30 cm sample of vegetation will be clipped and dried for determination of volumetric moisture content of vegetation.
Primary productivity variables (cover, moisture content) will be tested for correlations to individual and population-level condition indicators in prairie dogs. Carbon isotope ratios (δ13C) from prairie dog blood and fat samples will be analyzed on a continuous flow isotope ratio mass spectrometer. The relative contribution of C3 and C4 plants to the diet of each individual will be determined based upon δ13C ratios for C3 and C4 plants in the study area and a 2-endpiont mixing model, and will be calculated for each individual animal, population and season. Population estimates will be calculated using mark-resight estimates, and compared to maximum above-ground counts. The influence of resource pulses on prairie dog population parameters will be tested by comparing the vegetation cover, moisture content, and ratio of total C3:C4 plant cover to the ratio of C3:C4 plants in prairie dog diets, population estimates, and juvenile:adult ratios as an index to population recruitment.
*Instrument Name: Continuous flow isotope ratio mass spectrometer
*Manufacturer: Thermo-Finnigan IRMS Delta Plus
*Instrument Name: Elemental Analyzer
*Model Number: ECS4010
Other Field Crew Members: Talbot, William; Duran, Ricardo; Gilbert, Eliza; Donovan, Michael; Nichols, Erv; Sevilleta LTER prairie dog field crew led by Koontz, Terri; Sevilleta NWR prairie dog field crew led by Erz, Jon.
Tissue samples are analyzed for stable carbon isotope ratios in stable isotope laboratory operated by Dr. Zachary Sharp and Dr. Nicu-Viorel Atudorei of the Department of Earth and Planetary Sciences, University of New Mexico.
The primary objective of this study is to examine the control that substrate quality and climate have on patterns of long-term decomposition and nitrogen accumulation in above- and below-ground fine litter. Of particular interest will be to examine the degree these two factors control the formation of stable organic matter and nitrogen after extensive decay.
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