Woody plant encroachment of grassland ecosystems is a geographically extensive phenomenon that can lead to rapid land degradation and significantly alter global biogeochemical cycles, and this ecosystem change has been particularly well documented in the desert grassland of the southwestern United States. Fires are known to decrease vegetation cover and increase soil erodibility, and the shifts in wildfire regimes are currently occurring in Chihuahuan Desert. It is generally recognized that the invasion of woody vegetation into grasslands and savannas will increase the carbon stored in arid ecosystems. However, carbon storage may be complicated by disturbance such as wildfire, which alters the distribution and amount of C pools in the drylands. The relative distribution of each vegetation type to the soil C pool and its variability after fires are not well-understood in this ecosystem. This research will investigate the variations of SOC and its vegetation source partition at microsite scale in the woody shrub encroached grassland after the occurrence of fire, which will provide further information on wildfire’s influence on soil C pool dynamics in arid and semiarid lands. The post-fire changes of the spatial pattern of SOC and vegetation contributions in the shrub encroached grassland will be analyzed using a geostatistical method outlined in Guan et al. (2018). Overall, understanding the post-fire redistribution and sources of SOC may provide insights on the important role played by fire, aeolian processes and vegetation in the dynamics of desert grassland ecosystems.
A 100 m × 100 m monitoring area was established in March 2016. A prescribed fire was set to burn the monitoring area on March 10, 2016, the beginning of the windy season, to create the burned treatment. Within each (5 m × 5 m) sampling plot, 50 randomly distributed soil samples were collected from the top 5 cm of the soil profile. The coordinates of the sampling locations were randomly generated and a different set of sampling locations was used for each sampling period.
Data were collected during the following time periods:
2016/03/11 - 2016/03/13
2016/06/14 - 2016/06/16
2017/03/17 - 2017/03/19
2017/06/26 - 2017/06/28
Instrument Names: Meter stick, shovel, sampling bags, ball mill, element analyzer.
Manufacturer: ball mill (PBM-04 Planetary Ball Mill, RETSCH, Germany), element analyzer (FLASH 2000 OEA, Thermal Fisher Scientific, USA).
Model Number: PBM-04 Planetary Ball Mill, FLASH 2000 OEA
Each sample was analyzed three times and the results were averaged.
We greatly acknowledge the contributions of Jon Erz, Eric Krueger and Andy Lopez (FWS, SNWR), Scott Collins and Amaris Swan (Sevilleta LTER, New Mexico, USA), Julie McDonald and Bethany Theiling (The University of Tulsa) for their assistance in field work and laboratory analysis.
The site is a black grama (Bouteloua eriopoda) dominated grassland with creosote bush shrubs (Larrea tridentata), and the soil is primarily sandy loam. This sampling area is large enough to capture the heterogeneity in the landscape comprising of shrub, grass and bare soil microsites.
The soil TC and TN results of the same field site can be found in Guan et al., 2018. Ecosystems (Post-fire Redistribution of Soil Carbon and Nitrogen at a Grassland– Shrubland Ecotone).
The Monsoon Rainfall Manipulation Experiment (MRME) is designed to understand changes in ecosystem structure and function of a semiarid grassland caused by increased precipitation variability, by altering rainfall pulses, and thus soil moisture, that drive primary productivity, community composition, and ecosystem functioning. The overarching hypothesis being tested is that changes in event size and frequency will alter grassland productivity, ecosystem processes, and plant community dynamics. Treatments include (1) a monthly addition of 20 mm of rain in addition to ambient, and a weekly addition of 5 mm of rain in addition to ambient during the months of July, August and September. It is predicted that changes in event size and variability will alter grassland productivity, ecosystem processes, and plant community dynamics. In particular, we predict that many small events will increase soil CO2 effluxes by stimulating microbial processes but not plant growth, whereas a small number of large events will increase aboveground NPP and soil respiration by providing sufficient deep soil moisture to sustain plant growth for longer periods of time during the summer monsoon.
MRME contains three ambient precipitation plots and five replicates of the following treatments: 1) ambient plus a weekly addition of 5 mm rainfall, 2) ambient plus a monthly addition of 20 mm rainfall. Rainfall is added during the monsoon season (July-Sept) by an overhead (7 m) system fitted with sprinkler heads that deliver rainfall quality droplets. At the end of the summer, each treatment has received the same total amount of added precipitation, delivered in different sized events. Each plot (9x14 m) includes subplots (2x2 m) that receive 50 kg N ha-1 y-1. Each year we measure: (1) seasonal (July, August, September, and October) soil N, (2) plant species composition and ANPP, (3) annual belowground production in permanently located root ingrowth cores, and (4) soil temperature, moisture and CO2 fluxes (using in situ solid state CO2 sensors).
Soil temperature is measured with Campbell Scientific CS107 temperature probes buried at 2 and 8 cm In the soil. Soil volume water content, measured with Campbell Scientific CS616 TDR probes is an integrated measure of soil water availability from 0-15 cm deep in the soil. Soil CO2 is measured with Vaisala GM222 solid state CO2 sensors. For each plot, soil sensors are placed under the canopy of B. eriopoda at three depths: 2, 8, and 16 cm. Measurements are recorded every 15 minutes.
CO2 fluxes are calculated using the CO2, temperature, and moisture data, along with ancillary variables following the methods of Vargas et al (2012) Global Change Biology
Values of CO2 concentration are corrected for temperature and pressure using the ideal gas law according to the manufacturer (Vaisala). We calculate soil respiration using the flux-gradient method (Vargas et al. 2010) based on Fick’s law of diffusion where the diffusivity of CO2 is corrected for temperature and pressure (Jones 1992) and calculated as a function of soil moisture, porosity and texture (Moldrup et al. 1999).
Instrument Name: Solid State Soil CO2 sensor
Model Number: GM222
Instrument Name: Temperature Probe
Manufacturer: Campbell Scientific
Model Number: CS107
Instrument Name: Water Content Reflectometer Probe
Manufacturer: Campbell Scientific
Model Number: CS616
Additional Study Area Information
Study Area Name: Monsoon site
Study Area Location: Monsoon site is located just North of the grassland Drought plots
Vegetation: dominated by black grama (Bouteloua eriopoda), and other highly prevalent grasses include Sporabolus contractus, S.cryptandrus, S. lexuosus, Muhlenbergia aernicola and Bouteloua gracilis.
Humans are creating significant global environmental change, including shifts in climate, increased nitrogen (N) deposition, and the facilitation of species invasions. A multi-factorial field experiment is being performed in an arid grassland within the Sevilleta National Wildlife Refuge (NWR) to simulate increased nighttime temperature, higher N deposition, and heightened El Niño frequency (which increases winter precipitation by an average of 50%). The purpose of the experiment is to better understand the potential effects of environmental drivers on grassland community composition, aboveground net primary production and soil respiration. The focus is on the response of two dominant grasses (Bouteloua gracilis and B eriopoda), in an ecotone near their range margins and thus these species may be particularly susceptible to global environmental change.
It is hypothesized that warmer summer temperatures and increased evaporation will favor growth of black grama (Bouteloua eriopoda), a desert grass, but that increased winter precipitation and/or available nitrogen will favor the growth of blue grama (Bouteloua gracilis), a shortgrass prairie species. Treatment effects on limiting resources (soil moisture, nitrogen availability, species abundance, and net primary production (NPP) are all being measured to determine the interactive effects of key global change drivers on arid grassland plant community dynamics and ecosystem processes.
On 4 August 2009 lightning ignited a ~3300 ha wildfire that burned through the experiment and its surroundings. Because desert grassland fires are patchy, not all of the replicate plots burned in the wildfire. Therefore, seven days after the wildfire was extinguished, the Sevilleta NWR Fire Crew thoroughly burned the remaining plots allowing us to assess experimentally the effects of interactions among multiple global change presses and a pulse disturbance on post-fire grassland dynamics.
This data set provides soil N availability in each plot of the warming experiment for the monsoon season (also see SEV176).
Our experimental design consists of three fully crossed factors (warming, increased winter precipitation, and N addition) in a completely randomized design, for a total of eight treatment combinations, with five replicates of each treatment combination, for a total of 40 plots. Each plot is 3 x 3.5 m. All plots contain B. eriopoda, B. gracilis and G. sarothrae. Our nighttime warming treatment is imposed using lightweight aluminum fabric shelters (mounted on rollers similar to a window shade) that are drawn across the warming plots each night to trap outgoing longwave radiation. The dataloggers controlling shelter movements are programmed to retract the shelters on nights when wind speeds exceed a threshold value (to prevent damage to shelters) and when rain is detected by a rain gauge or snow is detected by a leaf wetness sensor (to prevent an unintended rainout effect).
Each winter we impose an El Nino-like rainfall regime (50% increase over long-term average for non-El Nino years) using an irrigation system and RO water. El Nino rains are added in 6 experimental storm events that mimic actual El Nino winter-storm event size and frequency. From January-March, there are 4x5mm applications, 1x10mm application and 1x20mm application. For N deposition, we add 2.0 g m-2 y-1 of N in the form of NH4NO3 because NH4 and NO3 contribute approximately equally to N deposition at SNWR (57% NH4 and 43% NO3; Báez et al., 2007, J Arid Environments). The NH4NO3 is dissolved in 12 liters of deionized water, equivalent to a 1 mm rainfall event, and applied with a backpack sprayer prior to the summer monsoon. Control plots receive the same amount of deionized water.
Soil N is measured using Plant Root Simulator Probes (PRS® Probes, Western Ag Innovations, Saskatoon, Saskatchewan, Canada https://www.westernag.ca/innov).
Probes are installed in late June or early July prior to the monsoon season and removed in October each year.
Study Area Name: Warming site
Study Area Location: Within the Sevilleta, the site is located just Northeast of Deep Well meteorological station. The site can be reached by parking on the main road next to the signs for deep well and the minirhiztron study. Note that the road to Deep Well met station does not permit vehicles. Travel on foot towards deep well and look for a well-trod path off to the right shortly before the met station.
Vegetation: The vegetation is Chihuahuan Desert Grassland, dominated by black grama (Bouteloua eriopoda & B. gracilis).
The Monsoon Rainfall Manipulation Experiment (MRME) is designed to understand changes in ecosystem structure and function of a semiarid grassland caused by increased precipitation variability, by altering rainfall pulses, and thus soil moisture, that drive primary productivity, community composition, and ecosystem functioning. The overarching hypothesis being tested is that changes in event size and frequency will alter grassland productivity, ecosystem processes, and plant community dynamics. Treatments include (1) a monthly addition of 20 mm of rain in addition to ambient, and a weekly addition of 5 mm of rain in addition to ambient during the months of July, August and September. We predict that soil N availability with interact with rainfall event size to alter net primary productivity during the summer monsoon. Specifically, productivity will be higher on fertilized relative to control plots, and productivity will be highest on N addition plots in treatments with a small number of large events because these events infiltrate deeper and soil moisture is available longer following large compared to small events.
MRME contains three ambient precipitation plots and five replicates of the following treatments:
1) ambient plus a weekly addition of 5 mm rainfall, 2) ambient plus a monthly addition of 20 mm rainfall.
Rainfall is added during the monsoon season (July-Sept) by an overhead (7 m) system fitted with sprinkler heads that deliver rainfall quality droplets. At the end of the summer, each treatment has received the same total amount of added precipitation, delivered in different sized events.
Each plot (9x14 m) includes subplots (2x2 m) that receive 50 kg N ha-1 y-1. Each year we measure: (1) seasonal (July, August, September, and October) soil N, (2) plant species composition and ANPP, (3) annual belowground production in permanently located root ingrowth cores, and (4) soil temperature, moisture and CO2 fluxes (using in situ solid state CO2 sensors).
Soil Measurements: We use plant root simulator probes (PRS® Probes, Western Ag Innovations, Saskatoon, Saskatchewan, Canada https://www.westernag.ca/innov).
Instrumentation: Plant root simulator probes
On August 4th, 2009, lightning ignited a ~3300 ha wildfire that burned through the entire experiment and its surroundings allowing us to assess experimentally the effects of interactions among rainfall pulse dynamics and wildfire on post-fire grassland dynamics and ecosystem processes.
Data was not collected in 2011.
Study Area Name: Monsoon site
Study Area Location: Monsoon site is located just North of the grassland Drought plots
Vegetation: dominated by black grama (Bouteloua eriopoda), and other highly prevalent grasses include Sporabolus contractus, S.cryptandrus, S. lexuosus, Muhlenbergia aernicola and Bouteloua gracilis.
This dataset consists of profiles of soil water potential measured via in situ thermocouple psychrometers located within a rainfall manipulation experiment in a piñon-juniper woodland. The sensors are centrally located within 40 m x 40 m water addition, water removal, infrastructure control, and ambient control plots. The profiles are installed under each of ten target piñon and juniper trees (five of each species) which were also used for other physiological measurements, as well as at five intercanopy areas. The raw sensor output (in μV) has been temperature-corrected and individual calibration equations applied.
Background: This sensor array is part of a larger experiment investigating the mechanisms of drought-related mortality in the piñon-juniper woodland. Briefly, one hypothesis is that, during periods of extended, very-negative, soil water potential (“drought”) trees experience xylem tensions greater than their threshold for cavitation, lose their hydraulic connection to the soil, dessicate and die. A second hypothesis is that in order to avoid this hydraulic failure, trees restrict water loss via reduction in stomatal conductance which also limits the diffusion of CO2 for photosynthesis, and eventually may starve to death depending on the drought duration.
The goal of the project is to apply drought stress on an area significantly larger than the scale of individual trees to determine whether hydraulic failure or carbon starvation is a more likely mechanism for mortality under drought conditions. The cover control treatment replicates the microenvironment created under the plastic rainfall removal troughs (slightly elevated soil and air temperatures and relative humidity) without removing ambient precipitation. The water addition treatment is intended to simulate 150% of the 30-yr average rainfall via n = 6 19-mm super-canopy applications during the growing season (April-October). More details on the experiment can be found in Pangle et al. 2012 Ecosphere 3(4) 28 (http://dx.doi.org/10.1890/ES11-00369.1). These three treatments, in addition to an ambient control with no infrastructure, are applied to three replicated blocks, one on relatively level terrain, one on a southeast-facing slope, and one on a north-facing slope. The soil psychrometers were installed in the southeast-facing block only, to measure the effectiveness of the treatments on plant-available soil moisture.
For the purposes of comparing soil water potential under various cover types (piñon, juniper, intercanopy), it should be noted that significant tree mortality has occurred on Plot 10. As described below, on 5 August 2008 the site was struck by lightening and many of the soil psychrometers were rendered inoperable. At approximately the same time, four of the five target piñon trees in the southeast-facing drought plot (Plot 10) started browning and it was discovered that they had bark beetle (Ips confusus) galleries and were infected with Ophiostoma fungi. By October 2008 those trees (T1, T2, T4, and T5) had dropped all their needles. Therefore the psychrometers buried under them were no longer located “under trees” after that time. By June 2009 the remaining target piñon (T3) died. By March 2010, one of the target juniper trees (T10) had died. At the time of this writing (April 2011) it is anticipated that more of the juniper trees on P10 will die during this year.
Methods: Within Plots 9-12 of the larger PJ rainfall manipulation experiment, thermocouple psychrometers (Wescor Inc., Logan, UT, USA) were installed. Soil psychrometers profiles were placed under each of the initial ten target trees in each plot, and at the same five intercanopy areas that were instrumented to measure soil and air temperature and soil volumetric water at 5 cm depth. Each profile consisted of sensors at (1) 15 cm; (20) cm; and (3) as deep as could be augered and installed by hand, generally 50-100 cm depth. Sensors were calibrated with four NaCl solutions of known water potential before field deployment.
Sensors are controlled via a Campbell Scientific CR-7 datalogger (Campbell Scientific, Logan, UT, USA). The datalogger takes measurements every 3 h but soil water potential does not change that fast and the daytime measurements are generally unusable because of thermal gradients between the datalogger and the sensors, therefore the data presented here are only the 3:00 AM timepoints.
Note that on 5 August 2008 the site was struck by lightening. Many of the soil psychrometers were destroyed by ground current, with the worst damage on the drought and cover control plots where the metal support posts for the infrastructure may have helped to propagate ground current. Some of those sensors were eventually replaced but in the case of the infrastructure plots we were limited to installing new sensors between the plastic troughs because it was impossible to auger under the plastic. Therefore, while the original installation was random with regard to the pattern of plastic domes and troughs, the replacement installation was exclusively outside the plastic and the data may therefore be biased towards wetter microsites.
Instrument Name: thermocouple psychrometer with stainless steel screen
Manufacturer: Wescor, Inc, Logan, UT, USA
Model Number: PST-55
The purpose of this project is to: 1.) determine how biological soil crust (BSC) cover changes along an elevation gradient and across seasons, 2.) determine how carbon and nitrogen exchanges of BSC communities vary with temperature along an elevation gradient in arid and semi-arid environments and, 3.) use photosynthetic and respiration rates of BSC communities to determine how the contribution of the BSC communities to whole ecosystem carbon exchange varies across the same gradient and over seasons.
At each sampling site and sampling period a small amount of surface crust (approx. one teaspoonful per sample) was taken from each of 10 locations at approximately 1 meter intervals over a transect. Samples were transported back to the laboratory in plastic bags.
On rare occasions we removed a larger sample, 0.5 liter volume or less, at one or two sampling stations.
Study sites included: Flux tower sites, desert grassland, desert shrubland, juniper savanna, piñon-juniper woodland, ponderosa pine forest, and mixed conifer forest.
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.
Soil temperature impacts both the abiotic and biotic processes at our site. The rate of evaporation, soil water content, VPD, and many other environmental factors are directly or indirectly affected by the temperature of the system. By monitoring the soil temperature at our site, we were able to determine its influence on the target trees and their associated physiological functions. Differences in soil temperature between plots can be impacted by the drought and cover-control structures used in our rainfall-manipulation treatments. Therefore, measuring soil temperatures in all three cover types and all four treatment regimes also allowed us to tease-out the temperature differences that were an artifact of the treatment structures as opposed to the actual treatments.
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. During subsequent years (2009-2012), a total of four to six irrigation events (19mm each) were applied (please contact Will Pockman and/or Robert Pangle for specific application dates and rates).
Site Abiotic Monitoring
We utilized Campbell Scientific dataloggers to continuously monitor and record abiotic conditions and physiological measurements across the site. All systems were connected to a solar-powered wireless network with NL100 relays (Campbell Scientific, Logan, UT). Plots were instrumented with CR-1000, CR-7, and CR-10X dataloggers (Campbell Scientific, Logan, UT). Each CR-1000 datalogger was accompanied by AM25T and AM 16/32 multiplexers to expand sensor measurement capacity (Campbell Scientific, Logan, UT). Abiotic conditions were measured under each cover type (n=3-5 locations per cover type): under piñon, juniper, and intercanopy areas between trees. These measurements included; a) soil temperature (TS) at –5 cm depth and shielded air temperature (TA) at 10 cm (above soil surface), both measured with 24 gauge Type–T thermocouples (Omega, Stamford, CT), b) shallow soil volumetric water content (VWC) at –5 cm measured using EC-20 ECH2O probes (Decagon, Pullman, WA), and c) soil VWC at depth using EC-5 soil moisture probes (Decagon, Pullman, WA). Soil VWC profiles had sensors installed at –15 cm, –20 cm, and as deep as possible (down to –100 cm, depending on soil conditions).
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.
The Plot Temperature data-set contains 15 minute interval data from 2006 thru 2012. Data Qa/Qc has been performed on these files. PJ day refers to days since start of project (i.e., 1/1/2006). PJ Timestamp denotes/records each 15 minute interval entry from 1/1/2006.The treatment classes provided in the file are as follows; ambient control (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.Detailed information on header columns for the SensorID, Tree_Name, Species, and Sensor_Location variables. SensorID refers to the label given to each thermocouple probe (it is installed beneath a target tree or a bare inter-canopy location). The tree name is an identifier that provides both the SensorID information and the location of probe as either a soil temperature or air temperature measurement. Species indicates the cover type where the measurement was made; PIED, JUMO, or bare ground/intercanopy (INCA). And the Sensor_Location simply indicates weather the reported value is a soil or air temperature value (in Celsius degrees). 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. B1 through B5 always designate an inter-canopy (i.e., bare) location. Note, For the Tsoil and Tair data – there are no “replacement” trees. All temperature measurements were made original target trees, i,e., the temperature probe installation positions/locations remained in their original locations regardless of any later tree death or mortality.Similar to the Sapflow-JS data, there may be differing tree labels (and sample sizes, i.e., n=3, n=4, or n=5) for each cover type in differing plots depending on; 1) the specific target trees under which measurements were made, and 2) the total number of target trees in a given plot under which thermocouples were installed (this varies from n=3 to n=5 per cover type for differing plots). This will be obvious when you view the files for different plots.
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).
Microbes substantially control many biogeochemical processes in semiarid systems, including carbon and nitrogen fixation and carbon mineralization. Bacteria and fungi are osmotrophs that release enzymes into the environment to generate assimilable carbon and nutrients from organic particles. These enzymes are also the first agents to respond to pulses of soil moisture. The capacity to stabilize extracellular enzymes on soil particles preserves the utility of these nutrient-generating agents during extended dry periods. Enzyme stability can relate to environmental conditions and increase with clay mineral and humic compound concentrations. To better understand microbial response to precipitation variability, our objective was to determine the stability of extracellular enzymes under various monsoon precipitation regimes. During summer 2010, soil enzyme activity was measured in a rainfall manipulation study within a mixed-grass semiarid grassland in New Mexico, USA. Plots received either one large rain event or three evenly spaced small rain events per month. Before and after the first rain of each month, soil samples from the rhizosphere and from interspaces between plants were collected and analyzed for activity of four hydrolases; beta-glucosidase, beta-N-acetylglucosaminidase, leucine aminopeptidase, and alkaline phosphatase.
For experimental design and precipitation manipulations see SEV218.
Before the first rain of each month, soil samples were collected from the rhizosphere and interspaces between plants. Four soil cores (1cm wide, 3 cm deep) were taken across the plot, with rhizoshpere samples from under B. eriopoda and B. gracilis, and mixed together for each sample. Enzyme activity in the rhizosphere and interspace were analyzed separately. Two hours after the rain event, soil samples were again collected in the same manner. Microbial response to precipitation is quick therefore 2 hours was ample time to assess microbial response. 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, leucine aminopeptidase, alkaline phosphatase, and phenol oxidase were measured in the lab following the methods of Stursova et al. (2006).
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