Post-fire SOC and delta-13C at different types of microsite at a grassland-shrubland ecotone


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.

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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

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Each sample was analyzed three times and the results were averaged.

Additional information: 

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).

Water Potential Data From Pinyon-Juniper Forest at Sevilleta National Wildlife Refuge, New Mexico


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. 

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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

Ecosystem-Scale Rainfall Manipulation in a Piñon-Juniper Forest at the Sevilleta National Wildlife Refuge, New Mexico: Volumetric Water Content (VWC) at 5 cm Depth Data (2006-2013)


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. 

Obviously, one of the important areas of interest in this experiment was the effects of elevated (greater-than-average) and decreased (less-than-average) precipitation levels on soil moisture.  The volumetric water content of the soil was monitored across all twelve plots, all four treatment types, and all three cover types.  The record created through these monitoring activities not only noted the initial “wetting-up” of the soil after a precipitation event but also tracked the “drying-down” of the soil after the event.  The water content of the soil and its associated storage capacity could then provide a frame of reference in which changes in the physiological properties of our two target tree species, such as water potential and sapflow rate, could be interpreted. 

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Site Description

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 (see Pangle et al. 2012 for detailed methodology)
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.  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 90 degree 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.

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 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.  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 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

Site Abiotic Monitoring (please see Pangle et al. 2012 for more detailed methodology) We used 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).

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Quality Assurance: 

Data processing and QA-QC were performed using either Matlab (The Mathworks, Inc.) or Microsoft Office 2010 Excel (Microsoft Corporation) software.  All raw and/or processed data traces were visually plotted and inspected for noisy, erroneous, or out of range data points or sensors traces.  All removed data points had a “NaN” value assigned.   Despite this QA-QC review and data cleaning, all data sets should still be evaluated for outliers, etc., as standard outlier statistical tests were not performed.

Additional information: 

The VWC_5cm depth 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.

Values are reported in decimal % (in other words, a 0.25 data entry = 25%).  There are three cover types within each plot; 1) VWC (5cm) data under Piñon canopy cover, 2) VWC (5cm) under juniper canopy cover, and 3) VWC (5cm) at inter-canopy locations (i.e., bare, no canopy cover).  The VWC (5cm) data was collected from probes installed/buried at 5cm soil depth.

Detailed information on VWC-5cm header columns for the Tree_Number, SensorID, Species, and Sensor_Location variables.  Tree_Number refers to the label given to each sensor probe (i.e., it is installed beneath a specific target tree or a bare inter-canopy location).  The SensorID is an identifier that provides both the Tree_Number information and the soil depth of the probe.  Species indicates the cover type where the measurement was made; PIED, JUMO, or bare ground/intercanopy (INCA).   And the Sensor_Location simply indicates the depth where the soil moisture (VWC) probe is installed.   

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 VWC_5cm data – there are no or very few “replacement” trees.  All (or most all) VWC_5cm measurements were made original target trees, i,e., the sensor 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 soil moisture probes 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.

Contributions of Soil Communities to Ecosystem Respiration and Greenhouse Gas Emmisions in a Piñon-Juniper Woodland at the Sevilleta National Widlife Refuge, New Mexico (2011)


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.

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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

Additional information: 

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.

Grazing in grasslands creates changes in plant community structure. The magnitude of these changes depends on the productivity and the intensity of grazing.

Keystone species have large impacts on community and ecosystem properties, and create important ecological interactions with other species.  Prairie dogs (Cynomys spp.) and banner-tailed kangaroo rats (Dipodomys spectabilis) are considered keystone species of grassland ecosystems, and create a mosaic of unique habitats on the landscape.

In this study, soil characteristics after a lightning-initiated fire were evaluated. Following the fire in July 1998, 25 experimental plots were established on the eastern edge of MacKenzie Flats at the Sevilleta National Wildlife Refuge. Ten of these plots were located in a Bouteloua gracilis (blue grama)-dominated site, while 15 were established in another area dominated by Bouteloua eriopoda (black grama).

Our objective was to evaluate the effects of kangaroo rat mounds on species diversity and composition at a semiarid-arid grassland ecotone. We expected that source populations of plants occurring on kangaroo rat mounds have important influences on species composition of vegetation at the landscape scale, and that these influences differ by grassland type.

Effects of Kangaroo Rat Mounds on Seed Banks of Grass and Shrublands at the Sevilleta National Wildlife Refuge, New Mexico (2001)


Disturbance is a major factor in determining the spatial structure and temporal dynamics of ecological systems. Many studies have been conducted concerning the plant assemblages around Dipodmys spectabilis mounds compared to the off mound area. These studies have shown that annual plant cover is higher on the kangaroo rat mound compared to off the mound. However, no studies have addressed the effects of these rodents disturbance on the soil seed bank. Soil seed banks are an important component of the plant community particularly in arid environments. Annual plants have been known to create viable seeds that remain dormant in the soil for many years making their seed bank a persistent one. A persistent seed bank allows for future recruitment of plants given favorable conditions that could have a dramatic impact on the overall species diversity of the community. We studied the seed bank of eight forb taxa to ask the following questions: 1) Are there more seeds in the seed bank around kangaroo rat mounds compared to other microhabitats? 2) Does the seed composition differ among the different microhabitats? 3) If the seed composition does differ, do specific physical components of microhabitats predict seed populations?

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Selecting of kangaroo rat mounds

25 active kangaroo rat mounds were located on the grassland and 10 mounds were randomly selected for this experiment. Once mounds were selected they were semi-permanently marked with their given number and soil samples were taken.

Collecting of soil samples

Ten active mounds were randomly selected. Sub-samples were taken from each mound and grouped into four categories: the base of the mound (base), one meter from base samples (surrounding), six meters from base samples at the edge of black grama grass clumps (edge) and six meters from base samples in the inter-space between black grama grass clumps (inter-space) (Figure 1). Mound locations will be referred to as base, surrounding, edge, and inter-space for the remainder of the manuscript. Base and surrounding samples were considered on the mound where edge and inter-space samples were considered off the mound. Samples were collected using a soil auger with a 10cm diameter and a 2cm depth. Also, we recorded percent cover of undisturbed bare soil, vegetation, litter, gravel and animal disturbance within a 900cm2 area at each sample location to understand the potential effects of these physical variables on seed accumulation. Undisturbed bare soil percent cover was calculated by subtracting the sum of the percent cover for the other variables from the total.

Processing of samples

Soil samples were dried in an oven for 48 h at 50 C. Then, samples were sifted using the finest possible sieve to capture small seeds and a larger sieve to exclude large particles. To further separate seeds from the soil remaining after sifting, samples were floated in a 1:2:5 salt solution (sodium bicarbonate: sodium hexa-meta-phospate: magnesium sulfate) and then dried. Sub-samples were taken and all seeds were tested for viability and counted. Eight target taxa were identified based on their high occurrences at an adjacent study site. Four of the taxa (Cryptantha crassisepala, Descurainia pinnata, Phacelia integrifolia, and Plantago patagonica) are spring annuals, three (Astragalus missouriensis, Lesquerella fendleri, and Oenothera spp.) are perennial forbs that flower in the spring, and one (Sphaeralacea spp.) is a perennial forb that flowers in the fall. Since we could not distinguish species for the seeds of Sphaeralacea and Oenothera at our site, we analyzed these seeds at the genus level. Identifications were made using a reference collection compiled by Sevilleta biologists along with seeds that we had collected. Viability was tested using the pressure method.


Data currently not available to the public.

Quality Assurance: 

Data were visually assessed for any errors.

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Additional Information on the Data Collection Period

Data were collected the last week in August 2001.

Additional Study Area Information

Study Area Name: Five Points Grass Core Site

Study Area Location: Five Points is the general area which emcompasses the Black Grama Grassland (known as Five Points Grassland) and Creosote Core (Five Points Larrea) study sites and the transition between Chihuahuan Desert Scrub and Desert Grassland habitats. Both core sites are subject to intensive research activities, including measurements of NPP, phenology, pollinator diversity, and ground dwelling arthropod and rodent populations. There are drought rain-out shelters in both the Grassland and Creosote sites, as well as another set in the mixed ecotone with co-located ET Towers. The grassland Small Mammal Exclosure Study is located here, as well as many plots related to patch mapping and biotic transitions.

Elevation: 1616 m

Vegetation: Desert Grassland habitat is ecotonal in nature and the Black Grama Core site is no exception, bordering Chihuahuan Desert Scrub at its southern boundary and Plains-Mesa Grassland at its northern, more mesic boundary. There is also a significant presence of shrubs, dominantly broom snakeweed (Gutierrezia sarothrae), along with less abundant fourwing saltbush (Atriplex canescens), Mormon tea (Ephedra torreyana), winterfat (Krascheninnikovia lanata), tree cholla (Opuntia imbricata), club cholla (O. clavata), desert pricklypear (O. phaeacantha), soapweed yucca (Yucca glauca), and what are presumed to be encroaching, yet sparsely distributed, creosotebush (Larrea tridentata). Characteristically, the dominant grass was black grama (Bouteloua eriopoda). Spike, sand, and mesa dropseed grasses (Sporobolus contractus, S. cryptandrus, S. flexuosus) and sand muhly (Muhlenbergia arenicola) could be considered co-dominant throughout, along with blue grama (B. gracilis) in a more mesic, shallow swale on the site. Notable forb species included trailing four o’clock (Allionia incarnata), horn loco milkvetch (Astragalus missouriensis), sawtooth spurge (Chamaesyce serrula), plains hiddenflower (Cryptantha crassisepala), blunt tansymustard (Descarania obtusa), wooly plaintain (Plantago patagonica), globemallow (Sphaeralcea wrightii), and mouse ear (Tidestromia lanuginosa).

North Coordinate:34.3381
South Coordinate:34.3381
East Coordinate:106.717
West Coordinate:106.717

Burn Study Sites Quadrat Data for the Net Primary Production Study at the Sevilleta National Wildlife Refuge, New Mexico (2004-present)


In 2003, the U.S. Fish and Wildlife Service conducted a prescribed burn over a large part of the northeastern corner of the Sevilleta National Wildlife Refuge. Following this burn, a study was designed to look at the effect of fire on above-ground net primary productivity (ANPP) (i.e., the change in plant biomass, represented by stems, flowers, fruit and foliage, over time) within three different vegetation types: mixed grass (MG), mixed shrub (MS) and black grama (G). Forty permanent 1m x 1m plots were installed in both burned and unburned (i.e., control) sections of each habitat type. The core black grama site included in SEV129 is used as a G control site for analyses and does not appear in this dataset. The MG control site caught fire unexpectedly in the fall of 2009 and some plots were subsequently moved to the south. For details of how the fire affected plot placement, see Methods below. In spring 2010, sampling of plots 16-25 was discontinued at the MG (burned and control) and G (burned treatment only) sites, reducing the number of sampled plots to 30 at each.

To measure ANPP (i.e., the change in plant biomass, represented by stems, flowers, fruit and foliage, over time), the vegetation variables in this dataset, including species composition and the cover and height of individuals, are sampled twice yearly (spring and fall) at each plot. The data from these plots is used to build regressions correlating biomass and volume via weights of select harvested species obtained in SEV157, "Net Primary Productivity (NPP) Weight Data." This biomass data is included in SEV185, "Burn Study Sites Seasonal Biomass and Seasonal and Annual NPP Data."

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Collecting the Data:

Net primary production data is collected three times each year, winter, spring, and fall, for all burn 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 and only creosote is measured.

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. It is possible to obtain a total percent cover greater than 100% for a given quadrat because vegetative units for different species often overlap.

Niners and plexidecs are additional tools that can 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

Cover Measurements:

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 centimeter 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 Measurements:

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 shrub 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.

Creosote Measurements till 2013:

To measure creosote (i.e., Larrea tridenta) break the observations into two categories:

1.) Small, individual clusters of foliage on a branch (i.e., branch systems): Measure the horizontal cover of each live (i.e., green) foliage cluster, ignoring small open spaces (keeping in mind the 15% guideline stated above). Then measure the vertical "height" of each cluster from the top of the foliage to a plane created by extending a line horizontally from the bottom of the foliage. Each individual foliage cluster within a bush is considered a separate observation.

2.) Stems: Measure the length of each stem from the base to the beginning of live (i.e., green) foliage. Calculate the cumulative total of all stem measurements. This value is entered under "height" with the species as "stem" for each quadrat containing creosote. All other variable receive a default entry of "1" for creosote stem measurements.

Do not measure dead stems or areas of dead foliage. If in doubt about whether a stem is alive, scrape the stem with your fingernail and check for the presence of green cambium.

Creosote Measurements 2013 and after:

Each creosote is only measured as one total cover. Each quad that contains creosote will have one cover observation for each creosote canopy in quad.

Recording the Data:

Excel spreadsheets are used for data entry and file names should begin with the overall study (npp), followed by the date (mm.dd.yy) and the initials of the recorder (.abc). Finally, the site abbreviation should be added (i.e., mg, ms, or g). The final format should be as follows: npp_burn.mm.dd.yy.abc.xls. File names should be in lowercase.

August 2009 Burn:

On August 4, 2009, a lightning-initiated fire began on the Sevilleta National Wildlife Refuge.  The fire reached the Mixed-Grass Unburned plots on August 5, 2009, consuming them in their entirety.  As a result, in the spring of 2010, the Mixed-Grass (MG) unburned plots were moved to a different area within Deep Well, southwest of the Warming site. 

Also, on August 4, 2009, some of the webs and quadrats within the unburned Black Grama (G) site were impacted by the fire.  Thus, webs 2 and 3 were abandoned and extra plots added to areas within webs 1, 4, and 5 that were not burned.  Changes were as follows:

Webs 1, 4, and 5: A plot was added to the northeast to compensate for the loss of all plots at webs 2 and 3.

Web 4: A plot was added to the northwest to compensate for the northern plot, which was burned.


01/13/2011-Burn NPP quad data was QA/QC'd and put in Navicat. Matadata updated and compiled from 2004-2010. The mixed-grass unburned plot was moved to the south after the original plot burned unexpectedly in the fire of August 2009. (JMM) 11/28/2009-Burn NPP quad data was QA/QC'd and put in Navicat. Metadata updated and complied from 2004-2009. Mixed-grass unburned data (Fall 2009) was not collected due to unexpected fire at Sevilleta LTER in Aug 2009. (YX) 01/14/09-Metadata updated and compiled from 2004-2008 data. As of 2007, winter measurements are longer being taken. (YX) 12/20/2008-This data was QAQC'd in MySQL. I checked for duplicates and missing quads. (YX)

Additional information: 

Other researchers involved with collecting samples/data: Chandra Tucker (CAT; 04/2014-present), Megan McClung (MAM; 04/2013-present), Stephanie Baker (SRB; 09/2010-present), John Mulhouse (JMM; 08/2010-04/2013), Amaris Swann (ALS; 08/2008-01/2013), Maya Kapoor (MLK; 08/2003-01/2005, 05/2010-03/2011), Terri Koontz (TLK; 02/2000-08/2003, 08/2006-08/2010), Yang Xia (YX; 01/2005-03/2010), Karen Wetherill (KRW; 02/2000-08/2009); Michell Thomey (MLT; 09/2005-08/2008); Seth Munson (SMM; 09/2002-06/2004), Jay McLeod (JRM; 01/2006-08/2006); Caleb Hickman (CRH; 09/2002-11/2004), Charity Hall (CLH; 01/2005-01/2006); Tessa Edelen (MTE, 08/2004-08/2005).Data updated 08/18/15: MOSQ changed to MUSQ3; ARPUP6 changed to ARPU9; SPWR changed to SPPO6; a single entry BOER changed to BOER4.


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