forest ecosystems

Riparian Evapotranspiration (ET) Study (SEON) from the Middle Rio Grande River Bosque, New Mexico (1999-2011): Energy Balance Data

Abstract: 

This study originated with the objective of parameterizing riparian evapotranspiration (ET) in the water budget of the Middle Rio Grande. We hypothesized that flooding and invasions of non-native species would strongly impact ecosystem water use. Our objectives were to measure and compare water use of native (Rio Grande cottonwood, Populus deltoides ssp. wizleni) and non-native (saltcedar, Tamarix chinensis & Russian olive, Eleagnus angustifolia) vegetation and to evaluate how water use is affected by climatic variability resulting in high river flows and flooding as well as drought conditions and deep water tables. Eddy covariance flux towers to measure ET and shallow wells to monitor water tables were instrumented in 1999. Active sites in their second decade of monitoring include a xeroriparian, non-flooding salt cedar woodland within Sevilleta National Wildlife Refuge (NWR) and a dense, monotypic salt cedar stand at Bosque del Apache NWR, which is subject to flood pulses associated with high river flows. These data are energy balance data collected as part of this study.

Core Areas: 

Data set ID: 

308

Keywords: 

Methods: 

Three-dimensional eddy covariance: Measures fluxes of latent heat, sensible heat, and momentum, integrated over an area such as a vegetation canopy. High frequency measurements are made of vertical wind speed and water vapor, and their covariance over thirty minutes is used to compute latent heat flux, the heat absorbed by evaporation, from the canopy surface. Latent heat flux (LE) is converted to a direct measurement of evapotranspiration (ET). Simultaneous, high frequency measurements of temperature are used with vertical wind speed to compute the sensible heat flux (H), the heat transfer due to vertical temperature gradients. Measuring net radiation (Rn) and ground heat flux (G), allows the energy balance to be calculated (Rn = LE + H + G), providing a self-check for accuracy and closure error.

Sites: Two Rio Grande riparian locations in P. deltoides forests, two in T. chinensis forests. In each forest type, one of the two sites is prone to flooding from elevated Rio Grande flows, and the other site does not flood. A fifth site was located in a mix of non-native Eleagnus angustifolia (Russian olive) and native Salix exigua (coyote willow) prone to flooding.

*Design: Eddy covariance systems were mounted on towers in the turbulent surface layer 2-2.5 m above the canopy. Measurement period was 10 Hz and the covariance period was 30 minutes. Additional energy fluxes were made at 1 Hz and averaged over 30 minutes.

Data sources: 

sev308_bosqueEB_20160727.csv

Instrumentation: 

*Instrument Name: 3-D Sonic Anemometer
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: CSAT3

*Instrument Name: CO2/H2O Analyzer
*Manufacturer: Li-Cor, Inc. (Lincoln, NE)
*Model Number: LI-7500

*Instrument Name: Net Radiometer
*Manufacturer: Kipp & Zonen (Delft, The Netherlands)
*Model Number: CNR1

*Instrument Name: Barometric Pressure Sensor
*Manufacturer: Vaisala (Helsinki, Finland)
*Model Number: CS105

*Instrument Name: Temperature and Relative Humidity Probe
*Manufacturer: Vaisala (Helsinki, Finland)
*Model Number: HMP45C

*Instrument Name: Wind Sentry (Anemometer and Vane)
*Manufacturer: R.M. Young (Traverse City, MI)
*Model Number: 03001

*Instrument Name: Tipping Bucket Rain Gage
*Manufacturer: Texas Electronics, Inc. (Dallas, TX)
*Model Number: TE525

*Instrument Name: Quantum Sensor (PAR)
*Manufacturer: Li-Cor, Inc. (Lincoln, NE)
*Model Number: LI-190

*Instrument Name: Water Content Reflectometer
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: CS616

*Instrument Name: Soil Heat Flux Plate
*Manufacturer: Radiation and Energy Balance Systems, Inc. (Bellevue, WA)
*Model Number: HFT3

*Instrument Name: Averaging Soil Thermocouple Probe
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: TCAV

*Instrument Name: Measurement and Control System (Datalogger)
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: CR5000

*Instrument Name: Levelogger and Barologger (Water Table)
*Manufacturer: Solinst Canada Ltd. (Georgetown, ON, Canada)
*Model Number: 3001 LT M10 and 3001 LT M1.5

*Instrument Name: Mini-Diver, Cera-Diver, and Baro-Diver (Water Table)
*Manufacturer: Van Essen Instruments ((Delft, The Netherlands)
*Model Number: DI501, DI701, and DI500

Discontinued Instruments:

*Instrument Name: Krypton Hygrometer
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: KH2O

*Instrument Name: Net Radiometer
*Manufacturer: Radiation and Energy Balance Systems, Inc. (Bellevue, WA)
*Model Number: Q-7.1

*Instrument Name: Pyranometer
*Manufacturer: Kipp & Zonen (Delft, The Netherlands)
*Model Number: CM3

*Instrument Name: Micrologger
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: CR23X

*Instrument Name: Submersible Sensor Pressure Transducer (Water Table)
*Manufacturer: Electronic Engineering Innovations (Las Cruces, NM)
*Model Number: 2.0 (2 m) and 5.0 (4 m)

Quality Assurance: 

a] Before ET is computed from LE, various standard corrections are applied. These include: coordinate rotation to align the wind vector with the sonic anemometer, corrections developed from frequency response relationships that incorporate sensor line averaging and separation (Massman corrections), and corrections to account for flux effects on vapor density as opposed to mixing ratio measurements. Corrections are made in a data analysis (Perl) program. See Cleverly, et al., Hydrological Processes 20: 3207-3225, 2006 for more detail and references.

b] On days in which 1-4 of the 30 min LE values are missing, a general linear regression model between LE and Rn is used to estimate missing data whenever the regression coefficient was significantly different from 0 (i.e. p > 0.5). ET is not calculated from LE on days that do not match the above criteria.

c] Other missing data required for derived data values, as well as out of range data are filtered out in data analysis (Perl) programs.

d] Closure of the energy balance is achieved by adding the measured Bowen Ration (H/LE) components to H and LE. Closure represents the error introduced when applying the energy balance method to estimate ET: closure = Rn - LE - H - G. The measured Bowen Ratio, H / LE, is used to parse the closure value into component H and LE values.

e] Soil water content data are calibrated with soil water content (% vol) values measured from field samples by linear regression in a data analysis (Perl) program.

Additional information: 

Note: the data are not continuous--all sites have numerous breaks in the data. Additionally, instruments were introduced and retired at various times. For example, measurements of latent heat flux began with krypton hygrometers (LE_kh_c) and were replaced by infrared gas analyzers (LE_irga_c), which also commenced CO2 data (Fc_c, co2_a). Soil water content (soil_water) and a backup barometric sensor (P_mb_2) were added in 2003. Solar radiation (Rg_AVG) and photosynthetically active radiation (PAR_AVG) were added in 2006.

Riparian Evapotranspiration (ET) Study (SEON) from the Middle Rio Grande River Bosque, New Mexico (1999-2011 ): CO2 Concentration and Flux data

Abstract: 

This study originated with the objective of parameterizing riparian evapotranspiration (ET) in the water budget of the Middle Rio Grande. We hypothesized that flooding and invasions of non-native species would strongly impact ecosystem water use. Our objectives were to measure and compare water use of native (Rio Grande cottonwood, Populus deltoides ssp. wizleni) and non-native (saltcedar, Tamarix chinensis, Russian olive, Eleagnus angustifolia) vegetation and to evaluate how water use is affected by climatic variability resulting in high river flows and flooding as well as drought conditions and deep water tables. Eddy covariance flux towers to measure ET and shallow wells to monitor water tables were instrumented in 1999. Active sites in their second decade of monitoring include a xeroriparian, non-flooding salt cedar woodland within Sevilleta National Wildlife Refuge and a dense, monotypic salt cedar stand at Bosque del Apache NWR, which is subject to flood pulses associated with high river flows. These data are CO2 concentration at canopy and CO2 flux from canopy collected as part of this study.

Core Areas: 

Data set ID: 

312

Keywords: 

Methods: 

Three-dimensional eddy covariance: Measures fluxes of latent heat, sensible heat, and momentum, integrated over an area such as a vegetation canopy. High frequency measurements are made of vertical wind speed and water vapor, and their covariance over thirty minutes is used to compute latent heat flux, the heat absorbed by evaporation, from the canopy surface. Latent heat flux (LE) is converted to a direct measurement of evapotranspiration (ET). Simultaneous, high frequency measurements of temperature are used with vertical wind speed to compute the sensible heat flux (H), the heat transfer due to vertical temperature gradients. Measuring net radiation (Rn) and ground heat flux (G), allows the energy balance to be calculated (Rn = LE + H + G), providing a self-check for accuracy and closure error.

Sites: Two Rio Grande riparian locations in P. deltoides forests, two in T. chinensis forests. In each forest type, one of the two sites is prone to flooding from elevated Rio Grande flows, and the other site does not flood. A fifth site was located in a mix of non-native Eleagnus angustifolia (Russian olive) and native Salix exigua (coyote willow) prone to flooding.

Design: Eddy covariance systems were mounted on towers in the turbulent surface layer 2-2.5 m above the canopy. Measurement period was 10 Hz and the covariance period was 30 minutes. Additional energy fluxes were made at 1 Hz and averaged over 30 minutes.

Data sources: 

sev312_bosqueETCO2_20160720.txt

Instrumentation: 

Current Instruments:

*Instrument Name: 3-D Sonic Anemometer
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: CSAT3

*Instrument Name: CO2/H2O Analyzer
*Manufacturer: Li-Cor, Inc. (Lincoln, NE)
*Model Number: LI-7500

*Instrument Name: Net Radiometer
*Manufacturer: Kipp & Zonen (Delft, The Netherlands)
*Model Number: CNR1

*Instrument Name: Barometric Pressure Sensor
*Manufacturer: Vaisala (Helsinki, Finland)
*Model Number: CS105

*Instrument Name: Temperature and Relative Humidity Probe
*Manufacturer: Vaisala (Helsinki, Finland)
*Model Number: HMP45C

*Instrument Name: Wind Sentry (Anemometer and Vane)
*Manufacturer: R.M. Young (Traverse City, MI)
*Model Number: 03001

*Instrument Name: Tipping Bucket Rain Gage
*Manufacturer: Texas Electronics, Inc. (Dallas, TX)
*Model Number: TE525

*Instrument Name: Quantum Sensor (PAR)
*Manufacturer: Li-Cor, Inc. (Lincoln, NE)
*Model Number: LI-190

*Instrument Name: Water Content Reflectometer
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: CS616

*Instrument Name: Soil Heat Flux Plate
*Manufacturer: Radiation and Energy Balance Systems, Inc. (Bellevue, WA)
*Model Number: HFT3

*Instrument Name: Averaging Soil Thermocouple Probe
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: TCAV

*Instrument Name: Measurement and Control System (Datalogger)
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: CR5000

*Instrument Name: Levelogger and Barologger (Water Table)
*Manufacturer: Solinst Canada Ltd. (Georgetown, ON, Canada)
*Model Number: 3001 LT M10 and 3001 LT M1.5

*Instrument Name: Mini-Diver, Cera-Diver, and Baro-Diver (Water Table)
*Manufacturer: Van Essen Instruments ((Delft, The Netherlands)
*Model Number: DI501, DI701, and DI500

Discontinued Instruments:

*Instrument Name: Krypton Hygrometer
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: KH2O

*Instrument Name: Net Radiometer
*Manufacturer: Radiation and Energy Balance Systems, Inc. (Bellevue, WA)
*Model Number: Q-7.1

*Instrument Name: Pyranometer
*Manufacturer: Kipp & Zonen (Delft, The Netherlands)
*Model Number: CM3

*Instrument Name: Micrologger
*Manufacturer: Campbell Scientific, Inc. (Logan, UT)
*Model Number: CR23X

*Instrument Name: Submersible Sensor Pressure Transducer (Water Table)
*Manufacturer: Electronic Engineering Innovations (Las Cruces, NM)
*Model Number: 2.0 (2 m) and 5.0 (4 m)

Quality Assurance: 

a] Before ET is computed from LE, various standard corrections are applied. These include: coordinate rotation to align the wind vector with the sonic anemometer, corrections developed from frequency response relationships that incorporate sensor line averaging and separation (Massman corrections), and corrections to account for flux effects on vapor density as opposed to mixing ratio measurements. Corrections are made in a data analysis (Perl) program. See Cleverly, et al., Hydrological Processes 20: 3207-3225, 2006 for more detail and references.

b] On days in which 1-4 of the 30 min LE values are missing, a general linear regression model between LE and Rn is used to estimate missing data whenever the regression coefficient was significantly different from 0 (i.e. p > 0.5). ET is not calculated from LE on days that do not match the above criteria.

c] Other missing data required for derived data values, as well as out of range data are filtered out in data analysis (Perl) programs.

d] Closure of the energy balance is achieved by adding the measured Bowen Ration (H/LE) components to H and LE. Closure represents the error introduced when applying the energy balance method to estimate ET: closure = Rn - LE - H - G. The measured Bowen Ratio, H / LE, is used to parse the closure value into component H and LE values.

e] Soil water content data are calibrated with soil water content (% vol) values measured from field samples by linear regression in a data analysis (Perl) program.

Additional information: 

SEV ET 3/18/2000--12/31/2011, water table 4/16/1999--12/31/2014
BDAS ET 3/16/2000--12/31/2011, water table 4/17/1999--6/30/2014
SHK ET 3/18/2000--12/31/2007, water table 3/16/2000--12/31/2013
BLN ET 3/22/2000--5/17/2004, water table 3/15/2000--11/18/2008
LARO ET 3/6/2003--12/17/2008, water table 4/16/2003--12/31/2009

Note: the data are not continuous--all sites have numerous breaks in the data. Additionally, instruments were introduced and retired at various times. For example, measurements of latent heat flux began with krypton hygrometers (LE_kh_c) and were replaced by infrared gas analyzers (LE_irga_c), which also commenced CO2 data (Fc_c, co2_a). Soil water content (soil_water) and a backup barometric sensor (P_mb_2) were added in 2003. Solar radiation (Rg_AVG) and photosynthetically active radiation (PAR_AVG) were added in 2006.

Pinon-Juniper (Core Site) Quadrat Data for the Net Primary Production Study at the Sevilleta National Wildlife Refuge, New Mexico (2003-present )

Abstract: 

This dataset contains pinon-juniper woodland quadrat data and is part of a long-term study at the Sevilleta LTER measuring net primary production (NPP) across four distinct ecosystems: creosote-dominant shrubland (Site C, est. winter 1999), black grama-dominant grassland (Site G, est. winter 1999), blue grama-dominant grassland (Site B, est. winter 2002), and pinon-juniper woodland (Site P, est. winter 2003). Net primary production is a fundamental ecological variable that quantifies rates of carbon consumption and fixation. Estimates of NPP are important in understanding energy flow at a community level as well as spatial and temporal responses to a range of ecological processes.

Above-ground net primary production is the change in plant biomass, represented by stems, flowers, fruit and and foliage, over time and incoporates growth as well as loss to death and decomposition. To measure this change the vegetation variables in this dataset, including species composition and the cover and height of individuals, are sampled twice yearly (spring and fall) at permanent 1m x 1m plots within each site. A third sampling at Site C is performed in the winter. 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 SEV182, "Seasonal Biomass and Seasonal and Annual NPP for Core Research Sites."

Data set ID: 

278

Core Areas: 

Additional Project roles: 

458
459
460
461

Keywords: 

Methods: 

Locating the Sampling Quadrats:

Site P, the pinon-juniper woodland site (Cerro Montosa), is set-up differently than the other core sites. In order to accommodate the different habitat types, groups of transects (i.e., "plots") were set up along north (N) and south (S) facing slopes as well as along vegas (V) and ridges (R). Transects on the first two plots consist of 40 quads each (10 quadrants for each of four habitat types). Plot one is slightly west of plot three and plot two is slightly west of the weather station. Plot three is located on a wide piedmont, which consists of four transects with five quadrats on each.

Collecting the Data:

Net primary production data is collected twice each year, spring and fall, for all sites. The Five Points Creosote Core Site is also sampled in winter. Spring measurements are taken in April or May when shrubs and spring annuals have reached peak biomass. Fall measurements are taken in either September or October when summer annuals have reached peak biomass but prior to killing frosts. Winter measurements are taken in February before the onset of spring growth.

Vegetation data is collected on a palm top computer. A 1-m2 PVC-frame is placed over the fiberglass stakes that mark the diagonal corners of each quadrat. When measuring cover it is important to stay centered over the vegetation in the quadrat to prevent errors caused by angle of view (parallax). Each PVC-frame is divided into 100 squares with nylon string. The dimensions of each square are 10cm x 10cm and represent 1 percent of the total area.

The cover (area) and height of each individual live (green) vegetative unit that falls within the one square meter quadrat is measured. A vegetative unit consists of an individual size class (as defined by a unique cover and height) of a particular species within a quadrat. Cover is quantified by counting the number of 10cm x 10cm squares filled by each vegetative unit.

Niners and plexidecs are additional tools that help accurately determine the cover a vegetative unit. A niner is a small, hand-held PVC frame that can be used to measure canopies. Like the larger PVC frame it is divided into 10cm x 10cm squares, each square representing 1% of the total cover. However, there are only nine squares within the frame, hence the name “niner.” A plexidec can help determine the cover of vegetative units with covers less than 1%. Plexidecs are clear plastic squares that are held above vegetation. Each plexidec represents a cover of 0.5% and has smaller dimensions etched onto the surface that correspond to 0.01%, 0.05%, 0.1%, and 0.25% cover.

It is extremely important that cover and height measurements remain consistent over time to ensure that regressions based on this data remain valid. Field crew members should calibrate with each other to ensure that observer bias does not influence data collection.

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 cm instead of cover and height. Cacti that occur as a dense ball/clump of stems (Opuntia leptocaulis) are measured using the same protocol as shrubs. Pincushion or hedgehog cacti (Escobaria vivipara, Schlerocactus intertextus, Echinocereus fendleri) that occur as single (or clustered) cylindrical stems are measured as a single cover.

Yuccas-Make separate observations for the leaves and caudex (thick basal stem). Break the observations into sections of leaves that are approximately the same height and record the cover as the perimeter around this group of leaf blades. The caudex is measured as a single cover. The thick leaves of yuccas make it difficult to make a cover measurement by centering yourself over the caudex of the plant. The cover of the caudex may be estimated by holding a niner next to it or using a tape measure to measure to approximate the area.

Height 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 shrubs and sub-shrubs (non-creosote)-Measure the height from the base of the green foliage to the top of the green foliage, ignoring all bare stems. Do not measure to the ground unless the foliage reaches the ground.

Plants rooted outside but hanging into a quadrat-Do not measure the height from the ground. Measure only the height of the portion of the plant that is within the quadrat. 

Creosote Measurements:

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.

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., c, g, b, p). The final format for sites B, G, and C should be as follows: npp_core.mm.dd.yy.abc.xls. For site P, the file format should be npp_pinj.mm.dd.yy.abc.xls. File names should be in lowercase.

Data sources: 

sev278_npppinjquadrat_20161214.csv

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; 08/2009-06/2013), 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), Heather Simpson (HLS; 08/2000 - 08/2002), Chris Roberts (CR; 09/2001- 08/2002), Shana Penington (SBP; 01/2000 - 08/2000), 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; ambiguous Quercus species resolved by New Mexico Natural Heritage Program and updated.

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)

Abstract: 

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. 

Core Areas: 

Data set ID: 

276

Additional Project roles: 

206
207
208
209
210
211
212
213

Keywords: 

Methods: 

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).

Data sources: 

sev276_pjvwc5cm06_20150707.csv
sev276_pjvwc5cm07_20150709.csv
sev276_pjvwc5cm08_20150708.csv
sev276_pjvwc5cm09_20150709.csv
sev276_pjvwc5cm10_20150709.csv
sev276_pjvwc5cm11_20150709.csv
sev276_pjvwc5cm12_20150709.csv
sev276_pjvwc5cm13_20150709.csv

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.

Ecosystem-Scale Rainfall Manipulation in a Piñon-Juniper Forest at the Sevilleta National Wildlife Refuge, New Mexico: Water Potential Data (2006-2013)

Abstract: 

Climate models predict that water limited regions around the world will become drier and warmer in the near future, including southwestern North America. We developed a large-scale experimental system that allows testing of the ecosystem impacts of precipitation changes. Four treatments were applied to 1600 m2 plots (40 m × 40 m), each with three replicates in a piñon pine (Pinus edulis) and juniper (Juniper monosperma) ecosystem. These species have extensive root systems, requiring large-scale manipulation to effectively alter soil water availability.  Treatments consisted of: 1) irrigation plots that receive supplemental water additions, 2) drought plots that receive 55% of ambient rainfall, 3) cover-control plots that receive ambient precipitation, but allow determination of treatment infrastructure artifacts, and 4) ambient control plots. Our drought structures effectively reduced soil water potential and volumetric water content compared to the ambient, cover-control, and water addition plots. Drought and cover control plots experienced an average increase in maximum soil and air temperature at ground level of 1-4° C during the growing season compared to ambient plots, and concurrent short-term diurnal increases in maximum air temperature were also observed directly above and below plastic structures. Our drought and irrigation treatments significantly influenced tree predawn water potential, sap-flow, and net photosynthesis, with drought treatment trees exhibiting significant decreases in physiological function compared to ambient and irrigated trees.  Supplemental irrigation resulted in a significant increase in both plant water potential and xylem sap-flow compared to trees in the other treatments. This experimental design effectively allows manipulation of plant water stress at the ecosystem scale, permits a wide range of drought conditions, and provides prolonged drought conditions comparable to historical droughts in the past – drought events for which wide-spread mortality in both these species was observed. 

Water potential measurements were used to monitor the water stress of the two target species across the four treatment regimes.  Sampling for water potentials occurred twice daily.  One set of samples was collected hours before dawn and another set was collected at mid-day.  The predawn readings provided the “least-stressed” tree water content values as they were collected after the trees had returned to equilibrium over the evening and had yet to start transpiring.  The mid-day values, collected after tree-level respiration had been occurring for hours and when the daily temperatures were highest, represented the opposite “most-stressed” scenario. To gauge the effect of the irrigation treatment on the water content of the trees, we sampled water potentials just before and just after irrigation events.   

Core Areas: 

Data set ID: 

275

Additional Project roles: 

376
377
378
379
380
381
382
383

Keywords: 

Methods: 

Site Description

In total, our study site consisted of 12 experimental plots located in three replicate blocks that varied in slope % and aspect. Slope varied from 0-2% in experimental plots situated in level portions of the site, with steeper grades ranging from 6-18% for plots established on hill-slopes. Soil depth across the site ranged from 20 to ≥ 100 cm, with shallower soil depths occurring on hill-slopes where depth to caliche and/or bed-rock was only 20-30 cm in some instances. 

The study utilized four different experimental treatments applied in three replicate blocks. The four experimental treatments included 1) un-manipulated, ambient control plots, 2) drought plots, 3) supplemental irrigation plots, and 4) cover-control plots that have a similar infrastructure to the drought plots, but remove no precipitation.  The three replicated blocks differed in their slope and aspect. One block of four plots was located on south facing slopes, one on north facing slopes, and one in a flat area of the landscape.  

Experimental Treatment Design 

To effectively reduce water availability to trees, we installed treatments of sufficient size to minimize tree water uptake from outside of the plot. Thus, we constructed three replicated drought structures that were 40 m × 40 m (1600 m2). We targeted a 50% reduction in ambient precipitation through water removal troughs that covered ~50% of the land surface area. Drought plot infrastructure was positioned to insure that targeted Piñon pine and juniper were centrally located within each drought plot to provide the maximum distance between tree stems and the nearest plot boundary.  Each drought and cover-control plot consists of 27 parallel troughs running across the 40 m plot. Each trough was constructed with overlapping 3ft ×10 ft (0.91 m × 3.05 m) pieces of thermoplastic polymer sheets (Makloron SL Polycarbonate Sheet, Sheffield Plastics Inc, Sheffield, MA) fixed with self-tapping metal screws to horizontal rails that are approximately waist height and are supported by vertical posts every 2.5-3.5 m. The plastic sheets were bent into a concave shape to collect and divert the precipitation off of the plot. The bending and spacing of the plastic resulted in 0.81 m (32 in) troughs separated by 0.56 m (22 in) walkways. 

Individual troughs often intersected the canopy of trees because of their height. The troughs were installed as close to the bole of the tree as possible without damaging branches in order to maximize the area covered by the plastic across the entire plot. An end-cap was attached to the downstream edge of the trough to prevent water from falling onto the base of the tree. The end-caps were 81 cm × 30 cm and made with the same plastic as the troughs. Each end-cap was fixed to the trough with a 75 cm piece of 20 gauge angle iron cut to match the curve of the bottom of the trough and held in place with self-tapping screws. The plastic junctures were then sealed with acrylic cement (Weld-On #3 epoxy, IPS Corp., Compton, CA). The middle of the end-cap was fitted with a 3 in (7.62 cm) PVC collar to allow water to flow through. A piece of 3 in (7.62 cm) PVC pipe or suction hose (used when the bole of a tree was directly below trough) was then attached to the downstream side of the end-cap, enabling water to flow into the trough on the other side of a tree. End-caps were also placed at the downhill end of the troughs on the edge of the plot and fitted with 90o fittings to divert water down into a 30 cm2 gutter (open on top) that ran perpendicular to the plot. Collected water was then channeled from the gutter into adjacent arroyos for drainage away from the study area. 

We built cover-control infrastructures to investigate the impact of the plastic drought structures independent of changes in precipitation. This was necessary because of the high radiation environment in central New Mexico, in which the clear plastic troughs can effectively act as a greenhouse structure. The cover-control treatment had the same dimensions as the drought plots with one key difference. The plastic was attached to the rails in a convex orientation so precipitation would fall on top of the plastic and then drain directly down onto the plot. The cover-control plots were designed to receive the same amount of precipitation as un-manipulated ambient plots, with the precipitation falling and draining into the walkways between the rows of troughs. Cover-control plots were constructed between June-21-07 and July-24-07; drought plots were constructed between August-09-07 and August-27-07.  The total plastic coverage in each plot is 45% ± 1% of the 1600 m2 plot area due to the variable terrain and canopy cover. A direct test of the amount of precipitation excluded via the plastic troughs was performed over a 2-week period during the summer monsoon season of 2008. Two rainfall collection gutters (7.6 cm width, 6.1 m length) were installed in a perpendicular arrangement across four plastic drought structures and four intervening open walkways. One gutter was located below the troughs (~0.6 m above ground), and the other was located just above (~1.35 m) and offset, to determine the interception of rainfall by the troughs. Rainfall totals collected via the perpendicular gutters were measured using Series 525 tipping bucket rain gauges (Texas Electronics, Dallas, TX). 

Our irrigation system consisted of above-canopy sprinkler nozzles configured to deliver supplemental rainstorm event(s) at a rate of 19 mm hr-1. Our irrigation system is a modified design of the above-canopy irrigation system outlined by Munster et al. (2006). Each of the three irrigation plots has three 2750 gal (10.41 m3) water storage tanks connected in parallel.  These tanks were filled with filtered reverse osmosis (RO) water brought to the site with multiple tractor-trailer trucks. During irrigation events, water is pumped from the tanks through a series of hoses that decrease from 7.62 cm (3 in) main lines out of the tank to 2.54 cm (1 in) hoses attached to 16 equally-spaced sprinklers within the plot. Each sprinkler is 6.1 m (20 ft) tall (2-3 m higher than mean tree height), and fitted with a sprinkler nozzle that creates an even circular distribution of water with a radius of 5 m on the ground. Due to the varying topography, sprinklers located downslope (if unregulated) would receive more pressure than those at the top of a hill and thus spray more water. To mitigate this problem, each sprinkler line was fitted with a pressure gauge and variable globe valve (inline water spigot with precise regulation) equidistant from the top of the sprinkler. Each sprinkler line was then set so that the pressure gauges were equal, thus ensuring equal distribution of water throughout the plot, regardless of elevational differences.  The irrigation systems were tested in October 2007 (2 mm supplemental), and full applications (19 mm) were applied in 2008 on 24-June, 15-July, and 26-August. During the 24-June event, we deployed six ~1 m2 circular trays across one of the irrigation plots to test the spatial variation of the wetting. Data from this test indicated that on average, collection trays received 19.5 (± 2.5) mm of water. 

Plant Physiological Response 

Multiple physiological characteristics of ten target trees (five piñon and five juniper) within each of the intensive measurement plots were continually monitored by automated sensors or periodic manual measurements. Predawn (PD) and mid-day (MD) plant water potentials were measured with multiple Scholander-type pressure chambers (PMS Instrument Co, Albany, OR) on all target trees. When possible, PD was measured both before and after supplemental irrigation events.  

Data sources: 

sev275_pjwaterpot_20160328.txt

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: 

Additional notes: The water potential data-set contains periodic tree level water potential data from 2006 thru 2012.  Measurements were made at either predawn or midday.  Data Qa/Qc has been performed on these files.   PJ day refers to days since start of project (i.e., 1/1/2006).
 
The treatment classes provided in the file are as follows; ambient (1), drought (2), cover-control (3), and irrigation (4).  The experiment used plot aspect as the blocking factor.   There are 3 different replicate blocks and block classifications designated in the files; flat aspect (1), north aspect (2), and south aspect (3).  This will be obvious when viewing the files.

Tree numbers are always grouped by species as follows (regardless of plot); Trees 1-5 are original Pinus edulis, Trees 6-10 are original Juniper monosperma.   When one of these original trees died, an additional tree in the plot was added to retain an adequate sample size over time (i.e., multiple years+).   These additional trees are grouped as follows; Trees 11-15 are “replacement” Pinus edulis, Trees 16-20 are “replacement” Juniper monosperma.  “Replacement” is used here in a more restricted sense, as these additional trees have their separate and unique tree designation number.

So, in differing plots you will have differing numbers of trees depending on; 1) the number of trees for which data was collected, and 2) how many additional “replacement trees” had to be designated due to mortality (or partial mortality) of original trees.  Many plots have n=10 trees, based on the original T1-T5 & T6-10 designation, as these particular plots did not experience mortality.   However, a plot like P10 has a total of n=16 trees.  In P10, the original T1-5 & T6-T10 trees are listed, a replacement Pinon (T11) is listed, and five additional/replacement junipers (T16-T20).   In some cases you will see data present at the same time for both original and replacement junipers (plots 6 & 10).  This is fine, as juniper experiences a slow/partial canopy dieback, so we monitored the original and replacement trees at the same time in these two plots.  Finally, we only provide data on trees for which data was collected (so for example, in some instances you may only have n=4 cols of data for a particular species in a particular plot).  

Ecosystem-Scale Rainfall Manipulation in a Piñon-Juniper Forest at the Sevilleta National Wildlife Refuge, New Mexico: Soil Temperature Data (2006-2013)

Abstract: 

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. 

Core Areas: 

Data set ID: 

274

Additional Project roles: 

248
249
250
251
252
253
254
255

Keywords: 

Methods: 

Site Description

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 sources: 

sev274_pjsoiltemp06_20140122.txt
sev274_pjsoiltemp07_20140124.txt
sev274_pjsoiltemp08_20140124.txt
sev274_pjsoiltemp09_20140127.txt
sev274_pjsoiltemp10_20140127.txt
sev274_pjsoiltemp11_20140127.txt
sev274_pjsoiltemp12_20150702.txt
sev274_pjsoiltemp13_20150702.txt

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 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.

Ecosystem-Scale Rainfall Manipulation in a Piñon-Juniper Forest at the Sevilleta National Wildlife Refuge, New Mexico: Meteorological Data (2006-2013)

Abstract: 

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.

A micrometeorological station was used to document the climatic conditions at the study site.  Monitoring the ambient environment in this way allowed us to more easily determine which tree growth responses were driven by changes in the native climate as opposed to those resulting from the rainfall manipulation treatments.  Environmental factors such as temperature, relative humidity, and photosynthetically active radiation (PAR) have a huge impact on the physiological processes that are being explored in this project.  The data collected by the station created a local climatic record which was needed to provide the context in which the treatment effects can be examined and sensor readings can be interpreted.

Data set ID: 

273

Additional Project roles: 

367

Core Areas: 

Keywords: 

Methods: 

A CR-10X datalogger was used to record data from a micrometeorological tower centrally located in an open intercanopy area of the study site. This tower recorded precipitation with a Series 525 rain gauge (Texas Electronics, Dallas, TX), net radiation with a Kipp and Zonen NK-LITE net radiometer (Campbell Scientific, Logan, UT), photosynthetically active radiation (PAR) with a LI-190SA sensor (Li-Cor, Lincoln, NE), windspeed and direction monitored with a 05103-L R.M. Young wind monitor (Campbell Scientific, Logan, UT), and air temperature and RH% with a Vaisala HMP45C sensor. During winter months the rain gauge was fitted with a snow adaptor to thaw snow and record the total amount in mm rain. All met-station measurements were made at a height of 1-3 m above ground depending on the sensor array in question. 

Data sources: 

sev273_pjmet_20130508.csv

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)

Abstract: 

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.

Data set ID: 

250

Core Areas: 

Additional Project roles: 

266
267

Keywords: 

Methods: 

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.  

 

Instrumentation: 

I

* 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.

Riparian Evapotranspiration (ET) Study (SEON) from the Middle Rio Grande River Bosque, New Mexico (1999-2011 ): Evapotranspiration Data (ET)

Abstract: 

This study originated with the objective of parameterizing riparian evapotranspiration (ET) in the water budget of the Middle Rio Grande.  We hypothesized that flooding and invasions of non-native species would strongly impact ecosystem water use.  Our objectives were to measure and compare water use of native (Rio Grande cottonwood, Populus deltoides ssp. wizleni) and non-native (saltcedar, Tamarix chinensis & Russian olive, Eleagnus angustifolia) vegetation and to evaluate how water use is affected by climatic variability resulting in high river flows and flooding as well as drought conditions and deep water tables.  Eddy covariance flux towers to measure ET and shallow wells to monitor water tables were instrumented in 1999.  Active sites in their second decade of monitoring include a xeroriparian, non-flooding salt cedar woodland within Sevilleta National Wildlife Refuge (NWR) and a dense, monotypic salt cedar stand at Bosque del Apache NWR, which is subject to flood pulses associated with high river flows.

Additional Project roles: 

478
479

Data set ID: 

192

Core Areas: 

Keywords: 

Methods: 

Three-dimensional eddy covariance:  Measures fluxes of latent heat, sensible heat, and momentum, integrated over an area such as a vegetation canopy.  High frequency measurements are made of vertical wind speed and water vapor, and their covariance over thirty minutes is used to compute latent heat flux, the heat absorbed by evaporation, from the canopy surface.  Latent heat flux (LE) is converted to a direct measurement of evapotranspiration (ET).  Simultaneous, high frequency measurements of temperature are used with vertical wind speed to compute the sensible heat flux (H), the heat transfer due to vertical temperature gradients.  Measuring net radiation (Rn) and ground heat flux (G), allows the energy balance to be calculated (Rn = LE + H + G), providing a self-check for accuracy and closure error.

Sites: Two Rio Grande riparian locations in P. deltoides forests, two in T. chinensis forests.  In each forest type, one of the two sites is prone to flooding from elevated Rio Grande flows, and the other site does not flood.  A fifth site was located in a mix of non-native Eleagnus angustifolia (Russian olive) and native Salix exigua (coyote willow) prone to flooding.

Design:  Eddy covariance systems were mounted on towers in the turbulent surface layer 2-2.5 m above the canopy.  Measurement period was 10 Hz and the covariance period was 30 minutes.  Additional energy fluxes were made at 1 Hz and averaged over 30 minutes.

Water table fluctuations were monitored at the sights with groundwater wells installed ~ 1 m below baseflow water table.  Wells were constructed of 5 cm inner diameter PVC pipe with approximately 1 m screen lengths. Automated pressure transducers were deployed to measure water table elevations at 30-minute intervals.

Precision:  Thirty minute average or total (e.g., precipitation) core data from field instruments and processed field data (thirty minute or daily average or total. Data are programmed for IEEE4 4 byte floating point output (~ 7 digits), but actual precision values are not apparent in the program or in many instrument manuals. 

Missing Data: Direct-from-field data time stamps are excluded if data are missing.

Data sources: 

sev192_bosqueET_20150729.txt

Instrumentation: 

Current Instruments:

Instrument Name: 3-D Sonic Anemometer

Manufacturer: Campbell Scientific, Inc. (Logan, UT)

Model Number: CSAT3


Instrument Name: CO2/H2O Analyzer

Manufacturer: Li-Cor, Inc. (Lincoln, NE)

Model Number: LI-7500


Instrument Name: Net Radiometer

Manufacturer: Kipp & Zonen (Delft, The Netherlands)

Model Number: CNR1


Instrument Name: Barometric Pressure Sensor

Manufacturer: Vaisala (Helsinki, Finland)

Model Number: CS105


Instrument Name: Temperature and Relative Humidity Probe

Manufacturer: Vaisala (Helsinki, Finland)

Model Number: HMP45C


Instrument Name: Wind Sentry (Anemometer and Vane)

Manufacturer: R.M. Young (Traverse City, MI)

Model Number: 03001


Instrument Name: Tipping Bucket Rain Gage

Manufacturer: Texas Electronics, Inc. (Dallas, TX)

Model Number: TE525


Instrument Name: Quantum Sensor (PAR)

Manufacturer: Li-Cor, Inc. (Lincoln, NE)

Model Number: LI-190


Instrument Name: Water Content Reflectometer

Manufacturer: Campbell Scientific, Inc. (Logan, UT)

Model Number: CS616


Instrument Name: Soil Heat Flux Plate

Manufacturer: Radiation and Energy Balance Systems, Inc. (Bellevue, WA)

Model Number: HFT3


Instrument Name: Averaging Soil Thermocouple Probe

Manufacturer: Campbell Scientific, Inc. (Logan, UT)

Model Number: TCAV


Instrument Name: Measurement and Control System (Datalogger)

Manufacturer: Campbell Scientific, Inc. (Logan, UT)

Model Number: CR5000


Instrument Name: Levelogger and Barologger (Water Table)

Manufacturer: Solinst Canada Ltd. (Georgetown, ON, Canada)

Model Number: 3001 LT M10 and 3001 LT M1.5


Instrument Name: Mini-Diver, Cera-Diver, and Baro-Diver (Water Table)

Manufacturer: Van Essen Instruments ((Delft, The Netherlands)

Model Number: DI501, DI701, and DI500


Discontinued Instruments:


Instrument Name: Krypton Hygrometer

Manufacturer: Campbell Scientific, Inc. (Logan, UT)

Model Number: KH2O


Instrument Name: Net Radiometer

Manufacturer: Radiation and Energy Balance Systems, Inc. (Bellevue, WA)

Model Number: Q-7.1


Instrument Name: Pyranometer

Manufacturer: Kipp & Zonen (Delft, The Netherlands)

Model Number: CM3


Instrument Name: Micrologger

Manufacturer: Campbell Scientific, Inc. (Logan, UT)

Model Number: CR23X


Instrument Name: Submersible Sensor Pressure Transducer (Water Table)

Manufacturer: Electronic Engineering Innovations (Las Cruces, NM)

Model Number: 2.0 (2 m) and 5.0 (4 m)

Quality Assurance: 

a]  Before ET is computed from LE, various standard corrections are applied.  These include: coordinate rotation to align the wind vector with the sonic anemometer, corrections developed from frequency response relationships that incorporate sensor line averaging and separation (Massman corrections), and corrections to account for flux effects on vapor density as opposed to mixing ratio measurements.  Corrections are made in a data analysis (Perl) program.  See Cleverly, et al., Hydrological Processes 20: 3207-3225, 2006 for more detail and references.


b]  On days in which 1-4 of the 30 min LE values are missing, a general linear regression model  between LE and Rn is used to estimate missing data whenever the regression coefficient was significantly different from 0 (i.e. p > 0.5).  ET is not calculated from LE on days that do not match the above criteria.


c]  Other missing data required for derived data values, as well as out of range data are filtered out in data analysis (Perl) programs.


d]  Closure of the energy balance is achieved by adding the measured Bowen Ration (H/LE) components to H and LE.  Closure represents the error introduced when applying the energy balance method to estimate ET: closure = Rn - LE - H - G.  The measured Bowen Ratio, H / LE, is used to parse the closure value into component H and LE values.


e]  Soil water content data are calibrated with soil water content (% vol) values measured from field samples by linear regression in a data analysis (Perl) program.


f]  Well loggers are pressure transducers that measure absolute pressure (barometric plus water column pressures).  An on-site barometric pressure transducer suspended above the water table is calibrated to quantify pressure in units of elevation head, which is subtracted from absolute head to arrive at the actual water level.


g]  Well data are calibrated using periodic manual measurements of water table elevations.

Litter Fall Collection Study in Pinyon-Juniper, Cottowood, and Spruce-Fir-Aspen Forests at the Sevilleta NWR, Bosque del Apache NWR, and the Cibola National Forest, New Mexico (1992-1993)

Abstract: 

The litterfall study was designed to assess the quantity of biomass (leaves, twigs, reproductive materials) falling from tree species in different ecosystem types. Three study sites selected were:  (1) the pinyon-juniper woodland site near Cerro Montoso on the Sevilleta NWR; (2) the cottonwood forest LTER site along the Rio Grande at Bosque del Apache NWR; and (2) the old-growth spruce-fir-aspen site near South Baldy in the Magdalena Mountains (Cibola National Forest).  The study was conducted over two years (1992-1993) to compare litterfall rates and quantities among sites, seasons and years.

Core Areas: 

Data set ID: 

22

Additional Project roles: 

54
55
56
57
58

Keywords: 

Purpose: 

To assess differences in rates and quantities of leaf, twig, reproductive parts (nuts, seeds, berries) of litterfall from tree species in various ecosystems studied by the Sevilleta LTER Program.

Methods: 

Sampling Design:

 A total of 120 litterfall baskets were distributed among the 3 study sites.  In the Sevilleta's Cerro Montoso site, 30 baskets were placed under juniper trees, and 30 were placed under pinyon trees.  At the Bosque del Apache site, 30 baskets were placed in 3 transect lines of 10 baskets each, at 10 meter intervals, through the cottonwood forest.  At the Magdalena Mountain site, 30 baskets were placed in 3 transect lines of 10 baskets each, at 10 meter intervals (as in the Bosque site).

Sample Unit:

Each basket was considered a sample unit. 

Frequency of Sampling:

During the same times as arthropod pitfall collections (several times/year)

Sample Size:

120 baskets total.  Each basket was a rubber basin with a small (5 mm) hole drilled in the bottom to allow rainwater and snowmelt to drain out. Basket dimensions were circular, with a diameter of 41.5 cm at the top rim, tapering inward to a diameter of 35 cm at the basket bottom.  The basket height was 12.5 cm.

Measurement Techniques:

Litterfall baskets were place under tree canopies to catch falling leaves, twigs, and reproductive parts.  In the Bosque del Apache and Magdalena Mountain sites, the baskets were placed systematically in 3 transect lines through the forest (which generally had a closed canopy).  In the Pinyon-Juniper site on SNWR, the baskets were placed under individual trees (basket locations were halfway between the trunk and the edge of the canopy) due to the patchiness of tree locations. Hence, the results for this site are for a "per tree" basis, and should be scaled up to reflect different tree densities in various Pinyon-Juniper sites.

Litterfall samples were collected by placing all litter into plastic zip-lock bags, marking each bag with the basket tag number, and taking the bags back to the laboratory. If samples were wet from rain/snowfall, the sample bags were opened and allowed to air-dry for several days.  Litter was then sorted by category (leaf, twig, reproductive part, or "miscellaneous" if the part could not be recognized) and by species.  The sorted litter was then oven dried at 60 degrees Centigrade for one week, and weighed on a Mettler top-loading balance.

Data sources: 

sev022_litterfall_09072011.txt

Additional information: 

Magdalen Mountains Site, Cibola National Forest:

- Soil: rocky soils, with high organic matter (litter) below tree canopies.

- Slope/Aspect:  Various, ranging from flat to 30 degrees.  Easterly aspect.

- Vegetation Community: Mixed-species conifer forest with aspens.

- Terrain/Physiography: Mountainous

- Geology/Lithology:  Magdalena Mountains, derived from volcanic activity.

- Hydrology - surface/groundwater:  Virtually no runoff during storms due to deep litter layer.

- Size:  sampling area covered approximately 1 ha

- History (if known):  Old growth forest, no logging and no fire history.

- Elevation: 3,243 meters at weather station (station #46).

- Climate (general):  A summary of the meteorological data from the Langmuir Laboratory weather station in the Magdalena Mountains is shown below. For further climate details and data, consult the Sevilleta Meteorology databases.

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