climate

Warming-El Nino-Nitrogen Deposition Experiment (WENNDEx): Soil Temperature, Moisture, and Carbon Dioxide Data from the Sevilleta National Wildlife Refuge, New Mexico (2011 - present)

Abstract: 

Humans are creating significant global environmental change, including shifts in climate, increased nitrogen (N) deposition, and the facilitation of species invasions. A multi-factorial field experiment is being performed in an arid grassland within the Sevilleta National Wildlife Refuge (NWR) to simulate increased nighttime temperature, higher N deposition, and heightened El Niño frequency (which increases winter precipitation by an average of 50%). The purpose of the experiment is to better understand the potential effects of environmental drivers on grassland community composition, aboveground net primary production and soil respiration. The focus is on the response of two dominant grasses (Bouteloua gracilis and B eriopoda), in an ecotone near their range margins and thus these species may be particularly susceptible to global environmental change.

It is hypothesized that warmer summer temperatures and increased evaporation will favor growth of black grama (Bouteloua eriopoda), a desert grass, but that increased winter precipitation and/or available nitrogen will favor the growth of blue grama (Bouteloua gracilis), a shortgrass prairie species. Treatment effects on limiting resources (soil moisture, nitrogen availability, species abundance, and net primary production (NPP) are all being measured to determine the interactive effects of key global change drivers on arid grassland plant community dynamics and ecosystem processes. This dataset shows values of soil moisture, soil temperature, and the CO2 flux of the amount of CO2 that has moved from soil to air.

On 4 August 2009 lightning ignited a ~3300 ha wildfire that burned through the experiment and its surroundings. Because desert grassland fires are patchy, not all of the replicate plots burned in the wildfire. Therefore, seven days after the wildfire was extinguished, the Sevilleta NWR Fire Crew thoroughly burned the remaining plots allowing us to assess experimentally the effects of interactions among multiple global change presses and a pulse disturbance on post-fire grassland dynamics.

Core Areas: 

Data set ID: 

305

Keywords: 

Methods: 

Experimental Design

Our experimental design consists of three fully crossed factors (warming, increased winter precipitation, and N addition) in a completely randomized design, for a total of eight treatment combinations, with five replicates of each treatment combination, for a total of 40 plots. Each plot is 3 x 3.5 m. All plots contain B. eriopoda, B. gracilis and G. sarothrae. Our nighttime warming treatment is imposed using lightweight aluminum fabric shelters (mounted on rollers similar to a window shade) that are drawn across the warming plots each night to trap outgoing longwave radiation. The dataloggers controlling shelter movements are programmed to retract the shelters on nights when wind speeds exceed a threshold value (to prevent damage to shelters) and when rain is detected by a rain gauge or snow is detected by a leaf wetness sensor (to prevent an unintended rainout effect).

Each winter we impose an El Nino-like rainfall regime (50% increase over long-term average for non-El Nino years) using an irrigation system and RO water. El Nino rains are added in 6 experimental storm events that mimic actual El Nino winter-storm event size and frequency. During El Nino years we use ambient rainfall and do not impose experimental rainfall events. For N deposition, we add 2.0 g m-2 y-1 of N in the form of NH4NO3 because NH4 and NO3 contribute approximately equally to N deposition at SNWR (57% NH4 and 43% NO3; Bez et al., 2007). The NH4NO3 is dissolved in 12 liters of deionized water, equivalent to a 1 mm rainfall event, and applied with a backpack sprayer prior to the summer monsoon. Control plots receive the same amount of deionized water.

Soil Measurements

Soil temperature is measured with Campbell Scientific CS107 temperature probes buried at 2 and 8 cm In the soil. Soil volume water content, measured with Campbell Scientific CS616 TDR probes is an integrated measure of soil water availability from 0-15 cm deep in the soil. Soil CO2 is measured with Vaisala GM222 solid state CO2 sensors. For each plot, soil sensors are placed under the canopy of B. eriopoda at three depths: 2, 8, and 16 cm. Measurements are recorded every 15 minutes.

CO2 fluxes are calculated using the CO2, temperature, and moisture data, along with ancillary variables following the methods of Vargas et al (2012) Global Change Biology

Values of CO2 concentration are corrected for temperature and pressure using the ideal gas law according to the manufacturer (Vaisala). We calculate soil respiration using the flux-gradient method (Vargas et al. 2010) based on Fick’s law of diffusion where the diffusivity of CO2 is corrected for temperature and pressure (Jones 1992) and calculated as a function of soil moisture, porosity and texture (Moldrup et al. 1999).

Data sources: 

sev305_wenndex_soiltemp_moisture_co2_2011
sev305_wenndex_soiltemp_moisture_co2_2012
sev305_wenndex_soiltemp_moisture_co2_2013
sev305_wenndex_soiltemp_moisture_co2_2014
sev305_wenndex_soiltemp_moisture_co2_2015

Instrumentation: 

Instrument Name: Solid State Soil CO2 sensor
Manufacturer: Vaisala
Model Number: GM222

Instrument Name: Temperature Probe
Manufacturer: Campbell Scientific
Model Number: CS107

Instrument Name: Water Content Reflectometer Probe
Manufacturer: Campbell Scientific
Model Number: CS616

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.

Monsoon Rainfall Manipulation Experiment (MRME) Soil Temperature, Moisture and Carbon Dioxide Data from the Sevilleta National Wildlife Refuge, New Mexico (2012- present)

Abstract: 

The Monsoon Rainfall Manipulation Experiment (MRME) is designed to understand changes in ecosystem structure and function of a semiarid grassland caused by increased precipitation variability, by altering rainfall pulses, and thus soil moisture, that drive primary productivity, community composition, and ecosystem functioning. The overarching hypothesis being tested is that changes in event size and frequency will alter grassland productivity, ecosystem processes, and plant community dynamics. Treatments include (1) a monthly addition of 20 mm of rain in addition to ambient, and a weekly addition of 5 mm of rain in addition to ambient during the months of July, August and September. It is predicted that changes in event size and variability will alter grassland productivity, ecosystem processes, and plant community dynamics. In particular, we predict that many small events will increase soil CO2 effluxes by stimulating microbial processes but not plant growth, whereas a small number of large events will increase aboveground NPP and soil respiration by providing sufficient deep soil moisture to sustain plant growth for longer periods of time during the summer monsoon.

Core Areas: 

Data set ID: 

304

Keywords: 

Methods: 

Experimental Design

MRME contains three ambient precipitation plots and five replicates of the following treatments: 1) ambient plus a weekly addition of 5 mm rainfall, 2) ambient plus a monthly addition of 20 mm rainfall. Rainfall is added during the monsoon season (July-Sept) by an overhead (7 m) system fitted with sprinkler heads that deliver rainfall quality droplets. At the end of the summer, each treatment has received the same total amount of added precipitation, delivered in different sized events. Each plot (9x14 m) includes subplots (2x2 m) that receive 50 kg N ha-1 y-1. Each year we measure: (1) seasonal (July, August, September, and October) soil N, (2) plant species composition and ANPP, (3) annual belowground production in permanently located root ingrowth cores, and (4) soil temperature, moisture and CO2 fluxes (using in situ solid state CO2 sensors).

Soil Measurements

Soil temperature is measured with Campbell Scientific CS107 temperature probes buried at 2 and 8 cm In the soil. Soil volume water content, measured with Campbell Scientific CS616 TDR probes is an integrated measure of soil water availability from 0-15 cm deep in the soil. Soil CO2 is measured with Vaisala GM222 solid state CO2 sensors. For each plot, soil sensors are placed under the canopy of B. eriopoda at three depths: 2, 8, and 16 cm. Measurements are recorded every 15 minutes.

CO2 fluxes are calculated using the CO2, temperature, and moisture data, along with ancillary variables following the methods of Vargas et al (2012) Global Change Biology

Values of CO2 concentration are corrected for temperature and pressure using the ideal gas law according to the manufacturer (Vaisala). We calculate soil respiration using the flux-gradient method (Vargas et al. 2010) based on Fick’s law of diffusion where the diffusivity of CO2 is corrected for temperature and pressure (Jones 1992) and calculated as a function of soil moisture, porosity and texture (Moldrup et al. 1999).

Data sources: 

sev304_mrme_soiltemp_moisture_co2_2012
sev304_mrme_soiltemp_moisture_co2_2013
sev304_mrme_soiltemp_moisture_co2_2014
sev304_mrme_soiltemp_moisture_co2_2015

Instrumentation: 

Instrument Name: Solid State Soil CO2 sensor
Manufacturer: Vaisala
Model Number: GM222

Instrument Name: Temperature Probe
Manufacturer: Campbell Scientific
Model Number: CS107

Instrument Name: Water Content Reflectometer Probe
Manufacturer: Campbell Scientific
Model Number: CS616

Additional information: 

Additional Study Area Information

Study Area Name: Monsoon site

Study Area Location: Monsoon site is located just North of the grassland Drought plots

Vegetation: dominated by black grama (Bouteloua eriopoda), and other highly prevalent grasses include Sporabolus contractus, S.cryptandrus, S. lexuosus, Muhlenbergia aernicola and Bouteloua gracilis.

North Coordinate:34.20143
South Coordinate:34.20143
East Coordinate:106.41489
West Coordinate:106.41489

Riparian Evapotranspiration (ET) Study (SEON) from the Middle Rio Grande River Bosque, New Mexico (1999-2011): Micrometeorological 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 are the meteorological data collected as part of this study.

Core Areas: 

Data set ID: 

311

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.

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: 

sev311_bosqueETmet_20160713.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)

Warming-El Nino-Nitrogen Deposition Experiment (WENNDEx): Soil Nitrogen Data from the Sevilleta National Wildlife Refuge, New Mexico (2006 - present)

Abstract: 

Humans are creating significant global environmental change, including shifts in climate, increased nitrogen (N) deposition, and the facilitation of species invasions. A multi-factorial field experiment is being performed in an arid grassland within the Sevilleta National Wildlife Refuge (NWR) to simulate increased nighttime temperature, higher N deposition, and heightened El Niño frequency (which increases winter precipitation by an average of 50%). The purpose of the experiment is to better understand the potential effects of environmental drivers on grassland community composition, aboveground net primary production and soil respiration. The focus is on the response of two dominant grasses (Bouteloua gracilis and B eriopoda), in an ecotone near their range margins and thus these species may be particularly susceptible to global environmental change.

It is hypothesized that warmer summer temperatures and increased evaporation will favor growth of black grama (Bouteloua eriopoda), a desert grass, but that increased winter precipitation and/or available nitrogen will favor the growth of blue grama (Bouteloua gracilis), a shortgrass prairie species. Treatment effects on limiting resources (soil moisture, nitrogen availability, species abundance, and net primary production (NPP) are all being measured to determine the interactive effects of key global change drivers on arid grassland plant community dynamics and ecosystem processes.

On 4 August 2009 lightning ignited a ~3300 ha wildfire that burned through the experiment and its surroundings. Because desert grassland fires are patchy, not all of the replicate plots burned in the wildfire. Therefore, seven days after the wildfire was extinguished, the Sevilleta NWR Fire Crew thoroughly burned the remaining plots allowing us to assess experimentally the effects of interactions among multiple global change presses and a pulse disturbance on post-fire grassland dynamics.

This data set provides soil N availability in each plot of the warming experiment for the monsoon season (also see SEV176).

Data set ID: 

307

Core Areas: 

Keywords: 

Data sources: 

sev307_Warmingsoilnitrogendata_20160711.csv

Methods: 

Experimental Design

Our experimental design consists of three fully crossed factors (warming, increased winter precipitation, and N addition) in a completely randomized design, for a total of eight treatment combinations, with five replicates of each treatment combination, for a total of 40 plots. Each plot is 3 x 3.5 m. All plots contain B. eriopoda, B. gracilis and G. sarothrae. Our nighttime warming treatment is imposed using lightweight aluminum fabric shelters (mounted on rollers similar to a window shade) that are drawn across the warming plots each night to trap outgoing longwave radiation. The dataloggers controlling shelter movements are programmed to retract the shelters on nights when wind speeds exceed a threshold value (to prevent damage to shelters) and when rain is detected by a rain gauge or snow is detected by a leaf wetness sensor (to prevent an unintended rainout effect).

Each winter we impose an El Nino-like rainfall regime (50% increase over long-term average for non-El Nino years) using an irrigation system and RO water. El Nino rains are added in 6 experimental storm events that mimic actual El Nino winter-storm event size and frequency. From January-March, there are 4x5mm applications, 1x10mm application and 1x20mm application. For N deposition, we add 2.0 g m-2 y-1 of N in the form of NH4NO3 because NH4 and NO3 contribute approximately equally to N deposition at SNWR (57% NH4 and 43% NO3; Báez et al., 2007, J Arid Environments). The NH4NO3 is dissolved in 12 liters of deionized water, equivalent to a 1 mm rainfall event, and applied with a backpack sprayer prior to the summer monsoon. Control plots receive the same amount of deionized water.

Instrumentation:

Soil N is measured using Plant Root Simulator Probes (PRS® Probes, Western Ag Innovations, Saskatoon, Saskatchewan, Canada https://www.westernag.ca/innov).

Probes are installed in late June or early July prior to the monsoon season and removed in October each year.

Additional information: 

Study Area Name: Warming site

Study Area Location: Within the Sevilleta, the site is located just Northeast of Deep Well meteorological station. The site can be reached by parking on the main road next to the signs for deep well and the minirhiztron study. Note that the road to Deep Well met station does not permit vehicles. Travel on foot towards deep well and look for a well-trod path off to the right shortly before the met station.

Vegetation: The vegetation is Chihuahuan Desert Grassland, dominated by black grama (Bouteloua eriopoda & B. gracilis).

North Coordinate:34.35946709
South Coordinate:34.35995732
East Coordinate:-106.69020587
West Coordinate:-106.69086619

Ecosystem-Scale Rainfall Manipulation in a Piñon-Juniper Forest at the Sevilleta National Wildlife Refuge, New Mexico: Sap Flow 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. 

The focus of this study was to determine the effects of rainfall manipulation on our two target tree species.  Therefore, the analysis of the water relations of these trees was an essential component of the project.  Sap-flow within each individual target tree was monitored through the use of Granier probes.  These monitoring efforts provided a window on processes such as transpiration and the night-time re-filling of the xylem tissue.  Drought tolerance and adaptation strategies were also explored by comparing differences in sap-flow rates across treatment types and between species.

Core Areas: 

Data set ID: 

277

Additional Project roles: 

361
362
363
364
365
366

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. 

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 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). The south facing block of experimental plots (the intensive physiology block) was extensively instrumented with sensors to measure both abiotic and plant physiological parameters. The non-intensive experimental plots in the north facing and flat blocks were initially only instrumented to monitor abiotic conditions.  

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.  Stem sap-flow (JS) was measured using Granier heat dissipation sap flow sensors installed in 2007 in each intensive physiology plot within the south aspect block.  Trees in north facing (plots 5-8) and flat blocks (plots 1-4) were not instrumented with sap-flow sensors during the 2007 or 2008 seasons.  All target trees had two 10mm Granier sap-flow sensors installed in the outermost sapwood (Granier 1987).  Each sensor used the traditional two probe heated and unheated reference design (Granier 1987), with two additional probes located 5 cm to the right side of the primary probes to correct for axial temperature gradients in the stem (Goulden and Field 1994). We found that this compensation for axial temperature gradients is critical to reduce measurement noise resulting from the open-canopy and high radiation environment of this ecosystem.  In addition, stems were wrapped with reflective insulation (Reflectix Inc., Markleville, IN) in an effort to shield sap-flow probes from short term ambient temperature fluctuations and direct solar irradiance.  Sapflow (JS) was calculated according to the methods outlined in Granier (1987) and Goulden and Field (1994). Sapwood depth was generally greater than 10 mm on the majority of instrumented trees, thus only a small % of measurements required a correction due to sensor installation in non-functional stem heartwood (see Clearwater and others 1999).  All data from sap-flow sensors was recorded using Campbell Scientific AM16/32 multiplexers and CR1000 dataloggers (Campbell Scientific, Logan, UT).

Statistics 

Statistical tests for treatment differences in stem sap-flow (JS) were analyzed using a linear-effects mixed model with repeated measures.  For the repeated measures analysis, an autoregressive first order [AR(1)] covariance structure was utilized.  Differences between groups and/or treatment means were deemed significant at a threshold α-value of p = 0.05.   All mean values are reported with ± 1 S.E.  

Data Processing and Quality Assurance & Control (QA-QC)

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.

Data sources: 

sev277_pjsapflow06_20150608.txt
sev277_pjsapflow07_20150608.txt
sev277_pjsapflow08_20150608.txt
sev277_pjsapflow09_20150608.txt
sev277_pjsapflow10_20150608.txt
sev277_pjsapflow11_20150608.txt
sev277_pjsapflow12_20150608.txt
sev277_pjsapflow13_20150608.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 Sapflow Js 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 (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.

The remaining cols in the data frame are the 15 minute sap-flow data for each tree in a particular plot.   This type of variable is commonly referred to as sapflow density, and it is represented by the symbol/abbreviation JS, in units of (g/m2 s).  

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: 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).  

Warming-El Nino-Nitrogen Deposition Experiment (WENNDEx): Meteorology Data (4/30/2007 - 8/5/2009)

Abstract: 

Humans are creating significant global environmental change, including shifts in climate, increased nitrogen (N) deposition, and the facilitation of species invasions. A multi-factorial field experiment is being performed in an arid grassland within the Sevilleta National Wildlife Refuge (NWR) to simulate increased nighttime temperature, higher N deposition, and heightened El Niño frequency (which increases winter precipitation by an average of 50%). The purpose of the experiment is to better understand the potential effects of environmental change on grassland community composition and the growth of introduced creosote seeds and seedlings. The focus is on the response of three dominant species, all of which are near their range margins and thus may be particularly susceptible to environmental change.

It is hypothesized that warmer summer temperatures and increased evaporation will favor growth of black grama (Bouteloua eriopoda), a desert grass, but that increased winter precipitation and/or available nitrogen will favor the growth of blue grama (Bouteloua gracilis), a shortgrass prairie species. Treatment effects on limiting resources (soil moisture, nitrogen mineralization, precipitation), species growth (photosynthetic rates, creosote shoot elongation), species abundance, and net primary production (NPP) are all being measured to determine the interactive effects of key global change drivers on arid grassland plant community dynamics.

Core Areas: 

Data set ID: 

258

Keywords: 

Data sources: 

sev258_warmingmet_03012012.txt

Methods: 


Experimental Design

Our experimental design consists of three fully crossed factors (warming, increased winter precipitation, and N addition) in a completely randomized design, for a total of eight treatment combinations, with five replicates of each treatment combination, for a total of 40 plots. Each plot is 3 x 3.5 m. All plots contain B. eriopoda, B. gracilis and G. sarothrae. Our nighttime warming treatment is imposed using lightweight aluminum fabric shelters (mounted on rollers similar to a window shade) that are drawn across the warming plots each night to trap outgoing longwave radiation. The dataloggers controlling shelter movements are programmed to retract the shelters on nights when wind speeds exceed a threshold value (to prevent damage to shelters) and when rain is detected by a rain gauge or snow is detected by a leaf wetness sensor (to prevent an unintended rainout effect).

Each winter we impose an El Nino-like rainfall regime (50% increase over long-term average for non-El Nino years) using an irrigation system and RO water. El Nino rains are added in 6 experimental storm events that mimic actual El Nino winter-storm event size and frequency. During El Nino years we use ambient rainfall and do not impose experimental rainfall events. For N deposition, we add 2.0 g m-2 y-1 of N in the form of NH4NO3 because NH4 and NO3 contribute approximately equally to N deposition at SNWR (57% NH4 and 43% NO3; Bez et al., 2007). The NH4NO3 is dissolved in 12 liters of deionized water, equivalent to a 1 mm rainfall event, and applied with a backpack sprayer prior to the summer monsoon. Control plots receive the same amount of deionized water.

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.

Biome Transition Along Elevational Gradients in New Mexico (SEON) AmeriFlux Data (ongoing since 2007)

Abstract: 

The varied topography and large elevation gradients that characterize the arid and semi-arid Southwest create a wide range of climatic conditions - and associated biomes - within relatively short distances. This creates an ideal experimental system in which to study the effects of climate on ecosystems. Such studies are critical givien that the Southwestern U.S. has already experienced changes in climate that have altered precipitation patterns (Mote et al. 2005), and stands to experience dramatic climate change in the coming decades (Seager et al. 2007; Ting et al. 2007). Climate models currently predict an imminent transition to a warmer, more arid climate in the Southwest (Seager et al. 2007; Ting et al. 2007). Thus, high elevation ecosystems, which currently experience relatively cool and mesic climates, will likely resemble their lower elevation counterparts, which experience a hotter and drier climate. In order to predict regional changes in carbon storage, hydrologic partitioning and water resources in response to these potential shifts, it is critical to understand how both temperature and soil moisture affect processes such as evaportranspiration (ET), total carbon uptake through gross primary production (GPP), ecosystem respiration (Reco), and net ecosystem exchange of carbon, water and energy across elevational gradients.

We are using a sequence of six widespread biomes along an elevational gradient in New Mexico -- ranging from hot, arid ecosystems at low elevations to cool, mesic ecosystems at high elevation to test specific hypotheses related to how climatic controls over ecosystem processes change across this gradient. We have an eddy covariance tower and associated meteorological instruments in each biome which we are using to directly measure the exchange of carbon, water and energy between the ecosystem and the atmosphere. This gradient offers us a unique opportunity to test the interactive effects of temperature and soil moisture on ecosystem processes, as temperature decreases and soil moisture increases markedly along the gradient and varies through time within sites.

Data for this project can be found on the website:  http://ameriflux.ornl.gov/

Additional Project roles: 

302

Core Areas: 

Data set ID: 

254

Keywords: 

Data sources: 

sev254_sevameriflux_20131211.csv

Methods: 

Data collection follows Ameriflux protocols.  

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