Shrub encroachment is a global phenomenon. Both the causes and consequences of shrub encroachment vary regionally and globally. In the southwestern US a common native C3 shrub species, creosotebush, has invaded millions of hectares of arid and semi-arid C4-dominated grassland. At the Sevilleta LTER site, it appears that the grassland-shrubland ecotone is relatively stable, but infill by creosotebush continues to occur. The consequences of shrub encroachment have been and continue to be carefully documented, but the ecological drivers of shrub encroachment in the southwestern US are not well known.
One key factor that may promote shrub encroachment is grazing by domestic livestock. However, multiple environmental drivers have changed over the 150 years during which shrub expansion has occurred through the southwestern US. Temperatures are warmer, atmospheric CO2 has increased, drought and rainy cycles have occurred, and grazing pressure has decreased. From our prior research we know that prolonged drought greatly reduces the abundance of native grasses while having limited impact on the abundance of creosotebush in the grass-shrub ecotone. So once established, creosotebush populations are persistent and resistant to climate cycles. We also know that creosotebush seedlings tend to appear primarily when rainfall during the summer monsoon is well above average. However, high rainfall years also stimulate the growth of the dominant grasses creating a competitive environment that may not favor seedling establishment and survival. The purpose of the Mega-Monsoon Experiment (MegaME) is twofold. First, this experiment will determine if high rainfall years coupled with (simulated) grazing promote the establishment and growth of creosotebush seedlings in the grassland-shrubland ecotone at Sevilleta, thus promoting infill and expansion of creosotebush into native grassland. Second, MegaME will determine if a sequence of wet summer monsoons will promote the establishment and growth of native C4 grasses in areas where creosotebush is now dominant, thus demonstrating that high rainfall and dispersal limitation prevent grassland expansion into creosotebush shrubland.
Vegetation and soil measurements are taken in the spring and fall each year. Spring measurements are taken in May when spring annuals have reached peak biomass for the growing season. Fall measurements are taken in either September or October when summer annuals and all perennial species have reached peak biomass for the growing season, but prior to killing frosts. Vegetation cover is measured to assess growth and survival of grasses and shrubs. Bare soil and litter covers are also measured to monitor substrate changes that occur within the plots.
One meter2 vegetation quadrats are used to measure the cover of all plants present in each m2. There are 10 quads in each plot, checkered along on side of the plot. There is a tag on one rebar of each quad with the representative quad number.
General vegetation measurements
The cover is recorded for each species of live plant material inside the quadrat. Vegetation measurements are taken in two layers: a ground level layer that includes all grasses, forbs, sub-shrubs, and a litter and bare soil, and a “shrub” layer that includes the canopy of Larrea tridentata. The purpose of this approach is to include Larrea canopies, while allowing the cover values of the ground level layer to sum to approximately 100%. The dead plant covers are not included in the measurement, thus the total amount may not equal 100%. It is assumed that the remaining cover missing from the 100% is a combination of dead plant material.
The quadrat boundaries are delineated by the 1 m2 PVC-frame placed above the quadrat. Each PVC-frame is divided into 100 squares with nylon string. The dimensions of each square are 10cm x 10cm and represent 1 % of the total quadrat area or cover. The cover and height of all individual plants of a species that fall within the 1m2 quadrat are measured. Cover is quantified by counting the number of 10cm x 10cm squares intercepted by all individual plants of a particular species, and/or partial cover for individual plants < 1%.
Vegetation cover measurements
Cover measurements are made by summing the live cover values for all individual plants of a given species that fall within an infinite vertical column that is defined by the inside edge of the PVC-frame. This includes vegetation that is rooted outside of the frame but has foliage that extends into the vertical column defined by the PVC-frame. Again, cover is quantified by counting the number of 10cm x 10cm squares intercepted by each species. Do not duplicate overlapping canopies, just record the total canopy cover on a horizontal plane when looking down on the quadrat through the grid.
Larger cover values will vary but the smallest cover value recorded should never be below 0.1%. When dealing with individual plants that are < 1.00%, round the measurements to an increment of 0.1. Cover values between 1.00% and 10.00% should be rounded to increments of 1.0, and values > 10.00% are rounded to increments of 5.
Larrea tridentata canopy is estimated using the portion of the canopy that falls within the quadrat. The canopy edge is defined by a straight gravity line from the canopy to the ground (i.e. imagine a piece of string with a weight on the end being moved around the canopy edge). ForLarrea seedlings the code LSEED is used and is a separate measurement from the Larrea canopy measurements. The cover measurement for LSEED is simply a count of individuals, not actual cover, as it is assumed that they would have a cover of < 1.00%.
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 tissue is frequently mixed with dead tissue in grass clumps.
The cover of forbs is the perimeter around the densest portion of the plant. Measure all foliage that was produced during the current season.
Cacti and Yucca
The cover of cacti and yucca is made by estimating a perimeter around the densest portion of the plant and recorded as a single cover. For cacti that consist of a cluster of pads or jointed stems (i.e., Opuntia phaecantha, Opuntia imbricata), estimate an average perimeter around the series of plant parts and record a single coverage measurement.
Vine cover (and some forbs) is often convoluted. Rather than attempt to estimate cover directly, take a frequency count of 10X10X10cm cubes that the vine is present in.
As with other vegetation measurements, the smallest cover value for seedlings should never be <0.1%. If the value of a seedling’s cover is less, round up to 0.1%.
Non-Vegetation cover measurements
Materials other than vegetation that are measured in the drought plots include soil and litter.
Measure the cover of the area occupied by abiotic substrates. Cover is quantified by summing the number of 10cm x 10cm squares intercepted by abiotic substrates. Cover values < 10.00% should be rounded to increments of and cover values > 10.00% should be recorded in increments of 5. If there is no soil in the quadrat, record “SOIL” in the species column for that quadrat and record a “0” for cover.
Measure the cover of the area occupied by litter, which is unattached dead plant material. Cover is quantified by summing the number of 10cm x 10cm squares intercepted by abiotic substrates. Cover values < 10.00% should be rounded to increments of 1 and cover values > 10.00% should be recorded in increments of 5. If there is no litter in the quadrat, record “LITT” in the species column for that quadrat and record a “0” for cover.
Clipping grass at Ecotone Site
After measurements are taken at the Ecotone Site, grass is clipped down to the soil and removed from half of the quads in each plot. The goal is to assess the impact of competition on successful creosote seedling germination. The following quads, # 2, 4, 6, 7, and 10, get clipped in every plot at the ecotone site.
The watering schedule varies based on seasonal rainfall. Our goal is to increase average monsoon precipitation (150mm) by 50%, so we shoot for a total of 225mm on the plots during the summer monsoon.
Additional Information on the personnel associated with the Data Collection:
Stephanie Baker 2014-present
Megan McClung 2014-present
Chandra Tucker 2014-present
Global climate change processes, especially prolonged droughts and increasingly high temperatures, are significantly affecting numerous arid ecosystems across the state of New Mexico. One of the more adversely affected ecosystems in New Mexico is piñon-juniper woodland (PJ), which includes areas near Mountainair, New Mexico, USA. Because changes in ambient temperature and decreases in water availability show pervasive effects on the above-ground status of existing PJ woodlands in New Mexico, it seems likely that the effects of changes in these two master variables will manifest themselves within soil processes such as soil organic matter (SOM) decomposition rates and soil respiration rates, as well as nutrient cycling rates and availabilities to both plants and soil microbial communities.
We conducted analyses of soil physicochemical properties and soil fungal biomass via soil ergosterol content, as well as evaluating the activity rates of multiple hydrolytic exoenzymes, which are indicative of fungal activity in soils. Samples were collected from multiple tree-to-tree competition gradients that were identified in May/June of 2011. These gradients were established based on the type of mycorrhizal fungus types expected to occupy the soil community established beneath the canopy of a focal tree, with there being two focal trees in each gradient. Gradients were established between two live piñon trees (Pinus edulis), two juniper trees (Juniperus monosperma), a live piñon and live juniper, and a dead piñon and live juniper. We only sampled from under live trees at the control site.
In order to obtain these samples, we collected soil samples from two different sites in a PJ woodland located within the boundaries of the Deer Canyon ranch. Changes in soil conditions were captured by sampling from the two sites at multiple times throughout the summer of 2011. We collected samples from Dr. Marcy Litvak’s girdled PJ woodland eddy-flux tower site in June, July, August and finally in late September. We also collected samples from Dr. Litvak’s control PJ woodland tower site in June and September of 2011. Significant differences in the activity rates of the hydrolytic exoenzymes alanine aminopeptidase, alkaline phosphatase, β-d-glucosidase, and β-N-acetyl glucosaminidase were observed within soils collected at multiple times from June through September when comparing the observed rates of activities under the trees in the live piñon to live piñon gradients vs. the juniper to juniper gradients. These differences were observed in samples from multiple dates at the girdled site without there being significant differences in soil fungal biomass across seasons or study sites. Continued work with the established sites on a year-to-year basis could provide an insight into how the fungal communities within New Mexican PJ woodlands will respond to future changes in soil conditions as global climate change processes advance in New Mexico.
Experimental design: Randomized complete block design was established at 2 different study sites, girdled piñon-juniper (PJ) woodland and non-girdled (control) PJ woodland. In late May, 2011, we set-up each study site to contain six complete blocks (plots), each with multiple tree-to-tree gradients. At the girdled PJ site, each plot included five different tree-to-tree gradients: Live pine to live pine, live pine to dead pine, live pine to live juniper, dead pine to live juniper, and live juniper to live juniper. At the control PJ site we also established 6 blocks (plots); however, at this site there were only three gradients: Live pine to live juniper, dead pine to live juniper, and live juniper to live juniper.
Setting up plots: Plots and gradients were established by marking sampling locations with orange flagging tape and pin-flags by Daniel Warnock and Kimberly Elsenbroek on May 19 and 23, 2011.
Sample collection, allocation and storage: Soil samples were collected monthly from the girdled PJ woodland to establish two pre-monsoonal (dry) season time points, with samples collected on June 6, 2011 and June 15, 2011 considered as being from single time point. Soil samples collected on July 20, 2011 represented our second dry season time point. Soil samples for our two post-monsoon moisture time points were collected on August 15, 2011 and September 28, 2011. As with the girdled site, soils sample from the control PJ woodland site were collected both before and after the onset of the monsoon season. However, unlike the girdled PJ woodland site, we only have one pre-monsoon time point June 29, 2011 and one post monsoon time point, September 15, 2011.
All soil samples were collected by combining three 0-10cm sub-samples into the same zipper-locking plastic storage bag. Samples were collected from three different locations within each tree-to tree gradient. Two of the three samples were collected from locations within 30cm of the trunk of each of the two focal trees within a gradient. The other sample for each gradient was collected from a point at the center of a zone formed by the edges of the canopies from the two competing focal trees. All samples were then transported to the lab for refrigeration.
Within 24-72 hours of sample collection, 5mL sub-samples were taken from each bulked soil sample and placed into individual Corning 15mL screw-cap centrifuge tubes. Each tube was then filled to the 10mL mark with an 0.8% KOH in Methanol solution. These tubes were placed in the fridge for storage until analyzed for ergosterol content. After preparation of the samples for ergosterol analyses, 1g samples were placed into 125mL round Nalgene bottles for analyses of fungal exoenzyme actitity (EEA) rates from each sample. All enzyme activity assays were performed within 1 to 5 days after collection. Further, for all but the final post-monsoonal time points, assays were performed within 2 to 3 days of sample collection.
After all of the fresh, refrigerated samples were alloquated for ergosterol and EEA analyses we placed the remaining quantities of soil for each sample into labeled paper bags for air-drying on a lab bench. After 1-2 weeks, 30g of each sample was placed into a labeled plastic bag for shipping to Ithaca, New York, USA for analyses of soil-physicochemical properties. While taking the 30g sub-samples, a separate 5g sub-sample from the air-dried sample was placed into a labeled, no. 1 coin-envelope for storage until analysis of soil hyphal abundance. After all sub-sampling was completed any remaining soil was kept in its sample bag and stored in the lab.
Hydrolytic exoenzyme activity (EEA) assays: All hydrolytic EEA assays were performed as follows: Each 125mL sample bottle was partially filled with 50mM sodium bicarbonate buffer solution and homogenized using a Kinematica Polytron CH 6010 (Lucerne, Switzerland). Upon homogenization, sample bottles were filled to 125mL with buffer solution. Sample bottles were then set aside until placement in black, 96-well, micro-plates. At the time of placement, each sample suspension was poured into a glass crystalizing dish where it was stirred at high speed into the appropriate columns within each micro-plate. These columns included a quench control (200 uL sample suspension + 50uL MUB or methylcoumrin substrate control), a sample control (200uL sample suspension + 50uL 50mM bicarbonate buffer) and an assay column (200uL suspension + 50ul 200mM substrate). Samples were pipetted into four sets of plates with each set analyzing the activity rates of a single hydrolytic enzyme. These enzymes included alanine amino peptidase, alkaline phosphatase, β-d-glucosidase, and N-acetyl-β-d-glucosiminidase. Further, all three samples from a single gradient within a single plot were added to the same plate (e.g., all samples from the live-pine-to-live-pine gradient from plot one were pipetted into a single plate for analyzing the activity of the enzyme alkaline-phospotase.
Ultimately our plate layout was completed as follows usingt two other columns for substrate controls: In column one, we added 200uL buffer and 50uL of a substrate standard, which accounts for the fluorescence emitted by either the MUB, or the methylcoumarin group that is a component of the substrate solution added to the assay wells. In column six of each plate was a substrate control, which is a solution of 200uL buffer and 50uL of one the four different substrates used in our hydrolytic EEA assays. Columns 3-5 were our quench controls, which accounts for the quantity of fluorescence emitted by the MUB or methylcoumarin molecule absorbed by the particles in the soil suspension itself. Columns 7-9 were the sample controls and account for the amount of fluorescence emitted by the soil suspension + buffer solution added to each well. Finally, columns 10-12 were our assay wells. From these wells we could determine enzyme activity by measuring the fluorescence emitted by the MUB or methylcoumarin molecules cleaved off of the substrates initially added to each well. The substrates included in these assays included: 7-amino-4-methylcoumarin (Sigma-Aldrich), 4-MUB-phosphate (Sigma-Aldrich), 4-MUB-β-d-glucoside (Sigma-Aldrich), and 4-MUB-N-acetyl-β-d-glucosiminide (Sigma-Aldrich).
Because the intrinsic EEA rates varied across our targeted exoenzymes, assay plates were scanned for flourscence in sets of two. Alanine aminopeptidase plates and alkaline phosphatase plates were scanned twice, first at 30-40 minutes after substrate addion and again at 50-80 minutes after substrate addition. β-d-glucosidase, and N-acetyl-β-d-glucosiminidase plates were all scanned at 3-4 hours after substrate addition. The timing of the second enzyme activity time point depended on expected soil moisture conditions. Here, the post monsoon soils were allowed to incubate for a total of 5-6 hours prior to the second scan and the pre-monsoon plates were incubated for a total of 7-9 hours.
Fungal biomass measurements: Fungal biomass was quantified by measuring the concentration of ergosterol in a sub-sample taken from each soil sample collected from June to September. Within 24-72 hours of sample collection, 5mL sub-samples were taken from each bulked soil sample and placed into individual Corning 15mL screw-cap centrifuge tubes. Each tube was filled to the 10mL mark with an 0.8% KOH in methanol solution. Tubes were refrigerated for storage until analyzed for fungal biomass by measuring the ergosterol content within each sample. Ergosterol concentration for each sample was determined using HPLC with 100% methanol as the solvent at a flow rate of 1.5mL/ minute and a c-18 column. Ergosterol was quantified by measuring the peak height that passed through a detector set to measure absorbance at 282nm, at 3.7min after the sample was injected into the column. The height of each peak was then converted into μg ergosterol/g soil and finally converted to mg fungal biomass/ g soil by applying a conversion factor.
* Instrument Name: Polytron
* Manufacturer: Kinematica
* Model Number: CH 6010
* Instrument Name: GeoXT
* Manufacturer: Trimble
* Model Number: GeoExplorer 3000 series
* Instrument Name: fmax
* Manufacturer: Molecular devices
* Model Number: type 374
* Instrument Name: versamax tunable micro-plate reader
* Manufacturer: molecular devices
* Model Number: ?
* Instrument Name: SSI 222D isocratic HPLC pump
* Manufacturer: SSI
* Model Number: 222D
* Instrument Name: Thermo Seperation Products AS 1000 autosampler
* Manufacturer: Thermo Seperation Products
* Model Number: AS 1000
* Instrument Name: Acutect 500 UV/Vis Wavelength detector
* Manufacturer: Acutect
* Model Number: 500
* Instrument Name: HP 3396 series iii integrator
* Manufacturer: Hewlitt Packard
* Model Number: 3396
Girdled and control PJ woodland: 34.36N, 106.27W.
Girdled PJ woodland sampled: 6/June/2011, 15/June/2011, 20/July/2011, 15/Aug/2011, 28/Sept/2011.
Control PJ woodland sampled: 29/June/2011, 15/Sept/2011.
Increased incidence of large-scale forest die-off attributed to drought has been observed globally over the past decade, raising concern about the future stability of forests as carbon sinks. To understand the mechanistic basis of semi-arid woodland responses to drought, we measured annual increment growth from branches of Pinus edulis in a rainfall manipulation experiment at the Sevilleta National Wildlife Refuge and LTER site in central New Mexico, USA. We collected 4 branches from each of five trees growing in drought, irrigation, cover control, and ambient control plots at a site in the Los Pinos Mountains. We measured annual branch elongation, stem diameter, sapwood area, and leaf area. We compared these structural data to fluctuations in annual precipitation across treatments to understand how such variation in available water influence branch growth. Rainfall manipulation produced clear differences among treatment groups, with drought trees exhibiting shorter stem lengths, decreased stem and sapwood diameters, and decreased leaf area production than control treatments. Irrigated trees displayed increased stem length, stem diameter, sapwood diameter, and leaf area production relative to ambient controls. The net effect of these responses is a likely shift in the allometric relationships, such as hydroactive xylem and absorbing root area.
Branch sampling, four small branches were removed from each of five target trees per plot according to aspect (North, South, East, West).
Experimental design: Single block from complete block design.
Plots: Four plots of varying treatments (Irrigation, Drought, Cover control, Ambient control) were used from preexisting study, each 40m X 40m.
Sampling: Samples taken according to aspect (North, South, East, West) on all pinon target trees within one replicate block.
Measurements: Stem length, two perpendicular midpoint diameter, and two perpendicular sapwood diameters were taken for each growth increment for each sample using digital callipers. Needles from each age cohort were scanned and leaf area was estimated using ImageJ software.
The germination rate of creosote (Larrea tridentata) on the Sevilleta appears to be very low. During the early years of the LTER project it was attempted to quantify such germination through the use of seedling plots which were monitored on a bi-annual basis (spring and fall). During the period from 1989 through 1992 there were no creosote seedling that germinated on the monitoring plots. In 1999 a rather sizeable population of small seedlings was observed in one quite localized area in the vicinity of Five Points. This rather large number of individuals in one very limited area raised several questions:1. When did this small community of individuals germinate- the supposition is that they had all germinated at the same time.2. What conditions existed in this particular location which allowed such prolific germination when there was no indication of virtually any other germination in this vicinty.3. The most immediate question was whether these seedlings would survive through the impending La Nina winter, spring and summer as many of the individuals did not appear to be very "healthy." To help answer these questions it was decided to begin a "small" monitoring project. All of the individuals in this small area thatappeared to be of the same age were marked with posts, located with GPS, measured (height) and photographed. This initial survey included 78 individuals. The population was resurveyed in August, 2000 and it was discovered that: 1. Many individuals were missed in the initial survey; 2. Most of the individuals (72 of 78) had survived the intervening 9 months; and 3. The average individual growth during this period was 1.4 cm. It is planned that this population will continue to be monitored (probably on an annual basis) to track survival and growth rate of these individuals.
Experimental Design: There has been little recent germination of creosote in the Five Points area. However, the discovery of a patch of relatively new seedlings in one localized area in Nov. 1999 prompted the initiation of this sampling. Continued measurement through time provides growth rates that can then be correlated with meteorological conditions.
Data Collection: Seedlings were marked by pounding galvanized pipes (about 1 m long) into the soil about 6" south of the seedlings. In some cases a single pipe was used to mark more than one seedling. Pipe numbers were written with black magic marker near the top of the pipe. Seedling numbers were written near ground level so they could be seen when photographed. Each pipe was GPS'd.
The height of each seedling was measured to the nearest mm. Measuring was done from the soil surface to a plane even with the top of the tallest leaves. Each seedling was photographed and a meter stick was laid horizontally on the ground (parallel to the plane of the photograph) against the corresponding pipe for scale. In some cases, multiple seedlings were included in one photograph. Arrows on the pipe indicated designated seedlings. These photos were taken with slide film and are currently in the possession of Doug Moore.
The initial cohort of seedlings from 1999 were remeasured on Aug 23, 2000 and seedlings 79-101 added to the data set. At that time, more seedlings were discovered. Seedlings 102-175 were measured on Sep 18, 2000.
Beginning in 2001, two diameters of the crown were measured; the first at the widest point and the second perpendicular to the first.
Between 2001 and 2004, the permenant marker that had been used to mark each pipe faded to the point that they could no longer be read. In 2004, numbered aluminum tags were attached to the pipes with wire but the numbers of the pipes and the corresponding samples no longer designate the same individual as prior to 2004.
Also, note the effect of the unprecedented freeze event of early 2011.
11/01/09 (JMM) Metadata updated and compiled from 1999 to 2009 data.
01/29/09 (YX) Metadata updated and compiled from 1999 to 2008 data.
01/28/2009 (YX) 99-2008 dataset was checked for errors and missing data.
Additional Information on the personnel associated with the Data Collection / Data Processing
Joy Francis, a post-doc with Jim Gosz, was instrumental in setting up this study.
1. Initiated - November 11, 1999, and Resurvey - August 23, 2000. 2. Marked missed seedlings - September 18, 2000. 3. Measured 1-79 - October 9, 2001-measured both height and 2 diameters. 4. Measured 129 - Dec.13, 2004 - Measured both height and 2 diameters. 5. Measured 1-129 - Sept. 22, 2005 - Measured both height and 2 diameters. 2006-2008 measured 1-129 for both height and 2 diameters.
Plant phenology or life-history pattern changes seasonally as plants grow, mature, flower, and produce fruit and seeds. Plant phenology follows seasonal patterns, yet annual variation may occur due to annual differences in the timing of rainfall and ambient temperature shifts. Foliage growth and fruit and seed production are important aspects of plant population dynamics and food resource availability for animals. The purpose of this study is to assess plant phenology patterns across a series of biotic communities that represent an environmental moisture gradient. These communites include: Chihuhuan Desert creosotebush shrubland, Chihuahuan Desert black grama grassland, and blue grama grassland. Plant phenology is recorded for all plant species across 4 replicate 200 m transects at each of the 3 habitat sites. Plant phenology measurements are taken once every month from February through October. The first ten individuals of each plant species encountered along each transect are assessed for life-history status. Data recorded include the status of leaves, flowers and fruit. Leaves are recorded as new, old, brown or absent. Reproductive status is recorded as absent, buds, flowers, fruits or both fruits and flowers. Data from the site P and J were only collected in 2000 and 2001 and are included in this data set.
The purpose of this study is to assess plant phenology patterns across a series of biotic communities that represent an environmental moisture gradient.
Locating the Transects:
Phenological conditions are recorded along four permanently marked 200 m x 2 m wide transects at each of the core study sites. The transects are located within four of the five rodent trapping webs. All five transects were originally measured, but in 2003 the least diverse transect at each site was dropped. Each web consists of twelve 100 m transects radiating as spokes from a central rebar stake marked #145. As measured from the center stake, the first four stakes within a ray are positioned at 5 m intervals and the remaining eight at 10 m intervals along a given transect. Plant phenology is recorded along two of these 100 m transects, the transect that extends due north from the central stake and the transect that extends due south from the central stake. The stakes that extend due north are marked 1-12 where stake #1 is closest to the center stake. The stakes that extend due south are marked 73-84 where stake #73 is closest to center.
Collecting the Data:
Each transect is sampled by one technician. Measurements are started from the northern (stake #12) end of each transect. The technician walks in a straight line from one stake to the next surveying a 1 m wide area on each side of the line until the opposite end of the transect is reached. As a transect is walked, phenological conditions are recorded for each species that occurs along the transect. The phenological condition of the first 10 individuals of each species is recorded. After the conditions of ten individuals have been recorded no more observations are made for that particular species even though more may be encountered. Conversely, for rare species only a few individuals may be encountered so there will be less than 10 observations.
Because measurements are taken on separate individuals, it is important to note that many plants have clonal growth forms. This can be seen in some grasses that occur as a clump of overlapping vegetation. In this case each clump is treated as a single individual. This is also true for some cactus and yucca species that appear as a cluster of many individual heads.
Determining Phenological Conditions:
1. New green foliage (N)
This category refers to a plant that is producing new vegetative tissue. The production of new vegetative tissue can be characterized in several ways depending on the species. In many herbaceous plants, new vegetative growth will be indicated by the presence of immature leaves or stems. In herbaceous plants this growth generally appears near the tips of shoots and also at axillary buds.
For species that have a rosette growth form (yucca, some herbaceous plants), the center of the rosette is examined for the presence of immature leaves.
In cacti, the spines are modified leaves and do not readily indicate new vegetative growth so cacti are examined for production of new stems. For example, in Opuntia spp., the presence of a new stem/pad represents new green foliage as each stem-joint represents a season's growth. Cacti that exhibit a cylindrical growth form are more difficult to classify. Cacti with tuberculate stems (Mammilaria spp.) are examined for new tubercules which can often be seen in the center of the head. More problematic are the ribbed cacti where the growth of one season is continuous with that of the preceding season. While these species may be producing new growth it is extremely difficult to identify and thus they are usually categorized as old green foliage.
2. Old green foliage (O)
This category refers to a plant that is not producing new vegetative tissue but exhibits only mature green foliage.
3. Brown leaves (B)
This category refers to a plant that has only brown leaves and is used to indicate a period of senescence or decline.
4. No leaves (Z)
This category is similar to the above category. It is meant to capture a period of senescence or decline and refers to a plant that has subsequently dropped its leaves. It only applies to growth forms that drop their leaves during a period of dormancy or senescence. This category is not used for plants such as Ephedra spp. that normally do not have leaves.
1. New flowers (FL)
This category refers to the presence of flowers at anthesis (open flowers). For many species the petals are large and showy making this condition easy to identify. In species with small or reduced flowers, this condition represents the presence of key reproductive structures such as stamens and/or carpels.
2. New fruit (FR)
This category refers to the presence of a ripened ovary that contains seed. Open fruits that do not contain seed are not categorized as fruiting. Open fruits that do contain seed belong in this category.
3. Fruits and Flowers (FF)
This category indicates that both fruit and flowers are present.
4. No Fruits or Flowers (Z)
This category indicates that neither fruits or flowers are present.
5. Flower buds (B)
This category indicates that only closed flower buds are present.
Each month, the data is QAQCd for typos and incorrect plant codes. To do this in Excel, place the cursor in the first cell of the actual data, not the headings. Go to Data/Filter and select auto filter. Each list formed should fit the parameters listed above. The plant list and the unknown plant list should be updated regularly. Check all errors against the paper data. Be sure that the numbers at the end of the kartez codes are correct. In most cases, all errors can be fixed at this time.
At the end of every year, compile all the data into one file for the year. Check to make sure no data is missing or duplicated. Also, each year, all the previous years data should be updated using the unknown plant list to replace former unknowns with their proper kartez code. At this point all compiled, yearly data sets should be re-archived, replacing the old data sets. Meta data should be maintained with every data set.
Recording the Data:
For each transect, the following is recorded:
1. Recorder- Recorder's initials and also the initials of anyone helping take measurements on that particular transect.
2. The date (month, day, year)
3. The site (B, G, C, J, P)
B = Blue grama grassland
G = Five-Points grassland
C = Five-Points creosote
J = Juniper Savanna
P = Pinon-Juniper woodland
4. The web (1,2,3,4,5)
5. The page number (1/3, 2/3, 3/3)
The species code for all the species occurring along the transect is recorded. Then the phenological conditions of the individual plants in the area are recorded in the Fol and Flw columns of the data sheet. The Fol column is for status codes reflecting the condition of a plant's foliage and the Flw column is for codes reflecting the reproductive status of the plant. The status codes are as follows:
N = new green foliage
O = old green foliage only
B = brown leaves only
Z = no leaves
FL = new flower
FR = new fruits
FF = new fruits and flowers
Z = no fruits or flowers
B = Only buds present
BFL = Buds and flowers
BFR = Buds and fruits
The phenology data is taken with paper and pencil.
For both 2007 and 2008, individual monthly files were checked for errors and compiled in pc_field/phenology. These were uploaded into navicat. Then all the data was exported and put on line with this updated meta data and EML.
Phenology data from 2001-2006 was taken out of flat files and imported into MySQL. Once in the database, I checked for duplicates. These most often happened when a recorder had already taken data for a particular species and accidentally started a new row for data for that species. In these instances, no data was deleted, but the observation numbers were made consecutive. Therefore, they end up with more than 10 observations per web. In no case was this more than 20. The other reason I found duplicates was in years where certain recorders collected separate data for seedlings and adults. In these cases, no data was thrown away and againg the observation number was made consecutive and there also can be up to 20 observations per web for these species. Always in this case the comment "SEEDLING" was added to the relevant observations. I also checked every plant code against the USDA Plants database online at http://plants.usda.gov/ All plant codes that have had nomenclature changes were updated. All previously unknown plants that have since been identified were also updated. All unknown plants that will never be identified were dropped from the database. All typos were corrected. The original code was stored in the database under the collumn title OLD_SPECIES, but is not available online.
Each month, the data should be QAQCd for typos and incorrect plant codes. To do this in Excel, place the cursor in the first cell of the actual data, not the headings. Go to Data/Filter and select auto filter. Each list formed should fit the parameters listed above. The plant list and the unknown plant list should be updated regularly. Check all errors against the paper data. Be sure that the numbers at the end of the kartez codes are correct. In most cases, all errors can be fixed at this time.At the end of every year, compile all the data into one file for the year. Check to make sure no data is missing or duplicated. Also, each year, all the previous years data should be updated using the unknown plant list to replace former unknowns with their proper kartez code. At this point all compiled, yearly data sets should be re-archived, replacing the old data sets. Meta data should be maintained with every data set.
Sevilleta Field Crew Employee History
Chandra Tucker (CAT; 04/2014-present), Megan McClung (MAM; 04/2013-present), Stephanie Baker (SRB; 10/2010-present), John Mulhouse (JMM; 08/2009-06/2013), Amaris Swann (ALS; 08/2008-01/2013), Maya Kapoor, August 9, 2003-January 21, 2005 and April 2010-March 2011, Terri Koontz, February 2000-August 2003 and August 2006-August 2010, Yang Xia, January 31, 2005-April 2009, Karen Wetherill, February 7, 2000-August 2009, Michell Thomey, September 3, 2005-August 2008, Jay McLeod, January 2006-August 2006, Charity Hall, January 31, 2005-January 3, 2006, Tessa Edelen, August 15, 2004-August 15, 2005, Seth Munson, September 9, 2002-June 2004, Caleb Hickman, September 9, 2002-November 15, 2004, Heather Simpson, August 2000-August 2002, Chris Roberts, September 2001-August 2002, Mike Friggens, 1999-September 2001, Shana Penington, February 2000-August 2000.
Dates of collection for each field site:
Site B: April 2001 - present
Site C: April 2000 - present
Site G: April 2000 - present
Site J: April 2000 - November 2001
Site P: April 2000 - November 2001