canopy cover

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


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

Above-ground net primary production is the change in plant biomass, represented by stems, flowers, fruit and and foliage, over time and incoporates growth as well as loss to death and decomposition. To measure this change the vegetation variables in this dataset, including species composition and the cover and height of individuals, are sampled twice yearly (spring and fall) at permanent 1m x 1m plots within each site. A third sampling at Site C is performed in the winter. Volumetric measurements are made using vegetation data from permanent plots (SEV278, "Pinon-Juniper (Core Site) Quadrat Data for the Net Primary Production Study") and regressions correlating species biomass and volume constructed using seasonal harvest weights from SEV157, "Net Primary Productivity (NPP) Weight Data."

Data set ID: 


Core Areas: 

Additional Project roles: 




Data Processing Techniques to Derive Biomass and NPP:

Data from SEV278 and SEV157 are used used to calculate seasonal and annual production of each species in each quadrat for a given year. Allometric equations derived from harvested samples of each species for each season are applied to the measured cover, height, and count of each species in each quadrat. This provides seasonal biomass for winter, spring, and fall.

Seasonal NPP is derived by subtracting the previous season's biomass from the biomass for the current season. For example, spring NPP is calculated by subtracting the winter weight from the spring weight for each species in a given quadrat. Negative differences are considered to be 0. Likewise, fall production is computed by subtracting spring biomass from fall biomass. Annual biomass is taken as the sum of spring and fall NPP.

Data sources: 


Additional information: 

Other researchers involved with collecting samples/data: 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-present), Maya Kapoor (MLK; 08/2003 - 01/2005, 05/2010 - 03/2011), Terri Koontz (TLK; 02/2000 - 08/2003, 08/2006 - 08/2010), Yang Xia (YX; 01/2005 - 03/2010), Karen Wetherill (KRW; 02/2000 - 08/2009);  Michell Thomey (MLT; 09/2005 - 08/2008), Heather Simpson (HLS; 08/2000 - 08/2002), Chris Roberts (CR; 09/2001- 08/2002), Shana Penington (SBP; 01/2000 - 08/2000), Seth Munson (SMM; 09/2002 - 06/2004), Jay McLeod (JRM; 01/2006 - 08/2006); Caleb Hickman (CRH; 09/2002 - 11/2004), Charity Hall (CLH; 01/2005 -  01/2006), Tessa Edelen (MTE, 08/2004 - 08/2005).

Gunnison's Prairie Dog Relocation Project: Vegetation Cover Data from the Sevilleta National Wildife Refuge, New Mexico (2005-2013)


Prairie dogs are keystone species that impact both animals and plants in grassland habitats. They
are a food resource for secondary consumers such as badgers, foxes, and raptors. Also, the mounds
that they construct are home to many arthropod and reptile species that otherwise might not survive
in grasslands. Both Gunnison’s and black-tailed prairie dogs can increase the number of plant
species in grasslands and landscape heterogeneity with their ecosystem engineering that creates
disturbed patches on the landscape. Gunnison’s prairie dogs, which were native herbivores at the
Sevilleta National Wildlife Refuge (NWR) before their populations disappeared, were reintroduced at
the Sevilleta NWR in 1997, 2005, and 2008. In 1998, a Gunnison’s prairie dog colony naturally
established along the northern border on the east side of the Refuge. The naturally occurring
colony and the colony that was reintroduced in 1997 have since then severely declined or gone
locally extinct. Still, with the removal of cattle from the Sevilleta in 1973, the reintroductions
of Gunnison’s prairie dogs in 2005 and 2008 provides an interesting opportunity to study how a
native keystone herbivore affects a grassland habitat without the pressures and competition from

Core Areas: 

Data set ID: 




Experimental Design

Three psuedo-replicates in a paired plot design: 1)plots where prairie dogs have been reintroduced and 2)control plots.

Sampling Design

Each 100 x 100m plot contains 36 sample units (quads) that are 20m apart in a 6 x 6 grid. These quads are numbered in a zig zag pattern starting in the NE corner of the plot where the first six quads go north to south, the next six plots that are west of the first quads go south to north, and so on for the remaining quads on the plot. These quads are marked by a numbered rebar stake.

Field/laboratory Procedures

A 50 x 50 cm quadrat separated into twenty-five 10 x 10 cm squares are placed southeast of a small white pvc pipe that marks permanent subplots. Then, percent covers and highest height are estimated for each plant species into palmtop computers. Species occupying less than 1%, a quarter of a 10 x 10 cm square, are recorded 0.1 %. When estimating plant species percent covers yellow and green plant material are included in the measurement. Individual plants that are completely gray, containing no yellow or green foliage, are not assessed in the percent cover estimate. For highest height, the ‘average’ height of the foliage for perennialspecies is recorded and for annual plant species the height to the top of the inflorescence, flowers and fruits,is recorded. The estimate of percent cover of disturbance from prairie dogs is the same as the plant cover estimates. Finally, all prairie dog fecal pellets that are in the quadrat, subplot, are counted.

Data sources: 



Data were qa/qced and obvious errors were corrected. A column for height was added to the data since we added to the protocol a height measurement in 2009. We also added in 2008 prairie dog fecal counts and in 2009 prairie dog disturbance measurements. Previous data were explored to renter past height measurements along with adding disturbance and prairie dog fecal pellet counts to the data. These measurements were not recorded for all years. 11 January 2010 tlk

Additional information: 

More information about who is involved with the samples/data:

Mike Friggens 1999-September 2001
Karen Wetherill February 7, 2000-Augst 2009
Terri Koontz February 2000-August 2003
August 2006-Present
Shana Pennington February 2000-August 2000
Heather Simpson August 2000-August 2002
Chris Roberts September 2001-August 2002
Caleb Hickman September 9, 2002-November 15, 2004
Seth Munson September 9, 2002-June 2004
Maya Kapoor August 9, 2003-January 21, 2005
March 2010-March 2011
Tessa Edelen August 15, 2004-August 15, 2005
Charity Hall January 31, 2005-January 3, 2006
Yang Xia January 31, 2005-Present
Michell Thomey September 3, 2005-August 2008
Jay McLeod January 2006-August 2006
Amaris Swann August 25, 2008-Jan 2013
John Mulhouse August 2009-Present
Amanda Boutz August 2009-May 2010
Stephanie Baker October 2010-Present
Megan McClung April 2013-Present

Additional Study Area Information

Study Area Name: Prairie Dog Town

Study Area Location: The study area is about 655 ha (~2.5 sq mi) in size and approximately1 km due west from the foothills of the Los Pinos Mountains. The study is also just north of the Blue Grama Core Site.

Elevation: 1670 m

Soils: sandy loam and sandy clay loam

Site history: historically large prairie dog colonies inhabited the study area

Vegetation Surveys in Chihuahuan Desert Grassland and Shrubland Sites Associated with Coyote Scat Surveys at the Sevilleta National Wildlife Refuge, New Mexico (2008-2009)


This data set contains information regarding vegetation structure at sites in grama grassland and both creosote and mesquite shrubland habitats at the Sevilleta NWR. This information was collected at randomly selected sites throughout the refuge. Each site is within 100 meters of one of the 22 road-based transects(20 in 2008) that were used to carry out coyote scat surveys during three seasons (spring, summer and fall) in 2009 (see "Coyote scat surveys in grassland and shrubland sites at the Sevilleta NWR, spring, summer and fall 2009" data set). Data was collected within at total of 22 circular vegetation plots (40 in 2008), each of which is 30m in diameter. Each plot was surveyed a total of three times, specifically in: April (spring), July (summer), and October (fall) 2009. Variables were selected based on their relevance to patterns of coyote habitat use, as well as their utility in calibrating Landsat images of the study site and the likelihood that they would vary seasonally. Measured variables include: average percent live woody vegetation cover, average percent live grass cover, average percent live forb cover, and average woody plant height. Information on woody plant species with individuals greater than 0.5 m in height is also presented.

Core Areas: 

Data set ID: 


Additional Project roles: 




Experimental Design: 

Vegetation surveys were carried out at grassland and shrubland sites located throughout the Sevilleta NWR. In 2008, two plot locations were randomly elected for each of twenty road based scat transects that were surveyed during the same field season. Vegetation plot location was determined by randomly selecting the following: a distance from the beginning of each mile long, road-based scat transect; side of the road (left or right); and a distance from the road (30-100m). 

One of the two plots associated with each of the 20 scat transects surveyed in 2008 was randomly selected and surveyed in each of the three seasons in which scat surveys were conducted in 2009. Two new vegetation plots, one for each of two new scat transects, were also surveyed in 2009.

Sampling Design: 

Each vegetation plot was circular with a 30m diameter intended to match the spatial scale of a Landsat satellite image pixel. In 2008, each of 40 plots was surveyed once between July 30th and August 20th, 2008.  At each plot, measurements were collected along 4 x 15m line intercept transects, one per cardinal direction, and in 5 x 1m^2 quadrats located at random distances and angles from the plot center. In 2009, half of these plots and two new ones were each surveyd three times, once in each of the following three months: April, July, October.  At each plot, measurements were collected along 4 x 15m line intercept transects, one per cardinal direction.

Field Methods: 

The coordinates of the center of each vegetation plot were determined using a GPS unit. In 2008, percent woody vegetation cover was measured, to the nearest 0.1m, along the 4 x 15m line intercept transects described in the sampling design section. This data was later combined to obtain estimates of percent woody cover for 2 x 30m transects that passed through the plot center and were perpendicular to one another such that one ran north-south and the other ran east-west. An attempt was made to measure percent cover only for live woody plants with a height of 0.5 m or greater. A plant was considered to be alive if it had green leaves on some part of it. The one exception to this rule was Gutierrezia sarothrae, for which percent cover was assessed for both plants with green leaves and plants with dead flowers but no green leaves. Each woody plant that crossed the line intercept transects was identified to species and, for each plant with a height of 0.5m or greater, the height was recorded and two perpendicular axes of the plant were measured. 5 interplant distances were measured from the first woody plant (0.5m or taller) that was encountered along each of the 4 line intercept transects in a plot. These distances were measured to the 5 closest woody plants that were also at least 0.5m tall and were within the plot and therefore represent nearest neighbor distances. When no woody plants were encountered along the line intercept transects, measurements were made from the woody plant closest to the first 1m^2 quadrat (described in sampling design section). Fewer than 5 distances were measured when there were fewer than 6 woody plants found within the plot boundaries. 

Measurements of percent grass cover were made in the 5 x 1m^2 quadrats described in the sampling design section. For each quadrat, the dominant grass, defined as the grass with the highest percent cover, was identified to genus and a small sample was collected. Two grass genera were recorded in cases where the two grasses had similar values for percent cover. A small sample of each woody plant species (excluding cholla and other cactus species) found within the plot was also collected. In 2009, percent live woody vegetation, grass and forb cover was measured, to the nearest 0.1m, along the 4 x 15m line intercept transects described in the sampling design section. This data was later combined to obtain estimates of percent woody, grass and forb cover for 2 x 30m transects that passed through the plot center and were perpendicular to one another such that one ran north-south and the other ran east-west. A plant was considered to be "live" if there were green leaves or stalks. For a given plant that intersected a line intercept transect, if only part of the plant had green leaves or stalks, then only that part was measured and included in the calculation of percent live vegetation cover. Each woody plant that crossed the line intercept transects was identified to species and, for each plant with a height of 0.5m or greater, the height was measured to the nearest 0.1m and recorded. As a result, a list of woody plant species with individuals of a height greater than or equal to 0.5m that crossed the line intercept transects is presented for each plot. A small sample of the dominant woody plant species (excluding cholla and other cactus species) and one of the dominant grass species found within the plot was collected. Dominance was determined based on vegetation data collected in 2008. In particular, dominance was defined as follows: woody plant species with the highest value for percent cover within the plot; grass species with the highest percentage cover in at least one of 5 1m^2 quadrats that was surveyed in each plot.

Laboratory Procedures: 

All plant samples were dried for 24 hours at 60 degrees Celsius and, in future, will be prepared and run through a stable carbon isotope analysis.

Data sources: 


Quality Assurance: 

Data were recorded in the field and entered into a spreadsheet in Excel. Extraneous information, for example information on woody plants less than 0.5m in height, was removed. No automated or quantitative data quality checks were performed.

Additional information: 

Additional Information on the personnel associated with the Data Collection / Data Processing

Other Field Crew Members:

Amanda Boutz

Michael Donovan

Teresa Seamster

Terri Koontz

Kelly Bowman

Karles McQuade

2003 Prescribed Burn Effect on Chihuahuan Desert Grasses and Shrubs at the Sevilleta National Wildlife Refuge, New Mexico: Grass Recovery Study (2003-2012)


The U.S. Fish and Wildlife's plan to apply a prescribed burn to a large portion of Mckenzie Flats was deemed an opportunity to study the effects of fire on vegetation at the boundary between shrubland and grassland. This study actually was undertaken on an area that had prescribed fire applied to 8 of 16 (300 m x 300 m) plots 10 years before in 1993. This previous study had also examined the effects of fencing to exclude the indigenous prong-horn antelope. In the 2003 study the prescribed fire was applied to the northeastern half of the 16 plots while the southwestern plots were intentionally protected. Sampling prior to the prescribed burn included quantification of cover of grass species in quadrats within all of the 16 plots. Measurements were made using "niner" quadrat frames that are 30 cm x 30 cm frames that are divided into 9 1-decimeter squares. Counts of grass species were made just prior to the June 2003 burn. Following the prescribed burn, quadrats were remeasured in the fall of 2003 to quantify mortality of grass species. These measurements were taken through the fall of 2012

Core Areas: 

Data set ID: 




To study the effects of fire on the vegetation at the boundary between shrubland and grassland.

Data sources: 




Within each 300 m x 300 m plot, 3 m x 4 m quadrats were marked off with rebar for use in a previous burn experiment. Each of these quadrats also had a piece of rebar on the southern edge of the quadrat with a numbered tag. Six of these quadrats were randomly selected in each plot. Measurements were made using a niner quadrat frame. These frames are PVC squares that are 30 cm x 30 cm and are divided off into 10 cm x 10 cm squares with string. This gives nine 1-decimeter squares within the "niner". The niner was placed over a corner rebar and aligned with the edge of the larger 3 m x 4 m quadrat. Counts were then made of the number of decimeters in which each species of grass was rooted. Values can be 0 to 9. The designation for the 4 niners in each quadrat was A through D starting with A in the SW corner, moving clockwise to D in the SE corner.

Note: For the fall collection in 2003 it was virtually impossible to identify the species of grass that had regrown following the fire. It was decided to just give a count of decimeters with live grass rooted in them and identify them as "GRASS".  With the fall moisture of 2003 there was a flush of annuals and it was decided to enumerate these with counts of any "forbs" rooted in decimeters of each quadrat.  This methodology was not repeated in subsequent years.

Also, Quad 3084 was not recorded in the 2003 season 2 and any years following 2005. For Quad 3141, data were not measured for years following 2006. This was done to balance the dataset; each "pre" plot has six quadrats rather than some having seven.

Specific location:

 Data were collected from 16 (300 m x 300 m) plots designated as the "Burn Antelope Exclosure" plots. These plots are located on the southern end of Mckenzie Flats. The plots are laid out in a 4 by 4 square with 300 m buffer between each plot. The plots are enclosed within a 440 ha box.

The bounding coordinates of this large box are:

               Latitude Longitude

NW corner 34.3138 106.6926

NE corner 34.3202 106.6711

SE corner 34.3024 106.6634

SW corner 34.2960 106.2960

This large expanse has a variable mix of grass species. The 2 dominant species are black grama (Bouteloua eriopoda) and blue grama (Bouteloua gracilis). There are also sizeable patches of mule grass (Scleropogon brevifolius). A mixture of the dropseed species are present as well. These include Sporobolus cryptandrus, Sporobolus contractus, Sporobolus flexuosus and Sporobolus airoides. Galleta grass (Pleuraphis jamesii) and a couple of Muhlenbergia species are also present. Into this grass matrix are mixed several shrubs and subshrubs. The most noticeable shrub is creosote bush (Larrea tridentata). Other common non-grasses include Yucca glauca, Ephedra torreyana and Gutierrezia sarothrae.


2003 through 2008 data files were merged into one file. Then, they were checked for obvious errors. 20 January 2009. TLK

checked and corrected 2009 data for obvious errors, appended data to Navicat table. 12 January 2010 tlk


Quality Assurance: 

Data were recorded on paper datasheets. Then this data were entered into an excel worksheet and assessed for errors. Data are stored in Navicat table niners_grass in directory burnx. In 2009, started distinguishing between field comments and QAQC comments. An '*' designates a QAQC comment. SAS program is used to check for duplicates and that all data points have been recorded and entered.

Additional information: 

Spring 2003 data were measurements done before the 2003 prescribed fire. Data collection is ongoing.

Small Mammal Exclosure Study (SMES) Vegetation Line Intercept from Chihuahuan Desert Grassland and Shrubland at the Sevilleta National Wildlife Refuge, New Mexico (1995-2005)


The purpose of this study is to determine whether or not the activities of small mammals regulate plant community structure, plant species diversity, and spatial vegetation patterns in Chihuahuan Desert shrublands and grasslands. What role if any do indigenous small mammal consumers have in maintaining desertified landscapes in the Chihuahuan Desert? Additionally, how do the effects of small mammals interact with changing climate to affect vegetation patterns over time?

This is data for perennial plant vegetation canopy cover measured from all SMES study plots, fall 1995 and fall 2005. The purpose of this data is to provide ground-truth data for comparison with low-level aerial photographs of each study plot. Three, 29 meter lines were measured along three of six rows of the permanent vegetation measurement quadrats. Each line was measured at 10cm resolution for intercepts of perennial plant live canopy cover, and for bare ground. 10cm resolution is comparable to the resolution of the aerial photos. All plants were identified to the species level. These line-intercept measurements are taken once every ten years, at the same time that low-level aerial photographs are taken. These data will be compared to both decadal air photos, and annual measures ofvegetation from one-meter2 quadrats on each plot to provide information on vegetation change over time relative to the various animal exclosure treatments.

Data set ID: 


Additional Project roles: 


Core Areas: 



Experimental Design:

There are 2 study sites, the Five Points grassland site, and the Rio Salado creosotebush site. Each study site is 1 km by 0.5 km in area. Three rodent trapping webs and four replicate experimental blocks of plots are randomly located at each study site to measure vegetation responses to the exclusion of small mammals. Each block of plots is 96 meters on each side. Each block of plots consists of 4 experimental study plots, each occupying 1/4 ofeach block. The blocks of study plots are all oriented on a site in a X/Y coordinate system, with the top to the north. Treatments within each block include one unfenced control plot (Treatment: C), one plot fenced with hardware cloth and poultry wire to exclude rodents and rabbits (Treatment: R), and one plot fenced only with poultry wire to exclude rabbits (Treatment: L). The three treatments were randomly assigned to each of the four possible plots in each block independently, and their arrangements differ from block to block. Each of the three plots in a replicate block are separated by 20 meters.

Each experimental measurement plot measures 36 meters by 36 meters. A grid of 36 sampling points are positioned at 5.8-meter intervals on a systematically located 6 by 6 point grid within each plot. A permanent one-meter by one-meter vegetation measurement quadrat is located at each of the 36 points. The 36 quadrats are numbered 1-36, starting with number 1 in the top left corner (north-west) of each plot (top being north), and running left (west) to right (east), then down (south) one row, and then right (east) to left (west), and so on. Quadrat/rebar number one is in the northwest corner of each plot, and numbers 1-6 are across the north side of the plot west to east,then quadrat/rebar number 7 is just south of quadrat/rebar number 6, and rebar numbers increase 7-12 east to west, and so on. 3-inch nails were originally placed in the top left (north-west) corner of each quadrat. These may be difficult to see. A 3-meter wide buffer area is situated between the grid of 36 points and the perimeter of each plot.

How Data Were Collected:

100 meter measuring tapes were attached to the steel re-bar posts marking vegetation quads 1, 3, and 5 on each study plot. The measuring tapes were extended south to the re- bar posts marking quads 36, 34, and 32. Data were recorded for all intercepts of live perennial plant canopy foliage, and for bare ground. The start and end points for each intercept were recorded to the nearest 10 cm on the measuring tape. Intercepts less than 5 cm were ignored, and intercepts between 5 and 10 cm were recorded to the nearest 10 cm. Intercept measurements were only recorded for perennial plant species, and for bare soil. Annual plants and dead perennial plants were ignored.

Data sources: 



April 9, 2002: File created by Kristin Vanderbilt.Updated by Karen Wetherill, January 4, 2006. In 2006, the 1995 data codes were updated to reflect current Kartesz codes as found on the USDA plants website. In particular ATCA to ATCA2, ERPU to DAPU7, HIJA to PLJA, MAUR2 to MUAR2, MUPO to MUPO2, OPPH to OPPHP, SATR12 to SATR12, SCBR to SCBR2, SEMU to SEMU2, SPFL to SPFL2. Codes that could not be decipher and are still in the data set are LEER, OPVI, SCPO (could be SCPA6), and SPUK. Other mistakes such as site=L for Larrea were change to site= C. Negative intercepts (4) were NOT corrected.

Quality Assurance: 

The data were entered in the field on to micro-cassette tape recorders. The taped recorded data were then entered on to MS Excel spreadsheets. A macro statement was used to subtract each observed intercept end measure from the start measure, to produce an intercept measure for each observation. Those data were then converted to space-formatted text files, and combined as one file. In 2006, the 1995 data codes were updated to reflect current Kartesz codes as found on the USDA plants website.

Pinon-Juniper Overstory Density, Cover and Biomass Data from Cerro Montosa, Sevilleta National Wildlife Refuge, New Mexico (2006-2009)


In 2006, to obtain a measure of pinon and juniper biomass in the Cerro Montosa area, belt transects were superimposed on transects along which understory net primary producitivy (NPP) is sampled. All trees rooted within 5 m to the north of each belt were tagged, although some shorter belts exist on which all trees within 5 m to either the north or south were tagged. The height of each tagged tree was measured, as was the diameter-at root-crown (DRC). Crown diameters both parallel and perpendicular to the belt transect were also measured.  Trees were re-measured in 2007, 2008, and 2009.

Core Areas: 

Data set ID: 


Additional Project roles: 



Data sources: 



Measurement Techniques:

Each 100m transect on webs 1 and 2, positioned along the existing understory net primary production (NPP) transects, is delineated with a tape measure. All trees rooted within 5 m to the north of each transect have been tagged with a numbered aluminum identification tag. The diameter-at-root-crown (DRC) of all boles greater than 2.5 cm on these trees is measured and recorded. The height of each tree is measured using a range pole extended near the highest point of the tree. Finally, the diameter of the crown both parallel and perpendicular to the belt transect is measured.

Transects at web 3 are shorter (50m) and thus 5 m to both the north and south of each transect is included within the belt.


3/8/10-Data and metadata compiled and updated through 2009. (JMM) Metadata created and compiled from 2006 to 2008 based on metadata and data supplied by Doug Moore. (YX)

Multi-temporal TM-NDVI Vectors at Rodent Webs from the Sevilleta National Wildlife Refuge, New Mexico (1984-1993)


This database contains mean NDVI values for 200 m diameter circles encompassing Rodent Webs on the Sevilleta National Wildlife Refuge (NWR), for 21 Landsat TM scene dating from 1984 to 1993. These NDVI vectors were generated as part of cooperative project between the Sevilleta LTER and the Indian Health Service, to study the 1992 Hantavirus outbreak.

Core Areas: 

Data set ID: 


Additional Project roles: 



Data sources: 



The following Landsat Thematic Mapper (TM) scenes (from the Sevilleta Information Management System (SIMS) image archive) were rectified to UTM (NAD-27) coordinate system, radiometrically calibrated and converted to reflectance, then transformed into Normalized Difference Vegetation Index (NDVI) images. Characteristics of the imagery were: 28.5 m cell resolution; UTM NAD-27 coordinate system; bounded by ULx = 303973 Easting, ULy = 3819519 Northing, LRx = 346752 Easting, LRy = 3761122 Northing.

84jun22 87sep10 88sep28 89mar07 89may19 89oct10 90jan14 90may06 90sep1191apr23 91sep30 92apr09 92jun04 92jul06 92jul14 92aug15 92oct02 93may3093sep03 93sep19 93oct05

Rodent Web coordinates were extracted from the SIMS GPS Master Archive database, converted into an Arc/Info point coverage, then buffered to create circular polygons of 200 m diameter centered on the Web center stake. Then Arc/Info base and GRID routines were used to overlay the Web polygon coverage on each NDVI image, and mean NDVI values for each 200 m polygon were calculated; this generates an NDVI vector at each of the Web locations. The exact procedure log is included in the Additional Information below.


06/10/97 - date this file created. More to be added soon. G. Shore.

06/11/97 - reformatted file. G. Shore.

07/02/97 - added more documentation. G. Shore.

07/04/97 - added more documentation. G. Shore.

09/19/97 - dataset code corrected from SEV103 to SEV107. G. MacKeigan.

Additional information: 

Additional Study Area Information

The Sevilleta National Wildlife Refuge (NWR) is located in Socorro County, New Mexico, in the United States of America. The Sevilleta LTER was initiated as the Sevilleta National Wildlife Refuge, a former Spanish land grant now administered by the U.S. Fish and Wildlife Service. The LTER recently has been expanded to a research area of approximately 3,600 km2 that ranges from Rio Grande riparian forests ('bosque') and Chihuahuan Desert up to subalpine forests and meadows. Four dedicated research areas comprise the core sites; Sevilleta National Wildlife Refuge (100,000 ha), Bosque del Apache National Wildlife Refuge (25,300 ha), Sierra Ladrones Wilderness Study Area (28,390 ha) and the Magdalena Mountains Research Area (15,000 ha). The research region spans the Rio Grande basin with elevations ranging from 1,350 m at the Rio Grande to 2,195 m in the Los Pinos Mountains in the east, to 2,797 m at Ladrone Peak in the northwest, and to 3,450 m in the Magdalena Mountains to the southwest.

Climate is characterized by an intriguing combination of abundant sunshine, low humidity and high variability in most factors. The site exists in the boundary between several major air mass zones which contributes to the dynamics of the local climate. Precipitation ranges from <100 mm to 600 mm with an average of 280 mm. Summer precipitation occurs as intense thunderstorms often accounting for over 1/2 of the annual moisture. El Nino and La Nina events influence winter precipitation and marked variations occur on an inter-annual basis. Mean monthly temperatures range from -2.5 C to 27 C. Topography, geology, soils, and hydrology, interacting with major air mass dynamics, provide a spatial and temporal template that has resulted in the region being a transition zone for a number of biomes.

The region contains communities representative of, and at the intersection of, Great Plains Grassland, Great Basin Shrub-steppe, Chihuahuan Desert, Interior Chaparral, and Montane Coniferous Forest. The elevational gradient of the Magdalena Mountains provides further transitions for Interior Chaparral, Pinyon-Juniper Woodland, Petran Montane Conifer Forest, Petran Subalpine Conifer Forest, and Subalpine Grassland. The regional location at the junction of a number of biomes is critical for quantifying (1) gradient relationships with distance, (2) the scale-dependent or independent nature of spatial variability, (3) how steep gradients influence system properties, (4) integrated responses across the region, and (5) biome responses to climate change. Many species of these communities are at their distributional limits. For example, 54 plant species terminate their distributions within the Sevilleta and some represent major life forms and physiologies, such as the C3 perennial grasses. Reptiles provide a dramatic example as 47 of the 58 species end their distributions in the vicinity of the Sevilleta (33 are northern limits of desert species). An important feature of the biodiversity of this region is the number of examples of sympatric swarms of closely related species. This sympatry affords opportunities for studying the evolutionary differential of species.

Problems You Should Know About

A) ***NOTE***: that images were examined for Cloud and Cloud-shadow problems and the following Scene_Dates/Rodent_Webs were determined to partially or wholly impacted by Clouds and Cloud-shadows (and thus probably unsuitable for analyses purposes): tm91sep30: FPL-1, FPL-3, FPG-1, FPG-3 thru FPG-5, SC-2 thru SC-5, BX-1-1, BX-1-3, BX-1-4, BX-2-2, BX-2-3, BX-3-3, BX-3-4, BX-4-1 thru BX-4-3; tm92jul14: 222-1 thru 222-5

B) ***NOTE: an NDVI value of -9999.0 indicates MISSING Satellite data for that TM scene date for that Web location

C) Information regarding attempted error correction of NDVI vectors:

From Wed Jul 2 16:40:05 1997
Date: Wed, 2 Jul 1997 00:20:08 -0600 (MDT)
From: Greg Shore
To: "Robert R. Parmenter"
Cc: Greg Shore
Subject: Sev/IHS Hanta Project

Hi Bob,

Well, I've tried several different approaches to developing correction factors for the NDVI values at the Web locations on the Sev, but have been foiled everytime. I am convinced that we'll just have to go back to the original bands and perform atmospheric correction on them utilizing the NASA correction algorithms Eric Vermote is developing. Unfortunately, that's probably a month or two away. In the meantime, I'm not sure what to think of the Landsat 4 imagery (6/4/92 and 7/6/92 scenes) since they seem to show unusually high NDVI values in relation to the Landsat 5 scenes just before and just after those dates (4/9/92 and 7/14/92). I know we received a lot of rain in May 1992, so some of this could be real but not sure how much. In addition, I've noticed that NDVI values generally seem higher starting in 1992, then before; and this could be due to a change in radiometric calibration procedures that EOSAT implemented in 1992. This points out the difficulty with doing multi-temporal analyses (looking for absolute changes at a location) with TM imagery. The next generation sensors (e.g., MODIS) will eliminate much of these variations and unknowns but that doesn't help us now.

Anyway, I've also taken a look at each image for cloud and cloud shadow effects, and have the following list of Webs and dates that should be excluded:

tm91sep30: FPL-1, FPL-3,
FPG-1, FPG-3 thru FPG-5,
SC-2 thru SC-5,
BX-1-1, BX-1-3, BX-1-4,
BX-2-2, BX-2-3,
BX-3-3, BX-3-4,
BX-4-1 thru BX-4-3

tm92jul14: 222-1 thru 222-5

Gregory A. Shore
GIS Analyst Programmer
phone: (505) 277-2109 begin_of_the_skype_highlighting     

Additional Metadata- Command Log

List of processing commands for IHS/SevLTER Hanta Virus Project

NOTE that indicated Unix shell scripts, "C" programs, Arc/Info
AML's, etc. are located in /net/sevilleta/export/db/work/ihs_hanta_proj/


cd /net/sevilleta/export/db/work/ihs_hanta_proj/arcinfo/

# Extract coordinates and attribute data for Sev Web Sites from GPS file
arc2rdb /db/work/geodesy/sev_CAcode_gps_pts.dbf \
| select 'Project_Area == "Sevilleta National Wildlife Refuge"
&& Study_Name != "Neotoma Sympatry" && Plot_Type == "Rodent Web"
&& Study_Name != "Hantavirus Enclosure"' \
| project Study_Name Site_Name Block_Num Plot_Num NAD27utm_easting
NAD27utm_northing \
| listtotable \
> web_coors.rdb

sed -f make_plotcode.sed web_coors.rdb > web_coors2.rdb

project Study_Name Site_Name Block_Num Plot_Num NAD27utm_easting
NAD27utm_northing plotcode \
< web_coors2.rdb \
| compute 'if (Block_Num == "na") plotcode = Site_Name "-" Plot_Num;
else plotcode = Site_Name "-" Block_Num "-" Plot_Num' \
| project NAD27utm_easting NAD27utm_northing plotcode Study_Name \
| tail +3 \
| sort +3 -4 +2 -3 \
| nl \
| expand \
| awk '{print} END {print "END"}' \
> web_coors3.gen

grep -v 'END' web_coors3.gen \
| awk '{printf ",,,,\n",$1,$4, $5, $2, $3}' \

# Generate the point coverage of Sev Web Sites, and add attribute data
Arc: precision double double
Arc: generate sev_webs_pt
Generate: input web_coors3.gen
Generate: points
Generate: q

Arc: projectdefine COVER sev_webs_pt
Project: ZONE 13
Project: DATUM NAD27

Arc: build SEV_WEBS_PT points

Arc: info



Arc: additem SEV_WEBS_PT.pat SEV_WEBS_PT.pat id 4 5 b # SEV_WEBS_PT-ID

Arc: info

# Buffer the Sev Web center stakes to create 200m diameter circular polygons,
# and add attribute data
Arc: buffer SEV_WEBS_PT SEV_WEBS_POLY # # 100 0.01 point

Arc: additem SEV_WEBS_POLY.pat SEV_WEBS_POLY.pat id 4 5 b # SEV_WEBS_POLY-ID

Arc: info


# Uncompress the 21 TM-NDVI Imagine scenes, convert them to Arc/Info GRID's
# (and fix them up for processing), then calculate mean of NDVI's within
# 200m circular zone around each Web.
# NOTE: creates GRID's called TMyymmmddNDVI
# Uncompress images
foreach f ( /db/work/vegmap_proj/ndvi_images/*.Z )
set fn = `basename $f | sed 's/\.Z//'`
uncompress -c $f > $fn

# Convert to GRID's

# Fix map projection in header

# Create multi-layer GRID stack
/bin/ls -d *ndvi | wc -l > tm_stacklst.txt
/bin/ls -d *ndvi >> tm_stacklst.txt
Grid: makestack tm_ndvi file tm_stacklst.txt

# Convert -1.1 values to NODATA values

# Copy Webs point coverage template to working coverage
Arc: copy SEV_WEBS_PT sevwebspt200m

# Create Web Zonal GRID from 200m diameter Webs polygon coverage
Grid: setcell TM84JUN22NDVI
Grid: setwindow TM84JUN22NDVI TM84JUN22NDVI
Grid: webzonegrid = polygrid(SEV_WEBS_POLY, ID)

# Finally, Calculate NDVI means of each Web Buffer Zone
# NOTE: mean NDVI values, by scene date, stored in attribute table
# of point coverage SevWebsPt200m.
calcmeans.csh webzonegrid sevwebspt200m


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