Jed Anderson, Mitchel P. McClaran, and Peter B. Adler. 2012. Cover and density of semi-desert grassland plants in permanent quadrats mapped from 1915 to 1947. Ecology 93:1492.
INTRODUCTION
This data set provides spatial locations of individual plants at annual temporal resolution for almost 20 years, supporting investigations of population and community dynamics. Population studies can combine records of individual plants with available data on weather and livestock grazing to ask how survival, growth, and mortality depend on climate variability, grazing and plant–plant interactions. Community studies can aggregate the individual level data to explore how species composition and diversity vary in space and time.
“Chart quadrats” are permanent 1-m² quadrats in which all individual plants are identified and mapped using a pantograph tracing tool that transfers a miniature image of plant location and shape to gridded paper (Hill 1920). Under Clements'(1907) influence, many range experiment stations across the western U.S. began mapping quadrats between the 1910s and the 1930s and continued annual censuses for decades (White 1985). We recently have published similar data sets from southern mixed-prairie in western Kansas (Adler et al. 2007), sagebrush-steppe in Idaho (Zachmann et al. 2010), and northern mixed-prairie in eastern Montana (Anderson et al. 2011). The data set described here, from semi-desert grassland in southern Arizona, contains 178 quadrats mapped annually from 1915 to 1935, and again in 1947. The new data will support more robust cross-site comparisons by providing records from a drier-warmer location with a different vegetation composition and physiognomy.
Chart quadrat data are unique in several ways. First, the fine spatial resolution of the maps makes it possible to track the fates of individual plants, providing detailed demographic information that is rare for herbaceous plants (Lauenroth and Adler 2008). Such demographic information is often essential for understanding community and ecosystem patterns and will be important for predicting how plant populations and communities respond to climate change. Second, the maps enable analysis of spatial patterns and interactions among plants in local neighborhoods (e.g., Purves and Law 2002). Third, the long-term nature of the data can reveal temporal variability in demographic performance and spatial interactions. And finally, these data are available for all species in the community.
Contemporary chart quadrat analyses use Geographic Information Systems and modern statistical techniques to take advantage of a unique combination of long-term, individual-level data for the whole community. We have automated analyses of the survival, life expectancies, and life spans of perennial grassland plants (Lauenroth and Adler 2008). Such demographic data can then be used to address additional research questions about the factors driving plant population dynamics (Adler and HilleRisLambers 2008, Dalgleish et al. 2011) and mechanisms of species coexistence (Adler et al. 2006, 2009, 2010).
Even before these contemporary analyses, chart quadrat data had a rich history in ecological and land management research. For example, this Arizona data set contributed to revised estimates of sustainable livestock grazing capacity on semi-desert rangelands (Canfield 1948) that were considerably more conservative than the initial estimates made in 1916 before the mapping effort began (Wooten 1916). A second focus of chart quadrat analyses has been the survival of perennial plants (Canfield 1957, Wright and Van Dyne 1976, West et al. 1979). These survival analyses and subsequent reanalyses (Sarukhán and Harper 1973, Fair et al. 1999) contributed much to our current knowledge about the demography of herbaceous perennial plants (White 1985). This data paper makes the “raw” measures of individual plant locations and cover available for the first time. Previous reports (Canfield 1948, 1957) only provided relative cover (as a proportion of live plant cover) and survival of grass species.
Canfield performed the last census of the quadrats in 1947. He also developed the line-intercept technique to measure plant cover along 100 foot-long transects while working in this semi-desert grassland (Canfield 1941, 1942). Today, line intercept is more commonly used because it is more efficient than chart quadrats for describing cover, and it can represent spatial variation at >1-m² scales. However, chart quadrats provide detailed spatial information for demographic analysis that is not available from line intercept measures.
The data set contains the following data and data formats: (1) the digitized maps in digital vector storage shapefile (.shp) format for use in geospatial software; (2) a tabular representation of location (x,y coordinates), basal or canopy cover (m²) for plants mapped as polygons, perimeter length (m), and seedling and clone status for each individual plant record; (3) quadrat information including elevation, livestock grazing history, and proximity to closest long-term rainfall gauge, (4) monthly precipitation values for those gauges, (5) a species list including synonymy of names and plant growth forms, (6) an inventory of the years each quadrat was sampled; and (7) summary information on unmapped plants in the quadrats, typically annual species but occasionally perennial forbs and sub-shrubs as well.
METADATA
CLASS I. DATA SET DESCRIPTORS
A. Data set identity: Mapped plant community time series, Santa Rita, AZ, 1915–1935,1947
B. Data set identification code:
C. Data set description
Principal Investigator: Peter B. Adler
Abstract:
This historical data set consists of 178 permanent 1-m² quadrats located on semi-desert grasslands at the Santa Rita Experimental Range, Arizona, USA. Individual plants in these quadrats were identified and mapped annually (in most cases) from 1915 to 1933 and again in 1947. Quadrats were located in ungrazed exclosures and in pastures grazed at various intensities by livestock. These data provide unique opportunities to test the interactive effects of grazing and climate variables on demographic rates, plant–plant interactions, and population and community dynamics. We provide the following data and data formats: (1) the digitized maps in shapefile format; (2) a tabular representation of centroid or point location (x,y coordinates), basal or canopy cover (m²) for plants mapped as polygons, perimeter length (m), and seedling and clone status for each individual plant record; (3) quadrat information including elevation, livestock grazing history, and proximity to closest long-term rainfall gauge, (4) monthly precipitation values for those gauges, (5) a species list including synonymy of names and plant growth forms, (6) an inventory of the years each quadrat was sampled, and (7) summary information on unmapped plants in each quadrat.
D. Key words: climate; Geographic Information Systems (GIS); livestock grazing; plant community; plant demography; Sonoran Desert; species interactions.
CLASS II. RESEARCH ORIGIN DESCRIPTORS
A. Overall project description: We digitized the Arizona data set as part of a National Science Foundation project (DEB-0614068, PI Adler) to digitize, distribute, and analyze four historical chart quadrat data sets.
B. Specific subproject description
1). Site description:
The 21,000 ha Santa Rita Experimental Range (31º50' N, 110º53' W) is located on the western alluvial fans of the Santa Rita Mountains approximately 50 km south of Tucson, Arizona, USA. Elevation increases from about 900 to 1450 meters above sea level with a corresponding increase in annual precipitation from 275 to 450 mm, and decreasing mean annual temperature from 20 to 17 C. The ~500 plant species (Medina 2003) include short trees, shrubs, succulents, and herbaceous grass and dicot life forms. The physiognomy ranges from desert scrub at the lowest elevations to oak woodlands at the highest elevations. For more information see http://ag.arizona.edu/srer.
Established in 1902, the Santa Rita is the oldest continuously operating rangeland research facility (McClaran et al. 2002, 2010) and among the five oldest biological field stations in the United States. Originally administered by the U.S. Department of Agriculture, the Santa Rita was transferred to the Arizona State Land Department in 1988 and is administered by the University of Arizona, College of Agriculture and Life Sciences (Medina 1996). Hundreds of experiments and manipulations have been performed to evaluate cattle grazing practices, rodent influences, methods of vegetation control, seeding of plants, and general ecological studies (Medina 1996, McClaran et al. 2003).
Between 1880 and 1903, overgrazing of vegetation was common because unlimited open access prevented the control of cattle numbers and recurring droughts limited forage production (Griffiths 1904, Bahre and Shelton 1996). From 1903 to 1916, cattle were excluded from all areas below 1200 m to allow recovery from overgrazing and to estimate a cattle carrying capacity (Wooten 1916). From 1916 to 1941, the stocking rate was about 0.12 animals·h-1·yr-1, but since the 1950s it has been 0.02 to 0.06 animals·h-1·yr-1 (increasing with elevation) which translated to 40–60% utilization of grass production (Martin and Cable 1974, Cable and Martin 1975, Martin and Severson 1988, Mashiri et al. 2008). Fires were probably common (10–20 yr interval) prior to the intensification of cattle grazing (Humphrey 1958, Bahre 1991), but since 1902, fires have been rare (Huang et al. 2007).
2). Experimental and sampling design:
a. Design characteristics:
We digitized maps for 178 permanent quadrats, a subset of the >200 quadrats established at Santa Rita. We chose not to digitize maps for quadrats which were only mapped sporadically between 1915 and 1933. The quadrat locations represent ungrazed livestock exclosures established in 1915 and other areas that were grazed at different intensities during the measurement period (Canfield 1948).
b. Permanent plots: 1 m² quadrats.
c. Data collection: Quadrats were mapped annually from 1915 to 1935 and 1947, but not every quadrat was mapped in every year (see the quadrat sampling schedule data file in IV). Quadrats were typically mapped between October and December after the summer (July–September) growing season.
While basal cover of perennial grasses was consistently mapped, other growth forms (annuals, forbs, and shrubs) were sometimes mapped as canopy cover or as points, or were not mapped but simply summarized with quadrat-level density or cover notes. Because of the inconsistency in mapping protocol for these non-grass growth forms, users should carefully inspect the data to determine whether they are appropriate for a chosen objective.
3. Research Methods
a. Field / laboratory: The data were collected in the field using pantographs (Hill 1920), a mechanical device used to make scale drawings. The original paper maps were first scanned and then stored as TIFF image files. These images were then converted into shapefiles by heads-up digitization in ArcGIS version 9.3. For a complete digitization protocol, contact Peter Adler.
b. Instrumentation: Pantographs, scanners, and computers running ArcGIS, Python, and R.
c. Taxonomy and systematics: Originally assigned plant names were corrected for synonyms based on the USDA Plants Database (http://plants.usda.gob/). We recorded these name changes in the species_name_changes.csv file.
d. Permit history:
e. Legal / organizational requirements:
CLASS III. DATA SET STATUS AND ACCESSIBILITY
A. Status
Latest update:
Latest Archive date:
Metadata status:
4. Data verification: After the initial digitizing phase, all maps were checked for completeness and accuracy. Jed Anderson made the following changes to the original (digitized) GIS dataset (stored shapefiles) in 2010 and 2011:
a) Shapefiles were rotated to have a consistent orientation;
b) Species names for unlabeled and obviously mislabeled polygons and points were assigned based on the species names of the same features in previous and later years;
c) Shapefiles were processed using R and Python scripts to clip the polygon and point features at the map borders and remove any small polygon “slivers” generated accidentally while digitizing;
d) Other miscellaneous corrections based on visual inspection of the shapefiles;
e) All species were then classified as either density- or cover-type features. Density-type species, typically forbs, were consistently mapped as points. Cover-type species, typically perennial grasses, were consistently mapped as polygons. Records of cover-type species mapped as points were converted to arbitrary small square polygons of 0.25 cm². Density-type species mapped as polygons were converted to point features with location at the centroid of the polygon;
f) Plants names were corrected for synonyms based on the USDA PLANTS Dataset (http://plants.usda.gov/); and
g) x, y coordinates of each polygon centroid were added to shapefile attribute tables.
B. Accessibility
1. Storage location and medium:
2. Contact person: Peter B. Adler, Department of Wildland Resources and the Ecology Center, Utah State University, Logan, UT, 84322 USA, peter.adler@usu.edu.
3. Copyright restrictions: None.
4. Proprietary restrictions: Users are requested to acknowledge their use of the data set in publications, research proposals, websites, and other outlets with citation of this data paper along with the following statement "Data sets were provided by the Santa Rita Experimental Range Digital Database. Funding for the digitization of these data was provided by the National Science Foundation and the University of Arizona." Users are requested to provide citations of publications using the data sets to Mitchel McClaran, School of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721 or mcclaran@email.arizona.edu.
5. Costs: None.
CLASS IV. DATA STRUCTURAL DESCRIPTORS
SPATIAL DATA
A. Data Set File
1. Identity: shapefiles.zip
2. Size: 23,685 Kb (compressed)
3. Format and storage mode: Shapefiles compressed and submitted together in a zipped directory.
4. Header information: The fields within the attributes tables for each shapefile are described in the tabular data, see “Records of all individual plants mapped as points” and “Records of all individual plants mapped as polygons” for the density and cover shapefiles, respectively.
B. Variable information: This is a zipped directory, containing every individual shapefile for each year that each quadrat was mapped. File names reflect the quadrat, year (YY), and geometry (C or D) of each shapefile. C refers to “cover” (features mapped as polygons) while D refers to “density” (features mapped as points). For example, “A1P_15_D.shp” is the point shapefile for year 1915 in Quadrat A1P. Each feature in these shapefiles has attributes that describe the individual, such as species name and location within the quadrat. Note that we removed shapefiles that contained no features from the the data set (e.g., if no forbs occurred in a quadrat in a given year, we removed the empty density shapefile).
RECORDS OF ALL INDIVIDUAL PLANTS MAPPED AS POINTS
A. Data Set File
1. Identity: allrecords_point_features.csv
2. Size: 488 Kb
3. Format and storage mode: ASCII text, comma separated. No compression scheme was used.
4. Header information: The first row of the file contains the variable names below.
B. Variable information
Variable name |
Variable definition |
Unit/ |
Storage type |
Precision |
Variable codes and definitions |
Quad |
Name of the quadrat |
N/A |
Character |
N/A |
N/A |
Year |
The year of the observation (just the last 2 digits). All observations are from the 1900's. |
YY |
Integer |
1 |
N/A |
Species |
Scientific name of the plant species (genus and species) or other label (e.g., “unknown”). |
N/A |
Character |
N/A |
N/A |
Seedling |
Indicates whether an individual was mapped as a seedling by the original surveyors.
|
N/A |
Character |
N/A |
N- Individual is not mapped as a seedling
Y- Individual is mapped as a seedling |
Canopy_cov |
Gives the area of the canopy cover for shrubs that were originally mapped as polygons and were later changed to points. |
m² |
Fixed Point |
N/A |
|
X |
Location of the record in the horizontal direction within the quadrat. |
m |
Fixed Point |
N/A |
|
Y |
Location of the record in the vertical direction within the quadrat. |
m |
Fixed Point |
N/A |
RECORDS OF ALL INDIVIDUAL PLANTS MAPPED AS POLYGONS
A. Data Set File
1. Identity: allrecords_polygon_features.csv
2. Size: 14,061 Kb
3. Format and storage mode: ASCII text, comma separated. No compression scheme was used.
4. Header information: The first row of the file contains the variable names below.
B. Variable information
Variable name |
Variable definition |
Unit/ |
Storage type |
Precision |
Variable codes and definitions |
quad |
Name of the quadrat |
N/A |
Character |
N/A |
N/A |
year |
The year of the observation (just the last 2 digits). All observations are from the 1900s. |
YY |
Integer |
1 |
N/A |
Species |
Scientific name of the plant species (genus and species) or other label (e.g., “unknown”). |
N/A |
Character |
N/A |
N/A |
Clone |
Indicates whether an individual was mapped as a clone by the original surveyors. Polygons sharing the same non-zero integer value belong to the same clone. |
N/A |
Character |
N/A |
zero- the polygon is not a clone
non-zero integer- see Variable definition |
Seedling |
Indicates whether an individual was mapped as a seedling by the original surveyors. |
N/A |
Character |
N/A |
N- Individual is not mapped as a seedling
Y- Individual is mapped as a seedling |
Area |
Area of the individual polygon |
m² |
Fixed Point |
N/A |
|
Length |
Perimeter of the individual polygon |
m |
Fixed Point |
N/A |
|
X |
Location of the polygon centroid in the horizontal direction within the quadrat |
m |
Fixed Point |
1.00E-015 |
N/A |
Y |
Location of the polygon centroid in the vertical direction within the quadrat |
m |
Fixed Point |
1.00E-015 |
N/A |
QUADRAT SAMPLING SCHEDULE
A. Data Set File
1. Identity: quad_inventory.csv
2. Size: 17 Kb
3. Format and storage mode: ASCII text, comma separated. No compression scheme was used.
4. Header information: The first row of the file contains the variable names below.
B. Variable information
Variable name |
Variable definition |
Unit/ |
Storage type |
Precision |
Variable codes and definitions |
year |
The year of the observation (just the last 2 digits). All observations are from the 1900's. |
YY |
Integer |
1 |
N/A |
Quadrat names |
Year values (YY) indicate that the named quadrat was sampled that year. NAs indicate the year specified by the "year" column was not sampled for the named quadrat. |
YY |
Integer |
1 |
See Variable definition |
QUAD INFORMATION
A. Data Set File
1. Identity: quad_info.csv
2. Size: 12 Kb
3. Format and storage mode: ASCII text, comma separated. No compression scheme was used.
4. Header information: The first row of the file contains the variable names below.
B. Variable information
Variable name |
Variable definition |
Unit/ |
Storage type |
Precision |
Variable codes and definitions |
quad name |
Quadrat name used in the digitized maps |
N/A |
Character |
N/A |
N/A |
quad original |
Original name used for the quadrat |
N/A |
Character |
N/A |
N/A |
elevation |
Elevation above sea level of the quadrat |
feet |
Integer |
1 |
N/A |
grazing status |
Presence or absence of grazing |
N/A |
Character |
N/A |
N/A |
grazing notes prior to time span of chart |
Narrative text |
N/A |
Character |
N/A |
N/A |
grazing notes during time span of chart |
Narrative text |
N/A |
Character |
N/A |
N/A |
rain gauge |
Name (“station code”) of closest long-term rain gauge. Monthly rainfall records since 1923 and location coordinates available in precipitation.csv file. |
N/A |
Character |
N/A |
N/A |
PRECIPITATION INFORMATION
A. Data Set File
1. Identity: precipitation.csv
2. Size: 66 Kb
3. Format and storage mode: ASCII text, comma separated. No compression scheme was used.
4. Header information: The first row of the file contains the variable names below.
B. Variable information
Variable name |
Variable definition |
Unit/ |
Storage type |
Precision |
Variable codes and definitions |
Rain gauge |
Name (“station code”) of closest long-term rain gauge. Additional gauges and years of data are available at the Santa Rita web site http://ag.arizona.edu/SRER/data.html. |
N/A |
Character |
N/A |
N/A |
Year |
The year of the observation. |
YYYY |
Integer |
1 |
N/A |
UTMx |
Universal Transverse Mercator projection in east-west axis within Zone 12S using datum NAD83. |
m |
Fixed Point |
1 |
N/A |
UTMy |
Universal Transverse Mercator projection in north-south axis within Zone 12S using datum NAD83. |
m |
Fixed Point |
1 |
N/A |
JANPPT |
Precipitation recorded in January in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
FEBPPT |
Precipitation recorded in February in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
MARPPT |
Precipitation recorded in March in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
APRPPT |
Precipitation recorded in April in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
MAYPPT |
Precipitation recorded in May in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
JUNPPT |
Precipitation recorded in June in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
JULPPT |
Precipitation recorded in July in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
AUGPPT |
Precipitation recorded in August in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
SEPPPT |
Precipitation recorded in September in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
OCTPPT |
Precipitation recorded in October in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
NOVPPT |
Precipitation recorded in November in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
DECPPT |
Precipitation recorded in December in given year. |
0.01 inch |
Fixed point |
1 |
-9999 = missing value. |
SPECIES LIST
A. Data Set File
1. Identity: species_list.csv
2. Size: 4 Kb
3. Format and storage mode: ASCII text, comma separated. No compression scheme was used.
4. Header information: The first row of the file contains the variable names below.
B. Variable information
Variable name |
Variable definition |
Unit/ |
Storage type |
Precision |
Variable codes and definitions |
species |
Scientific name of the plant species (genus, species) or other label (“unknown”, for example). |
N/A |
Character |
N/A |
N/A |
pointFeatures |
The total number of records of each species in the dataset (all quadrats and all years) mapped as points. These individuals can be found in shapefiles with file names ending "D.shp." An "NA" entry in "pointFeatures" for a species indicates that it shows up only as cover-type features in cover shapefiles, which have file names ending "C.shp." Unknown species are represented in both density and cover shapefiles. |
N/A |
Integer |
1 |
See Variable definition |
polygonFeatures |
The total number of records of each species in the data set (all quadrats and all years) mapped as polygons. These individuals can be found in shapefiles with file names ending "C.shp." An "NA" entry in "polygonFeatures" for a species indicates that it shows up only as density in density-type features shapefiles, which have file names ending "D.shp." |
N/A |
Integer |
1 |
See Variable definition |
unmapped |
The total number of quadrats of each species appears in the counts of unmapped plants. |
N/A |
Integer |
1 |
See Variable definition |
growthForm |
Classification of species by growth form. Information about species growth form was taken from the USDA PLANTS Database (http://plants.usda.gov/). |
N/A |
Character |
N/A |
forb – Forbs (non-graminoid herbaceous plants)
grass – Graminoid
shrub – Woody perennial plants
unknown – unknown growth form
vine – vine |
coverType |
Classification of polygonFeatures as basal or Canopy cover. |
N/A |
Character |
N/A |
basal – mapped as basal cover
canopy – mapped as canopy cover
N/A – non-applicable |
SPECIES NAME CHANGES
A. Data Set File
1. Identity: species_name_changes.csv
2. Size: 2 Kb
3. Format and storage mode: ASCII text, comma separated. No compression scheme was used.
4. Header information: The first row of the file contains the variable names below.
B. Variable information
Variable name |
Variable definition |
Unit/ |
Storage type |
Precision |
Variable codes and definitions |
originalName |
The original, mapped name of a plant species, typically the Scientific name, but occasionally the common name |
N/A |
Character |
N/A |
N/A |
newName |
Reassigned Scientific name of a plant species (genus, species) or one of a variety of "unknown" labels |
N/A |
Character |
N/A |
N/A |
COUNTS OF UNMAPPED PLANTS
A. Data Set File
1. Identity: unmapped_plants.csv
2. Size: 133 Kb
3. Format and storage mode: ASCII text, comma separated. No compression scheme was used.
4. Header information: The first row of the file contains the variable names below.
B. Variable information
Variable name |
Variable definition |
Unit/ |
Storage type |
Precision |
Variable codes and definitions |
quad |
Name of the quadrat |
N/A |
Character |
N/A |
N/A |
year |
The year of the observation. |
YYYY |
Integer |
1 |
N/A |
species |
Scientific name of the plant species (genus, species) or other label (“unknown”, for example) |
N/A |
Character |
N/A |
N/A |
count |
Number of individuals of each species in a given quadrat and year |
Individuals per m2 |
Integer |
1 |
N/A |
cover |
Proportion of the quadrat each species covered in a given quadrat and year |
Dimensionless (m² per m²); “t” = trace amount |
Fixed Point |
.01 |
N/A |
CLASS V. SUPPLEMENTAL DESCRIPTORS
A. Data acquisition
1. Data forms:
2. Location of completed data forms:
3. Data entry verification procedures: See II. 3 and III. 4.
B. Quality assurance/quality control procedures: The procedures above (II. 3 and III. 4) ensured accurate transfer of information from the original mapping stage. Nevertheless, future users must become familiar enough with the raw data provided here to determine whether or not it is appropriate for their particular research question. Two data quality issues warrant special attention: (1) Users should carefully inspect data for non-grass life forms (shrubs, forbs, annuals) because mapping protocols for these species appeared inconsistent; (2) In quadrats C4P, D2P, FH12, J6P, P2A, and WD3, polygons mapped in some years as Bothriochloa laguroides (often labeled “feather grass”), switched to Digitaria californica or Heteropogon contortus in other years, and often switched back to B. laguroides. We were unable to resolve the true species identity of these polygons.
C. Related materials:
D. Computer programs and data processing algorithms:
E. Archiving
1. Archival Procedures:
2. Redundant Archival Sites: http://cals.arizona.edu/srer/
ACKNOWLEDGMENTS
We thank Allison Peterson for retrieving and scanning original charts, and Erik Andrus, Kim Dutter, Mindi Lundberg, and SanShi Glover for their help in painstakingly digitizing data. Funding was provided by NSF DEB-0614068 and the Utah Agricultural Experiment Station, which has approved this work as journal paper number 8368.
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