Jed Anderson, Lance Vermeire, and Peter B. Adler. 2011. Fourteen years of mapped, permanent quadrats in a northern mixed prairie, USA. Ecology 92:1703.

INTRODUCTION

Despite the importance of demographic data for testing theory (Hubbell 2001, Muller-Landau et al. 2006, Angert et al. 2009) and for anticipating the ecological impacts of environmental change (Clark et al. 2001), empirical data remain limited. A number of long-term census plots are available for tree communities (Condit et al. 1996, Clark and Clark 2006), but longitudinal data for individual herbaceous plants are extremely scarce. Although hundreds of matrix population models have been built for herbaceous species, on average they cover just three year-to-year transitions, and very few extend beyond 10 years (Jongejans et al. 2010, Crone et al. 2011). In addition, virtually all of these studies focus on a single species, making it impossible to study plant–plant interactions. As a result, we have little information on mean lifespans or temporal variability in vital rates and population growth rates, let alone a quantitative understanding of how climate variables interact with density dependent processes to influence vital rates.

�Chart quadrat� data collected in the early 20th century are an exceptional source of long-term demographic data for herbaceous plant communities. Chart quadrats are permanent 1-m² quadrats in which all individual plants are identified and mapped using a pantograph (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. These data are unique in several ways. First, the fine spatial resolution of the maps makes it possible to track the fates of individual plants using computer algorithms, providing detailed demographic information that is rare for herbaceous plants (Lauenroth and Adler 2008). 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.

We have previously published digitized chart quadrat datat sets from southern mixed-prairie in western Kansas (Adler et al. 2007) and sagebrush steppe in eastern Idaho (Zachmann et al. 2010). By combining these data with Geographic Information Systems and modern statistical techniques, we have automated analyses of the survival, life expectancies, and life spans of perennial grassland plants (Lauenroth and Adler 2008), tested the influence of temporal variability on population persistence (Dalgleish et al. 2010) and coexistence (Adler et al. 2006, 2009, 2010) and identified the climate variables driving fluctuations in abundance (Adler and HilleRisLambers 2008, Dalgleish et al. 2011). In addition to this demographic research, chart quadrat data can be used to describe patterns of species diversity in space and time (Adler and Lauenroth 2003, Adler 2004, Adler and Levine 2007). These contemporary analyses go well beyond the original studies, which evaluated the effect of climate and grazing on range vegetation (Pechanec et al. 1937, Craddock and Forsling 1938, Blaisdell 1958) and described the survival of perennial plants (Canfield 1957, Wright 1972, West et al. 1979). The survival studies and subsequent re-analyses (Sarukh�n and Harper 1973, Fair et al. 1999, Lauenroth and Adler 2008) contributed much to our current knowledge about the demography of herbaceous perennial plants (White 1985).

Here we use a chart quadrat data set from the Fort Keogh Livestock and Range Research Laboratory, a USDA Agricultural Research Service field station in eastern Montana's northern mixed prairie. Fourty-four quadrats were mapped annually (with some exceptions) from 1932 through 1945. The quadrats were distributed among six pastures grazed by cattle at low, medium or high intensity from late spring through early fall, with two pastures assigned to each treatment. Details of the experimental design are available in Holscher (1953). To our knowledge, these data have not been extensively analyzed. Hurtt (1951) described the effect of the 1930s drought on plant cover. Reed and Peterson (1961) and Olson et al. (1985) studied the effects of grazing and precipitation on the basal cover of common species. Modern computational tools will help identify the demographic mechanisms underlying the observed relationships between cover and precipitation and grazing. Publication of this data set will also make possible comparisons with the southern mixed prairie and sagebrush steppe chart quadrat data sets.

This data set contains the following data and data formats: (1) all the digitized maps in shapefile format; (2) a tabular version of the entire data set (a table that replaces the full spatial data with one x,y coordinate for each individual perennial plant record); (3) grazing treatment information; 4) an inventory of the years each quadrat was sampled; (5) a species list, containing information on plant growth forms and shapefile geometry type (e.g. points or polygons); (6) a record of changes in species names; (7) daily precipitation and temperature records; and (8) counts of annual plants in the quadrats.

METADATA

CLASS I. DATA SET DESCRIPTORS

A. Data set identity: Mapped plant community time series, Miles City, MT, 1932–1945

B. Data set identification code: N/A

C. Data set description: N/A

1. Principal Investigator: Peter B. Adler
2. Abstract: This historical data set consists of 44 permanent 1-m² quadrats located on northern mixed prairie in Miles City, Montana, USA. Individual plants in these quadrats were identified and mapped annually from 1932 through 1945. Quadrats were located in six pastures assigned to cattle grazing treatments with light, moderate, and heavy stocking rates of 1.24, 0.92, and 0.76 ha/ animal-unit-month (two pastures in each). 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 version of the entire data set (a table that replaces the full spatial data with one x,y coordinate for each individual perennial plant record); (3) grazing treatment information; (4) an inventory of the years each quadrat was sampled; (5) a species list, containing information on plant growth forms and shapefile geometry type (e.g., points or polygons); (6) a record of changes in species names; (7) daily precipitation and temperature records; and (8) counts of annual plants in the quadrats (annuals were counted, not mapped, by the original mappers).

D. Key words: climate; demography; Geographic Information Systems (GIS); Montana; northern mixed prairie; plant community; plant population; species interactions

CLASS II. RESEARCH ORIGIN DESCRIPTORS

A. Overall project description: We digitized the Montana data set as part of a National Science Foundation project to digitize, distribute, and analyze four historical chart quadrat data sets.

B. Specific subproject description

1. Site description

Fort Keogh Livestock and Range Research Laboratory is located near the confluence of the Yellowstone and Tongue Rivers near Miles City, MT. The study site is on alluvial plains near the Tongue River (46°19'N, 105°48'W) with 2–8% slopes. The dominant soil series is Sonnett (fine, smectic, frigid Aridic Haplustalfs), but the pastures include 24 soil series and complexes that are highly interspersed. Sixty-five percent of the area is classified as a silty ecological site and 14% is a clayey ecological site. Climate is continental, with a January average minimum temperature of -14 °C and a July average maximum temperature of 32 °C. About 76% of the precipitation occurs from April through September and the long-term (1878–2009) annual average is 334 mm. Vegetation is grass-dominated, with blue grama (Bouteloua gracilis (Willd. Ex Kunth) Lag. Ex Griffiths), western wheatgrass (Pascopyrum smithii (Rydb.) A. L�ve), needle-and-thread (Hesperostipa comata (Trin. & Rupr.) Barkworth), and threadleaf sedge (Carex filifolia Nutt.) as the most abundant graminoids. Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis Beetle & Young) and fringed sagebrush (Artemisia frigida Willd.) are the most common woody plants and the succulent pricklypear (Opuntia polyacantha Haw.) occur frequently. Permanent quadrats were established on the site in 1932 to evaluate cattle stocking rate effects on pastures grazed annually from May through October. While the pasture boundaries have remained the same, grazing regimes have varied since the quadrat mapping period.

a. Design characteristics: 44 permanent quadrats were located in 6 different pasture units.
b. Permanent plots: We have not been able to relocate the original quadrats because of a lack of permanent markers.
c. Data collection: Quadrats were mapped annually from 1932 to 1945, with some exceptions (see the quadrat sampling schedule data file in IV). Quadrats were mapped in the late spring-early summer growing season each year (generally between late May and July).

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. For a complete digitization protocol, contact Peter Adler. Daily climate data were obtained from the Miles City airport, Wiley Field (800 m a.s.l., 46°26�N, 105°53�W) located 9 km north of the study site. For the period beginning in 1933, these data are available on-line from the National Climate Data Center at www4.ncdc.noaa.gov/cgi-win/wwcgi.dll?wwDI~StnSrch~StnID~20012408.
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.gov/). We recorded these name changes in the species_name_changes.csv file.
d. Permit history: N/A
e. Legal/organizational requirements: N/A

CLASS III. DATA SET STATUS AND ACCESSIBILITY

A. Status

Latest update: Some corrections made 3 January 2012. See readme.txt
Latest Archive date:
Metadata status:

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 data set (stored shapefiles) in 2010:

a) Shapefiles were rotated to have a consistent orientation;
b) Species names for unlabeled and obviously mislabeled polygons and points were assigned based on species names assigned to 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. Typically, perennial grasses are cover features, and forbs are points (density features). However, the classification ultimately depended on how each species was most commonly mapped by the original mappers, so some perennial grasses (e.g. Pascopyrum smithii) appear as points, and some forbs or shrubs as cover features. Occasionally, individuals of cover-type species were mapped as points; we converted these records to arbitrary small square polygons of 0.25 cm². Similarly, individuals of density-type species mapped as polygons were converted to point features with location at the centroid of the polygon;
f) Plant names were corrected for synonyms based on the USDA PLANTS Database on 31 January, 2011 (http://plants.usda.gov/);
g) x,y coordinates of each polygon centroid were added to shapefile attribute tables.
h) Climatic data was checked for extreme values by inspection of a visual representation of the data.

B. Accessibility

Storage location and medium:

Contact person: Peter B. Adler, Department of Wildland Resources and the Ecology Center, Utah State University, Logan, UT, 84322 USA, [email protected].

Copyright restrictions: None.

Proprietary restrictions: None, although we would like to hear how the data are being used (e.g., for what research questions or teaching exercises).

Costs: None.

CLASS IV. DATA STRUCTURAL DESCRIPTORS

A. Data Set File

Identity: shapefiles.zip
Size: 33,505,926 bytes.
Format and storage mode: Shapefiles compressed and submitted together in a zipped directory.
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 (A–F#), year (YY), and geometry (C or D) of each shapefile. C refers to �cover� (e.g., features mapped as polygons) while D refers to �density� (e.g., features mapped as points). For example, �A1_32_D.shp� is the point shapefile for year 1932 in Quadrat A1. 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 data set (e.g., if no forbs occurred in a quadrat in a given year, we removed the empty density shapefile).

A. Data Set File

Identity: allrecords_density.csv
Size: 125,201 records, 9,414,808 bytes.
Format and storage mode: ASCII text, comma separated. No compression scheme was used.
Header information: The first row of the file contains the variable names below.

B. Variable information

A. Data Set File

Identity: allrecords_cover.csv
Size: 81,365 records, 7,606,877 bytes.
Format and storage mode: ASCII text, comma separated. No compression scheme was used.
Header information: The first row of the file contains the variable names below.

B. Variable information

A. Data Set File

Identity: quad_info.csv
Size: 44 records, 656 bytes.
Format and storage mode: ASCII text, comma separated. No compression scheme was used.
Header information: The first row of the file contains the variable names below.

B. Variable information

A. Data Set File

Identity: quad_inventory.csv
Size: 14 records, 2,086 bytes.
Format and storage mode: ASCII text, comma separated. No compression scheme was used.
Header information: The first row of the file contains the variable names below.

B. Variable information

A. Data Set File

Identity: species_list.csv
Size: 155 records, 5,128 bytes.
Format and storage mode: ASCII text, comma separated. No compression scheme was used.
Header information: The first row of the file contains the variable names below.

B. Variable information

A. Data Set File

Identity: daily_climate_data.csv
Size: 5114 records, 128,441 bytes.
Format and storage mode: ASCII text, comma separated. No compression scheme was used.
Header information: The first row of the file contains the variable names below.

B. Variable information

A. Data Set File

Identity: annuals_counts_v2.csv
Size: 2,536 records, 79,051 bytes.
Format and storage mode: ASCII text, comma separated. No compression scheme was used.
Header information: The first row of the file contains the variable names below.

B. Variable information

CLASS V. SUPPLEMENTAL DESCRIPTORS

A. Data acquisition

Data forms: N/A
Location of completed data forms: USDA-ARS Fort Keogh Livestock and Range Research Laboratory
Data entry/verification procedures: See II.3 and III.4.

B. Quality assurance/quality control procedures: The procedures described above (II.3 and III.4) ensured accurate transfer of information from the original to the digital maps and correction of some errors introduced at 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.

C. Related material: N/A

D. Computer programs and data processing algorithms: N/A

E. Archiving: N/A

F. Publications using the data set: N/A

Hurtt, L.C. 1951. Managing Northern Great Plains cattle ranges to minimize effects of drought. USDA Agric. Circ. 865.
Olson, K. C., R. S. White, and B. W. Sindelar. 1985. Response of vegetation of the northern Great Plains to precipitation amount and grazing intensity. J. Range Manage 38:357–361.
Reed, M.J. and Peterson, R.A. 1961. Vegetation, soil and cattle responses to grazing on Northern Great Plains range. U. S. Forest Serv. Tech. Bull. No. 1252.

G. History of data set usage: N/A

Data request history: N/A
Data set update history: N/A
Review history: N/A
Questions and comments from secondary users: N/A

ACKNOWLEDGMENTS

We thank Anthony Frenzel, Camilla Frenzel, Daniel Anaya, Levi Rose, and Spencer Allred 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 8289. We thank Margaret Moore, Kurt Reinhardt and two anonymous reviewers who comments improved the manuscript.

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