Ecological Archives E088-161-D1

Peter B. Adler, William R. Tyburczy, and William K. Lauenroth. 2007. Long-term mapped quadrats from Kansas prairie: demographic information for herbaceaous plants. Ecology 88:2673.


INTRODUCTION

Current theory in plant ecology has increasingly focused on demographic processes. Patterns of births and deaths play a central role in neutral theory (Hubbell 2001) and in theories explaining tree size distributions (Muller-Landau et al. 2006). These recent advances emphasize that demographic information is often essential for understanding community and ecosystem patterns.

Demography will also be important for predicting how plant populations and communities will respond to climate change. The rate at which populations decline, disperse, or even adapt under changing climate will depend on life history traits such as the longevity of adult plants, persistence of seed banks, and seed dispersal distances. It will also be essential to understand the relationship between stochastic climate variables and vital rates such as fecundity, germination, and survival (Meyer et al. 2006).

Despite the overwhelming importance of demography for answering these theoretical and applied questions, empirical data are very limited. Many of the best available data come from long-term forest plots (Condit et al. 1996, Clark and Clark 2006), largely because individual trees are easy to identify and follow through time. The situation is much worse for herbaceous plants. A handful of species are well-studied, though usually for time periods of less than a decade (see for example Meyer and Schmid 1999, Eriksson and Eriksson 2000, Morris and Doak 2004, Williams and Crone 2006). For the vast majority of species, however, we have no information on mean lifespans and population growth rates, let alone a quantitative understanding of how climate variables interact with density dependent processes to influence vital rates. Because herbaceous communities are likely to respond more quickly than forests to perturbations such as climate change, this information is urgently needed.

Here we present a long-term data set that has great potential to increase our understanding of plant demographic processes. Every year from 1932–1972, researchers from Fort Hays State University, in Hays, Kansas, mapped all individual plants in a series of 1-m2 quadrats in a mixed grass prairie (38.8°N, 99.3°W) (Albertson 1937, Albertson and Tomanek 1965). Long-term mapping of individual herbaceous plants on permanent quadrats was a technique popularized by Clements (1907) for obtaining "an exact record of changes in structure " (p. 205). Albertson and colleagues used their data to describe how dominant species responded to and recovered from severe drought (e.g., Albertson and Weaver 1942, Albertson and Tomanek 1965). Perhaps because research questions about vegetation trends could be answered using more efficient sampling methods, data collection ended in 1972, a decade after Albertson's death, and the year before Dr. Gerald Tomanek transitioned from research to administration.

The Hays data set offers a rare combination of temporal extent and fine spatial resolution. Although the original researchers lacked the tools to fully utilize such data, Geographic Information Systems (GIS) and modern statistical techniques now make it possible to follow individual plants (or genets) through time and answer questions such as: How long do herbaceous clones live (Fair et al. 1999) and does survival vary with age (Lauenroth and Adler unpublished data)? What is the interannual variability in survival and recruitment rates, and can precipitation and temperature explain this variability? How are survival and recruitment modified by interactions with neighboring conspecifics and heterospecifics (e.g., Purves and Law 2002, Adler et al. 2006)?

The quadrats were distributed across gradients in soil type that produce distinct plants communities (Albertson 1937). Deep soils on the level uplands support a shortgrass community dominated by blue grama (Bouteloua gracilis) and buffalograss (Buchloë dactyloides). Shallow limestone soils on hillbrows and slopes support a community dominated by little bluestem (Schizachyrium scoparium). A distinct ecotone separates the shortgrass and little bluestem areas. The most productive sites are dominated by big bluestem (Andropogon gerardii). Most of the quadrats are located inside livestock exclosures.

The maps show basal cover, the part of the plant in contact with the soil surface. The density of individual plants can also be calculated from the maps. Whether to use basal cover or density as a measure of abundance depends on the functional type of the species being analyzed. For caespitose perennial grasses, basal cover is the clear choice: it is an excellent measure of importance, is sensitive to interannual fluctuations, and can be modeled on a spatial grid (Adler et al. 2006). For single-stemmed plants such as forbs, however, basal cover is insensitive to fluctuations. Instead we use density when analyzing forb population dynamics.

The data set contains the following data and data formats: (1) the digitized maps in Arc Export format, (2) a tabular, non-spatial version of the entire data set, (3) quadrat information, such as plant community type and location in the study site, (4) an inventory of the years each quadrat was sampled, (5) a species list, containing information on plant functional types, and (6) monthly precipitation and average temperature.

 

METADATA CLASS I. DATA SET DESCRIPTORS

A. Data set identity:

Title: Basal cover of vascular plants mapped in permanent quadrats in Kansas mixed-grass prairie

B. Data set identification code

C. Data set description

Principal Investigator: Peter Adler, Department of Wildland Resources and the Ecology Center, Utah State University, Logan, UT, 84322 USA; William Lauenroth, Department of Forest, Range and Watershed Stewardship, Colorado State University, Fort Collins, CO 80523 USA

Abstract:

Demographic data will play a central role in testing current theories in plant ecology and forecasting the effects of global change. However, long-term data on vital rates are very limited, especially for species in herbaceous plant communities. Here we present a data set that has great potential to increase our understanding of plant demographic processes. Every year from 1932 to 1972, researchers in Hays, Kansas (USA), mapped all individual plants in a series of 1-m2 quadrats in a mixed grass prairie. The rare combination of temporal extent and fine spatial resolution makes it possible to follow individual herbaceous plants (or genets) through time and to answer questions such as: How does individual survival and recruitment vary with precipitation and temperature? How are these relationships modified by interactions with neighboring conspecifics and heterospecifics? The data set includes the digitized maps in Arc Export format, a tabular, nonspatial version of the entire data set, descriptive information about each quadrat including its sampling schedule, a species list containing information on plant functional types, and monthly climate data.

D. Key words: climate; competition; demography; Geographic Information System; grassland, plant community.

CLASS II. RESEARCH ORIGIN DESCRIPTORS

A. Overall project description

Identity: Basal cover of vascular plants mapped in permanent quadrats in Kansas mixed-grass prairie

Originator: Dr. William Laurenroth

Period of Study: 1932–1972

Objectives:To monitor the establishment, growth, and survival of individual plants

Abstract: same as above.

Source(s) of funding: National Science Foundation

B. Specific subproject description

1. Site description: Permanent quadrats were established in 1932 in native, southern mixed-grass prairie plant communities in a pasture owned by Fort Hays State University.

Site type:  The permanent quadrats are located in fairly distinct plant communities. Deep soils on the level uplands support a shortgrass community dominated by blue grama (Bouteloua gracilis) and buffalo grass (Buchloë dactyloides). Shallow limestone soils on hillbrows and slopes support a community dominated by little bluestem (Schizachyrium scoparium). A distinct ecotone separates the shortgrass and little bluestem areas. Patches of tallgrass prairie, dominated by big bluestem (Andropogon gerardii), occur in swales.

Geography:  The study site is located approximately 2 miles west of the town of Hays (38.8 º N, 99.3 º W)

Habitat:  See "Site type" above.

Geology: Soils are derived from both limestone parent material as well as wind-deposited loess.

Watersheds/hydrology: N/A

Site history: The site has historically been managed with light intensity cattle grazing during spring and summer.

Climate: Mean annual precipitation is 580 mm, falling mostly April-September, and mean annual temperature is 12ºC.

2. Experimental design: 36 permanent quadrats were located in two livestock exclosures ("e1" and "e2"). Each exclosure contains quadrats arranged along a gradient of soil depth. 15 quadrats were located in grazed areas outside the exclosures, mostly in the shortgrass community.

Design characteristics: N/A

Permanent Plots: See quadrat information data file below.

Data Collection Period, Frequency: Quadrats were mapped annually from 1932–1972, with some exceptions (see the quadrat sampling schedule data file). Quadrats were mapped late in each summer growing season.

3. Research Methods

Field/Laboratory: The data were collected using pantographs (Hill 1920), a mechanical device used to make scale drawings. The original paper maps were first scanned, and then stored as tif image files. These images were then converted into a GIS as Arc coverages using heads-up digitizing.

After the initial digitizing phase, all maps were checked for completeness and accuracy. In addition, time series of species abundances were generated to identify outlier maps. Based on these error checks, we made the following changes to the data set: (1) We removed 15 coverages (quadrat-years) in which the mapping of a particular quadrat appeared obviously inconsistent with the preceding and following years. (2) Coverages were rotated to have a consistent N-S vertical orientation. (3) For large polygons that were unlabeled or obviously mislabeled, we corrected the assigned species name based on our best judgment (approximately 40 changes). The corrected coverages were then processed using the Arc Clean function to ensure good topology. Finally, we added the x,y coordinates of each polygon centroid using the Arc Addxy function.

We assigned species to functional groups based on information from the Flora of the Great Plains (Great Plains Flora Association, 1986) and the USDA Plants Database (http://plants.usda.gov/)

Monthly climate data was obtained from the National Climatic Data Center (http://www.ncdc.noaa.gov/oa/ncdc.html).

Instrumentation: N/A

Taxonomy and systematics: Originally assigned plant names were corrected for synonyms based on Flora of the Great Plains and the USDA Plants Database.

Permit history: N/A

Legal/organizational requirements: None.

4. Project personnel:  N/A

CLASS III. DATA SET STATUS AND ACCESSIBILITY

A.Status

Latest Update:Feb. 2007

Latest Archive date:Feb. 2007

Metadata status: The metadata are complete and up to date.

Data verification: See CLASS II, section 3, Research Methods.

B.Accessibility

Storage location and medium: (Ecological Society of America data archives [Ecological Archives], URL published in each issue of its journals). Original data files exist on author’s personal computer and on CD.

Contact person: Peter Adler, Department of Wildland Resources and the Ecology Center, Utah State University, Logan, UT, 84322 USA peter.adler@usu.edu

Copyright restrictions: None.

Proprietary restrictions: None.

Costs: None.

CLASS IV. DATA STRUCTURAL DESCRIPTORS

SPATIAL DATA

A. Data Set File

Identity: arcexport.zip

Size: 65,915,409 bytes.

Format and storage mode: Arc coverages in Arc Export format. Compressed using ZIP.

Header information: The first row of the file contains the variable names below.

Alphanumeric attributes: Mixed.

Special characters/fields: N/A

Authentication procedures: MD5 Checksum for the file: 6f80aa9b810796934b12dd759fd18069

B. Variable information

Description:  This is a zipped directory, containing a series of subdirectories, each corresponding to one quadrat. Within the subdirectories are individual files (Arc coverages in Arc Export format) for each year that the quadrat was mapped. The polygons show the location and area (basal cover) of individual plants.

RECORD OF ALL INDIVIDUAL PLANTS

A. Data Set File

Identity: allrecords.csv

Size: 163,401 records, 10,750,132 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.

Alphanumeric attributes: Mixed.

Special characters/fields: N/A

Authentication procedures: MD5 Checksum for the file: 2ddb4800fdc64b4dc583b05532c72e5c

B. Variable information

Variable name

Variable definition

Units

Storage type

Precision

Variable codes and definitions

plotyear

Name of the plot (quadrat) and the year if the observation (last 2 digits). For example, "e1q1-137" refers to quadrat e1q1-1 in year 1937.

N/A

Character

N/A

N/A

ID

Identification of each record (an individual plygon in the GIS) within a given quadrat in a given year.

N/A

Character

N/A

N/A

species

Name of the cover category or the Latin name of the plant species (genus, species).

N/A

Character

N/A

N/A

area

Basal cover in cm^2. Basal cover is the part of the plant in contact with the soil surface.

cm2

Floating Point

1e-8

N/A

x

Location of center-point of record in the East-West direction within the quadrat.

cm

Floating Point

1e-8

N/A

y

Location of the centerpoint of the record within the plot in the North-South direction.

cm

Floating Point

1e-8

N/A

QUADRAT INFORMATION

A. Data Set File

Identity: quadrat_info.csv

Size: 64 records, 3917 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.

Alphanumeric attributes: Mixed.

Special characters/fields: N/A

Authentication procedures: MD5 Checksum for the file: f994f5093bd6d4964acd7ed4100a7f11

B. Variable information

Variable name

Variable definition

Units

Storage type

Precision

Variable codes and definitions

quadrat

quadrat name

N/A

Character

N/A

N/A

shapefiles

Quadrat name for shapefiles: shapefiles have naming restrictions which required abbreviated versions of the original quadrat names

N/A

Character

N/A

N/A

grazing

Presence of absence of cattle grazing

N/A

Character

N/A

No - No grazing (inside exclosure)

Yes - Grazing (outside exclosure)

quadX

Approximate location of quadrat in East-West direction relative to the soutwest corner of exclosure 1.

cm

Floating Point

0.01

N/A

quadY

Location of quadrat in North-South direction relative to the southwest corner of exclosure 1.

cm

Floating Point

0.01

N/A

Description

Original description of quadrat vegetation in the 1930's.

N/A

Character

N/A

N/A

community

Code for quadrat vegetation based on the original description and dominant plant species

N/A

Character

N/A

sg - Shortgrass

et - Ecotone

lb - Little bluestem

bb - Big bluestem

group

The original investigators established groups of quadrats with similar vegetation. This code species the plant community and quadrat group within that community (last digit).

N/A

Character

N/A

N/A

QUADRAT SAMPLING SCHEDULE

A. Data Set File

Identity: quadrat_inventory.csv

Size: 43 records, 8687 bytes

Format and storage mode: ASCII text, comma separated. No compression scheme was used.

Header information: See variable names in Section B.

Alphanumeric attributes: Mixed.

Special characters/fields: N/A

Authentication procedures: MD5 Checksum for the file is: 4e77e602f7a50dbc39f602c6e67be315

B. Variable information

Variable name(s)

Variable definition

Units

Storage type

Precision

Variable codes and definitions

year

Calendar year in which the temperatures were recorded.

N/A

Integer

N/A

N/A

[quadrat name] 

(e1q1-1, e1q1-2, e1q1-3, etc. See Quadrat Information data file for complete list)

Indicates whether or not the named quadrat was sampled that year

N/A

N/A

N/A

No - not sampled

Yes - sampled

SPECIES LIST

A. Data Set File

Identity: species_list.csv

Size: 152 records, 6,473 bytes

Format and storage mode: ASCII text, comma separated. No compression scheme was used.

Header information: See variable names in Section B.

Alphanumeric attributes: Mixed.

Special characters/fields: N/A

Authentication procedures: MD5 Checksum for the file is: 643a0b13dce686194782da6df23ff15c

B. Variable information

Variable name

Variable definition

Units

Storage type

Precision

Variable codes and definitions

species

Name of cover class or Latin name of a plant species (genus, species)

N/A

Character

N/A

N/A

type

Functional groupings for plant species

N/A

Character

N/A

c3 - Perennial C-3 graminoids

forb - Perennial forbs (non-graminoid herbaceous plants)

shrub - Woody perennial plants

c4 - Perennial C-4 graminoids (excluding the shortgrasses)

annual - Any annual plant

remove - Cover classes that are not plants (e.g. bare ground)

shortgrass - The short C-4 grasses Bouteloua gracilis and Buchloë dactyloides

biennial - Forbs (non-graminoid herbaceous plants) with 2 year life cycles

succulent - Mostly cactus

count

Number of records of the species in the entire data set

dimensionless

Integer

1

N/A

PLANTS Symbol

The symbol used to signify the given species in the USDA PLANTS database at http://plants.usda.gov/

N/A

Character

The codes and their definitions can be found at the USDA PLANTS database website

 

PLANTS Synonym

The synonym code for the species name in the USDA PLANTS database when the species name used here does not correspond to the primary name given in the PLANTS database at http://plants.usda.gov

N/A

Character

N/A

The codes and their definitions can be found at the USDA PLANTS database website.

MONTHLY TEMPERATURES

A. Data Set File

Identity: monthly_temp.csv

Size: 112 records, 8103 bytes

Format and storage mode: ASCII text, comma separated. No compression scheme was used.

Header information: See variable names in Section B.

Alphanumeric attributes: Mixed.

Special characters/fields: N/A

Authentication procedures: MD5 Checksum for the file is: 1e4530e0948ac9fe5292dc4f81a7ea63

B. Variable information

Variable name(s)

Variable definition

Units

Storage type

Precision

Variable codes and definitions

YEAR

Calendar year in which the temperatures were recorded.

N/A

Integer

N/A

N/A

JAN, FEB, MAR, APR, MAY, JUN, JUL, AUG, SEP, OCT, NOV, DEC

Mean monthly temperature for that month, respectively

Celsius

Floating Point

0.01

N/A

MONTHLY PRECIPITATION

A. Data Set File

Identity: monthly_ppt.csv

Size: 112 records, 7058 bytes

Format and storage mode: ASCII text, comma separated. No compression scheme was used.

Header information: See variable names in Section B.

Alphanumeric attributes: Mixed.

Special characters/fields: N/A

Authentication procedures: MD5 Checksum for the file is: ca4c92155d92e045be6f5272e85c34bd

B. Variable information

Variable name(s)

Variable definition

Units

Storage type

Precision

Variable codes and definitions

YEAR

Calendar year in which the measurements were recorded.

N/A

Integer

N/A

N/A

JAN, FEB, MAR, APR, MAY, JUN, JUL, AUG, SEP, OCT, NOV, DEC

Total precipitation for that month, respectively

mm

Floating Point

0.1

N/A

 

CLASS V. SUPPLEMENTAL DESCRIPTORS

A. Data acquisition

Data forms:  NA

Location of completed data forms:  The original chart quadrat data sheets are archived in the special collections of the Forsyth Library, Fort Hays State University, Kansas, USA.

Data entry verification procedures: See CLASS II, section 3, Research Methods.

B. Quality assurance/quality control procedures: The procedures described above (CLASS II, section 3, Research Methods) ensured accurate transfer of information from the original to the digital maps and correction of some errors introduced at the original mapping stage. However, we identified three problems that were not easily corrected. First, before 1937 some grasses were not identified to species. Second, the general quality of the maps appears to decline after 1968 in many quadrats. Depending on the analysis, users may wish to conduct additional quality control on data from these early and late years or exclude the earliest and latest years from analyses. Third, we noticed mapping inconsistencies involving Bouteloua gracilis and Buchloë dactyloides, which is understandable since these two grasses can be difficult to distinguish in the field. Data on these species are high enough quality that the original investigators successfully contrasted their recovery following the Great Drought of the 1930's (Albertson and Tomanek 1965). In addition, we have found that automated analyses of these species' survival (Lauenroth and Adler unpublished data), which assume perfect data, produce results similar to a manual approach that removed mapping inconsistencies (Fair et al. 1999). Nevertheless, future users should inspect the maps before analyzing competitive interactions between these two species. More generally, 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: Zip files containing the scanned images of the original maps (TIFF format, *.tif) and the GIS files in shapefile format may be found at the Knowledge Network for Biocomplexity: http://knb.ecoinformatics.org/knb/metacat?action=read&qformat=knb&docid=adler.3.

D. Computer programs and data processing algorithms: 

E. Archiving

Archival Procedures: Data files and associated metadata have been archived on the Knowledge Network for Biocomplexity (KNB).  The current link for the metadata is  (http://knb.ecoinformatics.org/knb/metacat?action=read&qformat=knb&docid=adler.3).  Data files may also be retrieved from this site.

Redundant Archival Sites:  Data on the KNB is automatically replicated onto the Long-Term Ecological Research Network site (http://metacat.lternet.edu/knb/index.jsp).

F. Publications using the data set:

Adler, P. B. 2004.  Neutral models fail to reproduce observed species-time and species-area relationships in Kansas grasslands. Ecology 85:1265–1272.

Adler, P.B. and W.K. Lauenroth. 2003. The power of time: spatiotemporal scaling of species diversity. Ecology Letters 6:749–756.

Adler, P.B. and J. M. Levine. 2007.  Contrasting relationships between precipitation and species richness in space and time. Oikos 116:221–232.

Adler, P.B., HilleRisLambers, J., Kyriakidis, P., Guan, Q., and J.M. Levine. 2006. Climate variability has a stabilizing effect on coexistence of prairie grasses. Proceedings of the National Academy of Sciences 103:12793–12798.

Albertson, F. W. 1937. Ecology of mixed prairie in west central Kansas. Ecological Monographs 7:481–547.

Albertson, F. W., and G. W. Tomanek. 1965. Vegetation changes during a 30-year period in grassland communities near Hays, Kansas. Ecology 46:714–720.

Albertson, F. W., and J. E. Weaver. 1944. Nature and degree of recovery of grassland from the Great Drought of 1933 to 1940. Ecological Monographs 14:393–479.

Fair, J., Lauenroth, W. K., and D. P. Coffin. 1999. Demography of Bouteloua gracilis in a mixed prairie: analysis of genets and individuals. Journal of Ecology 87:233–243.

White, E.P., Adler, P.B., Lauenroth, W.K., Gill, R.A., Greenberg, D., Kaufman, D.M., Rassweiler, A., Rusak, J.A., Smith, M.D., Steinbeck, J.R., Waide, R.B. and J. Yao. 2006. A comparison of the species-time relationship across ecosystems and taxonomic groups. Oikos 112:185–195.

G. Publications using the same sites: N/A

H. History of data set usage

Data request history: N/A

Data set update history: N/A

Review history: N/A

Questions and comments from secondary users: N/A

ACKNOWLEDGMENTS


Digital archiving of the chart quadrat data was made possible by support from the Division of Biological Sciences at Fort Hays State University, the Colorado Agricultural Experiment Station Grant (157661), the National Science Foundation (DEB-9011659, DEB-0217631, and a Bioinformatics post-doctoral fellowhip to PBA) and the National Center for Ecological Analysis and Synthesis. F. W. Albertson and G. W. Tomanek and many generations of their graduate students were responsible for maintaining the site and collecting the data.

LITERATURE CITED

Adler, P. B., J. HilleRisLambers, P. Kyriakidis, Q. Guan, and J. M. Levine. 2006. Climate variability has a stabilizing effect on coexistence of prairie grasses. Proceedings of the National Academy of Sciences 103:12793–12798.

Albertson, F. W. 1937. Ecology of mixed prairie in west central Kansas. Ecological Monographs 7:481–547.

Albertson, F. W., and G. W. Tomanek. 1965. Vegetation changes during a 30-year period in grassland communities near Hays, Kansas. Ecology 46:714–20.

Albertson, F. W., and J. E. Weaver. 1942. History of the vegetation of western Kansas during seven years of continuous drought. Ecological Monongraphs 12:23–51.

Clark, D. B., and D. A. Clark. 2006. Annual tree growth, mortality, physical condition and microsite in an old-growth lowland tropical rain forest, 1983–2000. Ecology 87:2132.

Clements, F. 1907. Plant Physiology and Ecology. Henry Holt and Co., New York, New York, USA.

Condit, R., S. P. Hubbell, and R. B. Foster. 1996. Changes in a tropical forest with a shifting climate: results from a 50 ha permanent census plot in Panama. Journal of Tropical Ecology 12:231–256.

Eriksson, A., and O. Eriksson. 2000. Population dynamics of the perennial Plantago media in semi-natural grasslands. Journal of Vegetation Science 11:245–252.

Fair, J., W. K. Lauenroth, and D. P. Coffin. 1999. Demography of Bouteloua gracilis in a mixed prairie: analysis of genets and individuals. Journal of Ecology 87:233–243.

Great Plains Flora Association. 1986. Flora of the Great Plains. University Press of Kansas, Lawrence, Kansas, USA.

Hill, R. R. 1920. Charting quadrats with a pantograph. Ecology 1:270–273.

Hubbell, S. P. 2001. The unified neutral theory of biodiversity and biogeography. Princeton University Press, Princeton, New Jersey, USA.

Meyer, A. H., and B. Schmid. 1999. Experimental demography of the old-field perennial Solidago altissima: The dynamics of the shoot population. Journal of Ecology 87:17–27.

Meyer, S. E., D. Quinney, and J. Weaver. 2006. A stochastic population model for Lepidium Papilaferum (Brassicaceae), a rare desert ephemeral with a persistent seed bank. American Journal of Botany 93:891–902.

Morris, W. F., and D. F. Doak. 2004. Buffering of life histories against environmental stochasticity: Accounting for a spurious correlation between the variabilities of vital rates and their contributions to fitness. American Naturalist 163:579–590.

Muller-Landau, H. C. (and 43 others). 2006. Comparing tropical forest tree size distributions with the predictions of metabolic ecology and equilibrium models. Ecology Letters 9:589–602.

Purves, D. W., and R. Law. 2002. Fine-scale spatial pattern in a grassland community: quantifying the plant's-eye view. Journal of Ecology 90:121–129.

Williams, J. L., and E. E. Crone. 2006. The impact of invasive grasses on the population growth of Anemone patens, a long-lived native forb. Ecology 87:3200–3208.


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