METADATA CLASS I. DATA SET DESCRIPTORS
A. Data set identity:
Title: Mammal abundance indices in the northern portion of the Great Basin, 1962–1993
B. Data set identification code
Suggested Data Set Identity Code: Mammal_abundance_indices.txt
C. Data set description
Principal Investigator: R. A. Bartel’s current address is Zoology Department, Campus Box 7617, North Carolina State University, Raleigh, North Carolina.
Abstract:
Indices of abundance of selected mammals were obtained for two study areas within the Great Basin: the Idaho National Engineering and Environmental Laboratory, Idaho, and Curlew Valley, Utah, USA. Data collection occurred biannually 1962–1993, with varying durations among species and sites. Abundance indices were obtained for coyotes (Canis latrans), lagomorphs (primarily black-tailed jackrabbits, Lepus californicus), and eight species of rodents. Data were originally gathered as part of a long-term study of interactions among predator and prey populations, concentrating on aspects related to coyotes and black-tailed jackrabbits (Knowlton, F. F., and L. C. Stoddart. 1992. Some observations from two coyote-prey studies. Pages 101 – 121 in A. Boer, editor. Ecology and management of the eastern coyote. Wildlife Research Unit, University of New Brunswick, Fredericton, New Brunswick, Canada). Secondarily, these data are useful in portraying trends in mammal abundance on these two Great Basin sites.
D. Key words: abundance, black-tailed jackrabbit, Canis latrans, coyote, Great Basin, lagomorph, long-term data set, population trends, rodent.
CLASS II. RESEARCH ORIGIN DESCRIPTORS
A. Overall project description
Identity: Mammal abundance patterns in the northern portion of the Great Basin
Originators:
Frederick F. Knowlton
USDA/APHIS/WS/NWRC
Utah State University
Logan, Utah 84322-5295L. C. Stoddart
5425 York Rd.
Helena, Montana 59602Period of Study: 1962–1993
Objectives: To understand general patterns of mammal abundance in the Great Basin, especially as it relates to predator–prey interactions.
Abstract: same as above.
Source(s) of funding: U. S. Department of Agriculture—Animal and Plant Health Inspection Service
U. S. Department of Interior—U. S. Fish and Wildlife Service
U. S. Department of Energy
U. S. Atomic Energy Commission
B. Specific subproject description
Site description: We provide data from 2 field sites within the northern portion of the Great Basin (Fig. D1). The 700-km2 Curlew Valley (CV) site is located in Box Elder County, Utah, with primary boundaries on the north and northwest comprised of State Highway 30, on the east by the Snowville-Locomotive Springs road, on the south by salt flats adjacent to the Great Salt Lake and on the west by the Kelton access road. Climate is described as Northern Desert Shrub Biome (Fautin 1946) and Temperate Desert Division Ecoregion (Bailey 1998) with climate data recorded at the Snowville Station of the National Climatic Data Center (NOAA 2002, http://www.noaa.org). Vegetative communities are documented by Booth (2001). About 20% of the site was subject to range fires in 1983.
Our other study site encompassed 1,225 km2 of the Idaho National Engineering and Environmental Laboratory (INEEL), a National Environmental Research Park (NERP) located in portions of Bingham, Bonneville, Butte, Clark, and Jefferson Counties, Idaho. Located about 56 km northwest of Idaho Falls, it is situated within the northern portion of the Snake River Plain. Flora and faunal lists are available at http://www.stoller-eser.com and climatic data can be acquired at http://www.noaa.org. Vegetative communities are also described by Harniss and West (1973) and McBride et al. (1978).
FIG. D1. Two field sites within the northern portion of the Great Basin, Curlew Valley, Utah and the Idaho National Engineering and Environmental Laboratory, Idaho. Experimental or sampling design/field methods:
Indices of rodent abundance. — Trends in the abundance of various rodents were assessed via a series of rodent survey routes. Each survey route utilized 23.2 km (14.4 mi) of tertiary dirt road and consisted of 25 trapping transects located at 0.97-km (0.6 mi) intervals along and perpendicular to the route, alternately on the left and right of the road. Each transect consisted of 10 trap stations, spaced 10 m apart at which we placed 1 M-4 snap trap with an expanded treadle (Carley and Knowlton 1971). Traps were baited with a mixture of peanut butter and rolled oats and checked daily for three consecutive trap-nights. The indices of rodent abundance are expressed as “catch per unit effort,” with effort defined with the equation of Hoffman (1979), Stoddart (1987a, b), and Mills (1987) and Mills and Knowlton (1991):
E =
![]()
where:
E = effort (number of trap nights);
No = initial number of operable traps; and
Nt = No minus the number of sprung traps (with or without rodents),
which assumes the rate at which traps are sprung decreases in proportion to the number of traps still operable because once sprung, traps no longer contribute to the trapping effort.
We established 4 permanent rodent survey routes in CV and 6 in INEEL to assess relative rodent abundance. The attempted trapping effort in Curlew Valley was 3,000 trap-nights for each spring and fall sampling period between 1973 and 1986. On INEEL, the target trapping effort was 4,500 trap-nights each spring and fall 1975–1984.
Indices of lagomorph abundance.—Black-tailed jackrabbits were common to both study sites. A series of 1.6-km square flushing transects (0.4-km per side), were located near dirt roads and trails in randomly selected survey sections, as per Gross et al.(1974). A four-foot steel post permanently defined the starting and ending point of each transect. Each transect was walked each fall and spring between 0900 and 1600 h. The right-angle distance from the transect to the flushing point of each jackrabbit observed was determined and used to calculate a density estimate from frequency distributions of perpendicular flushing distances using the Fourier series estimator in program TRANSECT (Burnham et al. 1980). Subsequently, when experimental transects conducted on horseback provided a 141% higher estimate (Wywialowski and Stoddart 1988), density estimates from the walked transects were considered indices, effectively changing the scale but not the pattern of the estimates. In CV, transects (n = 59–65) were walked 1962–1993 and in INEEL (n = 80) 1975–1986. In 1985-1986, the overall index of jackrabbit abundance in INEEL was based upon 22 lines in the northeast section of the study area.
Two additional lagomorph species, mountain cottontails (Sylvilagus nuttallii), and pygmy rabbits (Brachylagus idahoensis) were detected on the INEEL site. Because positive species identifications of flushed rabbits was not always accomplished, our abundance indices for these two species were combined.
Indices of coyote abundance.— The methodology we used to assess relative coyote abundance changed several times as our understanding of caveats associated with each technique increased (Knowlton 1984). Ultimately, 4 independent indices contributed to our assessments of coyote abundance. We then synthesized a single index based upon results obtained as (1) catch-rates from coyote capture efforts, (2) coyote visitation rates to artificial scent stations, and (3) coyote scat deposition rates.
Two catch-rate indices were initially used to assess relative coyote abundance (Clark 1972). Between 1966 and 1981, a fall index of coyote abundance was obtained for the CV site based on coyote capture rates (no. of coyotes captured/trap-night) in about 30 days of trapping effort (1,424–2,942 trap-nights, x = 1,942) with #3 Victor leg-hold traps (Clark 1972). In an effort to extend the index of relative coyote abundance in CV retrospectively, Clark (1972) examined aerial gunning records from the Utah’s Animal Damage Control Program. The coyote kill-rate, in terms of the number of coyotes shot by aerial gunning teams per hour of flight in the Curlew Valley area was used to create another index of coyote abundance for 1963–1966 and thus project the coyote capture rate index backward by 3 years.
Another index of coyote abundance was derived from the deposition rate of coyote scats upon selected portions of dirt roads and trails. In Curlew Valley this initially involved recovering coyote scats from a 40-mile route of dirt roads and trails. To improve the sampling strategy, this was changed in 1976 to using a series of 23 1.6-km (1.0-mile) permanently identified transects (road segments) distributed throughout the CV site. The sampling effort increased by adding 24 additional transects in 1978 and 6 more in 1980. For each scat index value, each transect was walked and cleared of all coyote scats detected. Two and 4-weeks after clearing, each transect was walked again and all detected scats recovered and counted. A scat deposition rate index of coyote abundance was calculated for each sampling period in terms of the number of scats deposited per mile per day. A similar procedure was employed on the INEEL site where 100 scat deposition transects were used each September from 1976 until 1984. Spring scat deposition rate indices for coyotes were added to study protocols for both study sites in 1980. In 1985 and 1986, the number of scat deposition transects on INEEL were reduced to 25 in the northeast portion of the site.
We also used coyote visitations to artificial scent stations (Linhart and Knowlton 1975, Roughton and Sweeny 1982) as an index of coyote abundance. These consisted of a series of 4.3- km (2.7-mile) routes along tertiary trails and dirt roads. Artificial scent stations, with a 1 m diameter tracking surface and utilizing a FAS attractant (Roughton 1982), were placed at 0.48 km (0.3 mi) intervals on alternate sides of the route. There were 10 scent stations per survey line and each was operated for 1 night. On the CV site, we used 24 scent station survey lines totaling 240 scent stations between 1973 and 1986. On the INEEL site, 49 scent station lines contributed to the spring and fall indices between 1975 and 1984. Data were not obtained for spring 1983. In 1985–1986 the index for INEEL was restricted to 18 lines in the northeast section of the study area. We calculated a mean index value for all lines on each site to provide a single scent station index value for each sampling period and site.
To create a single index of relative coyote abundance for each spring and fall period, results from each of the 4 techniques were normalized with a common mean and averaged with equal weighting, whenever multiple techniques were acquired during a single sampling period (Stoddart 1987a and 1987b).
Research Methods: See above.
CLASS III. DATA SET STATUS AND ACCESSIBILITY
A.Status
Latest Update: 1993
Latest Archive date: 1993
Metadata status:
Data verification: Initially, double entries of field data were used to detect keying errors. Printed formats (numeric and graphic) were then visually inspected to identify atypical patterns which were subsequently resolved by back-referencing the original field data forms.B.Accessibility
Storage location and medium: Original data sheets are archived at the National Wildlife Research Center in Fort Collins, Colorado under Project DF-931.07. Summary data files exist on personal computers of R. A. Bartel and F. F. Knowlton in MS Excel format.
Contact person: For original data sheets, contact:
Archivist, National Wildlife Research Center
4101 LaPorte Avenue
Fort Collins, Colorado 80521-2154For electronic data summaries:
R. A. Bartel or F. F. KnowltonCopyright restrictions: None
Proprietary restrictions: None
Costs: Costs of reproduction only.
Authors believe scientific data should be freely available for scientific use.
CLASS IV. DATA STRUCTURAL DESCRIPTORS
A.Data Set File
Identity: Mammal_abundance_indices.txt
Size: 1260 records, not including header row.
Format and Storage mode: Ascii text, tab delimited. No compression schemes used.
Header information: Headers are given here as header name followed by more information such as basic descriptor and range of values.
Alphanumeric attributes:
Special characters/fields: -999 denotes no data collected given appropriate season.
Authentication procedures:
B. Variable definitions
Variable name
Variable definition
Storage
typeRange numeric
valuesMissing
value
codesYear
Year of data collection
Floating point
1962–1993 N/a
Season
Season of data collection, fall or spring
Character
N/a N/a
INEEL Canis
Coyote (Canis latrans) abundance indices for INEEL
Floating point
7.5–137.0 -999
INEEL Lepus
Black-tailed jackrabbit (Lepus californicus) abundance indices for INEEL
Floating point
0–422.0 -999
INEEL Rabbits
Abundance indices for mountain cottontails (Sylvilagus nuttallii), and pygmy rabbits (Brachylagus idahoensis)
Floating point
0–58.0 -999
INEEL Peromyscus
Deer mouse (Peromyscus maniculatus) abundance indices for INEEL
Floating point
4.0–24.1 -999
INEEL Perognathus
Great Basin pocket mouse (Perognathus parvus) abundance indices for INEEL
Floating point
0–0.8 -999
INEEL Dipodomys ordii Ord’s kangaroo rat (Dipodomys ordii) abundance indices for INEEL
Floating point
0.4–7.3 -999
INEEL Tamias
Least chipmunk (Tamias minimus) abundance indices for INEEL
Floating point
0.9–5.7
-999
INEEL Spermophilus
Townsend’s ground squirrel (Spermophilus townsendii) abundance indices for INEEL
Floating point
0.6–4.4 -999
CV Canis
Coyote (Canis latrans) abundance indices for CV
Floating point
0–29.0 -999
CV Lepus
Black-tailed jackrabbit (Lepus californicus) abundance indices for CV
Floating point
0.4–163.8 -999
CV Peromyscus
Deer mouse (Peromyscus maniculatus) abundance indices for CV
Floating point
3.0–36.7 -999
CV Reithrodontomys
Western harvest mouse (Reithrodontomys megalotis) abundance indices for CV
Floating point
0–1.9 -999
CV Onychomys
Northern grasshopper mouse (Onychomys leucogaster) abundance indices for CV
Floating point
0–0.8 -999
CV Perognathus
Great Basin pocket mouse (Perognathus parvus) abundance indices for CV
Floating point
0.1–4.8 -999
CV Dipodomys ordii
Ord’s kangaroo rat (Dipodomys ordii) abundance indices for CV
Floating point
0–5.0 -999
CV Dipodomys microps Chisel-toothed kangaroo rat (Dipodomys microps) abundance indices for CV
Floating point
0–1.4
-999
CV Tamias Least chipmunk (Tamias minimus) abundance indices for CV
Floating point
0.2–2.2 -999
CV Ammospermophilus White-tailed antelope squirrel (Ammospermophilus leucurus) abundance indices for CV
Floating point
0–1.4 -999
Notes: Missing values are indicated by the number “-999”. Fields with missing data indicate seasons when data were not recorded. All the categories are indices and therefore have no applicable units.
CLASS V. SUPPLEMENTAL DESCRIPTORS
A.Data acquisition
Data forms: n/a
Location of completed data forms:
Archives of National Wildlife Research Center
4101 LaPorte Avenue
Fort Collins, Colorado 80521-2154 USAB. Quality assurance/quality control procedures
Data were entered directly from source material into computer files and values were double checked upon entry. Double entries of field data were used to detect keying errors. Printed formats (numeric and graphic) were visually inspected to identify atypical patterns which were subsequently resolved by back-referencing the original field data forms.
C. Related material: n/a
D. Computer programs and data processing algorithms: n/a
E. Archiving: n/a
F. Literature Cited:
Bailey, R. G. 1998. Ecoregions: the ecosystem geography of the oceans and continents. Springer-Verlag, New York, New York, USA.
Booth, M. S. 2001. Effects of Bromus tectorum on nitrogen cycling and water balance in the Great Basin ecosystem: implications for plant competition and ecosystem function. Dissertation. Utah State University, Logan, Utah, USA.
Burnham, K. P., D. R. Anderson, and J. L. Laake. 1980. Estimation of density from line transect sampling of biological populations. Wildlife Monographs 72:1–202.
Carley, C. J., and F. F. Knowlton. 1971. Trapping woodrats: effectiveness of several techniques and differential catch by sex and age. Texas Journal of Science 22:248–251.
Clark, F. W. 1972. The influence of jackrabbit density on coyote population change. Journal of Wildlife Management 36:343–356.
Fautin, R. W. 1946. Biotic communities of the northern desertt shrub biome in western Utah. Ecological Monographs 16:253–307.
Gross, J. W., L. C. Stoddart, and F. H. Wagner. 1974. Demographic analysis of a northern Utah jackrabbit population. Wildlife Monographs No. 40:1–68.
Harniss, R. O., and N. E. West. 1973. Vegetation patterns of the National Reactor Testing Station, southeastern Idaho. Northwest Science 47:30–43.
Hoffman, S. W. 1979. Coyote-prey relationships in Curlew Valley during a period of low jackrabbit density. Thesis. Utah State University, Logan, Utah, USA.
Knowlton, F. F. 1984. Feasibility of assessing coyote abundance on small areas. Unpublished report of Work Unit 909:01, Denver Wildlife Research Center, Denver, Colorado, USA.
Knowlton, F. F., and L. C. Stoddart. 1992. Some observations from two coyote-prey studies. Pages 101–121 in A. Boer, editor, Ecology and management of the eastern coyote. Wildlife Research Unit, University of New Brunswick, Fredericton, New Brunswick, Canada.
Linhart, S. B., and F. F. Knowlton. 1975. Determining the relative abundance of coyotes by scent station use. Wildlife Society Bulletin 3:119–124.
McBride, R., N.R. French, A. H. Dahl, and J.E. Detmer. 1978. Vegetation types and surface soils of the Idaho National Engineering Laboratory Site. IDO-12084. National Technical Information Service, Springfield Virginia, USA.
Mills, L. S. 1987. Coyote space use in relation to prey abundance. Thesis. Utah State University, Logan, Utah, USA.
Mills, L. S., and F. F. Knowlton. 1991. Coyote space use in relation to prey abundance. Canadian Journal of Zoology 69:1516–1521.
Roughton, R. D. 1982. A synthetic alternative to fermented egg as a canid attractant. Journal of Wildlife Management 46:230–234.
Roughton, R. D., and M. W. Sweeny. 1982. Refinements in scent-station methodology for assessing trends in carnivore populations. Journal of Wildlife Management 46:217–229.
Stoddart, L. C. 1987a. Relative abundance of coyotes, jackrabbits, and rodents in Curlew Valley, Utah. Final Report Project DF-931.07, Predator Ecology and Behavior Project, Denver Wildlife Research Center, USDA/APHIS/ADC. Logan, Utah, USA.
Stoddart, L. C. 1987b. Relative abundance of coyotes, lagomorphs, and rodents in on the Idaho National Engineering Laboratory. Final Report Project DF-931.07, Predator Ecology and Behavior Project, Denver Wildlife Research Center, USDA/APHIS/ADC. Logan, Utah, USA.
Wywialowski, A. P., and L. C. Stoddart. 1988. Estimation of jack rabbit density: methodology makes a difference. Journal of Wildlife Management 52:57–59.
Publications citing the data set: These data have been cited in three publications:
Bartel, R. A. 2003. Functional and numerical responses of coyotes, Canis latrans, to fluctuating prey abundance in the Curlew Valley, Utah, 1963–1993. Thesis. Utah State University, Logan, Utah, USA.
Bartel, R. A., and F. F. Knowlton. 2005. Functional feeding responses of coyotes, Canis latrans, to fluctuating prey abundance in the Curlew Valley, Utah, 1977-1993. Canadian Journal of Zoology 83:569–578.
Bartel, R. A., F. F. Knowlton, and L. C. Stoddart. Submitted. Patterns in mammal abundance in northern portions of the Great Basin. Journal of Mammalogy.
G.History of data set usage
Data request history: A number of people have participated in the collection and use of portions of these data. Following is a list of related publications using the dataset:
Bartel, R. A. 2003. Functional and numerical responses of coyotes, Canis latrans, to fluctuating prey abundance in the Curlew Valley, Utah, 1963–1993. Thesis. Utah State University, Logan, Utah, USA.
Clark, F. W. 1972. The influence of jackrabbit density on coyote population change. Journal of Wildlife Management 36:343–356.
Clark, W. R. 1979. Population limitation of jackrabbits: an examination of the food hypothesis. Dissertation, Utah State University, Logan, Utah, USA.
Clark, W. R., and G. S. Innis. 1982. Forage interactions and black-tailed jackrabbit population dynamics: a simulation model. Journal of Wildlife Management 46:10188–1035.
Davison, R. P. 1980. The effect of exploitation on some parameters of coyote populations. Dissertation. Utah State University, Logan, Utah. USA.
Gross, J. E. 1967. Demographic analysis of a northern Utah black-tailed jackrabbit population. Dissertation. Utah State University, Logan, Utah, USA.
Gross, J. W., L. C. Stoddart, and F. H. Wagner. 1974. Demographic analysis of a northern Utah jackrabbit population. Wildlife Monographs No. 40:1–68.
Harniss, R. O., and N. E. West. 1973. Vegetation patterns of the National Reactor Testing Station, southeastern Idaho. Northwest Science 47:30–43.
Hibler, S. J. 1976. Coyote movement patterns with emphasis on home range characteristics. Thesis. Utah State University, Logan, Utah, USA.
Hoffman, S. W. 1979. Coyote-prey relationships in Curlew Valley during a period of low jackrabbit density. Thesis. Utah State University, Logan, Utah, USA.
Johnson, M. K. 1978. Food habits of coyotes in southcentral Idaho. Dissertation. Colorado State University, Fort Collins, Colorado, USA.
Johnson, M. K., and R. M. Hansen. 1979. Coyote food habits on the Idaho National Engineering Laboratory. Journal of Wildlife Management 43:951–956.
Kitts, J. R. 1970. The annual demography of a population of antelope ground squirrels in Curlew Valley, Utah. Thesis. Utah State University, Logan, Utah, USA.
Knowlton, F. F., and L. C. Stoddart. 1992. Some observations from two coyote-prey studies. Pages 101–121 in A. Boer, editor, Ecology and management of the eastern coyote. Wildlife Research Unit, University of New Brunswick, Fredericton, New Brunswick, Canada.
Knudsen, J. J. 1976. Demographic analysis of a Utah-Idaho coyote population. Thesis. Utah State University, Logan, Utah, USA.
MacCracken, J. G., and R. M. Hansen. 1987. Coyote feeding strategies in southeastern Idaho: Optimal foraging by an opportunistic predator: Journal of Wildlife Management. 51:278–285.
Mills, L. S. 1987. Coyote space use in relation to prey abundance. Thesis. Utah State University, Logan, Utah, USA.
Mills, L. S., and F. F. Knowlton. 1991. Coyote space use in relation to prey abundance. Canadian Journal of Zoology 69:1516–1521.
Nelson, L. 1970. Effects of sublethal, cerebral X-irradiation on movement and home-range patterns of black-tailed jackrabbits. Thesis. Utah State University;, Logan, Utah, USA.
Rice, B., and M. Westoby. 1978. Vegetative responses of some Great Basin shrub communities protected against jackrabbits and or domestic stock. Journal of Range Management 31:28–34.
Rusch, D. 1965. Some movements of black-tailed jackrabbits in northern Utah. Thesis, Utah State University, Logan, Utah, USA.
Smith, G. W. 1987. Mortality and movement within a black-tailed jackrabbit population. Dissertation. Utah State University, Logan, Utah, USA.
Smith, G. W. 1990. Home-range and activity patterns of black-tailed jackrabbits. Great Basin Naturalist 50:249–256.
Stoddart, L. C. 1972. Population biology of the black-tailed jackrabbit in northern Utah. Dissertation. Utah State University, Logan, Utah, USA.
Stoddart, L. C. 1978. Population dynamics, movement and home range of black-tailed jackrabbits (Lepus californicus) in Curlew Valley, northern Utah. Final Report, U. S. Department of Energy, Contract No. E-11-1-1329.
Stoddart. L. C. 1985. Severe weather related mortality of black-tailed jack rabbits. Journal of Wildlife Management 49:696–698.
Stoddart, L. C. 1987a. Relative abundance of coyotes, jackrabbits, and rodents in CurlewValley, Utah. Final Report Project DF-931.07, Predator Ecology and Behavior Project, Denver Wildlife Research Center, USDA/APHIS/ADC. Logan, Utah, USA.
Stoddart, L. C. 1987b. Relative abundance of coyotes, lagomorphs, and rodents in on the Idaho National Engineering Laboratory. Final Report Project DF-931.07, Predator Ecology and Behavior Project, Denver Wildlife Research Center, USDA/APHIS/ADC. Logan, Utah, USA.
Stoddart, L. C., R. E. Griffiths, and F. F. Knowlton. 2001. Coyote responses to changing jackrabbit abundance affect sheep predation. Journal of Range Management 54:15–20.
Wagner, F. H. 1981. The role of lagomorphs in ecosystems. Pages 668–694 in K. Myers and C. D. MacInnes, editors, Proceedings of the World Lagomorph Conference, Aukust 12–16, 1979. University Guelph Press, Guelp, Ontario, Canada.
Wagner, F. H., and L. C. Stoddart. 1972. Influence of coyote predation on black-tailed jackrabbit populations in Utah. Journal of Wildlife Management 36:329–342.
Wywialowski, A. P., and L. C. Stoddart. 1988. Estimation of jack rabbit density: methodology makes a difference. Journal of Wildlife Management 52:57–59.
H. Data set update history:
Review history:
Questions and comments from secondary users:
ACKNOWLEDGMENTS
Fred Wagner and a bevy of his graduate advisees undertook the initial phases of data collection. In 1972-1973, the effort continued under the auspices of the Denver Wildlife Research Center of the U. S. Fish and Wildlife Service under Study Plans DF-931.07 and DF-931.09 and subsequently under the National Wildlife Research Center after it was administratively transferred to the U. S. Department of Agriculture in 1986. Financial support for this endeavor came variously from the U. S. Fish and Wildlife Service within the U. S. Department of the Interior, the Animal and Plant Health Inspection Service of the U. S. Department of Agriculture, the U. S. Atomic Energy Commission under Contract No. AT (11-1)-1329, and the U. S. Department of Energy under Interagency Agreement No. DE-AI07-81ID12315. We are indebted to a myriad of technicians and graduate students for endless hours of field inventories, sometimes under arduous and unpleasant conditions, which made the compilation of these data sets possible. While we readily acknowledge contributions by individuals like R. J. Burns, S. Cherry, F. Clark, M. Collinge, V. Cross, S. Fortier, R. E. Griffiths, C. E. Harris, S. W. Hoffman, B. Jones, B. T. Kelly, J. J. Knudsen, A. J. Kriwox, L. S. Mills, K. Rose, R. D. Roughton, W. C. Stephenson, G. W. Smith, M. W. Sweeny, S. Whittemore, and A. Wywialowski, there are numerous others unnamed who also contributed to the effort. Our sincere apologies for anyone overlooked.
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