U.S. Department of the Interior

U.S. Geological Survey

Data Series 759

Alaska Geochemical Database Version 2.0 

(AGDB2)—Including “Best Value” Data 

Compilations for Rock, Sediment, Soil, 

Mineral, and Concentrate Sample Media
Cover art: “Late summer at Denali©” Watercolor in pen and ink, by Daniel Granitto, 2013. Used with permission.
Alaska Geochemical Database Version 2.0 

(AGDB2)—Including “Best Value” Data 

Compilations for Rock, Sediment, Soil, 

Mineral, and Concentrate Sample Media

By Matthew Granitto, Jeanine M. Schmidt, Nora B. Shew, Bruce M. Gamble, 

and Keith A. Labay

Data Series 759

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2013

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

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Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Granitto, Matthew, Schmidt, J.M., Shew, N.B., Gamble, B.M., and Labay, K.A., 2013, Alaska Geochemical Database, 

Version 2.0 (AGDB2)—including “best value” data compilations for rock, sediment, soil, mineral, and concentrate 

sample media: U.S. Geological Survey Data Series 759, 20 p. 1 DVD, http://pubs.usgs.gov/ds/759.
iii

Contents

List of Acronyms.............................................................................................................................................v

Useful websites.............................................................................................................................................vi

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Geographic Setting........................................................................................................................................2

Methods of Study...........................................................................................................................................2

Sample Media and Collection.............................................................................................................2

Analytical Techniques..........................................................................................................................4

Quality Assurance/Quality Control.....................................................................................................4

“Best Value” Concept...................................................................................................................................4

Determining “Best Value” Rankings..................................................................................................4

Sample Weight.............................................................................................................................4

Sample Decomposition...............................................................................................................5

Analytical Instrumentation.........................................................................................................5

Limits of Detection.......................................................................................................................5

Review of Analytical Methods............................................................................................................5

“Best Value” Ranking Tables..............................................................................................................6

Characteristics of the Relational Database ..............................................................................................6

Contents..................................................................................................................................................6

Structure.................................................................................................................................................6

Other Data Formats.............................................................................................................................10

“Best Value” Data Population ...................................................................................................................10

Detected Values..................................................................................................................................11

Non-detected Values .........................................................................................................................11

Acknowledgments.......................................................................................................................................12

References....................................................................................................................................................12

Database References ........................................................................................................................12

References Cited.................................................................................................................................12

Appendix 1.....................................................................................................................................................14

Analytical Methods.............................................................................................................................14

Appendix 2.....................................................................................................................................................17

Mineral Name Abbreviations............................................................................................................17

Appendix 3.....................................................................................................................................................19

Mineralogical Data References .......................................................................................................19

Figures

1. Geographic area covered by Alaska Geochemical Database Version 2.0 .........................3

2. Table relationships in the Alaska Geochemical Database Version 2.0................................8

3. “Best value” analytical method ranking table for silver used in the Alaska

Geochemical Database Version 2.0.........................................................................................11
iv

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft.) 0.3048 meter (m)

SI to Inch/Pound

Multiply By To obtain

Volume

liter (L) 0.2642 gallon (gal)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz.)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) or micrograms per liter (μg/L).

Tables

1. Tables of Alaska Geochemical Database Version 2.0 ............................................................7

2. List of spreadsheets containing data from Alaska Geochemical Database 

Version 2.0....................................................................................................................................10

A1. Analytical methods.....................................................................................................................14

A2. Mineral name abbreviations.....................................................................................................17
v

List of Acronyms

AA atomic absorption spectrometry

AGDB Alaska Geochemical Database (USGS Data Series 637)

AGDB2 Alaska Geochemical Database Version 2.0

AES inductively coupled plasma-atomic emission spectrometry

AMRAP Alaska Minerals Resource Assessment Program

CM colorimetric spectrophotometry

DCP direct-current plasma atomic emission spectrometry

EDX energy dispersive X-ray fluorescence spectrometry

ES direct current-arc emission spectrography

FA fire assay

HSSR Hydrogeochemical and Stream Sediment Reconnaissance

LIMS Laboratory Information Management System

LLD lower limit of determination

MDIRA Minerals Data Information Rescue in Alaska

MS inductively coupled plasma-mass spectrometry

NA instrumental neutron activation analysis

NGDB National Geochemical Database

NURE Atomic Energy Commission National Uranium Resource Evaluation

PLUTO in-house USGS geochemistry database used from mid-1970s through the mid-1990s

RASS USGS Rock Analysis Storage System

REE rare-earth elements

USGS U.S. Geological Survey

WDX wavelength dispersive X-ray fluorescence spectrometry

XRF X-ray fluorescence spectrometry
vi

Useful websites:

USGS main webpage.......................................................................................................................................

http://www.usgs.gov/

USGS publications search page ...................................................................................................................

http://pubs.er.usgs.gov/

USGS Alaska Science Center........................................................................................................................

http://alaska.usgs.gov/

USGS Mineral Resources On-line Spatial Data..........................................................................................

http://mrdata.usgs.gov/

USGS Open-File Report 99-433, Rock Analysis Storage System (RASS)................................................

http://pubs.usgs.gov/of/1999/of99-433/

USGS Open-File Report 97-492, National Geochemical Database (NURE, HSSR)................................

http://pubs.usgs.gov/of/1997/ofr-97-0492/

USGS Data Series 637, Alaska Geochemical Database (AGDB) .............................................................

http://pubs.usgs.gov/ds/637/

Alaska Department of Natural Resources...................................................................................................

http://dnr.alaska.gov/
Abstract

The Alaska Geochemical Database Version 2.0 (AGDB2) 

contains new geochemical data compilations in which each 

geologic material sample has one “best value” determination for each analyzed species, greatly improving speed and 

efficiency of use. Like the Alaska Geochemical Database 

(AGDB) before it, the AGDB2 was created and designed to 

compile and integrate geochemical data from Alaska in order 

to facilitate geologic mapping, petrologic studies, mineral 

resource assessments, definition of geochemical baseline 

values and statistics, environmental impact assessments, and 

studies in medical geology. This relational database, created 

from the AGDB that was released in 2011, serves as a data 

archive in support of present and future Alaskan geologic 

and geochemical projects, and contains data tables in several 

different formats describing historical and new quantitative 

and qualitative geochemical analyses. The analytical results 

were determined by 85 laboratory and field analytical methods 

on 264,095 rock, sediment, soil, mineral and heavy-mineral 

concentrate samples. Most samples were collected by U.S. 

Geological Survey (USGS) personnel and analyzed in USGS 

laboratories or, under contracts, in commercial analytical laboratories. These data represent analyses of samples collected 

as part of various USGS programs and projects from 1962 

through 2009. In addition, mineralogical data from 18,138 

nonmagnetic heavy-mineral concentrate samples are included 

in this database. The AGDB2 includes historical geochemical 

data originally archived in the USGS Rock Analysis Storage 

System database, used from the mid-1960s through the late 

1980s and the USGS PLUTO database used from the mid1970s through the mid-1990s. All of these data are currently 

maintained in the National Geochemical Database (NGDB). 

Retrievals from the NGDB were used to generate most of the 

AGDB data set. These data were checked for accuracy regarding sample location, sample media type, and analytical methods used. This arduous process of reviewing, verifying and, 

where necessary, editing all USGS geochemical data resulted 

in a significantly improved Alaska geochemical dataset. USGS 

data that were not previously in the NGDB because the data 

predate the earliest USGS geochemical databases, or were 

once excluded for programmatic reasons, are included here 

in the AGDB2 and will be added to the NGDB. The AGDB2 

data provided here are the most accurate and complete to date, 

and should be useful for a wide variety of geochemical studies. The AGDB2 data provided in the linked database may be 

updated or changed periodically.

Introduction

The U.S. Geological Survey (USGS) began scientific 

investigations in Alaska in 1889, shortly after its purchase 

from the Russian Empire in 1867, but much Alaskan scientific 

data had not always been readily accessible to the public. The 

USGS participated in the Congressionally-funded, multiagency Minerals Data Information Rescue in Alaska (MDIRA) 

Program from 1997 to 2003 in order to make its Alaska scientific data digital, correct, user-friendly, and accessible. The 

MDIRA program and subsequent efforts resulted in release of 

the Alaska Geochemical Database (Granitto and others, 2011; 

Granitto and others, 2012). The Alaska Geochemical Database 

(AGDB) provided comprehensive data on the analytical chemistry, mineralogy, and characteristics of geologic materials 

collected in Alaska from 1962‒2009. Because of the complexity and diversity of the data, the Alaska Geochemical Database 

Alaska Geochemical Database Version 2.0 (AGDB2)—

Including “Best Value” Data Compilations for Rock, 

Sediment, Soil, Mineral, and Concentrate Sample Media

By Matthew Granitto, Jeanine M. Schmidt, Nora B. Shew, Bruce M. Gamble, and Keith A. Labay
2 Alaska Geochemical Database Version 2.0 (AGDB2)

Version 2.0 (AGDB2) presented here contains new geochemical data compilations in which each geologic material sample 

has one “best value” determination for each analyzed species, 

greatly improving speed and efficiency of use.

The AGDB2 includes analyses of rocks, sediments 

(collected from streams, lakes, and various sources), soils, 

minerals, and heavy-mineral concentrates (derived from 

stream sediments, soils or rocks) compiled in part during 

the MDIRA process (Bailey and others, 1999), together 

with analyses of a variety of geologic materials from 1996 

through 2010. Many of the analyses were the result of mineral resource investigations conducted by the Alaska Mineral 

Resource Assessment Program (AMRAP) in the mid-1970s 

through early 1990s; some of the data were produced in 

support of other USGS programs such as National Geologic 

Mapping, Volcano Hazards, Development of Assessment 

Techniques, and Energy Resources.

Most of these data were originally entered into the USGS 

Rock Analysis Storage System (RASS) or PLUTO databases. 

The RASS database, which contained over 730,000 data 

records, was used by the USGS Geologic Division from the 

late 1960s through the late 1980s to archive geochemical data 

produced by the Branch of Exploration Services primarily 

from mineral resource studies. The PLUTO database, which 

contained over 530,000 data records, was used by the USGS 

Geologic Division from the late 1960s through 1997 to archive 

geochemical data from the Branch of Analytical Chemistry 

and successor branches. More recent geochemical data are 

presently stored in the commercial Laboratory Information 

Management System (LIMS) database (1996 to present). Data 

from these databases have been merged and are maintained 

in the Oracle-based National Geochemical Database (NGDB; 

available at http://mrdata.usgs.gov/) which currently contains 

nearly 2 million data records. Many of these determinations 

have been previously published in hardcopy or digital USGS 

Open-File Reports by the original sample submitters or analysts; however, some have never before been published.

These data were generated over a span of nearly 50 

years from 1962 to 2010 in USGS laboratories or, under contracts, in commercial analytical laboratories. Upon completion of the sampling and analysis, data for the original RASS 

and PLUTO databases were keypunched for digital storage. 

Automated data entry from a LIMS was begun in the late 

1980’s in the PLUTO database. Over the years, USGS scientists recognized several problems with the databases. Three 

primary issues were: (1) erroneous or missing sample locality coordinates, (2) sample media were often not adequately 

identified, and (3) analytical methods were poorly identified 

(often missing from the early PLUTO database structure). 

Beginning in 1998, a major review of Alaska samples from 

these databases was initiated to confirm sample and lab numbers for analyses, correct errors in sample site locations, add 

sample site locations when missing, and to correctly identify 

the sample media and analytical protocols for each record. 

This re-processing consisted of comparing the recorded digital information to the information found in original sample 

submittal forms, the original analytical reports, published 

reports, field notebooks and field sheets (sample locality 

maps), and follow-up discussions with submitters and analysts (when available). As necessary, additional data fields 

were added to the database structure to more fully describe 

sample preparation methods and sample media. Geochemical 

datasets that were not entered in RASS and PLUTO during 

the re-processing have been incorporated into the AGDB2 

database, resulting in the addition of thousands of sample 

data records to the NGDB. The RASS and PLUTO analytical data were not checked in great detail, but obvious errors 

were corrected. Discussion of these corrections and additions 

is found in Appendix 3 of Granitto and others, 2011.

The AGDB2 is the most current, complete, and accurate 

data compilation for new and historical geochemical analyses 

of rock, sediment, soil, and concentrate samples. The AGDB2 

also contains mineralogical information from optical examination of the nonmagnetic fractions of heavy-mineral concentrate samples. In addition, geochemical data from reanalyses 

of sediment samples collected under the Atomic Energy 

Commission National Uranium Resource Evaluation (NURE) 

Hydrogeochemical and Stream Sediment Reconnaissance 

(HSSR) program (henceforth called NURE), and reanalyses 

(2007–2009) of AMRAP sediment samples from the Alaska 

Range have been included in the AGDB2. Data from other 

recent projects in Taylor Mountains Quadrangle, southwestern 

Alaska, Fortymile district, and statewide Surveys and Analysis 

are also included in the AGDB2.

Geographic Setting

The geographic boundaries of the AGDB2 include all 

of Alaska as well as Federal and International waters of the 

Arctic and Pacific Oceans that are reasonable for inclusion. 

The current AGDB data extents are 71.6000°N. latitude, 

50.1834°N. latitude, 129.9939°W. longitude, and 173.1°E. 

longitude (fig. 1). 

Methods of Study

Sample Media and Collection

Analyses of 108,966 rock samples, 92,694 sediment samples, 6,869 soil samples, 7,470 mineral samples, and 48,096 

heavy-mineral concentrate samples are incorporated into the 

AGDB2. Samples in the AGDB2 were collected between 

1962 and 2009 and prepared according to a variety of USGS 

standard methods (variously described in Arbogast, 1990, 

1996; Miesch, 1976; Taggart, 2002) or by NURE methods 

(described in Smith, 1997). The database includes analyses of 

1,589 stream-sediment samples, originally collected during 

the USGS Heavy Metals and AMRAP programs (1966–1995), 

and reanalyzed during 2007–2010 by the Federal Lands in 
Figure 1. Geographic area covered by Alaska Geochemical Database Version 2.0. The state of Alaska is in the center of the map. Gray rec

1:250,000 topographic quadrangle outlines. The red dots are sediment, soil, and heavy-mineral concentrate sample localities. The blue dots amineral sample localities.
4 Alaska Geochemical Database Version 2.0 (AGDB2)

Alaska-Geologic Studies project (Bailey and others, 2010; 

Gamble and others, 2010); analyses of 3,015 rock, sediment, 

soil, mineral, and concentrate samples collected during the 

2004–2010 Taylor Mountains quadrangle project (Bailey and 

others, 2007; Klimasauskas and others, 2007; Klimasauskas, 

Miller, Bradley, Bundtzen and others, 2006; Klimasauskas, 

Miller, Bradley, Karl and others, 2006); data from 6,686 

NURE sediment samples that were reanalyzed, including, 

in part, 4,804 for the National Geochemical Survey project between 1998–2008 (U.S. Geological Survey, 2004) 

and 1,640 for AMRAP projects; and analyses of 536 rock, 

sediment, and soil samples collected during the 2007–2009 

Concealed Deposits—Pebble Cu-Au-Mo porphyry deposit 

project (Anderson and others, 2011; Fey and others, 2009, 

2008). Existing NGDB data from Alaskan water, leachate, 

and organic samples (including humus and peat) have been 

excluded from this database but are planned to be compiled, 

verified, and included in a later version of the AGDB. 

Analytical Techniques

Eighty-five different field and laboratory analytical 

methods were used to produce geochemical data included in 

the AGDB2. These methods reflect the evolution of analytical 

chemistry from 1960 to 2009. Appendix 1 provides a complete 

list of the analytical methods included in the AGDB2 and 

descriptive information for each. The AnalyticMethod table 

in the AGDB2 provides detailed information about techniques 

and the AnalyticMethodBiblio table contains citations for the 

analytical methods.

Quality Assurance/Quality Control

Quality assurance and quality control (QA/QC) procedures varied over the time of AGDB2 sample processing and 

analysis, and are not included in this database. Data from field 

sample-site duplicates and analytical replicates (splits of a 

single sample to check laboratory precision) are included in 

the database. USGS and contract laboratories reporting these 

analyses use constituent standards (for example, USGS geochemical reference rock standard STM–1, nepheline syenite) 

and blanks for their internal QA/QC controls (Arbogast, 1990; 

Taggart, 2002). Data for commonly used reference samples are 

described at (http://minerals.cr.usgs.gov/geo_chem_stand/).

“Best Value” Concept

The comprehensive nature of the first AGDB (Granitto and 

others, 2011) meant that it included as many as four separate 

values for a given element, where samples were analyzed by 

multiple analytical methods. The AGDB contained 7,346,935 

cases where there is only one determination of a given species 

(element) for a given sample record; 1,086,397 cases with two 

determinations; 54,761 cases with three determinations; and 

3,998 matches where there are four different determinations of 

a given species for a given sample record. Species that have the 

most multiple determination matches are Ag, As, Au, Bi, Cd, 

Cu, Mo, Pb, Sb, and Zn. While these comprehensive data are 

complete, for many users such multiple analyses raise difficult 

questions of which value to use in their work. 

This Alaska Geochemical Database Version 2.0 

(AGDB2) includes a subset of data that represents one “best 

value” per species for each of its samples. Where used in this 

report, the term “best value” means that single value per element per sample chosen by the rubric and reasoning described 

below. This rubric was designed to provide the best values for 

mineral exploration and assessment purposes and should not 

be assumed to be appropriate for other purposes (for example, 

evaluation of environmental background and baseline geochemical values would require development of a different 

“best value” ranking). The best values subset greatly reduces 

the total number of determinations a user must consider for a 

given sample, and facilitates use of the AGDB for geochemical mapping, data synthesis, and regional evaluation in Alaska.

Determining “Best Value” Rankings

Different analytical determinations of the same element 

for any given sample do not have equal value to a user for different purposes. Some analytical methods result in values that 

are more quantitative, precise, or accurate than others. When 

developing a ranking of methods best for any particular use it 

is necessary to take into account factors which vary between 

analytical methods. These include weight of sample analyzed, 

method of decomposition of the sample during the preparation 

for analysis, sensitivity and accuracy of the instrument used in 

each method, upper and lower limits of detection for a given 

element by a given method, the age of the method and stage 

of its development when a specific analysis was performed, 

and the exact analytical laboratory and equipment used. 

Creation of the AGDB2 “best value” subset followed a rubric 

or decision tree that considered all these factors in ranking the 

analytical methods in the AGDB2 to determine methods most 

useful to mineral resource evaluation.

Sample Weight

The amount of sample required for analysis varies widely 

between methods. On the high end, 15 to 30 grams (g) of sample are needed to determine gold or the platinum group elements 

by fire assay (FA) methods, and 10 to 15 g for the detection of 

Au by atomic absorption spectrometry (AA) or direct-current 

plasma (DCP). On the low end, only 10 milligrams (mg) of 

sample are needed for direct-current arc emission spectrography 

(ES), a method that was used to detect concentrations of 33 to 

65 elements. In general, larger sample aliquots provide a more 

accurate assessment of a sample’s chemical makeup, so determinations by ES, for example, are less quantitative than those 

by analytical methods that require larger sample amounts.
“Best Value” Concept 5

Sample Decomposition

The methods used to decompose a geologic sample to 

be analyzed vary by material (for example, rock vs. soil) 

and effectiveness, and are an important factor to consider 

in determining “best” methods. In general, methods which 

digest or dissolve a sample vary from near total (“complete”) 

to partial decomposition of a sample. The AGDB2 does not 

include results from any analytical methods that use passive 

or weak leaches of geologic material samples. Decomposition 

methods that result in complete or near complete digestion 

are herein referred to as “total.” Instrumental neutron activation analysis (NA) and energy dispersive X-ray fluorescence 

spectrometry (EDX), which comprises 3.3 percent of AGDB2 

analyses, are non-destructive techniques that analyze the 

entire sample without requiring digestion, and thus usually 

represent the best total decomposition of the sample. Wavelength dispersive X-ray fluorescence spectrometry (WDX), 

inductively coupled plasma-atomic emission spectrometry 

(AES), inductively coupled plasma-mass spectrometry (MS), 

atomic absorption (AA), and colorimetric spectrophotometry (CM), which comprise 5.2 percent of AGDB2 analyses, 

employ various highly effective fusion or sinter digestions 

that yield near “total” analyses of the elements of interest, 

but may drive off volatile elements such as As, Hg, S, Sb, or 

Te in the process. AES, MS, AA, and CM may also employ 

strong acid digestions that provide for virtually complete 

decomposition. A common “total” acid digestion technique 

using a four-acid solution (HF, HClO4

, HNO3, and HCl) 

is sufficient for many elements of interest, but may not be 

effective in putting Ba, Cr, Hf, Nb, Sc, Sn, Ta, Ti, W, Zr, 

and rare-earth elements (REEs) into solution. Decomposition techniques that employ HF account for 10.9 percent of 

AGDB2 analyses. Partial-digestion acid solution methods 

and partial fusion methods (9.5 percent of AGDB2 analyses) 

are moderately effective for some elements but ineffective 

for others. Most analytical methods are designed for the 

detection of one or a specific suite of elements and employ 

decomposition techniques suitable for those elements at the 

expense of accurate determinations of other elements.

Analytical Instrumentation

The sensitivity and reliability of individual analytic 

instruments is another factor which affects the method’s 

ranking in the “best values” rubric. The instruments most 

commonly used for analysis of Alaskan samples are: (1) ES, 

69.1 percent of the determinations, (2) AES, 14.7 percent, (3) 

AA, 6.3 percent, (4) XRF (X-ray fluorescence spectrometry), 

3 percent, (5) MS, 2.9 percent, and (6) NA, 2.3 percent. For 

the determination of most elemental concentrations, NA, 

AES, MS, and XRF are more sensitive and more quantitative 

than ES which was usually employed as a semi-quantitative 

method of determination. In general, newer models of 

instruments are more sensitive than older ones. For some 

instruments, spectral interferences, background shifts, matrix 

effects, and mineralogical and other structural effects cause 

some element determinations to be less accurate than others. 

Analytical methods that use WDX spectrometers have developed modifications in sample decomposition, or correction 

factors that yield more accurate chemical determinations 

(Taggart and others, 1987).

Limits of Detection

The lower limit of determination (LLD) is the lowest 

quantity of a substance that can be distinguished from the 

absence of that substance within a stated confidence limit 

(Taggart, 2002). As an analytical method becomes more 

sensitive and can detect lower elemental concentrations, 

its LLD moves lower. One analytical method may have 

multiple LLDs for a single element in the database due to 

preconcentration or dilution of a specific sample, improved 

sensitivity as newer models of instruments are used, varying 

dates of analysis for the same method, or different analytical 

laboratories using varying procedures for the same analytical method. The presence of interfering elements also can 

affect the LLD. Upper limits of detection are the highest 

quantity of an analyte that can be determined within a stated 

confidence limit without further dilution of the digestate. The 

methods and procedures of USGS laboratories and USGScontracted laboratories reported in AGDB2 are comparable, 

since contract laboratories are held to USGS quality assurance and quality control standards.

Review of Analytical Methods

A thorough understanding of all USGS analytical protocols used over the past 50 years was crucial in verifying the 

chemical analytical data in the AGDB. From 1998 through 

2010, analytical method publications from the 1950’s to the 

present were compiled (see table AnalyticMethodBiblio in 

the AGDB2), and chemists knowledgeable in various methods were frequently queried through phone calls, emails, and 

personal visits. These efforts were continued when developing the AGDB2 in order to capture the details of analytical 

methods to rank methods on an element by element basis. In 

December 2011, USGS emeritus chemists James G. Crock, 

Paul J. Lamothe, and Richard M. O’Leary, representing more 

than 110 cumulative years of USGS operational and research 

chemistry (1970 through 2012) along with senior author 

Matthew Granitto, systematically ranked all the AGDB species and elements by the quality of the analytical methods 

used. This ranking has since been refined and contributed 

significantly to the creation of the AGDB2 “best values” subset. Other chemists who have contributed to AGDB efforts 

over the past 14 years are Philip A. Baedecker, William M. 

Benzel, Zoe Ann Brown, James R. Budahn, Robert R. Carlson, LaDonna M. Choate, Anthony F. Dorrzapf, Michael W. 

Doughten, David L. Fey, Philip L. Hageman, Larry L. Jackson, Allen L. Meier, Stephen J. Sutley, Joseph E. Taggart, Jr., 

and Stephen A. Wilson.
6 Alaska Geochemical Database Version 2.0 (AGDB2)

“Best Value” Ranking Tables

The review of analytical methods discussed above 

resulted in a series of tables (BestValue_Rank.xlsx) which 

rank, from best to least preferred, the analytical methods 

that produced the “best values” for each element within the 

AGDB2. The ranking for each element contains two subsets—methods that employ “total” decomposition techniques 

(for example, rated as “01”) are listed above, and separate 

from methods that use partial decomposition techniques (for 

example, “P01”). The method ranking tables are compiled in 

the AGDB2 as the table Parameter_Rank, and as the Excel 

spreadsheet Parameter_Rank.xlsx.

The method ranking tables for each element contain the 

same field names (column headers). SPECIES is the chemical entity for which samples have been analyzed. PARAMETER is a concatenation of the fields SPECIES, UNITS, 

TECHNIQUE, DIGESTION, and sometimes DECOMPOSITION from the AGDB2. ANALYTIC_METHOD contains the 

short name of the analytical method as used in the AGDB. 

BESTVALUE_RANK is the numeric ranking of the analytical 

methods used in the determination of each species. NONDETECT_RANGE contains the range of non-detect values 

for the analytical method. Wherever the species concentration is lower than the LLDs of the method used, yielding 

a negative value entry in the QUALIFIED_VALUE field of 

the Chem2 table in the AGDB2, the NONDETECT_RANGE

value equals the LLD for that method. Non-detect values of 

a method vary due to sample preconcentration or dilution, 

instrumental sensitivity, the laboratory performing analyses, 

or the date of analysis. Non-detect ranges in parentheses 

represent approximately 90 percent of the non-detects in 

the AGDB2 for that analytical method species combination. Non-detect ranges such as “< 0.28” indicate that no 

non-detects were encountered, and that 0.28 was the lowest 

detected value in the AGDB2 for that particular analytical 

method and species. The field LLD_RANGE is the range of 

LLDs reported in USGS publications or in-house laboratory 

manuals, and does not represent actual analytical determinations in the AGDB2. The entry “na” indicates that no published LLD was found for the analytical method and species. 

NONDETECT_RANK is the ranking of LLD entries in LLD_

RANGE. No distinction is made between methods employing total or partial digestion, and NONDETECT_RANK 

reflects only the sensitivity of the method in recognizing the 

presence of the species. The field RANK_COUNT contains 

the total number of determinations of each species in the 

AGDB2 by the analytical method listed. Further method 

information is available in the field ANALYTIC_METHOD_

DESC of the AnalyticMethod table.

Characteristics of the Relational 

Database

Because of the scope and complexity of the Alaskan geologic materials analyzed, a tabular relational database which 

records both field site and sample observations and laboratory 

analyses was designed for data storage. The AGDB2 was constructed in Microsoft Access 2010 as an archive and a tool to 

be used for data synthesis and analysis. The database structure 

and format are a modification of that used by the National 

Geochemical Database (NGDB) because more than 85 percent 

of the data were originally retrieved from the NGDB (Smith 

and others, 2003).

Contents

The AGDB2 (2.34 gigabytes) comprises two linked databases, AGDB2.accdb and AGDB2_Chem.accdb, to accommodate the Microsoft Access limitation of 2 gigabytes for a single 

database. Data are contained in 12 tables, which are described 

in table 1of this report pamphlet. The six primary database 

tables contain quantitative analytical results, sample data, 

field site information, geologic and mineralogic data. Analytical method information and analytical method bibliography 

core-lookup tables provide references for quantitative results. 

A reference table of field name definitions assists the user in 

understanding the names and content of database fields. In 

this report, names of tables cited are in boldface; field names 

within tables are italicized.

Structure

AGDB2 data are contained in six primary tables, 

Geol2, Chem2, BestValue_Ag_Mo, BestValue_Na_Zr, 

BestValue_WholeRock, and Mnrlgy, and relationships are 

defined to link these tables (fig. 2). This structure provides 

for efficient storage of information and for data verification. 

Relationships between these tables are depicted as lines in 

figure 2. Geol2 is linked to Chem2 by the common field 

(LAB_ID). Therefore, all chemical values have corresponding sample information in Geol2. This is a one-to-many 

relationship; that is, a single sample may have many analytical results (for example, different elements, same element by 

multiple methods, and so forth). Geol2 is also linked to BestValue_Ag_Mo by the common field LAB_ID since chemical 

values cannot exist without corresponding sample information in Geol2. This is a one-to-one relationship; that is, a single sample record in Geol2 has one or more analytical results 
Characteristics of the Relational Database 7

Table 1. Tables of Alaska Geochemical Database Version 2.0.

Table name Type Description Primary key field Fields Records

Geol2 Primary Spatial, geologic, and descriptive attributes for heavy mineral concentrate, mineral, rock, bulk sediment, 

and soil samples

LAB_ID 42 264,095

Chem2 Primary All chemical data compiled for heavy 

mineral concentrate, mineral, rock, 

bulk sediment, and soil samples

CHEM_ID 13 9,699,962

BestValue_Ag_Mo Primary “Best value” chemical data - silver 

through molybdenum - for heavy 

mineral concentrate, mineral, rock, 

bulk sediment, and soil samples

LAB_ID 130 264,095

BestValue_Na_Zr Primary “Best value” chemical data - sodium 

through zirconium - for heavy 

mineral concentrate, mineral, rock, 

bulk sediment, and soil samples

LAB_ID 118 264,095

BestValue_WholeRock Primary “Best value” chemical “whole rock” 

data for heavy mineral concentrate, 

mineral, rock, bulk sediment, and 

soil samples

LAB_ID 145 264,095

Mnrlgy Primary Mineralogy data for non-magnetic 

heavy mineral concentrate samples

LAB_ID 28 18,138

AnalyticMethod Primary-lookup Analytic methods used to obtain 

chemical and physical data

ANALYTIC_METHOD 4 85

AnalyticMethodBiblio Primary-lookup References for analytic methods used 

to obtain chemical data

ANALYTIC_METHOD_PUB_ID 9 753

MnrlName Primary-lookup Mineral name abbreviations used in 

Mnrlgy table

MNRL_ABBRV 2 126

Parameter Primary-lookup Analytical method parameters used to 

obtain chemical and physical data

PARAMETER 3 989

Parameter_Rank Primary-lookup Analytical method parameters ranked 

by species

PARAMETER 11 847

FieldNameDictionary Reference Field name descriptions for all tables 

in the database

FIELD_NAME 5 496

in the chemical data tables. Geol2 is also linked to Mnrlgy

by the common field LAB_ID in a one-to-one relationship; 

that is, every sample with mineralogical data has geospatial 

and sample media data in Geol2. Data may be extracted from 

the AGDB2 to meet specific user needs by constructing userdefined queries.

Relationships between Geol2 and other tables in the 

AGDB2 are shown in figure 2. Geol2 contains 264,095 

records, and has 42 fields describing sample sites and the 

sample material collected at each site. Each analyzed sample 

has a unique LAB_ID, as well as a FIELD_ID provided by 

the sample collector. LAB_ID is a unique identifier assigned 

to each submitted sample by the analytical laboratory that 

received the sample. It is a key field that links the sample 

to its chemical and physical data found in the chemical data 

tables. Dates of sample submission and collection are stored 

in the DATE_SUBMITTED and DATE_COLLECT fields; less 

than 10 percent of samples have a collection date recorded. 

LATITUDE and LONGITUDE contain the geographic coordinates, whose precision is set at 0.00001 degree, although 

in many cases, location information collected by the sampler 

is accurate to only 2 or 3-digit precision by global positioning system (GPS) (Granitto and others, 2011). Associated 

SPHEROID and DATUM information is sometimes provided. 

PRIMARY_CLASS defines the sample material; SECONDARY_CLASS and SPECIFIC_NAME provide more detail about 
8 Alaska Geochemical Database Version 2.0 (AGDB2)

Figure 2. Table relationships in the Alaska Geochemical Database Version 2.0.
Characteristics of the Relational Database 9

the sample medium. Media type should be carefully noted 

so that data from different sample types are not mistakenly 

equated. For example, AGDB2 contains copper analyses for 

multiple subsamples (described in SPECIFIC_NAME) derived 

from one sediment sample site (for example, bulk sediment of 

various size-fractions, and their panned concentrate fractions 

of various magnetic susceptibilities). Information regarding the collection and preparation of the sample are found in 

METHOD_COLLECTED, PREP, and MESH_PORE_SIZE. 

Most of the LAB_ID entries are samples entered in the USGS 

laboratory information management system, archived in the 

NGDB (Smith and others, 2003).

The Chem2 table contains 9,699,962 records in 

13 fields with laboratory and field analytical measurements, 

expressed as numeric values. CHEM_ID is a unique identifier assigned to each measurement in the table and is a key 

field of software-assigned integers. Measurements in Chem2

consist of a numeric DATA_VALUE and an optional QUALIFIER, which is used to describe results such as those that 

were not detectable or that were estimates based on limits of 

instrumental detection (for example, “less than” values, such 

as < 2). QUALIFIER entries include “<” or “N,” meaning 

that the element was not detected at concentrations above the 

lower limit of determination for the method; “L,” meaning 

that the element was detected, but at concentrations below the 

lower limit of determination for the method; and “>” or “G,” 

meaning that the element was measured at a concentration 

greater than the upper limit of determination for the method. 

QUALIFIED_VALUE was populated by combining the data in 

DATA_VALUE with its complement in QUALIFIER, according 

to the following conventions: DATA_VALUE entries that are 

accompanied by “<,” “N,” or “L” entries in QUALIFIER are 

represented in QUALIFIED_VALUE as negative numbers (for 

example, “-2”); and DATA_VALUE entries that are accompanied by “>” or “G” entries in QUALIFIER are represented 

in QUALIFIED_VALUE as values with 0.00111, 0.01111 or 

0.11111 added to them (for example, >0.25 becomes 0.25111, 

>0.5 becomes 0.51111, and >10 becomes 10.11111).

 Measurement characteristics such as units and analytical 

techniques are identified using a PARAMETER code, which 

is a concatenation of data from the fields SPECIES, UNITS, 

TECHNIQUE, and DIGESTION. For example, the parameter 

“Sb_ppm_AA_F_HNO3_P” represents the concentration of 

antimony, expressed in parts per million, as detected by flame 

atomic absorption spectrometry after a partial digestion (dissolution) with HNO3

. PARAMETER is a 25-character-length field 

that contains a method summary that can be used as a column 

name in a data report or spreadsheet.

The chemical data have been split into tables BestValue_Ag_Mo, BestValue_Na_Zr and BestValue_WholeRock due to the 255-field limit of Access software. These 

data are derived from all of the determinations in the Chem2

table of the AGDB2 and are presented in “best value” format. 

In BestValue_Ag_Mo data for trace-elements Ag through 

Mo are reported for all samples. For non-rock samples (sediment, soil, mineral and heavy-metal concentrates), data for 

major elements Al, Ca, Fe, K, Mg, and Mn are reported in 

this table as elemental concentrations. BestValue_Na_Zr

includes data for trace-elements Nb through Zr for all 

samples. For non-rock samples (sediment, soil, mineral and 

heavy-metal concentrates), data for major elements Na, P, Si, 

and Ti are reported in this table as elemental concentrations. 

BestValue_WholeRock contains whole-rock data for all 

samples. For rock samples, major element chemical determinations are expressed as oxide concentrations and fields are 

named accordingly (for example, Al2O3_pct_WDX rather 

than Al_pct_WDX). LAB_ID, the key field of the chemical 

data tables, is described in the “BestValue” Ranking Tables 

section of this report.

The chemical data tables BestValue_Ag_Mo, BestValue_Na_Zr, and BestValue_WholeRock contain fields of 

the type “Species_ppm” (for example, Ag_ppm) that contain 

the “best value” for the species entered as qualified values 

from the QUALIFIED_VALUE field of the Chem2 table. 

The chemical data tables contain fields of the type “Species_ppm_AM” (for example, Ag_ppm_AM) which include the 

abbreviated name of the analytical method used to determine 

the “best value” for the species. These are the same methods 

and names found in the AGDB2. The chemical data tables also 

contain fields of the type “Species_ppm_SUM” (for example, 

Ag_ppm_SUM) that concatenate in order from best method 

to least, all available values and their respective analytical 

methods for the species and sample. For example, sample 

LAB_ID C286881 has a Ag_ppm_SUM entry “0.4, AES_AZ; 

-1, MS_ST; -1, MS_HF”. This indicates that the best value for 

Ag in this sample is “0.4 ppm” by AES_AZ, the second best 

value is “<1 ppm” by MS_ST, and the third best value is “<1 

ppm” by MS_HF. Descriptions of all analytical methods are 

found in the AnalyticMethod table. All determinations in the 

Chem2 table of the AGDB are contained in these “Species_

ppm_SUM” fields of the AGDB2.

The Mnrlgy table contains 28 fields with optical 

mineralogical data for 18,138 nonmagnetic heavy-mineral 

concentrate samples. The 18 fields record the occurrence of 

18 discrete ore-related minerals; NORM field indicates that 

no ore-related minerals were observed. Details and orerelated minerals beyond the 18 are recorded in OreRelatedMnrl_Comment; data regarding rock-forming minerals are in 

RockFormingMnrl_Comment. Appendix 2 lists the mineral 

name abbreviations in Mnrlgy. The relationship between 

Mnrlgy and Geol2 is shown in figure 2. More than 75 percent 

of these data were generated by Richard B. Tripp (retired, 

USGS) from1975 through 2009 in support of various USGS 

mineral resource assessment projects. Mineralogic data were 

originally recorded in hardcopy with mineral abundances 

variously reported as: (1) “present” or “not present”, (2) 

“abundant” or “moderate” or “trace” or “absent”, (3) as a percentage or as a percentage range, or (4) as numbers of mineral 

particles. The field Inferred_Comment contains R.B. Tripp’s 

comments based on chemical analyses and previous USGS 

map publications, and those that were noted during the Federal Lands in Alaska–Geologic Studies project (2007–2009) 
10 Alaska Geochemical Database Version 2.0 (AGDB2)

for samples that had been hand ground or consumed during 

analysis. Appendix 3 contains a bibliographic list of these 

USGS map publications as well as other USGS publications 

containing relevant mineralogical information.

AnalyticMethod, Parameter, Parameter_Rank, and 

AnalyticMethodBiblio are reference tables in the AGDB2. 

AnalyticMethod is a look-up table with additional information on the 85 field and laboratory techniques used for 

analysis of the various geologic materials. It is linked by 

ANALYTIC_METHOD to the Chem2 table. AnalyticMethod

includes a description of the methods and relevant published 

references, and is linked by ANALYTIC_METHOD_PUB_ID

to references in AnalyticMethodBiblio. In the Chem2

table, details of sample preparation methods are found in 

DECOMPOSITION, and LAB_NAME indicates the laboratory or work group responsible for the analysis. Parameter

is a look-up table of analytical method parameters used 

to describe measurement characteristics of chemical and 

physical data, and is linked by PARAMETER to the Chem2

table. There are 989 unique parameters in the AGDB2. The 

Parameter_Rank table contains the analytical method 

parameters of the AGDB2 ranked by species, and is 

linked by ANALYTIC_METHOD to the AnalyticMethod

table, and by PARAMETER to the Parameter table. The 

FieldNameDictionary table contains the field name, size, 

definition, and general data type of the 496 fields used in the 

AGDB2 tables as well as the names of tables in which these 

fields appear. Relationships between chemical data tables and 

all other tables in the AGDB2 are shown in figure 2.

Other Data Formats

To serve a wider audience of potential users of the 

AGDB2, all of the geospatial and chemical data have been 

exported from Access tables into five Excel spreadsheets 

with data on rock, sediment, concentrate, mineral, and soil 

samples. The reference tables are also provided as Excel 

spreadsheets. Table 2 lists the spreadsheet files included in 

the data release. In addition, these spreadsheets and tables 

are also included as tab-delimited ASCII flat files (.txt) that 

may be used by various applications. 

Relational databases can be implemented using a variety 

of proprietary or nonproprietary software packages. AGDB2 

data are reported here in proprietary (Microsoft Office 

Access 2010 and Excel 2010) and nonproprietary (ASCII 

tab-delimited) formats. 

“Best Value” Data Population

The AGDB2 “best value” chemical data tables were 

populated element by element with chemical determinations 

and corresponding analytical method data from the Chem2

table of the AGDB2 by the use of Microsoft Access select and 

update queries. Though an analytical method may determine 

multiple species concentrations, each species in the AGDB2 

was ranked individually to consider the many factors that 

have been mentioned in the section Determining “Best Value” 

Table 2. List of spreadsheets containing data from Alaska Geochemical Database Version 2.0.

Spreadsheet name Information contained in spreadsheet

AnalyticMethod.xlsx Analytical methods used to obtain chemical and physical data

AnalyticMethodBiblio.xlsx References for analytical methods used to obtain chemical data

BestValue_HMC.xlsx “Best value” chemical data for heavy-mineral concentrate samples

BestValue_Mnrl.xlsx “Best value” chemical data for mineral samples

BestValue_Rank.xlsx Workbook with tables for each species of analytical method parameters ranked by species

BestValue_Rock.xlsx “Best value” chemical data for rock samples

BestValue_Sed.xlsx “Best value” chemical data for bulk sediment samples

BestValue_Soil.xlsx “Best value” chemical data for soil samples

FieldNameDictionary.xlsx Description of field names used for all tables in the database

Mnrlgy.xlsx Mineralogy data for non-magnetic heavy-mineral concentrate samples

MnrlName Mineral name abbreviations used in Mnrlgy table

Parameter.xlsx Analytical method parameters used to obtain chemical and physical data

Parameter_Rank.xlsx Analytical method parameters ranked by species
“Best Value” Data Population 11

Rankings (sample size, decomposition, instrument used, limits 

of detection, interferences, method complexity, and so forth). 

Using Ag (silver) as an example, the process of “best value” 

data population is described here. The “best value” analytical method ranking table for Ag (worksheet AGDB_AnalMethRank_Silver in the workbook table BestValue_Rank.

xlsx) was used for reference (fig. 3). The AGDB2 fields to be 

populated with Ag data in the table BestValue_Ag_Mo are 

Ag_ppm, Ag_ppm_AM, and Ag_ppm_SUM. 

Detected Values

The first set of values to be populated is detected values 

(QUALIFIED_VALUE >0) by analytical methods using “total” 

digestion techniques. These methods correspond to “best 

value” rank 01 through 09 in the BESTVALUE_RANK field 

of the ranking table for silver. Rank 01 corresponds to 37 NA 

determinations for Ag in the Chem2 table. The detected values 

of this data set were populated from QUALIFIED_VALUE to 

Ag_ppm, the corresponding analytical method from ANALYTIC_METHOD to Ag_ppm_AM, and the concatenations 

of the value and method populated in Ag_ppm_SUM. Ranks 

02 through 09 were then populated in ascending order but 

each in the following order: (1) if Ag_ppm is not null (has 

already been populated) then populate Ag_ppm_SUM with 

its existing concatenation entry followed by a semi-colon and 

the new concatenation, and (2) if Ag_ppm is null (has yet to 

be populated) the population scheme of rank 01 is repeated. 

In this way the “best value” is reported and all other values 

are entered as well. The second set of values to be populated 

contains detected values by analytical methods employing 

partial digestion techniques, and was executed in the same 

manner as ranks 01 through 09. These partial digestion methods correspond to “best value” rank P01 through P08 in the 

BESTVALUE_RANK field of the ranking table for silver. This 

second step was skipped for species that didn’t employ partial 

digestion techniques.

Non-detected Values

The third set of values to be populated contains nondetect values (QUALIFIED_VALUE <0). The analytical methods for these values correspond to non-detect rank 01 through 

17 in the NONDETECT_RANK field of the ranking table for 

silver. Rank 01 corresponds to 17,368 AES_AZ_P determinations for Ag in the Chem2 table. The non-detect values in 

this data set were populated from QUALIFIED_VALUE to 

Ag_ppm, the analytical method from ANALYTIC_METHOD to 

Ag_ppm_AM, and the concatenations of the value and method 

populated in Ag_ppm_SUM. Ranks 02 through 17 were then 

populated in ascending order, but each in the following order, 

1) if Ag_ppm is not null (has already been populated) then 

populate Ag_ppm_SUM with its existing concatenation entry 

followed by a semi-colon and the new concatenation, and 2) 

if Ag_ppm is null (has yet to be populated) the population 

scheme of rank 01 is repeated.

Figure 3. “Best value” analytical method ranking table for silver used in the Alaska Geochemical Database Version 2.0.
12 Alaska Geochemical Database Version 2.0 (AGDB2)

Acknowledgments

The authors thank James G. Crock, Paul J. Lamothe, and 

Richard M. O’Leary (U.S. Geological Survey, Emeriti), and 

Steven M. Smith (U.S. Geological Survey) for their advice 

and assistance in defining the “best value” geochemical data 

model. We also thank Dorothy M. Trujillo for her assistance 

in providing data from the NGDB, and many thanks go to Jill 

Schneider (U.S. Geological Survey) for making the Alaska 

Technical Data Unit so accessible. The authors acknowledge 

David B. Smith (U.S. Geological Survey), and Elizabeth A. 

Bailey and Carl C. Abston (U.S. Geological Survey, retired) 

for their early work on the Alaska Geochemical Database 

project. Their assistance and encouragement throughout the 

life of this project is much appreciated. The authors acknowledge Peter N. Schweitzer, J.G. Crock, P.J. Lamothe, and R.M. 

O’Leary for their technical review of the manuscript and 

database; their expertise and assistance were invaluable in 

improving the work.

References

Database References 

Within the database, references are cited for analytical 

methods that were used to determine elemental concentrations 

in the chemical data tables. Information regarding the method 

of analysis or measurement used to obtain data is found in 

AnalyticMethodBiblio (table 1). Refer to the ANALYTIC_

METHOD_PUB_ID—in most cases the USGS Library call 

number—when researching the analytical method in question.

References Cited

Anderson, E.D., Smith, S.M., Giles, S.A., Granitto, Matthew, 

Eppinger, R.G., Bedrosian, P.A., Shah, A.K., Kelley, K.D., 

Fey, D.L., Minsley, B.J., Brown, P.J., 2011, Geophysical 

and geochemical data from the area of the Pebble Cu-AuMo porphyry deposit, southwestern Alaska—Contributions 

to assessment techniques for concealed mineral resources: 

U.S. Geological Survey Data Series 608, 43-p. pamphlet, 

accessed July 27, 2012, at http://pubs.er.usgs.gov/publication/ds608/.

Arbogast, B.F., 1990, Quality assurance manual for the Branch 

of Geochemistry, U.S. Geological Survey: U.S. Geological 

Survey Open-File Report 90–668, 184 p., accessed July 27, 

2012, at http://pubs.usgs.gov/of/1990/0668/report.pdf

Arbogast, B.F., ed., 1996, Analytical methods manual for 

the Mineral Resource Surveys Program, U.S. Geological 

Survey: U.S. Geological Survey Open-File Report 96–525, 

248 p., accessed July 27, 2012, at http://pubs.usgs.gov/

of/1996/0525/report.pdf

Bailey, E.A., Lee, G.K., Mueller, S.H., Wang, Bronwen, 

Brown, Zoe Ann, and Beischer, G.A., 2007, Major and 

trace-element data from stream-sediment and rock samples 

collected in the Taylor Mountains 1:250,000-scale quadrangle, Alaska: U.S. Geological Survey Open-File Report 

2007–1196, 7- p. pamphlet, v. 1.1, accessed July 27, 2012, 

at http://pubs.usgs.gov/of/2007/1196/.

Bailey, E.A., Shew, N.E., Labay, K.A., Schmidt, J.M., 

O’Leary, R.M., and Detra, D.E., 2010, Stream-sediment 

samples reanalyzed for major, rare-earth, and trace elements 

from ten 1:250,000-scale quadrangles, south-central Alaska, 

2007–2008: U.S. Geological Survey Open File Report 

2010–1147, 6-p. pamphlet, accessed July 27, 2012, at http://

pubs.usgs.gov/of/2010/1147/.

Bailey, E.A., Smith, D.B., Abston, C.C., Granitto, Matthew, 

and Burleigh, K.A., 1999, National Geochemical Database, 

U.S. Geological Survey RASS (Rock Analysis Storage System) geochemical data for Alaska: U.S. Geological Survey 

Open-File Report 99–433, v. 2.0, accessed on July 27, 2012 

at http://pubs.usgs.gov/of/1999/of99-433/

Fey, D.L., Granitto, Matthew, Giles, S.A., Smith, S.M., 

Eppinger, R.G. and Kelley, K.D., 2009, Geochemical data 

for samples collected in 2008 near the concealed Pebble 

porphyry Cu-Au-Mo deposit, southwest Alaska: U.S. 

Geological Survey Open-File Report 2009‒1239, 107-p. 

pamphlet, 2 plates, accessed July 27, 2012, at http://pubs.

er.usgs.gov/publication/ofr20091239/. Superseded by U.S. 

Geological Survey Data Series 608, http://pubs.usgs.gov/

ds/608/.

Fey, D.L., Granitto, Matthew, Giles, S.A., Smith, S.M., 

Eppinger, R.G. and Kelley, K.D., 2008, Geochemical data 

for samples collected in 2007 near the concealed Pebble 

porphyry Cu-Au-Mo deposit, southwest Alaska: U.S. 

Geological Survey Open-File Report 2008‒1132, 153-p. 

pamphlet, 1 plate, , accessed Jul. 27, 2012, at http://pubs.

er.usgs.gov/publication/ofr20081132/. Superseded by Data 

Series 608, http://pubs.usgs.gov/ds/608/.

Gamble, B.M., Bailey, E.A., Schmidt, J.M., Shew, N.B., 

Labay, K.A., ,Granitto, Matthew, O’Leary, R.M., and 

Detra, D.E., 2010, Stream sediment samples reanalyzed 

for major, rare earth, and trace elements from seven 

1:250,000-scale quadrangles, south central Alaska, 

2007-2009: U.S. Geological Survey Data Series 532, 4-p. 

pamphlet, accessed on Jul. 27, 2012 at http://pubs.usgs.

gov/ds/532/.

Granitto, Matthew, Bailey, E.A., Schmidt, J.M., Shew, 

N.B., Gamble, B.M. and Labay, K.A., 2011, Alaska Geochemical Database (AGDB)—Geochemical data for rock, 

sediment, soil, mineral, and concentrate sample media: 

U.S. Geological Survey Data Series 637, 11-p., accessed 

on July 27, 2012 at http://pubs.er.usgs.gov/publication/

ds637/.
References 13

Granitto, Matthew; Schmidt, J.M., Labay, K.A., Shew, N.B., 

Gamble, B.M., 2012, Alaska Geochemical Database—Mineral exploration tool for the 21st century—PDF of presentation: U.S. Geological Survey Open-File Report 2012‒1060, 

33-p. pamphlet, accessed on July 27, 2012 at http://pubs.

usgs.gov/of/2012/1060/.

Klimasauskas, E.P., Miller, M.L., and Bradley, D.C., 2007, 

Major- and trace-element concentrations in rock samples 

collected in 2006 from the Taylor Mountains 1:250,000-

scale quadrangle, Alaska: U.S. Geological Survey OpenFile Report 2007–1386, 6-p. pamphlet, accessed July 27, 

2012, at http://pubs.usgs.gov/of/2007/1386/.

Klimasauskas, E.P., Miller, M.L., Bradley, D.C., Bundtzen, 

T.K., and Hudson, T.L., 2006, Major- and trace-element 

concentrations in rock samples collected in 2005 from the 

Taylor Mountains 1:250,000-scale quadrangle, Alaska: 

U.S. Geological Survey Open-File Report 2006–1306, 8-p. 

pamphlet, accessed July 27, 2012, at http://pubs.usgs.gov/

of/2006/1306/.

Klimasauskas, E.P., Miller, M.L., Bradley, D.C., Karl, S.M., 

Baichtal, J.F., and Blodgett, R.B., 2006, Major- and 

trace-element concentrations in rock samples collected in 

2004 from the Taylor Mountains 1:250,000-scale quadrangle, Alaska: U.S. Geological Survey Open-File Report 

2006–1070, 8-p. pamphlet, v. 1.1, accessed July 27, 2012, at 

http://pubs.usgs.gov/of/2006/1070/.

Miesch, A.T., 1976, Sampling designs for geochemical surveys—Syllabus for a short course: U.S. Geological Survey 

Open-File Report 76–772, 128 p., accessed July 27, 2012, at 

http://pubs.er.usgs.gov/publication/ofr76772.

Smith, S.M., 1997, National Geochemical Database reformatted data from the National Uranium Resource Evaluation 

(NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR) Program: U.S. Geological Survey OpenFile Report 97–492, v. 1.4, accessed Jan. 27, 2011, at http://

pubs.usgs.gov/of/1997/ofr-97-0492/.

Smith, S.M., Smith, D.B., and Bailey, E.A., 2003, The U.S. 

Geological Survey’s National Geochemical Database [abs.]: 

Geological Society of America Abstracts with Program, 

v. 35, no. 7, p. 366.

Taggart, J.E., ed., 2002, Analytical methods for chemical 

analysis of geologic and other materials, U.S. Geological 

Survey: U.S. Geological Survey Open-File Report 2002–

0223, v. 5.0, accessed July 27, 2012, at http://pubs.usgs.gov/

of/2002/ofr-02-0223/.

Taggart, J.E., Lindsay, J.R., Scott, B.A., Vivit, D.V., Bartel, 

A.J., and Stewart, K.C., 1987, Analysis of geologic materials by wavelength-dispersive X-ray fluorescence spectrometry, in Methods for geochemical analysis: U.S. Geological 

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http://pubs.er.usgs.gov/publication/b1770.

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Survey, database and documentation: U.S. Geological Survey Open-File Report 2004–1001, v. 5.0, accessed July 27, 

2012, at http://pubs.usgs.gov/of/2004/1001/.

Publishing support provided by: 

Denver Publishing Service Center

For more information concerning this publication, contact:

Center Director, USGS Central Mineral and Environmental Resources 

Science Center

Box 25046, Mail Stop 973

Denver, CO 80225

(303) 236-1562

Or visit the Central Mineral and Environmental Resources Science 

Center Web site at:

http://minerals.cr.usgs.gov/
14 Alaska Geochemical Database Version 2.0 (AGDB2)

Appendix 1

Analytical Methods

Appendix 1 contains a table of analytical method names 

and descriptions of the analytical techniques that provided the 

chemical data of the Alaska Geochemical Database Version 2.0.

Table A1. Analytical methods.—Continued

Analytical Method Description

AA_CV mercury by cold vapor-atomic absorption spectrometry after multi-acid digestion and solution.

AA_F_AZ_Fuse_P silver, arsenic, bismuth, cadmium, copper, lead, antimony and zinc by flame atomic absorption spectrometry after partial digestion by K2S2O7 fusion, HCl-KI, ascorbic acid, and selective organic extraction with Aliquat 336-MIBK.

AA_F_AZ_H2O2_P silver, arsenic, bismuth, cadmium, copper, lead, antimony and zinc by flame atomic absorption spectrometry after 

partial digestion with HCl-H2O2-KI, ascorbic acid and selective organic extraction with Aliquat 336-MIBK.

AA_F_AZ_HCl_P silver, arsenic, bismuth, cadmium, copper, lead, antimony and zinc by flame atomic absorption spectrometry after 

partial digestion with HCl-KI, and selective organic extraction with Aliquat 336-MIBK.

AA_F_CX_P calcium, magnesium, sodium, potassium and cation exchange capability in soil by flame atomic absorption 

spectrometry after solution extraction and cation exchange.

AA_F_DTPA_P cadmium, cobalt, copper, iron, manganese, nickel, lead and zinc by flame atomic absorption spectrometry after DTPA 

extraction and cation exchange.

AA_F_Fuse major and minor elements by flame atomic absorption spectrometry after fusion digestion.

AA_F_Fuse_P molybdenum and antimony by flame atomic absorption spectrometry after K2S2O7 fusion, partial acid digestion, and 

selective organic extraction with Aliquat 336-MIBK.

AA_F_H2O_P calcium, magnesium, manganese and arsenic in saturation paste of soil by flame atomic absorption spectrometry after 

solution extraction.

AA_F_HBr silver, gold and tellurium by flame atomic absorption spectrometry after HBr-Br2 digestion and selective organic 

extraction with Aliquat 336-MIBK.

AA_F_HCl_OE_P antimony by flame atomic absorption spectrometry after partial digestion with HCl and selective organic extraction 

with Aliquat 336-MIBK.

AA_F_HCl_P copper and manganese by flame atomic absorption spectrometry after partial digestion with HCl.

AA_F_HF major and minor elements by flame atomic absorption spectrometry after multi-acid digestion with HF.

AA_F_HNO3_P silver, cadmium, copper, lead and zinc by flame atomic absorption spectrometry after partial digestion with hot HNO3.

AA_FE sodium and potassium by flame emission spectrometry (flame photometry) after HF-HClO4 dissolution or LiBO2 fusion.

AA_GF_HBr gold and tellurium by graphite furnace atomic absorption spectrometry after HBr-Br2 digestion and selective organic 

extraction with Aliquat 336-MIBK.

AA_GF_HF arsenic, gold, bismuth and tellurium by graphite furnace atomic absorption spectrometry after multi-acid digestion 

with HF and selective organic extraction with Aliquat 336-MIBK.

AA_GF_ST thallium by graphite furnace atomic absorption spectrometry after Na2O2 sinter, HCl-HNO3 dissolution, and 

selective organic extraction with DIBK.

AA_HG_Acid selenium by flow injection or continuous flow-hydride generation-atomic absorption spectrometry after digestion with 

HNO3-HCl-H2SO4-KMnO4.

AA_HG_HF arsenic, antimony, selenium and tellurium by flow injection or continuous flow-hydride generation-atomic absorption 

spectrometry after multi-acid digestion with HF.

AA_HG_ST arsenic and antimony by flow injection or continuous flow-hydride generation-atomic absorption spectrometry after 

Na2O2 sinter digestion.
Appendix 1 15

Table A1. Analytical methods.—Continued

Analytical Method Description

AA_TR mercury by thermal release and atomic absorption spectrometry after heating (Vaughn-McCarthy method).

AA_TR_W mercury by thermal release and atomic absorption spectrometry after heating (Vaughn-McCarthy method) and use of 

a willemite screen.

AES_Acid_P major and minor elements by inductively coupled plasma-atomic emission spectrometry after unknown partial acid 

digestion.

AES_AR_P major and minor elements by inductively coupled plasma-atomic emission spectrometry after partial digestion with 

aqua regia.

AES_AZ_P silver, arsenic, gold, bismuth, cadmium, copper, molybdenum, lead, antimony and zinc by inductively coupled 

plasma-atomic emission spectrometry after partial digestion with HCl-H2O2.

AES_Fuse major and minor elements by inductively coupled plasma-atomic emission spectrometry after fusion digestion.

AES_HF major and minor elements by inductively coupled plasma-atomic emission spectrometry after digestion with 

HF-HCl-HNO3-HClO4.

AES_HF_REE rare earth elements by ion exchange and inductively coupled plasma-atomic emission quantitative spectrometry after 

HF-HCl-HNO3-HClO4 digestion.

AES_IE molybdenum, niobium and tungsten by inductively coupled plasma-atomic emission quantitative spectrometry after 

HF-HCl-HNO3-HClO4 digestion and ion exchange separation.

AES_ST major and minor elements by inductively coupled plasma-atomic emission spectrometry after sinter digestion.

AFS_CV mercury in aqueous media by flow injection-cold vapor-atomic fluorescence spectrometry.

CB_CHN carbon, hydrogen and nitrogen by gas chromatography/thermal conductivity (CHN elemental) analyzer after combustion.

CB_IRC carbon and sulfur by infrared detection after combustion.

CB_TC total carbon and organic carbon by thermal conductivity detection after combustion.

CB_TT sulfur by iodometric titration after combustion.

CM_Acid bromine by colorimetry after acid digestion.

CM_Acid_P arsenic by modified Gutzeit apparatus confined-spot method colorimetry after partial digestion in KOH-HCl and 

chemical separation.

CM_CX_P heavy metal elements by colorimetry after partial extraction in aqueous ammonium citrate solution.

CM_Fuse major and minor elements by colorimetric spectrophotometry after fusion digestion.

CM_Fuse_P molybdenum and antimony by colorimetry after partial digestion by K2S2O7 fusion (Mo) or NaHSO4 fusion-HCl 

digestion (Sb, rhodamine B).

CM_H2O_P sulfate in saturation paste of soil by colorimetric titration after solution extraction.

CM_HF major and minor elements by colorimetric spectrophotometry after multi-acid digestion with HF.

CM_HFS fluorine by colorimetric spectrophotometry after H2SiF6 digestion and chemical separation.

CM_HNO3_P copper, lead and zinc by colorimetry after partial digestion with HNO3.

CM_PC_P uranium by paper chromatography after partial digestion with HNO3.

CM_ST chlorine by colorimetric spectrophotometry after Na2CO3 and ZnO sinter digestion.

CM_ST_P tungsten by colorimetry after partial digestion with carbonate sinter.

CP organic carbon, carbonate carbon and totals by computation.

DN uranium and thorium by delayed neutron activation counting.

EDX minor elements by energy dispersive X-ray fluorescence spectrometry.

ES_H2O_P boron by semi-quantitative direct-current arc emission spectrography after solution extraction.

ES_Q major and minor elements by quantitative direct-current arc emission spectrography.

ES_SQ major and minor elements by semi-quantitative direct-current arc emission spectrography.

FA_AA gold, silver and platinum group elements by graphite furnace atomic absorption spectrometry after PbO fire assay 

chemical separation.
16 Alaska Geochemical Database Version 2.0 (AGDB2)

Table A1. Analytical methods.—Continued

Analytical Method Description

FA_DC gold by direct current plasma-atomic emission spectroscopy or atomic absorption spectrophotometry after PbO fire 

assay chemical separation.

FA_ES gold and platinum group elements by direct-current arc quantitative emission spectrography after PbO fire assay 

chemical separation.

FA_MS platinum group elements by inductively coupled plasma-mass spectrometry after NiS fire assay chemical separation.

FL_HF beryllium, tin and uranium by fluorometry after multi-acid digestion with HF.

FL_HNO3 selenium by fluorometry after digestion with HNO3-H3PO4.

GRC uranium by gamma counting.

GV density, moisture and weight by gravimetry; ash or loss on ignition by weight loss after heating at 900° C.

GV_Acid major and minor elements by gravimetry after acid digestion.

GV_CR major and minor elements by gravimetry for Classical Rock Analysis after unknown digestion method.

GV_Flux moisture, bound water and total water by heating and weight loss with flux.

GV_Fuse major and minor elements by gravimetry after fusion digestion.

IC chlorine, fluorine, nitrate, sulfate and phosphate by ion chromatography.

INST pH by standard method combination pH electrode.

INST_P specific conductance by standard method conductivity electrode and pH by standard method combination pH 

electrode after partial digestion.

ISE_Fuse chlorine, fluorine and iodine by ion specific electrode after fusion digestion.

ISE_H2O chlorine by ion specific electrode after solution extraction.

ISE_HF chlorine by ion specific electrode after multi-acid digestion with HF.

MS_AR_P major and minor elements by inductively coupled plasma-mass spectrometry after partial digestion with aqua regia.

MS_HF major and minor elements by inductively coupled plasma-mass spectrometry after HF-HCl-HNO3-HClO4 digestion.

MS_ST major and minor elements by inductively coupled plasma-mass spectrometry after Na2O2 sinter digestion.

MS_ST_REE rare earth elements by inductively coupled plasma-mass spectrometry after Na2O2 sinter digestion.

NA major and minor elements by long or short count instrumental neutron activation analysis.

pH pH by standard method combination pH electrode.

TB_AR acid-soluble sulfate, sulfur and sulfide by turbidimetry after aqua regia digestion.

TT_Flux total water by Karl Fischer coulometric titration with flux after combustion.

TT_Fuse Fe2O3 by titration after fusion, decomposition and precipitation.

TT_HCl carbonate carbon and carbon dioxide (acid soluble carbon) by coulometric titration after HClO4 digestion and 

extraction.

TT_HF ferrous oxide by colorimetric or potentiometric titration after HF-H2SO4 digestion.

VOL carbon dioxide or carbonate carbon by evolution after acid decomposition; aka “gasometric” or “manometric”.

WDX_Fuse major and minor elements by wavelength dispersive X-ray fluorescence spectrometry after LiBO2 fusion digestion.

WDX_Raw chlorine, iodine and bromine by wavelength dispersive X-ray fluorescence spectrometry on raw sample.
Appendix 2 17

Appendix 2

Mineral Name Abbreviations

Appendix 2 contains a table of abbreviations for mineral 

names used in the Mnrlgy table of the Alaska Geochemical 

Database Version 2.0.

Table A2. Mineral name abbreviations.—Continued

Abbreviation Description

AB albite

AG silver

ALN allanite

AMG amalgam

AMP amphibole

AMP/PYX amphibole/pyroxene

AND andalusite

ANG anglesite

ANT anatase

APT apatite

ARG aragonite

ARS arsenopyrite

AU gold

AZR azurite

BAR barite

BI bismuth

BIO biotite

BIS bismuthinite

BLG boulangerite

BRK brookite

CAS cassiterite

CDT cordierite

CER cerussite

CHR chromite

CIN cinnabar

CLB columbite

CLN clinochlore

CLR chlorite

CONT contamination

COR corundum

CPY chalcopyrite

Table A2. Mineral name abbreviations.—Continued

Abbreviation Description

CR-D Cr-diopside

CUP cuprite

CUS/O copper sulfide/copper oxide

CYR cyrtolite

DUM dumortierite

ENG enargite

EPD epidote

FE/MN iron oxide/manganese oxide

FLR fluorite

FUC fuchsite

GAL galena

GAL/CER galena/cerussite

GAL/MIN galena/minium

GAR garnet

GHN gahnite

GRP graphite

HB hornblende

HMP hemimorphite

HMT hematite

ILM ilmenite

JAM jamesonite

KYN kyanite

LCX leucoxene

LIM limonite

LTH litharge

MAL malachite

MAR marcasite

MAS massicot

MGT magnetite

MIC mica

MIM mimetite

MIN minium

MLY molybdenite

MNZ monazite

MTZ metazeunerite

MUS muscovite

MUS/CLR muscovite/chlorite

NORM no ore-related minerals

OL olivine

OL/SRP olivine/serpentine

ORP orpiment

PHN phenakite
18 Alaska Geochemical Database Version 2.0 (AGDB2)

Table A2. Mineral name abbreviations.—Continued

Abbreviation Description

POW powellite

PRS proustite

PYC pyrochlore

PYH pyrrhotite

PYM pyromorphite

PYR pyrite

PYR/ARS pyrite/arsenopyrite

PYR/MAR pyrite/marcasite

PYX pyroxene

Q/F quartz/feldspar

Q_FE iron stained quartz

QTZ quartz

R1 rock fragments—graphitic

R2 rock fragments—grey

R3 rock fragments—chloritic

R4 rock fragments—tan

R5 rock fragments—pelitic

R6 rock fragments—pyritic

REE-M REE-rich minerals

RLG realgar

RUC rucklidgeite

RUT rutile

RUT/ANT rutile/anatase

RUT/ANT/BRK rutile/anatase/brookite

RUT/BRK rutile/brookite

RX rock fragments

SAF safflorite

SAP sapphire

SCH scheelite

SCH/POW scheelite/powellite

SIL sillimanite

SLF sulfide

SMA smaltite

SMI smithsonite

SPH sphalerite

SPN sphene

SPN-REE REE-rich sphene

SPN-TH thorium-rich sphene

SRC sericite

SRP serpentine

STB stibnite

TET tetrahedrite

Table A2. Mineral name abbreviations.—Continued

Abbreviation Description

TH-M Th-rich minerals

THN thorianite

THR thorite

TPZ topaz

TRN tourmaline

URN uraninite

UTH uranothorite

WOL wolframite

WUL wulfenite

XEN xenotime

ZIR zircon
Appendix 3 19

Appendix 3

Mineralogical Data References

Appendix 3 contains a bibliographic list of USGS map 

publications containing mineralogical information. Some of 

these publications have been cited in field Inferred_Comment

of the Mnrlgy table in the AGBD2 database.

Allen, M.S., and Slaughter, K.E., 1990, Mineralogical data 

and sample locality map of nonmagnetic, heavy-mineralconcentrate samples collected from the eastern part of the 

Lime Hills quadrangle, Alaska: U.S. Geological Survey 

Open-File Report 90–67, 64 p. 1 plate, scale 1:250,000, 

accessed Sept. 5, 2012, http://pubs.er.usgs.gov/publication/

ofr9067.

Bennett, G.J., and Church, S.E., 1987, Mineralogy and sample 

locality map of the nonmagnetic heavy- mineral-concentrate 

samples from the Mt. Katmai Quadrangle and portions of 

the Naknek, Afognak, and Iliamna quadrangles, Alaska: 

U.S. Geological Survey Open-File Report 87‒615, 39 p., 

accessed Sept. 5, 2012, http://pubs.er.usgs.gov/publication/

ofr87615.

Bennett, G.J., Gray, J.E., and Taylor, C.D., 1988, Mineralogy and sample locality map of the nonmagnetic, heavymineral-concentrate samples, Iditarod Quadrangle, Alaska: 

U.S. Geological Survey Open-File Report 88‒32, 37 p., 

accessed Sept. 5, 2012, at http://pubs.er.usgs.gov/publication/ofr8832.

Cathrall, J.B., Albanese, Mary, VanTrump, George, Jr., Mosier, 

E.L., and Lueck, Larry, 1989, Geochemical signatures, 

analytical results, mineralogical data, and sample locality 

map of placer and lode gold, and heavy-mineral concentrates from the Fortymile mining district, Eagle quadrangle, 

Alaska: U.S. Geological Survey Open-File Report 89‒451, 

32 p., l pl., accessed Sept. 5, 2012, at http://pubs.er.usgs.

gov/publication/ofr89451.

Cathrall, J.B., McDanal, S.K., VanTrump, George, Jr., Mosier, 

E.L., and Tripp, R.B., 1988, Analytical results, geochemical signatures, mineralogical data, and sample locality map 

of lode gold, placer gold, and heavy-mineral concentrates 

from the Tolovana mining district, Livengood Quadrangle, 

Alaska: U.S. Geological Survey Open-File Report 88‒578, 

32 p., accessed Sept. 5, 2012, at http://pubs.er.usgs.gov/publication/ofr88578.

Cathrall, J.B., Tripp, R.B., McDanal, S.K., Mosier, E.L., and 

VanTrump, G., Jr., 1988, Analytical results, geochemical 

signatures, mineralogical data, and sample locality map of 

placer gold, and heavy-mineral concentrates from the Circle

 mining district, Circle Quadrangle, Alaska: U.S. Geological 

Survey Open-File Report 88‒676, 48 p., accessed Sept. 5, 

2012, at http://pubs.er.usgs.gov/publication/ofr88676.

Church, S.E., and Bennett, G.J., 1990, Mineralogical maps 

showing the distribution of selected minerals identified in 

nonmagnetic heavy-mineral concentrates from the Mount 

Katmai and parts of the Afognak and Naknek quadrangles, 

Alaska: U. S. Geological Survey Miscellaneous Field Studies Map 2021‒D, 1 sheet, accessed Sept. 5, 2012, at http://

pubs.er.usgs.gov/publication/mf2021D

Frisken, J.G., Church, S.E. and Willson, W.R., 1988, Mineralogical map showing the distribution of selected ore-related 

minerals identified in nonmagnetic heavy-mineral concentrates from the Ugashik, Bristol Bay, and western Karluk 

quadrangles, Alaska: U.S. Geological Survey Miscellaneous 

Field Studies Map 1539‒H, 1 sheet, accessed Sept. 5, 2012, 

at http://pubs.er.usgs.gov/publication/mf1539H.

Gray, J.E., Detra, D.E., Eppinger, R.G., Hill, R.H., Slaughter, K.E., and Sutley, S.J., 1990, Geochemical data and 

sample locality maps for stream-sediment and heavymineral-concentrate samples, and mineralogical data of 

nonmagnetic, heavy-mineral-concentrate samples, collected near five cinnabar-stibnite mineral occurrences in 

the Kuskokwim River region, southwestern Alaska: U.S. 

Geological Survey Open-File Report 90‒299-A, 73 p., 

accessed Sept. 5, 2012, at http://pubs.er.usgs.gov/publication/ofr90299A.

Gray, J.E., Detra, D.E., Eppinger, R.G., Hill, R.H., Slaughter, K.E., and Sutley, S.J., 1990, Geochemical data and 

sample locality maps for stream-sediment and heavymineral-concentrate samples, and mineralogical data of 

nonmagnetic, heavy-mineral-concentrate samples, collected near five cinnabar-stibnite mineral occurrences in 

the Kuskokwim River region, southwestern Alaska: U.S. 

Geological Survey Open-File Report 90‒299‒B, 1 disk 

(51⁄4 in.), accessed Sept. 5, 2012, at http://pubs.er.usgs.gov/

publication/ofr90299B.

Kelley, K.D., Frisken, J.G., and Sutley, S.J., 1993, Maps showing geochemistry and mineralogy of nonmagnetic heavymineral-concentrate samples from the southern part of the 

Chandler Lake Quadrangle, Alaska: U.S. Geological Survey 

Miscellaneous Field Studies Map 2144‒B, 2 sheets, scale 

1:250,000, accessed Sept. 5, 2012, at http://pubs.er.usgs.

gov/publication/mf2144B.

Kelley, K.D., Mull, C.G., and Barton, H.N., 1995, Geochemistry and mineralogy of heavy-mineral concentrates from the 

Killik River 1 degree by 3 degrees quadrangle, Alaska:
20 Alaska Geochemical Database Version 2.0 (AGDB2)

 U.S. Geological Survey Miscellaneous Field Studies Map 

2225‒D, 2 sheets, scale 1:250,000, accessed Sept. 5, 2012, 

at http://pubs.er.usgs.gov/publication/mf2225D.

King, H.D., Smith, S.C., and Werschky, Scott, 1989, Mineralogical maps showing the distribution and abundance 

of selected minerals in nonmagnetic heavy-mineralconcentrate samples from stream sediment, Solomon and 

Bendeleben 1 degree by 3 degrees quadrangles, Seward 

Peninsula, Alaska: U.S. Geological Survey Miscellaneous 

Field Studies Map 2071‒C, 4-p. pamphlet, 1 sheet, scale 

1:250,000, accessed Sept. 5, 2012, at http://pubs.er.usgs.

gov/publication/mf2071C.

McDanal, S.K., Cathrall, J.B., Mosier, E.L., Antweiler, J.C., 

and Tripp, R.B., 1988, Analytical results, geochemical 

signatures, mineralogical data, and sample locality map 

of placer gold and heavy-mineral concentrates from the 

Manley Hot Springs, Tofty, Eureka, and Rampart mining districts, Tanana and Livengood quadrangles, Alaska: 

U.S. Geological Survey Open-File Report 88‒443, 54 

p., accessed Sept. 5, 2012, at http://pubs.er.usgs.gov/

publication/ofr88443.

Tripp, R.B., and Cathrall, J.B., 1983, Mineralogical map 

showing the distribution of selected minerals in nonmagnetic fraction of heavy-mineral concentrates from stream 

sediments, Petersburg area, Southeast Alaska: U.S. Geological Survey Open-File Report 83‒420‒X, 1 sheet, scale 

1:250,000, accessed Sept. 5, 2012, at http://pubs.er.usgs.

gov/publication/ofr83420X.

Tripp, R.B., and Crim, W.D., 1978, Mineralogical map 

showing the distribution and abundance of gold, scheelite, 

chalcopyrite, arsenopyrite, minium and sapphire corundum 

in heavy-mineral concentrates in the Seward and Blying Sound quadrangles, Alaska: U.S. Geological Survey 

Miscellaneous Field Studies Map 880‒G, 2 sheets, scale 

1:250,000, accessed Sept. 6, 2012, at http://pubs.er.usgs.

gov/publication/mf880G.

Tripp, R.B., Crim, W.D., Hoffman, J.D., O’Leary, R.M., and 

Risoli, D.A., 1986, Mineralogical and geochemical maps 

showing the distribution of selected minerals and elements 

found in the minus-80-mesh stream-sediment and related 

minus-30-mesh heavy-mineral-concentrate samples from 

the Circle quadrangle, Alaska: U.S. Geological Survey 

Open-File Report 83‒170‒F, 7-p. pamphlet,6 sheets, scale 

1:250,000, accessed Sept. 5, 2012, at http://pubs.er.usgs.

gov/publication/ofr83170F.

Tripp, R.B., Curtin, G.C., Day, G.W., O’Leary, R.M., and 

Carten, R.B., 1976, Maps showing mineralogical and 

geochemical data for heavy-mineral concentrates in the 

Tanacross quadrangle, Alaska: U.S. Geological Survey 

Miscellaneous Field Studies Map 767‒O, 2 sheets, scale 

1:500,000, accessed Sept. 6, 2012, at http://pubs.er.usgs.

gov/publication/mf767O.

Tripp, R.B., Curtin, G.C., Nokleberg, W.J., Huston, D.L., and 

Hampton, J.R., 1993, Mineralogical maps showing distribution of selected ore-related minerals in the nonmagnetic, 

heavy-mineral-concentrate fraction of stream sediment from 

the Mount Hayes 1 degree by 3 degrees quadrangle, eastern 

Alaska Range, Alaska: U.S. Geological Survey Miscellaneous Field Studies Map 1996‒E, 13-p. pamphlet, 3 sheets, 

scale 1:250,000, accessed Sept. 6, 2012, at http://pubs.

er.usgs.gov/publication/mf1996E.

Tripp, R.B., and Detra, D.E., 1980, Maps showing mineralogic 

data for selected minerals in nonmagnetic heavy-mineral 

concentrates of stream sediments in the Chignik and Sutwik Island quadrangles, Alaska: U.S. Geological Survey 

Miscellaneous Field Studies Map 1053‒I, 2 sheets, scale 

1:250,000, accessed Sept. 5, 2012, at http://pubs.er.usgs.

gov/publication/mf1053I.

Tripp, R.B., Carlson, R.C., and Curtin, G.C., 1978, Maps 

showing mineralogical data for nonmagnetic heavy-mineral 

concentrates in the Talkeetna Quadrangle, Alaska: U.S. 

Geological Survey Miscellaneous Field Studies Map 870‒I, 

1 sheet, scale 1:250,000, accessed Sept. 6, 2012, at http://

pubs.er.usgs.gov/publication/mf870I.

Tripp, R.B., and King, H.D., 1993, Maps showing distribution of selected minerals in the nonmagnetic heavy-mineral 

fraction of stream-sediment samples, Medfra Quadrangle, 

Alaska: U.S. Geological Survey Miscellaneous Field Studies Map 2207, 1 sheet, scale, 1:250,000, accessed Sept. 6, 

2012, at http://pubs.er.usgs.gov/publication/mf2207.

Tripp, R.B., King, H.D., and Light, T.D., 1995, Mineralogical 

maps showing the distribution of ore-related minerals in 

the minus-30-mesh, nonmagnetic heavy-mineral fraction of 

stream sediment, Healy quadrangle, Alaska: U.S. Geological Survey Miscellaneous Field Studies Map 2058‒D, 2 

sheets, scale, 1:250,000, accessed Sept. 6, 2012, at http://

pubs.er.usgs.gov/publication/mf2058D.
Granitto and others—Alaska Geochemical Database Version 2.0 (AGDB2)—Data Series 759