National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data, and Information Service(NESDIS)
This directory contains the documentation on Olson's World Ecosystems published in the Global Ecosystems Database:
*OLSON WORLD ECOSYSTEMS_help
Global Ecosystems Database Disc A: Chapter 5
Olson World Ecosystems
World Ecosystems (WE1.3A)
World Ecosystems (WE1.4D)
Resolution Codes for WE1.4D (WE1.4DR)
DATA-SET DESCRIPTION
Data-Set Name: Olson World Ecosystems
Principal Investigator: Jerry S. Olson
Global Patterns Company
Scientific Reference: (* reprint on CD-ROM)
+ Olson, J.S., J.A. Watts, and L.J. Allison, 1983. Carbon in
Live Vegetation of Major World Ecosystems, Report
ORNL-5862, Oak Ridge Laboratory, Oak Ridge, Tennessee.
(Incorporated in NDP-017, cited above)
SOURCE
Source Data Citation:
Olson, J.S., 1989-91. World Ecosystems (WE1.3 and WE1.4).
Digital Raster data on global Geographic (lat/long)
180x360 and 1080x2160 grids. NOAA National Geophysical
Data Center. Boulder, Colorado. Various working files
from GPC on floppy disk.
Contributor:
Dr. Jerry S. Olson
Global Patterns Company
Eblen Cave Road, Box 361A
Lenoir City, Tennessee
37771-9424, USA
(615) 376-2250
(Fax (615) 690-3906 c/o Business Computer Associates)
Distributor:
NGDC/WDC-A
Vintage:
circa 1970's and 1980's (continuing updates)
Lineage:
(1) Principal Investigator:
Jerry S. Olson
Global Patterns Company
(2) Reprocessed and updated by:
Jerry S. Olson, Lee Stanley, Jeff Colby, and Mark
Ohrenschall
NOAA/NGDC, Boulder, CO 80303
ORIGINAL DESIGN
Variables:
Characteristic (actual) ecosystem classes with respect to
carbon content.
(1) WE1.3A Major Groups at 30-minute resolution
(2) WE1.4D Detailed Categories at mixed 30-minute and 10-
minute resolution
(3) WE1.4DR Resolution codes for WE1.4D
Origin:
Numerous collected maps, references, and observations (see
Scientific Reference).
Geographic Reference:
latitude/longitude
Geographic Coverage:
Global
Maximum Latitude: +90 degrees (N)
Minimum Latitude: -90 degrees (S)
Maximum Longitude: +180 degrees (E)
Minimum Longitude: -180 degrees (W)
Geographic Sampling:
Characteristic classes for 30-minute cells with 10-minute
updates for selected classes in Africa
Time Period:
Modern
Temporal Sampling:
Modern composite
INTEGRATED DATA-SET
Data-Set Citation:
Olson, J.S. 1992. World Ecosystems (WE1.4). Digital Raster
Data on a 10-minute Geographic 1080x2160 grid. In:
Global Ecosystems Database, Version 1.0: Disc A.
Boulder, CO: National Geophysical Data Center. Three
independent single-attribute spatial layers on
CD-ROM, 5 MB.
Analyst:
Jerry S. Olson and Lee Stanley, NGDC, Boulder, Colorado
Projection:
Geographic (lat/long), GED window (see User's Guide).
Spatial Representation:
(1) WE1.3A: 30-minute characteristic classes on a 30-minute
grid
(2) WE1.4D: mixed 30-minute and 10-minute characteristic
classes on a 10-minute grid
(3) WE1.4DR: 10-minute cell labels
Temporal Representation:
Modern composite
Data Representation:
(1) WE1.3A: single-byte integer codes for 29 major
ecosystem/landscape groups.
(2) WE1.4D: single-byte integer codes for 73 detailed
ecosystem/landscape types.
(3) WE1.4DR: single-byte integer cell labels for WE1.4D
resolution.
Layers and Attributes:
3 independent single-attribute spatial layers
Compressed Data Volume:
215,231 bytes
ADDITIONAL REFERENCES (* reprint on CD-ROM)
(Also see references on page A05-37)
+ Olson, J.S., J.A. Watts, and L.J. Allison. 1985. Major
World Ecosystem Complexes Ranked by Carbon in Live
Vegetation: A Database. NDP-017. Carbon Dioxide
Information Center, Oak Ridge National Laboratory, Oak
Ridge, Tennessee.
Olson, R. J., F. G. Goff and J. S. Olson. 1976. Development
and applications of regional data resources in
energy-related assessment and planning. Advancements in
Retrieval Technology as Related to Information Systems.
AGARD-CP-201. pp. 12.1-12.7, Technical Information
Panel, AGARD, NATO, Washington D.C.
+ Olson, J.S., 1982. "Earth's Vegetation and Atmospheric
Carbon Dioxide," in Carbon Dioxide Review: 1982. Ed.
by W.C. Clark, Oxford University Press, New York, pp.
388-398. (Incorporated in NDP-017, cited above)
Olson, J. S., and J. A. Watts. 1982. Map of Major World
Ecosystem Complexes Ranked According to Carbon in Live
Vegetation, 1982. Map insert in: W. C. Clark (ed.),
Carbon Dioxide Review: 1982, Oxford University Press,
New York, (Also in Olson et al. 1983)
Olson, J.S. and J.A. Watts, 1982. "Major World Ecosystem
Complexes Ranked by Carbon in Live Vegetation." Oak
Ridge National Laboratory, Oak Ridge, Tennessee (map).
Olson, J.S., J.A. Watts, and L.J. Allison. 1985. Major
world ecosystem complexes ranked by carbon in live
vegetation: A Database. NDP-017, Carbon Dioxide
Information Analysis Center, Oak Ridge National
Laboratory, Oak Ridge, Tennessee.
References used in updating from WE1.2 (CDIAC Data Package
NDP-017) to WE1.4:
Barth, H. ----. Mangroves. In: D.N. Sen and K.S.
Rajpurohit (eds.), Contributions to the Ecology of
Halophytes. Dr. W. Junk, Publishers, The Hague (in press).
Bazilevich, N.I. 1974. Energy flow and biogeochemical
regularities of the main world ecosystems. pp. 182-
186. In: Structure, Functioning and Management of
Ecosystems. Centre for Agricultural Publishing and
Documentation, Wageningen, The Netherlands.
Bazilevich, N.I., and L. Ye Rodin. 1967. Maps of
productivity and the biological cycle in the Earth's
principal terrestrial vegetation types. Izv. Vses.
Geogr. Obschestva. 999(3):190-194.
Bazilevich, N.I., and L. Ye Rodin. 1971. Geographical
regularities in productivity and the circulation of
chemical elements in the Earth's main vegetation types.
Sov. Geogr.: Rev. and Transl. 12:24-53.
Bazilevich, N.I., and A.A. Titlyanova. 1980. Comparative
studies of ecosystem function. pp. 713-758. In: A.I.
Breymeyer and G.M. Van Dyne (eds.), Grasslands, Systems
Analysis and Man. Cambridge University Press,
Cambridge, United Kingdom.
Bazilevich, N.I., T.K. Gordeeva, O.V. Zalensky, L. Ye Rodin,
and J.K. Ross. 1969. Obschchie Teoreticheskie Problemi
Biologicheskoi Produktivnosti. Nauka, Leningrad.
Bazilevich, N.I. Pers. comm. 1968-1978. (1968 Symposium on
Roots Systems and Rhizosphere Organisms, Moscow,
Leningrad, Dushanbe; 1974 World Soils Congress, Moscow;
and her 1978 paper read by J. Olson to International
Ecological congress, the Hague, Netherlands.
Brown, S., and A.E. Lugo. 1981. The role of the
terrestrial biota in the global CO2 cycle. Preprints
26:1019-1025. In: Report of the Symposium on the
Carbon Dioxide Issue. American Chemical Society,
Division of Petroleum Chemistry, New York.
Br|nig, E.F. 1969. On the limits of vegetable productivity
in the tropical rain forest and the boreal coniferous
forest. J. Indian Bot. Soc. 46:314-322.
Duvigneaud, P. (ed.). 1971. Productivity of Forest
Ecosystems. UNESCO, Paris.
Gerasimov, E.P., et al. (eds.). 1964. Fiziko-geograficheskii
Atlas Mira (Physical-Geographic Atlas of the World).
USSR Academy of Science, Moscow. (also cited as Fillipov)
Goward, S. N., C. J. Tucker and D. G. Dye. 1985. North
American vegetation patterns observed with the NOAA-7
advanced very high resolution radiometer.
Vegetatio 64: 3-64.
Grubb, P.J. 1977. Control of forest growth and distribution
on wet tropical mountains. Ann. Rev. Ecol.
Syst. 8:83-107.
Henderson-Sellers, A., M. F. Wilson, G. Thomas, and R. E.
Dickinson. 1986. Current Global Land-Surface Data Sets
for Use in Climate-Related Studies. NCAR Technical
Notes, NCAR/TN-272+STR, National Center for Atmospheric
Research, Boulder, Colorado
Hobbs, R., and H. Mooney (eds.). 1990. Remote Sensing and
Biosphere Functioning. Ecological Studies.
Springer-Verlag, New York.
Koomanoff, V. A. 1988. Analysis of Global Vegetation
patterns: A Comparison Between Remotely Sensed Data and
a Conventional Map. Report 890201 of Laboratory for
Global Remote Sensing Studies, Geography, University of
Maryland, College Park MD.
K|chler, A.W. 1978. Natural vegetation map. pp. 16-17. In:
E.B. Espenshade, Jr., and J.L. Morrison (eds.), Goode's
World Atlas, 15th Edition. Rand McNally & Company, Chicago.
Loveland, T. R., J. W. Merchant, D. O. Ohlen, and J. F.
Brown. 1991. Development of a land-cover
characteristics database for the conterminous United
States. Photogram. Engineering and Remote
Sensing 57: 1453-1463.
M|ller, J.-F. 1992. Geographical distribution and seasonal
variation of surface emissions and deposition
velocities of atmospheric trace gases. J. Geophysical
Research 97: 3787-3804.
Rodin, L. Ye, and N.I. Bazilevich. 1967. Production and
Mineral Cycling in Terrestrial Vegetation. Oliver and
Boyd, Edinburgh. [Translated from L. Ye Rodin and N.I.
Bazilevich, 1965. Dynamics of the Organic Matter and
Biological Turnover of Ash Elements and Nitrogen in the
Main Types of the World Vegetation. Nauka, Moscow-
Leningrad (in Russian).]
Rodin, L. Ye, and N.I. Bazilevich. 1968. World
distribution of plant biomass. pp. 45-52. In: F.E.
Eckardt (ed.), Functioning of Terrestrial Ecosystems at
the Primary Production Level. UNESCO, Paris.
Rowe, J.S. 1972. Forests of Canada. Canadian Forestry
Service, Ottawa.
Schmith|sen, J. 1976. Atlas zur Biogeographie. Meyers
Grosser Physischer Weltatlas, Band 3, Bibliographisches
Institute, Manheim/Wien/Zurich, Switzerland.
Sollins, P., D.E. Reichle, and J.S. Olson. 1973. Organic
matter budget and model for a southern Appalachian
Liriodendron forest. EDFB/IBP-73/2. Oak Ridge National
Laboratory, Oak Ridge, Tennessee.
Specht, R.L. 1981. Structural attributes -- foliage
projective cover and standing biomass. In: A.N.
Gillison and D.J. Anderson (eds.), Vegetation
Classification in the Australian Region. Australian
National University Press, CSIRO, Canberra.
TECHNICAL REPORT
Jerry Olson
Global Patterns Company
Lenoir City, Tennessee
John J. Kineman, Mark A. Ohrenschall, and Jeffrey D. Colby
NOAA National Geophysical Data Center
Boulder, Colorado
PREFACE (Jerry Olson, April 22, 1992)
Several years spent before and after my 1985 early retirement
from Oak Ridge National Laboratory (ORNL) in Tennessee brought
together ideas and data on global patterns of ecological systems
(ecosystems). Patterns previously mapped by large computers
(Olson et al. 1983, 1985) are now made available, with
improvements, for personal computers (PCs).
Parts of 3 years in Europe (1985-88) and in Western States and
the Pacific (1988-91) helped improve my World Ecosystems
database. It was licensed for the National Center for Atmospheric
Research (NCAR), in Boulder, Colorado, to help set the parameters
for calculating air-landscape interaction in a new Community
Climate Model (CCM2, in NCAR's Climate and Global Dynamics
Division, CGD). Soon NCAR's Atmospheric Chemistry Division (ACD)
started using the 1989 version for estimating chemical
contributions from plants or fires to air (M|ller 1992).
In Boulder, I also started refining the half-degree resolution of
my previous worldwide grid (WE1.2: 720 columns x 360 rows of
picture elements or pixels to 10-minute resolution, initially for
a pilot project chosen for Africa by the World Data Center-A).
WDC-A's host, the National Geophysical Data Center of the
National Oceanic and Atmospheric Administration (NGDC/NOAA),
meanwhile was distributing other data, using the larger capacity
of compact disks.
During the beta test (outside checking) of NOAA's Global
Ecosystem Database (GED) in late 1991 I compared my mapping with
the index of greenness estimated from NOAA's meteorological
satellites and with GIS layers contributed by others. The
combined features WE1.4D show more than any data layer could
alone about global patterns. But they also emphasize a problem we
face repeatedly--striving for breadth of global coverage while
working toward depth of data layers, and eventually of
understanding, and of actions to improve our world. The grouping
of types in WE1.3A (section 2 below) is a step toward handling
such breadth and depth together.
Acknowledgment: I thank Lee Stanley of GPC and Mark Ohrenschall,
John Kineman, and David Hastings of NGDC/NOAA and WDC-A. We used
Idrisi Geographic Information System (GIS) software version 3.0
from Ron Eastman, Clark University, Worcester, Massachusetts,
01610; version 4.0 was not available during this work.
World Ecosystems WE is a Trademark and Global Patterns trade name
of Global Patterns Company of Roane County, Tennessee. Please
contact the author for further information or advanced or trial
versions of WE or further documentation. These working versions
of the World Ecosystems data-set are released for public testing
by GPC and for educational uses, with the understanding that it
is incomplete. Improvements by users may be offered to GPC for
"in kind" trade as part of the license fee for later versions
that are not released to the public domain, i.e. for research and
monitoring groups for whom the most current or tested version is
important for their work.
INTRODUCTION
This report explains how the World Ecosystem data-set version
1.4D (WE1.4D), and version 1.3A (WE1.3A) were produced from
previous versions, and how they describe land parts of Earth's
sphere of life, or Biosphere.
Detailed ecosystem types (0-73) in WE1.4D, at both 10-minute and
30-minute resolution, are related to the broader Main Groups of
ecosystem types (0-29) in WE1.3A, at 30-minute resolution. The
land Groups include forests of conifer, broadleaved, mixed, and
mostly tropical moist broadleaved (mostly evergreen) types. Other
mixtures include: grass-shrub, shrub-tree, semidesert and tundra,
field/woods and savanna, northern taiga, forest/field and dry
evergreen woods, wetlands, desert, succulent/thorn woods, crop
and settlements, and other (ice and fringe) types.
Since WE1.4D incorporates data at mixed resolutions (10 and 30
minutes lat/long), a separate data element (OWE14DR) is provided
with resolution codes for the main file (OWE14D). A special
palette file (OWE13A.PAL) is provided for the WE1.3A data, mostly
for convenience in recognition of some conventional color
assignments.
HISTORY OF THE OLSON DATA SET
The original version (1.0) of the Olson Ecosystems data set was
produced for the DOE Carbon Dioxide Information and Analysis
Center in Oak Ridge Tennessee by Jerry S. Olson, Julia A. Watts,
and Linda J. Allison. Reprints of the Primary Documentation from
this work are included on disc (see Reprint Files, above), and
should be consulted for detailed information on the creation of
these data and their use of estimating carbon content.
DATA UPDATING PROCEDURES FOR THE 1991 PROTOTYPE (WE1.4)
During the summer of 1989, Jerry Olson, Lee Stanley and research
assistants from the National Geophysical Data Center updated the
data set, "Major World Ecosystem Complexes Ranked by Carbon in
Live Vegetation: A Database." The results of this update have
been incorporated into Olson World Ecosystem WE1.4.
Data were revised at both 30 and 10 minute grid cells. Changes
were first made for the 30 minute data between 20 degrees West
and 70 degrees East. In addition, modifications were made to
limited portions of the United States data. Revisions were made
in the following ecological classes:
(1) tropical forest (type 33)
(2) polar deserts (type 69)
(3) ice (type 70)
(4) a few areas of mangrove/tropical swamp forest (type 72)
Updates for the United States were quite limited and affected
mostly the islands and coastlines of Alaska. To a lesser extent
changes were made along the western and eastern coastlines of the
lower 48 states.
Modifications at 10 minute resolution were numerous, but were
confined to the African continent and some coastlines. They
included changes in tropical montane complexes (type 28),
broadleaved evergreen forest types at high altitudes with cool
climates despite tropical latitudes (type 6), for example
Cameroon, Ethiopia, and other areas of East Africa and some in
the Atlas Mountains; mangrove tropical swamp forests (type 72),
and coastlines. Salt/soda flats (type 71) were not
systematically reviewed but received sample editing.
SUBSEQUENT EDITING FOR WE1.3A AND WE1.4D
Greenness indices from Advanced Very High Resolution Radiometer
(AVHRR) satellite data were used in certain desert and coastal
ecosystems. WE1.4D is a first step toward global resolution at
10 arc-minutes, replacing a test version called GOLSON in GED
Prototype (Version 0.1). Most of the main land cover complexes
are still effectively mapped at 30' (half-degree) scale in
WE1.4D. Ten arc-minute (10') improvements are mostly limited to
areas with low greenness indices from NOAA satellites and, in
Africa, to mangrove (type #72) and mountain complexes (#6, 28).
Conditions of high and intermediate greenness are important, but
have quite different meanings in different parts of the biosphere.
The quality of basic geographic data is very uneven from various
parts of the world. The computer media becoming available from
the NOAA National Geophysical Data Center/World Data Center-A
(WDC-A) and from Global Patterns Company (GPC) provide worldwide
coverage of many features that can be quantified for interpreting
changes of climate and atmospheric chemistry and many feedbacks on
life.
Ten-minute mapping of certain landscape types was donated in 1989
for NGDC's Africa Pilot Project for the IGBP, as one testing step
of GPC. Yet comparable refinement to 10' has not yet been done
evenly on any continent. The main patterns of the Olson World
Database for the NOAA CD-ROM in 1992 (GED) still have the same
half-degree resolution as the 1982 printed map of Olson and Watts
(~75 x 150 cm: enclosed with and documented by Olson et al. 1983,
and the 1985 re-release of the same report with computer-readable
data by Oak Ridge National Laboratory, ORNL). ORNL's Carbon
Dioxide Information and Analysis Center (CDIAC contact: Tom
Boden) will continue to distribute such maps, and the Olson et
al. (1985) Numeric Data Set 017, which is called WE1.2 in the
Global Patterns numbering series.
MAIN LANDSCAPE GROUPS AND ECOSYSTEM TYPES
The documentation file OWE14D.DOC gives the detailed category
legend for WE1.4D, modified slightly from that of the test
version (GOLSON) prepared in 1989 for testing in 1990-91. Closely
related types from WE1.4D are put in GROUPS, with Group numbers,
in the two sections below (A-main types, and B-selected "fringe"
types). These MAJOR GROUPS and numbers were used to create a new
30-minute data file (WE1.3A).
The narrower type numbers of WE1.4D are listed below each Major
Group description. Brackets [] enclose those legend numbers that
are still applied very unevenly. Braces {} foretell more
subdivisions, not yet used or even explained here. This list is
expanded slightly from previous ORNL reports (Olson et al. 1983,
1985), with additions between 0 and 19, and above 71. Readers
should consult GPC and references just cited for more
explanation. Readers should be forewarned that the Canadian
Centre for Remote Sensing (CCRS) compact disk will use an
intermediate version, renumbered to omit certain numbers that
were deliberately skipped here. Despite potential confusion in
numbering sequence between CCRS and other releases, the
three-LETTER mnemonic codes given below between old
(ORNL/GPC/NOAA) numbers and titles should clarify the match with
the ISY Global Change Encyclopedia (GeoScope).
The Group sequence itemized under Olson World Ecosystems WE1.3A is
arranged to take advantage of a standard IBM color palette for
either the Enhanced Graphic Adapter (EGA), or Video Graphics
Adapter (VGA). Thus, some color conventions (e.g. purple for
tropical moist forest) follow the UNESCO vegetation committee
suggestions or our older ORNL printed map (Olson and Watts 1982).
In most printing, black on the video screen (0) is replaced with
pale background for the ocean (e.g. pale cyan). A 16-color IDRISI
color palette is provided that retains the IBM color scheme with
this minor change to the background (OWE13A.PAL).
SOURCES
Improved mapping of the main ecosystem groups described imder Olson
World Ecosystems 1.3a, depends mainly on sources noted in this
report and Olson et al. (1983, 1985). Data from these sources
helped to improve and sometimes combine current information about
global patterns in ecological and landscape systems. WE1.3A and
WE1.4D represent examples of doing that using the sources and
history outlined below.
A. Maps and Source Data for Numeric Data Package-17
(NDP-017 = WE1.2)
1) Hummel-Reck Database (1978-79).
To aid studies of carbon cycling and climate at ORNL, Hummel and
Reck (1979) contributed a computer-readable data-set from General
Motors Laboratory. They had digitized a land-use map from Oxford
Economic Atlas (Jones 1972; also Cohen 1973). Their main
refinement was to add snow duration in one or two quarters of the
year (respectively "cool" and "cold") because it strongly
affected albedo, or reflectivity of the regional surface
affecting their climate models.
2) ORNL Map and Database (1978-85)
The Olson and Watts (1982) map resampled the modified Gall
projection of the Oxford Economic Atlas maps to half-degrees in
both latitude and longitude. Fig. 1 of Olson et al. (1983) shows
our splitting of several categories, especially "grazing lands"
and certain forests--especially Boreal (= taiga in Russian) and
mosaics of wooded/non-wooded types (see below). The
Russian-language Physical-Geographic Atlas of the World was cited
by Olson et al. (1983) after Gerasimov, Committee Chairman;
Fillipov, the operational Editor is cited as author of the same
atlas in NCAR's library in Boulder. Global vegetation map plates
were used previously; continental and USSR maps in some of the
revisions. Unpublished maps of the former Soviet Union from
Natalia Bazilivich are being digitized for NOAA databases by
Dmitri Varlyguin at Clark University.
Tropical/subtropical broadleaf humid forest includes extreme
"rainforest" and other somewhat seasonal (but not necessarily
deciduous) forms. In printing Olson and Watts (1982), blue
stipples were inserted over the purple to separate the former
type (#33) from the latter (#29). Hand-controlled (red line)
printing for mangroves on Olson and Watts (1972) used information
from any source. Yet half-degree pixels seem too coarse for
digitizing such a "fringe" type of the tropical/subtropical
land-saltwater margin. Its type (#72) was added for the ICSU/UNEP
project in 1989 when finer 10' pixels were first incorporated.
B. Early revisions by Olson (Global Patterns Company)
1) Europe (1985-88)
In October-November 1985, visits to the European Space Agency
(ESA) found much remote sensing information at laboratories in
Frascati and Ispra, Italy that was useful for ecosystem mapping.
From late May 1986 to 1987, cross-checking of maps in Sweden,
Belgium, Netherlands, Germany, Denmark, Norway, and Iceland
showed more possible refinements than have been used so far. In
July 1987, botanical fieldwork included Greece.
In April and June-July, 1988, two trips to Austria were added to
different routes in Sweden and Germany. At the International
Institute for Applied Systems Analysis (IIASA, at Laxenburg, near
Vienna), a data-set organized for analysis of acid deposition
quantified percentages of forest and total land, but for grid
cells of 0.5 degrees latitude x 1 degree longitude.
2) USA and Pacific (especially 1987-91)
Browsing in libraries and research laboratories in Asia,
Australia and New Zealand and the USA as well as Europe, showed
many more maps or articles than can be cited. Observations were
recorded on diverse base maps, many of which have schematic
overlays of green showing forest or tree cover. Some provide much
finer resolution than maps at a national to global level and also
suggest mosaic combinations: Forest/field has most continuity
between the main wooded parts of a patchwork. Field/woods has
more continuity between croplands, grasslands or other non-wooded
land categories than between forest/woodland patches (woodlots,
plantations, regrowing forests--commonly degraded by thinning,
grazing, or fire).
The triangle diagram shown below as Figure 1 (from Olson et al.
1983) ideally suggests 60 per cent nonwoods component for
separating Field/woods (above) from more evenly divided
Forest/field (40-60% nonwoods parts of the mosaic). Below that
level Olson divides broadleaved (or more concisely broadleaf)
forest or woodland (>75% of the woods stand area), from
broadleaf/conifer mixed woods (25-50% conifer), and a wider band
called conifer (>50% conifer).
Broadleaf gradations above or below 25% may be recognized but are
less commonly mapped. This tradition reflects common attribution
of more economic value to "softwood" forest products or of more
ecological/biophysical indicator value to percent conifer than
"hardwood" when in mixtures.
Where trees are sparse and/or dwarfed by cold, drought or other
stress, tall or dense scrub may be included in green overlay:
e.g. my groups 6 and 13. Olson's use of the term "woods," like
"the bush" in Australia, is a broad grouping, ranging from such
shrubby low growth to closed or open forest, of tall, medium, or
low stature.
The Cairns and Brisbane-Cooloola areas of Queensland, were
visited in September, 1990, and southeastern New South Wales in
October-December. As in Australia, New Zealand broadleaf woods
are mostly evergreens (southern beech, Nothofagus, and many
others). These could be separated in new types when the Olson
legend is being extended instead of being simplified as in this
report. {Type #77 will be for southern conifers (Podocarpus,
etc.) and/or planted Pinus alternating with broadleaved forest,
fjords, and glaciated peaks; #78 for forest that is tall (>30 m)
and/or dense (>70% foliage cover); #79 for other Eucalyptus
forest (30-70%.}
In Japan, several agencies are active in developing imagery for
sample localities. The Institute of Agro-environmental Research
in the science city Tsukuba (northeast of Tokyo) has data files
directly relevant to grazing and some tree crops as well as to
farming. Forestry records also have potential, and a national
land digital database (of land use and elevation) for planning
may be even more helpful, with pixels at a level of 10 km.
Much finer resolution is available in most countries of the world
but many questions remain about how to shift from "thinking
locally" to mapping and thinking globally.
Figure 1 Approximate relations of tree cover, regional percent
of non-tree formations, and major kinds of forest,
interrupted woods, and non-woods systems. (from
ORNL-DWG-81-9450, Oak Ridge National Laboratory)
METHODS
Showing just one land type or group for all nine 10' subcells in
one half-degree cell is commonly a simplification of the real
world. Yet heterogeneous regions may have one main category taken
as representative: a "winner" among competing nominee types. The
"runner-up" candidates may be winners in other cells or blocks.
The hope is that suitable proportions of all types used in
modeling the environment of a wider surrounding area, or the
whole planet, will average out. But wetland, mountain summit and
some other types often occur only in minor proportions. These may
be under-represented by weighting schemes in which "winner takes all."
Shifts toward finer resolution (e.g. from the 30' grid called
WE1.3A to 10' pixels of WE1.4D) are partly justified to overcome
or avoid such bias, as well as to refine boundary shapes. An
attempt was made to compensate by including
"representatives-at-large" among the mapped pixels--located in
places where the minority type is relatively important but not
necessarily the single commonest type or group.
During processing, a 30' cell may be temporarily flagged with a
minor type instead of losing the latter's identity and
approximate location completely. Later editing ought to show
which 10' subcell(s) deserve the less common labels when most
become reassigned like their commoner neighbors.
Techniques of map or database improvement include digitizing from
paper map sources or adapting global database information that is
already computer-readable. Both approaches are essential, but the
emphasis may shift as work progresses. Early editing of data has
used only a fairly small fraction of the possible refinements.
WE1.4D illustrates using data already digitized from satellites.
In 1989 the new digitizing of shore types (especially mangrove,
#72) and montane tropical complexes (#28 and/or #6) used the
ocean mask and altitude files from the FNOC Terrain data-set
[Chapter A13 in this volume], as improved by Roy Jenne and Dennis
Joseph of NCAR and John Kineman of NOAA. For Africa, the proper
elevation for montane rainforest was found to be only adjacent to
where it had been marked on Olson and Watts (1982). Altitude
data, first at 30' and then 10' resolution also clarified where
the Olson data had correctly included the peak or where it had
originally lacked enough location control to do so. The real
refinements at 10' are mostly limited to the few types just
mentioned and others which happen to have low greenness.
A. Editing from previous maps and diverse sources
For Africa, earlier 30' type locations were first refined
manually where available maps or references allowed. Then the 30'
grid was expanded 3-fold in both coordinates. That meant fewer
10' pixels needed to be fixed along the edges or within a 3x3
array of identical values--compared with editing all 9 values
independently. However, pending such follow-up checking at 10',
mountain labels may be left temporarily pinned on some pixels in
a valley or on a plain or plateau below altitudes defining the
real peak(s).
Much of the 1989 editing was done with Wordstar-2000, convenient
(though tedious) for dealing with single cells or data strings in
large files. Within Idrisi, substituting of new values for old
ones was also applied not only to points, rows, or columns, but
to rectangular arrays (commonly 3, 6, or 9 10' pixels wide, e.g.
in case 1, 2, or 3 of the half-minute pixels required large-area
correction).
However, the difficulty of mislocating points or boundaries,
relative to a sparse printed latitude-longitude net or landmarks,
had to be diminished first. This was accomplished by using
reference data already digitized in the GED Prototype disk.
B. Associating vegetation and greenness indexes
Indices of vegetation greenness from weather satellites of NOAA's
National Environmental Satellite, Data, and Information Service
(NESDIS) could be used in several ways. At NASA's Goddard Space
Flight Center (GSFC) and the University of Maryland, Koomanoff
(1988) used the old Olson et al. (1985: WE1.2) database to show
almost normally distributed variations of greenness for some type
groups (e.g. her Figs. 4.1 and 4.3). Skewness for other groups
(her Figs. 4.2-4.6) and more diversity for others (even distinct
peaks of greenness for her Figs. 4.7-4.16) indicated that the
lumped groups were heterogeneous, and individual cover types (as
originally mapped or refined later) may be significantly more
homogeneous.
Those and other Maryland analyses used early AVHRR indices
averaged over one whole year. Ignoring medium- and long- infrared
channels (#3-5), channel signals 1 and 2 (0.58-0.68 m visible;
0.73-1.10 m near-infrared) are commonly expressed as ratios of
difference/sum of reflectances Ch1 and Ch2: i.e.
XVI = (Ch2 - Ch1)/(Ch2 + Ch1) (1)
This unscaled index ranges from -0.1 for water, cloud or ice or
+/- 0.1 for nearly bare rock or soil to ~0.6 or 0.7 for dense,
vigorous vegetation. NOAA then derives integer values rescaled to
NDVI = (XVI+0.05)*350 + 15. (2)
Composite sampling and regridding discards values that are low
artificially (due to clouds, haze or dust). Extra bias toward
exceptionally green values by this procedure was decreased by
saving the last physically acceptable weekly value.
Second generation NOAA products include a weekly summary of equal
latitude - longitude grid cells (~16 km at the equator) for
latitudes 75N to 55S. Further NOAA quality control in developing
the NGDC monthly GED grids used here included (1) checking
registration accuracy against prominent geographic features and
(2) inspection for artifacts (e.g. bad scan lines and system
noise) and selection of images without co-located artifacts. Then
(3), both the low and high values were discarded from the
remaining weekly pixel values within each month, to eliminate
random noise evident in the weekly files. (4) A root-mean-square
average of the remaining "median" weekly values within each month
was computed for each pixel. (5) The images were then re-gridded
to a 10-minute grid using a spatially weighted average. (6) The
images used to process the World Ecosystems data-set were multi-
year averages of these monthly "generalized" images [provided in
Chapter A01 of this volume].
The GED compact disk also has corrections from Kevin Gallo for
pre-launch calibration, drift of the satellite or instrument, and
refinements related to solar zenith declination angles. Gallo's
file of weekly data masked the unusually low values of NDVI that
may be clouds in some places but glaciers or bare desert in
others. Monthly summary files from Gallo were not ready when the
work took place from December 1985 through November 1988 average
10' NDVI and GVI intervals.
Another kind of monthly AVHRR summary from Japan [Tateishi and
Kajiwara - see reference in Chapter A01 of this volume]
deliberately selects the greenest values for each month, and
therefore has least risk of cloud contamination of the image.
However, that advantage is traded off against highest
exaggeration of locally high selection (e.g. irrigated cropland;
dense, tall forest) or of seasonal trend favoring the summer end
of spring (or monsoon) season or autumn transition months.
Neither the Gallo or Japanese file is yet likely to be as
representative as Kineman's 3 year average used here.
After exploring data for particular months, annually averaged
3-month seasonal images (December-February, March-May,
June-August, September-November) and a 3-year average for all 12
months were produced. Another simplification was to establish
categories for the Monthly Generalized Global Vegetation Index
(MGV), each step matching 11 levels of the scaled MGV values
(which range from 0 to about 211). Our first questions concerned
lower intervals, i.e., low GVI Levels 0, 1, 2, 3: for MGV = 0-11,
12-22, 23-33, 34-44, respectively
Briefer inspection and analysis included:
medium GVI Levels 4, 5, 6: for MGV = 45-55, 56-66, 67-77;
and
high GVI Levels 7-11: for MGV > 77.
Clearly the latter deserve more attention. Lands in the high
range have most green foliage generating organic production,
nutrient recycling, and evaporation.
RESULTS
ECOSYSTEMS, VEGETATION, AND LANDSCAPES
1) Desert, cold, and water: low GVI landscapes
Investigation was made to determine the match between low
greenness index (MG-GVI, Chapter A01) and sand desert areas (type
50 on my legend), e.g. the Ergs of the Sahara. The lowest GVI
categories (Categories 1 and 2; MGV = 12-33) were associated with
salt flats or intermittent playa lakes (type #71), except for
some matches with water that were used to refine shore
delineation. Especially at the 10' pixel resolution, pixels or
clusters of pixels showed up in the depressions located from
altitude files (some below sea-level) or shown in many atlases.
A few very low index values also appeared on the highest Himalaya
Mountains and ranges on or west of the Tibetan Plateau. These may
represent glaciers (#70) or other very snowy landscapes that may
be missed or mislabelled #71, or else mixed with #8 as bare
"alpine" desert, along with the following true desert types.
The next lower level (Level 3; MGV = 34-44) in desert areas was
also not mainly in areas where the working database or extra maps
showed most dunes. A "mostly bare" desert category, already
defined as #8 was only sporadically used before 1991. It includes
some sand but commonly also rocky and fine-soil deserts with
little or no green cover. Independent cartography confirms many
such landscapes, but more checking is required, especially
outside Africa. In the Nubian, eastern and western Arabian, and
some Iranian deserts, areas originally mapped as grass-shrub
(Group 4, type #41, because of their designation as grazing lands
on the Oxford Economic Atlas) effectively belong in this bare or
true desert category in most years. Nomadic economies depend on
distant herd migrations to find the exceptional times and places
where grazers can be kept alive, even if not in thriving condition.
2) Gradients (Ecotones) of Intermediate Greenness (GVI Levels 4-6)
In the Sahara and elsewhere, some dune regions showed higher
index values for greenness (Levels 4 and 5) than the landscape
types of the preceding paragraphs. Seasonal or sporadic variation
in the index suggested ephemeral vegetation where occasional
rains occur. Alternatively, plants on the inter-dune depressions
could be sub-irrigated from rains previously intercepted along
the truly bare dune ridges. For part of the Kalahari desert, GVI
Level 6 (MGV = 67-77) overlapped areas of Kalahari sand that was
mapped as #50. It has not been confirmed whether this and a few
other areas represent just the upper range of a pixel variations
for sand desert and semidesert type, or if a "sand hill
grass/shrub" category should be created (#87 reserved), or if it
should be coded with existing shrub-grass types #50 or 51.
Oases (irrigated agriculture #37, Group 14) are likely to occur
more often as higher-resolution pixels are provided for. Most
seem too localized to show even at 10'--even when associated with
persistent marshy vegetation from natural seepage or drainage
(#45, Group 11).
In the USA, higher-resolution (~1.1 km) AVHRR imagery has been
treated in more detail by Loveland et al. (1991). They map
somewhat wider areas of effectively "bare" landscape and infer
(pers. com.) that these match deserts with only a few per cent of
green cover. Desert pixels of 10' and especially 30' typically
include mosaics of such nearly bare land plus shrub or
shrub-steppe or irrigated cover, and so are less likely to be
considered bare in the aggregate.
At high latitudes, the low sun angle, especially in winter,
limits use of AVHRR. Data are not even retained above 75 N
latitude. Nevertheless, a reasonable distinction between high
Arctic tundra (annual mean GVI Level 3) and low Arctic tundra
(GVI Level 4 or lower range of 5). The Wooded Tundra fringe
(mapped, illustrated and discussed in detail by Larsen 1989, for
North America) conversely has GVI mostly 4, less often (or less
clearly) 3. It needs to be much better defined at the 10'
resolution than the initial 30' mapping.
Within the Northern Taiga and other Boreal forest belts, there is
also an orderly progression of the GVI (from the MGV data-set),
despite numerous inclusions of locally lower GVI. The inclusions
of land-water mixtures (see section 4C) accounts for much of the
seeming "noise" that is related to lakes and mires but these are
not yet provided for in WE1.4D. Analyzing how the whole complex
can be resolved, with better resolution from Local Area Coverage
(LAC) AVHRR and still finer satellite imagery, will be a major
contribution of the planned BOREAS project of NASA and other
sponsors.
REFERENCES
ORIGINAL REFERENCES
Extensive references for the original work are given in Olson et
al. (1983) and its excerpt (scanned images of this reference are
provided on the CD-ROM -- see Primary Documentation, above). All
references related to the present work are listed under
Additional References, above.
REFERENCES FOR RECENT UPDATES AND COMPARISONS
Cohen, S. (ed.). 1973. The Oxford World Atlas.
Oxford University Press, London.
Goward, S. N., C. J. Tucker and D. G. Dye. 1985. North American
vegetation patterns observed with the NOAA-7 advanced very high
resolution radiometer. Vegetatio 64: 3-64.
Henderson-Sellers, A., M. F. Wilson, G. Thomas, and R. E.
Dickinson. 1986. Current Global Land-Surface Data Sets for Use in
Climate-Related Studies. NCAR Technical Notes, NCAR/TN-272+STR,
National Center for Atmospheric Research, Boulder, Colorado
Hobbs, R., and H. Mooney (eds.). 1990. Remote Sensing and
Biosphere Functioning. Ecological Studies. Springer-Verlag,
New York.
Hummel, J.R., and R.A. Reck. 1979. A global surface albedo model.
J. Appl. Meteorol. 18:239-253.
Jones, D.B. (ed.). 1972. Oxford Economic Atlas of the World, 4th
Ed. Oxford University Press, London.
Koomanoff, V. A. 1988. Analysis of Global Vegetation patterns: A
Comparison Between Remotely Sensed Data and a Conventional Map.
Report 890201 of Laboratory for Global Remote Sensing Studies,
Geography, Univ. of Maryland, College Park MD.
Larson, J.A. 1989. The northern forest border in Canada and
Alaska: Biotic communities and ecological relationships.
Ecological Studies 70. Springer-Verlag, New York.
Loveland, T. R., J. W. Merchant, D. O. Ohlen, and J. F. Brown.
1991. Development of a land-cover characteristics database for
the conterminous United States. Photogram. Engineering and Remote
Sensing 57:1453-1463.
Olson, J.S. 1992. Global changes and resource management.
ASPRS/ACSM/RY92 Technical Papers, Volume 1. P. 32-42.
*owe13a_help
DATA FILE DESCRIPTION
DATA ELEMENT: World Ecosystems (WE1.3A)
STRUCTURE:
Raster Data File:30-minute 720x360 GED grid (see User's Guide)
SERIES:
none
SPATIAL META-DATA:
OWE13A.DOC
file title : Olson World Ecosystems Version 1.3A
data type : byte
file type : binary
columns : 720
rows : 360
ref. system : lat/long
ref. units : deg
unit dist. : 1.0000000
min. X : -180.0000000
max. X : 180.0000000
min. Y : -90.0000000
max. Y : 90.0000000
pos'n error : unknown
resolution : 0.5000000
min. value : 0
max. value : 29
value units : classes
value error : unknown
flag value : none
flag def'n : none
legend cats : 30
category 0 : 0 OCEAN/SEA Oceans, Seas (including Black Sea)
category 1 : 1 CONIFOR Conifer Forest
category 2 : 2 BRODLFOR Broadleaf Forest: temperate, subtropical
drought
category 3 : 3 MIXEDFOR Mixed Forest: conifer/broadleaf; so. Boreal
category 4 : 4 GRASSHRB Grassland +/- Shrub or Tree
category 5 : 5 TROPICFR Tropical/subtr. Forest: montane,
seasonal, rainforest
category 6 : 6 SCRUBWDS Scrub +/- Woodland &/or fields
(evergreen/decid.)
category 7 : 7 SEMIDTUN Semidesert shrub/steppe; Tundra (polar,
alpine)
category 8 : 8 FLDWDSAV Field/Woods complex &/or Savanna,
tallgrass
category 9 : 9 NORTAIGA Northern Boreal Taiga woodland/tundra
category 10 : 10 FORFDREV Forest/Field; Dry Evergreen broadleaf woods
category 11 : 11 WETLAND Wetlands: mires (bog/fen); marsh/swamp
+/- mangrove
category 12 : 12 DESERTS Desert: bare/alpine; sandy; salt/soda
category 13 : 13 SHRBTRST Shrub/Tree: succulent/thorn
category 14 : 14 CROPSETL Crop/Settlement (irrigated or not)
category 15 : 15 CONIFRFC Conifer snowy Rainforest, coastal
category 16 : 16 not used
category 17 : 17 not used
category 18 : 18 not used
category 19 : 19 MANGROVE Mangrove/wet forest/thicket + tidal flat
category 20 : 20 WALANCST Water (~51-90%) & Land,
Coast/hinterland complexes
category 21 : 21 not used
category 22 : 22 not used
category 23 : 23 ISLFRING Island or Fringe land (91-99% water)
category 24 : 24 LANDWATR Land/Water (~21-50%) complexes
category 25 : 25 ICE Ice: Glaciers & emerging rocks near fringe
category 26 : 26 POLARDES Polar Desert
category 27 : 27 WTNDMHTH Wooded Tundra Margin; Heath/moorland
category 28 : 28 not used
category 29 : 29 INLDWATR Inland Water bodies
(including Caspian Sea)
comment : 14 Major Ecosystem classes and 8 fringe classes,
plus Ocean
lineage : Derived from WE1.4D by aggregating classes
to .5-degree
completeness: .5-degree coverage complete for land areas,
based on WE1.4D
consistency : All values represent spatial dominance at .5-degree
ATTRIBUTE META-DATA:
NONE
NOTES:
(1) 14 Major Ecosystem classes and 8 fringe classes,
plus Ocean
(2) Derived from WE1.4D by editing, aggregating classes,
and modal filtering to 0.5-degree. Also used FNOC %
water for fringe classes (FNOCWAT in Chapter A13).
(3) 0.5-degree coverage complete for land areas,
based on WE1.4D
(4) All values represent spatial dominance at 0.5-degree
MAJOR GROUP DESCRIPTION (OWE13A)
A. Main LAND GROUPS of Ecosystem Complexes (1-14):
(0) SEAS Oceans, Mediterranean Sea, Black Sea
FORESTS:
(1) CONIFOR CONIfer FORest here stands for all complexes
dominated by coniferous trees (evergreen or
deciduous, in snowy climate or not), except for
the coastal fringe below (i.e. group 15 type 20
in section 2B):
WE1.4D classes grouped here:
#21 MBC Main Boreal Conifer forest, closed or open;
#22 SNB Snowy Non-Boreal conifer forest;
#27 NSC Non-Snowy Conifer forest.
(2) BRODLFOR BROADLEAF FORest of temperate and seasonally dry
~subtropical (rain-green or partly
drought-deciduous) groups (#32 for the latter).
WE1.4D classes grouped here:
#25 SDF Snowy Deciduous Forest, i.e. summergreen (=
cold-deciduous) types;
#26 TBF Temperate Broadleaf Forest: deciduous,
semideciduous, and some temperate-subtropical
broadleaf evergreen types that are least active
in winter. (The latter could be shifted to type
#6 and perhaps to group 5 later, in order to get
more broadleaf evergreen types together.)
[#6] TBE Temperate/Tropical-montane Broadleaf Evergreen
covers warm temperate or montane broadleaf
evergreen forest, so far mostly in Africa where
our pilot test for 10' started.
#32 RGD Rain-green (Drought-deciduous) or very seasonal
dry evergreen forests to open woodlands, very
frequently burned.
(3) MIXEDFOR MIXED FORest here includes not only
deciduous-conifer mixtures, within stands and as
mosaics over the landscape, but many gradations
toward broadleaved evergreen. Conifers are
common, but often uneven; native and/or planted.
WE1.4D classes grouped here:
#23 CDF Conifer/Deciduous Forest: snow persisting in
winter;
#24 TBC Temperate Broadleaf/Conifer forest: with
deciduous and/or evergreen hardwood trees;
[#54] TER Temperate Evergreen Rainforests, e.g. in
Chile.
For simplicity, southern Boreal (= taiga in Russian) deciduous
mixtures with aspen, birch, and/or larch as well as evergreen
conifers are included here:
#60 SDT Southern Dry Taiga, or similar aspen/birch with
northern and/or mountain conifers;
#61 LT Larch Taiga with deciduous conifer.
(4) GRASSHRB GRASS-SHRUB-HERB complexes vary widely in
structure, precipitation and temperature. Few
trees (mostly sparse, planted, or
streamside/ravine patches, if any) break the
open horizon. Cropland, especially dryland
cereal grains or local irrigation, can be
important economically, but is a minor fraction
of total land cover/use in most years.
WE1.4D classes grouped here:
[#2] SSG Short or Sparse Grass/shrub of semiarid climates;
#40 CGS Cool Grass/Shrub, snowy in most years
#41 MGS Mild/warm/hot Grass/Shrub,
#42 CSM Cold Steppe/Meadow, +/- larch woods (in Siberia),
scrub (Bering sea) or tundra (Tibetan highland).
(This class might be regrouped with the tundra
margin group, especially when better defined at
10' resolution.)
(5) TROPICFR = TROPICAL/subtropical moist or Broadleaf Humid
FORest. Most are evergreen but deciduous forms
increase in the subtropics, especially with
extreme monsoon droughts.
WE1.4D classes grouped here:
#28 TMC Tropical Montane Complex, typically evergreen,
including dwarfed ("elfin") forest, opening to
grass, or tall or short forbs (puna, paramo)
above timberline;
#29 TBS Tropical Broadleaf Seasonal, with dry or cool
season;
#33 TRF Tropical RainForest.
(6) SCRUBWDS SCRUB-WOODS Complexes, often with grass or crops
locally, tend to have a dry season and/or
pronounced fire. Trees are not always rare, but
may be short or open-grown. The bigger ones tend
to cluster on favorable substrate or terrain, or
near places where fire starts or spreads less
often.
WE1.4D classes grouped here:
{#16} BES Broadleaf Evergreen Scrub, commonly with
the following
#46 MES Mediterranean-type Evergreen (mostly) broadleaved
Scrub and forest relics;
#47 DHS Dry or Highland Scrub or open woodland.
(7) SEMIDTUN SEMIDesert or TUNdra. Open shrub or shrub-steppe
(low grass) of very dry regions may grade into
the preceding groups 5 and 6. Dwarf-shrub or
grass-like (graminoid) tundra tends to occur
above the altitudes or latitudes of local tree
line (see groups 9 and 27 below).
WE1.4D classes grouped here:
#51 SDS SemiDesert/Desert Scrub/succulent/sparse grass;
#52 CSS Cool/cold Shrub Semidesert/steppe;
#53 TUN Tundra (polar, alpine).
(8) FLDWDSAV FIELD/WOODS mosaic or SAVANNA. Tall grass or
crops together often cover more area than forest
or woodland in Field/woods:
WE1.4D classes grouped here:
#55 SFW Snowy Field/Woods complex;
#58 FWG Field/Woods with Grass and/or Cropland;
#43 SGW Savanna/Grass, Seasonal Woods: Trees or shrubs
above grass groundcover may be interspersed on
many scales in savanna belts of varying drought
duration and high fire frequency.
(9) NORTAIGA NORThern TAIGA or SUBALPINE narrow-crowned sparse
conifer and/or dwarf deciduous
tree/scrub/meadow/wetland mosaics
WE1.4D classes grouped here:
#62 NMT Northern or Maritime Tiaga typifies a wide
latitude belt or a narrow altitude belt above
denser forest or woodland.
{#62a} or a new number might distinguish the subalpine
mosaics at lower latitudes.
(10) FORFDREV FOREst/FIELD or DRy EVergreen mixtures commonly
have much broadleaf tree and tall shrub, but
conifers pure or mixed (as in group 3) may be
important. Nonwooded land is also interspersed,
especially where low forest or open woodland is
cleared and burned for crops or grazing, and
where drought or seasonally wet soil limits
establishment or the mature height and density
of trees.
WE1.4D classes grouped here:
#56 FFR Forest/Field complex with Regrowth after
disturbances, mixed with crops and/or other
non-wooded lands;
#57 SFF Snowy Forest/Field, commonly openings are pasture
and/or mires;
#48 DEW Dry Evergreen Woodland or low forest, mapped
mostly in interior Australia and South America.
(11) WETLAND Mires, Marshes, or Swamps.
WE1.4D classes grouped here:
#44 MBF Mires include peaty Bogs and Fens (mostly in high
latitudes;
#45 MOS Marsh or Other Swampy wetlands include various
transitions to or mixtures with trees.
(Also see group 19 below for #72 mangrove, digitized first for
Africa in GED.)
(12) DESERTS ~Mostly Bare, Sandy, or Salt-Soda deserts grade
into semideserts (group 7); both have patches
interspersed within the other and within dry
grassland.
WE1.4D classes grouped here:
#8 DMB Desert, Mostly Bare stone, clay or sand;
#50 SDB Sand Deserts, partly Blowing Dunes;
#71 SSF Salt/Soda Flats: desert playas, occasionally with
intermittent lakes.
(13) SHRBTRST SHRUB-TRee, Succulent or Thorn thickets are
alternatives to the tree/grass life form
strategy response to tropical droughts. Two
droughts per year may occur near the equator as
rain belts shift north or south; or droughts may
persist with little or no relief as in eastern-
most Brazil.
WE1.4D classes grouped here:
#59 STW Succulent and Thorn Woods or scrub is widespread;
#49 HVI Hot Volcanic Islands presently is used in the
Galapogos Islands, which have local denser
forest on some older lava flows but wide areas
of sparse cover on recent lavas.
(14) CROPSETL CROP/SETTLement/Commercial Complexes include rice
and other irrigated cropland (#36; 37-39) and
other cropland, with interspersed villages,
cities, or industrial areas (#30, 31).
WE1.4D classes grouped here:
#30 CFS Cool Farmland and Settlements, more or less
snowy;
#31 MFS Mild-hot Farmland and Settlements;
#36 PRA Paddy Rice and Associated land mosaics;
#37 WCI Warm-hot Cropland, Irrigated extensively;
#38 CCI Cool Cropland with Irrigation of variable extent;
#39 CCP Cold Cropland and Pasture, irrigated locally.
B. Ice, Land-water and Other FRINGES (15-29):
Glacier ice and the following mostly narrow fringe types can be
distinguished on a separate video display (pagedown image with
Idrisi software using the same color palette as for 0-14). Or a
palette with more colors can be defined by the user.
(15) CONIFERFC CONIFER RAINForest FRinge Coast is here applied
to snowy conifer rainforest in a narrow band
from the southern Alaska to coastal Washington
and Oregon:
WE1.4D classes grouped here:
#20 SRC Snowy, Rainy Coastal Conifer
(16-18) temporarily reserved for later uses.
(19) MANGROVE is separately digitized only for Africa.
WE1.4D classes grouped here:
#72 MSM Mangrove and non-saline Swamps and tidal
Mudflats; may also be common within group 5, 7
or 10.
(20) WALANCST WAter/LANd mixtures & COASTal SYSTems. Previously
mapped mostly as Coast/hinterland complexes:
WE1.4D classes grouped here:
#65 CNW Coastal: NorthWest quadrant near most land;
#66 CNE Coastal: NorthEast quadrant near most land;
#67 CSE Coastal: Southeast quadrant near most land;
#68 CSW Coastal: Southwest quadrant near most land;
{80} CWL Coastal Water/Land (~51-90% water) besides those
oriented per #65-68: beach and various dunes,
cliff/rock/fjord, and delta complexes as well as
inland types are common. Locating such kinds of
coastal ecosystems and landscapes are
refinements for the future.
(21-22) reserved for later use.
(23) ISLFRING ISLand-shore water FRINGes really just mean >90%
water. But in practice this applies mostly to
small islands. Edges of islands or mainland may
occur, with near-shore ocean or inland water
bodies:
WE1.4D classes grouped here:
#73 ISL Islands and shore waters in oceans and/or lakes.
(24) LANDWATR LAND-WATER combinations, with water ~31-50%,
include not only additional coastal pixels with
more land but also many 10' land pixels with
small lakes or wide rivers or reservoirs.
WE1.4D classes grouped here:
{#74-76} in GPC's extended legend are expected to include
complexes with lake and wetland mixtures,
alluvial wildlands, floodplain and/or shoreline
farms and settlements or ports.
(25) ICE is mostly in Antarctica (#17, or new #12 when the long
legend is revised) or Greenland, or in smaller
glaciers (#70).
WE1.4D classes grouped here:
#17 ICE Antarctic glacial cap [may be #12 in future
versions];
#70 GLA Glaciers in polar or alpine complex, with rock
fringes.
(26) POLARDES POLAR "DESert" spans small but somewhat diverse
areas where precipitation is low and/or rarely
melted as water.
WE1.4D classes grouped here:
#69 PDL Polar "Desert" with rock Lichens, locally
abundant or productive (even between mineral
grains) but provide little food. Animals depend
on nearby waters, and import some residues from
their food chains for localized humus.
(27) WTNDMHTH Wooded TUNDra or Moorland-HEATH types
WE1.4D classes grouped here:
#63 WTM Wooded Tundra Margin or mountain scrub/meadow
#64 HMW Heath and Moorland, Wild or artificially managed,
as by burning and/or grazing. Moorland
conventionally includes wetland (#44-45)
interspersed with drier heath, with dwarfed or
taller, commonly dense scrub on peat or sand.
(28) reserved for later use.
(29) INLDWATR INLAND WATER here refers to specific lake body
pixels in which land is negligible. Otherwise
not distinguished from #0 in long legend.
*owe14d_help
DATA FILE DESCRIPTION
DATA ELEMENT: World Ecosystems (WE1.4D)
STRUCTURE:
Raster Data File: 10-minute 1080x2160 GED grid (see User's Guide)
SERIES:
none
SPATIAL META-DATA:
OWE14D.DOC
file title : Olson World Ecosystem Classes Version 1.4D
data type : byte
file type : binary
columns : 2160
rows : 1080
ref. system : lat/long
ref. units : deg
unit dist. : 1.0000000
min. X : -180.0000000
max. X : 180.0000000
min. Y : -90.0000000
max. Y : 90.0000000
pos'n error : unknown
resolution : mixed .167|.5
min. value : 0
max. value : 73
value units : classes
value error : unknown
flag value : none
flag def'n : none
legend cats : 74
category 0 : Waters, including Ocean and Inland Waters
category 1 : 1 CCX City complexes--being added for MM4
type cat.1
category 2 : 2 SSG Short or Sparse Grass/shrub of
semiarid climates
category 3 : 3 Not used
category 4 : 4 Not used
category 5 : 5 Not used
category 6 : 6 TBE Temperate/Tropical-montane Broadleaf
Evergreen covers warm temperate or montane broadleaf
evergreen forest [Africa only]
category 7 : 7 Not used
category 8 : 8 DMB Desert, mostly bare stone, clay or sand
category 9 : 9 Not used
category 10 : 10 Not used
category 11 : 11 Not used
category 12 : 12 Not used
category 13 : 13 Not used
category 14 : 14 Not used
category 15 : 15 Not used
category 16 : 16 {BES} Broadleaf Evergreen Scrub, commonly
with #46 and #47
category 17 : 17 ICE Antarctic ice cap
category 18 : 18 Not used
category 19 : 19 Not used
category 20 : 20 SRC Snowy, rainy coastal conifer
category 21 : 21 MBC Main Boreal conifer forest, closed or open
category 22 : 22 SNB Snowy non-Boreal conifer forest
category 23 : 23 CDF Conifer/deciduous, snow persisting in
winter
category 24 : 24 TBC Temperate Broadleaf/Conifer forest:
with deciduous and/or evergreen hardwood trees
category 25 : 25 SDF Snowy Deciduous Forest, i.e.
summergreen (=cold-deciduous) types
category 26 : 26 TBF Temperate broad-leaf forest: deciduous,
semideciduous, and some temperate-subtropical
broadleaf evergreen types that are least active in
winter.
category 27 : 27 NSC Non-snowy conifer forest
category 28 : 28 TMC Tropical montane complexes, typically
evergreen, including dwarfed ("elfin") forest,
opening to grass, or tall or short forbs (puna, paramo)
category 29 : 29 TBS Tropical Broadleaf Seasonal, with dry
or cool season
category 30 : 30 CFS Cool Farmland & Settlements, more or
less snowy
category 31 : 31 MFS Mild/hot farmland & settlements
category 32 : 32 RGD Rain-green (drought-deciduous) or very
seasonal dry evergreen forests to open woodlands,
very frequently burned.
category 33 : 33 TRF Tropical RainForest
category 34 : 34 Not used
category 35 : 35 Not used
category 36 : 36 PRA Paddy rice and associated land mosaics
category 37 : 37 WCI Warm/hot cropland, Irrigated
extensively
category 38 : 38 CCI Cool cropland with Irrigation of
variable extent
category 39 : 39 CCP Cold cropland and pasture, irrigated
locally
category 40 : 40 CGS Cool grass/shrub, showy in most years
category 41 : 41 MGS Mild/warm/hot grass/shrub
category 42 : 42 CSM Cold steppe/meadow +/- larch woods (in
Siberia), scrub (Bering sea) or tundra (Tibetan
highland)
category 43 : 43 SGW Savanna/Grass, seasonal woods: Trees
or shrubs above grass groundcover may be interspersed
on many scales in savana belts of varying drought
duration and high fire frequency
category 44 : 44 MBF Mires include peaty Bogs and Fens
(mostly in high latitudes)
category 45 : 45 MOS Marsh or other swampy wetlands include
various transitionsto or mixtures with trees
category 46 : 46 MES Mediterranean-type Evergreen (mostly)
broadleaved Scrub and forest relics
category 47 : 47 DHS Dry or highland scrub, or open woodland
category 48 : 48 DEW Dry Evergreen Woodland or low forest,
mapped mostly in interior Australia and South America
category 49 : 49 HVI Hot-mild volcanic "islands"
(Galapogos), with local denser forest on some older
lava flows but wide areas of sparse cover on recent
lavas)
category 50 : 50 SDB Sand Desert, partly Blowing dunes
category 51 : 51 SDS SemiDesert/Desert
Scrub/succulent/sparse grass
category 52 : 52 CSS Cool/cold shrub semidesert/steppe
category 53 : 53 TUN Tundra (polar, alpine)
category 54 : 54 TER Temperate Evergreen Rainforest (e.g.,
in Chile)
category 55 : 55 SFW Snowy Field/Woods complex
category 56 : 56 FFR Forest/Field complex with Regrowth
after disturbances, mixed with crops and/or other non-
wooded lands
category 57 : 57 SFF Snowy Forest/Field, commonly openings
are pasture and/or mires
category 58 : 58 FWG Field/Woods with Grass and/or Cropland
category 59 : 59 STW Succulent and Thorn Woods or scrub is
widespread
category 60 : 60 SDT Southern Dry Taiga or similar
aspen/birch with northern and/or mountain conifers
category 61 : 61 LT Larch Taiga with deciduous conifer
category 62 : 62 NMT Northern or maritime taiga typifies a
wide latitude belt or a narrow altitude belt above
denser forest or woodland
category 63 : 63 WTM Wooded tundra margin or mountain
scrub/meadow)
category 64 : 64 HMW Heath and Moorland, Wild or
artificially managed, as by burning and/or grazing.
Can include wetland (#44-45) interspersed with drier
heath, with dwarfed or taller, commonly dense scrub
on peat or sand
category 65 : 65 CNW Coastal: NorthWest quadrant near most land
category 66 : 66 CNE Coastal: NorthEast quadrant near most land
category 67 : 67 CSE Coastal: SouthEast quadrant near most land
category 68 : 68 CSW Coastal: SouthWest quadrant near most land
category 69 : 69 PDL Polar desert with rock Lichens, locally
abundant or productive (even between mineral grains)
but provide little food. Animals import residues for
localized humus
category 70 : 70 GLA Glaciers in polar or alpine complex,
with rock fringes
category 71 : 71 SSF Salt/soda flats desert playas,
occasionally with intermittent lakes
category 72 : 72 MSM Mangrove and non-saline swamps and
tidal Mudflats [Africa only]
category 73 : 73 ISL Islands and shore waters in oceans
and/or lakes [Elba Island]
comment : Olson's 72 World Ecosystem classes (not all
classes used)
comment : This version is a refinement of WE1.4. Changes include:
comment : (1) Trimmed desert and bare ground using AVHRR/GVI data
comment : (2) Trimmed coastline areas using elevation data
comment : (3) Added Elba Island
comment : (4) Corrected mis-located tropical montane classes
comment : (5) Other miscellaneous corrections
comment : This data file contains mixed resolutions.
comment : The data file named OWE14R provides an overlay to
determine
comment : which cells contain 10-minute and 30-minute data.
lineage : Derived from Olson World Ecosystems Ver 1.4 (prototype)
lineage : Version 1.4 was an extension of Ver 1.2 previously
lineage : distributed by CDIAC, Oak Ridge National Laboratory
completeness: 10-minute updates are incomplete. Complete coverage
completeness: of land areas is achieved by a mix of 10-min and
consistency : 30-min classes. Mixed spatial dominance at 10-minutes
consistency : and 30- minutes.
ATTRIBUTE META-DATA:
NONE
NOTES:
(1) Data represent mixed 0.5-degree and 10-minute classes
(see WE1.4DR)
(2) In refining low vegetation classes (desert, etc.) an
average of the monthly MG-GVI data over 3 years was
used. The actual multi-year average is not provided
for intercomparison, however it can easily be
reproduced from the Characteristic Month Averages in
Chapter A01.
(3) In refining coastal values, an "ocean mask" was used,
which was derived from the FNOC elevation data-set.
Since this mask itself may have errors, the mask is
provided with the FNOC data-set for intercomparison
(see Chapter A13).
(4) comment: not all classes are used.
(5) comment: This version is a refinement of WE1.4.
Changes include:
(a) Trimmed desert and bare ground using AVHRR/GVI data
(b) Trimmed coastline areas using elevation data
(c) Added Elba Island
(d) Corrected mis-located tropical montane classes
(e) Other miscellaneous corrections
(6) The data file named OWE14R provides an overlay to
determine which cells contain 10-minute and 30-minute
data.
(7) Derived from Olson World Ecosystems Version 1.4
(prototype)
(8) Version 1.4 was an extension of Version 1.2, previously
distributed by CDIAC, Oak Ridge National Laboratory
(9) 10-minute updates are incomplete. Complete coverage of
land areas is achieved by a mix of 10-min and 30-min
classes.
*owe14dr_help
DATA FILE DESCRIPTION
DATA ELEMENT: World Ecosystems (WE1.4DR)
STRUCTURE:
Raster Data File:10-minute 1080x2160 GED grid (see User's Guide)
SERIES:
none
SPATIAL META-DATA:
OWE14DR.DOC
file title : Resolution codes for OWE1.4D
data type : byte
file type : binary
columns : 2160
rows : 1080
ref. system : lat/long
ref. units : deg
unit dist. : 1.0000000
min. X : -180.0000000
max. X : 180.0000000
min. Y : -90.0000000
max. Y : 90.0000000
pos'n error : unknown
resolution : 0.1666667
min. value : 0
max. value : 2
value units : classes
value error : unknown
flag value : none
flag def'n : none
legend cats : 3
category 0 : 30' data
category 1 : 10' edits
category 2 : 10' residuals from edited regions
lineage : From edits of WE1.4D
ATTRIBUTE META-DATA:
NONE
NOTES:
(1) Produced from edits of WE1.4D
(2) This layer is provided as an index or overlay to
determine which values in the WE1.4D have 10-minute
spatial meaning and which have 30-minute spatial
meaning. It can be used to divide the 10-minute and 30-
minute data into separate data layers, if desired.
(3) "Residuals" are 10-minute cells within a 30-minute
major ecosystem type cell that were "orphaned" when
other cells in the 30-minute region were edited. They
are coded as having 10-minute spatial interpretation
only if they cover less than 1/2 the 30-minute cell
(i.e., "non-modal")
DATA ELEMENT: SOURCE ELEMENT: World Ecosystems (WE1.4)
STRUCTURE:
Raster Data File:10-minute 1080x2160 GED grid (see User's Guide)
SERIES:
none
SPATIAL META-DATA:
OWE14.DOC
file title : Olson Ecosystem Classes Version 1.4
data type : byte
file type : binary
columns : 2160
rows : 1080
ref. system : lat/long
ref. units : deg
unit dist. : 1.0000000
min. X : -180.0000000
max. X : 180.0000000
min. Y : -90.0000000
max. Y : 90.0000000
pos'n error : unknown
resolution : 0.1666667
min. value : 0
max. value : 72
value units : classed
value error : unknown
flag value : none
flag def'n : none
legend cats : 73
category 0 :Waters, including Ocean and Inland Waters
category 1 :CCX City complexes--being added for MM4 type cat.1
category 2 :SPV Shortgrass prairie variant of 40 or 41
category 3 :Not used
category 4 :Not used
category 5 :Not used
category 6 :TMT Temperate to montane tropical (major
forest and woodland)
category 7 :Not used
category 8 :DMB Desert, mostly bare
category 9 :Not used
category 10 :Not used
category 11 :Not used
category 12 :Not used
category 13 :Not used
category 14 :Not used
category 15 :Not used
category 16 :Not used
category 17 :ICE Antarctic ice, land or grounded shore ice
category 18 :Not used
category 19 :Not used
category 20 :SRC Snowy, rainy coastal conifer (with alder etc.)
category 21 :MBC Main Boreal conifers
category 22 :SNB Snowy non-Boreal conifer forest
category 23 :CDS Conifer/deciduous, snow persisting in winter
category 24 :SED (semi) Evergreen/deciduous, little/no snow
category 25 :SDF Similar to 26, snow persisting in winter
category 26 :TDF Temperate ~deciduous forest, little or no snow
category 27 :NSC Non-snowy conifer forest
category 28 :TMC Tropical montane complexes (tree & other)
category 29 :TSF Tropical seasonal forest
(evergreen...) (major forest/woodland)
category 30 :CFS Cool farmland & settlements (~snowy)
category 31 :MFS Mild/hot farmland & settlements
category 32 :RGD Rain-green (drought-deciduous) (major
forest and woodland)
category 33 :TRM Tropical rainforest (major forest and woodland)
category 34 :Not used
category 35 :Not used
category 36 :PRA Paddy rice and associated lands (part anaerobic)
category 37 :WCI Warm/hot crops with extensive irrigation
category 38 :CCI Cool crops with irrigation (variable extent)
category 39 :CCP Cold crops, pasture, irrigation ~local
category 40 :CGS Cool (snowy) grass/shrub (including much 2)
category 41 :MGS Mild/warm/hot grass/shrub
category 42 :CSM Cold steppe/meadow +/- larch, scrub
category 43 :STB Savanna, mostly tallgrass + bush fallow/woods
category 44 :MAG Mire (acid bog &/or groundwater-fed fen), cold
peatland (or muck): sphagnum, grass-like,
and/or dwarf shrub or mire tree vegetation
category 45 :MOS Marsh or other swamp (warm-hot)
salty/freshwater marsh, thicket, ~flooded woods
category 46 :MET Mediterranean evergreen tree/scrub (winter rain)
category 47 :ODH Other dry or highland scrub/tree (juniper, etc.)
category 48 :EAQ Eucalyptus or Acacia, quebracho, saxaul
category 49 :HVI Hot-mild volcanic "islands" (variable vegetation)
category 50 :SDB Sand desert, partly blowing
category 51 :ODS Other desert and semidesert
category 52 :CSS Cool/cold shrub semidesert/steppe (sagebrush...)
category 53 :TUN Tundra (polar, alpine)
category 54 :TRC Temperate rainforest (+/- conifer) (major forest
and woodland)
category 55 :SCW Similar to 58: cool-cold (~persistent snow)
category 56 :RWC Regrowing woods + crop/grass
category 57 :SWC Similar to 56: cool-cold (~persistent snow)
category 58 :GCW Grass/crop + <40% woods: warm, hot
category 59 :STW Succulent and thorn woods
category 60 :SDT Southern dry taiga (and other aspen/birch, etc)
category 61 :SLT Siberian larch taiga [partly other taiga 21]
category 62 :NMT Northern or maritime taiga/tundra
category 63 :WTM Wooded tundra margin (or mt. scrub, meadow)
category 64 :HMW Heath and moorland, wild or artificial (grazed)
category 65 :NW NW quadrant near most land (mainland,
large island,
category 66 :NE NE quadrant near most land (peninsula,
small islands,)
category 67 : SE SE quadrant near most land (...or isthmus)
category 68 : SW SW quadrant near most land
category 69 : PDL Polar desert (rock lichens)
category 70 : GLA Glaciers (other polar and alpine)
category 71 : SSF Salt/soda flats (playas, lake flats rarely ~wet)
category 72 : MSM Mangrove swamp/mudflat [Africa only]
ATTRIBUTE META-DATA:
NONE
NOTES:
(1) Data represent mixed 0.5-degree and 10-minute classes
(2) This data set is the one that was contributed for the
1992 International Space Year (ISY) Global Change
Encyclopedia (GlobeScope). It is included here for
comparison to the subsequent versions produced by Jerry
Olson and incorporated into GED Version 1.0, but also
to provide a link between these newer versions and the
ISY discs. Both data and legends have changed in the
newer versions.
RESOLUTION CODES AND 10-MINUTE UPDATES FOR WE1.4D
The resolution code overlay (OWE14DR) was produced by first
tagging all pixels on the WE1.4D 10-minute grid that differed
from their 30-minute mode (for the standard 30-minute grid
registration). These cells were coded 1 against a 0 background.
Known classes that were edited at 10-minutes were then over-
written onto the grid. The resulting map thus provides the
following codes:
EXPLANATION OF RESOLUTION CODES
0 unaltered cells representing 30-minute spatial
dominance (expanded to a 10-minute grid)
1 edited 10-minute cells
2 residual, or "orphaned" cells from 30-minute regions
within which other 10-minute updates were made. These
cells are presumed to represent spatial dominance at
less than 15-minutes (only coded if such cells cover
less than half of the original 30-minute cell), because
the other cells in the 30-minute region have been changed.
The following table describes the specific 10-minute updates made
to the data-set, on a background of 30-minute values:
TABLE OF 10-MINUTE EDITS IN OWE14D
OLSON14D DESCRIPTION
CLASS
0 Water, coastline edits for Africa and some other coasts
6 Montane forest, edits in Africa only
8 Bare desert, updated globally using average GVI.
28 Tropical montane, edits for Africa only
65-68 Coastline, mostly Africa but other areas as well.
71 Salt/soda flats, updated globally using average GVI.
72 Mangroves, Africa only
73 Island/Coastal (Elba Island only)
*OLSON WORLD ECOSYSTEMS
ANCILLARY ENVIRONMENTAL DATA
World Ecosystems (WE1.3A) #\data\ncillary\owe13a.img
World Ecosystems (WE1.4D) #\data\ncillary\owe14d.img
Resolution Codes for WE1.4D (WE1.4DR) #\data\ncillary\owe14dr.img
Scanned Documentation #*OWE SCANNED DOCUMENTATION
*OWE SCANNED DOCUMENTATION_help
The scanned documentation noted here is contained in the \document
directory on the CD-ROM as .gif files. These files can be read by
any computer program that reads PC Paintbrush format files.
The GeoVu software provided on this CD-ROM contains such a utility.
To use the GeoVu utility, merely select the appropriate file from
this menu, using the "Open Data" option that you have been using to
this point.
If you are VERY NEW to GeoVu, you can open a file by
1. Selecting "File" from the options at the top of your screen.
2. After selecting "File" select "Open Data" from the options that
appear in the pull-down menu.
3. Follow the hierarchy of menu paths to the data of your choice.
4. When the hierarchy leads you to a topic "Scanned Documentation"
merely select that topic. The next topic should read "Page 1, Page
2,... etc." or "Paper 1 Page 1, Paper 1 Page 2, .... Paper 2 Page
1.... etc. You can select the pages manually, or create a "slide
show" under the Utilities option at the top of the screen. The
first time the .gif file displays it might be reduced in size. This
is a "feature" of current versions of GeoVu that might be improved
in the future. If you redisplay the image (by selecting "Search"
from the options at the top of the screen, then "Create" from the
menu thus pulled down, you can modify the parameter that sets the
sampling rate from "n" [usually 2, 3, 4, or 5] to 1). This will
give you full resolution display of the scanned documentation.
It should be noted that this scanned documentation is a compromise.
We originally attempted to use optical character recognition
software to convert the scanned documentation to more usable text.
However, the technology was too immature at the time of scanning
(1992) to use successfully. Indeed, as of this writing (late 1995)
the technology is still too immature for convenient application to
this problem.
Thus, we present the scanned documentation as images.
NOTE: Many of the original documents are not copyright, and may be
reproduced freely. However, several other documents ARE copyright.
The National Geophysical Data Center has obtained permission to
reproduce all documents with a valid copyright. However, this
permission does not pass automatically to anyone else. Thus, though
all of the data on this CD-ROM are unrestricted, much of the
scanned documentation (which contains copyright notices) may not be
distributed further, without permission of the copyright holder, or
without a dontribution made to the Copyright Clearance Center under
the rules noted in the individual papers. (Also note that a few
documents authored by U. S. Government employees or contractors as
part of their work for the Government, had copyrights claimed by
the journals that published the papers. Such documents are not
subject to copyright, and the copyright claims of said journals
have been determined to be meritless.)
*OWE SCANNED DOCUMENTATION
OLSON WORLD ECOSYSTEMS
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