the global distribution of freshwater wetlands
TRANSCRIPT
NCAR/TN-416+STRNCAR TECHNICAL NOTE
September 1995
The Global Distribution ofFreshwater Wetlands
M. Stillwell-SollerF. KlingerPollardL. Thompson
CLIMATE AND GLOBAL DYNAMICS DIVISION
NATIONAL CENTER FOR ATMOSPHERIC RESEARCHBOULDER, COLORADO
L.L.D.S.
I - I
I
TABLE OF CONTENTS
Page
List of Tables . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . i
List of Figures . . . . . . . . . . . . . . . . . . .. . . .iv
Preface .................. vAcknowledgments .... ............. v. .. .vi
I Introduction .................... 1II Scientific Rationale . . . . . . . . . . . . . . . . . . . .. . . . . . . 3
III Description of Data ..... .................... 5
IV Presentation of Figures . . ............. ... ....
V Data Files ....... .. ...................... 9References . . . . . . . . . . . . . . . . . . . . . . . . . . .. 10Table Captions . ..... ..... ....... 13
Figure Captions . . . . . . . . . . . . . . . . . . . . . . . . . .18
ii
LIST OF TABLES
Page
Table 1. Aselman & Crutzen wetland categories ................ 14
Table 2. Aselman & Crutzen wetland category descriptions ......... . 15
Table 3. Wetland categories used and corresponding data files ........ . 16
Table 4. Bog and Fen vegetation types. ............. 17
iii
LIST OF FIGURES
Page0
Figure 1.
Figure 2.
Figure 3.
Figure 4.
Figure 5.
Figure 6.
Figure 7.
Figure 8.
Figure 9.
Figure 10.
Figure 11.
Figure 12.
Figure 13.
Figures 14.a-14.1
Figures 15.a-15.1
Figures 16.a-16.1
Figure 17.
Figure 18.
Figure 19.
Aselman & Crutzen's global distribution of wet-cultivation
rice paddiesAselman & Crutzen's monthly cultivated area of wet-
cultivation rice paddies for 10°latitude belts.Mid-range values for Aselman & Crutzen's wet-cultivation
rice paddy area.Distribution of total freshwater natural wetlands.
Distribution of wet-cultivation rice paddies.
Distribution of Fens.
Distribution of Bogs.
Distribution of Permanent Swamps.
Distribution of Permanent Marshes.
Distribution of Shallow Lakes
Distribution of Permanent Floodplains.
Distribution of Seasonal Floodplains
Distribution of Seasonal Swamps/Marshes.
Monthly distributions of Seasonal wet-cultivation Rice
Paddies.Monthly distribution of Seasonal Floodplains.
Monthly distribution of Seasonal Swamps/Marshes.
Seasonal Floodplains with unknown monthly variation.
Seasonal Swamps/Marshes with unknown monthly varia-
tion.Example of the ASCII text format for data files.
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PREFACE
During the last decade the complexity of land-surface models (LSMls) used in global
climate models (GCMs) has increased dramatically, from soil buckets with prescribed
albedos and surface roughness to explicit vegetation canopies overlying multi-layer soil
profiles. Although the optimal levels of complexity for various global modeling applications
are still unclear, some processes included in the newer LSMs can significantly affect GCM
sensitivities at global and regional scales (e.g., Garratt, 1993; Henderson-Sellers et al., 1995;
Pollard and Thompson, 1995). The added realism in the newer LSMs has created a need
for global gridded datasets of various aspects of vegetation, soil and surface hydrology, in
order to specify prescribed parameters in the models and to validate their predicted fields.
One such set is the geographical and seasonal distribution of various types of wetlands.
Although wetlands are not predicted or even prescribed yet in most LSMs, we anticipate
that they will be included in the near future because of their importance to surface
hydrology, trace gas fluxes, and the near-surface climate. To support this anticipated
development we have assembled a global dataset of wetland distributions, using existing
data sources and compiling them into a uniform set of digitized maps at 10x10 resolution
for convenient use with GCMs.
The main source for our dataset is Aselman and Crutzen (1989), who produced
global maps of percent cover for a variety of wetlands categories. Their categories,
which are physically based and well-suited for LSM applications, consist of Bogs, Fens,
Permanent Swamps, Permanent Marshes, Shallow Lakes, Permanent Floodplains, Seasonal
Floodplains, Seasonal Swamp/Marshes and Wet Rice Paddies. However, (i) their digitized
files are not readily available, (ii) their seasonal information is coded in a relatively
inconvenient way, and (iii) as discussed by Aselman and Crutzen, their data for Alaska is
poor. We have partially remedied the latter drawback by merging their maps. with a recent
dataset of Alaskan bogs and fens by Lee Klinger (NCAR, personal communication).
This technical note describes procedures used to assemble our dataset, presents global
maps of all the wetland categories, and provides some discussion of the importance of
wetlands for climate studies. The complete set of digitized l°by 1° global maps is available
by anonymous ftp and on the NCAR Mass Storage System, and information on the format
and locations of these files is given below.
v
One drawback of the Aselman and Crutzen data is that salt marshes are not includedbecause their original data was compiled specifically for the study of methane emissions
which are dominated by freshwater sources. Cogley (1991) provides global maps of some
types of salt water marshes and salt flats, but the overlap with the Aselman and Crutzen
data is not entirely clear so we decided to omit this category and restrict our dataset to
freshwater wetlands. Matthews and Fung (1987) have also compiled a global wetlands
dataset by combining maps of soils, vegetation and inundation. However this indirect
approach is relatively uncertain and indiscriminating compared to Aselman and Crutzen's
and Klinger's direct approach of compiling local data sources. The two approaches and
differences in their results are discussed by Aselman and Crutzen (1989).
vi
ACKNOWLEDGMENTS
This work was conducted as part of the GENESIS Earth Systems Modeling Project at
NCAR, supported by the U.S. Environmental Protection Agency Interagency Agreement
No. DW49935658-01-0. We thank Dennis Shea, Gordon Bonan and Steve Hostetler for
helpfull comments.
vii
I. Introduction.
Historically, General Circulation Models (GCMs) treated surface processes rather
simplistically as a result of technological and theoretical limitations. Consequently,
detailed information regarding surface processes was not necessary for climate studies.
With technological advancements, improved scientific knowledge and an increased
awareness of the importance of surface processes upon the climate, GCM surface
prescription capabilities became more sophisticated and better able to answer more
complex climatological questions. As a result a need has arisen for accurate data bases
containing necessary information about terrestrial systems. The global coverage and spatial
distributions of vegetation types, soil types, and water sources are a few examples of the
necessary surface information required for today's climate modeling studies. Other data
needs are sure to arise as our understanding of land-atmosphere interactions, and their
influence on the climate, improves.
Past global climate simulations have demonstrated that the climate system is sensitive
to relatively large changes in vegetation patterns and to the presence of water on the land
surface (Charney, et al., 1977; Sud et al., 1990; Bonan et al., 1992). The distribution of
wetlands is thus an important component of biosphere-atmosphere interactions because
they embody both vegetation and freely available water. In addition, Wetland areas
store and release atmospheric gases (CH4 and 002), decrease drainage and change surface
albedos. For climate modeling, accurate estimates of the total land area coverage and the
distribution of wetlands, as well as wetland types, are important if we are to understand
methane flux characteristics from wetlands, wetland carbon storage dynamics and the
effects of wetland hydrology on the climate system.
This report describes a global wetland data base for climate modeling. Our aim is
to provide an accurate, comprehensive and uniform set of files for convenient specification
of wetlands in global climate models. The completed Wetlands data base consists of 68
ASCII data files, half (34) of which are gridded at a resolution of 2.5°by 5°and the
other half gridded at a finer resolution of 1°by 1°. These data files are in the form of
global maps showing the areal extent of land covered by different types of wetlands. The
data base is essentially a re-gridding of Aselman and Crutzen's (1989) data base, with
some reorganization for seasonally varying categories (henceforth, we refer to Aselman &
1
Crutzen as AC, and their 1989 paper as AC89). Alaskan data for bogs and fens provided
by Dr. Lee Klinger (personal communication, 1995) are included because the AC data are
relatively poor for Alaska (AC89).
The remaining document is organized as follows: Section 2 includes a brief scientific
discussion on the climatological importance of wetland areas, section 3 describes the
original data and our data processing methods, section 4 presents the analyzed data in
graphical form, and section 5 describes the data files, including file format, storage and
access methods.
2
II. Scientific Rationale
Wetlands alter the climate on global scales through the storage and release of
greenhouse gases such as methane (CH4 ) and carbon dioxide (C0 2 ). Wetlands also
moderate the climate on regional scales through hydrological processes such as increased
evaporation and decreased drainage, and through an increase in the land albedo as
compared to boreal forest zones (Klinger, 1991).
The amount of methane gas in the atmosphere is increasing annually by approximately
1% (Matthews & Fung, 1987; AC89; Moore & Knowles, 1990). Several studies indicate
that this rise may be attributable to an increase in the production of abiotic sources,
and a decrease in OH radicals which are a major sink for atmospheric methane gas (AC89;
Matthews & Fung, 1987). In addition, several studies have determined a strong correlation
between the geographic distribution of northern latitude wetlands and the location of the
highest concentrations of methane gas emissions, suggesting that northern peatlands may
be significant contributors to the global methane budget (Aselman & Crutzen, 1989; Moore
& Knowles, 1990). Because methane is expected to contribute substantially to global
warming in the next century (Rosenzweig & Dickinson, 1986), establishing the total land
area covered in wetlands is an important first step for gaining a global methane emission
estimate for climate change studies.
The concentration levels of carbon dioxide are also affected by wetland areas. Most
wetland areas contain peat soils, which are rich in carbon. Peat soils gain a large portion of
their stored carbon from CO 2 in the atmosphere. As a result, peatlands account for at least
half of the carbon stored in the earth's vegetation, making them a significant historical
sink for atmospheric carbon (Maltby & Immirzi, 1993). However, as the climate warms
better soil aeration and increased drainage actually increase the release of carbon from
peat to the atmosphere, potentially changing peatlands from a sink to a source (Oechel et
al., 1993).
Wetlands alter the climate because of increased evaporation and higher albedos
(Klinger, 1991). Wetlands lose more moisture to evaporation than to surface runoff. The
flux of latent heat cools the local climate and may cool the regional climate because of
additional low cloud cover due to increased atmospheric moisture. Wetland areas are more
reflective than boreal forest areas because the albedo of standing water in general exceeds
the albedo of vegetation (Klinger, 1991). This effect tends to cool the regional climate.
3
The bog climax hypothesis (Klinger et al.. 1990, Klinger 1991) proposes that early
succession is influenced mainly by environmental factors and may not follow in a predictable
fashion. As succession progresses, biological factors become increasingly more important
in shaping late successional communities, which eventually converge on structurally and
compositionally stable bog landscapes. The evolution from woodland to peatland has
been identified in several regions from the arctic to the tropics (Flenley, 1978; Alhonen &
Auer, 1979; Glaser, 1987; Klinger et al., 1990). Barring large scale disturbance (ie. fires,
landslides, floods), the total land area covered with wetlands should increase over time.
A change in the total area covered in wetlands, or a change in the spatial distribution of
wetlands, may substantially modify the climate on both regional and global scales. As
the level of detail in climate models improve in the future, it will become increasingly
important to include different vegetation processes and to incorporate realistic vegetation
coverage data bases into climate studies.
4
III. Description of Data.
The global wetlands data base presented here has been assembled from two data
sets: Aselman and Crutzen's (1989) wetlands data set and Klinger's (pers. comm., 1995)
Political Alaska data set.
The AC data set described in AC89 contains globally gridded maps of the area of
freshwater wetlands in 2.5° latitude by 5° longitude grid cells. This data set was
originally compiled from various published maps and was created explicitly for the study
of methane emissions from freshwater sources. Consequently, the classification scheme used
by AC contained a few omissions and simplifications. Salt water marshes, for example,
were excluded from natural wetlands and only wet-cultivation rice paddies were included.
Also, AC89 state that shallow lakes were considered as a separate category (see below) only
for Europe, Africa and South America where methane emissions would be likely. In most
temperate and arctic regions shallow lakes were combined into other wetland categories,
and deeper lakes were not included. The AC data set is geographically complete except
for the Alaska region from 160° West to 140° East. At the time the data set was
assembled, AC found that there was no appropriate large-scale data for the Alaska region,
therefore they had to make crude estimates based on limited and conflicting published
sources coupled with calculated values for potential methane emissions. To remedy this
we have added Klinger's Alaska data for bogs and fens to cover this region (see below).
The original Aselman & Crutzen files include the fractional areas covered by
various distinct categories of wetlands. These are: bogs, fens, swamps, marshes, shallow
lakes and floodplains (all permanent year round), and seasonal floodplains, seasonal
swamps/marshes, and rice paddies (which dry out in some months). We retained AC's
permanent categories for bogs, fens, swamps, marshes, shallow lakes and floodplains, and
AC's seasonal categories for floodplains and rice paddies. However, AC's seasonal data files
did not contain any distinctions between seasonal swamps or seasonal marshes, therefore
it was necessary to combine seasonal swamps and seasonal marshes into one category to
utilize the seasonal-variation information. These categories are briefly described below and
in Table 1. The AC data files contain data for many sub-categories (referred to as 'types'
by AC). As shown in Table 2, our dataset uses only their major categories which are sums
of the individual sub-categories.
5
The wetland categories described in AC89 are distinguished by water source,
predominant vegetation and soil type. Bogs are peat forming wetlands with a high
accumulation of organic material. Their primary moisture and nutrient source is
precipitation, creating highly acidic conditions and allowing mosses to dominate. Fens are
also peat forming wetlands, but moisture is gained both by precipitation and groundwater.
As a result fens tend to be less acidic than bogs and may even approach alkaline conditions.
Typical vegetation for these areas are grasses and sedges. Swamps are categorized by their
lack of peat formation and the fact that they are forested. Marshes are similar to swamps,
except they tend not to be forested but are dominated by grasses and Sedges. Floodplains
are periodically flooded areas surrounding lakes and rivers. Shallow lakes are permanent
open bodies of water that are only "a few meters in depth" (AC89, p. 310). Rice paddies
are flooded areas used for wet-cultivation of rice (see Table 1). The distinction between
shallow lakes, permanent floodplains and seasonal floodplains was not made clear in AC89,
but we surmise that shallow lakes never dry out, permanent floodplains sporadically dry
out but are subject to flooding during any month of the year, whereas seasonal floodplains
always dry out on a regular seasonal cycle.
The raw data supplied on magnetic tape by Aselman & Crutzen consists in part
of global maps containing the total area (in square kilometers) covered by the various
categories of wetlands within each grid cell, on a regular grid with a resolution of
2.5° latitude by 5° longitude. We converted their absolute area values to fractional
area by dividing the absolute values by the total area of each 2.5° by 5° grid box. We
then interpolated the 2.5° by 5° gridded data to our standard 1° by 1° grid using
bilinear interpolation. The interpolated fractional cover maps for bogs and fens were then
merged with Klinger's Alaska data set (see below) to produce complete global coverage. It
should be noted that the interpolation of the AC data to the finer 1 o by 1 0 grid does not
generate any additional information, and is done purely for uniformity and convenience
for future GCM use. Except for Alaska, the intrinsic scale of the data remains at 2.5 0 by
5 .
AC's raw data contains global maps of the areas where seasonal swamps/marshes and
seasonal floodplains are present at any time of the year, and in a separate data file, the
individual months of occurrence of seasonal floodplains and seasonal swamps/marshes for
each grid box. Thus, the seasonal extent at a given location takes on only one of two
values throughout the year: zero or the maximum. By combining these two data sets, we
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generated 12 global maps of the monthly areal extent for both seasonal swamps/marshes
and seasonal floodplains, at a resolution of 2.5° by 5°. We then interpolated each map
to our 1° by 1° grid using bilinear interpolation.
The AC data file with the months of occurrence contains no data for seasonal marshes.
We therefore summed AC's global areal maps of seasonal swamps and seasonal marshes,
and used the monthly information for seasonal marshes to derive global monthly maps
for a combined category of seasonal swamps/marshes. Note that permanent swamps and
marshes are excluded from the seasonal swamp/marsh category, and similarly permanent
floodplains are excluded from the seasonal floodplains category. The "permanent"
categories are entirely distinct from the "seasonal" categories.
Although the magnetic tapes supplied by AC did not contain information on rice
paddies, AC89 contains a global map of rice paddy fractional area (Fig. 1) and some basic
information on the seasonal cycles versus latitude. Our Fig. 2 is a reproduction of AC89's
figure 4a (p. 338), which is the seasonal maximum area of rice paddies in each 2.5° by
5° grid box. Our Fig. 3 is a reproduction of their figure 4b (p. 338), giving the zonal total
cultivated area versus month for each 10° latitude band. We first digitized the data from
AC's figure 4b using the midpoint for each 10° latitude box and the mid-range values of
the cultivated-area bins (Fig. 3), then normalized the seasonal variations by dividing by
the seasonal maximum for each latitude band. Finally we multiplied their global map by
the normalized monthly values to produce a 2.5° by 5° map of rice paddy area for each
month. Each map was then bilinearly interpolated to our standard 1° by 1° grid.
Klinger's Alaska data set encompasses all of mainland Alaska and extends eastward to
1400E, the political border between Alaska and Canada. These data depict the fractional
area covered by two permanent categories, bogs and fens, on a regular 1° by 1° grid,
and are based on a map of the potential natural vegetation of Alaska (Kiichler, 1985).
Bogs and fens within each vegetation category were assigned cover values (Table 4) based
on quantitative studies (Klinger et al.., 1983; Klinger, 1988; Walker et al.., 1989) and
widespread aerial observations throughout Alaska by Klinger and by D.A. Walker (pers.
comm.). The map was overlaid with a 1° by 1° grid and the proportion of each vegetation
type within a grid cell was estimated. Wetland cover was calculated by multiplying wetland
cover values in table 4 with the fractional vegetation types and summing.
7
IV. Presentation of Figures.
In this section we present the final 1° by 1° global maps showing the combined AC
and Klinger data. The first two color maps show the fractional areal coverage for total
natural freshwater wetlands and rice-paddy wetlands (Figs. 4-5). We then show color
maps of the individual permanent categories (Figs. 6-11) followed by maps displaying theseasonal wetland categories wherever present (Figs. 12-13). Finally, we include 36 black
and white monthly maps showing the seasonal variations for rice paddies (Figs. 14.a-14.1),
seasonal floodplains (Figs. 15.a-15.1) and seasonal swamps/marshes (Figs. 16.a-16.1).
We found that not every data point within the AC global maps for seasonal floodplains
and seasonal swamps/marshes has a corresponding data point within the AC monthly
variation files. We have determined the data points within the global maps that do not
have matching seasonality data and show these points in two additional maps titled "A&C
Floodplains, Unknown Seasonality" (Fig. 17) and "A&C Swamps/Marshes, Unknown
Seasonality" (Fig. 18).
The rectangular or "blocky" appearance in some of Figs. 1-17, especially in the
smallest contour intervals, is due to the coarseness of the original 2.5° by 5° AC data
which is retained in our bilinear interpolation to 1° by 1°.
8
V. Data Files.
A complete set of files in our wetland dataset is available by anonymous ftp to
biscuit.cgd.ucar.edu and cd to pub/wetlands, or in two tar files on the NCAR Mass Storage
System in directory /POLLARD/wetlands.
The first part of each filename indicates the wetlands category, followed by the suffix
'.coarse' or '.1 x 1' indicating either the original Aselman & Crutzen resolution of 2.5 by
5° or our interpolated resolution of 1° by 1° . File names containing the string
'ack' contain merged data for bogs or fens from both AC and Klinger data sets, whereas
bogs.coarse, bogs.lxl, fens.coarse, and fens.lxl contain only AC data.
All files are in ASCII text format and appear as geographical maps if displayed without
wraparound. An example (bogs-ack.coarse) is shown in Fig. 19. They all have a common
format as described below.
* A header record containing an 8-character keyword (left-justified) representing the
wetlands category, followed by the longitudinal and latitudinal dimensions for the file
(either 72 72 or 360 180), followed by a descriptive comment. The Fortran format of
this record is (A8, 218, 8X, A).
* A blank record, followed by a record containing the longitude grid values, followed by
another blank record. These 3 lines are skipped by the model. The longitudes are
°E rounded to the nearest integer, and apply to the column below their last (least
significant) digit. The longitude and latitude values shown in the files correspond to
grid box centers.
* A sequence of data records, each containing data values for one latitude circle. These
records run from the northernmost latitude to the southernmost. The first value in
each record is the box-center latitude in degrees, followed by as many data values
as longitudes in the current resolution. All data values represent percentage area
covered by the wetland category. The Fortran format of these records is (F5.1, 3X,n15) where n is the number of longitudes. Blanks are used for ocean data points so
that continent-ocean outlines can be recognized (blanks are read by Fortran as zeros).
9
REFERENCES
Alhonen, P., and V. Auer, 1979: Stratigraphy of peat deposits in Tierra del Fuego, South
America: A review of the Results of Finnish expeditions. In Classification of Peat
and Peatlands. International Symposium in Hyytiaiil, Finland, 273-282. (Published
by the International Peat Society).
Aselman, I., and P.J. Crutzen, 1989: Global distribution of natural freshwater wetlands
and rice paddies: Their net primary productivity, seasonality and possible methane
emissions. J. Atmos. Chem., 8, 307-358.
Bonan, G.B, D. Pollard and S.L. Thompson, 1992: Effects of Boreal forest vegetation on
global climate. Nature, 359, 716-718.
Charney, J.G., W. Quirk, J. Chow and J. Kornfield, 1977: A comparative study of the
effects of albedo change on drought in semi-arid regions. J. Atmos. Sci., 34, 1366-
1385.
Cogley, J.G., 1991: GGHYDRO - Global Hydrographic Data Release 2.0. Trent Climate
Note 91-1, Trent University, Peterborough,Ontario, Canada.
Flenley, J.R., 1978: The Equatorial Rainforest: A Geological History. Butterworths,
London.
Garratt, J.R., 1993: Sensitivity of climate simulations to land-surface and atmospheric
boundary-layer treatments - a review. J. Climate, 6, 419-449.
Glaser, P.H., 1987: The ecology of patterned Boreal peatlands of northern Minnesota:
A community profile. Fish and Wildlife Service Biological Report B5 (7.14), United
States Department of the Interior.
Henderson-Sellers, A.H., K. McGuffie and C. Gross, 1995: Sensitivity of global climate
model simulations to increased stomatal resistance and CO2 increases. J. Climate, 8,
1738-1756.
10
Klinger, L.F., D.A. Walker, and P.J. Webber, 1983: The effects of gravel roads on
Alaskan arctic coastal plain tundra. In Permafrost: Fourth International Conference,Proceedings. National Academy of Sciences, National Academy Press, Washington,
D.C., pp. 628-633.
, 1988: Successional change in vegetation and soils of southeast Alaska. Doctoraldissertation, University of Colorado, Boulder, CO.
;___ , S.A. Elias, V.M. Behan-Pelletier and N.E. Williams, 1990: The bog climaxhypothesis: Fossil arthropod and stratigraphic evidence in peat sections from
southeast Alaska, USA., Holarctic Ecology, 13, 72-80.
Zimmerman, P.R., Greenberg, J.P., Heidt, L.E., and Guenther, A.B., 1994: Carbon
trace gas fluxes along a successional gradient in the Hudson Bay lowland. J. Geophys.
Res., 99, 1469-1494.
, 1991: Peatland formation and ice ages: A possible Gaian mechanism related tocommunity succession. In Scientists On Gaia (Stephen H. Schneider and Penelope J.Boston, Eds.), The MIT Press, London, England, 247-255.
Kuchler, A.W., 1985: Potential natural vegetation of Alaska. National Atlas of the United
States of Ameria, Department of the Interior, USGS, Map No. 55135-AD-NA-07M-00.
Maltby, E. and P. Immirzi, 1993: Carbon dynamics in peatlands and other wetland soils:
Regional and global dynamics. Chemosphere, 27, 999-1023.
Matthews, E. and I. Fung, 1987: Methane emission from natural wetlands: global
distribution, area, and environmental characteristics of sources. Global Biogeochemical
Cycles, 1, 61-86.
Moore, T.R. and R. Knowles, .1990: Methane emissions from fen, bog and swamp peatlands
in Quebec. Biogeochemistry, 11, 45-61.
Oechel, W.C., S.J. Hastings, G. Vourlitis, M. Jenkins, G. Riechers, and N. Grulke, 1993:
Recent change of arctic tundra ecosystems from a net carbon dioxide sink to a source.
Nature 361, 520-523.
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Pollard, D. and S.L. Thompson, 1995: Use of a land-surface-transfer scheme (LSX) in a
global climate model: the response to doubling stomatal resistance. Global Planetary
Change, 10, 129-161.
Rosenzweig, C. and R. Dickinson, Eds., 1986: Climate-Vegetation Interactions. Proc. ofNASA workshop. OIES, UCAR, Boulder, CO.
Sud, Y.C., P.J. Sellers, Y. Mintz, M.D. Chou, G.K. Walker and W.E. Smith, 1990:
Influence of the biosphere on the global circulation and hydrologic cycle - A GCMsimulation experiment. Agric. Forest. Meteor., 52, 133-180.
Walker, D.A., E. Binnian, B.M. Evans, N.D. Lederer, E. Nordstrand, and P.J. Webber.,
1989: Terrain , vegetation and landscape evolution of the R4D research site, Brooks
Range Foothills, Alaska. Holarctic Ecology, 12, 238-261.
12
TABLE CAPTIONS.
Table 1. List of Aselman & Crutzen's wetland categories and basic properties.
Table 2. List of categories used in the current data set, showing their seasonality and
the Aselman & Crutzen sub-categories or 'types' contributing to each category (see
text).
Table 3. List of wetland categories in this data base and the corresponding 2.5° by
5° (*.coarse) and 1° by 1° (*.1 x 1) data files available.
Table 4. Percentage cover of bogs and fens within major vegetation types for the six
geographic regions of Alaska.
13
Table 1.
AC Category
Bog
Fen
Swamps
Marshes
Floodplains
Lakes
Rice Paddies
Description
Peat producingMoist climatesNutrient and water input from precipitationRisen above land surfaceExtremely acidicNutrient deficientMajor vegetation: sphagnum moss
Peat producingNutrient input through soil waterMildly acidic or alkalineMajor vegetation: grasses, hedges,Major regions: boreal, tundra
and mosses
ForestedWaterlogged or inundated soilsMinimal peat accumulationPermanent or Seasonal
Herbaceous MiresGravitational water levelsPermanent or seasonalMajor vegetation: grasses, sedges or reeds
Periodically flooded areas along rivers or lakes
Shallow bodies of water < "a few meters" in depth
Periodically flooded areas used for wet cultivation of rice
14
Table 2.
15
CATEGORY SEASONAL AC SUB-CATEGORY (their 'Type')
Bog Permanent raised raised with hollows + poolsraised, plateaux raised, foresteddoomed, with lakes doomedblanked Plateaux, PalsasPolygonal PalsasString bogs homogeneouswet with hollows dry with sedgesRestiad bogs Bog-fen complex
Fen Permanent horizontal/sloping slopinghorizontal spring fenpolygonal polygonal/homogeneouspolygonal, sedges sedges + mosseshomogeneous Aapa/mixed mires
Swamps Permanent wooded or shrubby forested
Marshes Permanent Carex, Phragmites Papyrusherbaceous
Swamps/Marshes Seasonal Igapo wooded or shrubbyVarzea Papyrusherbaceous
Floodplain Permanent flooded Savannas
Floodplain Seasonal flooded Savannas
Lakes Permanent shallow only
Table 3.
CATEGORY
Total NaturalWetlands
Bog
Fen
Swamp
Marsh
SeasonalSwamp/Marsh
PermanentFloodplain
SeasonalFloodplain
Lakes
Rice Paddies
DATA FILE
total.dat
bogs.lxlbogs_ ack.coarse
fens. lxlfens_ ack.coarse
swamps.lxl
marsh.lx1
swamp-marsh. lxlswpjan.lxlswpapr.lxlswpjul.lxlswpoct.lxlswpjan.coarseswpapr.coarseswpjul.coarseswpoct.coarse
pfloodplain.lxl
sfloodplain.lxlfldjan. xlfldapr. lxlfldjul.lxlfldoct. xlfldjan.coarsefldapr.coarsefldjul.coarsefldoct.coarse
lakes.lxl
ricepd.lxljan-ricepd.lxlapr-ricepd.lxljul-ricepd.lxloct-ricepd.lxljan-ricepd.coarseapr-ricepd.coarsejul-ricepd.coarseoct-ricepd.coarse
bogs.coarse
fens.coarse
swamps.coarse
marsh.coarse
swamp-marsh.coarseswpfeb.lxlswpmay.lxlswpaug.lxlswpnov.lxlswpfeb.coarseswpmay.coarseswpaug.coarseswpnov.coarse
bogs-ack. xl
fens-ack.1 x 1
swpmar.lxlswpjun.lxlswpsep.lxlswpdec.lxlswpmar.coarseswpjun.coarseswpsep.coarseswpdec.coarse
pfloodplain .coarse
sfloodplain.coarsefldfeb.lxlfldmay.lxlfldaug.lxlfldnov.lxlfldfeb.coarsefldmay.coarsefldaug.coarsefldnov.coarse
lakes.coarse
ricepd.coarsefeb-ricepd.lxlmay-ricepd.lxlaug-ricepd.lxlnov-ricepd.lxlfeb-ricepd.coarsemay-ricepd.coarseaug-ricepd.coarsenov-ricepd.coarse
fldmar.lxlfldjun.lxlfldsep.lxlflddec.lxlfldmar.coarsefldjun.coarsefldsep.coarseflddec.coarse
mar-ricepd.lxljun-ricepd.lxlsep-ricepd.lxldec-ricepd.lxlmar-ricepd.coarsejun-ricepd.coarsesep-ricepd.coarsedec-ricepd.coarse
16
-I
Table 4 Percentage cover of bogs and fens within major vegetation types for the sixgeographic regions of Alaska.
Vegetation North South- South- South-type Slope Interior Western central western eastern
Bog Fen Bog Fen Bog Fen Bog Fen Bog Fen Bog FenHemlock-spruce 12 8 14 6 16 4 14 6 16 4 16 4
forestSpruce-birch 6 4 7 3 8 2 7 3 8 2 8 2
forestBlack spruce
forestMuskeg
30 20 35 15 40 10 35 15 40 10 40 10
54 36 63 27 72 18 63 27 72 18 72 18
Alderthickets
CottongrasstundraSedgetundraDryas
meadowsAleutian
meadowsAleutian
heath
3 2 3.5 1.5 4 1 3.5 1.5 4 1 4 1
36 24 42 18 48 12 42 18 48 12 48 12
48 32 56 24 64 16 56 24 64 16 64 16
3 2 3.5 1.5 4 1 3.5 1.5 4 1 4 1
6 4 7 3 8 2 7 3 8 2 8 2
6 4 7 3 8 2 7 3 8 2 8 2
17
FIGURE CAPTIONS.
Figure 1. Aselman & Crutzen's global distribution of wet-cultivation rice paddies. Values
are percent of area covered for each 2.5° by 5° grid cell (AC89, p.337, their figure
3). Reprinted by permission of Kluwer Academic Publishers.
Figure 2. Aselman & Crutzen's monthly cultivated area of wet-cultivation rice paddies
for each 10° latitude band (AC89, p.338 their figure 4a-4b). Reprinted by permission
of Kluwer Academic Publishers.
Figure 3. Monthly wet-cultivated rice paddy area for 10° latitude belts, digitized from
Fig. 2 using the mid-range values of Aselman & Crutzen's cultivated-area bins at the
midpoints of each 10° latitude band.
Figure 4. Distribution of Total Freshwater Natural Wetlands, in percent of area covered.
Outside of Alaska this is the sum of all Aselman & Crutzen's (1989) permanent and
seasonal categories except rice paddies, interpolated to our 1° by 1° grid. For Alaska,
this is the sum of bogs and fens from Lee Klinger's Alaskan data base (see text).
Figure 5. Distribution of wet-cultivation Rice Paddies, in percent of area covered, from
Aselman & Crutzen's (1989) data set interpolated to our 1° by 1° grid.
Figure 6. Distribution of Fens, in percent of area covered, interpolated from Aselman &
Crutzen's (1989) data set outside of Alaska, and from Lee Klinger's data set within
Alaska.
Figure 7. Distribution of Bogs in percent of area covered, interpolated from Aselman &
Crutzen's (1989) data set outside of Alaska, and from Lee Klinger's data set within
Alaska.
Figure 8. Distribution of Permanent Swamps in percent of area covered, interpolated
from Aselman & Crutzen's (1989) data set.
Figure 9. Distribution of Permanent Marshes in percent of area covered, interpolated
from Aselman & Crutzen's (1989) data set.
18
Figure 10. Distribution of Shallow Lakes in percent of area covered, interpolated fromAselman & Crutzen's (1989) data set.
Figure 11. Distribution of Permanent Floodplains in percent of area covered, interpolatedfrom Aselman & Crutzen's (1989) data set.
Figure 12. Distribution of Seasonal Floodplains in percent of area covered, interpolatedfrom Aselman & Crutzen's (1989) data set.
Figure 13. Distribution of Seasonal Swamps/Marshes in percent of area covered,interpolated from the sum of Aselman & Crutzen's (1989) categories for seasonalswamps and seasonal marshes.
Figures 14.a-14.1 Monthly Distributions of Seasonal wet-cultivation Rice Paddies inpercent of area covered, produced by combining Aselman & Crutzen's (1989) globalrice-paddy map with their zonally integrated seasonal-variation information (see text).
Figures 15.a-15.1 Monthly Distribution of Seasonal Floodplains in percent of areacovered, produced by combining Aselman & Crutzen's (1989) global seasonalfloodplains map with their seasonal-variation data.
Figures 16.a-16.1 Monthly Distribution of Seasonal Swamps/Marshes in percent of areacovered, produced by combining Aselman & Crutzen's (1989) global maps of seasonalswamps and seasonal marshes, and combining with their seasonal-variation data.
Figure 17. Seasonal Floodplains with unknown monthly variation, in percent of areacovered. These are regions with seasonal floodplains according to Aselman & Crutzen's(1989) global map, but without any corresponding seasonal-variation data.
Figure 18. Seasonal Swamps/Marshes with unknown monthly variation in percent of areacovered. These are regions with seasonal swamps and/or seasonal marshes accordingto Aselman & Crutzen's (1989) global maps, but without any corresponding seasonal-variation data.
Figure 19. Example of the ASCII text format used to display data files as geographical
maps.
19
Figure 1.
DISTRIBUTION OF RICE PADDIES£mst
2. 122.S 33 . . s T2.2 2.5 4. 5 32 02. 31.5 22.s 32.S 42.S 352.1 362.S 12.s
63.T 3. 1.61.2S 3$1.U35t.15 363033
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435;== .113. 04... 3. … 01 ….6.= ° 2 ....... - 333
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.3.11 -- 0.2 13 -3.2 3533
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-36.2135** . -- 323630
3038TI 1341. T0. S.88 J3S1 l
4?:1 Rice Paddlies - - ^"&".45.11____________________ - 3336331
33.T8 1388000__ _
.46.21 - 30663--333------- .... S.1..$ 36. .J
1. a 31. 2A. 5T.5 41T. 6T.1 61.6 TT. 3T.3 . 0T.S 31.1. 31.5 33.1 14T.S 341 . 31 1 36.1 31.
36T.» 1T.0 3U1ST.5 14T.1 131.5 132T.S 331T.5 30T.5 3T.5 6. TT.5 *T6.1 1T. 4T.1 3T.S 21T. 31. .1 1,T.1
66.11 43301166.21 «3036
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1325 436363.15……-- - -- 1663 00,7 _-
S3.TS- _ _ _ _ _ _300_ _ _ _ unio663.15……… -_ 66200 _ _ _ ___ _ _ .II613.2 - 143)0056.11- - - --- 303016.25 133*f^53.15- -- -- -- -- -- -- -- -- -2I333
S 1.23 Wo 6613346.11- - - -- - - - - -- - - 333333046.25 1S63343.TS1 33360343.2 .0.3 .3 3336.11o 3. 0-- - -. 3 0_.2 3,3S033 ,36.25 0. … - Ii- 0. 32460523.1 3.1 -. - - 33503.2 - - - - .T - - - 33230121S - - - 0.6 - - 3S11026.2S-.*- - - - 3360023.1 -- - - -- - 41403121.25 - - - 0.3 0.1 - - 4433333.1-- -- 0.3 - 1.2 . -1 - - 4630U36.35 0. - 602 0.3 340 3004132.1 0.3 0.I - O.S - ISO35I33. - O.I.2 0.3 0. . 0. - . S3I536*
T S
0.5 3.3 0.1 0.4 0.3 2.6 0.9 1.4 S31300.21. 02 0.4 0.3 0.3 O.T 2.4 0.1 3360U
5.15. 0.3 0.3 -- - 4304201.2»- - - -= . -- -- S4SO-1.3.S .1 ….3.3 3S4503)-3.TS1 21333-6.2S 0 - -- - - - - -- S3II363
.13.TS 30 .13313o
*3I6.35 0-- 3.4 - 4.6 - 1313,1-1 ,TS- .....- 4.9-- - .633,1
31.25- -4 - 4.3 5.5 44313111.35.T5--- - 4.3 2. 341400-10.3S- - 0.4 - 333313126.TS-- -- 3 0.2 6.6 3133.3lI
.3 1.2 -- -- - I.S 1321-33.TS 0.2 - 0.2 . 12311Sn36.2 2- - - 3463..38.T1
31231111'.335 Rice Paddies I 36 3
^~~~~____________________=. _________J;
-4 S 03.. I2 1 13 2.33633
-4312s
-46.25 333f33e 0
S~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 13,,s...
-46.T1 3036033
312.5 362.1 352.5' 343.5 332.5 322.1 333.5 030.1 62.1 32.5 13.5 62.S 13. 42.5 32.1 22.51 .3.S 2.5
20
Figure 2.
MONTHLY CULTIVATED RICE PADDY AREA
Fig. 4a. Distribution of rice paddies along 10' latitudinal belts.
Latitudes
Monthly cultivated area of rice paddies 103 km' ]
I 1o [r.j so-100I 0.001 o -1 " 100 -300
1 - 10 : ~ 300-500
EI 10 - 50 m 500 -750Fig. 4b. The monthly cultivated rice paddy area for 10' latitude belts in correspondence to Figure 4a
21
Figure 3.
RICE PADDY AREA PER 10 ° LATITUDE BELTS
22
Latitudes 45 35 25 15 5 -5 -15 -25 -35
January 0 0 400 200 75 75 30 30 5
February| 0 0 400 75 75 75 30 30 5
March 0 0 400 75 75 75 30 30 5
April 0 0 400 30 75 75 5 5 0
May 0 200 400 30 75 75 5 5 0
June 30 200 625 75 75 75 5 5 0
July 30 200 625 200 75 75 0 0 0
August 30 200 625 200 75 75 0 0 0
September 30 75 625 200 75 75 0 0 0
October 0 30 625 200 75 75 0 0 0
November 0 5 400 200 30 75 0 30 5
December 0 0 400 200 75 75 30 30 5
& CRUTZEN;TI A kilrC
90
65
40
15
-10
-35
-60
ASELMAN & CRUTZEN90
65
40
15
-10
-35
-60
Figs. 4 & 5
23
90
65
40
15
-10
-35
-60
90
65
40
15
-10
-35
-60
Figs. 6 & 7
24
90
65
40
15
-10
-35
-60
90
65
40
15
-10
-35
-60
Figs. 8 & 9
25
CRII T7
0 60 180
Figs. 10 & 11
26
ASEL90
65
40
15
-10
-35
-60
90
65
40
15
-10
-35
0.5 To1.(
.120.-120180 -60
ASFI I
30.0 TO 40.(20.0 To030,10.0 T020.C5.0 To10.01.0 TO 5.00.5 TO1.0
,0.0 T 0.5
-120-60
-1 -60
90
65
40
15
-10
-35
-60
90
65
40
15
-10
-35
-60
Figs. 12 & 13
27
ASELMAN & CRUTZEN
-120 -60 0 60 120
ASELMAN & CRUTZEN
-120 -60 0 60 120
Figs. 14.a & 14.b
28
90
65
40
15
-10
-35
-60-180 180
90
65
40
15
-10
-35
-60-180 180
90
65
40
15
-10
-35
-60
90
65
40
15
-10
-35
-60
-180 -120 -60 0 60 120 180
-180 -120 -60 0 60 120 180
Figs. 14.c & 14.d
29
ASELMAN
-60
& CRUTZEN
0 60
ASELMAN & CRUTZEN
-120 -60 0 60 120
Figs. 14.e & 14.f
30
90
65
40
15
-10
-35
-60-180 -120 120 180
90
65
40
15
-10
-35
-60-180 180
ASELMAN & CRUTZEN
-120 -60 0 60 120
ASELMAN & CRUTZEN
-120 -60 0 60 120
Figs. 14.g & 14.h
31
180
90
65
40
15
-10
-35
-60
90
65
40
15
-10
-35
-60
180
-180 180
ASELMAN & CRUTZEN
-120 -60 0 60 120
ASELMAN & CRUTZEN
-120 -60 0 60 120
Figs. 14.i & 14.j
32
90
65
40
15
-10
-35
- n60-180 180
90
65
40
15
-10
-35
- 60-180 180
ASELMAN & CRUTZEN
-120 -60 0 60 120
ASELMAN & CRUTZEN
-120 -60 0 60 120
Figs. 14.k & 14.1
33
90
65
40
15
-10
-35
-60-180 180
90
65
40
15
-10
-35
-60-180 180
ASELMAN & CRUTZEN
-120 -60 0 60 120
-120 -60 0 60 120
Figs. 15.a & 15.b
34
-180
90
65
40
15
-10
-35
-60
90
65
40
15
-10
-35
-60
180
180 180
ASELMAN & CRUTZEN
-60 0 60
ASELMAN & CRUTZEN
-120 -60 0 60 120
Figs. 15.c & 15.d
35
90
65
40
15
-10
-35
-60-180 -120 120 180
90
65
40
15
-10
-35
-60-180 180
ASELMAN90
65
40
15
-10
-35
-Rn
& CRUTZEN
-120 -60 0 60 120
-120 -60 0 60 120
Figs. 15.e & 15.f
36
v -
-180 180
90
65
40
15
-10
-35
- I60-180 180
ASELMAN & CRUTZEN
-120 -60 0 60 120
ASELMAN & CRUTZEN
-120 -60 0 60 120
Figs. 15.g & 15.h
37
90
65
40
15
-10
-35
_- n-18-180 180
90
65
40
15
-10
-35
-60-180 180
ASELMAN & CRUTZEN90
65
40
15
-10
-35
-60
90
65
40
15
-10
-35
-60
-180 -120 -60 0 60 120 180
-180 -120 -60 0 60 120 180
Figs. 15.i & 15.j
38
ASELMAN90
65
40
15
-10
-35
- fin
& CRUTZEN
-120 -60 0 60 120
ASELMAN & CRUTZEN
-120 -60 0 60 120
Figs. 15.k & 15.1
39
-180 180
90-
65
40
15
-10
-35
- 60-180 180
90
65
40
15
-10
-35
_-Cn-180 -120 -60 0 60 120 180
90
65
40
15
-10
-35
-60v v
-180 -120 -60 0 60 120 180
Figs. 16.a & 16.b
40
I
I
& CRUTZEN*90
65
40
15
-10
-35
-60
90
65
40
15
-10
-35
-60
-180 -120 -60 0 60 120 180
-180 -120 -60 0 60 120 180
Figs. 16.c & 16.d
41
90
65
40
15
-10
-35
-R60-180 -120 -60 0 60 120 180
90
65
40
15
-10
-35
-60-180 -120 -60 0 60 120 180
Figs. 16.e & 16.f
42
I
ASFI MAN & CRIUT7FN
-120 -60 0 60 120
ASELMAN & CRUTZEN
-120 -60 0 60 120
Figs. 16.g & 16.h
43
90
65
40
15
-10
-35
-60-180 180
90
65
40
15
-10
-35
-60-180 180
ASELMAN & CRUTZEN
-120 -60 0 60 120
-120 -60 60 60120
Figs. 16.i & 16.j
44
90
65
40
15
-10
-35
-gnv- v
-180 180
90
65
40
15
-10
-35
-60-180 180
90
65
40
15
-10
-35
-60
90
65
40
15
-10
-35
-60_ _
-180 -120 -60 0 60 120 180
-180 -120 -60 0 60 120 180
Figs. 16.k & 16.1
45
A & C FLOODPLAINS
-120 -60 0 60 120
-120 -60 0 60 120
Figs. 17. & 18.
46
-180
90
65
40
15
-'10
-35
-60
90
65
40
15
-10
-35
-60
180
-180 180
Figure 19.BOGS 72 72 Asolman+Crutzen bog % area
-173-163-153-142-133-123-113-103 -93 -83 -73 -63 -53 -43 -33 -23 -13 -2 8 18 28 38 47 58 68 77 88 98 108 118 128 138 148 158 168 178
92710 19 8971 2
2241610 31212413 6 8 913
1 1102223 5 72712 1211171110253723 3 312 3
1 3 3 4 71615153424 8 21010 42 1 1 811202617 3 2
41410 2 13 41 12 2
2 432 41 1
4 1143113226 3 9423310 3 7 231 6 9
1 51617 4 9 912192944 2297 4 4 3 517 5 4 4 21527403238255 2 1 32016 2 6 2 2536534536466 1 33 5 2 6 3 7224250 5
5 1
31 1
1 21
47
7
1 1211
2 62010
5 412644
4 22072
4 211 7
323 27
88.886.283.881.278.876.373.871.268.866.263.861.358.856.353.851.348.846.243.841.338.736.333.731.328.826.223.821.218.816.213.711.2
8.76.23.71.2-1.2-3.7-6.2-8.8
-11.2-13.7-16.2-18.8-21.3-23.8-26.2-28.8-31.2-33.8-36.3-38.8-41.2-43.8-46.2-48.8-51.3-53.8-56.3-58.8-61.3-63.8-66.2-68.8-71.3-73.8-76.3-78.8-81.2-83.8-86.2-88.8
12 3
256
13
5 3535 5
1816