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.

iv

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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

6

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.

11

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

T3.T __ -- 330013.1S1 -- 30300

T3.TS-- -- -- -- -- 3Tll33.11--- 46300

53.7s~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~510

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435;== .113. 04... 3. … 01 ….6.= ° 2 ....... - 333

33;.T ,s -;73 - - -., = i, _9 j,._9 3. I =Z ... .03 0 -7 °.- 1 03. 6.4 32,:3;3S.1 -- I… . 3 .3 3.3 3. .3 . 3 1321301111

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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

63.TSf3636I.2 3-…- 310016.1T 3010013.21 ---- -- -- -36100-13.TS - - 0 4330

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