NCAR/TN-416+STR NCAR TECHNICAL NOTE I - I September 1995

The Global Distribution of Freshwater

L. M. Stillwell-Soller L. F. Klinger D. Pollard S. L. Thompson

CLIMATE AND GLOBAL DYNAMICS DIVISION I NATIONAL CENTER FOR ATMOSPHERIC RESEARCH BOULDER, COLORADO TABLE OF CONTENTS

Page

List of Tables ...... i List of Figures ...... iv Preface ...... v Acknowledgments ...... vi v. I Introduction ...... 1 II Scientific Rationale ...... 3 III Description of Data ...... 5 IV Presentation of Figures ...... V Data Files ...... 9 References ...... 10 Table Captions ...... 13 Figure Captions ...... 18

ii LIST OF TABLES

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Table 1. Aselman & Crutzen categories ...... 14

Table 2. Aselman & Crutzen wetland category descriptions ...... 15

Table 3. Wetland categories used and corresponding data files ...... 16

Table 4. and vegetation types...... 17

iii LIST OF FIGURES

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Figure 1. Aselman & Crutzen's global distribution of wet-cultivation 20 rice paddies Figure 2. Aselman & Crutzen's monthly cultivated area of wet- 21 cultivation rice paddies for 10°latitude belts. Figure 3. Mid-range values for Aselman & Crutzen's wet-cultivation 22 rice paddy area. Figure 4. Distribution of total freshwater natural wetlands. 23 Figure 5. Distribution of wet-cultivation rice paddies. 23 Figure 6. Distribution of . 24 Figure 7. Distribution of . 24 Figure 8. Distribution of Permanent . 25 Figure 9. Distribution of Permanent . 25 Figure 10. Distribution of Shallow 26 Figure 11. Distribution of Permanent Floodplains. 26 Figure 12. Distribution of Seasonal Floodplains 27 Figure 13. Distribution of Seasonal Swamps/Marshes. 27 Figures 14.a-14.1 Monthly distributions of Seasonal wet-cultivation Rice 28 Paddies. Figures 15.a-15.1 Monthly distribution of Seasonal Floodplains. 34 Figures 16.a-16.1 Monthly distribution of Seasonal Swamps/Marshes. 40 Figure 17. Seasonal Floodplains with unknown monthly variation. 46 Figure 18. Seasonal Swamps/Marshes with unknown monthly varia- 46 tion. Figure 19. Example of the ASCII text format for data files. 47

iv 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 , 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 /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 included because their original data was compiled specifically for the study of 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 (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 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 . 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 . 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/ 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 the seasonal 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, , 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 , 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 . 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. Doctoral dissertation, University of Colorado, Boulder, CO.

;___ , S.A. Elias, V.M. Behan-Pelletier and N.E. Williams, 1990: The bog climax hypothesis: 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 lowland. J. Geophys. Res., 99, 1469-1494.

, 1991: Peatland formation and ice ages: A possible Gaian mechanism related to community 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. of NASA 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 GCM simulation 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 Description

Bog Peat producing Moist climates Nutrient and water input from precipitation Risen above land surface Extremely acidic Nutrient deficient Major vegetation: moss

Fen Peat producing Nutrient input through soil water Mildly acidic or alkaline Major vegetation: grasses, hedges, and mosses Major regions: boreal, tundra

Swamps Forested Waterlogged or inundated soils Minimal peat accumulation Permanent or Seasonal

Marshes Herbaceous Gravitational water levels Permanent or seasonal Major vegetation: grasses, sedges or reeds

Floodplains Periodically flooded areas along rivers or lakes

Lakes Shallow bodies of water < "a few meters" in depth

Rice Paddies Periodically flooded areas used for wet cultivation of rice

14 Table 2.

CATEGORY SEASONAL AC SUB-CATEGORY (their 'Type')

Bog Permanent raised raised with hollows + pools raised, plateaux raised, forested doomed, with lakes doomed blanked Plateaux, Polygonal Palsas String bogs homogeneous wet with hollows dry with sedges Restiad bogs Bog-fen complex

Fen Permanent horizontal/sloping sloping horizontal spring fen polygonal polygonal/homogeneous polygonal, sedges sedges + mosses homogeneous Aapa/mixed mires

Swamps Permanent wooded or shrubby forested

Marshes Permanent , Phragmites Papyrus herbaceous

Swamps/Marshes Seasonal Igapo wooded or shrubby Varzea Papyrus herbaceous

Floodplain Permanent flooded Savannas

Floodplain Seasonal flooded Savannas

Lakes Permanent shallow only

15 Table 3.

CATEGORY DATA FILE

Total Natural total.dat Wetlands Bog bogs.lxl bogs.coarse bogs-ack. xl bogs_ ack.coarse Fen fens. lxl fens.coarse fens-ack.1 x 1 fens_ ack.coarse Swamp swamps.lxl swamps.coarse Marsh marsh.lx1 marsh.coarse Seasonal swamp-marsh. lxl swamp-marsh.coarse Swamp/Marsh swpjan.lxl swpfeb.lxl swpmar.lxl swpapr.lxl swpmay.lxl swpjun.lxl swpjul.lxl swpaug.lxl swpsep.lxl swpoct.lxl swpnov.lxl swpdec.lxl swpjan.coarse swpfeb.coarse swpmar.coarse swpapr.coarse swpmay.coarse swpjun.coarse swpjul.coarse swpaug.coarse swpsep.coarse swpoct.coarse swpnov.coarse swpdec.coarse

Permanent pfloodplain.lxl pfloodplain .coarse Floodplain Seasonal sfloodplain.lxl sfloodplain.coarse Floodplain fldjan. xl fldfeb.lxl fldmar.lxl fldapr. lxl fldmay.lxl fldjun.lxl fldjul.lxl fldaug.lxl fldsep.lxl fldoct. xl fldnov.lxl flddec.lxl fldjan.coarse fldfeb.coarse fldmar.coarse fldapr.coarse fldmay.coarse fldjun.coarse fldjul.coarse fldaug.coarse fldsep.coarse fldoct.coarse fldnov.coarse flddec.coarse Lakes lakes.lxl lakes.coarse Rice Paddies ricepd.lxl ricepd.coarse jan-ricepd.lxl feb-ricepd.lxl mar-ricepd.lxl apr-ricepd.lxl may-ricepd.lxl jun-ricepd.lxl jul-ricepd.lxl aug-ricepd.lxl sep-ricepd.lxl oct-ricepd.lxl nov-ricepd.lxl dec-ricepd.lxl jan-ricepd.coarse feb-ricepd.coarse mar-ricepd.coarse apr-ricepd.coarse may-ricepd.coarse jun-ricepd.coarse jul-ricepd.coarse aug-ricepd.coarse sep-ricepd.coarse oct-ricepd.coarse nov-ricepd.coarse dec-ricepd.coarse -I

16 Table 4 Percentage cover of bogs and fens within major vegetation types for the six geographic 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 Fen Hemlock-spruce 12 8 14 6 16 4 14 6 16 4 16 4 forest Spruce-birch 6 4 7 3 8 2 7 3 8 2 8 2 forest Black spruce 30 20 35 15 40 10 35 15 40 10 40 10 forest 54 36 63 27 72 18 63 27 72 18 72 18 Alder 3 2 3.5 1.5 4 1 3.5 1.5 4 1 4 1 thickets Cottongrass 36 24 42 18 48 12 42 18 48 12 48 12 tundra Sedge 48 32 56 24 64 16 56 24 64 16 64 16 tundra Dryas 3 2 3.5 1.5 4 1 3.5 1.5 4 1 4 1 meadows Aleutian 6 4 7 3 8 2 7 3 8 2 8 2 meadows Aleutian 6 4 7 3 8 2 7 3 8 2 8 2 heath

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 from Aselman & Crutzen's (1989) data set.

Figure 11. Distribution of Permanent Floodplains in percent of area covered, interpolated from Aselman & Crutzen's (1989) data set.

Figure 12. Distribution of Seasonal Floodplains in percent of area covered, interpolated from 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 seasonal swamps and seasonal marshes.

Figures 14.a-14.1 Monthly Distributions of Seasonal wet-cultivation Rice Paddies in percent of area covered, produced by combining Aselman & Crutzen's (1989) global rice-paddy map with their zonally integrated seasonal-variation information (see text).

Figures 15.a-15.1 Monthly Distribution of Seasonal Floodplains in percent of area covered, produced by combining Aselman & Crutzen's (1989) global seasonal floodplains map with their seasonal-variation data.

Figures 16.a-16.1 Monthly Distribution of Seasonal Swamps/Marshes in percent of area covered, produced by combining Aselman & Crutzen's (1989) global maps of seasonal swamps and seasonal marshes, and combining with their seasonal-variation data.

Figure 17. Seasonal Floodplains with unknown monthly variation, in percent of area covered. 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 area covered. These are regions with seasonal swamps and/or seasonal marshes according to 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. 4. . 2.5 s T2.2 5 32 02. 31.5 22.s 32.S 42.S 352.1 362.S 12.s

63.T 3. 1. 35t.15 363033 61.2S 3$1.U

T3.T __ -- 3300 13.1S1 -- 30300 T3.TS------3Tll 33.11--- 46300

35.11 WI111 63.3SS.5 …… . .... -- .800 33..< 53.7s~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~510 13.15.T`S - -…4 __ ------.3...... -. -- -83113113 -1- - -46 1 46.21- ...... 6. 0.6 .... 0. 6 1 3 3 60. - - 0.-...... 3336ilI 3I 53«.2T 01…3-- -- 3--3

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

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

2 23.21…5~~~~~~~~~~~~~~~~~~~~~~~~~~~~.6 2.043.3 3333 4.3 - - 2.0 30.0' 'I3.I3 1336300 23.15…1.6 3.TS ~~~~~~~O.I_ .'l __ O_ -- 1.0 I 53 32334.. O 1651 ,--32 153. 21 233333't5<) 23.25…6 --. . .26.4 31.49--0 19.1 T.2 344333 36.1…1 T 3.2 T1. 13.5 2.3 3.0 2.4 4230I 36.32 ... …34 4.3 83. s.* 30.2 3 2 06 33.11 ...... 0.1 3433 3...... I I3503 0 613.3…53.I4 20330 4.42.2 353500 6.2 3. 2.0…… 3.6 3. 6.115.2 2.2 I52710.3 -0.a35 C. 0 - 0. -- 0. 2 3.0 - 2.3 3536 3.1S 0.1.. O-.4 - 31431133 3f.31 I.3.2 -« 6.6. -3.6 - 6.0.3 6.1- 4.1 0.5 0.4 - 3145330541330 - -- -38.TS.3.T11;_ _ 888 4.1- . - 011.. --- .M831.- -06.1 IS4S-.12132653333 Sill# *3.31 3038TIT0. - _. -_ 0. 4.1 1341. 1.5 2.4S.88 -- - 3142333J3S1 l -6.TS-. - 1: 1: o:I 20.1 23533020. - - 33.T8-I.3 . -. - 0. ------_ T.. …0I. 13880001352TII _ __ O 3 - .3.11 -- 0.2 133.2 - 3533 .3.3T… .2 0.1 1.3 - - 3.3 3323 31 .331.5 . -0.T- _ .1` 0.40 33.TS8- 3.2 I434003 - -.*36.1 0 -- - - 3.

*31.3- -- .

-36.2135** . -- 323630 ^ & 4?:1 .45.11______Rice Paddlies - - " " - 3336331 .46.21 S.1..$ 36. .... - .J30663--333------1. a31. 2A. 5T.5 41T. 6T.1 61.6 TT. 3T.3 . 0T.S 31.1. 31.5 33.1 14T.S341 . 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 66.21 «3036433011 63.TSf363 6I.2 31003-…- 16.1T 30100 13.21 ------36100- 13.TS - - 43300 1325 4363 63.15……-- - -- _- 166300,7

S3.TS- ______300_ _ _ _ unio6 613.2 - 143)00 63.15……… ______-_ 66200.II 56.11------3030 16.25 *f^53.15- 133 ------2I333 1.23S 66133Wo 46.11-46.25 ------3333330 1S633 43.TS1 333603 43.2 .0.3 .3 33 36.11o ^~~~~______=. 3. - -. ______J; 0--3 0_.2 3,3S033, -4312s36.25 0. … - Ii- 0. 32460 523.1 S~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~3.1. - - - 13,,s... 3.2 3350 - - - - .T - - - 332301 21S - - - 0.6 - - 3S110 26.2S-.*- - - - 33600 23.1 ------414031 21.25 - - - 0.3 0.1 - - 44333 33.1-- -- 0.3 - 1.2 . -1 - - 4630U 36.35 0. - 602 0.3 3403004 132.1 0.3 0.I - O.S - ISO35 I33.T S 0.3 - O.I.20. . 0. - . S3I53 6* 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 -- - 430420 1.2»- - - = - . -- -- 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 - 3333131 26.TS-- -- 0.2 6.6 3133.3lI3 .3 1.2 -- -- - I.S 1321 -33.TS 0.2 - 0.2 . 12311Sn 36.2 - - 3463.2- .38.T1 31231111 '.335 Rice Paddies I 363 -4 S 03.. I2 1 13 2.33633 -46.25 333f33e0 -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' ] 1oI [r.j so-100 I o0.001 -1 " 100 -300

1 - 10 : ~ 300-500 EI 10 - 50 m 500 -750

Fig. 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

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

22 & CRUTZEN ;TI A kilrC 90

65

40

15

-10

-35

-60

ASELMAN & CRUTZEN 90

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 ASEL 90

65

40

15

-10

-35 0.5 To1.( -60 .120. 180 -120 -60 ASFI I CRII T7 90

65

40

15 30.0 TO 40.( -10 20.0 To030, 10.0 T020.C 5.0 To10.0 -35 1.0 TO 5.0 0.5 TO1.0 -60 ,0.0 T 0.5 -1 -120 -60 0 60 180

Figs. 10 & 11

26 90

65

40

15

-10

-35

-60

90

65

40

15

-10

-35

-60

Figs. 12 & 13

27 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

Figs. 14.a & 14.b

28 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

Figs. 14.c & 14.d

29 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

Figs. 14.e & 14.f

30 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 180 -120 -60 0 60 120 180 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

Figs. 14.g & 14.h

31 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

- n60 -180 -120 -60 0 60 120 180 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

- 60 -180 -120 -60 0 60 120 180

Figs. 14.i & 14.j

32 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

Figs. 14.k & 14.1

33 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

90

65

40

15

-10

-35

-60 180 -120 -60 0 60 120 180

Figs. 15.a & 15.b

34 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

Figs. 15.c & 15.d

35 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-Rnv - -180 -120 -60 0 60 120 180

90

65

40

15

-10

-35

- I60 -180 -120 -60 0 60 120 180

Figs. 15.e & 15.f

36 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

_--18 n -180 -120 -60 0 60 120 180 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

Figs. 15.g & 15.h

37 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

Figs. 15.i & 15.j

38 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

- fin -180 -120 -60 0 60 120 180 ASELMAN & CRUTZEN 90-

65

40

15

-10

-35

- 60 -180 -120 -60 0 60 120 180

Figs. 15.k & 15.1

39 90

65

40

15

-10

-35

_-Cn -180 -120 -60 0 60 120 180

90

65

40

I 15

-10

-35

I -60v v -180 -120 -60 0 60 120 180

Figs. 16.a & 16.b

40 & CRUTZEN *90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

90

65

40

15

-10

-35

-60 -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 I -180 -120 -60 0 60 120 180

Figs. 16.e & 16.f

42 ASFI MAN & CRIUT7FN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

Figs. 16.g & 16.h

43 ASELMAN & CRUTZEN 90

65

40

15

-10

-35

-gnv- v -180 -120 -60 0 60 120 180

90

65

40

15

-10

-35

-60 -180 -120 -60 60 60120 180

Figs. 16.i & 16.j

44 90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

90

65

40

15

-10

-35

-60_ _ -180 -120 -60 0 60 120 180

Figs. 16.k & 16.1

45 A & C FLOODPLAINS 90

65

40

15

-'10

-35

-60 -180 -120 -60 0 60 120 180

90

65

40

15

-10

-35

-60 -180 -120 -60 0 60 120 180

Figs. 17. & 18.

46 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 88.8 86.2 83.8 81.2 78.8 76.3 73.8 1 1 71.2 211 5 412 68.8 7 92710 1 4 114311322 2 6 644 66.2 9 8971 2 6 3 9423310 3 7 231 6 9 2010 63.8 2241610 3 1 51617 4 9 912192944 229 61.3 1212413 6 8 913 7 4 4 3 517 5 4 4 2152740323825 58.8 1 1102223 5 72712 1 2 4 5 2 1 32016 2 6 2 253653453646 4 2 56.3 211171110253723 3 312 3 3 6 1 33 5 2 6 3 7224250 5 20 53.8 1 3 3 4 71615153424 8 21010 4 2 4 5 1 4 2 7 51.3 2 1 1 811202617 3 2 1 1 11 7 2 48.8 41410 2 13 4 323 2 46.2 1 12 2 7 43.8 41.3 38.7 36.3 3 33.7 1 1 31.3 1 2 28.8 1 26.2 23.8 21.2 18.8 16.2 13.7 11.2 8.7 6.2 1 3.7 2 3 5 3 1.2 25 53 -1.2 6 5 5 -3.7 13 18 -6.2 16 -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

47