U.S. Geological Survey

Climate-Vegetation Atlas of North America

Introduction, Methods, and Sources of Data


On the continental scale, climate is the primary determinant for the overall geographic ranges of plant species (Woodward, 1987; Woodward and Williams, 1987). Geologic studies reveal that the geographic locations and extents of plant species have changed greatly as climate has varied in the past (e.g., Huntley and Webb, 1988; Wright and others, 1993). In this volume we explore the climatic parameters that may likely control the modern distributions of selected plant taxa for North America. The data presented here may be used in the reconstruction of past climates from paleoecological data, in the estimation of the potential future ranges of important trees and shrubs under various global-change scenarios (such as those depicted by Houghton and others, 1996, and Thompson and others, 1998), and in validation exercises that compare past plant distributions with those simulated based on numerical-climate-model simulations of past climates (Bartlein and others, 1998). This information may also be useful in a variety of ecological and biogeographic studies, particularly in generating hypotheses for testing.

This atlas presents information on the modern relations between climate and the distributions of 407 plant taxa and biogeographic entities from across North America. Included among these are 115 conifer species, 32 conifer groups (such as the genera and subgenera), 239 hardwood species, and 21 hardwood groups.

The atlas is divided into two volumes. The first volume, U.S. Geological Survey (USGS) Professional Paper 1650-A, contains the Abstract, Introduction (including supporting figures and tables), References Cited, and the atlas pages for conifers. The second volume, USGS Professional Paper 1650-B, contains the Abstract, an abbreviated Introduction (including supporting tables), and the atlas pages for hardwoods. These two volumes are published together and are not available separately. In the first part of each volume, we provide atlas pages of graphical displays of the modern relations between climate and distributions of important trees and shrubs in North America. The graphical displays include (1) maps of geographic distributions of taxa; (2) univariate plots that indicate the presence or absence of the taxon under consideration in relation to single climatic (mean January, July, and annual temperature; mean January, July, and annual precipitation) and bioclimatic (growing degree days, mean temperature of the coldest month, and moisture index) variables; (3) bivariate plots that illustrate the presence and absence of the taxon for various combinations of seasonal temperatures, seasonal precipitation, July temperature (a proxy for growing-season temperature), and annual precipitation; and (4) complex displays that indicate the presence and absence of the taxon in relation to combinations of the three bioclimatic variables.

In the second part of each volume, we provide atlas pages of histograms for each taxon that display the percentage of the total number of grid points for the taxon that occur within a specified range of each climatic or bioclimatic variable. This information permits the user to see where the taxon is most abundant and also to examine the variability of a taxon along specific environmental gradients. In the third part of each volume, the histogram data are presented in tabular form so that users can obtain quantitative information without having to interpret the data from the visual displays.

Methodology and Sources of Data

We constructed an equal-area grid for North America, each point of which was approximately 25 km from each adjacent point ("25-km grid" in this report), to compare the modern distributions of plant taxa with climatic parameters (fig. 1). Thirty-year climate "normals" for the period 1951 to 1980 were taken where possible from more than 8,000 weather stations in Canada, the United States, Mexico, and Central America (Canadian Climate Program, 1982a, 1982b; WeatherDisc Associates, 1989; Willmott and others, 1981). In some regions, when data were sparse, a small number of stations were included with different, and possibly shorter, normal periods. There are few weather stations in the Arctic and parts of Central America, and in these regions we supplemented the station data with data digitized from the World Meteorological Organization atlas for North America (Steinhauser, 1979). Information is also sparse on snowfall in the mountains of the Western United States, and in this area we used SNOTEL data (Dolph and Marks, 1992; Barton and Burke, 1977; Rallison, 1981) to augment the available information from weather stations.

We used the singular value decomposition least-squares estimation technique (Press and others, 1986) with the modern climatic data to develop regression equations that allowed us to estimate the monthly and annual values for temperature and precipitation at each point on the 25-km grid as functions of location and elevation (figs. 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, and 14) (Lipsitz, 1988; Bartlein and others, 1994). A separate regression equation was used for each target grid point using observations from the vicinity of the target point. Elevation data from the ETOPO5 5-minute topographic grid (Edwards, 1992) were used to provide information for the estimates at each grid point-experimentation revealed that elevation was a reliable predictor of temperature, whereas smoothed elevation worked best for estimation of precipitation. After estimating the monthly temperature and precipitation values, we calculated a series of "bioclimatic" variables that have been demonstrated to more directly control plant distributions than do temperature and precipitation (Prentice and others, 1992; Sykes and others, 1996). The bioclimatic variables employed here are (1) the mean temperature of the coldest month (MTCO, Prentice and others, 1992), (2) growing degree days on a 5°C base (GDD5, Newman, 1980), and (3) a moisture index (MI) that incorporates the full seasonal cycle of precipitation and evapotranspiration (actual evaporation/potential evaporation (AE/PE), based on Thornthwaite and Mather, 1955, 1957; Willmott and others, 1985).

Nearly all of the range maps were obtained from atlases of tree and shrub distributions compiled by Elbert L. Little, Jr. and his associates at the Forest Service of the U.S. Department of Agriculture (Little, 1971, 1976, 1977; Critchfield and Little, 1966). Additional distribution maps were obtained from Bailey (1970), Benson and Darrow (1981) and Yang (1970). The original source for each map is listed in table 1, and table 2 shows the species comprising the groups listed in table 1. For each taxon, we digitized the distribution map and determined at which of the points on the 25-km grid the taxon was present. This information was merged with climate information to create a presence- absence matrix of plant distributions associated with modern climatic (and bioclimatic) data. Graphical displays were then prepared to illustrate the modern geographic distribution of the taxon under consideration and the relations between the plant's distribution and climatic parameters. There have been no mathematical manipulations of the presence-absence data in the following figures and tables. Instead, these figures and tables display the relationships between plant distributions and climate simply by plotting both the presences and absences of the plants in relation to climatic parameters.

Displays of Geographic Distributions and Climatic Relations

A sample graphical display presented in this atlas is shown in figure 15. In this portrayal of the relationships among the modern geographic distribution and climatic parameters for Pinus edulis (pinyon pine), each panel (or groups of panels) is labeled with a letter that is used to demarcate a portion of the atlas page for the following discussion.

Panel "a" on each atlas page (graphical display) illustrates the modern distribution of the taxon on the 25-km grid. Figure 16 illustrates the distributions (taken from the individual atlas pages for these taxa) of four species of pines that inhabit different areas of North America and that presumably have very different climatic tolerances. Each species is portrayed by depicting the grid points where the taxon is present and omitting those where the taxon is absent. In the sample shown here, Pinus edulis inhabits the mesas and mountain slopes of the Colorado Plateau region of the American Southwest; P. engelmannii (Apache pine) lives in subtropical semiarid northwestern Mexico; P. banksiana (jack pine) forms a major constituent of the boreal forest and northern mixed forest of Canada and the Northeastern United States; and P. clausa (sand pine) lives in moist subtropical environments in central Florida.

Panel "b" on each atlas page shows univariate plots of the presence and absence of each taxon relative to single climatic parameters. Each box contains two lines of points: the upper line illustrates climate values at which the taxon is present, whereas the lower line indicates those where it is absent. Together, these two lines represent all grid points from across North America. In all cases, a given plant is absent from many sites where the recording of "presences" indicate that it should be able to survive under the environmental conditions represented by a single variable. This is probably because other climatic and (or) environmental variables, not portrayed in any one univariate view, control the plant's distribution. For example, for the four pine species (fig. 17), the upper three boxes in each panel represent mean annual, January, and July temperature (in °C). The three central boxes represent mean annual, January, and July precipitation (in mm) plotted on a logarithmic scale, which stretches out the distance between points on the lower end of the scale. The lower three boxes represent bioclimatic variables (discussed above) that should be more closely tied to the physiological limits of the plants than are temperature and precipitation (Prentice and others, 1992). The mean temperature of the coldest month (MTCO) represents the coldest conditions experienced by the plant over the course of a year--MTCO is usually, but not always, January in North America. Growing degree days on a 5°C base (GDD5, Newman, 1980) represents the total amount of energy available to the plant through the course of the year (incorporation of information on both the length and intensity of the growing season), and actual evaporation divided by potential evaporation is a moisture index (MI) based on Thornthwaite and Mather (1955, 1957) and implemented by Willmott and others (1985). The latter index incorporates the full seasonal cycle of precipitation and temperature, as well as soil moisture and moisture storage in snowpack. This index is probably a more realistic depiction of the moisture conditions experienced by plants than either seasonal or mean annual precipitation. Regions where moisture is sufficient to maintain evaporation at its potential rate (i.e., humid regions) have moisture-index values close to 1.0, whereas dry regions have moisture-index values somewhat less than 1.0.

The comparison of the four pine species shown in figure 17 illustrates their different adaptations in regard to temperature. Pinus clausa is limited to environments where mean January temperatures are above 10°C and mean July temperatures are in a limited range at the very warm part of the scale. P. engelmannii is also apparently intolerant of freezing temperatures, but it is not as limited by cold as is P. clausa. It also has a larger range of acceptable July temperatures than does P. clausa. P. edulis can survive freezing temperatures but does not survive mean winter temperatures below -10°C. P. banksiana lives in a summer temperature regime that is slightly cooler than that of P. edulis, but it lives under much colder winter climates (well below -10°C). Similar patterns are evident in the comparisons of the MTCO and GDD5 for these taxa.

Panel "c" of figure 15 uses bivariate plots to illustrate potential interactions among climatic variables in controlling plant species' ranges. Here, gray dots represent where the taxon is absent, black dots where it is present. Gray and black together represent the total climate space of North America as depicted for the particular combination of climatic parameters presented. For example, the left-hand box in panel "c" illustrates the presence (or absence) of the species in relation to mean July temperature and mean annual precipitation. For most sites, these two parameters should provide a measure of growing-season temperature versus total moisture through the year. Comparisons among the four pine species in figure 18 shows that, in this "climate space," Pinus clausa inhabits a remarkably small area where mean July temperatures are very warm and mean annual rainfall is very high-these are some of the hottest and wettest environments in North America (it may also be that P. clausa is further limited to sandy substrates, as its name implies).

P. engelmannii, the other subtropical pine in this group of four species, lives under a wider range of summer temperatures and moisture conditions than P. clausa, and it also occupies a much greater geographic range. In contrast, P. banksiana lives in relatively cool summer environments under a wide range of moisture conditions. P. edulis inhabits environments with mean July temperatures between those of P. engelmannii and P. banksiana, but it lives in generally drier regions than either of these two other pines. The central box in panel "c" on figure 15 illustrates the presence (or absence) of the species relative to the seasonal extremes of mean January and July temperature. In the example shown here (fig. 18), P. clausa lives under a narrow band of hot July conditions and a slightly broader range of warm January temperatures. P. engelmannii has a broader range of tolerance for July and January temperatures, although still within the warm end of the spectrum for both months. P. edulis lives in moderately warm July environments with January temperatures generally near freezing, whereas P. banksiana is adapted to moderate July temperatures and very cold January temperatures. The right-hand box in panel "c" (figs. 15 and 18) provides a similar view of species presence (or absence) in relation to mean January and July precipitation. Here, it can be seen that P. engelmannii lives under a strongly summer precipitation dominated regime with little January precipitation; P. clausa receives abundant rainfall in both seasons; P. banksiana lives under a relatively narrow range of July precipitation and a larger range of January precipitation; and P. edulis is adapted to moderate levels of precipitation in both winter and summer.

Panel "d" (fig. 15) incorporates the three bioclimatic variables into a single figure (see Huntley and others, 1995, for a similar presentation of correspondences between climatic parameters and tree distributions in Europe). Each of the four boxes within this panel represents a quartile of the moisture conditions in North America, from the driest quarter of the grid cells on the left to the wettest on the right. Within each box, the presence (black) or absence (gray) of each species is plotted relative to GDD5 and MTCO. In the example shown in figure 19, Pinus clausa lives in a very restricted range in the wettest and warmest environments of North America. In contrast, P. banksiana lives across the spectrum from dry to wet sites but is restricted to locations where MTCO is below freezing and GDD5 is less than approximately 2,500. P. edulis and P. engelmannii both inhabit environments in the lower three quartiles of the moisture index, with P. edulis more common toward the dry end. MTCO and GDD5 differentiate the climates of these two pines, with P. engelmannii restricted to environments with warmer winters and greater total energy inputs (GDD5) over the course of the year.

In terms of precipitation and moisture conditions, the climatic distribution of P. clausa falls at the extreme wet end of the moisture index (>0.9), and the precipitation plots indicate that it receives more moisture in July than in January. The other three pine species survive in a fairly wide range of moisture conditions (as seen in the moisture-index plots), but live in different seasonal precipitation regimes. P. engelmannii lives under moisture conditions ranging from only slightly drier than the moisture-requiring P. clausa to moderately dry environments, with July precipitation dominant over January. P. edulis is the most drought-adapted of the four pines and lives under a nearly even mix of January and July precipitation. P. banksiana lives under moisture conditions that range from moderately dry to very moist, with January and July precipitation nearly equally dominant.

For species with five or fewer occurrences on the North American climate grid (18 conifer species, 9 hardwood species), we identified grid points closest to the digitized polygons that represent the range of each species and used these grid points to approximate climatic parameters. The atlas pages with graphical displays for these species have the text "minimal data-nearest grid points used with environmental parameters" after the species name at the top of the page. These species were treated differently than more abundant species in that (1) large dots were used on the species map to indicate the grid points used in the analysis, (2) "absence data" were not plotted on the displays of distribution against climatic parameters, and (3) the species were not included in the histograms or tables.

Histograms of Relations Between Plant Distributions and Single Climatic Variables

Histograms that depict the number of occurrences of each taxon in relation to a given range of each of the climatic and bioclimatic variables are also presented in this atlas. For example, in figure 20 the width of each bar represents a specified range (1°C) of mean annual (left), January (middle), or July (right) temperature. The height of each bar represents the percentage of the total number of occurrences of a taxon relative to the total number of grid cells at that specified range of temperature. The gray histograms at the bottom of the page show the number of grid cells within each specified temperature range for all of North America. The nine pine species illustrated here represent north- to-south transects in western (Pinus flexilis [limber pine], P. ponderosa [ponderosa pine], P. edulis, P. engelmannii) and eastern (P. banksiana, P. resinosa [red pine], P. rigida [pitch pine], P. serotina [pond pine], P. clausa) North America.

Some taxa (e.g., P. clausa) have very narrow ranges of temperature requirements. Others, such as P. flexilis and P. ponderosa, live under a broader range of temperatures. Some appear to be limited by freezing winter temperatures (look at mean January temperature for P. engelmannii and P. serotina), whereas some require warmer winters (P. clausa). Many taxa have near-Gaussian distributions for temperature response, although some (for example, P. engelmannii) exhibit bimodal responses.

The same format is used in figure 21 to illustrate the species' distributions relative to mean annual, January, and July precipitation (log scale). As with temperature, some species live in narrow, clearly defined ranges (most of the eastern pines), whereas others (especially P. ponderosa) live under a wide range of precipitation regimes. Figure 22 shows the species' distributions in relation to the bioclimatic variables. The patterning for MTCO is very similar to that for mean January temperature. The histograms for GDD5 are similar to those for mean July temperature, but with some differences. P. clausa and P. serotina live under very narrow ranges of July temperatures but have broader ranges relative to GDD5. In regard to the moisture index (actual evaporation divided by potential evaporation), all the pines from eastern North America (except for P. banksiana) are at the wet end of the scale (MI = 0.9 and above). In contrast, western pines live under a variety of moisture conditions but are generally found in much drier habitats than their eastern counterparts.

Tables of Relations of Plant Distributions to Single Climatic Variables

The histograms presented above provide visual displays of the relations between species' distributions and climatic parameters. Tables 3 and 4 provide examples of data taken from these tables: the entries represent the climatic or bioclimatic variables that correspond with chosen cumulative percentages of the total number of grid points for each taxon. To obtain these values, we started a counter for each parameter at the left (low) end of the climatic or bioclimatic range and then moved up the scale until the first occurrence of the plant was encountered-this was labeled as the "0 percent" point. We then continued to move up the climatic scale until 10 percent of the total number of occurrences of the taxon had been encountered. This value on the climatic scale represents the conditions that correspond with 10 percent of the cumulative occurrences of the species. The same method was then employed to identify 25, 50, 75, 90, and 100 percent of the plant's distribution relative to the chosen climatic parameter. Although many of the distributions appear to be Gaussian, many are not, so we did not choose percentage values that would imply Gaussian distributions. The 0 to 100 percent values identify the total range of the taxon in relation to the given climatic or bioclimatic variable, although 10 to 90 percent may be more realistic representations of the taxon's range, given potential errors in modern climate estimation and range maps.

Table 3 illustrates these values for Pinus edulis, and inspection of these values provides a broad characterization of the distribution of this species in relation to climatic parameters. As an example of how to read this information, the first row of data indicates that this pine lives under mean January temperatures that range from -11.4°C (0 percent) to 5.8°C (100 percent), with the median (50 percent) temperature at -2.0°C. Comparisons of the breadth of climatic estimates for the apparent total range (0 to 100 percent) reveal that they are 1.75 to 3.0 times greater than those for the 10- to 90-percent band. This suggests that the total apparent climatic range includes outliers that may represent problems with the original range maps and (or) our estimates of present-day climatic means, and thus the apparent total range is probably overestimating the climatic tolerance of the taxon.

Table 4 provides comparisons of the median (50 percent) values for the distributions of the nine pine species discussed above relative to each of the climatic parameters. The median value represents the midpoint or most likely value for the occurrence of each species and thus provides a good starting point for comparing the climatic tolerances of the taxa. In table 4, the north-to-south gradients of the western pines (the first four species) and of the eastern pines (the last five species) are clearly evident in the temperature, MTCO, and GDD5 data. The precipitation and MI data reveal that the plants live under a variety of moisture regimes and that there are no simple north-to-south gradients in regard to moisture conditions.

Climatic Parameters and Plant Distributions

Examination of the figures and tables in this atlas will convince most readers that climate is an important element in the distribution of North American plant taxa, at least on the scale of the entire continent. On finer scales, competition among species, soil conditions, and other environmental factors strongly influence the actual distributions of plant species. As climate is constantly changing, it is highly likely that many species are currently adjusting their ranges, and thus the data in this atlas may underestimate the climatic tolerances of some taxa. It is also probable that some species could prosper in areas far from their native habitats, as planted Douglas-fir trees (native to western North America) do in parts of northeastern North America today. However, intervening natural barriers to immigration, such as the dry climates of the Great Plains for Douglas fir, have prevented these species from colonizing these far-away habitats.


Bev Lipsitz designed and conducted many of the analyses of the climatic data. Gary Selner and Dick Taylor kindly provided software that allowed us to digitize tree distributions and place them on the North American grid. Jenny Buchner, Eric Dorsett, Eric Fisher, Jeff Honke, David McIntyre, Larissa Agbulos, and Marketa McGuire digitized many of the tree distributions used in this study, and Bev D'Amato and Ollie Williams keypunched climatic data from Canada and Latin America. Laurie DeMarco (deceased) was very helpful in the initial stages of this research. Peter Schweitzer and Randy Schumann provided technical advice, and the USGS Global Change and Climate History Program funded this effort. We also thank Steve Jackson, Sarah Shafer, and Jack Williams for their thorough and valuable reviews of the manuscript. Rick Scott carefully edited the manuscript and Carol Quesenberry designed the cover and section dividers. Botanical illustrations were taken from Sudworth (1908).

References Cited

Bailey, D.K., 1970, Phytogeography and taxonomy of Pinus subsection Balfourianae: Annals of the Missouri Botanical Garden, v. 57, p. 210-249.

Bartlein, P.J., Anderson, K.H., Anderson, P.M., Edwards, M.E., Mock, C.J., Thompson, R.S., Webb, R.S., Webb, T., III, and Whitlock, C., 1998, Paleoclimate simulations for North America over the past 21,000 years: Features of the simulated climate and comparisons with paleoenvironmental data: Quaternary Science Reviews, v. 17, no. 6-7, p. 549-586.

Bartlein, P.J., Lipsitz, B.B., and Thompson, R.S., 1994, Modern climatic data for paleoenvironmental interpretations: American Quaternary Association Program and Abstracts of the 13th Biennial Meeting, 19-22 June 1994, p. 197.

Barton, M., and Burke, M., 1977, SNOTEL: An operational data acquisition system using meteor burst technology: Albuquerque, N. Mex., Proceedings of the 45th Western Snow Conference, p. 82-87.

Benson, L., and Darrow, R.A., 1981, Trees and shrubs of the southwestern deserts (3rd ed.): University of Arizona Press, 416 p.

Canadian Climate Program, 1982a, Canadian Climate Normals, Volume 2, Temperature, 1951-1980: Environment Canada.

---1982b, Canadian Climate Normals, Volume 3, Precipitation, 1951-1980: Environment Canada.

Critchfield, W.B., and Little, E.L., Jr., 1966, Geographic distribution of the pines of the world: U.S. Department of Agriculture Miscellaneous Publication, v. 991, p. 1-97.

Dolph, J., and Marks, D., 1992, Characterizing the distribution of observed precipitation and runoff over the continental United States: Climatic Change, v. 22, p. 99-119.

Edwards, M., 1992, Global gridded elevation and bathymetry, in Kineman, J.J., and Ohrenschall, M.A., eds., Global Ecosystems Database, Version 1.0 [CD-ROM], Documentation Manual, Disc A: National Geophysical Data Center, Key to Geophysical Records Documentation No. 26 [incorporated in Global Change Database, Volume 1: Boulder, Colo., National Oceanic and Atmospheric Administration, p. A14-1-A14-4].

Houghton, J.T., Meira Filho, L.G., Callander, B.A., Harris, N., Kattenberg, A., and Maskell, K., 1996, Climate change 1995, the science of climate change, contribution of working group I to the second assessment report of the intergovernmental panel on climate change: Cambridge, Cambridge University Press, 572 p.

Hultén, E., 1968, Flora of Alaska and neighboring territories, a manual of the vascular plants: Stanford, Stanford University Press, 1008 p.

Huntley, B., Berry, P.M., Cramer, W., and McDonald, A.P., 1995, Modeling present and potential future ranges of some European higher plants using climate response surfaces: Journal of Biogeography, v. 22, p. 967-100.

Huntley, B., and Webb, T., III, eds., 1988, Vegetation history, handbook of vegetation science, volume 7: Dordrecht, Kluwer Academic Publishers, 803 p.

Lipsitz, B.B., 1988, Climatic estimates for locations between weather stations in the Pacific Northwest: Comparison and application of two linear regression analysis methods: Eugene, Oreg., University of Oregon, M.A. thesis, 68 p.

Little, E.L., Jr., 1971, Atlas of United States trees, volume 1, conifers and important hardwoods: U.S. Department of Agriculture Miscellaneous Publication, v. 1146, 9 p., 200 maps.

---1976, Atlas of United States trees, volume 3, minor Western hardwoods: U.S. Department of Agriculture Miscellaneous Publication, v. 1314, 13 p., 290 maps.

---1977, Atlas of United States trees, volume 4, minor Eastern hardwoods: U.S. Department of Agriculture Miscellaneous Publication, v. 1342, 17 p., 230 maps.

Newman, J.E., 1980, Climate change impacts on the growing season of the North American "corn belt:" Biometeorology, v. 7, no. 2, p. 128-142.

Prentice, I.C., Cramer, W., Harrison, S.P., Leemans, R., Monserud, R.A., and Solomon, A.M., 1992, A global biome model based on plant physiology and dominance, soil properties and climate: Journal of Biogeography, v. 19, p. 117-134.

Press, W.H., Flannery, B.P., Teukolsky, S.A., and Vetterling, W.T., 1986, Numerical recipes, the art of scientific computing: Cambridge, Cambridge University Press, 818 p.

Rallison, R.E., 1981, Automated system for collecting snow and related hydrological data in mountains of the Western United States: Hydrological Science Bulletin, v. 26, p. 83-89.

Steinhauser, F., 1979, Climatic atlas of North and Central America, I, maps of mean temperature and precipitation: Hungary-World Meteorological Organization, UNESCO, 28 maps.

Sudworth, G.B., 1908, Forest trees of the Pacific slope: Washington, U.S. Department of Agriculture, Forest Service, 441 p.

Sykes, M.T., Prentice, I.C., and Cramer, W., 1996, A bioclimatic model for the potential distributions of north European tree species under present and future climates: Journal of Biogeography, v. 23, p. 203-233.

Thompson, R.S., Hostetler, S.W., Bartlein, P.J., and Anderson, K.H., 1998: A strategy for assessing potential future changes in climate, hydrology, and vegetation in the Western United States. U.S. Geological Survey Circular 1153, 20 p.

Thornthwaite, C.W., and Mather, J.R., 1955, The water balance: Publications in Climatology, v. 8. ---1957, Instructions and tables for computing potential evapotranspiration and the water balance: Publications in Climatology, v. 10, no. 3, p. 181-311.

Viereck, L.A., and Little, E.L., Jr., 1975, Atlas of United States trees, Volume 2, Alaska trees and common shrubs: U.S. Department of Agriculture miscellaneous publication, v. 1293, 19 p., 82 maps. WeatherDisc Associates, 1989, World WeatherDisc, version 1.0: Seattle, Wash. [CD-ROM].

Willmott, C.J., Mather, J.R., and Rowe, C., 1981, Average monthly and annual surface air temperature and precipitation data for the world, Part 2. The Western Hemisphere: Publications in Climatology, v. 34, p. 1-378.

Willmott, C.J., Rowe, C.M., and Mintz, Y., 1985, Climatology of the terrestrial seasonal water cycle: Journal of Climatology, v. 5, p. 589-606.

Woodward, F.I., 1987, Climate and plant distribution: Cambridge, Cambridge University Press, 174 p.

Woodward, F.I., and Williams, B.G., 1987, Climate and plant distribution at global and local scales: Vegetation, v. 69, p. 189-197.

Wright, H.E., Jr., Kutzbach, J.E., Webb, T., III, Ruddiman, W.F., Street- Perrott, F.A., and Bartlein, P.J., eds., 1993, Global climates since the last glacial maximum: University of Minnesota Press, 569 p.

Yang, T.W., 1970, Major chromosome races of Larrea in North America: Journal of the Arizona Academy of Science, v. 6, p. 41-45.

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