A Comparison of Forest Survey Data with Forest 

Dynamics Simulators FORCLIM and ZELIG along 

Climatic Gradients in the Pacific Northwest

Scientific Investigation Report 2004-5078

U.S. Department of the Interior

U.S. Geological Survey
ii

A Comparison of Forest Survey Data with 

Forest Dynamics Simulators FORCLIM 

and ZELIG along Climatic Gradients in the 

Pacific Northwest

By Richard T. Busing and Allen M. Solomon

Scientific Investigation Report 2004-5078

U.S. Department of the Interior

U.S. Geological Survey
iii

U.S. Department of the Interior

Gale A. Norton, Secretary

U.S. Geological Survey

Charles G. Groat, Director

U.S. Geological Survey, Reston, Virginia: 2004

For sale by U.S. Geological Survey, Information Services

Box 25286, Denver Federal Center

Denver, CO 80225

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Telephone: 1-888-ASK-USGS

World Wide Web: http://www.usgs.gov/

Any use of trade, product, or firm names in this publication is for descriptive purposes only and does not imply 

endorsement by the U.S. Government.
iv

Contents

Abstract .......................................................................................................................................................... 1

Introduction ................... .................................................................................................................................1

Methods .......................................................................................................................................................... 1

Models and Field Data ........................................................................................................................ 1

Parameterization of ZELIG ......................................................................................................... 2

Parameterization of FORCLIM .................................................................................................. 2

Types and Sources of Field Data .............................................................................................. 4

Model Tests ............................................................................................................................................ 4

West Cascades Test .................................................................................................................. 5

Geographic Transect Test ......................................................................................................... 5

Forested Ecoregion Test ............................................................................................................ 6

Actual Vegetation along Test Gradients ................................................................................. 7

Species Pool Effects .................................................................................................................. 7

Results............................ .................................................................................................................................7

Actual Vegetation Patterns ............................................................................................................... 7

Simulated Vegetation Patterns .......................................................................................................... 8

Western Cascade Range ........................................................................................................... 8

Geographic Transect Gradient ................................................................................................. 9

Forested Ecoregions .................................................................................................................. 9

Conclusions ................................................................................................................................................... 9

Acknowledgements ..................................................................................................................................... 10

References .................................................................................................................................................... 10

Figures

Figure 1. Maps of Oregon, including (A) locations of CVS forest survey plots used within Level IV 

Ecoregions, and (B) locations of nine sites along the geographic gradient transect. The 

eight ecoregions include coastal Volcanics (1d), Mid-Coastal Sedimenta ....................... 3

Figure 2. Basal area by species, including values simulated by FORCLIM and ZELIG, and values 

from stands at H.J. Andrews Experimental Forest, western Cascade Range. FORCLIM 

results include the normal 18-species version and an eight-species version for dire .... 4

Figure 3. Percent frequency by diameter class of trees at H.J. Andrews sites (A) near 500 m 

elevation, (B) near 1000 m elevation, and (C) near 1400 m elevation. Values simulated 

by the ZELIG and FORCLIM models are provided for comparison. ..................................... 5

Figure 4. Basal area by species along a geographic transect of western Oregon sites from dry, 

continental treeless shrub-steppe, across cold subalpine forests to wet maritime 

coastal forests. Results include (A) CVS forest plot data, (B) FORCLIM simulation ......... 5

Figure 5. Basal area (m2/ha) by species in Ecoregion Level IV sites from (A) CVS forest data, and 

(B) FORCLIM simulation output. The four-letter species codes consist of the first two 

letters of the genus and species names. ................................................................................. 6

Figure 6. Basal area (m2/ha) by species in Ecoregion 4b (Western Cascades Highlands), including CVS forest data, FORCLIM simulation output, and ZELIG simulation output. The 

four-letter species codes consist of the first two letters of the genus and species ........ 7
v

Tables

Table 1. Similarity of species composition simulated by each model to actual species composition for (A) west Cascades sites, (B) western Oregon transect sites, and (C) forested 

ecoregions. Similarity is measured with Sorensen’s quantitative index using species 

basal area .......................................................................................................................................... 8
Abstract

Two forest dynamics simulators are compared along 

climatic gradients in the Pacific Northwest. The ZELIG and 

FORCLIM models are tested against forest survey data from 

western Oregon. Their ability to generate accurate patterns 

of forest basal area and species composition is evaluated for 

series of sites with contrasting climate. Projections from both 

models approximate the basal area and composition patterns 

for three sites along the elevation gradient at H.J. Andrews 

Experimental Forest in the western Cascade Range. The 

ZELIG model is somewhat more accurate than FORCLIM at 

the two low-elevation sites. Attempts to project forest composition along broader climatic gradients reveal limitations of 

ZELIG, however. For example, ZELIG is less accurate than 

FORCLIM at projecting the average composition of a west 

Cascades ecoregion selected for intensive analysis. Also, 

along a gradient consisting of several sites on an east to west 

transect at 44.1oN latitude, both the FORCLIM model and 

the actual data show strong changes in composition and total 

basal area, but the ZELIG model shows a limited response. 

ZELIG does not simulate the declines in forest basal area and 

the diminished dominance of mesic coniferous species east 

of the Cascade crest. We conclude that ZELIG is suitable 

for analyses of certain sites for which it has been calibrated. 

FORCLIM can be applied in analyses involving a range of 

climatic conditions without requiring calibration for specific 

sites.

Introduction

Two ecological simulators of forest dynamics in the 

Pacific Northwest are ZELIG (Urban 1993) and FORCLIM 

(Bugmann 1994). Both are individual-based “gap models” (sensu Shugart 1984) designed for simulation of forest 

dynamics at multiple spatial and temporal scales (e.g. Smith 

and Urban 1988). The ZELIG model has been modified and 

applied for over a decade to project stand and landscape 

dynamics of forests in response to various human and natural disturbances, including tropospheric ozone (Urban et al. 

1993; Hansen et al. 1995; Miller and Urban 1999; Weinstein 

2001; Busing and Garman 2002; Garman et al. 2003). The 

FORCLIM model has been applied recently to project forest 

stand composition across regional climatic gradients in the 

Pacific Northwest, and earlier, in eastern North America and 

western Europe (Bugmann and Solomon 1995, 2000). 

The two models have several contrasting features. ZELIG 

has enhanced spatial complexity, allowing consideration of 

stand and landscape structure (Smith and Urban 1988; Urban 

1993). The simulation of up to several hundred interacting 

plots at once enables ZELIG to address landscape-level processes such as seed transport and fire spread. FORCLIM, on 

the other hand, has enhanced consideration of site and climatic 

effects on tree species performance (Bugmann 1994). Current 

versions of FORCLIM are especially suitable for regions with 

strong seasonal contrasts in climate (e.g. winter precipitation 

alternating with summer drought), such as the Pacific Northwest (Bugmann and Solomon 2000), by virtue of mechanistic 

routines to simulate impacts of growing season drought on tree 

growth and survival. 

The objective of this report is to provide readers with the 

information they need to choose one or the other model for the 

application they are planning. It focuses on how ZELIG and 

FORCLIM perform along regional environmental gradients 

in western Oregon. We emphasize the ability of the models to 

reproduce patterns of forest composition and structure along 

climatic gradients. We believe that an important capability of 

the models in this regard is their simulation of forests where 

forests grow, and forest absence in places forests do not now 

grow. Also, where forests grow, the models should simulate 

dominance by the actual dominant species (as measured 

in field plot surveys and studies), the approximate order of 

species importance, and total stand biomass that resembles 

estimates from field data.

Methods

Models and Field Data

The FORCLIM model version 2.9 was employed using 

18 species (Bugmann 1996). The species set included all 

common dominant trees species in western Oregon north of 

43o N latitude. For reasons outlined below, certain FORCLIM 

simulations used only 8 species. 

A version of the ZELIG model was applied that had been 

modified and tested using a set of 8 tree species in the westA Comparison of Forest Survey Data with Forest Dynamics 

Simulators FORCLIM and ZELIG along Climatic Gradients 

in the Pacific Northwest

By Richard T. Busing and Allen M. Solomon

1

 Ten other species, including some potential dominants (e.g. Picea sitchensis and Pinus ponderosa) were added to create a larger pool of species. For the set 

of species added, growth scaling constants (G) were set equal to four times the value used in FORCLIM. Rescaling of these constants was necessary because 

the two models have somewhat different growth equations, despite their use of Moore’s (1989) formulation for tree growth. Following tests with even further 

increases in the growth scaling constants and removal of competing species, it was concluded that environmental constraints as modeled in ZELIG must be limiting the growth of some of these new species.
ern Cascade Range of Oregon. Using the personal-computer 

program for this model, known as PNWGAP version 1.0 

(Garman 2003), we simulated forest dynamics with a set of 18 

tree species common to western Oregon and Washington. This 

required adding 10 tree species to the ZELIG simulations. 

However, ZELIG model runs using all 18 species were distinctive in that several of the 10 new species had poor growth 

and survival. This problem persisted despite several attempts 

to enhance performance of certain species1. Hence, as mentioned below, we also ran simulations in which both ZELIG 

and FORCLIM contained only the 8 species common to 

both, in order to generate valid comparisons between the two 

models. However, the emphasis in this report is not on how 

they compare to each other, but rather on the degree to which 

each model approximates measured vegetation. This latter 

assessment demands that each model be run with its optimum 

configuration, whether that involves 8 or 18 species. 

Other versions of ZELIG were considered for this 

analysis, but concerns over species parameterization difficulties led to the selection of the PNWGAP version. Attempts 

to parameterize the version of ZELIG used primarily in the 

Appalachian Mountain region were unsuccessful despite the 

use of values for species variables based on parameterization 

guidelines (Laurence et al. 2001). A major difficulty was that 

Douglas-fir (Pseudotsuga menziesii), a very common dominant species in the Pacific Northwest, was an uncommon species at any successional stage simulated. Under-representation 

of Pseudotsuga also occurred in previous simulation work by 

independent researchers attempting to apply earlier versions 

of ZELIG to western Oregon (Garman and Hansen 1991; 

Urban et al. 1993). By contrast, Pseudotsuga is a successional 

dominant in simulations by the PNWGAP version of ZELIG. 

This version has been adapted to, and tested for simulation of, 

forest composition in the western Cascade Range of central 

Oregon. Considering the foregoing, and, that this version has 

been under development and testing for the past 15 years, we 

believe it represents the optimum available configuration for 

ZELIG in the western Oregon tests we describe below. 

Parameterization of ZELIG

Parameters for the eight species in Garman’s PNWGAP 

program were not altered. These species included Pacific 

silver fir (Abies amabilis), noble fir (Abies procera), Douglasfir (Pseudotsuga menziesii), western red cedar (Thuja plicata), 

western hemlock (Tsuga heterophylla), bigleaf maple (Acer 

macrophyllum), red alder (Alnus rubra) and mountain hemlock 

(Tsuga mertensiana). Growing-degree-day limits (DDMIN 

and DDMAX) followed the values published in Urban et al. 

(1993). The inseeding parameter SEED was set equal to 3 

for the additional 10 species. This is an intermediate level of 

inseeding. None of the new species was assigned a mineral 

soil requirement for regeneration. For each new species, adult 

reproductive size was set at 20, which is the minimum diameter (cm dbh) of seed producing trees. Simulation sites had silt 

loam soils with a depth of 1m, a field capacity of 43.7 cm/m 

and a wilting point of 16.3 cm/m per layer. Only monthly 

mean precipitation and temperature were varied among sites.

Parameterization of FORCLIM

Version 2.9 of the FORCLIM model (Bugmann 1996, 

Bugmann and Solomon 2000) was used with 18 species (interior region subspecies of Pseudotsuga menziesii and lodgepole 

pine/shore pine (Pinus contorta) were included, making a total 

of 20 taxa simulated). Species parameters generally matched 

those in Bugmann (1996), derived as described by Bugmann 

and Solomon (2000)2. However, certain parameterizations 

were revised following examination of species parameters 

for drought tolerance and growing-degree-day minima for 

each species. Comparison of the old parameters to values in 

recently published climatic data sets associated with species’ 

ranges (Thompson et al. 2000 a, b) revealed some discrepancies. In cases where the Thompson et al. data clearly did not 

agree with the parameter value of Bugmann (1996), new values provided by Thompson et al. were assigned. Specifically, 

the drought tolerance parameters (percent of growing season 

days with soil moisture below the wilting point) of Abies amabilis and Abies procera were reduced from 0.4 and 0.3 to 0.2 

and 0.25, respectively. The DDMIN values (minimum growing 

degree days) of grand fir (Abies grandis), Abies procera, Alnus 

rubra, and Engelmann spruce (Picea engelmannii) (705, 821, 

705, and 488, respectively) also were reduced (to 600, 550, 

600 and 400, respectively). 

Simulation sites were assumed to have a slope aspect 

factor of 0, water holding capacity of 20% (i.e., 20 cm/m) 

and a water table of 10 m. Soils were assumed to be fertile. 

Only monthly mean precipitation and temperature were varied 

among sites.

FORCLIM is implemented primarily in MODULA2 

computer code. Previously published results are from the 

MODULA2 program (e.g. Bugmann and Solomon 2000). 

2. Climatic parameters were estimated based on overlays of tree distribution maps by maps of bioclimatic indices (minimum degree-days kDDMin, min. 

and max. winter temperature tolerances kWiTN, kWiTX, and drought tolerance kDrT). These estimation procedures yielded congruent values that resulted 

in plausible simulation results except for the minimum degree-day and drought tolerance parameters. Steep climatic gradients were problematic here. For 

example, the initial estimates of the kDDMin parameter obtained from overlaying distribution maps (Little 1971) on maps of the degree-day sums yielded 

estimates that had a resolution of no more than 200 °C·days. We refined those estimates from the ranking of species’ minimum temperature requirements in 

Franklin & Dyrness (1973, p. 161). The estimates of the kDrT parameter obtained from overlays of distribution maps with maps of the simulated drought 

index values, uDrE and uDrD, matched the ranking of the species by Franklin & Dyrness (1973, p. 130). However, several species had been assigned only 

slightly different drought indices by the crude means applied, although according to Franklin and Dyrness (1973) they behave rather differently toward soil 

moisture. Therefore, we modified the kDrT parameters of Alnus rubra, Acer macrophyllum, Pinus ponderosa, and Abies grandis accordingly. See Bugmann & 

Solomon (2000) for additional details and references.

 A Comparison of Forest Survey Data with Forest Dynamics Simulators 
Oregon ecoregions and vegetation plot sites

Ecoregion Name

1d-Volcanics

1g-Mid-Coastal Sedimentary

4a-W. Cascades Lowlands and Valleys

4b-W. Cascades Montane Highlands

4c-Cascade Crest Montane Forest

4e-High S. Cascades Montane Forest

9d-Ponderosa Pine/Bitterbrush Woodland

9e-Pumice Plateau Forest

or_state_boundary

A B

Figure 1. Maps of Oregon, including (A) locations of CVS forest survey plots used within Level IV Ecoregions, and (B) locations of nine sites along the g

sect. The eight ecoregions include coastal Volcanics (1d), Mid-Coastal Sedimentary (1g), Western Cascades Lowlands and Valleys (4a), Western Casc(4b), Cascade Crest Montane Forest (4c), High Southern Cascades Montane Forest (4e), Ponderosa Pine—Bitterbrush Woodland (9d), and Pumice Pla

sites, proximate CVS forest plots were used in comparisons of simulations to actual vegetation.
0 20 40 60 80 100 120

500m Actual

FORCLIM-c2

FORCLIMc2-8spp

ZELIG

1000m Actual

FORCLIM-c2

FORCLIMc2-8spp

ZELIG

1400m Actual

FORCLIM-c2

FORCLIMc2-8spp

ZELIG

Source/Elevation

Basal area

ABAM

ABGR

ABPR

CHNO

PISI

PIPO

PSME

THPL

TSHE

TSME

Other

0 20 40 60 80 100 120

500m Actual

FORCLIM-c2

FORCLIMc2-8spp

ZELIG

1000m Actual

FORCLIM-c2

FORCLIMc2-8spp

ZELIG

1400m Actual

FORCLIM-c2

FORCLIMc2-8spp

ZELIG

Source/Elevation

Basal area

ABAM

ABGR

ABPR

CHNO

PISI

PIPO

PSME

THPL

TSHE

TSME

Other

 A Comparison of Forest Survey Data with Forest Dynamics Simulators 

However, unless noted otherwise, a C version of the program 

running under the UNIX operating system and developed for 

USEPA (Dodson 1997), was used for the simulations herein. 

Types and Sources of Field Data

Forest plot data from recent ecological surveys and studies in western Oregon were used for evaluations of the models. 

The data sets include ecological survey data from plots on a 

grid extending across federal lands, and stand data from plots 

in selected sites at H.J. Andrews Experimental Forest in the 

Cascade Range. 

The ecological survey data included 2323 forest stands 

in western Oregon that were assembled from USDA and 

USDI databases (Busing 2004). All stands were inventoried 

after 1993 using USDA Forest Service conventions adopted 

for an ecological survey of forested federal lands (Max et 

al. 1996). In that system, known as the Current Vegetation 

Survey (CVS), plots were established on a square grid at 5.5 

km intervals (Fig. 1A). A five-subplot design covered a 1-ha 

area for tree stratum data collection at each plot site. Measurements on live trees included diameter at breast height, canopy 

height and, for selected individuals at most sites, tree age. We 

selected sites in which all five subplots were inventoried and 

tree age data were collected.

Our analyses with the Current Vegetation Survey data 

included all live trees >7.6 cm dbh. We calculated basal area 

for selected dominant species and for all species combined. 

Stand age was estimated as the maximum age of a cored tree 

at each plot site. Climate data were assigned to each plot site 

using the geographic coordinates of the plot and the interpolated climate data sets described in Lugo et al. (2000).

Another set of long-term research plots in old growth 

forests, known as the H.J. Andrews Experimental Forest reference stands, was also used (Acker et al. 1998; Garman and 

Hansen 1991). A total of 25 stands representing old (>400 

yr), well-developed forests along the elevation gradient in the 

western Oregon Cascade Range were selected for analysis. For 

the comparisons with simulated data, stands were grouped into 

one of three elevation classes: 1) ca. 500 m (n=11); 2) ca. 1000 

m (n=9); and 3) ca. 1400 m (n=5). 

Model Tests

Models were tested for their ability to reproduce compositional and structural patterns observed in the field. All simulations were initiated on bare ground and were run to match 

measured ages of actual stands. Simulated basal area means 

were compared among simulations and with actual data. In 

comparisons with the reference stands data at H.J. Andrews 

Experimental Forest in the western Cascade Range (Garman 

and Hansen 1991) size-class distributions were examined as 

well. 

Actual data from the survey plots located on forested 

lands in western Oregon representing vegetation types 

occurring north of 43o N latitude were used in another set of 

tests. Two separate vegetation classifications were applied: a 

transect across the commonly applied forest vegetation zones 

of Franklin and Dyrness (1988) (Fig. 1B); and (primarily 

for FORCLIM comparisons to actual vegetation) Omernik’s 

Ecoregion IV classification (Thorsen et al. 2002) (Fig. 1A), 

which emphasizes physiographic and climatic as well as 

vegetation classification variables. Both of these classifications 

are commonly used and understood, though each primarily 

by workers in different disciplines. Comparisons applying 

both systems provide readers with the opportunity to picture 

the forests that the models are simulating in terms that they 

understand best. 

Figure 2. Basal area by species, including values simulated by FORCLIM and ZELIG, and values from stands at H.J. Andrews 

Experimental Forest, western Cascade Range. FORCLIM results include the normal 18-species version and an eight-species 

version for direct comparison to ZELIG simulations. The eight-species version is not used for other FORCLIM simulations in this 

report unless so noted. The four-letter species codes consist of the first two letters of the genus and of the species names, 

respectively.
West Cascades Test 

Both models were run at three sites along the elevation 

gradient (~500, 1000, & 1400 m) at H.J. Andrews Experimental Forest (Fig. 1B). Both ZELIG and FORCLIM had previously been run at these sites because comprehensive vegetation data for comparison to simulation output was available 

there. These sites are actually composites of many measured 

plots at each elevation, retrieved and formatted from the H. J. 

Andrews Long Term Ecological Research (LTER) database by 

Garman and Hansen (1991). Basal area means for each species 

and for all species combined were compared at each site (Fig. 

2). Diameter distributions for all species combined in diameter classes, from forest surveys (10 cm dbh), FORCLIM (18 

species) and ZELIG (8 species) simulations, were compared 

using percent frequency by diameter class (Figs. 3A, 3B, 3C, 

respectively). 

Geographic Transect Test

A geographical climate gradient in western Oregon was 

described and analyzed by Bugmann and Solomon (2000). 

This gradient was composed of a set of sites along a westeast transect from the coast to the steppe in central Oregon 

(at 44.13o N), approximately as described by Franklin and 

Dyrness (1988). For the comparative analyses, we selected 

nine of the 27 sites along this transect (See Fig. 1B) that were 

simulated by Bugmann and Solomon (2000). The nine test 

sites included wet, coastal forests, mesic and zeric montane 

forests, cold subalpine forests, and dry, treeless steppe. Basal 

area means for each species and for all species combined from 

CVS data (several to many CVS plots combined per site) and 

from FORCLIM and ZELIG simulations, were compared at 

each site (Figs. 4A, 4B, 4C, respectively).

Figure 3. Percent frequency by diameter class of trees at H.J. 

Andrews sites (A) near 500 m elevation, (B) near 1000 m elevation, 

and (C) near 1400 m elevation. Values simulated by the ZELIG and 

FORCLIM models are provided for comparison.

Figure 4. Basal area by species along a geographic transect of 

western Oregon sites from dry, continental treeless shrub-steppe, 

across cold subalpine forests to wet maritime coastal forests. 

Results include (A) CVS forest plot data, (B) FORCLIM simulation 

output, and (C) ZELIG simulation output. The four-letter species 

codes consist of the first two letters of the genus and species 

names.

500 m Elevation Sites

Frequency (%)

0

5

10

15

20

25

30

35

0-10 10--20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 >90

DBH class (cm)

FORCLIM

ZELIG

Actual

1000 m Elevatio n Sites

F requency (%)

0

5

10

15

20

25

30

35

40

45

50

0-10 10--20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 >90

D B H class (cm)

FORCLIM

ZELIG

Actual

1400 m Elevatio n Sites

F requency (%)

0

5

10

15

20

25

30

35

40

0-10 10--20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 >90

D B H class (cm)

FORCLIM

ZELIG

Actual

Actual forest vegetation along western Oregon transect

0 30 60 9

-124

-123

-122

-121.87

-121.75

-121.62

-121.5

-121.46

-121

West Longitude in Degrees

Basal area in m2/ha

ABAM

ABGR

ABPR

CHNO

PISI

PIPO

PSME

THPL

TSHE

TSME

Other

Pinus ponderosa zone

Abies grandis zone

Subalpine Forest zone (dry)

Subalpine Forest zone (high)

Subalpine Forest zone (wet)

Abies amabilis zone

Tsuga heterophylla zone

Picea sitchensis zone

Shrub-steppe zone

0

FORCLIMc2 simulations along western Oregon transect

0 30 60 9

-124

-123

-122

-121.87

-121.75

-121.62

-121.5

-121.46

-121

West Longitude in degrees

Basal area in m2/ha

ABAM

ABGR

ABPR

CHNO

PISI

PIPO

PSME

THPL

TSHE

TSME

Other

Picea sitchensis zone

Tsuga heterophylla zone

Abies amabilis zone

Subalpine Forest zone (wet)

Subalpine Forest zone (high)

Subalpine Forest zone (dry)

Abies grandis zone

Pinus ponderosa zone

Shrub-steppe zone

0

ZELIG simulations along western Oregon transect

0 30 60 90 120

-124

-123

-122

-121.87

-121.75

-121.62

-121.5

-121.46

-121

West Longitude in degrees

Basal area in m2/ha

ABAM

ABGR

ABPR

CHNO

PISI

PIPO

PSME

THPL

TSHE

TSME

Other

shrub-steppe zone

Pinus ponderosa zone

Abies grandis zone

Subalpine Forest zone (dry)

Subalpine Forest zone (high)

Subalpine Forest zone (wet)

Abies amabilis zone

Tsuga heterophylla zone

Picea sitchensis zone

Methods 5
Forested Ecoregion Test

Eight ecoregions from the Omernik classification (level 

IV; Thorson et al. 2002) in western Oregon were selected 

based on the number of field plots (>12 plots) confirmed to 

represent older stands (age >150 yr) in each level IV category. 

Ecoregions at low elevations centered south of 43o N latitude 

(i.e., the Siskiyous) were excluded because they contained 

dominant species that are not currently considered in either 

FORCLIM or ZELIG. Unlike the other tests, this one segregated vegetation by substrate features as well as climate, 

permitting the examination of vegetation composition and 

biomass patterns conforming to soil texture and nutrient status.

The eight ecoregions are listed and mapped in Figure 

1A. The climatic regime of each ecoregion, extracted from the 

4-km climate data set (Dodson 1997), was assembled from 

climate data at multiple randomly selected CVS plot sites (n = 

10 to 20). A FORCLIM simulation was run for each of these 

sites. Results were pooled by ecoregion (Figs. 5A, 5B).

Figure 5. Basal area (m2/ha) by species in Ecoregion Level IV sites from (A) CVS forest data, and (B) FORCLIM simulation output. The 

four-letter species codes consist of the first two letters of the genus and species names.

Actual Vegetation by Omernik Ecoregion--Stands >150 yr

0 10 20 30 40 50 60 70

1d--Volcan

1g--MCoastSed

4a--WCascLow

4b--WCascHig

4c--CascCrest

4e--HiSouthCasc

9d--PPine

9e--PumicePlat

Ecoregion Level IV

Basal area

ABAM

ABGR

ABPR

CHNO

PISI

PIPO

PSME

THPL

TSHE

TSME

Other

FORCLIMc2 simulations by Omernik ecoregion in western Oregon--multiple random sites

0 10 20 30 40 50 60 70 80

1d

1g

4a

4b

4c

4e

9d

9e

Ecoregion level IV

Basal area

ABAM

ABGR

ABPR

CHNO

PISI

PIPO

PSME

THPL

TSHE

TSME

Other

�

�

 A Comparison of Forest Survey Data with Forest Dynamics Simulators 
Actual Vegetation along Test Gradients

Actual vegetation along the two broad test gradients and 

the ecoregions was documented from the field data. For the 

geographic transect gradient, CVS plots having trees known 

to be at least 150 years old were selected from a belt between 

43.13 and 45.13o N latitude. For each point along the transect, 

plot sites with similar longitude and within 500 ft elevation 

of the transect point were analyzed for mean species basal 

area and total basal area. Mean age was also calculated. For 

the forested ecoregions, these values were generated for each 

ecoregion. Plots were excluded if they had basal area <10 m2 

ha-1 (indicating lack of closed canopy) or no evidence of trees 

>150 years old (indicating early successional forests). 

Species Pool Effects

All of the FORCLIM and ZELIG tests involved 18 species, and were repeated with only the eight tree species from 

the version of ZELIG calibrated by Garman (1999). All other 

species were excluded from the simulations so that results 

could be evaluated without the effects of additional FORCLIM 

species, which had not been calibrated for the two models. Ten 

forest sites (>150 yr) were randomly selected for the comparison. FORCLIM and ZELIG simulations were run for each of 

these sites. Actual and simulated data for dominant tree species were summarized for the ecoregion (Fig. 6). 

Unlike FORCLIM simulations, running ZELIG at these 

sites required a separate parameterization for model runs at 

each site within each ecoregion (i.e., 8 ecoregions X 10-20 

sites). To reduce the time required to prepare for the ecoregion comparisons using both models, we ran only a single set 

of FORCLIM and ZELIG simulations, covering the Western 

Cascades Montane Highlands ecoregion (class 4b). All forest 

dominants in this ecoregion have been tested previously for 

reasonable growth in the ZELIG model, making this ecoregion optimal for ZELIG in a comparison of ZELIG. We note 

that when simulation output is compared to actual vegetation, 

at least in FORCLIM, model performance is degraded by 

exclusion of species known to grow in the area being modeled 

(Bugmann et al. 2001). Hence, FORCLIM with eight species is likely to be considerably less accurate than FORCLIM 

simulations that include the missing species. An additional 

disadvantage of species exclusion is that it reduces the identifiable differences among the data sets by leaving out signature 

species (e.g., ponderosa pine [Pinus ponderosa] in dry eastern 

forests, Sitka spruce [Picea sitchensis] in wet coastal forests). 

However, species exclusion does have the virtue of reducing 

the potential for unwanted species calibration effects, which 

apply, to ZELIG but not to FORCLIM (species of which are 

not calibrated by site). It also allows evaluation of model sensitivity to species pool selection.

Results

Actual Vegetation Patterns 

The field data on forest vegetation show somewhat 

subtle compositional changes along environmental gradients. 

Major geographic trends in composition along the geographic 

transect at 44.1o N latitude from the coast to the dry steppe 

are evident (Fig. 4A). Near the coast (-124o W longitude), 

forests are dominated by Pseudotsuga, Tsuga heterophylla

and Picea sitchensis. In the Cascade Range (-123o and -122o

W longitude), Pseudotsuga, Tsuga heterophylla and Thuja plicata dominate. In the high Cascades (-121.87o

 to -121.62o W 

longitude) Tsuga mertensiana dominates sites warm enough 

Figure 6. Basal area (m2/ha) by species in Ecoregion 4b (Western Cascades Highlands), including CVS forest data, FORCLIM simulation 

output, and ZELIG simulation output. The four-letter species codes consist of the first two letters of the genus and species names.

Actual and simulated forest dominants in Ecoregion 4b--Western Cascades Montane Highlands

0 10 20 30 40 50 60 70

Actual

FORCLIMc2

ZELIG

Source

Basal area

ABAM

ABGR

ABPR

CHNO

PISI

PIPO

PSME

THPL

TSHE

TSME

Results 7
to permit tree growth. On the lower, eastern slopes of the Cascades (-121.5o

 W longitude) Pinus ponderosa dominates and 

total basal area diminishes. Forest is absent at the eastern-most 

site (-121o W longitude).

Deciduous species (e.g. Acer macrophyllum and Alnus 

rubra in the mesic low-elevation sites) and subalpine conifers 

(e.g. Picea engelmannii and Abies lasiocarpa in the highelevation sites) occur in the CVS plots sporadically, and are 

assigned to the “other” species category.

Similar compositional changes were evident in the series 

of eight ecoregions from wet, coastal forests to dry forests of 

central Oregon (Fig. 5A). However, ecoregion summaries also 

revealed the potential diversity of tree species on the landscape 

in a given ecoregion. For example, in the high elevation ecoregions along the Cascade crest, the landscape is not dominated 

exclusively by one or two tree species.

Simulated Vegetation Patterns

Western Cascade Range

Performance of the FORCLIM and ZELIG models at 

three elevations (500, 1000 & 1400 m) in the western Oregon Cascades (H.J. Andrews Experimental Forest) may be 

acceptable for most purposes to which the models would be 

applied. Both ZELIG and FORCLIM projected dominance 

by Pseudotsuga and Tsuga heterophylla at the 500 and 1000 

m elevation sites, as observed in the actual reference stands at 

these two sites (Fig. 2). At the high-elevation site (1400 m), 

however, there were obvious discrepancies between species 

composition measured and that simulated by both models. The 

actual forest composition was Pseudotsuga—Abies procera—

Tsuga mertensiana. FORCLIM simulated a forest of Abies 

amabilis—Abies procera—Pseudotsuga. ZELIG produced a 

Tsuga mertensiana—Abies amabilis forest. FORCLIM underestimated the amount of Pseudotsuga at the upper site where 

ZELIG overestimated the amount of Tsuga mertensiana and 

greatly underestimated the amount of Pseudotsuga and Abies 

procera. 

Quantitative indices of similarity in species composition 

were used to further evaluate model performance. Sørensen’s 

Index of Similarity [a quantitative Coefficient of Community 

(CoC); Magurran 1988] indicates that ZELIG simulations 

are particularly accurate at the 500 and 1000 m sites, and that 

FORCLIM is similarly accurate at the 500 m sites, but less so 

at the 1000 m sites (Table 1A). Although the CoC indicates 

that FORCLIM is considerably more accurate at 1400 m than 

is ZELIG, neither model appears to be acceptably correct, 

assuming the measured values are characteristic of the forests 

at these high elevations.

However, there is some reason to question whether these 

specific high- and mid-elevation measurements are indeed representative of upper-elevation forests. It is noteworthy that the 

data from actual reference stands representing these two sets 

of sites contained much higher basal area than did most of the 

simulations (Fig. 2). This may result from bias towards recording well-developed stands during the selection of these study 

plot sites in the field. On average, the CVS vegetation survey 

plots covering these same high elevations do not contain such 

high basal area (e.g. Figs. 4A, 5A, 6A) even though sites with 

human disturbance are excluded. Hence, the actual total basal 

area (if not the species basal area) values from the reference 

stands must be interpreted cautiously, as they do not appear to 

represent randomly selected sites.

Size-class structures (or diameter distributions) of the 

actual plots at these three sites all had the typical pattern of 

decreasing stem densities with stem size (Figs. 3A, 3B, 3C). 

Both FORCLIM and ZELIG also produced this pattern. Over-

[(A) H.J. Andrews LTER comparisons]

Site Actual vs. FORCLIM Actual vs. ZELIG

H.J. Andrews 500 m 0.746 0.884

H.J. Andrews 1000 m 0.579 0.814

H.J. Andrews 1400 m 0.488 0.336

[(B) Western Oregon transect at 44.1o N comparisons]

Longitude Forest Zone Actual vs. FORCLIM Actual vs. ZELIG

-124 Picea sitchensis 0.828 0.632

-123 Tsuga heterophylla 0.745 0.649

-122 Abies amabilis 0.738 0.835

-121.87 Tsuga mertensiana 0.397 0.750

-121.75 Tsuga mertensiana 0.477 0

-121.62 Tsuga mertensiana 0.757 0.761

-121.5 Abies grandis 0.524 0

-121.46 Pinus ponderosa 0.870 0.098

Mean and Standard Deviation All 0.667+0.176 0.466+0.365

[(C) Ecoregion comparison]

Region Actual vs. FORCLIM Actual vs. ZELIG

Ecoregion 4b 0.740 0.655

Table 1. Similarity of species composition simulated by each model to actual species composition for (A) west Cascades sites, (B) western Oregon transect sites, and (C) forested ecoregions. Similarity is measured with Sorensen’s quantitative index using species basal 

area.

 A Comparison of Forest Survey Data with Forest Dynamics Simulators 
all, the FORCLIM size-class frequencies fit the actual distributions somewhat better than the ZELIG frequencies do. ZELIG 

overestimated the density of large stems (>90 cm DBH) at the 

500 m sites and the density of small stems (0-10 cm DBH) at 

the 1000 m sites while none of the size classes simulated by 

FORCLIM were similarly inaccurate (Figs. 3A, 3B, 3C).

The results above were based on a species pool of 18 

species. However, only eight species were tested in previous work with ZELIG. When only these eight species, which 

include the dominants at most sites, were used with ZELIG 

and FORCLIM (Fig. 2), the major compositional trends noted 

above did not change. Although certain minor species were 

absent, the dominant species showed similar trends regardless 

of the size of the species pool used as model input. 

Geographic Transect Gradient

When these same models were applied along broader gradients extending beyond the west slope of the Cascade Range, 

projected composition and total basal area diverged sharply 

from each other. Along the geographic transect at 44.13o N 

latitude (Fig. 1B), FORCLIM (with 18 species) was better able 

to capture several measured aspects of forest composition and 

basal area (Figs. 4A, 4B) than was ZELIG (with 8 species) 

(Fig. 4C). ZELIG was particularly inaccurate at the eastern, 

dry end of the gradient which should have low total basal area 

and, at the easternmost point of the gradient (-121o W), no forest at all (Fig. 4A). Instead, ZELIG projected Pseudotsuga—

Tsuga heterophylla forests with high basal area at these sites, 

essentially the same as it projected at the western Cascades 

mid-elevation sites, a clearly unacceptable result. This result 

was obtained even when soil depth was reduced from 1 to 0.1 

m, on the supposition that the soil moisture calculation with 

deep soils was not affecting tree growth. 

By contrast, FORCLIM projected a low total basal area 

near the eastern end of the gradient, and a lack of trees at the 

eastern most point (Fig. 4B). Note that the CoC values (Table 

1B) suggest that ZELIG has its greatest accuracy in the Abies 

amabilis and subalpine zones of the western Cascades. CoC 

values also demonstrate that ZELIG accuracy declines greatly 

both to the east and the west of the western Cascades sites. 

In contrast, CoC values for FORCLIM are uniformly high, if 

somewhat variable, along the length of the transect.

In contrast to its projection of dense forest in the nonforested eastern site, ZELIG simulates no forest at the highestelevation site along the gradient (Fig. 4C). There, both forest 

survey data (Fig. 4A) and FORCLIM output describe a Tsuga 

mertensiana forest at this site (Fig. 4B). We note this difference is not necessarily important because both models could 

be correct at the highest elevations, where both treeless alpine 

areas and subalpine forests with Tsuga mertensiana occur. 

Forested Ecoregions

FORCLIM reproduced the major vegetation patterns and 

total basal area trends in the series of ecoregions from wet 

maritime to dry continental climate (Figs. 5A, 5B). However, 

in some cases, FORCLIM overrepresented species that are 

rare or absent on the actual landscape of an ecoregion. For 

example, Abies grandis and Pinus ponderosa were projected 

to be minor species in several coastal and wet montane ecoregions where they were rare or absent. It also overestimated the 

amount of Pseudotsuga in the dry continental ecoregions (9d 

& 9e).

In the Western Cascades Montane Highlands ecoregion 

(4b), selected for simulation by ZELIG as well as FORCLIM, 

both models projected dominance of Pseudotsuga as observed 

in the actual field data from within the ecoregion (mean values 

from 10 sites; Fig. 6). However, the abundance of other species 

varied. The actual data showed abundant Tsuga heterophylla, 

Abies amabilis and A. procera in the ecoregion, in that order. 

FORCLIM projected the same species in reverse order, as 

other important species. By contrast, ZELIG projected Tsuga 

mertensiana, Abies amabilis, and Tsuga heterophylla as other 

important species. The high abundance of Tsuga mertensiana

and the absence of Abies procera in the ZELIG simulations are 

noteworthy deviations from the actual data. The CoC values 

(Table 1C) indicate that FORCLIM simulations are somewhat 

more accurate estimators of actual vegetation in ecoregion 4b 

than are ZELIG simulations, although both model results may 

be acceptable for many applications.

Conclusions

Both models performed reasonably well in the western 

Cascade Range of Oregon. Simulated composition of H. J. 

Andrews forests at low to mid elevations, dominated by Pseudotsuga and Tsuga heterophylla, generally agreed with actual 

data. ZELIG did somewhat better than FORCLIM in western 

Cascades and eastern Coast Range forest sites dominated by 

Pseudotsuga menziesii, Tsuga heterophylla, and Thuja plicata

and on this basis, ZELIG may be the better choice for applications in these forests, particularly if the applications do not 

involve transient shifts in moisture availability. Differences 

between actual composition and that simulated by both ZELIG 

and FORCLIM were evident in forests at higher elevations 

(ca. 1400 m) of the western Cascades. Under the high-elevation climate, at least one of the several actual dominant species 

was absent from output by both models. Although FORCLIM 

matched vegetation survey data better at these high elevations 

along the geographic transect, it is not certain that ZELIG was 

incorrect in simulating no trees at all (i.e., and alpine vegetation). Along broader climatic gradients in the western Oregon 

region, FORCLIM captured considerably more of the compositional variation than ZELIG did. FORCLIM also simulated 

the drought-regulated forest-steppe boundary accurately, while 

Conclusions 9
ZELIG projected dense Pseudotsuga forests on steppe lands 

where trees do not currently grow.

 The major finding from this comparison of model 

output with actual vegetation data is that just one set of species 

parameters permits one to simulate much of the forest compositional response to climatic gradients in western Oregon with 

FORCLIM. The FORCLIM model mimicked the general compositional differences across those gradients, although some 

discrepancies were noted for certain sites and ecoregions. 

FORCLIM also captured the stand biomass trends, although 

simulated levels of biomass and basal area exceeded those 

measured at some of the sites and ecoregions examined. The 

ability of FORCLIM to produce reasonable trends in composition and basal area across major gradients leads us to suggest 

that FORCLIM is probably able to capture the variation in 

forest composition and structure that is generated locally by 

climate differences in complex terrain (i.e., slope, exposure, 

mountain-valley winds, and so on), and to respond with the 

correct species composition to chronic changes in climate. We 

note however, that none of the tests we applied assessed the 

rates at which simulated vegetation would change in response 

to projected rapid climate change.

Although ZELIG was superior to FORCLIM in the 

Cascades and Coast Range Pseudotsuga menziesii - Tsuga 

heterophylla forests, and although it has some very desirable 

capabilities (e.g., multiple interacting plots [Urban 1993], 

available links to the TREGRO carbon allocation model, and 

scaling of ozone effects [Laurence et al., 2001]), it is not as 

accurately applied across environmental gradients. This is 

a considerable disadvantage for ZELIG within the complex 

terrain of western Oregon. A single set of species parameters 

does not produce the variation in composition observed along 

broad climatic gradients in western Oregon. Thus, it appears 

that ZELIG requires species re-parameterization when moved 

from one site to another with differing climate. This limitation 

casts doubt on the suitability of ZELIG for assessments of forest response to climatic changes that are great enough to force 

shifts in forest composition, or from forest to steppe. It also 

suggests that regional analyses of forest response to changing 

atmospheric chemistry (i.e., ozone shifts) with ZELIG require, 

at the least, multiple parameterizations of the model. 

Acknowledgements

We are very grateful to Steve Garman, Oregon State 

University, for generously providing the computer code for 

his PNWGAP 1.0 version of the ZELIG model, and for his 

useful advice during our work on this project. We are grateful to Connie Burdick, Western Ecology Division, U.S. EPA, 

for the time and efforts she expended in providing geographic 

data and creating the map of CVS plot sites and ecoregions 

(Fig. 1A). Sarah Shafer, U.S. Geological Survey, also provided assistance with geographic data. An earlier draft of the 

manuscript was considerably strengthened by constructive 

and helpful reviews by Steven Garman, Robert Pabst, Oregon 

State University, John Laurence, U.S.D.A. Forest Service, and 

David Tingey, U.S. Environmental Protection Agency.

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