United States

Department of 

Agriculture

Forest Service

Northern 

Research Station

General Technical

Report NRS-113

Site Index Comparisons for 

Forest Species in the Upper 

Great Lakes Area of the 

United States and Canada

Willard H. Carmean

Jerold T. Hahn

Ronald E. McRoberts

Dan Kaisershot

Site Index

Species

American 

basswood

Sugar 

maple White ash

Trembling 

aspen

Northern 

whitecedarBlack 

spruce Jack pine Red pine
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June 2013 Email: nrspubs@fs.fed.us

The Authors

Willard H. Carmean is a professor emeritus, Natural Resources Management, Lakehead 

University, Thunder Bay, Ontario, and a retired soil scientist with the U.S. Forest Service, 

North Central Forest Experiment Station, St. Paul, MN.

Jerold T. Hahn is a retired mensurationist with the U.S. Forest Service, North Central 

Research Station, St. Paul, MN.

Ronald E. McRoberts and Dan Kaisershot are mathematical statistician and forest 

technician, respectively, with the U.S. Forest Service, Northern Research Station, St. 

Paul, MN.

Abstract

This report summarizes six studies that compare site index relations between 24 

hardwood and conifer species in the Upper Great Lakes area of the United States and 

Canada. These six studies have many regression models and graphs for comparing site 

index between forest species thus providing tools for estimating site index for alternative 

tree species based on direct site index measurements using tree species actually present 

in forest stands. Thus the objective of this summary paper is to summarize these models 

so that we can provide the most accurate tools available for estimating the tree species 

that are most productive and economically valuable for management on each forest site.
1

INTRODUCTION

A key question in timber management is “What species 

of tree is the most productive and commercially desirable 

for each forest location?” Such a question is frequently 

encountered with stand conversion, tree planting, release, 

timber stand improvement, thinning, and with fi nal 

harvest prescriptions. Th is is a critical question because 

for each forest location tree species may diff er in site 

quality, rate of growth, and volume and value of yield. 

Some of the greatest increases in yield and value of 

timber are obtained when poorly stocked forest stands 

having slow-growing, poor quality, less commercially 

valuable forest species are converted to fully stocked 

stands having fast-growing tree species capable of rapidly 

producing yields of the most commercially valuable forest 

products. Th us forest managers need site quality and 

yield estimates, not only for the species of tree actually 

present at a forest location, but also for all alternative tree 

species that might be considered for future management 

at that location.

Th e question about the most productive tree species 

for each location could easily be answered only in the 

unlikely situation where all forested areas have older, 

even-aged, fully stocked, undisturbed mixed stands, and 

where all of these mixed stands contain free-growing 

dominant and codominant trees of each of the alternative 

tree species that might be considered for management on 

that location. Th us for these undisturbed mixed forest 

stands we could measure and compare the growth achieved 

by each of the alternative tree species. Th ese on-the-ground 

measurements then would provide the evidence about 

which tree species is the most productive at that location. 

But we rarely have such fully stocked and undisturbed 

mixed forest stands containing free-growing dominant 

and codominant trees of all alternative species. Instead, 

we are confronted by a variety of partially cut, unevenaged or high-graded forest stands that are not indicative 

of the actual productive abilities of the diff erent tree 

species in these stands. Th is dilemma is particularly acute 

when we are dealing with tree species that are naturally 

uncommon, or that presently are uncommon due to past 

overcutting or high-grading because of past harvesting 

that removed the most valuable and merchantable tree 

species from the forest stand.

A desirable alternative for selecting the most productive 

and desirable species are species comparative trials 

consisting of older plantations where various alternative 

tree species are grown on adjacent plots of land having 

similar soil, topography, and site quality. Th e growth and 

yield performance of each species of tree in these trial 

plantations is then evidence of what tree species is most 

productive for that particular site.

Examples of such species comparison trials are studies 

by Alban (1978, 1985) and Schlaegel (1975). Th e 1978 

Alban study was based on 25 pairs of adjacent 28- to 

42-year-old red pine1

 and jack pine plantations and 

showed that red pine plantations had greater annual 

increment and greater basal area than adjacent similar 

aged jack pine plantations. McClain et al. (1994) and 

Homagain et al. (2011) also showed that red pine 

plantations in northwestern Ontario produced much 

greater yield than adjacent similar aged white and black 

spruce plantations.

Unfortunately we rarely have suffi cient even-aged 

undisturbed natural stands, and we rarely have older 

species comparison trials that can provide the information 

needed for comparing growth and yield for alternative 

tree species. Th e few older species comparison trials 

available for representing growth and yield of alternative 

tree species are unlikely to represent the full range of 

forest sites or forest species found in a forest region.

Species site index comparisons

Th erefore we must turn to alternative methods such as 

studies that compare site index for tree species growing 

together in locations similar in site quality. Th is method 

is based on the close association between site index and 

stand volume as refl ected in normal yield tables for most 

of our major tree species; these tables express potential 

yield for pure, fully stocked stands according to stand 

age and site index. Th us site index comparisons between 

forest tree species can be considered as an alternative for 

the direct comparisons of volume based on undisturbed 

fully stocked natural stands or by plantation species 

comparison trials. If we know the site index value for 

each of the alternative species being compared, we then 

1

Scientifi c names for tree species are given in Appendix I.
2

can refer to yield tables for each of these species for 

comparisons of yield at various ages for specifi ed levels of 

site index.

We frequently have many undisturbed even-aged natural 

forest stands where several tree species are growing 

together and where each of these tree species have freegrowing dominant and codominant trees. For such 

stands, we can directly measure and compare site indices 

for each of these alternative tree species using site index 

curves published for each of these species (Carmean et 

al. 1989). Potential yield and potential commercial value 

then could be estimated for each of the alternative species 

using appropriate yield tables and models.

However many even-aged forest stands are essentially 

pure stands having only a single species with measurable 

dominant and codominant trees, e.g., pure jack pine, 

black spruce, or trembling aspen stands. For example, 

a pure even-aged jack pine stand might only have 

dominant and codominant jack pine trees, thus we only 

are able to directly estimate jack pine site index using jack 

pine site index curves (Carmean et al. 2001). For such 

pure stands, we would be uncertain about site indices 

for other alternative tree species such as black spruce, 

trembling aspen, and red pine that could be considered 

for management on that site. Th e reason is that no 

direct estimates of site index for these alternative species 

are possible simply because this stand lacks suitable 

dominant and codominant trees for these alternative tree 

species.

Th e species site index comparison method (Carmean 

1975, 1979, 1996, Carmean and Vasilevsky 1971) uses 

direct site index measurements from tree species present 

in the stand as a means for estimating site index of 

alternative species not present in the stand that might 

be considered for management on that particular site. 

For example, in the pure jack pine stand described above 

we could directly estimate jack pine site index using 

height and age measurements from the dominant and 

codominant jack pine trees together with jack pine site 

index curves. We then could use models and graphs 

that relate measured jack pine site index to estimated 

site index for other alternative tree species not present 

in the stand. Armed with site index estimates for each 

of the alternative tree species, we then could refer to 

yield tables or yield models for estimations about which 

of the alternative tree species is most productive and 

commercially valuable tree for that location. Th is is 

accomplished for each location by ranking the estimated 

site index values for the various alternative species, 

and then by referring to yield tables and models for 

estimates of potential yields and product values for fully 

stocked stands of each of these alternative tree species. 

Silvicultural practices then could be considered for 

establishing and managing stands of the most productive 

and commercially desirable species of tree for each 

location.

Species site index comparison studies are based on 

research where a large number of comparison plots are 

located in fully stocked even-aged stands representing 

the wide range of soil and site conditions found in a 

particular area or region. Each plot should contain freegrowing, uninjured dominant and codominant trees for 

two or more tree species thus providing paired site index 

observations for each of the tree species on the plot. Site 

index relations between these paired tree species using 

many comparison plots are then expressed using linear 

regression models and graphs that estimate site index for 

each of the alternative species based on direct site index 

measurements from the particular tree species that are 

actually present in the stand.

Th e objective of this report is to summarize results from 

six site index comparison studies for the Upper Great 

Lakes area: one study was for tree species in northern 

Minnesota (Carmean and Vasilevsky 1971), and another 

study was for northern hardwood species in northern 

Wisconsin and upper Michigan (Carmean 1979). An 

unpublished site index comparison study is available 

based on a Forest Resources Evaluation Program 

(FREP) report for Minnesota, Wisconsin, and Michigan 

(Carmean and Hahn 1981). Th ree unpublished H.B.Sc. 

Forestry theses also are available at Lakehead University 

in Th under Bay, Ontario (Dillabough 1983, Ortiz 1985, 

Th urston 1984).

Th ese six site index comparison studies have produced 

a large number of regression models and site index 

comparison graphs for 24 of the major hardwood and 
3

conifer forest species in the Upper Great Lakes area. 

Several of these studies provide separate and independent 

models for the same paired species comparisons, 

thus these separate and independent models for the 

same species comparisons can be compared and 

recommendations can be given about which models are 

the most precise site index comparison models for use in 

forest stands of the Upper Great Lakes area of the United 

States and Canada.

THE SIX SITE INDEX COMPARISON 

STUDIES

Northern Minnesota

Th is study (Carmean and Vasilevsky 1971) was based 

on tree height and total age data from a large number of 

randomly located U.S. Forest Service, Forest Inventory 

and Analysis plots (hereafter referred to as forest survey 

plots); several U.S. Soil Conservation Service (USCS)2

plots also were included. Th e forest survey plots were 

carefully screened to reject plots in stands that were 

poorly stocked, uneven-aged, or that were too young for 

dependable site index estimation. For our analysis, each 

even-aged plot had suitable dominant and codominant 

trees for two or more tree species so total age and total 

height measurements from these trees were used for 

estimating site index for each of the species found on the 

plot. Average site index (total height in feet of dominant 

and codominant trees at 50 years total age) for each 

species on each plot was estimated using harmonized 

site index curves (Carmean et al. 1989). Site index 

measurements from paired species combinations from 

many plots then were used to estimate linear regression 

models and site index comparison graphs for nine site 

index comparisons among conifer and hardwood tree 

species in northern Minnesota (Table 1).

Northern Hardwoods in Northern 

Wisconsin and Upper Michigan

Th is detailed study (Carmean 1979) was based on stem 

analyses from dominant and codominant trees growing 

in 204 carefully selected, fully stocked, even-aged, 

undisturbed northern hardwood plots. On each plot 

average height-age curves were constructed for each 

species using stem analyses from one to six dominant 

and codominant trees. Site index for each species on each 

plot then was estimated using average height-age curves 

to observe average tree height (site index) at 50 years 

total age. Paired site index estimates on each plot then 

were used to develop regression models and site index 

comparison graphs for 51 species site index comparison 

models for various northern hardwood tree species in 

northern Wisconsin and Upper Michigan (Table 1). 

Th ese stem analysis data also were used for constructing 

polymorphic (many shaped) site index curves for 12 

northern hardwood tree species (Carmean 1978).

The FREP Study

Th is unpublished study (Carmean and Hahn 1981) was 

similar to the earlier Carmean and Vasilevsky (1971) 

study but used a much greater number of forest survey 

and USCS plots located in Minnesota, Wisconsin, and 

Michigan. Th e randomly located forest survey plots were 

screened to reject plots that were poorly stocked or that 

had plots with trees that were uneven-aged or too young. 

Site index estimates again were based on harmonized site 

index curves (Carmean et al. 1989); site index estimation 

was aided using site index curve formulations developed 

by Lundgren and Dolid (1970). Site index estimates 

for paired tree species combinations then were used to 

develop regression models and graphs for 46 site index 

comparisons among conifer and hardwood tree species in 

Minnesota, Wisconsin, and Michigan (Table 1).

Conifers and Trembling Aspen in 

North Central Ontario

Th is unpublished H.B.Sc. Forestry thesis (Th urston 

1984) was based on 101 carefully selected plots in well 

stocked, even-aged, undisturbed stands having mixtures 

of conifer species and trembling aspen. Several of these 

plots already had site index estimates based on stemanalysis data that had been used for polymorphic site 

index curve and soil-site studies in north central Ontario 

(Carmean 1996, 2007). But most plots used total 

age and total height measurements from one to four 

dominant and codominant trees for each tree species on 

each plot; site index for each species was estimated using 

the polymorphic site index curves for northwest Ontario 2

Now known as Natural Resources Conservation Service.
4

Table 1.—Species site index comparisons between hardwood and conifer tree species are given in six studies for the Upper 

Great Lakes area. For each paired species combination, the number of plots and coefficients of determination (R2

) are given. 

Recommended models are noted with an asterisk.

Comparison 

number

Species

compared

Carmean 

and Hahn 

(1981) 

Carmean and

Vasilevsky

(1971)

Thurston

(1984)

Ortiz

(1985)

Dillabough

(1983)

Carmean

(1979)

1 Sugar maple-red maple 17 (0.33) - - - - 89 (0.79)*

2 Sugar maple-yellow birch 18 (0.61) - - - - 109 (0.74)*

3 Sugar maple-Am. beech - - - - 14 (0.33) 19 (0.38)*

4 Sugar maple-Am. basswood 159 (0.51) - - - 23 (0.68) 109 (0.71)*

5 Sugar maple-Am. elm 15 (0.76) - - - - 94 (0.74)*

6 Sugar maple-white ash 41 (0.40) - - - 52 (0.37) 59 (0.69)*

7 Sugar maple-black ash 9 (0.40) - - - - 27 (0.60)*

8 Sugar maple-n. red oak 77 (0.42) - - - 16 (0.62) 26 (0.44)*

9 Sugar maple-white birch - - - - - 23 (0.59)*

10 Sugar maple-aspens 79 (0.30) - - - - 7 (0.61)*

11 Sugar maple-bigtooth aspen 13 (0.61)* - - - - -

12 Sugar maple-black cherry - - - - 27 (0.32) 36 (0.73)*

13 Sugar maple-bitternut hickory - - - - 16 (0.64)* -

14 Red maple-yellow birch 12 (0.32) - - - - 71 (0.70)*

15 Red maple-Am. beech - - - - - 13 (0.38)*

16 Red maple-Am. basswood - - - - - 45 (0.79)*

17 Red maple-Am. elm - - - - - 39 (0.56)*

18 Red maple-white ash 14 (0.56) - - - - 30 (0.63)*

19 Red maple-black ash - - - - - 19 (0.60)*

20 Red maple-n. red oak 33 (0.29) - - - - 23 (0.72)*

21 Red maple-black cherry - - - - - 33 (0.58)*

22 Red maple-white birch 10 (0.36) - - - - 16 (0.67)*

23 Red maple-aspens 51 (0.31) - - - - 8 (0.80)*

24 Yellow birch-Am. beech - - - - - 15 (0.43)*

25 Yellow birch-Am. basswood 10 (0.40) - - - - 70 (0.78)*

26 Yellow birch-Am. elm - - - - - 60 (0.78)*

27 Yellow birch-white ash - - - - - 37 (0.68)*

28 Yellow birch-black ash - - - - - 20 (0.61)*

29 Yellow birch-n. red oak - - - - - 14 (0.74)*

30 Yellow birch-black cherry - - - - - 25 (0.61)*

31 Yellow birch-white birch - - - - - 16 (0.73)*

32 Yellow birch-aspens - - - - - 7 (0.89)*

33 Am. basswood-Am. elm 22 (0.70) - - - - 86 (0.70)*

34 Am. basswood-white ash - - - - 33 (0.47) 64 (0.70)*

35 Am. basswood-black ash 10 (0.49) - - - - 31 (0.63)*

36 Am. basswood-n. red oak - - - - 13 (0.59) 29 (0.76)*

37 Am. basswood-black cherry - - - - 11 (0.58) 15 (0.68)*

38 Am. basswood-white birch 14 (0.76) - - - - 20 (0.67)*

39 Am. basswood-aspens 85 (0.33) - - - - 8 (0.72)*

40 Am. basswood-trembling aspen 68 (0.35) 16 (0.45)* - - - -

41 Am. elm-white ash - - - - - 51 (0.78)*

42 Am. elm-black ash 17 (0.58) - - - - 34 (0.65)*

43 Am. elm-n. red oak - - - - - 15 (0.39)*

continued
5

44 Am. elm-black cherry - - - - - 16 (0.78)*

45 Am. elm-white birch - - - - - 12 (0.71)*

46 Am. elm-aspens - - - - - 7 (0.83)*

47 White ash-black ash - - - - - 27 (0.75)*

48 White ash-n. red oak 42 (0.48) - - - 24 (0.55) 22 (0.77)*

49 White ash-white birch - - - - - 9 (0.69)*

50 White ash-aspens - - - - - 7 (0.85)*

51 Black ash-n. red oak - - - - - 10 (0.51)*

52 Black ash-balsam poplar 8 (0.49)* - - - - -

53 N. red oak-white oak 37 (0.77)* - - - - -

54 N. red oak-trembling aspen 106 (0.48)* - - - - -

55 N. red oak-bigtooth aspen 58 (0.55)* - - - - -

56 N. red oak-aspens 164 (0.53) - - - - 7 (0.59)*

57 N. red oak-white birch - 32 (0.44) - - - 15 (0.63)*

58 White birch-trembling aspen 267 (0.37) 106 (0.51)* - - - -

59 White birch-bigtooth aspen 25 (0.61)* - - - - -

60 White birch-aspens 292 (0.39) - - - - 7 (0.91)*

61 Trembling aspen-bigtooth aspen 25 (0.83)* - - - - -

62 Trembling aspen-balsam poplar 122 (0.51)* - - - - -

63 Black cherry-bitternut hickory - - - - 11 (0.68)* -

64a Jack pine-red pine 48 (0.63)* 66 (0.40) - - - -

65 Jack pine-black spruce - - 57 (0.66) 39 (0.80)* - -

66 Jack pine-tamarack - - 6 (0.60)* - - -

67 Jack pine-trembling aspen 80 (0.32) - 35 (0.33) 26 (0.69)* - -

68 Jack pine-white birch 7 (0.62)* - - - - -

69a Red pine-white pine 77(0.70)* 58 (0.47) - - 58 (0.55) -

70 Red pine-white spruce 8 (0.44) 15 (0.65)* - - 11 (0.56) -

71 Red pine-red maple 8 (0.61)* - - - - -

72 White pine-white spruce - 23 (0.62) - - 23 (0.71)* -

73 White pine-trembling aspen 14 (0.72)* - - - - -

74 White pine-red maple 10 (0.46)* - - - - -

75 Black spruce-tamarack 26 (0.34) 67 (0.52) 9 (0.91)* - - -

76 Black spruce-trembling aspen - - 16 (0.27) 19 (0.74)* - -

77 White spruce-n. white cedar 9 (0.84)* - - - - -

78 White spruce-trembling aspen 28 (0.42)* - - - - -

79 White spruce-Norway spruce - - - - 23 (0.76)* -

80 Balsam fir-n. white cedar 15 (0.71)* 19 (0.43) - - - -

81 Balsam fir-white birch 15 (0.68)* - - - - -

82 Tamarack-n. white cedar 10 (0.67)* - - - - -

a Data from USCS plots located in Minnesota, Wisconsin, and Michigan.

Comparison 

number

Species

compared

Carmean

and Hahn

(1981) 

Carmean and

Vasilevsky

(1971)

Thurston

(1984)

Ortiz

(1985)

Dillabough

(1983)

Carmean

(1979)

Table 1.—continued 
6

(Carmean 1996, 2007). Paired site index estimates for 

tree species on each of these 51 plots then were used to 

estimate linear regression models and graphs for fi ve site 

index comparisons among conifer species and trembling 

aspen in north central Ontario (Table 1).

Conifers and Trembling Aspen in 

Northwestern Ontario

Th is unpublished H.B.Sc. Forestry thesis (Ortiz 1985) 

was based on 84 carefully selected plots in well stocked, 

even-aged, undisturbed stands having mixtures of 

conifer species and trembling aspen. Total age and total 

height measurements were taken from at least three 

dominant and codominant trees for each tree species on 

each plot and were used for estimating site index using 

polymorphic site index curves for northwest Ontario 

(Carmean 1996, 2007). Paired site index estimates 

from each of the 84 plots then were used to develop 

linear regression models and graphs for three site index 

comparisons between conifer species and trembling aspen 

in northwest Ontario (Table 1).

Northern Hardwoods and Conifers in 

Southern Ontario

Th is unpublished H.B.Sc. Forestry thesis (Dillabough 

1983) was based on 310 carefully selected plots in well 

stocked, even-aged, undisturbed hardwood stands and 

in older conifer plantations. Total age and total height 

measurements taken from at least two dominant and 

codominant trees for each species of tree on each plot 

were used for site index estimation. Site index estimation 

for the hardwood species was based on polymorphic 

site index curves for northern Wisconsin and Upper 

Michigan (Carmean 1978), and site index estimation 

for the conifer species was based on polymorphic site 

index curves for northwest Ontario (Carmean 1996, 

2007). Paired site index estimates for each of the tree 

species on each of the 310 plots then were used to 

develop regression models and graphs for 15 site index 

comparisons between hardwood and conifer tree species 

in southern Ontario (Table 1).

ANALYSIS

Methods used for computing the site-index estimation 

models (Table 2) were similar for each of the six 

separate studies. For example, the northern hardwood 

study (Carmean 1979) had 89 plots for comparing site 

indices between sugar maple and red maple (Table 2—

comparison 1). Two regression models were computed: 

one model used site index observations of sugar maple 

as the dependent variable and the other model used 

site index observations of red maple as the dependent 

variable. Both of these regression models had excellent 

precision (R2

 = 0.79) and there was no apparent reason to 

favor one model over the other. However, an additional 

model also was desired that could be solved forward 

and backward, so a third graphically constructed model 

was produced that averaged the trends produced by the 

fi rst two models. Th ese graphically constructed average 

models are given for all comparisons (Table 2), and 

these are the models used for computing all site index 

prediction graphs (Figure 1).

For each species pair, the graphically constructed average 

model was obtained by graphing the trends produced 

by each of the two regression models. For species 

comparison pairs having excellent precision (large R2 

values), the trend graphs based on the two models were 

very similar. However, for species comparison pairs that 

were less precise (smaller R2 values), the two-trend graphs 

varied widely at the extremes of very high or very poor 

site index even though the two-trend graphs coincided 

at average site index. Th e graphically constructed average 

trend graph was obtained by graphing an average line 

between the two computed trend lines. Two limitations 

were observed for this graphically plotted line: (i) the 

graphed line was not extrapolated beyond actual observed 

site index values; and (ii) the graphically constructed line 

was only used when site index diff erences between the 

two computed regression lines were less than 5 feet.
7

Table 2.—Recommended regression models for 82 site index comparisons between hardwood and conifer species in the 

Upper Great Lakes area. For each comparison, the first two listed models are the computed models and the third listed model 

is the average model that was used from constructing the graphs in Figure 1. For 10 comparisons, improved precision was 

attained when a variable expressing drainage was added to the model (e.g., 1a, 2a, ...).

Comp.

no. Species compared Study†

No. of 

plots

SI range

(ft.) Models

Coeff. of 

determ.

(R2

)

Std. error of 

estimate

(%)

1 Sugar maple 6 89 42-74 SISM = 3.336 + 0.930 (SIRM) 0.79 3.14

 vs. red maple 89 42-73 SISM = 9.362 + 0.851 (SISM) 0.79 3.00

SISM = -3.563 + 1.048 (SIRM)

 1a§ SISM =-0.204 + 0.948 (SIRM) + 0.700 (dr) 0.81 3.04

SIRM = 11.933 + 0.852 (SISM) - 0.730 (dr) 0.81 2.88

SISM = -6.778 + 1.055 (SIRM) + 0.715 (dr)

2 Sugar maple 6 109 42-75 SISM = 6.787 + 0.885 (SIYB) 0.74 3.66

 vs. yellow birch 109 40-76 SIYB = 10.327 + 0.825 (SISM) 0.74 3.63

SISM = -2.119 +1.036 (SIYB)

2a§ SISM = 4.016 + 0.892 (SIYB) + 0.661 (dr) 0.74 3.60

SIYB = 12.389 + 0.829 (SISM) - 0.663 (dr) 0.74 3.47

SISM = -4.775 + 1.037 (SIYB) + 0.662 (dr)

3 Sugar maple 6 19 47-65 SISM = 25.063 + 0.611 (SIB) 0.38 3.66

 vs. Am. beech 19 45-61 SIB = 17.057 + 0.628 (SISM) 0.38 3.91

SISM = 4.902 + 0.989 (SIB)

4 Sugar maple 6 109 42-75 SISM = 6.299 + 0.832 (SIAB) 0.68 3.77

 vs. Am. basswood 109 45-80 SIAB = 15.101 + 0.821 (SISM) 0.68 3.74

SISM = -4.970 +1.008 (SIAB)

4a§ SISM = 2.136 + 0.839 (SIAB) + 1.141 (dr) 0.71 3.61

SIAB = 17.229 + 0.842 (SISM) - 1.042 (dr) 0.71 3.62

SISM = -8.299 + 1.000 (SIAB) + 1.092 (dr)

5 Sugar maple 6 94 43-75 SISM = 10.609 + 0.766 (SIAE) 0.74 3.52

 vs. Am. elm 94 47-81 SIAE = 8.840 + 0.925 (SISM) 0.74 3.87

SISM = 1.262 + 0.912 (SIAE)

5a§ SISM = 8.466 + 0.750 (SIAE) + 1.028 (dr) 0.74 3.37

SIAE = 9.334 + 0.957 (SISM) - 0.778 (dr) 0.72 3.81

SISM = 0.820 + 0.874 (SIAE) + 0.903 (dr)

6 Sugar maple 6 59 42-75 SISM = 11.189 + 0.728 (SIWA) 0.69 3.88

 vs. white ash 59 46-84 SIWA = 10.572 + 0.941 (SISM) 0.69 4.41

SISM =1.006 + 0.880 (SIWA)

7 Sugar maple 6 27 42-70 SISM = 7.706 + 0.801 (SIBA) 0.60 4.48

 vs. black ash 27 52-78 SIBA = 20.285 + 0.743 (SISM) 0.60 4.31

SISM = -7.746 + 1.041 (SIBA)

8 Sugar maple 6 26 42-70 SISM = 0.906 + 0.885 (SINRO) 0.44 4.23

 vs. n. red oak 26 57-72 SINRO = 35.432 + 0.493 (SISM) 0.44 3.16

SISM = -25.774 + 1.304 (SINRO)

9 Sugar maple 6 23 43-69 SISM = 6.306 + 0.809 (SIWB) 0.59 4.24

 vs. white birch 23 47-72 SIWB = 21.018 + 0.726 (SISM) 0.59 4.24

SISM = -8.975 + 1.055 (SIWB)

 10 Sugar maple 6 7 42-75 SISM = 2.624 + 0.780 (SIA) 0.61 7.82

 vs. aspens 7 65-85 SIA = 25.430 + 0.776 (SISM) 0.61 7.81

SISM = -12.575 + 0.998 (SIA) 

continued
8

11 Sugar maple 1 13 44-67 SISM = 18.35 + 0.56 (SIBA) 0.61 5.1

 vs. bigtooth aspen 13 47-91 SIBA = 4.09 + 1.14 (SISM) 0.61 7.3

SISM = 8.19 + 0.71 (SIBA)

12 Sugar maple 6 36 42-68 SISM = 14.384 + 0.729 (SIBC) 0.73 3.22

 vs. black cherry 36 47-73 SIBC = 2.176 + 1.000 (SISM) 0.73 3.77

SISM = 6.752 +0.854 (SIBC)

13 Sugar maple 5 16 54-98 SISM = 13.10 + 0.80 (SIBH) 0.64 11.2

vs. bitternut hickory 16 62-99 SIBH = 17.43 + 0.80 (SISM) 0.64 11.2

SIBH = 1.66 + 1.01 (SISM)

14 Red maple 6 71 42-73 SIRM = 7.837 + 0.876 (SIYB) 0.70 3.60

 vs. yellow birch 71 40-72 SIYS = 10.943 + 0.802 (SIRM) 0.70 3.44

SIRM = -2.119 + 1.048 (SIYB) 

15 Red maple 6 13 50-63 SIRM = 28.555 + 0.547 (SIB) 0.38 3.47

 vs. Am. beech 13 45-60 SIB = 13.616 + 0.688 (SIRM) 0.38 3.89

SIRM = 9.510 + 0.904 (SIB)

16 Red maple 6 45 43-72 SIRM = 4.068 + 0.881 (SIAB) 0.79 3.40

 vs. Am. basswood 45 45-74 SIAB = 9.417 + 0.892 (SIRM) 0.79 3.42

SIRM = -2.628 +0.991 (SIAB)

17 Red maple 6 39 46-71 SIRM = 19.926 + 0.628 (SIAE) 0.56 4.09

 vs. Am. elm 39 47-76 SIAE= 8.686 + 0.899 (SIRM) 0.56 4.90

SIRM = 6.729 + 0.844 (SIAE) 

18 Red maple 6 30 46-70 SIRM = 21.977 + 0.593 (SIWA) 0.63 4.02

 vs. white ash 30 44-76 SIWA = 0.017 + 1.065 (SIRM) 0.63 5.39

 SIRM = 11.937 + 0.751 (SIWA)

19 Red maple 6 19 43-68 SIRM = 5.616 + 0.870 (SIBA) 0.60 4.42

 vs. black ash 19 51-70 SIBA = 20.283 + 0.688 (SIRM) 0.60 3.93

SIRM = -9.376 + 1.119 (SIBA) 

20 Red maple 6 23 46-72 SIRM = -1.339 + 0.951 (SINRO) 0.72 3.79

 vs. n. red oak 23 50-74 SINRO = 18.470 + 0.760 (SIRM) 0.72 3.39

SIRM = -11.597 + 1.114 (SINRO)

21 Red maple 6 33 42-72 SIRM = 19.203 + 0.655 (SIBC) 0.58 4.33

 vs. black cherry 33 42-73 SIBC = 8.391 + 0.889 (SIRM) 0.58 5.05

SIRM = 6.478 + 0.864 (SIBC)

22 Red maple 6 16 46-72 SIRM = -3.591 + 0.999 (SIWB) 0.67 4.75

 vs. white birch 16 47-70 SIWB = 21.976 + 0.675 (SIRM) 0.67 3.90

SIRM = -16.538 + 1.215 (SIWB)

23 Red maple 6 8 46-70 SIRM = -11.216 + 1.047 (SIA) 0.80 4.01

 vs. aspens 8 53-75 SIA = 21.133 + 0.766 (SIRM) 0.80 3.44

SIRM = -18.897 + 1.168 (SIA)

24 Yellow birch 6 15 51-65 SIYB = 25.611 + 0.614 (SIB) 0.43 2.80

 vs. Am. beech 15 48-61 SIB = 12.459 + 0.703 (SIYB) 0.43 3.00

SIYB = 7.717 + 0.948 (SIB)

Table 2.—continued

Comp.

no. Species compared Study†

No. of 

plots

SI range

(ft.) Models

Coeff. of 

determ.

(R2

)

Std. error of 

estimate

(%)

continued
9

24a§ SIYB = 38.764 + 0.630 (SIB) - 3.060 (dr) 0.65 2.29

SIB = -11.994 + 0.897 (SIYB) + 2.858 (dr) 0.57 2.74

SIYB = 27.645 + 0.842 (SIB) - 2.959 (dr)

25 Yellow birch 6 70 40-76 SIYB = 2.585 + 0.883 (SIAB) 0.78 3.45

 vs. Am. basswood 70 45-78 SIAB = 11.951 + 0.880 (SIYB) 0.78 3.44

SIYB = -4.758 + 0.998 (SIAB)

 26 Yellow birch 6 60 43-76 SIYB = 11.861 + 0.746 (SIAE) 0.78 2.93

 vs. Am. elm 60 47-81 SIAE = 1.371 + 1.050 (SIYB) 0.78 3.47

SIYB = 5.216 + 0.850 (SIAE) 

27 Yellow birch 6 37 43-76 SIYB = 12.318 + 0.715 (SIWA) 0.68 4.02

 vs. white ash 37 46-84 SIWA = 9.273 + 0.956 (SIYB) 0.68 4.65

SIYB = 1.885 + 0.872 (SIWA)

28 Yellow birch 6 20 48-68 SIYB = 22.082 + 0.585 (SIBA) 0.61 3.49

 vs. black ash 20 52-78 SIBA = 1.628 + 1.049 (SIYB) 0.61 4.68

SIYB = 11.436 + 0.751 (SIBA) 

28a§ SIYB = 22.159 + 0.656 (SIBA) - 1.792 (dr) 0.80 2.84

SIBA = -6.289 + 1.069 (SIYB) + 2.618 (dr) 0.81 2.30

SIYB = 14.950 + 0.781 (SIBA) - 2.205 (dr)

29 Yellow birch 6 14 51-68 SIYB = 3.045 + 0.849 (SINRO) 0.74 2.52

 vs. n. red oak 14 58-72 SINRO = 14.390 + 0.867 (SIYB) 0.74 2.55

SIYB = -6.197 +0.992 (SINRO)

30 Yellow birch 6 25 42-71 SIYB = 18.053 + 0.674 (SIBC) 0.61 4.06

 vs. black cherry 25 42-73 SIBC = 7.385 + 0.899 (SIYB) 0.61 4.69

SIYB = 6.718 + 0.863 (SIBC) 

31 Yellow birch 6 16 42-67 SIYB = -0.735 + 0.903 (SIWB) 0.73 3.79

 vs. white birch 16 47-72 SIWB = 17.342 + 0.806 (SIYS) 0.73 3.58

SIYB = -10.258 + 1.058 (SIWB)

32 Yellow birch 6 7 53-76 SIYB = -5.865 + 0.934 (SIA) 0.89 3.75

 vs. aspens 7 53-85 SIA = 12.670 + 0.958 (SIYB) 0.89 3.80

SIYB = -9.885 + 0.994 (SIA) 

33 Am. basswood 6 86 48-80 SIAB = 14.611 + 0.770 (SIAE) 0.70 3.59

 vs. Am. elm 86 47-81 SIAE = 6.421 + 0.904 (SIAB) 0.70 3.89

SIAB = 4.856 + 0.921 (SIAE)

34 Am. basswood 6 64 45-80 SIAB = 18.977 + 0.689 (SIWA) 0.70 3.66

 vs. white ash 64 44-84 SIWA = 0.885 + 1.012 (SIAB) 0.70 4.45

SIAB = 9.642 + 0.828 (SIWA)

35 Am. basswood 6 31 47-78 SIAB = 13.427 + 0.797 (SIBA) 0.63 4.19

 vs. black ash 31 51-78 SIBA = 13.243 + 0.789 (SIAB) 0.63 4.17

SIAB = -0.256 + 1.101 (SIBA)

36 Am. basswood 6 29 45-75 SIAB = -5.183 + 1.065 (SINRO) 0.76 3.10

 vs. n. red oak 29 50-74 SINRO = 19.132 + 0.711 (SIAB) 0.76 2.53

SIAB = -15.079 + 1.221 (SINRO) 

Table 2.—continued

Comp.

no. Species compared Study†

No. of 

plots

SI range

(ft.) Models

Coeff. of 

determ.

(R2

)

Std. error of 

estimate

(%)

continued
10

36a§ SIAB = -4.459 + 1.107 (SINRO) - 1.166 (dr) 0.80 2.84

SINRO = 15.415 + 0.725 (SIAB) + 0.980 (dr) 0.81 2.30

SIAB = -12.118 + 1.232 (SINRO) -1.703 (dr) 

37 Am. basswood 6 15 50-74 SIAB = 26.527 + 0.592 (SIBC) 0.68 3.96

 vs. black cherry 15 49-74 SIBC = -10.699 + 1.151 (SIAB) 0.68 5.53

SIAB = 18.257 + 0.725 (SIBC)

38 Am. basswood 6 20 49-74 SIAB = 9.115 + 0.825 (SIWB) 0.67 3.81

 vs. white birch 20 47-72 SIWB = 13.238 + 0.813 (SIAB) 0.67 3.78

SIAB = -1.913 + 1.001 (SIWB) 

39 Am. basswood 6 8 45-78 SIAB = 1.482 + 0.855 (SIA) 0.72 6.40

 vs. aspens 8 53-85 SIA = 17.712 + 0.847 (SIAB) 0.72 6.37

SIAB = -8.775 + 1.004 (SIA)

40 Trembling aspen 2 16 40-80 SITA = 22.41 + 0.75 (SIAB) 0.45 8.1

 vs. Am. basswood 16 37-80 SIAB = 20.49 + 0.59 (SITA) 0.45 7.2

SITA = 0.60 + 1.11 (SIAB)

41 Am. elm 6 51 49-81 SIAE = 10.769 + 0.807 (SIWA) 0.78 3.28

 vs. white ash 51 46-84 SIWA = 4.696 + 0.963 (SIAE) 0.78 3.58

SIAE = 3.405 + 0.916 (SIWA) 

41a§ SIAE = 10.869 + 0.833 (SIWA) - 0.704 (dr) 0.79 3.22

SIWA = 3.201 + 0.946 (SIAE) + 1.003 (dr) 0.79 3.43

SIAE = 4.066 + 0.940 (SIWA) - 0.854 (dr)

42 Am. elm 6 34 45-76 SIAE = 13.004 + 0.804 (SIBA) 0.65 4.19

 vs. black ash 34 48-76 SIBA = 11.452 + 0.814 (SIAE) 0.65 4.22

SIAE = 0.946 + 0.993 (SIBA)

42a§ SIAE = 3.775 + 0.888 (SIBA) + 6 .190 (dr) - 

 1.671 (dr2)

0.78 3.46

SIBA = 10.381 + 0.852 (SIAE) - 4.166 (dr) +

 1.321 (dr2) 

0.79 3.39

SIAE = -2.945 + 1.010 (SIBA) + 5.178 (dr) -

 1.496 (dr2) 

43 Am. elm 6 15 60-75 SIAE = 7.671 + 0.903 (SINRO) 0.39 3.91

 vs. n. red oak 15 59-72 SINRO = 35.862 + 0.429 (SIAE) 0.39 2.69

SIAE = -24.195 + 1.402 (SINRO)

44 Am. elm 6 16 47-73 SIAE = 14.628 + 0.792 (SIBC) 0.78 3.89

 vs. black cherry 16 42-74 SIBC = -0.755 + 0.984 (SIAE) 0.78 4.33

SIAE = 8.384 + 0.893 (SIBC) 

45 Am. elm 6 12 49-76 SIAE = 5.168 + 0.899 (SIWB) 0.71 4.49

 vs. white birch 12 47-72 SIWB = 14.042 + 0.784 (SIAE) 0.71 4.20

SIAE = -5.084 + 1.066 (SIWB)

46 Am. elm 6 7 49-81 SIAE = 5.206 + 0.816 (SIA) 0.83 4.81

 vs. aspens 7 53-85 SIA = 6.593 + 1.011 (SIAE) 0.83 5.35

SIAE = -0.214 + 0.896 (SIA) 

Table 2.—continued

Comp.

no. Species compared Study†

No. of 

plots

SI range

(ft.) Models

Coeff. of 

determ.

(R2

)

Std. error of 

estimate

(%)

continued
11

47 White ash 6 27 51-76 SIWA = 3.969 + 0.981 (SIBA) 0.75 3.44

 vs. black ash 27 52-76 SIBA = 12.862 + 0.766 (SIWA) 0.75 3.04

SIWA = -5.428 + 1.128 (SIBA)

48 White ash 6 22 44-76 SIWA = -22.933 + 1.362 (SINRO) 0.77 3.95

 vs. n. red oak 22 50-72 SINRO = 27.478 + 0.566 (SIWA) 0.77 2.55

SIWA = -34.762 + 1.549 (SINRO) 

48a§ SIWA = -22.374 + 1.414 (SINRO) -1.419 (dr) 0.81 3.70

SINRO = 24.477 + 0.573 (SIWA) + 0.956 (dr) 0.82 2.35

SIWA= -31.350 + 1.561 (SINRO) - 1.188 (dr)

49 White ash 6 9 46-74 SIWA = -3.853 + 1.023 (SIWB) 0.69 5.18

 vs. white birch 9 47-70 SIWB = 21.765 + 0.674 (SIWA) 0.69 4.21

SIWA = -16.344 + 1.225 (SIWB)

50 White ash 6 7 44-84 SIWA = -17.000 + 1.111 (SIA) 0.85 5.86

 vs. aspens 7 60-85 SIA = 23.089 + 0.767 (SIWA) 0.85 4.87

SIWA = -23.105 + 1.201 (SIA) 

51 Black ash 6 10 52-76 SIBA = -9.946 + 1.154 (SINRO) 0.51 4.99

 vs. n. red oak 10 58-72 SINRO = 35.708 + 0.444 (SIBA) 0.51 3.09

SIBA = -37.214 + 1.579 (SINRO)

52 Black ash 1 8 42-72 SIBA = 23.68 + 0.57 (SIBP) 0.49 6.8

 vs. balsam poplar 8 35-78 SIBP = 3.23 + 0.99 (SIBA) 0.49 9.0

SIBA = 11.71 + 0.77 (SIBP)

53 N. red oak 1 37 33-83 SINRO = 7.99 + 0.95 (SIWO) 0.77 6.6

 vs. white oak 37 25-79 SIWO = 5.48 + 0.82 (SINRO) 0.77 6.2

SIWO = -1.24 + 0.94 (SINRO)

54 N. red oak 1 106 36-100 SINRO = 6.74 + 0.82 (SITA) 0.48 8.4

 vs. trembling aspen 106 42-94 SITA = 29.63 + 0.59 (SINRO) 0.48 7.1

SITA = 13.86 + 0.86 (SINRO)

55 N. red oak 1 58 37-94 SINRO = 9.93 + 0.77 (SIBA) 0.55 7.2

 vs. bigtooth aspen 58 46-91 SIBA = 24.23 + 0.73 (SINRO) 0.55 5.7

SIBA = 7.99 + 0.98 (SINRO)

56 N. red oak 6 7 50-74 SINRO = 15.208 + 0.672 (SIA) 0.59 5.38

 vs. aspens 7 56-80 SIA = 13.919 + 0.883 (SINRO) 0.59 6.16

SINRO = 1.756 + 0.872 (SIA) 

57 N. red oak 6 15 50-74 SINRO = 0.014 + 0.997 (SIWB) 0.63 4.35

 vs. white birch 15 54-70 SIWB = 23.734 + 0.628 (SINRO) 0.63 3.46

SINRO = -16.401 + 1.255 (SIWB)

58 Trembling aspen 2 106 43-90 SITA = 24.36 + 0.67 (SIWB) 0.51 6.2

 vs. white birch 106 37-82 SIWB = 9.87 + 0.75 (SITA) 0.51 6.6

SITA = 8.50 + 0.95 (SIWB)

59 White birch 1 25 46-76 SIWB = 24.28 + 0.56 (SIBA) 0.61 5.0

 vs. bigtooth aspen 25 46-91 SIBA = -1.48 + 1.11 (SIWB) 0.61 7.0

SIWB = 13.93 + 0.71 (SIBA)

Table 2.—continued

Comp.

no. Species compared Study†

No. of 

plots

SI range

(ft.) Models

Coeff. of 

determ.

(R2

)

Std. error of 

estimate

(%)

continued
12

60 White birch 6 7 47-69 SIWB = 5.271 + 0.849 (SIA) 0.91 2.37

 vs. aspens 7 53-75 SIA = -0.239 + 1.077 (SIWB) 0.91 2.67

SIWB = 2.296 + 0.818 (SIA) 

61 Trembling aspen 6 25 54-96 SITA = 3.81 + 0.93 (SIBA) 0.83 4.3

 vs. bigtooth aspen 25 54-94 SIBA = 7.99 + 0.90 (SITA) 0.83 4.2

SIBA = 2.22 + 0.98 (SITA)

62 Trembling aspen 6 122 30-96 SITA = 19.53 + 0.75 (SIBP) 0.51 8.0

 vs. balsam poplar 122 30-86 SIBP = 14.53 + 0.69 (SITA) 0.51 7.6

SIBP = -2.68 + 0.96 (SITA)

63 Black cherry 5 11 68-93 SIBC = 49.45 + 0.42 (SIBH) 0.68 6.6

 vs. bitternut hickory 62-104 SIBH = -55.49 + 1.63 (SIBC) 0.68 13.0

SIBH = -88.69 + 2.00 (SIBC)

64◊ Jack pine 1 48 43-80 SIJP = 12.09 + 0.82 (SIRP) 0.63 5.3

 vs. red pine 48 43-79 SIRP = 11.97 + 0.77 (SIJP) 0.63 5.2

SIJP = -0.08 + 1.03 (SIRP)

65‡ Jack pine 4 39 30-74 SIJP = 0.46 + 1.01 (SIBS) 0.80 5.1

 black spruce 39 28-69 SIBS = 9.45 + 0.79 (SIJP) 0.80 4.5

SIJP = -5.71 + 1.13 (SIBS)

66‡ Jack pine 3 6 46-59 SIJP = -4.89 + 1.00 (SIT) 0.60 2.4

 vs. tamarack 6 51-62 SIT = -5.75 + 0.60 (SIJP) 0.60 2.0

SIJP = -21.26 + 1.29 (SIT)

67‡ Jack pine 4 26 28-72 SIJP = 15.94 + 0.67 (SITA) 0.69 5.9

 vs. trembling aspen 26 30-74 SITA = -0.10 + 1.04 (SIJP) 0.69 7.3

SIJP = 8.01 + 0.81 (SITA)

68 Jack pine 1 7 52-83 SIJP = 1.53 + 1.09 (SIWB) 0.62 6.3

 vs. white birch 7 49-68 SIWB = 18.12 + 0.63 (SIJP) 0.62 4.8

SIJP = -11.77 + 1.31 (SIWB)

69◊ Red pine 1 77 37-75 SIRP = 12.12 + 0.80 (SIWP) 0.70 4.7

 vs. white pine 77 29-71 SIWP = 5.04 + 0.88 (SIRP) 0.70 4.9

SIRP = 3.93 + 0.96 (SIWP)

70 Red pine 1 15 43-70 SIRP = 26.58 + 0.56 (SIWS) 0.65 4.0

 vs. white spruce 15 36-67 SIWS = -11.87 + 1.17 (SIRP) 0.65 5.8

SIRP = 18.90 + 0.70 (SIWS)

71 Red pine 1 8 51-75 SIRP = 23.60 + 0.59 (SIRM) 0.61 5.3

 vs. red maple 8 38-75 SIRM = -2.03 + 1.04 (SIRP) 0.61 7.0

SIRP = 13.60 + 0.76 (SIRM)

72 White pine 5 23 58-98 SIWP = 16.52 + 0.85 (SIWS) 0.71 10.7

 vs. white spruce 23 53-93 SIWS = 8.75 + 0.84 (SIWP) 0.71 10.0

SIWS = -5.50 + 1.01 (SIWP)

73 White pine 1 14 41-72 SIWP = 0.15 + 0.94 (SITA) 0.72 5.7

 vs. trembling aspen 14 40-75 SITA = 15.80 + 0.79 (SIWP) 0.72 5.3

SIWP = -9.00 + 1.09 (SITA)

Table 2.—continued

Comp.

no. Species compared Study†

No. of 

plots

SI range

(ft.) Models

Coeff. of 

determ.

(R2

)

Std. error of 

estimate

(%)

continued
13

74 White pine 1 10 46-87 SIWP = 21.50 + 0.68 (SIRM) 0.46 7.6

 vs. red maple 10 40-77 SIRM = 12.92 + 0.77 (SIWP) 0.46 8.2

SIWP = 5.26 + 0.94 (SIRM)

75‡ Black spruce 3 9 9-53 SIBS = -2.36 + 0.85 (SIT) 0.91 4.3

 vs. tamarack 9 17-62 SIT = 7.02 + 1.06 (SIBS) 0.91 4.8

SIBS = -4.33 + 0.89 (SIT)

76‡ Black spruce 4 19 31-66 SIBS = -5.74 + 1.00 (SITA) 0.74 5.4

 vs. trembling aspen 19 45-71 SITA = 19.35 + 0.74 (SIBS) 0.74 4.7

SIBS = -15.94 + 1.17 (SITA)

77 White spruce 1 9 25-56 SIWS = -15.25 + 1.66 (SINWC) 0.84 4.0

 vs. n. white cedar 9 24-40 SINWC = 12.57 + 0.52 (SIWS) 0.84 2.2

SIWS = -19.49 + 1.79 (SINWC)

78 White spruce 1 28 29-82 SIWS = 13.30 + 0.67 (SITA) 0.42 9.7

 vs. trembling aspen 28 25-86 SITA = 26.63 + 0.67 (SIWS) 0.42 9.7

SIWS = -7.89 + 1.00 (SITA)

79 White spruce 5 23 31-86 SIWS = 2.62 + 0.90 (SINS) 0.76 11.5

 vs. Norway spruce 23 48-97 SINS = 16.66 + 0.88 (SIWS) 0.76 4.8

SINS = 7.40 + 0.97 (SIWS)

80 Balsam fir 1 15 28-61 SIBF = -6.81 + 1.59 (SINWC) 0.71 4.8

 vs. n. white cedar 15 25-40 SINWC = 11.63 + 0.46 (SIBF) 0.71 2.6

SIBF =-15.20 + 1.85 (SINWC)

81 Balsam fir 1 15 28-66 SIBF = 18.22 + 0.59 (SIWB) 0.68 6.0

 vs. white birch 15 26-77 SIWB = -6.62 + 1.20 (SIBF) 0.68 8.5

SIBF = 12.10 + 0.71 (SIWB)

82 Tamarack 1 10 25-55 SIT = -4.22 + 1.67 (SINWC) 0.67 5.9

 vs. n. white cedar 21-35 SINWC = 9.95 + 0.42 (SIT) 0.67 3.0

SIT = -12.71 + 1.98 (SINWC)

† Study: (1) Carmean and Hahn (1981) (4) Ortiz (1985)

 (2) Carmean and Vasilevsky (1971) (5) Dillabough (1983)

 (3) Thurston (1984) (6) Carmean (1979)

§ Drainage (dr) classes are: 1 = poorly drained; 2 = somewhat poorly drained; 3 = moderately well drained; 4 = well drained; and 5 = somewhat excessively 

drained (USCS 1975)

◊ Data for comparisons 64 and 69 were from USCS plots in Minnesota, Wisconsin and Michigan.

‡ Equations 65, 66, 67, 75 and 76 were metric equations in the original reports. Converting these equations to English equations involved multiplying the 

bo coefficients by the 3.28 converting factor.

Table 2.—continued

Comp.

no. Species compared Study†

No. of 

plots

SI range

(ft.) Models

Coeff. of 

determ.

(R2

)

Std. error of 

estimate

(%)
14

Figure 1.—Site index comparison graphs for 82 recommended models that express site index relations between hardwood and 

conifer species in the Upper Great Lakes area. These graphs were constructed using the average models listed in Table 2.
15

Figure 1.—Continued.
16

Figure 1.—Continued.
17

Figure 1.—Continued.
18

Figure 1.—Continued.
19

Figure 1.—Continued.
20

Figure 1.—Continued.
21

Figure 1.—Continued.
22

Figure 1.—Continued.
23

Figure 1.—Continued.
24

Figure 1.—Continued.
25

Figure 1.—Continued.
26

Figure 1.—Continued.
27

Figure 1.—Continued.
28

Figure 1.—Continued.
29

Figure 1.—Continued.
30

RESULTS

Th e six separate and independent studies produced linear 

regression models expressing site index relations between 

82 paired combinations of hardwood and conifer tree 

species in the Upper Great Lakes area (Tables 1 and 2). 

Several of these six studies had regression models for the 

same paired species combinations, thus we were able to 

compare results between the studies for the same paired 

species combinations thus allowing us to select the most 

precise (largest R2

) models for use in the Upper Great 

Lakes area. For example, for the sugar maple versus red 

maple comparison (Table 1—comparison 1), results were 

available from two studies. We selected the northern 

Wisconsin and Upper Michigan model (Carmean 1979) 

because this study covered a wide range of observed site 

indices, had 89 carefully selected plots, dominant and 

codominant site trees in each plot were carefully selected, 

site index was based on stem analyses from these selected 

trees, and this study had excellent precision (R2

 = 0.79). 

Th is study had much better precision than the relatively 

poor precision (R2

 = 0.33) for the Carmean et al. (1981) 

model that only had 17 plots. Site index for this 1981 

study was based only on total tree age and total height 

measurements and site index was estimated using older 

harmonized site index curves.

Th e 82 recommended models are indicated in Table 

1 for each species comparison and average models for 

these recommended models are given in Table 2.3

Generally the recommended models in Tables 1 and 

2 were the most precise (largest R2

), were based on 

the greatest number of plots, and covered the widest 

range of site index. Th e alternative models from 

the other independent studies for the same paired 

species combinations were considered as separate 

and independent models useful for verifying the 

recommended models. Comparisons of trends shown by 

the recommended models (Table 1) with trends shown 

by the other verifying models showed that all trends were 

similar, therefore, giving confi dence in the reliability of 

the recommended models.

Figure 1, comparison 4 (Comp 4) illustrates how to use 

site index comparison graphs. Suppose you would like 

to estimate site index for American basswood in a sugar 

maple stand. For this stand, total height and total age 

measurements from several dominant and codominant 

sugar maple trees indicate that estimated site index for 

sugar maple is 60 feet; site index curves for sugar maple 

(Carmean 1978) are used for this direct site sugar maple 

index 60 estimation. In Figure 1, comparison 4, arrows 

illustrate that you start at 60 feet on the site index scale 

and then read right to the sugar maple line, then read up 

to the American basswood line, then read left back to the 

site index scale where site index for American basswood is 

estimated as 65 feet.

Th e reverse of this procedure also can be used in a stand 

where height and age measurements from American 

basswood trees indicate that American basswood has a 

site index of 65 feet. Using Figure 1 (comparison 4) we 

estimate that site index 65 feet for American basswood 

indicates that estimated sugar maple has a site index of 

60. Th is example illustrates that the average model (Table 

2—comparison 4) can be used forward or backward for 

estimating site indices for either basswood or sugar maple.

DISCUSSION

Study Methods

Large diff erences in precision are evident among the 

six studies (Table 1). Th e northern hardwood study 

(Carmean 1979) usually had models with very precise 

results (large R2 values), but the two studies based mostly 

on forest survey data (Carmean and Vasilevsky 1971, 

Carmean and Hahn 1981) usually had models with less 

precise results (small R2

 values).

Reasons for the excellent precision for the northern 

hardwood study (Carmean 1979) are: (i) plots were 

located in carefully selected areas having similar soil 

and topography; (ii) plots had similar older, even-aged, 

fully stocked, undisturbed, hardwood stands; (iii) site 

trees on each plot were carefully selected so that only 

free-growing, undamaged dominant and codominant 

trees were used; (iv) stem analyses from two or more 

site trees for each tree species on each plot were used for 

developing individual tree height-age curves that then 

3 Ten of the recommended 82 comparisons in Table 2 are for 

models where precision (R2) was improved using an added 

variable that expressed soil drainage.
31

were used for direct observation of site index; (v) for 

each of the species comparisons a large number of plots 

covering a wide range of site index were available for 

regression analysis; and (vi) improved precision for 10 

hardwood species comparisons was gained by adding an 

independent variable expressing soil drainage.

In contrast, the two studies based mostly on forest survey 

data (Carmean and Vasilevsky 1971, Carmean and Hahn 

1981) usually had models with poorer precision (smaller 

R2

). Reasons for poorer precision are: (i) forest survey 

plots were randomly located, thus many plots had to 

be rejected because they were in partially cut or poorly 

stocked stands, were in uneven-aged stands, or were in 

very young stands. We screened plot data attempting 

to reject such plots, however, a few less desirable plots 

might have been retained in the forest survey data set; 

(ii) some of the dominant and codominant site trees used 

on the forest survey plots might have suff ered from past 

suppression and crown injuries thus such trees may not 

have been suitable for accurate site index estimation; (iii) 

tree ages were based on fi eld examination of increment 

cores but accurate ring counts in the fi eld often are 

diffi cult for diff use porous tree species such as the aspens, 

white and yellow birch, and American beech; (iv) site 

index estimations were based on older harmonized 

site index curves (Carmean et al. 1989) that may not 

accurately express polymorphic tree-height growth 

patterns. Site index estimates from such harmonized 

site index curves might have particularly large errors for 

very old or very young trees, or for very good or very 

poor levels of site index; and (v) most of these older 

harmonized site index curves were based on total tree age 

rather than on breast-height age, thus precision of site 

index estimation is reduced because of slow and erratic 

early height growth before trees reached breast height.

Despite these many shortcomings, the two studies based 

on forest survey data (Carmean and Vasilevsky 1971, 

Carmean and Hahn1981) produced general results 

(Tables 1 and 2; Figure 1) that are still useful until more 

precise studies are made based on stem-analysis data 

from carefully selected plots, and from carefully selected 

dominant and codominant trees. Th e older Carmean 

and Vasilevsky (1971) study still has two recommended 

models (Table 1—comparisons 40 and 58); the larger 

Carmean et al. (1981) study still has 19 recommended 

models (Table 1).

Effects of Drainage

Th e northern hardwood study (Carmean 1979) produced 

regression models and graphs for 51 site index species 

comparisons having large R2

 values (Table 1, Figure 

1). Th is table also shows that precision for 10 of these 

models could be further improved when a drainage 

variable was added to the regression model.

Figure 2 illustrates that this drainage variable was 

constructed using depth to common or many soil 

mottles; a linear transformation provided a numerical 

code for representing depth to such mottles. We found 

that changes in soil drainage are associated with changes 

in site index for 10 species comparisons, and the 

Figure 2.—Soil drainage classes can 

be estimated based on depth to a 

soil horizon having common or many 

mottles (Carmean 1979—adopted 

from USDA 1975).
32

magnitude of these site index changes associated with 

drainage diff ered for diff erent tree species.

For example site index improvement with improved 

drainage was statistically signifi cant but the magnitude 

of improvement was small for the sugar maple versus red 

maple comparison as well as for the sugar maple versus 

yellow birch comparison (Table 2—comparisons 1a 

and 2a). Th is indicates that sugar maple, red maple, and 

yellow birch have similar site indices on better drained 

soils (drainage classes 5, 4 and 3), but on somewhat poor 

(drainage class 2) and poorly drained soils (drainage class 

1) red maple and yellow birch have slightly higher site 

indices than sugar maple.

But improved drainage has a major eff ect on the 

precision and site index diff erences for some paired 

species combinations. For example, for the yellow birch 

versus black ash comparison (Table 2 and Figure 1—

comparison 28a) adding the drainage variable improved 

precision from R2

=0.61 to R2=0.80; for the American 

elm versus black ash comparison (Table 2 and Figure 

1—comparison 42a) the drainage variable improved 

precision from R2

=0.65 to R2=0.78. Th e comparison 

graph (Figure 1—comparison 28a) shows that when 

growing together on poorly-drained soils (drainage class 

1) black ash and yellow birch have similar relatively poor 

site indices. However, as drainage improves (drainage 

classes 2, 3, and 4) site indices are better for black ash 

than for yellow birch site indices. Th e comparison graph 

(Figure 1—comparison 42a) indicates that when growing 

together on poorly drained and somewhat poorly drained 

soils (drainage classes 1, 2, 3) American elm and black 

ash have relatively similar site indices, but on well 

drained soils (drainage class 4) site indices for black ash 

are much better than site indices for American elm.

Site Index Comparisons for 

Hardwood Species

Results (Table 1, Figures 1 and 3) show that the aspens 

have the highest site indices and American beech has the 

lowest site indices when compared to other hardwood 

species. Sugar maple, red maple, and yellow birch have 

relatively similar site indices (Table 2 and Figure 1—

comparisons 1, 2, 14), but these three species usually 

have higher site indices than American beech and lower 

site indices than more intolerant hardwood species that 

include American basswood, American elm, white ash, 

black ash, northern red oak, black cherry, and white birch. 

Bitternut hickory was not included in the Carmean (1979) 

study but Dillabough’s (1983) study (Table 2 and Figure 

1—comparison 13) shows that bitternut hickory in 

southern Ontario grows exceptionally well on good sites.

Th e site index comparison models indicate four major 

hardwood site index groupings:

1. Low site index class. American beech 

consistently has much lower site indices than 

other associated hardwood species (Table 2 and 

Figure 1—comparisons 3, 15, 24) 

2. Medium site index class. Sugar maple, red 

maple, and yellow birch have similar site indices 

(Table 1 and Figure 1—comparisons 1, 2, 14) 

but each of these three species consistently 

have higher site indices than American beech 

(comparisons 3, 15, 24). However, when site 

indices for these three tree species are compared 

to site indices for more intolerant hardwood 

species such as American basswood, American 

Figure 3.—Site index comparison graph showing site 

index relations between groupings of northern hardwood 

forest species in northern Wisconsin and Upper Michigan 

(Carmean 1979). 
33

elm, white ash, black ash, black cherry, northern 

red oak, and white birch, we fi nd that they 

consistently have lower site indices than for the 

more intolerant hardwoods (Table 2 and Figure 

1; for sugar maple comparisons 1 to 13; for red 

maple comparisons 16 to 23; for yellow birch 

comparisons 25 to 32).

3. High site index class. Th is class includes several 

relatively intolerant hardwood species such 

as American basswood, American elm, white 

ash, black ash, black cherry, northern red oak, 

and white birch. Th ese more intolerant species 

have consistently higher site indices than sugar 

maple, red maple, and yellow birch, but have 

consistently lower site indices than the aspens 

(Table 2 and Figure 1:—for American basswood 

comparisons 4, 16, 25, 39, 40; for American 

elm comparisons 5, 17, 26, 46; for white ash 

comparisons 7, 19, 28; for black ash comparisons 

7, 19, 28, for black cherry comparisons 12, 21, 

30, 44; and for northern red oak comparisons 8, 

20, 29).

But trends sometimes diff er among these 

rapid-growing intolerant hardwood species. 

For example, white ash on very good sites has 

higher site indices than all other hardwood 

species except the aspens (Table 2 and Figure 

1—comparisons 34, 41, 47 to 50). In contrast, 

northern red oak and white birch on poor sites 

have higher site indices than all hardwood 

species other than the aspens (Table 2 and Figure 

1:—for northern red oak comparisons 38, 45, 

49, 51, 57 to 60; for white birch comparisons 

38, 45, 49, 57, 60). Th ese variations among 

species in the high site index class prompted 

separating these relatively intolerant hardwood 

species into four subgroups: (a) white ash; (b) 

American bassswood, American elm, and black 

ash; (c) northern red oak and white birch; and 

(d) black cherry.

4. Very high site index class. Th e aspens 

consistently have much higher site indices than 

all other associated hardwood species (Table 2 

and Figure 1—comparisons 10, 11, 23, 32, 39, 

46, 50 to 56, 58 to 62, 67, 73, 76, 78).

Multiple species comparison graphs also were constructed 

(Figures 4 to 7) illustrating site index diff erences between 

various hardwood and conifer species in the Upper Great 

Lakes area. Th ese multiple species comparison graphs are 

for illustrative purposes only and the actual paired species 

models and graphs (Table 2, Figure 1) are recommended 

for site index estimation purposes.

Site Index Comparisons for the 

Aspens

We expanded on the results from the earlier northern 

hardwood study (Carmean 1979) with further details 

(Carmean and Hahn 1981) about site index relations 

between trembling aspen and bigtooth aspen as well as 

relations between the aspens and northern hardwood 

and conifer species. Site index comparisons between the 

aspens showed that bigtooth and trembling aspen have 

similar site indices for all levels of site index (Table 2 and 

Figure 1—comparison 61). Trembling aspen consistently 

have higher site indices when compared to balsam poplar 

(Table 1 and Figure 1—comparison 62). Both bigtooth 

and trembling aspen consistently have higher site indices 

when compared to other hardwood species at all levels of 

site index (Table 2 and Figures 1, 5, and 6).

Comparisons between the aspens and conifer species also 

shows that the aspens consistently have higher site indices 

than the conifers (Table 2 and Figure 1—comparisons 

67, 73, 76, 78; Figure 7). However, only a few of those 

comparisons have aspen site indices less than 40 feet. 

Reasons for this lack of poor-site aspen plots are indicated 

in studies for northwest Ontario where few merchantable 

trembling aspen stands occur on poor sites such as dry 

sands, shallow to bedrock morainal soils, or poorly 

drained soils (Carmean 1996, Carmean and Li 1998, 

Carmean et al. 2006). Trembling aspen may regenerate 

on these poor sites but defect and early “stand breakup” 

occurs, thus few older merchantable aspen stands are found 

on such poor sites. For relatively poor sites, bigtooth 

aspen and white birch have similar site indices, but on 

good sites bigtooth aspen has much higher site indices 

than white birch (Table 2 and Figure 1—comparison 

59). Likewise for relatively poor sites, trembling aspen 

and jack pine have similar site indices but for better sites 

trembling aspen site indices are higher than jack pine site 

indices (Table 2 and Figure 1—comparison 67; Figure 7).
34

Figure 4.—Multiple species site 

index comparison graph for 

conifer tree species in the Upper 

Great Lakes area. This graph was 

constructed using models 5, 69, 

70, 75 and 77 (Table 2).

Figure 5.—Multiple species site index comparison 

graph for trembling aspen, white birch, northern 

red oak and American basswood in the Upper 

Great Lakes area. This graph was constructed 

using models 40, 54 and 58 (Table 2).
35

Figure 6.—Multiple species 

site index comparison 

graph for bigtooth aspen, 

white birch, northern red 

oak and sugar maple in 

the Upper Great Lakes 

area. This graph was 

constructed using models 

11, 55 (Table 2).

Figure 7.—Multiple species site 

index comparison graph for 

trembling aspen, jack pine, red pine, 

white pine, black spruce and white 

spruce in the Upper Great Lakes 

area. This graph was constructed 

using models 67, 73, 76 and 78 

(Table 2).
36

Site Index Comparisons for Oak 

Species

Comparisons for oaks and yellow-poplar are summarized 

for the Central States (Carmean and Hahn 1983). 

Results from this northern study are similar to the 

Central States study where we show that northern red 

oak consistently has higher site indices than white oak 

(Table 2 and Figure 1—comparison 53). Northern red 

oak usually has lower site index than the aspens (Table 2 

and Figure 1—comparisons 54, 55), but has higher site 

indices than sugar maple, red maple, and yellow birch 

(Table 2 and Figure 1—comparisons 8, 20, 29, 87).

Site index comparisons for conifers

Tamarack consistently has much higher site indices than 

other conifers (Table 2 and Figure 1—comparisons 66, 

75, 82; Figure 4). In contrast, northern white cedar 

consistently has much lower site indices than the other 

conifers (Table 2 and Figure 1—comparisons 77, 80, 82; 

Figure 4). We found that site indices are relatively similar 

for jack pine, red pine, white pine, black spruce, and 

white spruce (Table 2 and Figure 1—comparisons 65, 

65, 69). Norway spruce plantations in southern Ontario 

consistently has higher site indices than white spruce 

plantations (Table 2 and Figure 1—comparison 79); 

excellent growth for Norway spruce is indicated by site 

index curves for Norway spruce plantations in southern 

Ontario (Gordon et al. 1989), and in central New York 

(Jokela et al. 1988).

YIELD AND VALUE COMPARISONS

Th e six site index comparison studies summarized in this 

report have produced a wealth of information comparing 

site index relations among 24 hardwood and conifer 

species in the Upper Great Lakes area. Th is information 

when combined with yield tables, yield models, and 

product value estimates will assist in deciding which 

tree species is most productive and economically more 

desirable for management on forest lands having diff erent 

levels of site index. However, we should recognize that 

site index comparisons are only comparisons of dominant 

and codominant tree heights at 50 years. Th erefore 

estimating site index is only the fi rst step for determining 

the most productive and commercially valuable tree 

species for each site; the next step should be using these 

site index estimates to enter yield tables and yield models 

for estimates of potential yield and potential product 

values for alternative tree species at various ages as well as 

yields and product values at diff erent levels of site index.

Site index (tree height) comparisons, while indicative of 

potential yield diff erences, also should be accompanied 

by yield and product value comparisons for each species 

at diff erent levels of site index. For example, Table 2 

and Figure 1, comparison 64, indicate that jack pine has 

slightly higher site index than red pine. However, when 

site index estimates for jack pine and red pine are related 

to yield tables (Plonski 1974), we fi nd that red pine has 

much greater yield than jack pine at the same level of site 

index. Th e reason for this much greater yield is that fully 

stocked red pine stands have much higher basal areas than 

fully stocked jack pine stands (Alban 1978). Red pine 

also is longer-lived than jack pine thus red pine maintains 

height, diameter, and basal area growth better than jack 

pine. Th erefore, yield diff erences would be even greater 

when yield comparisons are made between red pine and 

jack pine at older ages (Carmean and Th rower 1995, 

Lundgren 1982).

Comparisons of product values also favor red pine 

because older red pine stands on good sites usually have 

considerable volume in valued saw logs, veneer logs, cabin 

logs, and utility poles while, in contrast, older jack pine 

stands usually have smaller volumes of these valuable 

products. Accordingly, product value comparisons also 

are needed in addition to tree height (site index) and yield 

comparisons. Th us tree species that can produce valuable 

veneer and saw logs might be preferred on certain sites 

even though height, site index, and biomass yield might 

be less than the site index and yields produced by rapid 

growing short-lived species such as aspen that are utilized 

mostly for less valuable pulp and fi ber.

Tree height and volume growth before and after site 

index age also should be compared. Certain short-lived 

species such as the aspens may grow rapidly in early years, 

thus at 50 years (site index age) are usually taller and 

stands have greater volumes when compared to stands of 

longer-lived species that have slower early height growth 

such as red pine and white pine. But red pine and white 
37

pine maintain height, diameter, and volume growth and 

eventually these species will be taller and will have more 

volume and greater values than aspen. Accordingly, these 

pines will have higher site indices, greater yields, and 

greater values than aspen if 100 years was used as site 

index age rather than 50 years.

We now have the means for developing comparative yield 

and comparative value models for alternative tree species 

growing on diff erent sites. Comparative models based 

on site index, yield, and commercial value can provide 

tools for determining which species of tree is the most 

productive and commercially desirable for each level of 

site quality in the Upper Great Lakes area.

LITERATURE CITED

Alban, D.H. 1978. Growth of adjacent red and jack 

pine plantations in the Lake States. Journal of 

Forestry. 76: 418-421.

Alban, D.H. 1985. Volume comparison of pine, 

spruce, and aspen growing side by side. Res. 

Note NC-327. St. Paul, MN: U.S. Department of 

Agriculture, Forest Service, North Central Research 

Station. 6 p.

Carmean, W.H. 1975. Forest site quality evaluation in 

the United States. Advances in Agronomy. 27: 209-

269.

Carmean, W.H. 1978. Site index curves for northern 

hardwoods in northern Wisconsin and upper 

Michigan. Res. Pap. NC-160. St. Paul, MN: U.S. 

Department of Agriculture, Forest Service, North 

Central Research Station. 16 p.

Carmean, W.H. 1979. Site index comparisons among 

northern hardwoods in northern Wisconsin and 

upper Michigan. Res. Pap. NC-169. St. Paul, MN: 

U.S. Department of Agriculture, Forest Service, North 

Central Research Station. 17 p.

Carmean, W.H. 1996. Site-quality evaluation, sitequality maintenance, and site-specifi c management 

for forest land in northwest Ontario. Tech. Rep. 

TR-105. Th under Bay, ON: Ontario Ministry of 

Natural Resources, Northwest Science and Technical 

Unit. 121 p.

Carmean, W.H. 2007. Intensive plantation 

management for good-site forest land in northwest 

Ontario. Forestry Chronicle. 83(1): 41-53.

Carmean, W.H.; Hahn, J.T. 1981. Site index 

comparisons for Lake States forest species. St. 

Paul, MN: U.S. Department of Agriculture, Forest 

Service, North Central Forest Experiment Station. 

Unpublished FREP report on fi le at the National 

Forest Service LIbrary, Fort Collins, CO; www.fs.fed.

us/library/

Carmean, W.H.; Hahn, J.T. 1983. Site comparisons 

for upland oaks and yellow-poplar in the Central 

States. Journal of Forestry. 81: 736-739.

Carmean, W.H.; Hahn, J.T.; Jacobs, R.D. 1989. Site 

index curves for forest species in the eastern United 

States. Gen. Tech. Rep. NC-128. St. Paul, MN: U.S. 

Department of Agriculture, Forest Service, North 

Central Research Station. 142 p.

Carmean, W.H.; Hazenberg, G.; Deschamps, K.C. 2006. 

Polymorphic site index curves for black spruce and 

trembling aspen in northwest Ontario. Forestry 

Chronicle. 82(2): 231-242.

Carmean, W.H.; Li, Y. 1998. Soil-site relations for 

trembling aspen in Northwest Ontario. Northern 

Journal of Applied Forestry. 15(3): 146-153.

Carmean, W.H.; Niznowski, G.P.; Hazenberg, G. 2001. 

Polymorphic site index curves for jack pine in 

northern Ontario. Forestry Chronicle. 77(1): 141-

150.

Carmean, W.H.; Th rower, J.S. 1995. Early height 

growth and site index for planted red pine in 

North Central Ontario. Northern Journal of Applied 

Forestry. 12(1): 23-29.
38

Carmean, W.H.; Vasilevsky, A. 1971. Site index 

comparisons for tree species in northern Minnesota.

Res. Pap. NC-65. St. Paul, MN: U.S. Department of 

Agriculture, Forest Service, North Central Research 

Station. 8 p.

Dillabough, B.V. 1983. Site index comparisons among 

northern hardwood and softwood tree species in 

southern Ontario. Th under Bay, ON: Lakehead 

University, School of Forestry. 62.p. H.B.Sc. thesis. 

On fi le at Lakehead University Library.

Gordon, A.M.; Williams, P.A.; Taylor, E.P. 1989. 

Site index curves for Norway spruce in southern 

Ontario. Northern Journal of Applied Forestry. 6: 

23-26.

Homagain, K.; Shahi, C.K.; Carmean, W.H.; Leitch, M.; 

Bowling, C. 2011. Growth and yield comparisons 

for red pine, white spruce and black spruce 

plantations in northwestern Ontario. Forestry 

Chronicle. 87(4): 494-503.

Jokela, E.J.; Jack, S.B.; Nowak, C.A. 1988. Site index 

curves for unthinned Norway spruce plantations in 

New York. Northern Journal of Applied Forestry. 5: 

251-254.

Little, E.L., Jr. 1953. Check list of native and 

naturalized trees of the United States (including 

Alaska). Agric. Handb. 41. Washington, DC: U.S. 

Department of Agriculture, Forest Service. 472 p.

Lundgren, A.L. 1982. Can red pine in the Lake States 

out produce loblolly and slash pine in the South?

In: Proceedings. Artifi cial regeneration of conifers 

in the Upper Great Lakes Region; 1982 October 

26-28; Green Bay, WI. Houghton, MI: Michigan 

Technological University: 377-344.

Lundgren, A.L.; Dolid,W.A. 1970. Biological growth 

functions describe published site index curves for 

Lake States timber species. Res. Pap. NC-36. St. 

Paul, MN: U.S. Department of Agriculture, Forest 

Service, North Central Research Station. 9 p.

McClain, K.M.; Morris, D.M.; Hills, S.C.; Buse, L.U. 

1994. Th e eff ects on initial spacing on growth and 

crown development for planted northern conifers: 

37-year results. Forestry Chronicle. 70(2): 174-182.

Ortiz, R.W. 1985. Site index comparisons among 

jack pine, black spruce, trembling aspen in 

northwestern Ontario. Th under Bay, ON: Lakehead 

University, School of Forestry. 59 p. H.B.Sc. thesis. 

On fi le at Lakehead University Library.

Plonski, W.L. 1974. Normal yield tables (metric) for 

major forest species of Ontario. Toronto, ON: 

Ontario Ministry of Natural Resources, Division of 

Forestry. 40 p.

Schlaegel, B.E. 1975. Yield of 40-year old conifers and 

aspen in adjacent stands. Canadian Journal of Forest 

Research. 5: 278-280.

Th urston, D.L. 1984. Site index comparisons among 

boreal species in the north central region of 

Ontario. Th under Bay, ON: Lakehead University, 

School of Forestry. 43 p. H.B.Sc. thesis. On fi le at 

Lakehead University Library.

U.S. Department of Agriculture. 1975. Soil taxonomy.

Agric. Handb. 436. Washington, DC: U.S. 

Department of Agriculture, Soil Conservation Service. 

754 p.
39

APPENDIX I.

Scientifi c and common names of tree species (Little 1953)

Scientifi c name Common name

Abies balsamea (L.) Mill.

Acer rubrum L.

Acer saccharum Marsh.

Betula alleghaniensis Britton

Betula papyrifera Marsh.

Carya cordiformis (Wangenh.) K. Koch

Fraxinus americana L.

Fraxinus nigra Marsh.

Larix laricina (Du Roi) K. Koch

Liriodendron tulipifera

Picea abies (L.) Karst.

Picea glauca (Moench) Voss

Picea mariana (Mill.) B.S.P.

Pinus banksiana Lamb.

Pinus resinosa Ait.

Pinus strobus L.

Populus balsamifera L.

Populus grandidentata Michx.

Populus tremuloides Michx.

Prunus serotina Ehrh.

Quercus alba L.

Quercus rubra L.

Th uja occidentalis L.

Tilia americana L.

Ulmus americana L.

Balsam fi r

Red maple

Sugar maple

Yellow birch

White birch

Bitternut hickory

White ash

Black ash

Tamarack

Yellow-poplar

Norway spruce

White spruce

Black spruce

Jack pine

Red pine

Eastern white pine

Balsam poplar

Bigtooth aspen

Trembling aspen

Black cherry

White oak

Northern red oak

Northern white cedar

American basswood

American elm

Printed on Recycled Paper

Carmean, Willard H.; Hahn, Jerold T.; McRoberts, Ronald E.; Kaisershot, D. 2013. 

Site index comparisons for forest species in the Upper Great Lakes area of 

the United States and Canada. Gen. Tech. Rep. NRS-113. Newtown Square, 

PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. 

39 p.

This report summarizes six studies that compare site index relations between 24 

hardwood and conifer species in the Upper Great Lakes area of the United States 

and Canada. These six studies have many regression models and graphs for 

comparing site index between forest species thus providing tools for estimating site 

index for alternative tree species based on direct site index measurements using tree 

species actually present in forest stands. Thus the objective of this summary paper is 

to summarize these models so that we can provide the most accurate tools available 

for estimating the tree species that are most productive and economically valuable 

for management on each forest site.

KEY WORDS: height growth, predicting most productive tree species

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