Table Of ContentGreatBasinNaturalist54(2),©1994,pp. 177-181
NEEDLE BIOMASS EQUATIONS FOR SINGLELEAF PINYON
ON THE VIRGINIA RANGE, NEVADA
T. R. De Rochei-i and R.J. Tausch2
Abstract.—Foliar biomass ofsingleleafpinyon {Pinus monophylla Torr. & Frem.) was estimated on the Virginia
Mountains, Nevada,basedontheeasilymeasureddimensionsofcrownvolumeandsapwoodarea. Leafbiomassestima-
tion techniques used in other studies ofpinyonwhere total leafbiomass was collectedwere supported. Both sapwood
area (cm^) andcrownvoliune, calculated as one-halfofan ellipsoid (m'^), were found tobe significantly related to total
dn,'weightneedlemass (g). Bestpredictiveequationsforcrownvolumewereobtainedwithnonlinearregressionanaly-
sis. Apreviouslvreportedtwo-partrelationshipbasedontreesizeforpredictingneedlebiomasswithsapwoodareawas
supported. Foliarbiomassofsingleleafpinyoncanbeaccuratelyestimatedwithaminimumof10sapwoodcores.
Keywords:singleleafpinyon,foliagebiomass,sapwoodarea,biomassprediction.
In recent years land managers trying to ful- on a tree is strongly related to the area ofcon-
fill the goal of multiple use have needed to ducting tissue transportingwater and nutrients
ascertain the potential value and use ofpin- to these tissues. This relationship has been
yon-juniper woodlands extending over 17 mil- found for many conifers (Grier and Waring
lion ha across the Rock\' Mountain and Great 1974, Kaufmann and Troendle 1981, Marchand
Basin regions (Chojnacky 1986). Singleleaf 1984, Miller et al. 1987), including pinyon
pinyon and Utahjuniper (Juniperus osteosper- (Tausch and Tueller 1989). Survival oftrees in
ma Little) woodlands cover more than 6 mil- arid environments demands efficiency, and
lion ha in the Great Basin alone (Tausch and production of excess xylem and associated
Tueller 1990). This forest type has historically supporting tissue would waste precious
supplied fuelwood, charcoal, nuts, fence posts, resources. Alternately, insufficient develop-
and poles (Fogg 1966), especially during ment of conducting tissue would dehydrate
heightened mining activity in the late 1800s and starve atree. Also, as atree grows, its mass
(Budy andYoung 1979). Pinyon-juniperforests and the spatial volume it inhabits expand in a
also provide essential areas for wildlife habitat nonlinearfashion (Tausch andTueller 1988).
(McCulloch 1969, Short and McCulloch 1977, Many studies have shown close relation-
Balda and Masters 1980). Balancing out these ships between whole-tree phytomass and easi-
benefits is the nearly complete loss offorage ly measured plant dimensions (Budy et al.
and potential increased soil erosion resulting 1979, Milleret al. 1981, Gochran 1982, Hatch-
from the establishment of this species ell et al. 1985, Tausch and Tueller 1989, 1990).
(Doughty 1987). Measuring needle mass of entire singleleaf
&
Estimates ofbiomass are essential to most pinyon {Piniis monophylla Torr. Frem.) trees
studies ofplant community competition, suc- through harvest can be inefficient and expen-
cession, and resource allocation including sive (Meeuwig and Budy 1979), especially on
studies of pinyon-juniper woodlands. Total large trees in remote areas. The ability to
foliar biomass, or phytomass, can be vital to accurately estimate phytomass based on sim-
assessment ofplantwater-use efficiency (Long ple allometric measurements can greatly ease
et al. 1981, Waring 1983), nutrient cycling the process. Cross-sectional sapwood areas for
(Waringand Running 1978), soil moisture con- pinyon pine can be estimated with a high
ditions (Grier and Running 1977), the hydro- degree ofaccuracy using increment cores and
logic environment (Nemani and Running trunk diameter measurements (Whitehead
1989), andcompetitive interactions (Tausch and 1978, Tausch 1980). Equations generated by
Tueller 1990). The amount of foliage biomass these procedures can apparently vary for this
'DepartmentofRange,WildlifeandForestry,Universit>'ofNevada-Reno,Reno,Nevada89512.
2U.S.DepartmentofAgriculture,ForestService,IntermountainForestandRangeExperimentStation,Reno,Nevada89512.
177
178 Great Basin Natuiulist [Volume 54
species depending!; on location in the Great in the canopy with increasing age. Error can
Basin (Tausch and Tueller 1988). Develop- be introduced in needle biomass estimation
ment and refinement oftechniques to acquire based on crown volume calculated fi^om sim-
reliable mensurational data will only enhance ple canopy dimensions without an estimate of
the further study, understanding, and proper the voided space. This study incorporated a
management of pinyon-juniper woodlands. grid method of determining average canopy
The objective of this study was to apply density similar to the method proposed by
evolved methods of estimating whole-tree Belanger and Anderson (1989). The procedure
needle biomass to singleleafpinyon on a third involved viewing each sampled tree canopy
Great Basin site. through a 6 X 60-cm Plexiglas sheet that had
a 3-cm2 grid transposed onto it. A perspective
Methods was chosen that approximated an average of
canopy fullness that was sufficiently distant to
Study Area visually contain the entire tree height within
Research was conducted on USDI Bureau the vertically held grid when viewed at arm's
of Land Management pinyon-juniper wood- length. First, the left upright edge ofthe grid
lands 32 km SE ofReno, Nevada (39°17'30"N, was then aligned with the trunk and the
119°42'30"W). The study site lies at 1963 m canopy height centered within the grid. This
elevation in a near level east-west saddle placed the grid over the right side ofthe tree.
formed between a basalt plug and the west- Within the grid a smooth canopy border was
facing slope of the Virginia Mountains. Soils imagined as if a ribbon were stretched from
are 0-10 cm deep and poorly developed from the top along the outside edge ofthe canopy
decomposed Cretaceous granodiorite and to the base. Next, grid squares more than half-
Pliocene-Pleistocene volcanics. This area way within this perimeter line were counted
receives approximately 336 mm of precipita- for the maximum area covered by the canopy.
tion annually (Desert Research Institute Last, squares within the perimeter covered by
1991), mostly as snow. Some Utah juniper >50% foliage (versus open space, trunk, or
occurs in the area, but singleleafpinyon is the branches) were counted. Dividing the number
dominant tree species. offoliage-covered squares by the total number
ofsquares within the canopy perimeter deter-
Field Techniques mined a ratio ofrelative canopy density. This
procedure was then repeated by placing the
Tree selection procedures were based on
the five maturity classes described in Black- grid overthe left side ofthe tree canopy.
burn and Tueller (1970). Ten trees from each Following crown measurements and esti-
maturity class were randomly selected for mation ofcanopy density, all green foliage was
potential measurement within relationships of harvested by cutting offbranches and placing
accessibility associated with placing potome- them in feed bags. After being air-dried, the
ters for tree water-use studies (De Rocher needles were dried at 80°C for24 h to achieve
1992). Five trees from each maturity class consistency and then weighed. A trunk cross
were randomly selected for a total of25 trees section was also cut approximately 15 cm
to be measured and harvested. Total tree above the root crown. These cross sections
height (cm), canopy height (cm), maximum were measured for sapwood area (cm^) usinga
canopy diameter and canopy diameter per- paper trace, which was cut into small pieces
pendicular to the maximum (cm), and trunk and run through a model LI-3100 leaf area
circumference (cm) at approximately 15 cm meter (LI-COR, Inc., Lincoln, Nebraska).
above the root crown were determined for all
Analysis Techniques
trees.
Past studies have shown that includingesti- Longest crown diameter, diameter peipen-
mates ofcanopy density improves predictabil- dicular to it, and crown height for each tree
ity ofneedle biomass (Miller et al. 1981), but were used to compute the crown volume (ni"^)
visual estimates used were not easily compa- based on the formula for one-halfofan ellip-
rable between studies. Canopy needle bio- soid (Tausch 1980, Beyer 1984). Crown vol-
mass density decreases as voids develop with- ume was also adjusted for canopy density by
1994] SiNGLELEAF PiNYON BlOMASS EQUATIONS 179
Table 1. Singleleafpinyonfoliarmasspredictionmodelsusingsapwoodareaandcrownvolumeapproximatedasone-
halfofanellipse.
Standarderror
Relation Equation R2 ofestimate
Linearregression
Needlevs.sapwood Y = 265.3 + 122.IX .977 4059
Mass(g) Area(cm^)
(Allmaturityclasses)
Needlevs.sapwood Y =-142.5 + 106.4X .947 227
Mass(g) Area(cm^)
(Trees <40cm2sapwood)
Needlevs.sapwood Y = 3234.7+ 117.4X .971 6822
Mass(g) Area(cm^)
(Trees >40cm2sapwood)
Logtransformedlinearregression
Needlevs.sapwood InY : 35.31 + 1.24lnX .782 16,886
Mass(g) Area(cm-)
(Allmaturityclasses)
Needlevs.sapwood Inv = 33.9 + 1.37lnX .973 194
Mass(g) Area(cm-)
(Trees <40cm2sapwood)
Needlevs.sapwood InY= 186.5 + 0.94lnX .970 6453
Mass(g) Area(cm^)
(Trees >40cm^sapwood)
Nonlinearregression
Needlevs.sapwood Y = 181.4X0-94 3847
Mass(g) Area(cm^)
(Allmaturityclasses)
Needlevs.sapwood Y = 20.1X1-497 .995 83
Mass(g) Area(cm^)
(Trees <40cm2sapwood)
Needlevs. sapwood Y = 194.4X0929 .970 6444
Mass(g) Area(cm^)
(Trees >40cm2sapwood)
Needlevs.ellipsoid Y = 2.34X0-58 .976 5643
Mass(g) Volume(m^)
(Allmaturityclasses)
Needlevs.ellipsoid Y = 1.36X0-62 .977 5459
Mass(g) Volume(m-'^)
(Adjustedforcanopydensity)
(Allmaturityclasses)
multiplying the calculated volume by the the original untransformed data (Tausch and
canopy density ratio. Two types ofregression Tueller 1988), and the best fit results are
analyses were used to evaluate relationships reported. Comparisons among regression
between oven-dryfoliage weight and sapwood results were made using highest coefficients
area and crown volume. Prediction equations of determination (R^) and lowest standard
utilizing any form of data transformation to error of the estimate values, to a level of sig-
linearize the data for least-squares analysis nificance of p < .01 for the least-squares
were repeated usingnonlinearregression with analyses results.
180 Great Basin Naturalist [Volume 54
Results and Discussion (Tausch and Tueller 1989), application ofnon-
linearregression analysis produced the best fit
The amount of foliage supported per unit between phytomass and all tree dimensions,
area of conducting tissue ranged from 37.4 g as reflected by increased coefficient ofdeter-
cm-2 for the smallest tree to 157.2 g cm"^ for mination values and reduced standard errors
one ofthe largest, and averaged 88.8 g cm~2 ofthe estimate overotherregression methods.
for all sampled trees. Using a nonlinear Estimates of singleleaf pinyon phytomass
regression techni(|ue that iteratively approxi- for hx'drological and ecological studies ofpin-
mates optimal fit without data transformation yon-juniperwoodlands canbe most accurately
provided as tight afit to the full data set as lin- obtained from a minimum of10 sapwood area
ear regression utilizing log-transformed data measurements. Canopy dimensions and an
in relating dried needle mass and sapwood assessment offoliage density can also be used
area. Reapplication of untransformed data to to reliably estimate whole-tree phytomass.
linear models decreased the relationship This study, conducted on the western edge of
(Table 1). For trees with <40 cm^ sapwood the Great Basin, achieved needle biomass
area (maturity classes 1-3), this relationship regressions based on sapwood area that were
was definitely nonlinear, as was observed by nearly identical to those from work performed
Tiiusch and Tueller (1989). The slope of the in southwestern Utah. Future research should
linear regression line for these western Neva- concentrate on comparing numerous isolated
studies across the Great Basin ofwhole-tree
da data is nearly identical to the slope for
pinyon from southwestern Utah (Tausch foliar mass hanest so that a regional biomass
equation maybe developed.
1980), suggesting a potential singular relation-
ship across the Great Basin. For both these
Acknowledgments
data and the Tausch 1980 southwestern Utah
data, the entire foliage was harvested from This researchwas supportedinpartbyftmds
each tree. A similarrelationship was notfound provided by the Intermountain Research
between data from Tausch 1980 and Tausch Station, Forest Service, U.S. Department of
and Tueller 1989. Tausch and Tueller (1989)
Agriculture.
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characteristics inthe SweetwaterMountains. USDA Accepted4November1993
