WATER RESOURCESRESEARCH,VOL. 30, NO. 1, PAGES1-9, JANUARY 1994
A water usemodelfor locatingthe boreal/deciduous
forest
ecotone in eastern North America
Lelani
L. Arris
GlobalActionand InformationNetwork, SantaCruz, California
Peter S. Eagleson
Department
of CivilandEnvironmental
Engineering,
Massachusetts
Institute
of Technology,
Cambridge
Abstract. A modelis developedfor predictingthe locationof majorvegetation
ecotonesin easternNorth America.The modelis baseduponthe interactionof plant
physiologicalcharacteristics,climate, and soil in order to be useful as an interactive
boundaryconditionin atmospheric
generalcirculation
models.The modelrepresents
the relativecompetitive
abilityof differentvegetation
typesby theirannualnet primary
productivityas expressed
throughwateruse.At any givenlocation,the vegetationtype
with the highestproductivity is assumedto be dominant. Ecotonesare located where
competitivedominanceshiftsfrom one vegetationtype to another.Productivityis
computedas a functionof annualevapotranspiration,
whichis a functionof the length
of the growingseason,photosynthetic
capacity,potentialevapotranspiration,
and soil
moistureavailability,amongotherthings.When consideringthe coniferous
boreal/deciduous
forestecotone,it is foundthatinherentphysiological
differences
betweenconifersand deciduous
treesleadto differences
in productivitywhichare
relatedprimarilyto temperature.The modelpredictsa reversalof deciduous/coniferous
productivedominanceat the latitude of the observedecotone;that is, within the
transitionzone of mixedforest.The productivitymodeldoesnot adequatelyexplain
the existenceof the deciduous/southern
pineecotone.Soil chemistryapparentlyplaysa
role in the determinationof this boundary.
introduction
important validating test of general circulation models. Existingknowledgeof these transitionsis primarily in the form
Large-scale numerical models of coupled atmospheric, of empirical correlations of primary vegetation formations
ocean, and land surface dynamicsare seen as a primary with variables such as temperature and precipitation[e.g.,
mechanismfor increasingour understandingof the global Mather and Yoshioka, 1968; Whittaker, 1975] and water
climate systemand for predictingwhat changesare likely in deficit [Stephenson,1990]. While these relationshipsmay
the future. Characterizationof the dynamicbehaviorof land provide some cluesto the underlying physical mechanisms,
surfaceprocesses,includingvegetationcover, is essentialif they are important ecologically only indirectly throughtheir
these modelsare to accuratelymimic the real systems.One effect on the competitivenessof plants [Walter and Breckle,
important parameter in these interactionsis the type of 1985, p. 159].
vegetation at any given location on the continents. Different
At the other extreme are models which "grow" individual
types of vegetation may have quite different heat and mois- plants and chart the changes in vegetation systems over
ture flux characteristics[e.g., Kramer, 1983, chapter 11], many generationsof plants [e.g., Shugart, 1984]. Although
and will thereby have different effects on the climatic sys- these models have been quite successfulin simulatingcurtem. Furthermore, the responseof variousvegetationtypes rent conditionsand could undoubtedly aid in the prediction
to changesin climate is very poorly understoodand is of of future distributionsas well, they are limited by a lack of
critical importance.For long-rangepredictionsof climatic physiologicalrealism.
change,the modelsshouldincludean interactivevegetation
Our approachattemptsto provide a simpleformulationof
component such that global vegetation distributionsshift as
physicalmechanismsthat can explain the observedheat and
climate changes.
moisture limits to primary vegetation formations at the
In studyingthe responseof vegetationto climate, it is
helpfulto look at ecotones,the transitionsseparatingdifferent biomes (i.e., differentplant formations).Figure 1 (redrawn from Eyre, I968, Appendix I, map five) illustrates
these ecotonesin eastern North America. Becausethey
regional
scale(say,104 km2)resolved
bygeneral
circulation
Copyright1994by the AmericanGeophysical
Union.
models.We beginwith a successionof postulatesasfollows:
(1) Relationshipsbetween plant types at a givenlocationare
competitive. (2) Competitive dominanceresults from the
ability of one vegetationtype to out produceall other types
at a givenlocation.(3) Net primary production(NPP) (both
above and below ground), rather than grossprimary production, is the important quantity in determiningcompetitive
Paper number 93WR02746.
0043-1397/94/93
WR-02746505.00
the rate of net primary production.
represent marginal conditions, ecotones will be sensitive to
changingclimate,thuspredictingtheir currentlocationis an
advantage.(4) Canopy transpirationrate is a surrogatefor
2
ARRIS AND EAGLESON'
LOCATING
THE BOREAL/DECIDUOUS
F()REST
EC(YI'()NE
TUNDRA
BOREAL FOREST
48ø
MIXED
FOR ES
DECIDUOUS
FOREST
.,
APPROXIMATE NORTHERN
LIMIT OF FLORIDAN
AQUIFER
SYSTEM
BROADLEAVED
;"t'•'
•,•,,,u 300 600
EVERGREEN
FOREST
Figure 1. Forest formationsof Eastern North America (map from I,itth, [!97! t' vegetationboundaries
from Eyre [!968]; aquifer boundaryfrom Sun and Weeks[19911).
With these assumptionsour approachis limited to those
situationsin which a water use model of productivityis
adequateand appliesequally to each of the competitors.
Exceptionsto thisare probablynumerousincluding(but not
limited to) locationswhere soil chemistry,fire, or pests
selectivelylimit productivity.
We limit our studyto one of the two major vegetation
functionof the typeof photosynthetic
processemployedby
the plant{i.e., C 3, (7 4, •n'(i:AM} and of the percentageof
gross productionwhich is consumedby respiration. All
temperatefore,,ttree speciesuseC 3 photosynthesis.
Annual
Transpiration
E-r•
ecotones in eastern North America, the transition from
Transpiration
is periodicat the daily scaleaccordingto the
evergreen (coniferous) boreal to deciduous fl.)rest, as is
shown in Figure 1.
availabilityof light, and this oscillationis modulatedseason-
ally according(primarily)to temperature.In estimatingthe
annual
totaltranspiration
E.]awe will average
thediurnal
variationfor eachday and sumtheseaveragesover all the
Model of Net Primary Productivity
daysof the year. Analytically, this is
We use the last of thesepostulatesto write the annualnet
primaryproductivityof a closedcanopy:
NPP= aETaM
365
E'i'•= "ZEr,Cif(Li)
(1)
whereNPPisthenetprimaryproductivity
(gdryweightm-2
(2)
-2
whereET,isthetotaltranspiration
duringdayi (g H20 m
land)d-I); L is the leafareaindex(m2 (leafarea)
(land)yr-•); a isthewateruseefficiency
ofproduction
(g (canopied
land));f(L i) is canopyfunction;
andthe
dryweight
g-• H20transpired);
Eraistheactual
evapo-m"2 (canopied
transpiration
(g H20 m-2 (canopied
land)yr-•); andM is temperature-dependent
seasonalmodulatoris Ci, photosyncanopy
density
(m2 (canopied
land)m-2 (land)).
thetic capacity (0 -< C • I). Definition of these factors
CanopyDensityM
follows.
TranspirationRate Er.
Complex modelsexist for esti-
Thefractionoflandsurfaceshaded
bythecanopy
withthe matingthe transpiration
rate Er of (2) as a functionof plant
Sunat the zenithis M, the canopydensity.For M = I the physiologyand the environmentalforcing [e.g., Sellerset
canopyis saidto be "closed."Canopydensityis a function al., 1986;Dickinsonet al., 1986].In their completeform
of climate, soil, and the water use characteristicsof the thesemodelscontaina large numberof parametersto be
plantscomposing
the canopy[Eagleson,1978].
estimatedfor each application.Their simplified,genetic
form
is illustratedby the so-called"big leaF' or "single
Water Use Efficiencyof Productiono•
source" canopyrepresentationshown in Figure 2 as given
Thewateruseefficiency
of productivity
a is defined
by by Dickinson[1992,p. 140].In this diagramRn is the net
Larcher[1983]astheamount
of drymatterproduced
per radiation,q is the water vapor mixing ratio, T is tempera-
unitof watertranspired.On an annualbasis,itsvaluecanbe ture, u is the windspeed,r is the (equivalent)resistance,and
assumed
to be relativelyconstant
for a givenspecies.
It is a the subscriptsa and c refer to atmosphereand canopy,
ARRIS AND EAGLESON:
LOCATING
THE BOREAL/DECIDUOUS
canopy. Point a in the atmosphere is located at "screen
height" abovethe canopy. It is commonlyassumedthat the
separate atmosphericresistancesr a to the flux of water
vapor and of heat are identical.
Monteith [1965] first employed this resistive model in his
derivation of the well-known Penman-Monteithequationfor
evaporative flux from a vegetatedsurface.This equationcan
be used in the manner of Shuttleworth [1979] to write
Er
--- = k •
1
1+
rc/r a
ECOTONE
3
F[n
respectively.The path on the left-handsiderepresentsthe
moistureflux, with c denotingcanopy(includingstomatal)
conditions).The path on the right-handsiderepresentsthe
heat flux, with c denotingsomeaveragelocationwithin the
E•,
FOREST
Ta'qa'U
ra
ra
,
(3)
1 +A/y
in which •/ = cp p/[(0.622),•],,k is the latent heat of
vaporization,
cp is the specificheatof atmosphere
at constant pressure,p is the atmosphericpressure, A is the slope
of saturated vapor pressure-temperaturecurve, and E•, is
the potential evaporation, under the given climatic conditions, from a referencecanopy (e.g., the "short greengrass"
of Penman [1948]in which the canopyresistancer c is zero.
The coefficient k depends upon plant species, canopy
structure, and the various climate and soil parameters(both
physicaland chemical)controllingthe plant's accessto light,
soil water, and nutrients. Climate dependenceof k resides
both in r,, through the dependenceof atmosphericresistance on wind speed [e.g., Brutsaert, 1982, p. 112), and in
A/y, which is a function of atmospherictemperature[Van
Bavel, 1966]. Speciesdependenceof k residesboth in ra,
through the dependence of the latter on the aerodynamic
roughnesscharacteristicsof the stand [e.g., Brutsaert, 1982,
p. 1!2), and in r c, through dependenceof the canopy
resistanceon canopy structure,and on the differingstomatal
responseto soil moisturestress,atmosphericcarbondioxide
concentration, atmospheric vapor pressure deficit, heat,
light, etc. [Monteith, 1973, chapter 12; Evans, 1963].
In short, this singlecoefficientincorporatesa multitudeof
climatic, biophysical,and biochemicalprocessesdetermining the evaporative efficiency of plant stands. For this
reason, k is of limited utility in describingand understanding
interspeciesdifferencesat small time and spacescales.For
the same reason, k, along with its partner M, may be
adequate(as well as practical)to describethe vegetallink
between climate and soil at the larger scales important to
climate modeling.
Agriculturalistscall k a "crop coefficient," and there is
considerable literature concerning its numerical value for
agriculturalplant andagriculturaltree species[e.g.,Doorenbos and Pruitt, 1977]. It takes on values 0 -< k -< 1 and may
vary over its full rangein a singleday accordingto the many
Figure 2.
p. 140].
Simple generic canopy model [Dickinson, 1992,
affected by temperature, whereas leaf color changeis primarily relatedto photoperiod,both of which are ultimatelya
function of latitude. Although conifers do not lose their
leaves during the winter, low temperatures can reduce or
completely prohibit photosynthesisand likewise transpiration [e.g. Parker, 1961;Pisek, 1973]. In addition, the physiological changes that northern species undergo in their
annualprocessof cold acclimationoften reducestheir photosyntheticcapacityeven during winter warm spells[Woodward, 1987]. Transpiration may also be prevented solely by
the physicalrestrictionof the water in the soil or in the tree
being frozen. This can also restrict the transfer of carbon
dioxide.
In general,for any givenplant at a specificseasonandtime
in its life cycle, there is some optimum temperatureat which
photosynthesiswill proceed at a maximum rate if other
factors such as light are not limiting. This optimum is
primarily related to the enzymatic steps involved in the
photosyntheticprocess and is not necessarilyconstant;it
may shift with the seasonsas the plant acclimatesto changing average temperatures. All of these considerationsare
accountedfor in the model by the photosyntheticcapacity
coefficient
C.
Multiple leaf layers. An importantcanopycharacteristic
is that of multiple, overlappinglayers of leaves.This characteristic is measuredby the species-dependent
leaf area
environmentalinfluenceson r a, r c, •, and % Sincesomeof indexL, which representsthe total (one-sided)areaof leaves
theseinfluencesarepoorlyunderstood
andmanyaredifficult per unit of canopy.It clearly hasan effecton productivityas
to quantify,agriculturalists
commonlyuse a singlevalueof formulated here: first, through the multiplicity of (varyingly
k, time-averagedover the growing season,to reflect the shielded)evaporatingsurfaces,it affectsE r, and second,
surfaces,it affectsthe
relativewater use of a given speciesat maturity. We follow throughthesesamephotosynthesizing
energy supply.
that simplificationhere for trees.
In this model we assumethat the steadystateeffectof L is
Photosynthetic
capacityC. Seasonalchangesaffectdaily
implicit
in k. The effectof changingL at the beginningand
E r by determiningthe length of the active photosynthetic
period, which is also the active transpiration period. In end of the deciduousgrowing seasonis describedby the
deciduoustrees, the timing of leaf emergenceis primarily canopy functionf(L).
4
ARRIS AND
EAGLESON'
LOCATING
THE BOREA!,/I)Ir:XtlI)[J()LJS
normal data tk)r the same time peri½)dFrom six Canadian
cities[Atmo,s'!•ht'ri•'
Environt•tent,¾er•'i•'t',1982a, b, c, d, e,
fl.
Thedatasetbeingusedtk)rthemodelrestrictstheoptions
tk)restimatingE z, to thosewhich use only air temperature
andother easilyobtainedc{)elticients.
The empiricalrelationshipof Hamon[I 961]watsselectedtk)rits simplicityand
ease of calculation. Hamoh'S equati{m, converted to metric
units for daily computation, is
Ef,'.....r3'2/•
•,
(61
whereEp is the potentialevapg•ration
(crnd •)'x = 9.7 x
10.....
2 {m3 cm d kg....
• h 2). y is the possible
amountof
sunshine
(h d •; andp, is thesaturated
vapordensity
at
(kg m '•1. 'l'he modelusesa
Figure 3. Hypotheticalrelationshipof net primaryproduc- meandaily air temperature
tivity and latitudefor two competingvegetationtypes,
routinemodifiedt?{m•("ttrtiattttd t'Jttgle.vott
]1982] to compute y f¾omlatitudeand time •f year. Saturatedvapor
densityis expressed
as a fkmctionof air temperature
only
usingstandardthermodynamic
pr:ocedures
[Roger.v.19791.
Ecotone Location
Assumingthat net productivityas represented
by NIPPis
an adequatesurrogatefor biomassproductionand hence
relative competitiveability (postulate3), we hypothesize
that the geographicalboundarybetweena monocultureof
type"a" vegetationandone of type "b" vegetationis found
1Iamon'x[ 19611
equationwas{•riginatlytk•rmulatedfor use
withmonthlyaverages,
whereasthe productivitymodeluses
daily data. A comparison
of Ifs, valuesc{m•putedby the
model with publishedevaporationdata [l"ttrt•.•'•,orthand
where
modelconsistently
underestimated
!q•,. ActualannualD'ee
(NPP), = (NPP)t,
(4)
as is ill'ustratedin Figure 3. From (1) and (2Jwe write
365
77tomp.vot,,
198.2;bktrtts•,ortht't •l., 19821showed that the
water surt•.tceevaporationwas clelerminedIk)r 1()9 stations
by multiplyingrecordedpan evap{•r•,lion[l"arttsworthand
IIu,np.von, 1982] by a coefficient {•btained tYom an atlas
[bk•rn.vwortlt
t,t al., 1982].'i'hescvalueswere comparedto
modelE•, computationslk)r the same stations,and a factor
NPPj(0;
= aikjM
j ''• QiiE,,,(4•)J)(Zi)(•
If,f{ actual)
!" ........................................................(7)
E,t,(
in which4' is the geographic
location(latitude,longitude,
WgtS
pR)ttcd:tgainstlatitude,and
elevation),jisthevegetation
typea or b, andi isthedayof wascomputed.Thist•rtGlOI'
a regression
analysiswas perti)rmed,whichproducedthe
the year.
relationship
To locatethe ecotonerequiressolving(4} and($} for 4,.
Valuesof C andE•, are computed
daily,whereas•, k, and
F ::'•0,92-.•.,
(},014, r 2 ::•:=
0.49
(8)
M arevegetation-specific
annualaveragevalues.The producto9kjM
• setstherelative
levelofNPPj,whilethefactors where• is latitude.All Et, valuescomputedby the Hamon
underthedailysummation
determine
itslatitudinal
gradient. [196!1methodon a dailybasiswereadjustedby thisfactor.
Estimation of Model Parameters
This sectionprovidesa summaryof the methodsusedto
CanopyFunctionf(L)
The canopyfunction.[•L) describesseasonal
changes
in
the evaporating
surface.Accordingly,l•orconiferoustrees
estimate
parameters
fortheproductivity
model.A completef(L) willbeunityall year,whereas
for deciduous
trees,J•L)
will be zero duringthe winter, unity duringthe growing
foundin theworksby Arris[!989]or ArrisandEagleson season,
andbetween
zeroandunityduringthespringandfall
descriptionas well as referencesfor all data sourcescanbe
[•989].
transition periods.
PotentialEvaporation
At theregional
scaleofinterest
here,it seems
appropriateGrowingSeason
to considertime-average
(i.e., climatic)conditionsas the
To aid in computingthe lengthof the growingseason,
determining
environmental
criteriafor thepresence
or ab- phenologicaIdata were gatheredfrom the literaturefor red
senceof a particular
vegetation
typeat a specific
location. oak and other speciesfor a numberof locationsand dates.
Thedatasetthatwe choseto supplyclimaticinformation
as Temperature
datafor the nearestrecordingstationfor the
inputforthemodel
isdailynormals
oftemperature,
precip-corresponding
yearswerealsoobtained.Accumulated
grow-
itation,and degreedays,whichwe obtainedfrom the Na- ingdegree
dayswerecomputed
usinga threshold
of 5øCand
tionalClimaticData Centerin Asheville,North Carolina. a starting
dateof February! for cumulation,
whichproduced
Thenormals
werecomputed
forthetimeperiod1951-1980. an averageof 194degreedaysnecessaryfor bud break.
Out of thisdataset, 167stations
in 31 stateswereusedfor
A certainamountof timeis thennecessary
for the treeto
modelcalculations.
All stationsselected
wereeastof 97øW develop
itsfullcomplement
ofleaves.Verylittleinformation
longitude.
TheU.S.datasetwassupplemented
withdaily isavailableaboutthenatureofthisprocess;
however,Taylor
ARRIS AND EAGLESON:
LOCATING
THE BOREAL/DECIDUOUS
[1974]presentsa curveof percentleaf emergenceagainst
elapsed
timefor yellowpoplar(Liriodendron
tulipifera
L.)
whichwehaveusedasa model.Theaverage
number
ofdays
elapsed
frombudbreak
tofullleafwascomputed
fromthe
FOREST ECOTONE
5
•.OT
•
0.91
cz
0.7
phenological
towith
be
19
days.
This
was
then
fitted
tothe
Taylor [1974]data
curve,
the
following
result'
p = tanh(0.17e)
(9)
wherep equalsthe percentageof leavesemerged(0 <
- p <
- 1)
and e equalsthe numberof dayselapsedfrom the day of bud
break.
Sinceleafcolorchange
is primarily
a function
of photo-
•
0.4
•
0.3
•
..
,"
0.2
/
,,
,,'
o.
,,
o.o
-•0
period, which is, in turn, directly a function of latitude, the
date of leaf color change was determined from a linear
regressionof the day of color changeagainstlatitude. This
Figure 4.
relationship is
perature.
cc = 392- 2.84>
•
spruce (bore
,..... pine
,
,
,,
0
5
10
15
20
25
AVERAGE
DAILYTEMPERATURE
(øC)
Relationship of photosynthetic capacity to tem-
(10)
dry matter per g H20 transpired. The midpoint of these
where CC is the day of initial color changeand 4>is latitude.
valuesis a = 3 x 10-3 g dry matterperg H20 transpired,
Gee and Federer [1972] have shown that transpiration
and this was selected for use in the model for both conifers
ceasesshortly after color changebegins. Although data are
and deciduous trees.
scarce, color change takes approximately 17 days to complete. Due to the completelack of more specificinformation, Plant Coefficient k
this transition
is assumed to be linear.
In the model it is
representedby f(L) goingfrom a value of one on the day that
color changebeingsto a value of zero 17 days later. Model
runs for different latitudes comparedwith informationfrom
various sourcesregardingthe length of the growing season
indicates that this model successfullypredicts the length of
the growing season.
Although widely used in the agricultural literature [e.g.,
Doorenbos and Pruitt, 1977], values of k for forest trees are
nonexistent, and values of M are seldom measured. Fortunately, we need only the product Mk which we can estimate
from existing forest measurements. To do this we rearrange
(5) as
NPP
PhotosyntheticCapacity C
Using information obtained from the literature regarding
temperature criteria for photosynthesisin spruceand pine,
the relationships shown in Figure 4 were developed to
represent changingphotosyntheticcapacity in the model.
The temperaturecriterion is supplementedby an additional
restriction that C is always equal to zero on any day when
both maximum and minimum daily temperaturesfall below
0øC.The plateauat the level where C is equalto 1 is designed
to account for the shifts in optimum temperature as the
seasonprogresses.The relationshipis portrayed as linear
due to the fact that the curves shown in most diagrams are
linear througha large part of their range, and becausethere
were insufficientdata to warrant any other treatment. The
curves are approximate, especiallybecauseaveragedaily
temperaturesare beingused to determineC, but they serve
to placereasonablerestrictionson the photosyntheticperiod
for conifers, especially in the northern latitudes.
Water Use Efficiency of Production o•
Latchet [1983] provideswater use efficiencyvaluesa for
mk =
(11)
365
a Z CiEPif(Li)
i=1
Measured above-ground net primary productivity data
were then collected
from
the literature
for a total of 30
locations in eastern North America (different from the climatic stations used to estimate NPP), including four coniferous (midlatitude), 12 deciduous, and 14 southern pine
forests. No NPP data were found for northern (i.e., boreal)
coniferous forest. Climatic
data for the closest station were
adjusted for any elevational differences using an average
lapse rate of 5.46øC/kmand then used to computeE•,. The
model was run for each site, and a value of the product Mk
was computedusing(11). The estimatedMk valuesandtheir
averagesfor each vegetationtype are listed in Table 1.
Note the variability of the estimatesof Mk. In additionto
the direct climatic dependenceof k upon rc and &/T mentioned earlier, there is indirect climatic dependenceof M on
water availability. The cause of the variation in Mk is, at
leastfor a given vegetationtype, due in part to thesefactors
deciduous
treesofbetween
2.86x 10-3 and5.0 x 10-3 gdry
as well as to observational errors in the NPP from which the
matter per g H20 transpired,and a valuesfor conifersof
product Mk was computed.
between3.3 x 10-3 and5.0 x 10-3 g drymatterperg H20
transpired. However, since the model was fitted with net
primary productivity values for above-groundproduction
only, it is necessaryto adjustthesedownwardsomewhatto
eliminatebelow-ground(root) production.A review of Cannell [1982] indicates that between 13 and 35% of total net
primary production is below-groundproduction. This re-
ducesthea valuesto between1.9 x 10-3 and4.3 x 10-3 g
Model
Prediction
of Ecotone
Location
We expectourmodelto be mostapplicableto situations
in
which the transpirationis limited by availableenergyrather
than by availablewater. In the caseof water limitationwe
mightexpecteachcompetingplantcommunityto be capable
of usingall the availablewater, whereuponrelative produe-
h
ARRIS
Table 1.
ANI)
EA(}I,ES()N:
IX)CA'tlN(i
THE
B½)RI•:;AI,/I)ECII)U(.)[JS
F()REST
EC()T()NE
Net Primary Productivity l)ata Used to Estimate Mk
Location
I,atitude,
Ereration,
Weather
•N
m
Station
NPP
Mk
Source
("on4/?rousForest
Smoky Mountains,Tennessee
Smoky Mountains, Tennessee
Smoky Mountains, Tennessee
Smoky Mountains,Tennessee
Average
35.53
35.53
35.53
35.53
('edar Creek, Minnesota
('edar Creek, Minnesota
44.88
44.88
44.88
43,75
35.53
35.53
35,53
35.53
35.53
36.{•2
36.02
36,02
I620
18(14}
!920
I900
DccidltoUs
('cdar Creek, Minnesota
l?tubbardBrook, New Hampshire
Smoky Mountains, Tennessee
Smoky M•mntains, Tennessee
Smoky Mountains, Tennessee
Smoky Mountains, Tennessee
Smoky Mountains, Tennessee
{)i•k Ridge, Tennessee
{)ak Ridgc, Tennessee
{)irk Ridge, Tennessee
Average
Bradibrd (=?ity,t:i<•rida
Br;.•dlbrd('ity, Horida
Bradibrd City, Fl{•rida
llradlbrd City, Florida
ttradtbrd City, t:!{•rida
Bradibrd City, Fl•)rida
Bradl'brdCity, Florida
Bradl'i)rdCity, t:1orida
BradIbrd ('ity, Florida
Smoky Mountains, Tennessee
Sm.o.
ky Mountains, 'l'enncssee
Am'or'a, North Carolina
Aurora, North
Triangle Site, North Carolina
Average
700
730
820
82(!
7(}{}
i310
3{g)
310300
310300
3103(}0
3103(}0
920
980
465
650
0.49
0.56
0.28
0.39
0.43
Whittaker[1966]
Whittaker [19661
Whittaker [1966]
Whittaker[1966]
707
870
762
848
1!50
1900
14(•)
24(14}
1050
12!.}0
1526
1603
0.38
0,47
0.41
0.74
0.56
0.96
0.71
I. 15
0.67
0.51
(}.64
t!.67
Art and Marks [ 1971]
Reiners [ 1972]
Ovington et al, [1963]
Bortnattn and Likens [1979l
Whittaker [19661
Whittaker [1966]
Whittaker [1966]
Whittaker [1966]
Whittaker [1966]
Whittaker [ ! 966]
Itarris et al. [19751
Ilarris et al. [19751
Forest
215435
215435
215435
271683
3!03(•1
3 I(}3(14)
310300
3 I03(Ri
3111300
4{16750
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(;holz and b¾sher[19821
(;holz and Fi.s'her[19821
(;holz and t"i,s'her[ 19821
Ghotz and !,¾sher[ 1982]
(';holz and l'¾sher[19821
(;holz and Fisher [19821
(;holz and Fisher [19821
(;h•lz and Fisher [I 982]
Gholz and t,'isher [1982]
Whittt&er [1963, 19661
Whittaker [1963, 1966]
Netm,th [ 19731
Nemeth [ 19731
Lieth [ 19781
0.31
tire advantagewould be det.erminedby a differentfi•ctor asquickly.At somenorthwardpoint, dependingon relative
such as nutrition.
photosynthetic
ratesandgrowingseasons,
the coniferswill
The boreal coniferous tbrest-.deciduous lores( coo(one becomemore productivethan the deciduoustrees because
runegenerallyeast to west (Figure !• and hasbeenempiri- the high photosyntheticrates of the deciduoustrees no
growingseason.Figure5
cally linked to varioustemperatureconstraints.We have longeroffsetthegreatlyshortened
shownpreviously[Arrisand Ea#!eson,!989] thatsupercool- illustratesthe variation of primary productionover the
ing as a means of resistingfreezing stressesmay set an course of the year for these two vegetation types at a
absolutephysicallimit for the northernmigrationof most northernlocation(Figure 5a) and a southernlocation(Figdeciduoustrees, thereby determiningthe northernlimit of ure 5hi as computedby the model. The area under the
the annualNPP, m•dthe dominanttypeat
the deciduous forest fc)rmationas well. We use the produc- curvesrepresents
tivity modelto explorewhy the borealconiferousforestdoes each location should have the greater productivity. If the
hypothesis
is valid,thelatitudeat whichannualproductivity
not grow at lower latitudes.
In the warmer latitudes the deciduous trees have a relafor the two vegetationtypes is equal should mark the
tively long growing season. The length of this growing location of the ecotone.
Usingthe parameters
discussed
previously,the modelwas
seasoncoupled with high photosyntheticrates leads to a
higher net primary productivity for the deciduoustrees run for the borealand deciduoustoresttypesat eachclimatic
comparedwith the conifers, becausethe lower photosyn- data station north of 36ø latitude and the productivities
thetic rate of the conifers more than offsets their extended
compared;Figure6 illustratesthe results.Figure6 indicates
growing season due to their evergreen habit. As one that the deciduoustrees are, indeed, more competitive to a
progresses
north,thegrowingseason
for thedeciduous
trees latitude of about 47ø north which lies within the observed
ø)as givenby Eyre [1968]and indicatedby
getsshorterandshorter,causingproductivityto bereduced. ecotone(420-48
The growingseasonfor the conifersalsogetsshorter,butnot the two dotted lines. This reflects the latitude range of the
ARRIS AND EAGLESON'
LOCATING
THE BOREAL/DECIDUOUS
FOREST
ECOTONE
7
14
Sept lies, Quebec
Latitude
12
'E'
13' N
Deciduous Forest
2000
......
deciduous
boreal
/-,,%
8
o
Annual
NPP
Boreal Forest
'-.•.o
•) o
øoo
•o
..=_ 1500
.>_
E
O0
boreal
4
."
Annual NPP
0'•
• o
,
ß
.
ß
z
Transition Zone
Observed
Location
of
Vegetatio
Types
0
---deciduous
•',1o
•"
50
?
,.."'
657g/m2 ..""
..,
..• 0 0
o
6 Lo•o o oo
lOOO
'D.
..
ß
,
,
ß
30
60
90
120 1,50 180 210 240 270 500 350 3
z
,
500
36
JULIAN DAY
,
,
•
,
•
40
,
t
,
,
44
,
, ,:0 :
48
52
Latitude(degrees)
Figure 5a. Comparisonof the daily course of primary
productionin deciduousand coniferousboreal forestsat a Figure6. Annualnet primaryproductivityversuslatitude
northern
location.
for deciduous and coniferous boreal forests in the eastern
United
States.
mixed forest transitionzone shown in Figure 1. Someof the
theory is that with increasinglywarm winters at more
southerlylatitudesthepinescanphotosynthesize
essentially
all year [Perry, 1971],andthat this shouldpromotea higher
net primaryproductivityin the pinesthanin the deciduous
variabilities which lead to differences in microclimate. In this
trees. However, according to similar calculations,again
transition zone a small reduction in temperature would be assumingan unlimitedmoisturesupply,the southernpines
sufficientto shift the competitiveadvantagefrom deciduous do not have a higherproductivity than the deciduoustrees
forest to coniferous boreal forest. The sparsity of data anywherein their range, despitehavinga longergrowing
stationsin this region does not adequatelyreflect the vari- season.Some limitingfactor other than the effectsof tem-
scatter in the data at each latitude is due to the range of
longitudesover which the stationsare spread.
The abundanceof both speciesin the mixed foresttransition zone is probably due to local topographicand other
ability of the microclimatesof the area.
The majorsensitivityto the parameterization
of the model
lieswith the assumedequalityof the wateruseefficiencies
of
productiona for thecompeting
canopies.For example,if the
a valuesfor the two canopieswere chosenat oppositeends
of the observed range (quoted earlier), the productivity
curvesof Figure6 wouldintersectoffscaleratherthanwithin
the observedtransition zone. However, sincethe rangesof a
peratureand growingseasonon water use appearsto be
operatingsouthof this boundary.Frequentfire has been
blamedby manyinvestigators
for the lack of deciduous
trees
in this regionas has the barrenqualityof the sandysoils
[e.g., Eyre, 1968,p. 63]. Supportfor a soil-relatedexplanation is foundby comparingthe northernlimit of the southern
pinewiththe reportednorthernlimitof the Floridanaquifer
system[Sunand Weeks,1991],as is donein Figure1. This
given in the literatureare essentiallythe samefor both questionremainsunresolved.
canopies,the assumption
of equala is unbiased.
Preliminarystudiesof the deciduous
forest-southern
pine
Conclusions
ecotonemadeessentiallythe samehypothesisasthatfor the
Our long-range
objectiveis to formulateand test simple
coniferousboreal-deciduousecotoneexcept in reverse.The
physically
basedmodelsfor predicting
thelocationof major
vegetation
ecotones
whichcanserveasinteractive
boundary
conditionsin atmosphericgeneralcirculationmodels.As a
14,
partof thislargereffort,this studyhassoughtto formulate
Evansville, Indiana
deciduous
12'
Latitude58 3'N
--
deciduous
J ..:
Annual NPP
%1
/
boreel
boreal
z
•
fr
sucha modelfor locatingthe major vegetationecotonesin
AnnualNPP•
1578g/mz
eastern North America. These ecotones are the deciduous
forest/coniferousboreal forest ecotone in the north and the
'"1
"'
J....
southernpine/deciduous
forest ecotonein the south.Our
hypothesis
is that theseboundaries
are determined
by the
climaticallyinfluencedrelativecompetitiveabilityof each
vegetation
typeasrepresented
by net primaryproductivity
....
at each location of interest. We reasonthat the specieswith
' .
..
C)l
o
I
•
30
60
....•
,
90 120 150 180 210 240 270 300 330 560
JULIAN DAY
the highestNPP in any givenlocationwill dominateat that
location,and that ecotoneswill occurwhere a reversalin
competitive
abilitiesoccursdue to the changing
physical
environment of the plant.
We testedthishypothesis
for theenergy-limited
deciduous
forest/coniferous
borealforest ecotoneusingcanopytranspi-
Figure5b. Comparisonof the daily courseof primary
production
in deciduous
and coniferous
borealforestsat a rationas a surrogatefor NPP and found that the two forest
typesdoindeedundergo
a reversalin relativeproductivity
at
southern location.
8
ARRIS
AN1) t::A(iI.I,.Si>N'
IA)('ATIN(;
TIlE
B()RI:.AI./I)E('tl)tI()US
a location within the observed tran,,ition li.c.., cootone!. The
Acknowledgments.The w•,rk rept•rted herein wits .supportedin
breadthof the transitionzone betwcm•the two forest types part by the U.S, National Science l;{mndaticmunder grant ECE8•)3628 and in part by the Edmund K. '!"urnerProfessorshipin the
is probablydue 1o difikrc'ncesin microclimal,
e favoring
Departmentof ('ivil and EnvironmentalEngineering,Massachusetts
vegetationlypc ower another.
Institute of Technol•gy.
We alsotestedthis hypotheqsin the samemannertbr the
southernpine/deciduousforest ccotonewith no success,due References
probably to unincorporatedlimitations other than :energy,
Arris, I,. I,., A physioh•gicalexplanation!:k•rvegetatione.cotonesin
eastern North America. M.S. thesis, 247 pp., Dep. of Civ. Eng.,
The model has a number of weaknesses,especiallywhere
Mass. Inst. ofTechnol. Cambridge, 1989.
data tBr estimating parameters are limited. Of special conAn'is, I•. I,., and P.S. Eagleson, A physiological explanation
tern are the values cff water use efficiency (a> an.dthe plant
vegetationecotonesin easternNorth America, Ralph M. Parsons
coefficient (k•. Very few direct measurements of these
Lab, Rep. 323, 247 pp., I)ep. Civ. Eng., Mass. inst. ofTechnol.,
Cambridge, I989,
parametersare available fbr !•rest trees, and a change in
either value could have a significante•ect on modelresults. Art, H. W., and P. i,, Marks, A summary table of biomassand net
annual primary pmducti•min tbrest ecosystemsof the world,
The characterizationof photosyntheticresponseto temperForest BiomassStudies,edited by 1..I,ti. Young, pp, 3-27,
aturc in conifers, and the effects of water limitations in both
Sci, Exp. Sta. Mis•., t'uhl, I32, tJniv, of Maine, ()rono, 197!.
deciduoustreesand conit•rs are alsoapproximateand based Atmospheric Envir.t'mmentService, ('limatic Nortnal.• i951..,80
•)ttt'ht't'A, {]ttt',, N.S, gi5'82, ('anadian(;overnmentPublishing
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It can be arguedtlmt the model violatesbiologicalprinciplesin at leasttwo ways. First, it describesmany individuals
as one lumped, "average" individual, in essenceassuming
that all individtials are behaving identically. Second, it
assumesthat relative location is not importam, that is, all
individualsa•Fcctone another equally [t!u.stonet al., 19881.
Both of these argumentshave merit. However, becauseof
the temporaland spatialscalesof concernin climatemodeling,we tkel that this *•averaging"{•t'individualbehavior
both appropriateand necessary.
The results indicate that with some refinement and t•hc
incorporationof limiting ritetots other than energy
water or nutrientsl, the productivity approach to
predictionmay be a useRii addition to generalcirculation
models.It shouldbe possibleto keepit relativel'ysimpleand
still generate results which are accurate at the size of the
currentnumericalgrids.The modelis, however,an equilibrium model and would require modification!br the simu!ation of transient conditions.
Notation
C photosyntheticcapacity.
CC Julian day of initial color change, days.
El, potential
evaporation,
g H20 m' 2 {canopied
land)
yr.....
Er actualtranspiration,
g H20 m'"'2
(canopied
land)
yr......
•).
yr-•).
e days elapsedfrom bud break, days.
Hamon
correction
factor.
k plant coefficient.
L leaf area index, m' (leaf area) m "(canopied land).
M canopydensity,m2 (canopied
land)m-2 (land).
NPP netprimaryproductivity,
g dryweightm-2 (land)
yr-•).
p
percentageof leaves emerged.
x Hamonconstant,
m3cmd kg-• h-2).
y possible
amount
of sunshine,
h d-•.
a
water use efficiencyof production,g dry weight g
H20 transpired.
,os saturatedvapordensityat meandaily air
temperature,
kgm-•.
0
1982tt,
Atm•sphcric Environn•cnlService, (7imatit' Nt•rmaLv
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(Received October 26, 1992; revised September 13, 1993;
accepted September27, 1993.)