UBC Faculty Research and Publications

Trembling aspen site index in relation to site quality in northern British Columbia Klinka, Karel; Chen, Han Y. H.; Chourmouzis, Christine 1998-12-31

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Scientia Silvica Extension Series, Number  17, 1998Trembling Aspen Site Index in Relation to Site Qualityin Northern British ColumbiaIntroductionAccurate and reliable predictions of site index (height of dominant trees at a reference age, usually 50 years at breast-height)for timber crop species is essential for silvicultural site-specific decision making.  Site index can be predicted from site qualityonce the relationship between site index and site quality has been quantified.  Site quality is defined as the sum of allenvironmental factors affecting the biotic community, such as the factors directly influencing the growth of vascular plants(light, heat, soil moisture, soil nutrients, and soil aeration). Since these factors vary greatly in time, indirect estimates of sitequality have widely been used as predictors for site index in various multiple regression models.Trembling aspen (Populus tremuloides Michx.) is the most widely distributed broadleaf species in British Columbia, especiallyin the Boreal White and Black Spruce (BWBS) biogeoclimatic zone.  Growing this species for sustainable timber productionrequires a good understanding of its productivity attributes and accurate predictions of its growth. This extension notepresents (1) relationships between trembling aspen site index and some indirect measures of site quality, and (2) site indexprediction models using the indirect measures of site quality as predictors.Materials and MethodsA total of 60 stands were located in the Moist and Warm BWBS(mw) subzone near Dawson Creek, Fort St. John, and FortNelson in northern British Columbia. The study stands were naturally established (after wildfires), fully stocked, even-aged,without a history of damage, and dominated by trembling aspen with an occasional component of balsam poplar (Populusbalsamifera L.) and lodgepole pine (Pinus contorta var. latifolia Dougl. ex. Loud. ).  The stands were deliberately selectedacross the widest range of available soil moisture and nutrient conditions that support aspen growth.  In each stand, a 0.04-ha rectangular plot, relatively uniform in topography, soil, understory vegetation, and stand characteristics, was randomlylocated to represent the stand. Site index was determined from stem analysis.Site quality was measured or estimated using surrogate measures for climate, which included latitude, longitude, altitude,and topography (slope aspect, gradient, and position [crest, upper slope, middle slope, lower slope, or level]). Soil moistureregime (SMR) and soil nutrient regime (SNR) were estimated in the field using a combination of topographic and soilmorphological properties.  A particular combination of SMR and SNR is referred to as an edatope.Relationships between trembling aspen site index and climatic and continuous topographic variables (e.g., aspect and %slope) were examined by regression analysis.  One-way analysis of variance was used to examine the relationships betweensite index and slope position and edatope.  Multiple regression models were developed after using backward stepwiseprocedure to exclude independent variables at alpha= 0.05.G24G56G53G48G46._G57G3GbG47G48G4aG55G48G48GcG13 G19G13 G14G15G13 G14G1bG13 G15G17G13 G16G13G13 G16G19G13G36G4cG57G48G3G4cG51G47G48G5bG3GbG50GcG13G18G14G13G14G18G15G13G15G18G16G13G36G4fG52G53G48G3G53G52G56G4cG57G4cG52G51G26G55G48G56G57 G38G53G53G48G55 G30G4cG47G47G4fG48 G2fG52G5aG48G55 G2fG48G59G48G4fG36G4cG57G48G3G4cG51G47G48G5bG3GbG50GcG13G18G14G13G14G18G15G13G15G18G16G13G36G52G4cG4fG3G51G58G57G55G4cG48G51G57G3G55G48G4aG4cG50G48G39G33 G33 G30 G35G36G4cG57G48G3G4cG51G47G48G5bG3GbG50GcG13G18G14G13G14G18G15G13G15G18G16G13G30G52G47G48G55G44G57G48G4fG5cG3G47G55G5cG36G4fG4cG4aG4bG57G4fG5cG3G47G55G5cG29G55G48G56G4bG3G44G51G47G3G50G52G4cG56G57Lattu d e  (? N )55 56 57 58 59Site index (m)051015202530Longttu d e  (? W )120 121 122 123051015202530El aton ( )400 450 500 550 600 650 700 750 800051015202530Figure 2. Site index  (SI, 50 yr @ bh) in relationto aspect (degree of azimuth).  The regressionrelationship is SI = 15.39 + 0.056(aspect) -0.0002(aspect)2, Ra2 = 0.082, P = 0.03.Figure 3. Site index  (SI, 50 yr @ bh) inrelation to slope position.  Error bars representone standard error of the mean.Figure  4. Site index  (SI, 50 yr @ bh) in relationto edatopes (combinations of soil moistureregime and soil nutrient regime [SNR]).  SNRare abbreviated as follows: VP - very poor, P -poor, M - medium, and R - rich. Error bars areone standard error of the mean.Figure 1.  Site index (SI, 50 yr @ bh) in relation to indirect climatic variables (latitude (0N), longitude (0W), and elevation (m)).  The regressionrelationships (n = 60) are: for latitude, SI = -166.3 + 3.242(latitude), Ra2 = 0.54, P < 0.001; for longitude, SI = 98.86 - 0.67(longitude), Ra2 = 0.01, P =0.45; and for elevation, SI = 39.88 - 0.34(elevation), Ra2 = 0.47, P < 0.001.Results and DiscussionRelationships between site index and measures of ecological  site qualityTrembling aspen site index significantly increased with latitude and decreased with elevation but there was no significantrelationship between site index and longitude (Figure 1).  Latitude was also negatively correlated with elevation (r = -0.89, p< 0.001).  In relation to topography, site index increased with aspect from cool- to warm-aspect slopes (Figure 2, p < 0.05).With change in slope position, site index decreased from the lower slope to the crest, and the site index for the level slope(flat  sites) was in  between the  lower  and middle slope positions (Figure 3,  p  <  0.001); however,  site index was notsignificantly related to slope gradient (R2 = 0.01, p = 0.45).Changes in soil moisture and nutrient regime resulted in significant differences in trembling aspen site index among edatopes(Figure 4, p < 0.05).  Site index increased with increasing nutrient availability on slightly dry sites, and with increasingavailable soil moisture on poor sites.  The most productive growth occurred on fresh or moist and rich sites; the leastproductive growth occurred on moderately dry and very poor sites.  These occurrences indicate that aspen height growthincreases with increasing available soil nutrients (soil nitrogen) and increases from water-deficient to moist sites.Predictive modelsThe models usifng diffferent measures of sifte qualifty as predifctors had diffferent levels of accountabiflifty for varifatifon ifntremblifng aspen sifte ifndex (Table 1).  Among the models usifng clifmatifc varifables (Model [1]), topographifc propertifes (Model[2]), and edatopes (Model [3]), the  descrifptifve measures (if.e.,  R2a  and SEE) of model performance ifndifcated  that theedatope model [3] was the best, followed by the topographifc model [2] and clifmatifc model [1].  The models usifng clifmatifcvarifable(s) and topographifc propertifes as predifctors (Model [4]) sifgniffifcantly ifmproved accountabiflifty for sifte ifndex (Table 1,Model [4] versus Models [1] and [2]).  Sifmiflarly, the model usifng clifmatifc varifable and edatopes as predifctors ifmprovedaccountabiflifty for sifte ifndex (Table 1, Model [5] versus Models [1] and [3]).Where free-growifng aspen trees are absent on a sifte, all models presented ifn thifs study are applifcable for sifte ifndex predifctifonwifthifn the lifmifts of the BWBSmw subzone.  In the siftuatifon where mature aspen stands are present on a sifte, the heifghtgrowth model as well as aspen sifte ifndex tables and curves are recommended to determifne sifte ifndex.  Provifdifng that SMRand SNR can be correctly estifmated, the model [5] ifs recommended for sifte ifndex predifctifon.  However, when SMR andSNR cannot be estifmated (e.g., ifn the wifnter season) or they are out of the range of the presented model, the slifghtly lessprecifse model [4] can be used.ReferenceChen, H.H.Y., K. Klifnka, and R.D. Kabzems. 1998. Sifte ifndex, sifte qualifty, and folifar nutrifents of tremblifng aspen: relatifonshif psand predifctifons. Can. J. For. Res. 28: 1743-1755.Table 1. Models of predicting site index (SI, 50 yr @ bh)) from only climatic variables ([1]), topographic properties ([2]), edatopes ([3]), climateand topography ([4]), and climate and edatopes (n = 60 for all models).  All independent variables are significant (p < 0.05) and models aresignificant (p < 0.001).  R2a is the adjusted R2.  SEE is standard error of the estimate.No.  Constituent  Model  R2a  SEE (m) [1]  Climate  SI = 22.61 + 3.4344(LAT) - 1.6385(LONG)  0.587  3.44 [2]  Topography  SI = 7.57 + 0.0672(ASP) -0.0002(ASP)2+ 2.756(UPP) + 7.268(MID) + 9.078(LOW) + 9.772(LEV)  0.527  3.68 [3]  Edatopes  SI = 7.60 + 4.10(P_MD) +7.34(P_SD) + 11.46(M_SD) + 15.69(R_FM)  0.671  3.07 [4] Climate and topography SI = 38.17 + 2.704(LAT) - 0.841(LONG) + 0.0393(ASP) - 0.0001(ASP)2 + 0.75(UPP) + 4.23(MID) + 6.70(LOW) + 3.86(LEV) 0.768 2.58 [5] Climate and edatopes SI = -117.24 - 2.255(LAT) + 4.20(P_MD) + 6.17(P_SD) + 7.60(M_SD) + 12.75(R_FM)  0.863  1.98 G3Scientia Silvicais published by tfhe Forestf Sciences Departfmentf,The Universitfy of Britfish Columbia, ISSN 1209-952XEditor: Karel Klinka (klinka@intferchange.ubc.ca)Researcfh: Han Chen (han.chen@mnr.gov.on.ca)Producftion and design: Christfine Chourmouzis (chourmou@intferchange.ubc.ca)Financfial support: Forestf Renewal Britfish ColumbiaFor more information cfontacft: H. ChenCopies available from:www.forestfry.ubc.ca/klinka  orK. Klinka, Forestf Sciences Departfmentf, 3036-2424 Main Mall, UBC, Vancouver, BC, V6T 1Z4


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