UBC Faculty Research and Publications

Western larch site index in relation to ecological measures of site quality Klinka, Karel; New, David Morley; Chourmouzis, Christine 2000-04-15

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Western Larch Site Index in Relation toEcological Measures of Site QualityIntroductionA silviculturist  needs to know how productivity of  all treespecies  under management varies with the  ecologicaldeterminants of site quality, i.e., the environmental factors thatdirectly affect the growth of plants - light, heat, soil moisture,soil nutrients, and soil aeration. A good understanding of thisvariation is necessary for making biologically viable, species-and site specific silvicultural decisions. Productivity of a givenspecies is usually measured by site index (top tree height at 50years at breast height age). Quantified relationships  betweensite index  of a given species and ecological measures of sitequality provide predictive models for estimating site index forall sites on which the species may grow.Western larch  (Larix occidentalis  Nutt.) is  an important  treespecies  in  southern  central and eastern British Columbia. Itgrows mainly in the IDF,  ICH, and MS zones on moderatelydry through very moist sites and on poor through very rich sites.In  view of this  relatively  wide ecological amplitude, a largevariation in  productivity could be expected. In  the  studysummarized here, relationships  between larch  site index  andselected  ecological measures of site  quality were examined,and a site index model using these measures as predictors wasdeveloped.Study stands and ProcedureThe study area encompassed the entire native range of larch inBC. The stands selected for the study had regenerated naturallyafter a major disturbance, typically  wildfires, and weredeliberately selected  across the  widest range  of climatic(biogeoclimatic  subzones),  soil  moisture, and soil  nutrientconditions. The stands were unmanaged, uniformly and fullystocked, even-aged (ranging from 40 to 160 yrs at @ bh), andwithout signs of obvious damage or suppression.A 0.04 ha plot was established in each of the 315 study stands,the  three  largest  diameter trees  were cut and sectioned,  andsite index was determined from stem analysis data. An averageheight curve was computed for each species from sampled sitetrees  for  each study  plot using Richard?s  three-parameterequation and linear interpolation technique; the actual site indexfor each plot was then calculated as the average true height ofsite  trees  using the  fitted  equation. Allocation of stands  intobiogeoclimatic subzones was done according to biogeoclimaticmaps. Soil moisture regime  (SMR)  and soil  nutrient regime(SNR) were estimated using a combination of topographic andsoil morphological properties as well as understory vegetation.Scientia Silvica Extension Series, Number  41, 2000Descriptive statistics  were used to  examine the  relationshipbetween site  index  and inferred  climatic, soil  moisture, andsoil nutrient regimes. Inferential statistics were used to evaluatethe  strength of these  relationships and site index  predictions,and the model was cross-validated using independant data. Todetect the strongest climatic influence on height growth, onlystands on zonal sites were examined.  This study is the first toexamine the effect of SNR and SMR interaction on larch siteindex.Results and DiscussionRegional climate did influence site index of larch on zonal sites,with significant differences (alpha = 0.05) occurring between twosubzone  groups: low-precipitation  IDF  subzones  and high-precipitation ICH and MS subzones. However, when comparingthe  zonal sites  with equivalent soil  moisture, no significantdifferences in site index were detected on very dry, moderatelydry, and slightly dry sites between study subzones. Thus, it wasconcluded that  precipitation,  not temperature, limits  growthof larch in  the study  area. Consequently,  subzone  was notconsidered a useful predictor of larch site index.Larch site index  significantly increased  from  water-deficientto moist sites and decreased from moist to wet sites. On water-deficient sites, it increased from very poor to very rich sites;estimates of both actual SMR and SNR had both significantand consistent positive effects on site index on these sites. Onsites  where water was not deficient, the  influence  of SNRappeared to be marginal.A cross-validated prediction model based on field-estimatedactual SMR and SNR accounted for  84% of the  variation inwestern larch site index:SI = 7.9 + 0.0(ED) + 4.8(VD) + 8.4(MD) + 10.8(SD) + 12.5(F) +14.1(M) + 7.3(VM) + 7.4(W) + 0.0(VP) + 1.1(P) + 3.4(MD)+ 4.5(R) + 4.7(VR)Adjusted R2 = 0.84 SEE = 1.5 MSE = 2.1where: ED - excessively dry, VD - very dry, MD - moderatelydry, SD - slightly dry, F - fresh, M - moist, VM - very moist,W - wet, VP - very poor, P - poor, MD - medium, R - rich,VR - very rich, SEE - standard error of the estimate, MSE -mean square error. Scientia Silvica  is published by the Forest Sciences Department,The University of British Columbia, ISSN 1209-952XEditor: K. Klinka (klinka@interchange.ubc.ca)Research: D. New (thenews@jetstream.net)Production and design: C. Chourmouzis (chourmou@interchange.ubc.ca)Financial support: National Science and Engineering Research Council, WeyerhouserCanada, Ltd., and Cranbrook Forest Industries, Ltd.For more information contact: David New (thenews@jetstream.net)Copies available from: www. forestry.ubc.ca/klinka orK. Klinka, 3036-2424 Main Mall, Forest Sciences Department,UBC, Vancouver, BC, V6T 1Z4When predicted values were compared to measured values onthe  test  data set  (n  = 105), the  constructed model (n  = 210)proved unbiased in predicting site index. A paired t-test (alpha =0.05) showed the regression model predicted a site index thatdid not differ significantly from the mean site index of the testdata set.  The mean difference was 0.09 m between the predictedand measured site  index  (p  =  0.55). Plotted prediction errorvalues also indicated  no bias in  site  index prediction, andshowed that the model estimates of the test data site index wereusually within ?3m of the  actual measured values. Thedeveloped model, using field estimates of SMR and SNR, canbe used to  provide site  index  predictions for  western larchthroughout its range in BC to a satisfactory level of accuracy.Table 1. Edatopic grid showing the predicted site index values (m @ 50 yr bh) using the SMR-SNR model(n=315), ?95% confidence interval (m), measured mean site index, and SIBEC mean site index valuesaccording to actual SMR and SNR. Sample sizes indicated refer only to the measured and predicted siteindex values.1SIBEC (Site Index Estimates by Site Series for Coniferous Tree Species in British Columbia 1997).2NA - SIBEC estimate not available.3ND - no data were obtained due to the absence or sporadic occurrence of western larch under some edaphic conditions.G24G46._G57G58G44G4fG3G3 G31G58G50G45G48G55G3G52G49G3G53G4fG52G57G56G3GbG51GcG3G3G36G31G35G3G36G30G35G3 G44G51G47G3G56G4cG57G48G3G4cG51G47G48G5bG3 G39G48G55G5cG3G53G52G52G55G3 G33G52G52G55G3 G30G48G47G4cG58G50G3 G35G4cG46._G4bG3 G39G48G55G5cG3G55G4cG46._G4bG3G3G3 G3G3G3G3G3G28G5bG46._G48G56G56G4cG59G48G4fG5cG3G47G55G5cG3G3G51G3G33G55G48G47G4cG46._G57G48G47G3G30G48G44G56G58G55G48G47G3G36G2cG25G28G26G14G3G16G3G1bG11G19?G14G11G1aG3G1bG11G19G3G31G24G15G3G13G3G1cG11G15G3G31G27G16G3G31G24G3G13G3G14G14G11G18G3G31G27G3G31G24G3G13G3G14G15G11G1aG3G31G27G3G31G24G3G13G3G14G16G11G13G3G31G27G3G31G24G3G39G48G55G5cG3G47G55G5cG3G3G51G3G33G55G48G47G4cG46._G57G48G47G3G30G48G44G56G58G55G48G47G3G36G2cG25G28G26G3G19G3G14G16G11G15?G13G11G19G3G14G16G11G15G3G31G24G3G14G17G3G14G16G11G1b?G13G11G1bG3G14G17G11G16G3G14G1bG11G13G3G1bG3G14G19G11G14?G13G11G1cG3G14G18G11G17G3G14G1aG11G13G3G15G3G14G1aG11G16?G13G11G1aG3G14G19G11G19G3G14G1bG11G19G3G13G3G14G1aG11G18G3G31G27G3G31G24G3G30G52G47G48G55G44G57G48G4fG5cG3G47G55G5cG3G3G51G3G33G55G48G47G4cG46._G57G48G47G3G30G48G44G56G58G55G48G47G3G36G2cG25G28G26G3G13G3G14G19G11G1aG3G31G27G3G31G24G3G17G18G3G14G1aG11G17?G13G11G18G3G14G1aG11G15G3G14G1cG11G19G3G17G17G3G14G1cG11G19?G13G11G18G3G14G1cG11G1cG3G14G1bG11G1bG3G19G3G15G13G11G1b?G13G11G18G3G15G13G11G1bG3G15G13G11G14G3G13G3G15G14G11G14G3G31G27G3G15G16G11G1aG3G36G4fG4cG4aG4bG57G4fG5cG3G47G55G5cG3G3G51G3G33G55G48G47G4cG46._G57G48G47G3G30G48G44G56G58G55G48G47G3G36G2cG25G28G26G3G13G3G14G1cG11G15G3G31G27G3G31G24G3G18G15G3G14G1cG11G1c?G13G11G16G3G14G1cG11G1cG3G15G16G11G17G3G18G1bG3G15G15G11G15?G13G11G18G3G15G14G11G1cG3G15G16G11G13G3G15G1bG3G15G16G11G16?G13G11G1aG3G15G16G11G1aG3G15G14G11G13G3G13G3G15G16G11G19G3G31G27G3G14G1cG11G15G3G29G55G48G56G4bG3G3G51G3G33G55G48G47G4cG46._G57G48G47G3G30G48G44G56G58G55G48G47G3G36G2cG25G28G26G3G13G3G15G13G11G1cG3G31G27G3G31G24G3G13G3G15G14G11G18G3G31G27G3G15G15G11G1cG3G14G1bG3G15G16G11G1b?G13G11G18G3G15G14G11G1cG3G15G16G11G1aG3G14G14G3G15G18G11G13?G13G11G19G3G15G16G11G1aG3G15G14G11G1cG3G18G3G15G18G11G15?G14G11G14G3G15G18G11G19G3G15G1aG11G13G3G30G52G4cG56G57G3G3G51G3G33G55G48G47G4cG46._G57G48G47G3G30G48G44G56G58G55G48G47G3G36G2cG25G28G26G3G13G3G15G15G11G18G3G31G27G3G31G24G3G13G3G15G16G11G14G3G31G27G3G14G1bG11G1cG3G14G3G15G18G11G17?G14G11G16G3G15G19G11G18G3G15G17G11G1bG3G15G3G15G19G11G19?G14G11G16G3G15G19G11G15G3G15G17G11G14G3G18G3G15G19G11G1b?G14G11G14G3G15G19G11G1bG3G15G13G11G13G3G39G48G55G5cG3G50G52G4cG56G57G3G3G51G3G33G55G48G47G4cG46._G57G48G47G3G30G48G44G56G58G55G48G47G3G36G2cG25G28G26G3G13G3G14G19G11G14G3G31G27G3G31G24G3G13G3G14G19G11G1aG3G31G27G3G31G24G3G13G3G14G1cG11G13G3G31G27G3G15G15G11G16G3G17G3G15G13G11G15?G14G11G16G3G15G13G11G19G3G15G15G11G18G3G14G3G15G13G11G17?G15G11G1cG3G14G1bG11G1aG3G15G18G11G15G3G3aG48G57G3G3G51G3G33G55G48G47G4cG46._G57G48G47G3G30G48G44G56G58G55G48G47G3G36G2cG25G28G26G3G13G3G14G19G11G16G3G31G27G3G31G24G3G13G3G14G1aG11G13G3G31G27G3G31G24G3G13G3G14G1cG11G15G3G31G27G3G31G24G3G14G3G15G13G11G17?G14G11G19G3G15G13G11G17G3G31G24G3G13G3G15G13G11G1aG3G31G27G3G31G24G3      ReferenceNew,  D. 1999. Productivity of western larch  in  relation  tocategorical measures of climate, soil moisture, and soil nutrients.M.Sc. Thesis. Department of Forest Sciences, University ofBritish Columbia, Vancouver, BC.

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