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Towards a quantitative classification of soil nutrient regimes in British Columbia : comparison of regional.. Klinka, Karel; Varga, Pal; Chourmouzis, Christine 1999

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Scientia Silvica Extension Series, Number  25, 1999Towards a Quantitative Classification of Soil Nutrient Regimes inBritish Columbia: Comparison of Regional StudiesIntroductionThe three major components in the site classification of the biogeoclimatic ecosystem classification system are:  climatic regimes,soil moisture regimes (SMRs) and soil nutrient regimes (SNRs).  Both SMRs and SNRs can be identified in the field using soilcharacteristics and indicator plants.  In the case of SMRs a quantitative classification was also developed that allow comparison ofSMRs in different subzones.  However, similar quantitative classification has not yet been developed for SNRs.  This pamphletsummarizes  and compares the  results  of several  regional  studies  conducted in  different biogeclimatic zones.   Each of thesesstudies aimes to develop a quantitative SNR classification (Table 1).  The comparison will examine:  (1) how well the field-basedclassification matches quantitative classification, and (2) which direct measures distinguish best between field-identified SNRs.Study Stands and ProcedureIn each study stand SNR was identified using field-observable soil morphological properties and indicator plants and a compositesample was taken from the forest floor and 0-30 cm of the mineral soil.  Site index of the study species was obtained from stemanalysis.  The composite samples were analyzed for the following nutrient properties: pH, total C (tC), total N (tN), mineralizable-N (min-N), and extractable Ca (eCa), Mg (eMg), K (eK) or their sum (SEB), P (eP), and S (eSO4-S). All properties were expressedas concentration on a dry mass basis. To describe the quality of organic matter and N-availability, C:N ratio was calculated.In most studies the stands were stratified into five SNRs by two methods:  (1) using field estimates and (2) using direct measuresof soil properties, and two classifications were compared by discriminant analysis.  The relationship between these classificationsand site index was evaluated by regression analysis.ResultsIn all studies, the  field-based and quantitative classifications provided very similar results: 60-70% of the plots were classifiedinto the same SNR by both methods.   In every study soil nutrient properties increased consistently from very poor to very richSNRs.  In general, N-related measures (min-N, tN and C:N ratio) had the largest differences between SNRs.  In all studies, thesingle most important  variable was min-N, which in  some studies had strong relationships with tN.    Most neighbouring SNRscould be distinguished based on the mean min-N values.  Similarly, site index values showed strong relationships with both field-based and qualitative classifications in all studies.  However, when the studies are combined SNRs cannot be differentiated basedon min-N values because the min-N values for a given SNR in one study does not often agree with another study (Figure 1).  Inconsequence, a given range of min-N values may comprise different SNRs in different zones.Table 1.  Summary of regional studiesG3  Study Study stands Zone 1 Kabzems (1985)  Douglas-fir  CWH 2  Klinka and Carter (1990)  Douglas-fir  CWH 3  Kayahara (1992)  Western hemlock  CWH 4 Klinka et al. (1994)  Lodgepole pine and interior spruce  SBS 5 Chen et al. (1998)  ( Scientia Silvica Number 22)  Subalpine fir and Engelmann spruce  ESSF 6  Splechtna unpublished data ( Scientia Silvica Number 21)  Pacific silver fir  MH 7  Varga and Klinka unpublished data ( Scientia Silvica Number 24)   CWH G3DiscussionAlthough the studies under comparison were conducted in different climatic and soil environments, they showed similarresults and trends. In general, field-based classification provided more consistent classes across different regions thanquantitative classification. We concluded that in all regions N is the most important nutrient for characterizing a soil nutrientgradient and framing SNRs as well as for predicting forest productivity. Despite the fact that mineral soil min-N was themost significant and suitable differentiating characteristic, when all the studies were combined, min-N values were similarfor some SNRs and had a wide range for some other SNRs (Figure 1). For example, the min-N values between 30 and 50mg kg-1 included poor, medium, rich, and very rich SNRs. This was partly due to a high variation of min-N values in severalstudies conducted in the CWH zone, while only one study was conducted in each of the MH, ESSF, and SBS zones. Thissituation emphasizes importance of (1) having several studies within a zone and (2) selecting the study sites irrespective oftree species.Figure 1.  Comparison of mineral soil mineralizable-N values between regional studies in four zones.The symbols represent mean values and bars indicate the standard error of the mean.G30G4cG51G48G55G44G4fG3G56G52G4cG4fG3G50G4cG51G48G55G44G4fG4cG5dG44G45G4fG48G10G31G3G3GbG50G4aG3G4eG4aG10G14GcG13 G18G13 G14G13G13 G14G18G13 G15G13G13 G16G13G13 G16G18G13G36G52G4cG4fG3G51G58G57G55G4cG48G51G57G3G55G48G4aG4cG50G48G39G33G33G30G35G39G35G26G3aG2bG3G3GbG36G57G58G47G4cG48G56G3G14GfG3G15GfG3G16GfG3G1aGc G36G25G36G3G3GbG36G57G58G47G5cG3G17GcG28G36G36G29G3G3GbG36G57G58G47G5cG3G18GcG2fG48G4aG48G51G47On the other hand, the min-N values determined for each of the five SNRs in the MH, ESSF, and SBS zones were quite similar,suggesting that SNRs in these three zones could be separated by common min-N values. As these zones are considerably differentin their climate and soils, it is reasonable to assume the between-zone variation is less than within-zone variation. This means thatthe field identified SNR would have more or less the same value in each of these three zones.Keeping in mind the development of an absolute or zone-independent classification based on mineral soil min-N, we suggest thereare two  possible approaches -  either to  recognize  more than  five  SNRs or to  continue using five  SNRs. For both approachesarbitrary limits of min-N values have to be established for each SNR. Using five SNR classes, the arbitrary limits might be  <10 forvery poor SNR, 11 - 30  for poor SNR, 31 - 70 for medium SNR, 71 - 150 for rich SNR, and >150 for very rich SNR. In addition,both approaches would require revision of the key to identification of SNRs in the field.ConclusionsThe comparison of regional studies showed similar results and trends for different climatic and soil environments, and demonstratedthat  for  some  zones field-based  and quantitative classifications are zone-independent. The most promising way to  develop aquantitative support for field-identified SNRs across the province is (1) to continue using N related measures for characterizationof a soil nutrient gradient, (2) to replicate studies in some zones, (3) to expand regional studies to the IDF and ICH zones, and (4)to impose arbitrary limits on five SNRs accompanied by revision of field-keys.ReferencesChen, H.Y.H.,  Klinka, K.,  Fons, J.,  and Krestov,  P.V.  1998. Characterization of nutrient regimes in  some continental subalpineboreal forest soils. Can. J. Soil Sci. 78: 467-475.Kabzems, R.D. 1985. Quantitative classification of soil  nutrient regimes  of some  mesothermal Douglas-fir ecosystems. M.Sc.Thesis, Univ. British Columbia, Vancouver, BC. 252 pp.Kayahara, G. J. 1992. Ecological site quality and productivity of western hemlock ecosystems in the Coastal Western Hemlockzone of British Columbia. M.Sc. Thesis, Univ. British Columbia, Vancouver, BC. 164 pp.Klinka, K. and Carter, R.E. 1990. Relationships between site index and synoptic environmental factors in immature coastal Douglas-fir stands. For.  Sci. 36: 815-830.Klinka, K., Wang, Q., and Kayahara, G.J. 1994. Quantitative characterization of nutrient regimes in some boreal forest soils. Can.J. Soil Sci. 74: 29-38.Scientia Silvica is published by the Forest Sciences Department,The University of British Columbia, ISSN 1209-952XEditor: Karel Klinka (klinka@interchange.ubc.ca)Research: P?l Varga (pvarga@interchange.ubc.ca) and K. KlinkaProduction and design: Christine Chourmouzis (chourmou@interchange.ubc.ca)Financial support: Forest Renewal British ColumbiaFor more information contact: P?l VargaCopies available from:  www.forestry.ubc.ca/klinka orK. Klinka, Forest Sciences Department, UBC,3036-2424 Main Mall,Vancouver, BC  V6T 1Z4


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