ten-year responses of soil quality and conifer growth to silvicultural treatments

Ten-Year Responses of Soil Quality and Conifer Growth to Silvicultural TreatmentsCatherine Perie* and Alison D. Munson

ABSTRACTThe development of sustainahle forestry practices and credible

certification systems relies on continuous monitoring of indicators.In the present study, carried out at the Petawawa Research Forest(Ontario, Canada), we evaluated the impacts of three intensive silvi-cultural treatments: scarification, fertilization, and herbicide treat-ment, applied alone or in combination—on indicators of organic layerquality, foliar nutrition, and tree growth—10 yr after establishmentof eastern white pine (Finns strobus L.) and white spruce [Piceaglauca (Moench) Voss] plantations. We compared these 10-yr resultswith measurements made 3 to 4 yr after plantation establishment. Inboth 1989 and 1996, the herbicide treatment had the greatest effecton organic layer quality. In 1996, compared with the no-treatmentcontrol, herbicide application reduced organic C mass by 46%, totalN mass by 15%, and acid phosphatase activity by 64%. These negativeeffects were offset when herbicide was applied in combination withfertilizer. The negative impact of herbicide on microbial biomass Cnoted in 1990 was no longer evident in 1996. In herbicide-treatedplots, the nitrate-dominated cycle observed 1989-1990 was replacedby an ammonium-dominated cycle in 1996. Although herbicide appli-cation negatively affected soil quality, it increased tree growth andgenerally improved foliar nutrition; thus organic layer and tree re-sponses were not correlated. The indicators used were sensitive tochanges in the ecosystem over time and signaled soil impacts thatcould have consequences for long-term productivity.

SUSTAINABLE FOREST MANAGEMENT has been adoptedas an objective through both international and na-

tional accords, and in Canada, provincial regulationsand industrial certification increasingly reflect this con-text. We consider practices to be sustainable where in-herent site productivity is maintained over time. Theevaluation of sustainable use of forest resources relieson a system of continuous monitoring of criteria, andmore specific and locally defined indicators (Nordin,1996; Morris et al., 1997). Evaluation of plantation for-estry must be an important part of this process; largereforestation efforts in Canada in the last decade meanthat more than 4 000 000 ha have been planted, mainlyto spruce and pine (Anonymous, 1997). The success rateof these conifer plantations is often limited by competi-tion from non-crop woody and herbaceous vegetation(Walstad and Kuch, 1987). Thus, to inhibit the compet-ing vegetation during plantation establishment, the siteis often prepared by scarification and herbicide applica-tion (Lepage and Coates, 1993; Richardson, 1993). Scar-ification also increases soil temperature (Bassman,1989). Fertilization is applied to enhance the growth ofplanted trees (Swift and Brockley, 1994; McLaren andJeglum, 1998).

In 1986 and 1987, a plantation study was established

Centre de recherche en biologie forestiere, Faculte de foresterie etde geomatique, Pavilion Abitibi-Price, Universite Laval, Sainte-Foy,QC G1K 7P4, Canada. Received 28 May 1999. *Corresponding author([email protected]).

Published in Soil Sci. Soc. Am. J. 64:1815-1826 (2000).

in three major climate zones of Canada, to quantifygrowth and physiological response of native pine andspruce to factorial combinations of scarification, fertil-ization, and vegetation control with herbicide (Brandand Janas, 1986). Although these treatments were non-operational in nature (complete removal of organic mat-ter, 6 yr of fertilization and 4 yr of vegetation control),they represent an extreme that is a useful context formonitoring specific indicators of sustainable forest man-agement.

Soil is a key natural resource interacting with above-ground plant and animal communities (Canadian Coun-cil of Forest Ministers, 1995), and maintaining site pro-ductivity and soil resources are two key internationaland national criteria for defining and monitoring forestsustainability (Harris and Bezdicek, 1992; Papendickand Parr, 1992). Soil quality may be defined as thecapacity of a soil to accept, store, and recycle water,nutrients, and energy, sustain biological productivity,maintain environmental quality, and promote plant andanimal health (Doran and Parkin, 1994). Or, in simpleterms, soil quality is the capacity (of soil) to function(Karlen et al., 1997). Assessment of the state of soilorganic matter is a valuable step towards identifying theoverall quality of a soil because organic matter is theprimary source of, and a temporary sink for, plant nutri-ents (Gregorich et al., 1994; Larson and Pierce, 1994;Morris et al., 1997). To evaluate soil organic matterquality, Gregorich et al. (1994) proposed a number ofindicators, including organic C (Corg), total N (Nt), soilcarbohydrates, light fraction and macroorganic matter,microbial biomass C (Cmic) and N (Nmic), and finally,enzyme activities. We used a subset of these indicatorsto assess impacts of forest practices 10 yr after planta-tion establishment.

The present study is revisiting treatments that werefirst assessed 3 to 4 yr after plantation establishmentand are now being reassessed 10 yr after establishment.The objectives of the study were to evaluate treatmentimpacts on organic layer properties and fertility, as wellas foliar nutrition and growth of planted trees. By mea-suring these over time (3-4 yr and 10 yr) we are ableto monitor changes in ecosystem function and develop-ment after disturbance related to different single andcombinations of silvicultural treatments. By comparingeach treatment with a harvest-only control, we can noteif this function and development differ from a morenatural process of recovery after disturbance.

MATERIALS AND METHODSSite Description and Experimental Design

The experimental site is in central Ontario, Canada, on thenorth shore of Cartier Lake (45°57'50" N, 77°34'45" E; 170 m

Abbreviations: Cmic, microbial biomass C; COTg, organic carbon; DBH,diameter at breast height; F, fertilization; Nmic, microbial biomass N;N,, total nitrogen; S, scarification; V, vegetation control with herbicide.

1815

1816 SOIL SCI. SOC. AM. J., VOL. 64, SEPTEMBER-OCTOBER 2000

above sea level) within the Petawawa Research Forest. It isin the Middle Ottawa Section of the Great Lakes-St. LawrenceForest region (Rowe, 1984). The underlying bedrock is Pre-cambrian granite and gneiss, and the soil is a deep, well-drained loam to sandy-loam, classified as an orthic humoferricpodzol or Haplorthod (Soil Classification Working Group,1998). The regional climate is moist-humid (Hills, 1959), withannual precipitation of 800 mm. Mean daily maximum temper-atures are recorded in July (25.4°C) and minimum tempera-tures in January (—18.4°C). The site supported a mature mixedwood stand as described by Brand and Janas (1988), beforebeing clear-cut during the summer of 1985.

The experimental design was a randomized complete block,23 factorial. The factors were scarification (S; Levels 0 and 1),fertilization (F; Levels 0 and 1), and vegetation control (V;Levels 0 and 1). Level 0 in all treatments represented an undis-turbed post harvest condition. Scarification (SI) representedremoval of logging debris and forest floor organic material byblade scarification. Fertilization at Level 1 (Fl) representedan annual application of Osmocote, which is a slow-releasetemperature-dependent fertilizer (17:16:10 NPK plus micronu-trients with 9.1% NH4+-N and 7.9% NO3~-N). Fertilizer wasapplied each year for 6 yr; 30 g of fertilizer were placed aroundeach tree in the first growing season, increasing to 200 g pertree in the sixth growing season (40, 60, 80,135 g from Year2-5). Vegetation control at Level 1 (VI) represented the an-nual removal of competing vegetation with the herbicideglyphosate [^-(phosphonomethyl) glycine] applied at 2.0 kgha"1 of active ingredient in midsummer each year for 4 yr.There were four replicates of each treatment combination,located in randomized blocks, for a total of 32 experimentalplots. Half of each 20- by 40-m plot was planted with white pineand half with white spruce; 100 3-yr-old bare-root seedlings perspecies were planted at 2- by 2-m spacing in April 1986.

Soil Sampling and AnalysesA 30-m transect was randomly laid out within each experi-

mental plot, parallel to the longest side of the plot. The transectextended into areas of both seedling species. Five samplinglocations were randomly distributed along each transect. Or-ganic layer samples consisting of all organic matter above themineral soil surface were collected at each sampling locationof SO treatments in May and August 1996 and composited byplot. Organic layer depth was measured at the same time.There was insufficient organic layer in SI treatments to collectand analyze. Fresh organic matter pH was measured accordingto McLean (1982). Water content was determined by dryingsubsamples at 105°C for 48 h before weighing. Organic matterwas measured gravimetrically by loss on ignition (Gallardo etal., 1987). The organic matter was converted to organic C(Corg) by a conversion factor of 0.56 (Nelson and Sommers,1982). Total N was analyzed with a Tecator 1030 Macro-Kjel-dahl Analyzer (Hoganas, Sweden). Total elements (P, K, Caand Mg) were measured by inductively coupled plasma emis-sion (Perkin-Elmer Instruments, Norwalk, CT) after completedigestion in HNO3, HC1O4, and HF in Teflon beakers (Limand Jackson, 1982). Exchangeable cations (K, Mg, and Ca)were extracted with an unbuffered 1.0 M NH4NO3 solution(Stuanes et al., 1984) and measured by inductively coupledplasma emission. Available P was determined by the Bray IImethod and was analyzed with an Automated Ion Analyzer(Lachat QuickChem 8000, Zellweger Analytics Inc., Milwau-kee, WI).

Carbohydrates were extracted by shaking 2 g of air-driedorganic layer (250 u,m-2 mm) for 8 h with 20 mL of hot water(80°C). To remove the brown color of organic matter, the

extracts were centrifuged for 6 min at high speed, after whichthe supernatants were re-centrifuged at the same speed. Glu-cose, fructose, mannose, inositol, cellubiose, and sucrose wereanalyzed by HPLC (Hewlett Packard 1090, Palo Alto, CA)on a Sugar-Pak I column (300 mm X 6.5 mm ID, Waters,Milford, CT) with 1 mM CaEDTA as a mobile phase. Injectionvolume was 10 jiL and flow was set up to 0.5 u.L min"1.Separation was performed at 90°C and the temperature of therefraction index detector (Hewlett Packard 1047A, Palo Alto,CA) was 40°C. The values of individual carbohydrates weresummed to yield total hot-water-soluble carbohydrates.

The buried polyethylene bag technique was used to evaluatenitrogen mineralization rates in situ (Eno, 1960; Zou et al.,1992) at five locations per plot. Soil cores were prepared byhammering sharpened polyvinylchloride pipes (height =10cm, diameter =7 cm) into the soil, keeping the organic layerand surface mineral soil intact. The two horizons were sepa-rated and the organic layer was transferred from the tube intoa polyethylene bag. The bag was then sealed, buried in thesame hole and covered with a 2-cm-deep litter, and incubatedfor 22 wk (27 May-22 October 1996). In May 1996, a secondset of cores was sampled to determine initial levels of inorganicnitrogen (NHf plus NO3~). Inorganic N was extracted in thefield according to Van Miegroet (1995). The filtrates werefrozen before NKf-N and NO3~-N were quantified by a La-chat Automated Ion Analyzer.

In August 1996, microbial biomass C (Cmic) and N (Nmic)were determined on organic layer samples for all treatmentsexcept scarification by the fumigation-extraction procedure(Brookes et al., 1985). The samples were processed in thelaboratory within 48 h. Values of extractable-C and -N wereobtained as the difference between the amounts of C and N,respectively, extracted with 0.5 M K2SO4 from chloroform-fumigated (for 24 h) and unfumigated samples. Analyses ofextractable organic C were made with a compact C titrator(Mettler DL20, Mettler-Toledo, Inc., Worthington, OH) andanalyses of the soluble organic N were made with the Tecator1030 Macro-Kjeldahl Analyzer. A kEC-factor of 0.38 (Vanceet al., 1987) was used for converting extractable-C flush toCMC , and a kEN-factor of 0.45 (Brookes et al., 1985; Jenkinson,1988) was used for the conversion of extractable-N flush toNnic. Acid and alkaline phosphatase activities were determinedaccording to Jordan et al. (1995). The biomass C to biomassN ratio (Cmic/Nmic) was estimated on the basis of these data,and the ratio of microbial biomass C to total soil organic C(Cmjc/Corg), and microbial biomass N to total soil organic N(Nmic/Nt) were estimated from data from basic soil analyses.

All data are expressed on an oven-dry basis and are con-verted into a mass per hectare of soil using the measured bulkdensity values. In May 1996, bulk density was estimated bysampling the organic layer (n = 3 per plot) from volumetriccores (height = 10 cm, diameter = 7 cm). The samples weredried at 105°C for 48 h before weighing.

Growth, Foliar Sampling, and AnalysesIn October 1996, five white spruce and five white pine trees

per plot were randomly chosen, and tree height as well asdiameter at breast height (DBH) were measured. Within theupper one third of the live crown of each tree, three subsam-ples of the current year's foliage were collected from threelateral branches. The foliage samples from each plot werepooled by species and dried at 65°C for 48 h. The dry massof current needles (grams per 100 needles) was measured andrecorded for each composite sample. The dried needles wereground (0.42 mm), and digested in H2O2-H2SO4-Se. Total N,P, and cations were quantified as described earlier. The effects

PERIE & MUNSON: TEN-YEAR SOIL AND TREE RESPONSES TO SILVICULTURAL TREATMENTS 1817

of silvicultural treatments on nutrient status were analyzedusing the vector analysis technique (Timmer and Stone, 1978;Munson et al, 1993). The technique permits simultaneouscomparison of needle dry mass, nutrient concentration, andnutrient content. On the basis of the magnitude and directionof vectors describing response to treatment in terms of thesethree variables, analyses can be used to diagnose nutrientstatus: sufficiency, deficiency, luxury consumption, toxicity,and antagonism. All the data were expressed on a leaf dryweight basis.

Statistical AnalysesOrganic layer properties (except N, and acid phosphatase

activity) were analyzed with a three-factor ANOVA con-taining the following terms and their associated degrees offreedom: block, 3; F, 1; V, 1; F X V, 1; and error 9. Theerror term consisted of all block interaction terms, under theassumption of no interaction between blocks and other factors.Nt and acid phosphatase activity were analyzed with a four-factor ANCOVA containing the following terms and theirassociated degrees of freedom: block, 3; Corg, 1; F, 1; V, 1;F X V, 1; and error 8. The error term consisted of all blockinteraction terms, under the assumption of no interaction be-tween blocks and other factors. Analysis of organic layer prop-erties excluded scarification, because organic layers of theseplots were too thin to sample. Tree growth data were analyzedusing a four-factor ANOVA containing the following termsand their associated degrees of freedom: block, 3; S, 1; F, 1;V, 1; S X F, 1; F X V, 1; S X V, 1; S X F X V, 1 and error21. The error term consisted of all block interaction terms,under the assumption of no interaction between blocks andother factors.

Homogeneity of variance and normality of the distributionof all data were verified and data that were not homogeneouswere natural log transformed prior to analysis. Pearson linearcorrelations were based on plot means, and were performedusing data from all treatments and replicates (n = 16 withoutscarified plots and n = 32 with scarified plots). Ratios wereanalyzed by the adjusted ratio method according to Bauce etal. (1994). To evaluate relative recovery of soil after distur-

bance, a Dunnett's test was used, comparing single treatmentsand treatment combinations with the control plot (a = 0.10).All the statistical analyses were performed by SAS programs(SAS, 1989).

RESULTSChemical Properties of the Organic Layer

Fertilization and vegetation control treatments didnot have an effect on depth of the organic horizon, andthe average depth was 3.5 cm. On scarified plots, theorganic horizon was present on only 30% of the plotarea, with an average depth of 0.4 cm. The pH of theorganic matter was also unaffected by treatments after10 yr. Bulk density was significantly reduced by thefertilization treatment (Table 1). With the exception ofCorg and total P, the amounts of total elements werenot altered by the applied treatments (Table 1). Thefertilization and vegetation control treatments inter-acted to affect Corg (P = 0.0077). When either fertiliza-tion or vegetation control was applied alone, Corg contentof the organic layer decreased, but when the two treat-ments were combined, there were no significant changesin Corg levels, compared with the control plot. The samescenario was observed for total P (Table 1); total P wassignificantly reduced by vegetation control alone butwhen vegetation control was combined with fertilizationthere was no difference from the control plot. The N,and the C/N ratio of the organic matter were not affectedby silvicultural treatments (Table 1). Fertilization signif-icantly increased available Ca; other available nutrientswere not affected by the treatments (Table 1). All theavailable elements were positively correlated with totalelements (r = 0.80, r = 0.87, r = 0.79, r = 0.82 forP, K, Ca, and Mg, respectively). Carbohydrates in theorganic layer were not affected by the silvicultural treat-ments and the mean value of total hot-water-solublecarbohydrates was 270 kg ha"1 (2.5 mg g"1). Carbohy-

Table 1. Silvicultural treatment effects on bulk density, pH, and chemical properties of the organic layer, 10 yr after conifer plantationestablishment. Net N mineralization was evaluated by a 22-wk in situ incubation. (F = fertilization, V = vegetation control; 0 = notreatment applied, 1 = treatment applied).

MeanSE§F

Bulkdensity

gem 3

0.30

*

Total elements

PH

5.50.2

r1 N + c /ivv^org ^tT ^'org'^— 1

Mg ha-'20.5 0.91 22

0.04 1

P

kg ha~'70.0

K Ca

Mg ha"1

1.70 1.830.20 0.20

Mg

32245

Available elements

P

3.90.5

K

67.618.2

Ca Mg

- kg ha~' ——1.73 136

23*

N mineralization

N-NOj-

0.145

N-NHJ

0.729

SEflV

SEfl

FOFl

voVI

0.350.250.02

1.392.080.20

0.2030.0320.055

F X V

SEft

FOVOFOV1F1VOF1V1

**27.414.913.926.03.6

t94.445.356.384.612.1

**- - - - - 0.531- - - - - -0.083- - - - - -0.740- - - - - 3.868

0.674

t,*.** Significant at the 0.10, 0.05 and 0.01 probability levels, respectively.t ANCOVA (COIg as covariable).§ SE, standard error used when no treatment is significant, calculated as square root of square mean error divided by 16.II SE, standard error used when F is significant, calculated as square root of square mean error divided by 8.# SE, standard error used when V is significant, calculated as square root of square mean error divided by 8.ft SE, standard error used when F X V is significant, calculated as square root of square mean error divided by 4.


Table 2. Correlations (Pearson's coefficient) between chemical and biological properties of the organic layer, ten years after coniferplantation establishment.

Phosphatase

Soil property! N, wsc Alkaline Acid

0.94N,CmicN™WSCAlkaline phosphataseAcid phosphatase

0.840.83

0.720.660.83

0.460.420.300.17

0.650.710.820.650.09

0.670.690.660.500.520.66

t Cmio microbial biomass C; Nmk, microbial biomass N; WSC, hot-water-soluble carbohydrates.P < 0.05 if r > 0.25; and P < 0.01 if r > 0.33.

drates were positively correlated with organic carbon,Cmic and acid phosphatase activity of the organic layer(Table 2).

To evaluate the relative recovery of the soil ecosystemafter the different levels of treatment and disturbance,all treatment plots were compared to control plots,which were undisturbed since plantation establishment(no subsequent silvicultural treatment since harvest).The Dunnett's test showed that the vegetation controltreatment was still markedly different from the control(Fig. 1). Herbicide applications reduced Corg and Nt re-serves by 46 and 15%, respectively.

Nitrification and Ammonificationof the Organic Layer

Net nitrification rate was reduced by vegetation con-trol, whereas net ammonification rate was significantlyincreased by the combination of fertilization and vegeta-tion control (Table 1). Net N mineralization rate(NO3~ plus NH4

+) was strongly correlated with the am-monification rate (/- = 0.99, P = 0.0001) but not signifi-cantly correlated with the nitrification rate (r = 0.24,P = 0.42). As a result, the treatment effects on net Nmineralization were the same as those observed for netammonification. Fertilization and vegetation control in-

teracted to affect net N mineralization (NH4+ plus

NCV). When vegetation control and fertilization treat-ments were applied separately, nitrogen immobilizationwas observed. However, when the two treatments werecombined net N accumulation was observed, and theinorganic N availability in the humus was increased fivefold compared with the control.

Microbial Biomass Carbon, MicrobialBiomass Nitrogen, and Acid and Alkaline

Phosphatase ActivitiesFertilization and vegetation control treatments inter-

acted to influence Cmic and Nmic contents (Table 3). Vege-tation control reduced both Cmic and Nmic whereas fertil-ization decreased Cmic and tended to reduce Nmic.However, when fertilization and vegetation controlwere combined, Nraic increased to levels similar to thoseof the control plot, while Cmic increased to a lesser degree(Table 3). Craic and Nmic averaged 235 kg ha"1 and 41 kgha"1, respectively. Cmic and Nmic were positively corre-lated with each other (Table 2). The CmjC to organiccarbon ratio (Cmic/Corg), Nmic to total nitrogen ratio (Nmic/N,), and Cmic to Nmic ratio (CmiC/Nmic) were not influencedby silvicultural treatments (Table 3). Alkaline phospha-tase activity was greater than acid phosphatase activity.

Control plot Vegetation control plotFig. 1. Effects of vegetation control (Dunnett's test; alpha = 0.10) on C,,,e, N, and phosphatase activity of the organic layer.


Table 3. Silvicultural treatment effects on microbial biomass C (C,,lic) and N (Nmic), on phosphatase activities and on Cmic/C,,rB, Nmi/N,and Cmk/N,nic ratios, 10 yr after conifer plantation establishment (F = fertilization, V = vegetation control; 0 = no treatment applied,1 = treatment applied).______________________________________________________________

Phosphatases

Acid! Alkaline

MeanSE§

SEfl

SE#

SEft

—— kg ha-' ——234.8 40.9 13.0

1.6

— kg PNP ha~' h"1

49.5 6.34.9 0.6

1.76 4.860.82

F X V

FOFl

VOVI

FOVOFOV1F1VOF1V1

2.580.930.30

t307.4209.5192.7229.535.4

t59.729.630.543.711.4

t,*,** Significant at the 0.10, 0.05 and 0.01 probability levels, respectively.t ANCOVA (Cor| as covariable).§ SE, standard error used when no treatment is significant, calculated as square root of square mean error divided by 16.11 SE, standard error used when F is significant, calculated as square root of square mean error divided by 8.# SE, standard error used when V is significant, calculated as square root of square mean error divided by 8.ft SE, standard error used when F X V is significant, calculated as square root of square mean error divided by 4.

Table 4. Silvicultural treatment effects on biomass (weight of 100 needles), foliar nutrient concentrations and growth parameters (DBH,diameter at breast height) of white pine and white spruce, 10 yr after conifer plantation establishment (S = scarification, F =fertilization, V = vegetation control; 0 = no treatment applied, 1 = treatment applied).

Biomass

mgMean 750SEt

SSOSI

SE§F

FOFl

SEflV **

VO 570VI 920

SE# 80S X F

SOFOSOF1S1FOS1F1

SEttS x V

sovoSOV1S1VOS1V1

SEttF x V

FOVOFOV1F1VOF1V1

SE§§

White pine

Foliar nutrients

N P K Ca

——————— mg kg"1 ————15.0 1.86 6.52 3.29

_ _ _ __ _ _ _

_ _ _ __ _ _ _

** **14.3 - - 2.7715.7 - - 3.800.2 0.09

_ _ _ __ _ _ __ _ _ __ _ _ _

** **1.96 7.641.83 5.891.75 6.321.90 6.220.04 0.18

t7.135.776.836.34

Growth

Mg Height DBH

1.24 402 6.95

*38242211

_ _ __ _ _

**1.201.290.03

_ — __ _ __ _ __ _ _

*2.949.864.89

10.130.36

t- 361 -

440- 334 -

47316

White spruce

Foliar nutrients

Biomass N P K Ca Mg

mg ——————— mg kg"1 ———————260 11.9 1.91 7.32 6.01 0.98

5

_ _ _ _ _ __ _ _ _ _ _

_ _ _ _ _ __ _ _ _ _ _

t- - - - 1.00- - - - 0.96

0.02

_ _ _ _ _ __ _ _ _ _ __ _ _ _ _ __ _ _ _ _ _

* ** **12.2 2.20 9.5311.1 1.68 6.0811.7 1.85 7.6212.6 1.91 6.320.4 0.05 0.32

t4.80

- - - 6.974.35

- 7.910.11

Growth

Height

——— cm350

*33036911

__

--

.____

____

*27344422146115

DBH

5.22

t4.475.970.86

__

**2.647.81

____

____

____

t,*,** Significant at the 0.1, 0.05, and 0.01 probability levels, respectively.| SE, standard error used when no treatment is significant, calculated as square root of square mean error divided by 32.§ SE, standard error used when S is significant, calculated as square root of square mean error divided by 16.fl SE, standard error used when F is significant, calculated as square root of square mean error divided by 16.# SE, standard error used when V is significant, calculated as square root of squire mean error divided by 16.ft SE, standard error used when S X F is significant, calculated as square root of square mean error divided by 8.It SE, standard error used when S x V is significant, calculated as square root of square mean error divided by 8.§§ SE, standard error used when F X V is significant, calculated as square root of square mean error divided by 8.


240100

200 -

O

'"c 1600)OOOC 120 -

10)rr

80 -

40 -

• Without vegetation controlO With vegetation control

Reference

40r

80

163

.3?TJ0)

0

1CDcc

120 160 200 240

Relative nutrient contentFig. 2. Effects of vegetation control on foliar nitrogen, calcium, and magnesium nutrition of eastern white pine, measured 10 yr after plantation

establishment. Nutrient status of trees of plots without vegetation control was adjusted to 100 for comparison with trees on treated plots.

The applied treatments had no effect on the alkalinephosphatase activity; however, vegetation control mark-edly reduced acid phosphatase activity (Table 3; Fig. 1).Alkaline and acid phosphatase were both significantlycorrelated with Cmic and Nmic and the correlation wasstrongest for Cmic (Table 3).

Foliar Nutrient LevelsWhite Pine

Vegetation control significantly increased the needlemass as well as N, Ca, and Mg concentrations (Table 4).The treatments of vegetation control and scarificationinteracted to affect foliar P and K concentrations (Table4). When vegetation control or scarification were ap-plied alone, they significantly reduced needle P concen-tration but when the two treatments were combined, Pconcentration did not differ from the control. Vegeta-tion control alone reduced foliar K concentration butwhen it was combined with scarification, the K concen-tration was the same as that of the control. For N, Ca,and Mg, vector analysis (Fig. 2) indicated a positivefoliar response of eastern white pine to the suppressionof competing vegetation in terms of the three compo-nent variables: concentration, content, and average nee-dle dry mass. Between 1989 and 1996, with or withoutvegetation control, the average needle dry mass andthe relative N content increased while the relative Nconcentration decreased (Fig. 3); however, the increasewas more important in VO plots than in VI (greaterdilution in VO). For P and K, vector analysis indicatedthat when vegetation control was applied, with or with-out scarification, the average needle dry mass and therelative P and K contents increased, whereas relative

concentrations decreased (Fig. 4). However, scarifica-tion alone decreased P and K concentrations, slightlyincreased the average needle dry mass and had no effecton P and K relative contents.

White SpruceThe average mass of 100 fall-sampled, current-year

white spruce needles did not differ among treatments(Table 4). The effects of vegetation control and scarifica-tion on N concentration interacted. Without scarifica-tion, vegetation control decreased N concentration, butwhen it was combined with scarification, the N concen-tration was similar to that of the control plot. Vegetationcontrol and scarification treatments also interacted toaffect foliar P and K concentrations (Table 4). All thetreatments reduced both P and K concentrations (Table4). In the case of P, combined herbicide and scarificationreduced levels to a lesser degree than either treatmentalone. Herbicide reduced levels of foliar K to a greaterdegree than scarification, while the effects of the twocombined were intermediate. Fertilization and vegeta-tion control interacted to affect Ca concentration; foliarCa levels decreased following fertilization alone, in-creased in response to vegetation control and were high-est when vegetation control was combined with fertiliza-tion. Vegetation control slightly reduced foliar Mgconcentration. We did not apply vector analysis forspruce because treatments had no significant impact onaverage needle dry mass.

Growth ParametersWhite pine tree height was increased 10% by scarifi-

cation (Table 4). The vegetation control and fertilization

PERlfi & MUNSON: TEN-YEAR SOIL AND TREE RESPONSES TO SILVICULTURAL TREATMENTS 1821

Relative needle dry mass100

110175

gHo>o

105 -

100 -

95 -

I3 90CDtr

85 -

80

1989 198

80 100 120 140 160 180 200

Relative N contentFig. 3. Effects of vegetation control on foliar nitrogen nutrition of eastern white pine measured 4 and 10 yr after plantation establishment.

Nitrogen status of trees of plots without vegetation control (YO) measured in 1989 was adjusted to 100 for comparison with the nitrogenstatus of trees of the same plots measured in 1996. Nitrogen status of trees of plots with vegetation control (VI) measured in 1989 wasadjusted to 100 for comparison with the nitrogen status of trees of the same plots measured in 1996.

treatments interacted to affect the height of white pine.Fertilization alone reduced height, while greatest heightwas achieved when vegetation control was combinedwith fertilization (4.7 m). Effects of scarification andvegetation control on DBH interacted (Table 4). Scarifi-cation alone and vegetation control alone increasedDBH compared to the control and when scarificationand vegetation control were combined, DBH was up tofour times greater than controls.

White spruce height and DBH increased significantly(by 12 and 34%, respectively) following scarification(Table 4). Vegetation control also increased DBH byalmost 200%. Vegetation control and fertilization inter-acted to affect height; height increased in response toboth treatments, but to a lesser extent following fertiliza-tion, and to the greatest extent in response to the twotreatments combined (almost 70%, 4.6 m).

DISCUSSIONImpacts on Organic Layer Nutrient Status

and Microbial BiomassMeasurements of soil properties and processes over

time, as well as tree growth and nutrition, allowed usto discern changes in the ecosystem resulting from dif-ferent silvicultural treatments, and the recovery relativeto a harvested control. In 1996, as in 1989, the pH ofthe organic layer was not influenced by silviculturaltreatments, but the average pH value increased from5.2 (Munson et al., 1993) in 1989 to 5.5 in 1996. Thisincrease could be due to the considerable development

of deciduous trees and herbs in plots where herbicidewas not applied. Total and available P, K, Ca, and Mgcontents of the organic layer were in the same order asthose measured by Burgess et al. (1995) in 1992.

Because the depth of the organic layer is decreasingover time, from an approximate 6-cm depth in 1986 (attime of plantation, Brand and Janas, 1986) to a 3.5-cmdepth measured in 1996, impacts on Corg and Nt reserves(t ha"1) are important. Herbicide applications stronglydecreased Corg reserves; this decrease is evident both incomparison to the control (Fig. 1), but also over time.In 4 yr (1992-1996), control plots had lost 13% of Corgreserves while vegetation control plots had lost 46%(data from Burgess et al., 1995). In 1992, N, reserves incontrol and herbicide-treated plots were not signifi-cantly different (Burgess et al., 1995); however, in 1996,Nt reserves were markedly lower (15%) in herbicide-treated plots (Fig. 1). Even though Corg and Nt reservesdecreased in response to the vegetation control treat-ment (Fig. 1), the C/N ratio was not influenced by thesilvicultural treatments and the mean value of the ratiowas stable over time, i.e., 21 in 1989 (Munson et al.,1993) and 22 in 1996. The total amount of litter addedannually to the organic layer in vegetation control plotswas not statistically different from that added to controlplots (Munson, 1999, personal communication) but thecomposition of the litter was markedly different. Thelitter of the control plots was dominated by deciduousleaves (83%) while that of vegetation control plots wasdominantly needles (97%). Normally, mean residencetime of the latter material is longer than that of decidu-


Relative needle dry mass100

180

150

.0*

C 120CDO

OO

0)

"•̂JOocc

90 -

60 -

30 -

0I30 60

I90

163

120 150 180

Relative nutrient contentFig. 4. Effects of vegetation control and scarification on foliar phosphorus and potassium nutrition of eastern white pine, measured 10 yr after

plantation establishment. Nutrient status of trees of plots without vegetation control and where scarification was not realized was adjustedto 100 for comparison trees on treated plots (V = vegetation control, S = scarification; 0 = no treatment applied, 1 = treatment applied).

ous litter (Waring and Running, 1998); however, micro-climate appears to be the main factor influencing or-ganic matter dynamics. Higher soil temperatures andmoisture level observed in the vegetation control plot(Brand and Janas, 1988; Munson et al., 1993; Boucheret al., 1998) appear to have accelerated decompositionrates of the organic matter present before harvest, de-creasing the depth of the organic layer, and thus the Cand nutrient reserves, especially N.

In 1990, the vegetation control treatment reduced Cmicin the organic horizon. This effect was no longer evidentin 1990, indicating a recovery of 0™ relative to thecontrol treatment. However, acid phosphatase activityin the organic layer was reduced by 64% (comparedwith control), indicating that microbial activity is stillaffected by the intensive herbicide application. In theseslightly acid soils, acid phosphatase activity is likely tobe more sensitive than alkaline phosphatase activity(Tabatabai, 1994). The Cmic concentration in the organichorizon has tended to decrease over time in all situa-tions, most markedly in the plots without vegetationcontrol (Fig. 5). This may be related to changing micro-climate, i.e. colder soils with canopy closure in theseplots, and to changes in litter quality. The Cmic/Corg ratioalso decreased from an average of 1.9 and 1.6% in con-trol and vegetation control plots in 1990 to 1.2 and 1.5%in the same plots in 1996, supporting the hypothesis ofreduced litter quality as the plantation ages. Bauhus etal. (1998) also noted a decrease in this ratio with increas-ing age of mixed-wood boreal stands. On the other hand,

Nmic tended to increase over time (Fig. 5), indicatingimmobilization in microbial biomass as a stronger sinkin the 10-year-old plantations compared to 5-year-oldplantations. The mean value of Nmic/N, measured in 1996(4.4%) was smaller than an average for organic layerdata (6.6%) compiled by Bauhus and Khanna (1999)and also lower than ratios noted for natural, matureforests in the southern boreal (Bauhus et al., 1998),north of the study site. The mean value of Cmic/Nmic ratiomeasured in 1996 (6.3) was similar to the ratio of 6.7,suggested by both Jenkinson (1988) and Fenn et al.(1993) as typical for coniferous forest soil microbialbiomass. These values are lower than those measuredby Ohtonen et al. (1992), suggesting a change in thepopulation structure of the microbial community since1990 (Wheatley et al., 1990). The strong correlationobserved in 1996 between Cmic and Corg was probably dueto carbon limitation caused by the soil organic matterquality (Bauhus and Khanna, 1999). The mean value ofCmic/Corg ratio (1.3%) was slightly lower than the ratioof 1.8% observed by Bauhus and Khanna (1999) as amean value for a wide range of organic layer substrates.

Ten years after plantation establishment, impacts ofintensive silvicultural treatments on N mineralizationwere still evident; vegetation control combined with fer-tilization markedly increased N availability, and N im-mobilization was observed when either of the two treat-ments were applied alone. There appears to be asynergistic effect of the two treatments combined. Fertil-ization alone has often been shown to have minimal


O)O)

O

5

4 -

3-

2 -

1 -

0

'cnO)E

0.4 -

0.2 -

0.1 -

0.0

I 1990I 1996

I

luUl

20 •

FOVO F1VO FOV1 F1V1Fig. 5. Microbial biomass C (Cmi,,) and N (Nmif) concentrations of

organic layer in nonfertilized (FO), and fertilized plots (Fl) withoutvegetation control (VO) or with vegetation control (VI); measured4 and 10 yr after conifer plantation establishment. 1990 data wereadapted from Ohtonen et al. (1992).

effects where vegetation competition is important, sinceit may actually stimulate competition for nutrients. Veg-etation control alone did stimulate N availability at4 years after plantation establishment (Munson et al.,1993) but this effect is no longer observed. Greater Navailability with F1V1 may be related to higher litterproduction, hence increased Corg, total P, with positiveimpacts on total microbial biomass C and N (mg ha~').The nitrate-dominated cycle observed during the first5 yr of plantation development (Ohtonen et al., 1992;Munson et al., 1993), typical of harvest impacts in certainforest types (Vitousek et al., 1982; Pietikainen andFritze, 1995), has been replaced by an ammonium-domi-nated N cycle (Fig. 6), which is representative of moremature forest ecosystems (Kimmins, 1987; Zak et al.,1989). The microbial C/N ratios may provide an indica-tion of the availability of microbial N for mineralization.In general, low CmiC/Nmic ratios are associated with netN mineralization, and high Cmic/Nmic ratios with net im-mobilization of N in the microbial biomass (Paul andJuma, 1981; Edmonds, 1987). In 1996, the Cmic/Nmic ratiowas highest in the vegetation control plot and lowest inthe control plot; coupled with the apparent N immobili-zation in these plots, this suggests that the microbialbiomass in the vegetation control plots is N stressed.Therefore, even if the microbial community of the vege-tation control plot maintains its current Cmic/Nmic ratiolevel, microbes would be competing more strongly withtrees for N to meet their maintenance requirementsand growth potential. Thus, in the 10-yr-old plantationwhere competing vegetation was controlled, the soil eco-system was C and N limited, whereas in the 5-yr-oldplantation (Ohtonen et al., 1992), it was only C limited.

Impacts on Tree Nutrition and GrowthScarification alone increased height of white pine and

height and DBH of white spruce (Table 4). This re-sponse was not evident seven years earlier (Table 5).

cn00cn

15 -

10 -

5 -

D)

-5 •

I——1 1989_NO317-7] 1989_NH4I——1 1996_NO3r-T-l 1996_NH4 - 1.5

- 1.0

2.0

COcncn

- 0.5 b)

O)

0.0

-0.5FOVO F1VO FOV1 F1V1

Fig. 6. Net nitrate and ammonium production by field incubation oforganic layer in nonfertilized (FO), and fertilized plots (Fl) withoutvegetation control (VO) or with vegetation control (VI); measured3 and 10 yr after conifer plantation establishment. 1989 data wereadapted from Munson et al. (1993).

Microclimate measures showed that this treatment in-creased soil temperature (Munson et al., 1993; Boucheret al., 1998), thus the effect on growth may be partlyachieved through greater root growth (Bassman, 1989).The enhanced foliar biomass and N, Ca, and Mg contentin response to vegetation control was of the same orderof magnitude as noted 7 yr earlier (Table 5). In contrastto responses in 1989, P and K nutrition were no longeraffected by this treatment in 1996. Compared with nutri-tional standards (Morrison, 1974), white pine foliar nu-trients were generally sufficient and there were onlysmall differences in concentrations between the differ-ent treatments. White pine of the plots where herbicidewas applied were always larger than those of the plotswithout vegetation control.

As for pine, white spruce showed marked growthresponse to vegetation control by herbicide (Table 4).Foliar P, K, and Mg were comparable to concentrationsmeasured by both Morrison (1974) and Swift andBrockley (1994), where no growth limitation was evi-dent, whereas N levels were in the deficient range (Mor-rison, 1974), where growth may be reduced. Spruce isgenerally considered to be a higher nutrient demandingspecies than pine, and any potential nutrient limitationsare likely to be first diagnosed in spruce.

Although vector analysis indicated some relativetreatment differences, foliar nutrient concentrationsvaried little between treatments for both species (Table4). Nutritional differences are now likely to be expressedin total foliar mass as well as at the leaf level (Munsonand Timmer, 1995). The positive response of both spe-cies to vegetation control indicates the response to in-creased light during this phase of plantation develop-ment (Boucher et al., 1998); however, there was also anearlier foliar nutritional response to vegetation control(Munson et al., 1993) and response to increased wateravailability (Boucher et al., 1998). As noted previously(Munson et al., 1993; Burgess et al., 1995), white pine isstill outgrowing white spruce; however, this may change


Table 5. Foliar nutrient concentrations and growth parameters (biomass determined by weight of 100 needles) of eastern white pineand white spruce measured in 1989 and 1996, 3 and 10 yr after conifer plantation establishment, respectively (1989 data were adaptedfrom Munson et al., 1993).

N

SOFOVOSOF1VOSOFOV1SOF1V1S1FOVOS1F1VOS1FOV1S1F1V1

1989

1514202017141618

S X V**F x V**

1996

1415161614141615v**

p1989

———— mgg

2.02.01.91.81.81.81.81.7

1996-i

1.92.01.71.91.71.81.91.9

S X V**

1989

White6.46.17.56.26.26.06.26.4

K

1996

pine7.97.45.66.16.46.25.96.6

S x V**F X Vf

Biomass1989

———— mg-

297228532541337284454571

F X V**

1996

4206158489836955488081043y#*

1989

108109155141124120144157v**

Height1996

- cm ————

336297437460387372443486

S*F X Vf

White spruceSOFOVOSOF1VOSOFOV1SOF1V1S1FOVOS1F1VOS1FOV1S1F1V1

915202112121720

S X F**

1212111112121720

S X V*

1.82.02.01.91.71.82.01.9

2.22.31.81.61.81.91.82.0

S x V**

6.48.85.25.76.97.06.15.9F*

9.89.96.35.86.98.35.96.7

S x V**

9776878510310597101

268245265265270253268248

848886868089103113

246185447444300257441477

S*

t,*,** Significant at the 0.1, 0.05, and 0.01 probability levels, respectively.

following observed repeated attacks of the white pineweevil [Pissodes strobi (Peck)], especially in the openconditions created by herbicide application. These at-tacks may continue until 20 yr of age (Boulet, 1999).

CONCLUSIONThe impact of silvicultural treatments on organic mat-

ter quality indicators was still important 10 yr after har-vest and subsequent disturbance by the different treat-ments. Organic layer chemical properties such as Corgand Nt, as well as biological properties such as Cmic, Nmicor phosphatase activity and net N mineralization, wereuseful indicators to monitor soil perturbations and eco-system recovery because they were sensitive and easyto measure. In both 1989-1990 and 1996, vegetationcontrol had the most impact on both soil quality indica-tors and tree response. In 1996, herbicide applicationdecreased organic layer reserves, especially Corg and Nt;this negative effect of herbicide on reserves of the or-ganic horizon was offset by fertilization when the twotreatments were combined. The negative impact of veg-etation control on CmjC noted in 1990 was no longerevident in 1996; however, microbial activity (as mea-sured by acid phosphatase activity) is still lower in thoseplots. Changes in Cmic/Corg and Cmic/Nmic over time (1990-1996) suggest that litter quality and the soil microbialcommunity have changed during this period. In the veg-etation control plots, the nitrogen cycle has changedfrom a nitrate-dominated cycle in 1989-1990 to an am-monium-dominated cycle in 1996.

Although vegetation control negatively affected cer-tain soil quality indicators, this treatment alone or com-bined with fertilization resulted in the greatest gainsin tree height and DBH, probably because of reducedcompetition for both light and nutrients. Soil fertility

was evidently sufficient to 10 yr, since no foliar nutrientlimitation was evident, except a potential N limitationof white spruce. The responses of soil indicators andtrees are not necessarily synchronized. A negative im-pact of vegetation control on fertility may become moreevident in the trees (especially spruce) later in the rota-tion as nutrient demand increases, or in a second rota-tion, depending on rates of accumulation of reservesduring the current rotation. At 10 yr, the soil indicatorsdo not show a direct relation to current productivity;their real utility will be tested in the long term, as indica-tors of potential productivity losses.

ACKNOWLEDGMENTSWe thank Andre Beaumont, Alain Brousseau, Mathieu

Cote, Real Mercier, and Gina Racine for their assistance inthe field and in the laboratory, and Sylvain Boisclair for helpwith statistical analyses. Thanks to Craig Robinson and SteveD'Eon for continued excellent logistical support at the Peta-wawa Research Forest. Comments by J-F. Boucher, A. Wall-stedt, and R. Ohtonen on an earlier version of the paper weregreatly appreciated. We thank two anonymous reviewers andP. Homann (associate editor) for subsequent comments toimprove the manuscript. Research funding was provided bya grant from the Natural Sciences and Engineering ResearchCouncil of Canada to A.D. Munson.


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ten-year responses of soil quality and conifer growth to silvicultural treatments

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