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DIVISION S-7-FOREST & RANGE SOILS

Ten-Year Responses of Soil Quality and Conifer Growth to Silvicultural Treatments

Centre de recherche en biologie forestière, Faculté de foresterie et de géomatique, Pavillon Abitibi-Price, Université Laval, Sainte-Foy, QC G1K 7P4, Canada

catherine.perie{at}mrn.gouv.qc.ca

	ABSTRACT

TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion Conclusion REFERENCES

 
The development of sustainable 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 silvicultural treatments: scarification, fertilization, and herbicide treatment, applied alone or in combination—on indicators of organic layer quality, foliar nutrition, and tree growth—10 yr after establishment of eastern white pine (Pinus strobus L.) and white spruce [Picea glauca (Moench) Voss] plantations. We compared these 10-yr results with measurements made 3 to 4 yr after plantation establishment. In both 1989 and 1996, the herbicide treatment had the greatest effect on organic layer quality. In 1996, compared with the no-treatment control, herbicide application reduced organic C mass by 46%, total N mass by 15%, and acid phosphatase activity by 64%. These negative effects were offset when herbicide was applied in combination with fertilizer. The negative impact of herbicide on microbial biomass C noted in 1990 was no longer evident in 1996. In herbicide-treated plots, the nitrate-dominated cycle observed 1989–1990 was replaced by an ammonium-dominated cycle in 1996. Although herbicide application negatively affected soil quality, it increased tree growth and generally improved foliar nutrition; thus organic layer and tree responses were not correlated. The indicators used were sensitive to changes in the ecosystem over time and signaled soil impacts that could have consequences for long-term productivity.

Abbreviations: C_mic, microbial biomass C • C_org, organic carbon • DBH, diameter at breast height • F, fertilization • N_mic, microbial biomass N • N_t, total nitrogen • S, scarification • V, vegetation control with herbicide

	INTRODUCTION

TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion Conclusion REFERENCES

 
SUSTAINABLE FOREST MANAGEMENT has been adopted as an objective through both international and national accords, and in Canada, provincial regulations and industrial certification increasingly reflect this context. We consider practices to be sustainable where inherent site productivity is maintained over time. The evaluation of sustainable use of forest resources relies on a system of continuous monitoring of criteria, and more specific and locally defined indicators (Nordin, 1996; Morris et al., 1997). Evaluation of plantation forestry must be an important part of this process; large reforestation efforts in Canada in the last decade mean that more than 4 000 000 ha have been planted, mainly to spruce and pine (Anonymous, 1997). The success rate of these conifer plantations is often limited by competition from non-crop woody and herbaceous vegetation (Walstad and Kuch, 1987). Thus, to inhibit the competing vegetation during plantation establishment, the site is often prepared by scarification and herbicide application (Lepage and Coates, 1993; Richardson, 1993). Scarification also increases soil temperature (Bassman, 1989). Fertilization is applied to enhance the growth of planted trees (Swift and Brockley, 1994; McLaren and Jeglum, 1998).

In 1986 and 1987, a plantation study was established in three major climate zones of Canada, to quantify growth and physiological response of native pine and spruce to factorial combinations of scarification, fertilization, and vegetation control with herbicide (Brand and Janas, 1986). Although these treatments were non-operational in nature (complete removal of organic matter, 6 yr of fertilization and 4 yr of vegetation control), they represent an extreme that is a useful context for monitoring specific indicators of sustainable forest management.

Soil is a key natural resource interacting with aboveground plant and animal communities (Canadian Council of Forest Ministers, 1995), and maintaining site productivity and soil resources are two key international and national criteria for defining and monitoring forest sustainability (Harris and Bezdicek, 1992; Papendick and Parr, 1992). Soil quality may be defined as the capacity of a soil to accept, store, and recycle water, nutrients, and energy, sustain biological productivity, maintain environmental quality, and promote plant and animal health (Doran and Parkin, 1994). Or, in simple terms, soil quality is the capacity (of soil) to function (Karlen et al., 1997). Assessment of the state of soil organic matter is a valuable step towards identifying the overall quality of a soil because organic matter is the primary source of, and a temporary sink for, plant nutrients (Gregorich et al., 1994; Larson and Pierce, 1994; Morris et al., 1997). To evaluate soil organic matter quality, Gregorich et al. (1994) proposed a number of indicators, including organic C (C_org), total N (N_t), soil carbohydrates, light fraction and macroorganic matter, microbial biomass C (C_mic) and N (N_mic), and finally, enzyme activities. We used a subset of these indicators to assess impacts of forest practices 10 yr after plantation establishment.

The present study is revisiting treatments that were first assessed 3 to 4 yr after plantation establishment and are now being reassessed 10 yr after establishment. The objectives of the study were to evaluate treatment impacts on organic layer properties and fertility, as well as foliar nutrition and growth of planted trees. By measuring these over time (3–4 yr and 10 yr) we are able to monitor changes in ecosystem function and development after disturbance related to different single and combinations of silvicultural treatments. By comparing each treatment with a harvest-only control, we can note if this function and development differ from a more natural process of recovery after disturbance.

	Materials and methods

TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion Conclusion REFERENCES

 
Site Description and Experimental Design
The experimental site is in central Ontario, Canada, on the north shore of Cartier Lake (45°57'50'' N, 77°34'45'' E; 170 m above sea level) within the Petawawa Research Forest. It is in the Middle Ottawa Section of the Great Lakes–St. Lawrence Forest region (Rowe, 1984). The underlying bedrock is Precambrian granite and gneiss, and the soil is a deep, well-drained loam to sandy-loam, classified as an orthic humoferric podzol or Haplorthod (Soil Classification Working Group, 1998). The regional climate is moist-humid (Hills, 1959), with annual precipitation of 800 mm. Mean daily maximum temperatures are recorded in July (25.4°C) and minimum temperatures in January (-18.4°C). The site supported a mature mixed wood stand as described by Brand and Janas (1988), before being 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 undisturbed post harvest condition. Scarification (S1) represented removal of logging debris and forest floor organic material by blade scarification. Fertilization at Level 1 (F1) represented an annual application of Osmocote, which is a slow-release temperature-dependent fertilizer (17:16:10 NPK plus micronutrients with 9.1% NH⁺₄–N and 7.9% NO^-₃–N). Fertilizer was applied each year for 6 yr; 30 g of fertilizer were placed around each tree in the first growing season, increasing to 200 g per tree in the sixth growing season (40, 60, 80, 135 g from Year 2–5). Vegetation control at Level 1 (V1) represented the annual removal of competing vegetation with the herbicide glyphosate [N-(phosphonomethyl) glycine] applied at 2.0 kg ha^-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 experimental plots. Half of each 20- by 40-m plot was planted with white pine and half with white spruce; 100 3-yr-old bare-root seedlings per species were planted at 2- by 2-m spacing in April 1986.

Soil Sampling and Analyses
A 30-m transect was randomly laid out within each experimental plot, parallel to the longest side of the plot. The transect extended into areas of both seedling species. Five sampling locations were randomly distributed along each transect. Organic layer samples consisting of all organic matter above the mineral soil surface were collected at each sampling location of S0 treatments in May and August 1996 and composited by plot. Organic layer depth was measured at the same time. There was insufficient organic layer in S1 treatments to collect and analyze. Fresh organic matter pH was measured according to McLean (1982). Water content was determined by drying subsamples at 105°C for 48 h before weighing. Organic matter was measured gravimetrically by loss on ignition (Gallardo et al., 1987). The organic matter was converted to organic C (C_org) by a conversion factor of 0.56 (Nelson and Sommers, 1982). Total N was analyzed with a Tecator 1030 Macro-Kjeldahl Analyzer (Hoganas, Sweden). Total elements (P, K, Ca and Mg) were measured by inductively coupled plasma emission (Perkin-Elmer Instruments, Norwalk, CT) after complete digestion in HNO₃, HClO₄, and HF in Teflon beakers (Lim and 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 coupled plasma emission. Available P was determined by the Bray II method and was analyzed with an Automated Ion Analyzer (Lachat QuickChem 8000, Zellweger Analytics Inc., Milwaukee, WI).

Carbohydrates were extracted by shaking 2 g of air-dried organic layer (250 µm–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 which the supernatants were re-centrifuged at the same speed. Glucose, fructose, mannose, inositol, cellubiose, and sucrose were analyzed 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. Injection volume was 10 µL and flow was set up to 0.5 µL min^-1. Separation was performed at 90°C and the temperature of the refraction index detector (Hewlett Packard 1047A, Palo Alto, CA) was 40°C. The values of individual carbohydrates were summed to yield total hot-water-soluble carbohydrates.

The buried polyethylene bag technique was used to evaluate nitrogen mineralization rates in situ (Eno, 1960; Zou et al., 1992) at five locations per plot. Soil cores were prepared by hammering sharpened polyvinylchloride pipes (height =10 cm, diameter =7 cm) into the soil, keeping the organic layer and surface mineral soil intact. The two horizons were separated and the organic layer was transferred from the tube into a polyethylene bag. The bag was then sealed, buried in the same hole and covered with a 2-cm-deep litter, and incubated for 22 wk (27 May–22 October 1996). In May 1996, a second set of cores was sampled to determine initial levels of inorganic nitrogen (NH⁺₄ plus NO^-₃). Inorganic N was extracted in the field according to Van Miegroet (1995). The filtrates were frozen before NH⁺₄–N and NO^-₃–N were quantified by a Lachat Automated Ion Analyzer.

In August 1996, microbial biomass C (C_mic) and N (N_mic) were determined on organic layer samples for all treatments except scarification by the fumigation-extraction procedure (Brookes et al., 1985). The samples were processed in the laboratory within 48 h. Values of extractable-C and -N were obtained 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 of extractable organic C were made with a compact C titrator (Mettler DL20, Mettler-Toledo, Inc., Worthington, OH) and analyses of the soluble organic N were made with the Tecator 1030 Macro-Kjeldahl Analyzer. A k_EC-factor of 0.38 (Vance et al., 1987) was used for converting extractable-C flush to C_mic , and a k_EN-factor of 0.45 (Brookes et al., 1985; Jenkinson, 1988) was used for the conversion of extractable-N flush to N_mic. Acid and alkaline phosphatase activities were determined according to Jordan et al. (1995). The biomass C to biomass N ratio (C_mic/N_mic) was estimated on the basis of these data, and the ratio of microbial biomass C to total soil organic C (C_mic/C_org), and microbial biomass N to total soil organic N (N_mic/N_t) were estimated from data from basic soil analyses.

All data are expressed on an oven-dry basis and are converted into a mass per hectare of soil using the measured bulk density values. In May 1996, bulk density was estimated by sampling the organic layer from volumetric cores (height = 10 cm, diameter = 7 cm). The samples were dried at 105°C for 48 h before weighing.

Growth, Foliar Sampling, and Analyses
In October 1996, five white spruce and five white pine trees per plot were randomly chosen, and tree height as well as diameter at breast height (DBH) were measured. Within the upper one third of the live crown of each tree, three subsamples of the current year's foliage were collected from three lateral branches. The foliage samples from each plot were pooled by species and dried at 65°C for 48 h. The dry mass of current needles (grams per 100 needles) was measured and recorded for each composite sample. The dried needles were ground (0.42 mm), and digested in H₂O₂–H₂SO₄–Se. Total N, P, and cations were quantified as described earlier. The effects of silvicultural treatments on nutrient status were analyzed using the vector analysis technique (Timmer and Stone, 1978; Munson et al., 1993). The technique permits simultaneous comparison of needle dry mass, nutrient concentration, and nutrient content. On the basis of the magnitude and direction of vectors describing response to treatment in terms of these three variables, analyses can be used to diagnose nutrient status: sufficiency, deficiency, luxury consumption, toxicity, and antagonism. All the data were expressed on a leaf dry weight basis.

Statistical Analyses
Organic layer properties (except N_t and acid phosphatase activity) were analyzed with a three-factor ANOVA containing the following terms and their associated degrees of freedom: block, 3; F, 1; V, 1; F x V, 1; and error 9. The error term consisted of all block interaction terms, under the assumption 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 their associated degrees of freedom: block, 3; C_org, 1; F, 1; V, 1; F x V, 1; and error 8. The error term consisted of all block interaction terms, under the assumption of no interaction between blocks and other factors. Analysis of organic layer properties excluded scarification, because organic layers of these plots were too thin to sample. Tree growth data were analyzed using a four-factor ANOVA containing the following terms and 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 error 21. The error term consisted of all block interaction terms, under the assumption of no interaction between blocks and other factors.

Homogeneity of variance and normality of the distribution of all data were verified and data that were not homogeneous were natural log transformed prior to analysis. Pearson linear correlations were based on plot means, and were performed using data from all treatments and replicates (n = 16 without scarified plots and n = 32 with scarified plots). Ratios were analyzed by the adjusted ratio method according to Bauce et al. (1994). To evaluate relative recovery of soil after disturbance, a Dunnett's test was used, comparing single treatments and treatment combinations with the control plot . All the statistical analyses were performed by SAS programs (SAS, 1989).

	Results

TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion Conclusion REFERENCES

 
Chemical Properties of the Organic Layer
Fertilization and vegetation control treatments did not have an effect on depth of the organic horizon, and the average depth was 3.5 cm. On scarified plots, the organic horizon was present on only 30% of the plot area, with an average depth of 0.4 cm. The pH of the organic matter was also unaffected by treatments after 10 yr. Bulk density was significantly reduced by the fertilization treatment (Table 1) . With the exception of C_org and total P, the amounts of total elements were not altered by the applied treatments (Table 1). The fertilization and vegetation control treatments interacted to affect . When either fertilization or vegetation control was applied alone, C_org content of the organic layer decreased, but when the two treatments were combined, there were no significant changes in C_org levels, compared with the control plot. The same scenario was observed for total P (Table 1); total P was significantly reduced by vegetation control alone but when vegetation control was combined with fertilization there was no difference from the control plot. The N_t and the C/N ratio of the organic matter were not affected by silvicultural treatments (Table 1). Fertilization significantly increased available Ca; other available nutrients were not affected by the treatments (Table 1). All the available elements were positively correlated with total elements . Carbohydrates in the organic layer were not affected by the silvicultural treatments and the mean value of total hot-water-soluble carbohydrates was 270 kg ha^-1 (2.5 mg g^-1). Carbohydrates were positively correlated with organic carbon, C_mic and acid phosphatase activity of the organic layer (Table 2) .

View larger version (23K): [in this window] [in a new window]   Fig. 1 Effects of vegetation control (Dunnett's test; alpha = 0.10) on Corg, Nt and phosphatase activity of the organic layer

Microbial Biomass Carbon, Microbial Biomass Nitrogen, and Acid and Alkaline Phosphatase Activities
Fertilization and vegetation control treatments interacted to influence C_mic and N_mic contents (Table 3) . Vegetation control reduced both C_mic and N_mic whereas fertilization decreased C_mic and tended to reduce N_mic. However, when fertilization and vegetation control were combined, N_mic increased to levels similar to those of the control plot, while C_mic increased to a lesser degree (Table 3). C_mic and N_mic averaged 235 kg ha^-1 and 41 kg ha^-1, respectively. C_mic and N_mic were positively correlated with each other (Table 2). The C_mic to organic carbon ratio (C_mic/C_org), N_mic to total nitrogen ratio (N_mic/N_t), and C_mic to N_mic ratio (C_mic/N_mic) were not influenced by silvicultural treatments (Table 3). Alkaline phosphatase activity was greater than acid phosphatase activity. The applied treatments had no effect on the alkaline phosphatase activity; however, vegetation control markedly reduced acid phosphatase activity (Table 3; Fig. 1). Alkaline and acid phosphatase were both significantly correlated with C_mic and N_mic and the correlation was strongest for C_mic (Table 3).

View larger version (19K): [in this window] [in a new window]   Fig. 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

View larger version (20K): [in this window] [in a new window]   Fig. 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 (V0) measured in 1989 was adjusted to 100 for comparison with the nitrogen status of trees of the same plots measured in 1996. Nitrogen status of trees of plots with vegetation control (V1) measured in 1989 was adjusted to 100 for comparison with the nitrogen status of trees of the same plots measured in 1996

View larger version (20K): [in this window] [in a new window]   Fig. 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 adjusted to 100 for comparison trees on treated plots (V = vegetation control, S = scarification; 0 = no treatment applied, 1 = treatment applied)

Growth Parameters
White pine tree height was increased 10% by scarification (Table 4). The vegetation control and fertilization treatments interacted to affect the height of white pine. Fertilization alone reduced height, while greatest height was achieved when vegetation control was combined with fertilization (4.7 m). Effects of scarification and vegetation control on DBH interacted (Table 4). Scarification alone and vegetation control alone increased DBH compared to the control and when scarification and vegetation control were combined, DBH was up to four 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 by almost 200%. Vegetation control and fertilization interacted to affect height; height increased in response to both treatments, but to a lesser extent following fertilization, and to the greatest extent in response to the two treatments combined (almost 70%, 4.6 m).

	Discussion

TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion Conclusion REFERENCES

 
Impacts on Organic Layer Nutrient Status and Microbial Biomass
Measurements of soil properties and processes over time, as well as tree growth and nutrition, allowed us to discern changes in the ecosystem resulting from different silvicultural treatments, and the recovery relative to a harvested control. In 1996, as in 1989, the pH of the organic layer was not influenced by silvicultural treatments, but the average pH value increased from 5.2 (Munson et al., 1993) in 1989 to 5.5 in 1996. This increase could be due to the considerable development of deciduous trees and herbs in plots where herbicide was not applied. Total and available P, K, Ca, and Mg contents of the organic layer were in the same order as those measured by Burgess et al. (1995) in 1992.

Because the depth of the organic layer is decreasing over time, from an approximate 6-cm depth in 1986 (at time of plantation, Brand and Janas, 1986) to a 3.5-cm depth measured in 1996, impacts on C_org and N_t reserves (t ha^-1) are important. Herbicide applications strongly decreased C_org reserves; this decrease is evident both in comparison to the control (Fig. 1), but also over time. In 4 yr (1992–1996), control plots had lost 13% of C_org reserves while vegetation control plots had lost 46% (data from Burgess et al., 1995). In 1992, N_t reserves in control and herbicide-treated plots were not significantly different (Burgess et al., 1995); however, in 1996, N_t reserves were markedly lower (15%) in herbicide-treated plots (Fig. 1). Even though C_org and N_t reserves decreased in response to the vegetation control treatment (Fig. 1), the C/N ratio was not influenced by the silvicultural treatments and the mean value of the ratio was stable over time, i.e., 21 in 1989 (Munson et al., 1993) and 22 in 1996. The total amount of litter added annually to the organic layer in vegetation control plots was not statistically different from that added to control plots (Munson, 1999, personal communication) but the composition of the litter was markedly different. The litter of the control plots was dominated by deciduous leaves (83%) while that of vegetation control plots was dominantly needles (97%). Normally, mean residence time of the latter material is longer than that of deciduous litter (Waring and Running, 1998); however, microclimate appears to be the main factor influencing organic matter dynamics. Higher soil temperatures and moisture level observed in the vegetation control plot (Brand and Janas, 1988; Munson et al., 1993; Boucher et al., 1998) appear to have accelerated decomposition rates of the organic matter present before harvest, decreasing the depth of the organic layer, and thus the C and nutrient reserves, especially N.

In 1990, the vegetation control treatment reduced C_mic in the organic horizon. This effect was no longer evident in 1990, indicating a recovery of C_mic relative to the control treatment. However, acid phosphatase activity in the organic layer was reduced by 64% (compared with control), indicating that microbial activity is still affected by the intensive herbicide application. In these slightly acid soils, acid phosphatase activity is likely to be more sensitive than alkaline phosphatase activity (Tabatabai, 1994). The C_mic concentration in the organic horizon has tended to decrease over time in all situations, most markedly in the plots without vegetation control (Fig. 5) . This may be related to changing microclimate, i.e. colder soils with canopy closure in these plots, and to changes in litter quality. The C_mic/C_org ratio also decreased from an average of 1.9 and 1.6% in control and vegetation control plots in 1990 to 1.2 and 1.5% in the same plots in 1996, supporting the hypothesis of reduced litter quality as the plantation ages. Bauhus et al. (1998) also noted a decrease in this ratio with increasing age of mixed-wood boreal stands. On the other hand, N_mic tended to increase over time (Fig. 5), indicating immobilization in microbial biomass as a stronger sink in the 10-year-old plantations compared to 5-year-old plantations. The mean value of N_mic/N_t measured in 1996 (4.4%) was smaller than an average for organic layer data (6.6%) compiled by Bauhus and Khanna (1999) and also lower than ratios noted for natural, mature forests in the southern boreal (Bauhus et al., 1998), north of the study site. The mean value of C_mic/N_mic ratio measured 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 microbial biomass. These values are lower than those measured by Ohtonen et al. (1992), suggesting a change in the population structure of the microbial community since 1990 (Wheatley et al., 1990). The strong correlation observed in 1996 between C_mic and C_org was probably due to carbon limitation caused by the soil organic matter quality (Bauhus and Khanna, 1999). The mean value of C_mic/C_org ratio (1.3%) was slightly lower than the ratio of 1.8% observed by Bauhus and Khanna (1999) as a mean value for a wide range of organic layer substrates.

View larger version (24K): [in this window] [in a new window]   Fig. 5 Microbial biomass C (Cmic) and N (Nmic) concentrations of organic layer in nonfertilized (F0), and fertilized plots (F1) without vegetation control (V0) or with vegetation control (V1); measured 4 and 10 yr after conifer plantation establishment. 1990 data were adapted from Ohtonen et al. (1992)

View larger version (23K): [in this window] [in a new window]   Fig. 6 Net nitrate and ammonium production by field incubation of organic layer in nonfertilized (F0), and fertilized plots (F1) without vegetation control (V0) or with vegetation control (V1); measured 3 and 10 yr after conifer plantation establishment. 1989 data were adapted from Munson et al. (1993)

Although vector analysis indicated some relative treatment differences, foliar nutrient concentrations varied little between treatments for both species (Table 4). Nutritional differences are now likely to be expressed in total foliar mass as well as at the leaf level (Munson and Timmer, 1995). The positive response of both species to vegetation control indicates the response to increased light during this phase of plantation development (Boucher et al., 1998); however, there was also an earlier foliar nutritional response to vegetation control (Munson et al., 1993) and response to increased water availability (Boucher et al., 1998). As noted previously (Munson et al., 1993; Burgess et al., 1995), white pine is still outgrowing white spruce; however, this may change following observed repeated attacks of the white pine weevil [Pissodes strobi (Peck)], especially in the open conditions created by herbicide application. These attacks may continue until 20 yr of age (Boulet, 1999).

	Conclusion

TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion Conclusion REFERENCES

 
The impact of silvicultural treatments on organic matter quality indicators was still important 10 yr after harvest and subsequent disturbance by the different treatments. Organic layer chemical properties such as C_org and N_t, as well as biological properties such as C_mic, N_mic or phosphatase activity and net N mineralization, were useful indicators to monitor soil perturbations and ecosystem recovery because they were sensitive and easy to measure. In both 1989–1990 and 1996, vegetation control had the most impact on both soil quality indicators and tree response. In 1996, herbicide application decreased organic layer reserves, especially C_org and N_t; this negative effect of herbicide on reserves of the organic horizon was offset by fertilization when the two treatments were combined. The negative impact of vegetation control on C_mic noted in 1990 was no longer evident in 1996; however, microbial activity (as measured by acid phosphatase activity) is still lower in those plots. Changes in C_mic/C_org and C_mic/N_mic over time (1990–1996) suggest that litter quality and the soil microbial community have changed during this period. In the vegetation control plots, the nitrogen cycle has changed from a nitrate-dominated cycle in 1989–1990 to an ammonium-dominated cycle in 1996.

Although vegetation control negatively affected certain soil quality indicators, this treatment alone or combined with fertilization resulted in the greatest gains in tree height and DBH, probably because of reduced competition for both light and nutrients. Soil fertility was evidently sufficient to 10 yr, since no foliar nutrient limitation was evident, except a potential N limitation of white spruce. The responses of soil indicators and trees are not necessarily synchronized. A negative impact of vegetation control on fertility may become more evident in the trees (especially spruce) later in the rotation as nutrient demand increases, or in a second rotation, depending on rates of accumulation of reserves during the current rotation. At 10 yr, the soil indicators do not show a direct relation to current productivity; their real utility will be tested in the long term, as indicators of potential productivity losses.Rowe 1972

	ACKNOWLEDGMENTS

 
We thank André Beaumont, Alain Brousseau, Mathieu Côté, Réal Mercier, and Gina Racine for their assistance in the field and in the laboratory, and Sylvain Boisclair for help with statistical analyses. Thanks to Craig Robinson and Steve D'Eon for continued excellent logistical support at the Petawawa Research Forest. Comments by J-F. Boucher, A. Wallstedt, and R. Ohtonen on an earlier version of the paper were greatly appreciated. We thank two anonymous reviewers and P. Homann (associate editor) for subsequent comments to improve the manuscript. Research funding was provided by a grant from the Natural Sciences and Engineering Research Council of Canada to A.D. Munson.

Received for publication May 28, 1999.

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TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion Conclusion REFERENCES

 

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