Aspen Harvest Intensity Decreases Microbial Biomass, Extracellular ...

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Aspen Harvest Intensity Decreases Microbial Biomass, Extracellular Enzyme Activity, and Soil Nitrogen Cycling John E. Hassett and Donald R. Zak* ABSTRACT

bial community composition and function. However, we have an incomplete understanding of how forest harvesting changes microbial community composition and function, and we do not understand how such changes could feed back to influence soil N availability and longterm forest productivity. Forest harvesting changes the quantity and biochemical composition of plant litter, which serves as the primary substrate for microbial activity. Although harvesting may leave an abundance of dead organic matter on the soil surface, inputs of detritus are diminished following this initial substrate pulse, and postharvest residual organic matter represents a biochemically different substrate from the fine roots, leaves, and dead plant tissues composing litter in unharvested forests (Covington, 1981). Such a change in substrate input has the potential to alter the composition of soil microbial communities because bacteria, actinomycetes, and fungi differ in their physiological abilities to metabolize organic substrates contained in plant litter (Paul and Clark, 1996). Forest harvesting has a dramatic effect on soil microclimate, which also may alter microbial community composition and function. As harvest intensity increases and canopy trees are removed, evapotranspiration declines and throughfall increases, resulting in greater soil water availability. In turn, greater soil water availability increases the diffusion of soluble substrates and extracellular enzymes (Griffin, 1981), potentially enhancing rates of organic matter decomposition. Increased incident solar radiation following canopy removal warms soil, which influences the kinetics of microbial enzymes and changes microbial utilization of substrate pools (Stanford et al., 1973; Zogg et al., 1997). These changes in the soil environment can alter microbial access to substrate pools, and may initially increase decomposition and rates of soil N cycling, depending on how forest harvesting has altered the input of organic substrates to soil. Our primary objective was to determine if microbial communities show compositional and functional differences in aspen-dominated ecosystems following harvest of varying intensity. Because tree removal alters microclimate and litter biochemistry, we reasoned that intensive harvest methods would have a greater effect on soil microbial communities than conventional harvest methods (i.e., merchantable bole removal). A secondary objective was to compare the composition and function of microbial communities in forests that have similar vegetation but differ in climatic and edaphic characteristics. Climate and edaphic conditions set limitations on microbial activity (Zak et al., 1994); therefore, we ex-

Forest harvesting alters plant litter inputs to soil and modifies the soil environment, which could alter the composition and function of soil microbial communities. Harvest-induced reductions in microbial activity could eventually feed back to modify soil N availability and forest productivity. We reasoned that increasing harvest intensity should decrease microbial community biomass and function via reduced litter input to soil. We further expected microbial communities to differ in response to harvest intensity in aspen-dominated (Populus tremuloides Michx. and P. grandidentata Michx.) forests located in climatically and edaphically different conditions. To test these ideas, we quantified microbial community composition and function 8 to 10 yr following harvest in two climatically and edaphically distinct aspendominated forests in Michigan. Harvest treatments included control (no harvest), merchantable bole harvest (MBH), total tree harvest (TTH), and total tree harvest ⫹ forest floor removal (FFR). Microbial community composition was quantified using phospholipid fatty acid (PLFA) analysis, and microbial community function was assayed using extracellular enzyme activity and 15N pool dilution. All harvest methods reduced microbial biomass (–24%), the activity of extracellular enzymes involved with litter decomposition (⫺10 to ⫺30%), gross N mineralization (⫺36%), and microbial N immobilization (⫺38%), regardless of climatic and edaphic differences between stand locations. Microbial community composition was not affected by harvest treatment, nor did it differ between locations. Lower rates of extracellular enzyme activity and gross N transformation in harvested aspen stands corresponded with a reduction in microbial biomass, which in turn may be driven by reduced litter input and changes in soil microclimate following clear-cut harvest.

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oil microorganisms control the cycling of C and N in forest soils, and overstory harvesting could alter microbial community composition and function in ways that affect long-term forest productivity (Bradley et al., 2001; Donegan et al., 2001; Seta¨la¨ et al., 2000). The supply of N from soil organic matter most often limits the productivity of temperate forests (Vitousek and Howarth, 1991; Aber et al., 1989), and the rate at which N is released from soil organic matter is controlled by the physiological activity of heterotrophic soil microorganisms (Drury et al., 1991). Important controls on the rates of microbial activity (and hence the supply of N for plant growth) include soil temperature, water availability, and the amount and biochemical composition of plant litter (Paul and Clark, 1996). Because forest harvesting substantially alters the physical environment in soil, as well as the amount and biochemical characteristics of plant detritus, it has the potential to alter micro-

School of Natural Resources & Environment, Univ. of Michigan, Ann Arbor, MI 48109-1115. Received 17 Nov. 2003. *Corresponding author ([email protected]).

Abbreviations: FAME, fatty acid methyl ester; FFR, total tree harvest ⫹ forest floor removal; l-DOPA, l-3,4-dihydroxyphenylalanine; MBH, merchantable bole harvest; MUB, methylumbelliferone; PLFA, phospholipid fatty acid; TTH, total tree harvest.

Published in Soil Sci. Soc. Am. J. 69:227–235 (2005). © Soil Science Society of America 677 S. Segoe Rd., Madison, WI 53711 USA

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SOIL SCI. SOC. AM. J., VOL. 69, JANUARY–FEBRUARY 2005

Fig. 1. Locations of study stands in the Huron and Ottawa National Forests in Michigan’s Upper and Lower Pennisula, USA.

pected that microbial communities in contrasting soils and climates will differ in composition and activity (Priha et al., 1999) and in their response to forest harvest. To address these objectives, we used microbial PLFAs to quantify microbial community composition and biomass, and we employed extracellular enzyme assays and 15N pool dilution to gain insight into litter decomposition and soil N cycling beneath aspen stands that received different harvest treatments. METHODS Study Sites Our research was conducted in two aspen-dominated forest stands; one in the Huron National Forest and one in the Ottawa National Forest (Fig. 1). These study sites are part of the USDA Forest Service Long-Term Soil Productivity (LTSP) research program (Stone, 2001; Tiarks et al., 1997). The sites differ in their climatic and edaphic characteristics (Table 1), but are nonetheless both dominated by mature Table 1. Climate and soil characteristics at two study locations in Michigan. Climate data comes from the National Oceanic and Atmospheric Administration’s climate database for locations near the study sites. Edaphic characteristics were measured in the laboratory. Standard errors are in parentheses. Mean annual temperature, ⴗC Total annual precipitation, cm Texture % Sand % Silt % Clay pH Organic C, g C kg⫺1 Total N, g N kg⫺1 C:N ratio

Ottawa

Huron

5 107 Clay 29 30 41 5.5 43.2 (2.57) 2.5 (0.13) 17 (0.3)

8 70 Sand 90 9 1 5.2 26.1 (2.11) 1.4 (0.09) 18 (0.5)

aspen. The Ottawa stand is situated on a glacial lake plain in Michigan’s Upper Peninsula (46⬚38⬘ N, 89⬚13⬘ W). The soils are Glossic Hapludalfs formed in moderately well-drained calcareous lacustrine clay parent material. Aspens comprised 78 ⫾ 4% (mean ⫾ SE) of the aboveground biomass in the uncut forest; codominant trees include Picea glauca (Moench) Voss (8 ⫾ 4% of aboveground biomass) and Abies balsamea (L.) Mill (12 ⫾ 7% of aboveground biomass). In contrast, the Huron stand resides on a glacial outwash plain in Michigan’s Lower Peninsula (44⬚39⬘ N, 83⬚31⬘ W). Huron soils are Entic Haplorthods formed in well-drained, acidic outwash sand. Aspens represented 84 ⫾ 8% of aboveground biomass; codominant trees at this site are Acer rubrum L. (10 ⫾ 9% of aboveground biomass) and Quercus rubra L. (5 ⫾ 4% of aboveground biomass). The experiment consisted of four harvest intensity treatments arranged in a completely randomized design; each treatment was replicated three times at each location. The harvest treatments varied in intensity of biomass removal: the control was not harvested; MBH removed tree boles, but left slash on the site; TTH extracted entire trees; and FFR consisted of removing all aboveground woody biomass and the forest floor. The FFR treatment was designed to represent intensive harvest practices that substantially disturb the forest floor, in addition to removing all the overstory trees. These four treatments were randomly assigned to three 50- by 50-m plots in each block (n ⫽ 3). Treatments were applied to the Huron site in late January and early February 1992; the Ottawa forest site was harvested in January of 1994. In the summer of 2002, we sampled the woody vegetation and soils in each plot to quantify and summarize their edaphic and vegetative characteristics. Within control plots, we recorded the species, number, height, and diameter at breast height of all trees within a 15-m radius of the plot center. In harvested plots, trees were counted and measured 15 cm above ground level in each of 10 randomly placed 2- by 2-m subplots. Tree diameter and height measurements were used to estimate the aboveground overstory biomass using published allometric regression equations (Roussopoulos and Loomis, 1979; Smith and Brand, 1983; Host et al., 1989; Ter-Mikaelian and Korzukhin, 1997). Soil samples were collected in June 2002 by randomly choosing coordinates to locate 10 points in each plot. At each sample point, we removed the Oi horizon and collected a soil sample using a 1.9-cm-diam. core, which extended to a depth of 10 cm and included Oe, A, and E horizon material. Cores from within a plot were composited in the field, stored on ice for transport to the laboratory, and homogenized by coarse sieving (1-cm mesh) before analyses.

Physical and Chemical Properties of Soil Soils were characterized in the laboratory by analysis of soil texture, pH, organic C, and total N. Soil texture was determined using the hydrometer method (Gee and Bauder 1986). A glass-membrane electrode was used to measure soil pH in a 1:2 soil/deionized water paste. Organic C and total N were determined by dry combustion on a Thermo Flash EA1112 NC elemental analyzer (CE Elantech, Lakewood, NJ) using soil subsamples that had been pulverized using a SPEX CertiPrep 8000M mixer mill (Spex Certiprep, Metuchen, NJ).

Microbial Community Composition Phospholipid fatty acids contained in cell membranes display taxonomically useful variation and can be used to quantify


HASSETT & ZAK: MICROBIAL COMMUNITIES AND ASPEN HARVEST

microbial community composition in soil (Vestal and White, 1989; Zelles et al., 1995; Zelles, 1999). We analyzed PLFAs to gain insight into harvesting effects on the relative proportions of bacteria, actinomycetes, and fungi in soil. The quantity of microbial PLFA is also a function of microbial biomass (Frostega˚rd et al., 1991); therefore, we used total community PLFA C in soil (pg C g⫺1) as a measure of microbial biomass. Fresh soil samples were subsampled and freeze-dried to preserve their PLFA content. Five-gram subsamples of freezedried soil were taken for analysis, to which we added 50 ␮L of a 21:0 standard solution for the calculation of PLFA recovery. Lipids were extracted using a single-phase, phosphate-buffered CHCl3/CH3OH solution, and we separated the polar lipid fraction by silicic acid chromatography. An alkaline system was used to form fatty acid methyl esters (FAMEs). The FAMEs were separated and quantified using an Agilent 6890 Series capillary gas chromatograph (Agilent Technologies, Wilmington, DE) using a 50-m nonpolar column (0.2-mm i.d., 0.11-␮m film thickness) in line with a Finnigan Delta Plus isotope ratio mass spectrometer (Thermo-Finnigan, San Jose, CA). Column temperature was held at 60⬚C for the first 2 min of the analysis, increased to 150⬚C at 10⬚C per minute, and finally increased to 312⬚C at 3⬚C per minute. The injector inlet was maintained at 270⬚C during the analysis. Peaks were resolved using Isodat 6.0 software (Thermo-Finnigan, San Jose, CA) and identified by comparison of peak retention times with those of known calibration standards. We estimated bacterial abundance as the sum of the percentage molar fractions of 15:0, a15:0, i15:0, i16:0, 17:0, a17:0, i17:0, 18:1␻7, cy17:0, and cy19:0 (Frostega˚rd and Ba˚a˚th, 1996). Fungal biomass was estimated as the sum of the percentage molar fractions of 18:2␻6 and 18:1␻9c (Federle, 1986; Frostega˚rd and Ba˚a˚th, 1996). These values were then used to calculate the ratio of fungal to bacterial PLFA.

Microbial Community Function Extracellular Enzyme Activity Soil microorganisms degrade plant litter by synthesizing extracellular enzymes. We used methylumbelliferone (MUB)linked substrates to quantify extracellular enzyme activities in soil, following the methods of Saiya-Cork et al. (2002). The activities of four extracellular enzymes were assayed: 1,4␣-glucosidase, which cleaves ␣-1,4 glycosidic bonds in starch degradation; cellobiohydrolase, which hydrolyzes cellobiose dimers produced during cellulose breakdown, 1,4-␤-N-acetylglucosaminidase, which cleaves ␤-1,4 glycosidic bonds in N-acetylglucosamine (NAG)-containing polymers such as chitin and bacterial peptidioglycan; and phosphatase, which breaks phosphoester bonds and releases inorganic phosphorus. We suspended 1.0 g of fresh soil from each composite sample in 60 mL of 50 mM acetate buffer (pH 5.0), mixed the slurry with a tissue homogenizer (Polytron Devices, Inc., Paterson, NJ), and then diluted it with additional buffer to 125 mL. The suspensions were stored in 125-mL glass screw-cap bottles for up to 30 min before analysis. Sixteen replicates of three separate enzyme assays were conducted on individual 96-well microplates. Assay wells contained 200 ␮L of the soil– buffer solution and 50 ␮L of 200 ␮M MUB-linked substrate. Each plate also contained eight replicates of a blank (buffer only), a 4-MUB standard (buffer plus 50 ␮L of 10 ␮M 4-MUB), a negative control (buffer plus substrate), and a quench standard (soil solution plus 4-MUB standard). Plates were covered and incubated at 25⬚C for 2 or 4 h, depending on the substrate. Following incubation, 25 ␮L of 200 mM NaOH were added to each well to terminate the enzymatic reactions. Fluorescence

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resulting from the cleavage of 4-MUB from utilized substrates was determined with an f-Max fluorimeter (Molecular Devices Corporation; Sunnyvale, CA). Excitation energy was 355 nm and emission was measured at 460 nm. Enzyme activities were reported as nmol 4-MUB g⫺1 h⫺1. We used colorimetric assays to determine the activities of phenol oxidase and peroxidase, which are involved in the degradation of lignin and other polyphenolic compounds. Phenol oxidase and peroxidase activities were measured in transparent microplates (LabSystems, Helsinki, Finland); each contained sixteen replicates of each soil. Assay wells contained 200 ␮L of soil–buffer solution and 50 ␮L of 25 mM l-3,4-dihydroxyphenylalanine (l-DOPA) solution prepared in acetate buffer. There were eight blank replicates for each soil (soil with no substrate), as well as eight replicates of a reference standard (substrate with no soil). For the peroxidase assay, 25 ␮L of 0.3% H2O2 were added to each well to provide the necessary electron acceptor for peroxidase enzymes. Plates were incubated in the dark at 25⬚C for 24 h, and absorbance was read on an EL-800 plate reader (Biotek Instruments, Inc., Winooski, VT) at 450 nm. Activity was reported as ␮mol l-DOPA converted g⫺1 h⫺1. The results of all enzymatic assays were expressed on a dry-weight basis. Specific enzyme activities (enzyme activity per unit microbial biomass) were calculated as the rate of enzyme activity per gram of total community PLFA. Microbial Nitrogen Transformations To quantify microbially-mediated N transformations, we estimated gross rates of N-mineralization, nitrification, and 15 NH⫹ 4 immobilization using the N pool dilution method (Mosier and Schimel, 1993). Twenty grams of fresh soil from each plot was placed in each of four specimen cups and preincubated at 25⬚C for 24 h in a moist incubator. Two samples received 1-mL additions of 89 ␮g mL⫺1 NH4Cl enriched to 1.3 atom% 15N to measure gross mineralization; the other two ⫺1 KNO enriched cups received 1 mL of NO⫺ 3 of 89 mg mL 3 to 1.3 atom% 15N to measure gross nitrification. We immediately extracted exchangeable inorganic N in one 15NH⫹ 4 and one 15NO⫺ 3 –labeled sample with a solution of 2 M KCl (Mulvaney, 1996); the remaining cups were incubated at 20⬚C for 2 d before KCl extraction. The KCl-extracted samples were passed through Whatman No. 2 filter paper, and the extract was refrigerated before isotopic analysis. We determined NH⫹ 4 and NO⫺ 3 in extracts using a Flow Solution 3000 continuous flow analyzer (OI Analytical, College Station, TX). ⫺ In preparation for isotopic analysis, NH⫹ 4 –N and NO3 –N in KCl extracts were collected separately in two stages of diffusion (Brooks et al., 1989). First, MgO was added to convert NH⫹ 4 to NH3, which was trapped as it diffused over glassfiber disks acidified with 10 ␮L of 2.5 M KHSO4. In the second step, the acidified disks were replaced and Devarda’s alloy was used to convert NO⫺ 3 to NH3, which was again trapped by the new acidified disks. Disks were dried in a dessicator, placed in tin capsules, and analyzed for 15N abundance by mass spectroscopy using an NC 2500 elemental analyzer (CE Elantech, Lakewood, NJ) in line with a Finnigan Delta Plus isotope ratio mass spectrometer (Thermo-Finnigan, San Jose, CA). We used the equations of Hart et al. (1994) to calculate rates of gross N mineralization and nitrification; NH⫹ 4 immobilization was calculated by the method of Davidson et al. (1991). We also calculated specific rates of microbial N transformation by dividing N transformations rates by total PLFA.

Statistical Analysis We used a two-way ANOVA for a completely randomized design to test the null hypotheses that location and treatment


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did not affect the composition and function of microbial communities. We used Fisher’s Protected LSD for multiple comparisons to determine where significant differences occurred between treatment means. Data were checked for normality using the Shapiro-Wilkes W test. Significance was accepted at ␣ ⫽ 0.05. We used ANCOVA to determine if there was significant covariance of total PLFA with soil C content, and to determine if there were any differences in PLFA content between treatment plots following adjustment of total PLFA by soil C content. This allowed us to investigate the effect of forest harvesting on microbial community composition and function, while normalizing for differences in soil organic matter content between sites and harvest treatments. The PLFA results also were analyzed using principle components analysis to determine the separation of the microbial communities’ responses to treatment in multivariate space.

RESULTS Aboveground Biomass Aboveground biomass differed significantly between harvest treatments (F ⫽ 32.763, 3 df, P ⬍ 0.001) but not between locations (F ⫽ 0.753, 1 df, P ⫽ 0.753; Table 2). There was no significant interaction of site and treatment (F ⫽ 0.653, 3 df, P ⫽ 0.592). Multiple comparisons of harvest treatment means revealed significant differences between control and harvested plots: the biomass in control plots was 5 to 13 times greater than in harvested plots (Table 2). No significant difference in total aboveground biomass was found between the various harvesting treatments (Table 2). The mean aboveground biomass for treatments displayed a large variance, both in total biomass and in the percentage of biomass dominated by aspens.

Microbial Community Composition Twenty-four FAMEs were identified, and these represented 87% of total PLFA. Recovery of the 21:0 internal standard averaged 91%. Harvest treatments differed significantly in total PLFA content, with total PLFA showing an apparent decline with increasing levels of harvest removal (F ⫽ 4.106, 3 df, P ⫽ 0.024; Fig. 2). Within harvest treatments, the mean PLFA content of the control treatment differed significantly from that of the TTH and FFR treatments. The MBH was not significantly different from the other treatments in PLFA content (Fig. 2). Mean total PLFA was significantly different between locations, averaging 5.60 ng C g⫺1 in Huron forest soil and 11.71 ng C g⫺1 in Ottawa forest soil (F ⫽ 55.091, 1 df, P ⬍ 0.001). There was no significant interaction of harvest treatment and location (F ⫽ 1.202, 3 df, P ⫽ 0.341). Soil carbon content was a significant covariate for total PLFA content (F ⫽ 19.899, 1 df, P ⬍ 0.001). Least

Fig. 2. Mean total phospholipid fatty acid (PLFA) in harvest treatments. Values have been averaged across study sites, and treatments with the same letter did not differ significantly at ␣ ⫽ 0.05. Error bars are standard errors of the mean.

square mean total PLFA C was significantly different between locations (7.12 ng C g⫺1 in Ottawa soils vs. 10.19 ng C g⫺1 in Huron soils; F ⫽ 12.192, 1 df, P ⫽ 0.003). Averaged across locations, least square means also were significantly different between control and all three treatments (Control ⫽ 10.60 ng C g⫺1; MBH ⫽ 8.87 ng C g⫺1; TTH ⫽ 8.12 ng C g⫺1, FFR ⫽ 7.03 ng C g⫺1; F ⫽ 7.123, 3 df, P ⫽ 0.003). Least square mean total PLFA in MBH was significantly different from FFR (P ⫽ 0.035) but did not differ from TTH (P ⫽ 0.361). There was a significant interaction of treatment and location (F ⫽ 5.127, 3 df, P ⫽ 0.012), with the magnitude of differences between least square treatment means being greater in Ottawa soils than in Huron soils. The abundance of 17 identified PLFAs differed significantly between Huron and Ottawa soils; the average change in relative abundance of any single PLFA between locations was 0.1% and was never greater than ⫾ 1.3% (Fig. 3). Averaged across locations, fungal 18:1␻9c was significantly more abundant in control plots (9.76 ⫾ 0.43% of total PLFA) relative to harvested plots (8.47 ⫾ 0.20%; F ⫽ 3.596, 3 df, P ⫽ 0.037). Gram-positive bacterial i17:0 was significantly less abundant in control plots (3.44 ⫾ 0.31%) relative to harvested plots (3.74 ⫾ 0.14%; F ⫽ 4.588, 3 df, P ⫽ 0.017). None of the remaining PLFAs displayed significant differences between treatments averaged across locations (Table 3). No significant interaction of treatment with location was discovered in any of the identified PLFAs. Bacterial PLFA accounted for 41% of total PLFA in Huron and Ottawa forest soils and did not differ significantly between locations (F ⫽ 1.199, 1 df, P ⫽

Table 2. Mean aboveground biomass 8 to 10 yr following harvest treatment in aspen stands in two locations: Control ⫽ no harvest, MBH ⫽ merchantable bole harvest, TTH ⫽ total tree harvest, and FFR ⫽ total tree harvest ⫹ forest floor removal. For each location and treatment, means with the same letter are not significantly different at ␣ ⫽ 0.05. Standard errors are in parentheses. Ottawa

Total biomass, Mg Aspen biomass, %

ha⫺1

Huron

Control

MBH

TTH

FFR

Control

MBH

TTH

FFR

110.6a (12.87) 78 (3.9)

8.5b (2.30) 50 (11.8)

8.3b (2.66) 77 (17.8)

13.9b (3.42) 77 (12.1)

92.3a (27.68) 84 (8.4)

19.9b (2.95) 81 (10.0)

11.3b (4.01) 68 (18.3)

7.6b (2.67) 87 (4.8)

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Fig. 3. The molar fraction of individual PLFAs in Huron and Ottawa forest soils; values have been averaged across harvest treatments. The PLFAs marked with an asterisk (*) differed significantly at ␣ ⫽ 0.05.

0.290) or treatments (F ⫽ 0.468, 3 df, P ⫽ 0.709). Fungal PLFA was 15% of total PLFA, and we found no significant differences between locations (F ⫽ 0.674, 1 df, P ⫽ 0.424) or treatments (F ⫽ 1.719, 3 df, P ⫽ 0.203). Mean fungal PLFA/bacterial PLFA ratio was 0.42 ⫾ 0.035 for control, 0.36 ⫾ 0.035 for FFR, 0.37 ⫾ 0.011 for MBH, and 0.36 ⫾ 0.011 for TTH, and did not differ significantly between treatments (F ⫽ 1.465, 3 df, P ⫽ 0.262) or locations (F ⫽ 0.099, 1 df, P ⫽ 0.757). Principle components analysis did not yield apprecia-

ble separation of treatments or locations from one another (data not shown). The first and second principle component axes accounted for 33.3 and 12.0% of the variation in the data set (data not shown).

Extracellular Enzyme Activity Location had a significant main effect on extracellular enzyme activity, wherein phosphatase, cellobiohydrolase, N-acetylglucosaminidase, peroxidase, and phenol

Table 3. The relative abundance (mole %) of bacterial, actinomycetal and fungal PLFAs in harvest treatments. Means in a row with the same letter are not significantly different at ␣ ⫽ 0.05. Standard errors are in parentheses. PLFA Marker

Control

MBH

TTH

FFR

% Gram ⫹ Bacteria i15:0 a15:0 i16:0 10me16:0 a17:0 i17:0 Gram ⫺ Bacteria 16:1␻5c cy17:0 cy19:0 18:1␻5c 18:1␻7 General Bacteria 16:1␻7c 16:1␻9c Actinomycetes 10me18:0 Fungi 18:1␻9c 18:2␻6 General Eukarya 18:3␻3 22:0

5.28a 3.44a 2.27a 3.39a 1.57a 1.04a

(0.27) (0.31) (0.09) (0.21) (0.14) (0.03)

5.49a 3.67a 2.41a 3.55a 1.54a 1.12b

(0.20) (0.26) (0.08) (0.06) (0.10) (0.02)

5.28a 3.71a 2.41a 3.58a 1.58a 1.12b

(0.37) (0.17) (0.18) (0.22) (0.09) (0.03)

5.43a 3.83a 2.55a 3.66a 1.59a 1.18b

(0.21) (0.31) (0.16) (0.14) (0.12) (0.03)

3.44a 2.27a 9.67a 2.12a 13.01a

(0.20) (0.12) (0.40) (0.10) (0.67)

3.64a 2.17a 8.95a 1.99a 13.13a

(0.13) (0.09) (0.37) (0.09) (0.19)

3.49a 2.14a 9.37a 2.15a 13.41a

(0.15) (0.06) (0.35) (0.11) (0.51)

3.58a 2.08a 9.59a 2.20a 13.26a

(0.23) (0.09) (0.32) (0.15) (0.54)

5.36a (0.18) 1.28a (0.07)

5.41a (0.13) 1.36a (0.06)

5.23a (0.19) 1.33a (0.04)

5.14a (0.27) 1.36a (0.06)

1.21a (0.06)

1.06a (0.06)

1.18a (0.09)

1.21a (0.07)

9.76a (0.43) 7.18a (0.72)

8.40b (0.37) 6.65a (0.53)

8.32b (0.44) 6.43a (0.24)

8.69b (0.28) 6.27a (0.23)

1.24a (0.13) 0.26a (0.03)

1.27a (0.06) 0.26a (0.04)

1.32a (0.08) 0.27a (0.03)

1.28a (0.12) 0.23a (0.04)

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Table 4. Harvest treatment means for extracellular enzyme activity. For each treatment and enzyme, mean activities with the same letter in a row do not differ significantly at ␣ ⫽ 0.05. Standard errors are in parentheses.


Enzyme

Control

MBH

TTH nmol

Phosphatase N-acetylglucosaminidase ␣-glucosidase Cellobiohydrolase Peroxidase Phenol oxidase

487a 84a 2a 28a 2937a 1067a

(60.1) (10.5) (0.7) (10.4) (835.7) (309.8)

oxidase had significantly greater activities in the Ottawa forest relative to Huron (data not shown). Variability in the measurement of ␣-glucosidase activity was large and revealed no significant differences between locations (F ⫽ 0.208, 1 df, P ⫽ 0.657). Averaged across locations, only phosphatase exhibited significant differences in activity between harvest treatments (Table 4), with the control treatment showing activity 30% greater than in the harvested plots. However, there was a nonsignificant trend in the data toward a 10 to 30% reduction in extracellular enzyme activity in harvested vs. control plots. We observed significantly higher specific activities (i.e., activity per unit microbial biomass) in Huron forest

Fig. 4. Mean gross (A) N mineralization and (B) N immobilization in harvest treatments. For each treatment, means with the same letter are not statistically different at ␣ ⫽ 0.05.

360b (38.9) 74a (14.5) 2a (0.2) 23a (5.3) 1835a (240.6) 853a (193.0)

g ⫺1

FFR

h ⫺1 381a 65a 1a 34a 1756a 721a

(26.5) (12.4) (0.4) (8.4) (570.6) (185.2)

356b (61.3) 60a (7.6) 2a (0.3) 19a (6.0) 2698a (748.2) 701a (215.4)

soils for two enzymes: phosphatase (F ⫽ 12.842, 1 df, P ⫽ 0.002) and N-acetylglucosaminidase (F ⫽ 6.140, 1 df, P ⫽ 0.025). No significant differences in specific activity were observed between harvest treatments for any enzyme, nor was there a significant interaction of location and harvest treatment.

Microbial Nitrogen Transformations The interaction of location with harvest treatment had a significant effect on gross N mineralization (F ⫽ 4.315, 3 df, P ⫽ 0.022), and it resulted from a single low rate measurement of 0.98 mg N kg⫺1 d⫺1 in a control plot in the Huron site; the other two Huron control plots had gross N mineralization of 3.04 and 2.21 mg N kg⫺1 d⫺1. Averaged across locations, control plots exhibited significantly greater gross N mineralization (control ⫽ 3.18 mg N kg⫺1 d⫺1; MBH ⫽ 2.18 mg N kg⫺1 d⫺1; TTH ⫽ 2.08 mg N kg⫺1 d⫺1; FFR ⫽ 1.83 mg N kg⫺1 d⫺1; F ⫽ 4.635, 3 df, P ⫽ 0.017). Gross N immobilization also was significantly greater under the control treatment (control ⫽ 4.58 mg N kg⫺1 d⫺1; MBH ⫽ 2.94 mg N kg⫺1 d⫺1; TTH ⫽ 2.99 mg N kg⫺1 d⫺1; FFR ⫽ 2.66 mg N kg⫺1 d⫺1; F ⫽ 9.346, 3 df, P ⫽ 0.001; see Fig. 4). There were no significant differences in gross N mineralization and N immobilization among the 3 levels of harvest intensity. Gross N mineralization averaged 2.60 ⫾ 0.34 mg N kg⫺1 d⫺1 in Ottawa soil and 2.04 ⫾ 0.21 mg N kg⫺1 d⫺1 in Huron soil; these means were not significantly different (F ⫽ 3.976, 1 df, P ⫽ 0.065). However, we found significantly lower mean rates of gross N immobilization in Huron soil (2.91 ⫾ 0.31 mg N kg⫺1 d⫺1) than in Ottawa soil (3.68 ⫾ 0.29 mg N kg⫺1 d⫺1; F ⫽ 7.374, 1 df, P ⫽ 0.015). Gross nitrification averaged 0.08 mg N kg⫺1 d⫺1 in Huron soils and 0.14 mg N kg⫺1 d⫺1 in Ottawa soils, but did not differ significantly across location (F ⫽ 1.693, 1 df, P ⫽ 0.212) or harvest treatment (F ⫽ 1.086, 3 df, P ⫽ 0.383). Nonetheless, mean nitrification rates were highest in control plots (data not shown). Microbial communities in the Huron site displayed greater specific rates of N mineralization (0.37 g N d⫺1 g PLFA C⫺1) vs. the Ottawa site (0.20 g N d⫺1 g PLFA C⫺1; F ⫽ 16.285, 1 df, P ⫽ 0.001). Specific N immobilization also was significantly more rapid at the Huron site (0.55 g N d⫺1 g PLFA C⫺1) relative to the Ottawa site (0.32 g N d⫺1 g PLFA C⫺1; F ⫽ 10.838, 1 df, P ⫽ 0.005). No significant differences were observed in specific N-cycling rates between treatments, nor was there a significant interaction between location and harvest treatment. Across sites and treatments, there was a significant correlation of total PLFA with rates of N mineralization



(r 2 ⫽ 0.61; P ⫽ 0.002) and immobilization (r 2 ⫽ 0.42, P ⫽ 0.041).

DISCUSSION Forest harvesting can alter the quantity and type of organic matter available to the soil microbial community, and it also changes soil microclimate in ways that influence soil microbial activity. Our results demonstrate that clear-cut harvesting of aspen reduced microbial biomass, extracellular enzyme activity, and soil N-cycling, regardless of climatic and edaphic differences between aspen-dominated ecosystems. Lower rates of extracellular enzyme activity and gross N transformations in harvested forest stands result from a reduction in microbial biomass rather than a harvest-induced change in microbial community function. This reduction could result from a decline in plant litter input, a change in microclimate, or both.

Microbial Community Composition Contrary to our expectation that different site conditions might dictate contrasting responses, soil microbial communities at the two sites responded similarly to forest harvesting treatments. Total PLFA C declined with increasing levels of harvest intensity, consistent with the expectation that removal of organic matter causes a decline in microbial biomass. Analysis of covariance confirmed a positive relationship between soil organic matter content and microbial biomass; however, we still found significant differences in microbial biomass between treatments even when they were adjusted for soil organic matter content. Although our results show that there is a relationship between organic matter content and microbial biomass, other factors that differ with intensity of harvest treatment also must reduce microbial biomass in harvested plots. One possible factor is the decrease in litter input following harvest, which reduces the pool of substrates available for microbial metabolism. This could reduce microbial biomass but not alter specific activity (i.e., activity per unit microbial biomass). Harvest-induced changes in soil temperature and water availability also may play an important role, but we are unable to quantify their separate influence in our study. There was a notable decrease in the fungal to bacterial ratio from 0.42 in control plots to 0.36 in harvested plots, albeit this decrease was not significant. This is similar to the result of Siira-Pietikaïnen et al. (2001), who attributed declining fungal biomass in clear-cut Norway spruce [Picea abies (L.) H. Karst.] forests to a decreased concentration of mycorrhizal root tips. If clear-cut harvest reduced live aspen root biomass in this experiment, it seems probable that the biomass of mycorrhizal fungi has also declined, yielding a net decline in total community fungal biomass. Alternatively, removal of mature woody biomass by harvesting might reduce the size of the fungal community by decreasing the relative availability of lignified substrates that favor lignocellulolytic saprophytes. Such a change is consistent with the de-

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crease we observed in the activities of phenol oxidase and peroxidase. Although individual PLFAs differed significantly between the Huron and Ottawa sites, the small difference (⬍1.3%) in abundance of individual PLFAs between sites suggest that microbial community composition was indeed similar. Furthermore, principle components analysis was not able to discriminate between locations, suggesting that the differing environments of the Huron and Ottawa sites do not translate into distinct microbial community compositions, at least as measured by PLFA. From these results, we conclude that the different climatic and edaphic conditions of the Huron and Ottawa forests do not dictate compositional differences between their microbial communities. The lack of large difference in PLFA abundance between these aspen-dominated ecosystems suggests that vegetation type was the major factor determining microbial community composition. This is consistent with Myers et al. (2001), who found distinct differences in microbial community composition, assessed via PLFA, between upland forest ecosystems with similar soil types but different dominant vegetation. In contrast, Bossio et al. (1998) observed that soil type had a greater influence on microbial community composition than vegetation in agricultural systems. Priha et al. (2001) also found distinct differences in PLFA abundance in forest stands with similar vegetation but differing soil types in Finland. These examples illustrate the need to further understand how vegetation, soil, climate, and management history interact to determine microbial community composition and function on local and regional scales.

Microbial Community Function We hypothesized that removal of plant biomass by harvesting would decrease extracellular enzyme activity and N-cycling processes of soil microorganisms, and this expectation was borne out by our results. Extracellular enzymes tended to show lower activity in harvested plots, although the trends we observed were not significant. This generalized reduction in microbial activity was reflected in rates of gross N mineralization and immobilization, which also were lower in harvested plots, and did not differ between treatments of differing harvest intensity. However, specific activity did not differ between treatments for any enzyme or for rates of gross N mineralization and immobilization. Reductions in enzyme activity and N-cycling rates in harvested plots therefore appear to be directly related to a decline in microbial biomass following forest harvest, and do not result from physiological differences between microbial communities in different treatments. All harvest treatments tended to reduce extracellular enzyme activity from 10 to 30%. This is similar to the observations of Waldrop et al. (2003), who found that postharvest treatments (slash, mechanical chipping and piling, and broadcast burning) reduced the activities of extracellular enzymes in the forest floor of mixed-conifer forests in California. In that case, reductions in enzyme activity resulted from changes in soil water potential and in the quantity and biochemical composition of


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litter. Similar mechanisms may be at work in the harvested forests we studied, although our finding that specific enzyme activities did not differ between treatments suggests that enzyme activity also has some relationship with microbial biomass. We found that gross N mineralization was lower in regenerating aspens vs. unharvested aspen forests, and that this change was related to concomitant declines in microbial biomass, extracellular enzyme activity, and soil organic matter content. A similar decline in net N mineralization was observed in aspen clearcuts in southern British Columbia, suggesting that net N mineralization might recover as the microbial community returned to a preharvest condition (Forge and Simard, 2000). Moreover, Hendrickson et al. (1985) also observed that net N mineralization increases with both soil organic matter content and soil respiration. Therefore, we conclude that lower gross N mineralization in our study resulted from harvest-induced reductions in microbial biomass and soil organic matter. Because our study evaluated microbial processes after 8 to 10 yr of ecosystem development, our finding that harvesting decreased gross N mineralization does not conflict with findings of short-term increases in gross and net N mineralization following clear-cut harvest (Hendrickson et al., 1985; Prescott, 1997; Holmes and Zak, 1999). These studies explained increases in N mineralization by a variety of interacting mechanisms: elevated soil temperature, increased soil water, decomposition of root tissue, and microbial mortality resulting from changes in substrate availability. However, aspen’s rapid clonal regeneration preserves a significant percentage (43 to 80%) of live root biomass (DesRochers and Lieffers, 2001). Regenerating aspen also quickly recover leaf area: stands in British Columbia attained leaf area and biomass equivalent to, and exceeding that of mature aspen stands within 5 to 10 yr of harvest (Peterson and Peterson, 1996; Lieffers et al., 2002). For these reasons, the factors that increase gross N mineralization are likely to have been abated by aspen regeneration since the time of harvest in our experiment, even though control plots contained 5 to 13 times the biomass of harvested plots. From this, it is reasonable to conclude that the duration of gross N mineralization enhancement depends on the ability of vegetation to regenerate following harvest, and this conclusion is supported by the findings of many other authors (Hornbeck and Kropelin, 1982; Bormann and Likens, 1979; Duggin et al., 1991; Iseman et al., 1999). These studies have noted that ecosystem succession seems to have a moderating effect on excess net N mineralization and nitrification following harvest. The level of net N mineralization following the initial increase may be higher, lower, or identical to the preharvest level, depending on the interaction of climatic, edaphic, and vegetative factors in the regenerating forest. Future forest productivity will depend on the ability of the soil microbial community to return to the levels of activity that existed before harvesting. If the reduced rates of N cycling we observed are due solely to lower biomass and litter input in harvested stands, and if microbial biomass increases with time, there will be no

long-term effect of harvesting on microbial activity and no net effect on forest productivity. This relationship between soil organic matter content, microbial biomass, and microbial community function has important implications for the management of high-productivity crop trees like aspen. If the length of forest rotations does not allow time for soil organic matter to return to preharvest levels, successive rotations will result in an increasingly depleted soil organic matter pool and reduced microbial biomass, with possible negative effects on microbiallymediated processes that feed back into forest productivity. In conclusion, clear-cut harvesting reduced the biomass and activity of soil microbial communities in aspendominated forest ecosystems, regardless of differences in soil type and climate. Harvest-induced reductions in extracellular enzyme activity and N cycling rates appeared to be related to lower microbial biomass, which in turn was correlated with lower soil organic carbon content in harvested plots. However, microbial biomass was still significantly lower in harvested plots even after accounting for variation in soil organic matter. It is plausible that a change in litter biochemistry or the soil environment is responsible for this effect. However, further information on the biochemical constituents of litter and changes in soil temperature and water availability would be necessary to support this contention. If microbial biomass and activity do not recover as intensely harvested aspen forests regenerate, diminished N availability could limit the productivity of these ecosystems. ACKNOWLEDGMENTS Funding for this study was provided by the USDA Forest Service, North Central Research Station through a collaborative agreement with the Belowground Processes Work Unit (NC-4159), Houghton, MI. We thank Dr. Kurt Pregitzer, Dr. Alex Friend, Dr. Doug Stone, John Elioff, and Forest Service personnel for establishing the experiment, and for the many ways they have assisted us in this endeavor.

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