Wood decomposition over a first-order watershed: Mass loss as a function of lignocellulase activity

Soil Bid. Biochem. Vol. 24, No. 8, pp. 143-749,

0038-0717/92 WI0

1992

Printed in GreatBritain. All rightsreserved

WOOD DECOMPOSITION OVER A FIRST-ORDER WATERSHED: MASS LOSS AS A FUNCTION OF LIGNOCELLULASE ACTIVITY R. L. SINSABAUGH,R. K. ANTIBUS,A. E. LINKINS,C. A. MC~LAUGHERTY, L. RAYBURN, D. REPFXTand T. WEILAND Biology

+ 0.00

Copyright 0 1992Pcrgamon PYZSS Ltd

Clarkson University, 10

NY 13699, 1992)

Summary-Because plant litter is directly mediated by enzymes, analyses of dynamics of activity may clarify that rates to quality to temperature, and nutrient availability We investigated this by placing of white ice-cream sticks at upland, riparian and sites on forested watershed northern New For 3 samples were for mass protein, nitrogen and phosphorus accumulation and activity of classes of enzymes involved in degradation and nutrient cycling. Despite considerable heterogeneity both and between rates were closely related the activity of

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R. L. SINSABAUCH et

(Be&la poplifolia) and Prunus sp. also present. There was little understory development. Basal stem area was estimated 12.6 m2 ha-’ at the upland deciduous 1 site, which had a S.E. aspect, and 14.5 m2 ha-’ at the upland deciduous 2 site, which had a N.E. aspect. Because these sites were located on a ridge, the soils were shallow, rocky and undifferentiated. Based on texture analysis, they were classified as silty clay loams with an average composition of 9% sand, 58% silt and 33% clay. Organic matter content averaged 30% and bulk pH was 5.0 & 0.4 (SD). The two hemlock (Tsuga canadensis) sites were monoculture stands, one with a S.E. aspect and the other a N.W. aspect. Estimated basal stem area was 35.6m2 ha-’ at both sites. The soil was classified as silt loam with an average texture of 33% sand, 55% silt and 12% clay. The organic horizon was 2-3 cm deep with an organic matter content of 60-85%; the A horizon material was about 15% organic matter. Bulk soil pH averaged 4.9 + 0.4. One of the riparian sites was associated with a mixed deciduous overstory and the other with a hemlock overstory. Cover estimates were 12.6 and 35.6 m* ha-‘, respectively. Ground cover included mosses and ferns. During the study period, these riparian sites were flooded for brief periods in the spring and autumn. The stream, Pegs Run, has a mean channel width of i-2 m and a basal discharge of about 10 1s-’ which is regulated by a beaver impoundment about 200 m upstream. The water was brown (0.D.Z54 = 0.4-0.6) with a pH slightly above neutral (ca 7.5) and a total carbonate alkalinity of about 1.7 mequiv 1-l. The mean gradient over the sample reach was 0.0225 (2.9%). The substrata consisted largely of sand and silt with scattered boulders, cobbles and debris dams. Water temperature varied from 0 to 20°C over an annual cycle. Sample preparation

White birch (Betulapapyfera) ice-cream sticks were obtained from a commercial supplier. The sticks were sorted by weight and a small hole was drilled at one end. Sampling units were prepared by stringing 10 sticks on a loop of monofilament nylon line. The mass of each unit was recorded, corrected for moisture and ash content and affixed to the sample loop with an aluminum tag. At each field site, approx. 100 sampling units were attached to a nylon cord and arranged in a linear array. The sampling units were unconfined and readily accessible to invertebrates. Fiber analysis of the birch sticks yielded an estimated composition of 5% extractable substances, 79% acid-soluble carbohydrates (holo~ll~ose), 15% acid-insoluble substances (lignin) and 0.2% ash. Total Kjeldahl N was about 200 pg g-r dry mass and total P approx. 40 pg g’ dry mass. Analyses by Wong et al. (1988) indicate that the holocellulose fraction was approx. 60% cellulose and 40% xylan.

al.

Sample processing

The sampling units were placed on 30 October 1987. Eight sample collections, at approx. 4 month intervals, were made over 32 months. On each date, five sample units were collected from each of the eight sites. Six sticks from each sampling unit were rinsed, oven dried at 50°C and weighed to obtain preliminary mass loss data. To correct for moisture and ash, two of the six sticks were dried at 105°C weighed and ashed. Enzyme assays

Four sticks from each sampling unit were used to assay enzyme activities. These sticks were rinsed, broken into fragments, pulverized in a water-cooled mill, suspended in acetate buffer (50 mM, pH S), polytron and homogenized in a Brinkmann centrifuged. Both the supernatant (extract) and the pellet were retained for enzyme assays. Each extract and pellet was assayed for 11 enzymes involved in ligno~llulo~ d~omposition and N, P, S recovery. However, only data from the six lignocellulose assays are presented here: fl- 1,4-glucosidase (EC 3.2.1.21), fl-1,4-endoglucanase (endocellulase, EC 3.2.1.4), /I-1,4-exoglucanase (exocellulase, EC 3.2.1.91), /I-xylosidase (EC 3.2.2.37), phenol oxidase (EC 1.10.3.2 and 1.14.18.1) and peroxidase (EC 1.11. I .7). There were four analytical rephcates and duplicate controls of each extract and pellet assay. All assays were conducted at 20°C in pH 5 acetate buffer. Enzyme activities, except endocellulase, were expressed as pmol substrate converted h-’ g AFDM-’ (g ash-free dry mass). Phenol oxidase activity was determined by mixing 1.Oml of extract with 1.0 ml of 10 rnM L-dihydroxyphenylalanine (DOPA) (prepared in acetate buffer) in a cuvette. Buffer-diluted extract is used as the control. Peroxidase activity was determined concurrently by mixing 1.0 ml extract, 1.0 ml L-DOPA solution and 0.1 ml 0.3% HZOZ in a cuvette. Bufferdiluted extract with 0.1 ml of 0.3% Hz02 was used as the control. All cuvettes are placed in a scanning spectrophotometer and the optical density (O.D.) at 460 nm was recorded for 30 min. Peroxidase activity was calculated as the activity difference between samples reacted with or without HtO,. Bound phenol oxidase activity was estimated by assaying pellet suspensions. Pellet suspension (2 ml) was combined with 2 ml of L-DOPA solution in a 5 ml polypropylene test tube. Control tubes received 2ml of buffer. Bound peroxidase activity was similarly assayed, the only difference being the addition of 0.2 ml of H,O, to the controls and to the samples. The test tubes were capped and tumbled for in a platelet mixer. After the 1 h at 3 revmin-’ reaction, they were centrifuged and 1 ml of supernatant was withdrawn for determination of O.D. at 46Onm.

Wood decomposition and lignocellulase activity Exocellulase activity was estimated as the rate of generation of glucose from microcrystalline cellulose (MCC). The assay mixture contained 2 ml of extract or pellet suspension and 2ml of 2% MCC in a test tube. A drop of toluene was added to each tube to inhibit microbial glucose assimilation. The tubes were kept at 20°C for 18 h with continuous tumbling. After incubation, the tubes were centrifuged and 1 ml of supernatant was withdrawn for determination of reducing sugar concentration using the NelsonSomogyi assay (Nelson, 1944). To maximize the sensitivity of the assay, controls were prepared by mixing 2 ml of sample and 2 ml of MCC in a test tube, centrifuging immediately (rather than after 18 h), then removing 1 ml of supernatant. This procedure increases sensitivity by allowing reducing sugar generated from sample particles to be included in the activity estimate. We use this assay to estimate exocellulase activity because the rate of degradation of crystalline cellulose is related to exocellulase activity and the reaction products quantified are generated either directly or indirectly from exocellulase; however, this assay is not specific for exocellulase activity because the hydrolysis of crystalline cellulose requires interaction between exo- and endocellulase (Eriksson and Wood, 1985). Endocellulase activity was determined by the rate of viscosity decrease in a mixture containing 0.4 ml of extract and 0.8 ml of 2% carboxymethyl cellulose (CMC) using the method of Almin and Eriksson (1967). Bound activity was estimated by incubating 1 ml of pellet suspension with 2 ml of CMC solution. After reaction. the tubes were centrifuged and the viscosity of the supernatant determined by fall velocity in a small bore pipette. Activity was reported in units proportional to absolute activity. The substrates for the p-glucosidase and B-xylosidase assays were p nitrophenyl (pNP) j -D-ghCOpyranoside and pNP-/I-xylopyranoside, respectively. For soluble activity, 1 ml of extract was mixed with 1 ml of 10m~ pNP substrate solution and reacted for 4-6 h. The reaction was terminated by addition of 0.2 ml of 1.ON NaOH. Solution volume was brought to lOm1 with distilled water and O.D. measured at 410 run. Controls for extract and substrate color were processed in parallel. Bound activity was determined by reacting 2 ml of pellet suspension with 2 ml of pNP substrate in a test tube with continuous tumbling. After incubation, the tubes were centrifuged and 2 ml of supernatant removed. These 2 ml aliquots were processed in the same manner as the extract assays.

0

0.2

745

0.4

0.8

0.8

1

Cumulalb Frequency Fig. 1. Cumulative frequency distribution of zero-order mass loss constants expressed as g mo-’ (mo = 30.4d) for white birch sticks decomposing at upland deciduous, upland hemlock, riparian and lotic sites (n = 80 per site).

frequency distributions of these rate constants by site (Fig. 1). Variation in mass loss rates was highest at the upland deciduous sites and lowest in Pegs Run. Variation also existed at larger scales (Fig. 2). After an initial lag of several months, mean mass loss rates were generally linear with the highest average rate occurring at the upland deciduous sites, k = 0.38 g AFDM mo-’ (mo = an average month of 30.4 d), and the lowest at the riparian sites, k = 0.14 g AFDM mo-I; the corresponding rates for the lotic and upland hemlock sites were 0.23 and 0.29 g AFDM mo-‘, respectively. The highest mass losses recorded for individual samples were 89.4,84.4, 62.8 and 47.2% at the upland deciduous, upland hemlock, lotic and riparian sites, respectively. No seasonal differences in mass loss rates were evident. Enzyme activities

The activities of lignocellulose-degrading enzymes generally increased through time, with no consistent seasonal pattern (Figs 3-7). Ratios of bound (pelletassociated) to total (extract + pellet) activity (B/T) varied among enzymes but not spatially or temporally. Pooling the data from all samples, the mean B/T activity ratios were: endocellulase 0.44 & 0.01 (SE, n = 320), B-glucosidase 0.67 f 0.01, /3-xylosidase 0.68 + 0.01, exocellulase 0.74 + 0.01,

RESULTS

Mass loss

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40

Considerable small scale variation in mass loss rates existed within nominally uniform sites. We calculated a zero-order rate constant, assuming a simple linear relationship between mass loss and time, for each sample collected and plotted the cumulative

20

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. 12

10

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22

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Fig. 2. Mean mass loss with time for white birch sticks decomposing at upland deciduous, upland hemlock, riparian and lotic sites, n = 10 for each point.

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R. L. SINSABAUGH et al.

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Hemlock

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Riparian

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15 5

, 0 10 Q5 5

NOV

APR

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3. Mean j3-glucosidase activity (+ SE, n = 10) over time associated with decomposing white birch sticks at upland deciduous, upland hemlock, riparian and lotic sites. The activities shown are total, i.e. the sum of extractable and immobilized activities.

Fig.

NOV

APR

JUL

NOV

APR

W-B

Hemlock

A-A

Lotic

a-_*

Riparian

JUL

NOV

APR

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Time

Fig. 4. Mean endocellulase activity (+ SE, n = 10) over time associated with decomposing white birch sticks at upland deciduous, upland hemlock, riparian and lotic sites. The activity units plotted on the ordinate are in thousands. phenol oxidase 0.75 + 0.01. The perioxidase activity data were erratic, perhaps because of non-enzymatic reactions between added H,Or and extract constituents, and were therefore not included in this report. Statistical

mode&g

The high degree of intercorrelation among the measured variables indicated that principal compo-

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Fig. 6. Mean b-xylosidase activity (f SE, n = 10) over time associated with decomposing white birch sticks at upland deciduous, upland hemlock, riparian and lotic sites. nents analysis could be used to condense the data. The initial analyses were performed by site. Three significant factors (eigenvalues > 1) were generated for the upland deciduous, lotic and riparian sites and two for the upland hemlock sites, accounting for 77-81% of the total variance. A common element in these analyses was a tendency for temporally integrated variables (mass loss, total Kjeldahl N, total P) to segregate from instantaneous variables (enzyme activities). The clearest example of this trend was found in the upland hemlock data (Table 1). To relate moss loss and enzyme activities on the same temporal scale, we integrated activity over time, expressing the results in units of activity-months. Linear regressions for mass loss as a function of integrated activity were calculated by site. For the five lignocellulose-degrading enzymes, the models were strong with no significant differences among sites. Consequently, the data were pooled across sites to generate general linear models with r* values ranging from 0.65 for endocellulase to 0.83 for /I?-glucosidase (Table 2). A multiple linear regression model of mass loss as a function of these five cumulative enzyme activity variables had an r2 value of 0.84 (Table 3), but due to high intercorrelation among the nominally independent variables none made significant individual contributions to the model. 1

Hemlock

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= CT sr 0 m2 q 3

0 NOV

APR

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NOV

APR

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NOV

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Fig. 5. Mean exocellulase activity (&SE, n = 10) over time associated with decomposing white birch sticks at upland deciduous, upland ^hemlock, riparian and lotic sites over a first-order catchment.

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4

NOV

APR

JUL

NOV

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JUL

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JUL

Time

Fig. 7. Mean phenol oxidase activity (&SE, n = 10) over time associated with decomposing white birch sticks at upland deciduous, upland hemlock, riparian and lotic sites.

Wood decomposition and lignocellulase activity Table 1. Rotated factor loadings from a principal components analysis of birch stick data from the upland hemlock sites. The temporally integrated variables, mass loss, total Kjeldahl nitrogen and total phosphorus tend to segregate from the instantaneous enzyme activity variables. Overall these two factors accounted for 79% of the total variance Rotated factor matrix loadinas Variable

Factor 1

Time % Mass loss Total P Total Kjeldahl N Extractable protein p-Glucosidase activity Acid phosphatase activit .Y Aryl sulphatase activity Chitobiase activity B-Xylosidase activity Endocellulase activity Exocellulase activity Phenol oxidase activitv

Factor 2

Enzyme

rz

Slope

Intercept

0.83 0.77 0.65 0.80 0.78

0.163 0.078 0.252 0.687 0.166

6.5 7.7 10.9 6.2 10.5

Enwme

T

SE

B

-0.0138 0.0457 -0.0406 0.2796 0.1259 6.02

0.0502 0.0353 0.3169 0.2762 0.0790 1.89

SIG

-0.274 1.296 -0.128 1.012 1.592 3.192

0.785 0.200 0.898 0.316 0.117 0.002

Table 4. Generation of a temporally-integrated lignocellulase activity factor by principal components analysis. Five integrated enzyme activity variables with a high degree of intercorrelation were condensed into a single factor termed integrated lignocellulase activity to simplify mass loss modelling. This new factor accounted for 92% of the total variance amone the oriainal variables Variable (cumulative activity)

Table 2. Linear regression models for birch stick percent mass loss as a function of the temporally integrated activity of five lignocellulose-degrading enzymes (n = 64, 8 sites x 8 samulina dates)

fl-Glucosidase Exocellulase Endocellulase p-Xylosidase Phenol oxidase

Table 3. Multiple linear regression model for birch stick percent mass loss as a function of the temporally integrated activity of five lignocellulose-degrading enzymes (n = 64,8 sites x 8 sampling dates, d.f.: 5 for regression, 58 for residual, 12= 0.84). B = regression coefficient, SE = standard error for B, constant = y intercept, T = T statistic for the stepwise addition of each enzyme variable to the model. SIG = significance level for T

Phenol oxidase Endocellulase /I-Xylosidase Exocellulase /?-Glucosidase Constant

0.710 0.792 0.847 0.900 0.552 0.514 0.530 0.918 0.225 0.573 0.063 0.440 0.139

0.542 0.556 0.337 0.262 0.787 0.769 0.703 0.044 0.831 0.723 0.617 0.792 0.798

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Communality

Factor loadings

0.966 0.941 0.779 0.946 0.966

0.214 0.211 0.192 0.212 0.214

fi-Glucosidase Exoccllulase Endocellulase B-Xvlosidase bhenol oxidase

yield a final regression model that accounted for 94% of the variance in mass loss (Fig. 9).

This result suggested that further simplification could be achieved by collapsing the five cumulative activity variables into a single factor using principal components analysis. This new factor was termed cumulative lignocellulase activity and incorporated 92% of the total variance among the five original variables (Table 4). When regressed against mass loss, cuulative lignocellulase activity accounted for 83% of the mass loss variance (Fig. 8). Because the data appeared to lie along a hyperbolic curve, they were further linearized by logarithmic transformation to

DISCUSSION

Although we observed a generally linear rate of mass loss from the birch sticks, we also calculated rate constants for a first-order exponential decay model to facilitate comparison with other studies. For the upland deciduous sites, the mean first-order mass loss rate was 0.466 yr-‘; corresponding values for the upland hemlock, lotic and riparian sites were 0.395, 0.268 and 0.137 yr-‘, respectively. These rate constants are within the range reported for small

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4 60. r= +3 I 4 22 C 1

4 0

50

100

Lignocellulose

150

200

2 50

actiwty-months

Fig. Linear model mass as function temporally-integrate activity white sticks eight on first-order watershed = 8 x sampling Integrated lignocellulase activity is a compound variable generated by condensing integrated /?-glucosidase, fi-xylosidase, endocellulase, exocellulase and phenol oxidase activities by principal components analysis. r2 = 0.83.

0

1

0 In

2

3

4

5

6

LLignocellulase activity-months)

Fig. Linear model mass as function temporally-integrated activity from data decomposing birch ateightsitesonafirst-orderwatershed(n = 64, lsites x Isampling dates). Integrated lignocellulase activity is a compound variable generated by condensing integrated b-glucosidase, /?-xylosidase, endocellulase, exocellulase and phenol oxidase activities by principal components analysis. r* = 0.94.

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R. L. SINSABAUGH et al.

sticks by Golladay and Webster (1988) in a survey of published breakdown rates. However, we want to emphasize that mass losses generally did not follow exponential decay curves. After an initial lag of several months, losses were more-or-less linear at all sites, with no indication of a winter attenuation in decomposer activity. This finding is consistent with the work of Coxson and Parkinson (1987) who reported substantial winter respiration from the litter and soils of northern aspen forest. They attributed the maintenance of heterotrophic activity at sub-zero air temperatures to the insulating effects of snow cover, high moisture availability and freeze-thaw disturbances, which releaselabileorganicmatter(SkoglandetaZ., 1988). From an enzymic perspective, it is known that extracellular enzymes retain substantial activity at temperatures below freezing (Bremner and Zantua, 1975; Linkins et al., 1984), that freezing-thawing promotes enzyme desorption and remobilization (Sinsabaugh and Linkins, 1989), and that waterlogging can lead to marked changes in enzyme activity (Pulford and Tabatabai, 1988). The relative contribution of these various processes to winter decomposition activity is not known. As for the lotic sites, water temperature in Pegs Run remains at or near 0°C for nearly half the year, a period during which extensive decomposition of autumnal litter input occurs. Although considerable research into the microbial physiology and biochemistry of wood degradation has been conducted (see reviews in Higuchi, 1985), little data have been published on wood-associated enzyme activity in an ecological context. In comparative studies of microbial activity on organic substrata in a mid-size (fourth-order) river, enzyme activities associated with white birch sticks were similar to those reported here, while activity on white pine blocks was generally lower, consistent with their slower breakdown rate (Golladay and Sinsabaugh, 1991; Sinsabaugh et al., 1991b). In both cases, a temporal trend of accumulating enzyme activity accompanying progressive substrate softening was evident. Our finding that mass loss rates across all sites could be described by a single statistical model is consistent with the enzyme regulation hypothesis presented in the Introduction. If extracellular enzyme activity is directly or indirectly controlled by site characteristics and substrate properties, and if extracellular lignocellulase activity is the rate-limiting step in litter degradation, then the relationship between mass loss and lignocellulase activity should transcend site and substrate differences. Although we used a uniform substrate, the environment to which the sticks were exposed spanned a wide range of edaphic and hydrologic conditions with concomitant differences in microbial and invertebrate community structure. The greatest contrast was between the lotic and terrestrial sites (see reviews by Harmon et al., 1986; Webster and

Benfield, 1986). Within a year, fungal hyphae had penetrated and softened the terrestrial sticks, but microbial activity in the stream remained confined to a surface biofilm. Even at mass losses of 60% the residual birch wood was structurally sound and would snap when broken. While not as conspicuous, substantial differences also exist in the microbiota of deciduous and hemlock soils (Pritchett and Fisher, 1987). In general, soils under coniferous canopies have a higher ratio of fungal to bacterial production than deciduous soils. To confirm that edaphic differences in microbial activity were reflected in birch stick decomposition, we periodically assayed litter and soil samples from the upland sites for the same suite of enzyme activities monitored on the sticks. These samples showed the same pattern of intersite variation as the birch sticks themselves. The generality of the relationship between mass loss and the potential activity of lignocellulosedegrading enzymes suggests an emergent similarity in decomposition process among landscape patches that transcends differences in microbial and invertebrate community composition. From a basic ecology perspective, our “bottom up” integration of microbial process converges at the same place, i.e. the microbial community, as “top down” models such as the one presented by Insam et al. (1989) and Insam (1990), which predicts soil microbial biomass from climatic data. The convergence of these approaches suggests a potential for development of decomposition models that integrate scales from the molecular to the ecosystem which may improve prediction of perturbation effects, such as climate change, on a landscape scale. From an applied ecology perspective, the emergent similarity of decomposition process might be exploited to facilitate estimation of decomposition rates among landscape units. The general approach would be to make periodic estimates of detritus standing stock and to assay composite samples for the activity of one, and preferably several, lignocellulose-degrading enzymes. Decomposition rates would then be estimated from temporally-integrated enzyme activities using empirically established, statistical models similar to the one presented in Fig. 9. From these rates and standing stock data, carbon turnover could be calculated. The utility of this approach remains to be established, but Sinsabaugh and Linkins (1992) have shown that mass loss from deciduous leaves of contrasting composition decomposing at a single site can also be reliably estimated from a single integrated enzyme activity model similar to the one developed here for a single substrate decomposing at contrasting sites. Acknowledaements-This research was suuoorted by grants from the Department of Energy and the-National Science Foundation. We thank Peg and Ted Walrich for allowing us to use their property as a research site.

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