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Soil Science Society of America Journal 66:1669-1676 (2002)
© 2002 Soil Science Society of America

DIVISION S-7—FOREST & RANGE SOILS

Quantifying Harvesting Impacts using Soil Compaction and Disturbance Regimes at a Landscape Scale

R. Block, K. C. J. Van Rees* and D. J. Pennock

Dep. of Soil Science, 51 Campus Dr., Univ. of Saskatchewan, Saskatoon, SK, Canada, S7N 5A8

* Corresponding author (vanrees{at}sask.usask.ca)


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSION
 REFERENCES
 
Several indicators have been identified for the conservation and maintenance of soil criterion in the Montreal Protocol. The objective of this study was to use soil compaction and disturbance measures to determine harvesting impacts at a landscape scale in the boreal forest of Saskatchewan. Forest harvesting impacts were studied pre and postharvest for five harvested sites by (i) sampling soil bulk density (Db) at prescribed grid-points, and (ii) measuring soil disturbance regimes on two 30-m transects at each grid-point. Mean soil Db in the harvested area increased significantly (8–11%) from pre to postharvest conditions for the two winter-harvested sites at both the 10- and 20-cm depths, while two of the three summer harvested sites also showed significant Db increases (7–15%) at the 10-cm depth. Combining all five sites, showed that after harvest 32% of all the grid-points had an increased Db of >15%. Mean soil Db at a 10-cm depth for roadways and landings was significantly higher (8–14%) than postharvest Db for postharvest levels at four of the five harvested sites. Surface soil disturbance regimes were higher for the summer-harvested sites than that for the winter-harvested sites. Landscape position showed no significant differences in Db between the shoulder, backslope, and footslope positions; however, within each landscape position, significant differences in Db were found between pre and postharvest conditions. Soil Db and soil disturbance regimes measured on a grid basis provided a simple, but reliable method for monitoring soil compaction and disturbance effects from harvesting at a landscape scale.

Abbreviations: BE, Birch East • BM, Bull Moose • BW, Birch West • Db, bulk density • DEM, digital elevation model • RL, Roberts Lake • SL, Stuart Lake


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSION
 REFERENCES
 
LIKE MANY JURISDICTIONS in North America, Saskatchewan is developing a forest management impacts monitoring program that balances the use of the forests for economic, social and cultural purposes while protecting long-term forest ecosystem health. One aspect of forest ecosystem health, as stated in the Montreal Protocol, is to conserve and maintain the soil resource, as it is the basis for productive forests and sustainable management (Ramakrishna and Davidson, 1998; Canadian Council of Forest Ministers, 2000). The definition and measurement of soil quality, however, is neither simple nor direct. Soil quality must include both physical and biological parameters, must define the functional elements of the soils that sustain productivity, and must be an indicator of these functions (Powers et al., 1998). Several indicators have been suggested for measuring this criteria ranging from soil erosion, soil organic matter, soil compaction, and soil and water pollution (Ramakrishna and Davidson, 1998) to microbial indicators (Staddon et al., 1999).

Soil compaction increases soil strength and reduces macrospore space and there is evidence that compaction reduces tree growth (Corns, 1988; Froehlich and McNabb, 1984) and vegetative suckering (Stone and Elioff, 1998). Reversing the effects of compaction in the boreal forest is very slow even with freeze-thaw cycles and is assumed to persist for many decades (Corns, 1988; Froehlich and McNabb, 1984).

Regardless of the soil indicator used, it must be sensitive enough to detect change, be easy to use and interpret, and be cost effective (Burger, 1997). Soil compaction can be determined from bulk density (Db) or soil resistance measurements. There have been many studies investigating the relationship between tree growth and both soil resistance (Greacen and Sands, 1980) and Db (Corns, 1988). Powers et al. (1998) suggested that soil resistance was a better measure of assessing soil physical properties related to productivity than Db. In the boreal forest, however, there are many soils that are stoney, which would make the use and interpretation of soil resistance data difficult in a monitoring program. In addition, soil resistance readings are sensitive to changing soil moisture contents, thus making comparisons of resistance readings between harvested areas and uncut stands difficult. The water content problem is particularly important if the indicator utilizes undisturbed stands as a baseline of natural variation. Soil water contents on these sites can be lower because of greater transpiration rates, resulting in greater soil resistance readings in relation to the recently harvested areas, which may be wetter. Therefore, Db was selected as the measure of soil compaction because of the potential difficulties with using recording cone penetrometers in boreal soils.

Grigal (2000) stated that to understand forest management impacts on productivity, one should work at the landscape scale. Some parts of the landscape may be more sensitive to soil compaction or disturbance because of differences in soil moisture, texture, organic matter, slope, and the kind of harvesting activities occurring there. Few studies, however, have investigated the effects of harvesting at landscape scales. Pennock and van Kessel (1997a)( b) used grid sampling and soil-landform models to investigate changes in Db, N, and organic C between harvested and undisturbed forests at a landscape scale. Wulfsohn (1997) investigated changes in soil Db and soil disturbance by conventional and mechanical operations using grid sampling.

The objectives of this study were to (i) determine the feasibility of using Db and soil disturbance regimes as indicators for monitoring the impacts of forest management practices at a landscape scale, and (ii) examine the relationships between landscape position and soil compaction.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 CONCLUSION
 REFERENCES
 
Five sites were selected representing a range of soil and forest cover types commonly harvested in the mid-boreal upland ecoregion of central Saskatchewan (Beckingham et al., 1996). All five study sites—Stuart Lake (SL), Roberts Lake (RL), Birch East (BE), Birch West (BW), and Bull Moose (BM)—were located in north-central Saskatchewan, within Weyerhaeuser's Forest Management License Area. Soil characteristics and season and method of harvest for each site are listed in Table 1.


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  		Table 1. Site descriptions, season, and method of harvest for the five sites.

 
Soil Db was sampled using a systematic grid pre and postharvest. Three sites (SL, BE, BW) were sampled on a 4 by 8 grid with 50-m spacing while the RL and BM sites were sampled on a 6 by 8 and 7 by 7 grid, respectively with 100-m spacing. The spacing between grid-points was altered for the different sites so that the sampling grid covered the harvested block. The number of grid-points for each site, pre and postharvest sampling and adjacent areas are found in Table 2. Bulk density samples at each grid-point were collected from the horizontal face of a soil pit (20 by 30 by 30 cm) at 10-cm and 20-cm depths using a soil core (5 by 5 cm). Soil pits were identified with pin flags and georeferenced (see below). At each grid-point, the thickness of the forest floor (LFH) was also recorded. Additional Db samples were collected from the roads existing within the harvested site by selecting a random starting point on the road and using a 50- or 100-m transect to collect the samples. Postharvest samples were taken within a year of taking the preharvest samples from new soil pits immediately adjacent to or near as possible to the pit from the preharvest sampling. In three of the five sites (SL, BM, and RL), additional Db samples were also taken by extending the grid into the adjacent uncut stands at postharvest sampling for comparison to preharvest conditions in the harvested area. Adjacent areas were selected based on similarity in soils and vegetation to the harvested block. Samples were oven-dried at 55°C for 72 h, and dry weights used to determine Db (Culley, 1993).


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  		Table 2. Mean (±SE) bulk density values at the 10- and 20-cm depths for preharvest, adjacent sites, postharvest and roadway sampling for the five sites.

 
Soil disturbance regimes were measured at 1-m intervals on two 30-m transects at each grid-point. The bearing of the first transect was selected randomly and the second transect bearing was determined by adding 90° to the first bearing. The criteria for soil disturbance types were adapted from the disturbance guidelines in British Columbia (British Columbia Ministry of Forests, 1991). Briefly, rutting was defined as a depression originating from machine traffic that was either (i) 30 cm wide, >15 cm deep at the deepest point from the top of the LFH and covered a distance of 5 m, or (ii) on fine-textured soils >5 cm deep at the deepest point from the mineral soil surface and 30 cm wide and 5 m long, or (iii) an area of 1 by 2 m that exhibited altered soil structure relative to the undisturbed area or was puddled. Puddling, although difficult to identify when the soil is dry, was classified as an area that exhibited ponded water on the disturbed soil surface. A deep gouge was any soil displacement that resulted in a gouge over 30 cm deep into the mineral soil. A long gouge was >5 cm deep covering an area of 1 by 3 m while a wide gouge covered more than 80% of a 2 by 2 m area. Scalping referred to the displacement of LFH only. Erosion was qualitatively described as the presence or absence of erosion. The procedure for determining the percent area for each disturbance regime is reported by Curran and Thompson (1991).

Grid-points and roadways in SL, BE, and BW harvested sites were geo-referenced using a Trimble Pathfinder Pro XRS GPS (Trimble Navigation, Santa Clara, CA) unit and also topo-surveyed using a laser theodolite (SOKKISHA Total Station SET5, Tokyo, Japan) for landscape analysis. Collected global positioning system (GPS) data was corrected to the base station at Prince Albert, Saskatchewan.

All data corresponding to each grid-point location was spatially interpolated through SURFER software using the point kriging method of gridding (Golden Software Inc., 1999). The XYZ survey data of the prescribed sample grids at SL, BE, and BW were analyzed for landscape position, according to the landform classification developed by Pennock et al. (1994). A digital elevation model (DEM) for SL was constructed with the interpolated Db data.

Data analysis was completed by SPSS statistical software (SPSS Inc., 1998); paired t-tests were performed to identify significant differences between preharvest and postharvest values for mean Db and LFH thickness, and to compare postharvest Db between roadways and the harvested area. Independent sample t-tests compared the differences in mean Db and LFH depth between pre and postharvest by landscape position.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 CONCLUSION
 REFERENCES
 
Soil bulk densities for pre and postharvest sampling ranged from 0.88 to 1.92 g cm-3 for all sites and soil depths. Postharvest sampling indicated a significant increase in soil Db at the 10-cm depth for SL, and at the 10-cm and 20-cm depths for the BE, BW, and BM sites compared with preharvest levels (Table 2). Roberts Lake, which had an initially high preharvest Db, did not show any significant increase in postharvest Db. Soil Db values for roadways at the 10-cm depth were significantly higher than preharvest levels for all sites and also, higher than the postharvest sampling at three of the five sites for the postharvest sampling at the 10-cm depth (Table 2). Adjacent, uncut forest stands had similar Db's to the preharvest levels, except at the RL site, where measured Db at the 20-cm depth was significantly lower than both pre and postharvest values (Table 2). Postharvest Db values expressed as a percentage change from preharvest levels ranged from a 1% decrease (RL) to a 13% increase (BM) (Fig. 1) . The winter harvested sites (BE, BW) displayed a greater percent increase in Db than two of the three summer-harvested sites (SL, RL). Grid-points that showed a large decrease in Db were usually disturbed and contained incorporated organic material.



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  		Fig. 1. Percentage of change in bulk density from preharvest to postharvest for each site and soil depth. The upper dashed line indicates a 15% bulk density increase threshold. The solid horizontal lines in the boxes represent the median value while the upper and lower limits of the boxes represent the 25th and 75th percentiles. The vertical bars (whiskers) represent the largest and smallest values that are not outliers.

 
Frequency distributions of the percentage change in Db showed that the highest proportion of grid-points sampled at both the 10-cm and 20-cm depth occurred when the Db increased in the 0 to 7.5% and the 7.5 to 15% range (Fig. 2) . Thirty-two percent of all the grid-points, however, had an increase in Db >= 15% from the preharvest value and the BM site accounted for 42% of these grid-points. For the individual sites, 46% of the grid-points at BM had a Db >= 15%, RL had the least at 14% and BE, BW, and SL were intermediate at 23 to 30%.



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  		Fig. 2. Frequency distribution of percent change in soil bulk density values at two depths from all sites.

 
Soil disturbance was also quantified by measuring the thickness and displacement of the forest floor. A significant decrease in LFH thickness was found at the BW, BM, and RL sites (Fig. 3) . The percentage change in LFH thickness from pre to postharvest levels ranged from an increase of 8% for the BE site, to decreases of 6 to 31% for the BW, SL, BM, and RL sites.



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  		Fig. 3. Pre and postharvest LFH forest floor thickness for each site. The solid horizontal lines in the boxes represent the median value while the upper and lower limits of the boxes represent the 25th and 75th percentiles. The vertical bars (whiskers) represent the largest and smallest values that are not outliers. Box diagrams with the same letter for pre and postharvest at the same site are not significantly different at P = 0.05.

 
Site disturbance in the harvested areas was measured by identifying soil disturbance types at points 1 m apart on two 30-m transects located at each grid-point (Table 3). Each site except for BM had been mechanically site prepared with a Delta power disc-trencher, which made it difficult to assess the disturbance caused by harvesting operations alone. However, a higher percentage of area of disturbance was found for the summer-harvested sites (RL, SL, and BM) compared with the winter-harvested sites (BE and BW). Roadways, landings, and machine-trafficked areas accounted for the majority of the disturbance differences between summer and winter-harvested sites and rutting, gouges, and scalps were present on summer harvested sites but not on winter harvested sites. Areas considered undisturbed were greatest at BM, because of the lack of site preparation. Among the sites that were site-prepared, the total percentage of the area undisturbed with or without logging slash was highest for both the winter-harvested BE and BW sites (53–55%) compared with the summer-harvested SL and RL sites (40–45%). Site-preparation disturbance was similar among SL, BE, and BW, ranging from 40–45% while disc trenching resulted in only 28% disturbance at the RL site.


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  		Table 3. Postharvest soil disturbance (% area of block) by disturbance type for each site.

 
The SL, BE, and BW sites were topographically surveyed and the landscapes were analyzed to determine if slope position exerted any effect on Db and LFH depth between pre and postharvest. Each grid-point was classified into one of three landform element complexes (shoulder, backslope, or footslope) based on morphological and positional attributes (Pennock et al., 1994). Mean Db values were not significantly different between landscape positions for either pre or postharvest conditions at SL, BE, and BW (data not shown). Further comparison of mean Db values at SL revealed that the significant increase in Db from pre to postharvest at the 10-cm depth occurred at all three landscape positions (Table 4), and was not exclusive to any particular part of the landscape. One grid-point from a total of 30 from the SL site was classified as a depression, and the Db was found to have increased 48% from the preharvest value (1.10 g cm-3) at the 10-cm depth. No significant differences were detected at the 20-cm depth from pre to postharvest among the landscape positions. Spatial interpolation of preharvest Db (Fig. 4) and the mean percentage of change in Db (Fig. 5) at the 10-cm depth at SL indicated that areas in low depressional landscape positions or areas with lower preharvest Db experienced the greatest increases in Db.


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  		Table 4. Mean bulk density at the 10-cm depth for three landscape positions at the Stuart Lake site.

 


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  		Fig. 4. Digital elevation model (DEM) of Stuart Lake site showing preharvest bulk density at the 10-cm depth using spatial interpolation through Surfer software. Solid lines represent the in-block roads.

 


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  		Fig. 5. Digital elevation model (DEM) of Stuart Lake site showing percent change in Db at the 10-cm depth from pre to postharvest using spatial interpolation through Surfer software. Solid lines represent the in-block roads.

 
Sites BE and BW had a much more level landscape than SL, with the majority of the sample points classified as level. At the BE site, the level landscape position postharvest mean Db was significantly higher than the preharvest Db at both the 10- and 20-cm depths (data not shown). The backslope landscape position showed a significantly higher postharvest Db value at 10 cm, but Db did not differ between pre and postharvest at 20 cm. At BW, most sample points were classified as level; only four points were considered depressional areas. The comparison, therefore, was not according to landscape position but rather between depressional and nondepressional areas. Postharvest mean Db values in the nondepressional areas were significantly higher than preharvest levels for both 10- and 20-cm depths (Table 5). The depressional areas showed higher postharvest Db values at 20 cm, but at 10 cm the pre and postharvest Db values were not significantly different.


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  		Table 5. Mean bulk density (g cm-3) at the 10- and 20-cm depths for landscape elements at the Birch West site.

 
Depth of LFH was not significantly different among the landscape positions at the SL, BE, and BW sites, although the LFH values data suggested greater LFH disturbance at the shoulder than the footslope positions (data not shown).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
CONCLUSION
 REFERENCES
 
Preharvest mean Db for individual sites in this study ranged from 1.31 to 1.59 g cm-3 and were within the range of Db reported for other studies in north-central Saskatchewan (Pennock and Van Kessel 1997a; Wulfsohn, 1997). Pennock and van Kessel (1997a) found the Db of undisturbed, medium-textured Luvisolic (i.e., Haplocryalfs) soils ranged from 0.96 to 1.74 g cm-3 in three depth increments from 0 to 45 cm; while clear-cuts (<5 yr old) had a similar range in mean Db (0.95–1.85 g cm-3). Wulfsohn (1997) reported a range in mean Db from 1.40 to 1.46 g cm-3 for undisturbed coarse-textured Brunisolic (i.e., Eutrochrepts) soils at the 0- to 30-cm depth, while conventionally and mechanically logged harvested areas ranged from 1.45 to 1.62 g cm-3. Some soils observed in this study (i.e., Roberts Lake) had inherently high natural Db levels which were within the critical growth-limiting Db levels of 1.50 to 1.80 g cm-3 given by Greacen and Sands (1980), Heilman (1981), and Daddow and Warrington (1983).

Results of LFH thickness measurements before and after harvest suggest that logging activities during the summer have a pronounced effect on the redistribution of the LFH layer. Both SL and RL showed greater variation in LFH depth at postharvest, ranging from complete removal of the LFH layer to a two-fold increase in the thickness of the LFH. Variable topography on steeper slopes, such as at SL, would enhance the potential for LFH redistribution, as machine tires and tracks are more prone to slippage. Wide roads and numerous landings at RL increased the proportion of sample points on these high-disturbance areas, and which are largely responsible for the significant differences seen in LFH differences between pre and postharvest conditions. At BW, however, the cause for significant LFH loss is unknown. No LFH disturbance occurred at the adjacent BE site and both sites were winter-harvested.

In-block roadways present a special management issue, as Db levels were significantly higher than both preharvest and most average postharvest levels, especially at the 10-cm depth. Although roadways occupy a relatively small area (<5%) within the harvested area, the degree of compaction has direct implications on future productivity and reestablishment of vegetation in these specific areas. The percentage of the area of roadways, landings, and machine traffic in summer-harvested areas are of concern particularly at the RL site where they accounted for 14% of the total harvested area.

The effects of harvesting on soil compaction and LFH disturbance as a function of landscape position are not readily discernable from data collected in this study. The significant increases in Db following harvest were not limited to any particular landscape position at the sites BE, BW, and especially SL, where the relief was greatest. The areas classified as depressions at BW, however, showed a significant increase in Db at both 10- and 20-cm depths. As well, SL had one sample point within a small depression, and where the postharvest Db was 48% higher than the preharvest level. Depressions are landform elements that have a high specific catchment area and a low specific dispersal area, and thus are more susceptible to compaction as they may remain wet for relatively long periods compared with the rest of the landscape (Pennock et al., 1994). McNabb et al. (2001) also stated that managing soil wetness was the most important factor in rating the susceptibility of soils to soil compaction and surface disturbance. Therefore, interpolation of soil moisture using soil water potentials and landscape positions from DEMs may be useful in determining the potential for soil compaction on different landscapes.

The USDA Forest Service has used a threshold value of 15% increase in Db for determining detrimental soil compaction in their monitoring programs (Powers et al., 1998). The sole use of the percentage of change of soil Db, however, is ineffective because the percentage of change from initial Db values may vary in their biological significance (Williamson and Neilsen, 2000). For example, if the RL site (preharvest Db of 1.59 g cm-3) had an increase in mean Db >= 15%, there would be a greater potential for impacting tree growth than if a similar percentage increase occurred at the SL site (preharvest Db of 1.33 g cm-3). Therefore, a greater percentage of change in Db would be required for the SL site to reach the growth-limiting Db that occurred at the RL site. Another method for determining detrimental harvesting impacts would be the development of an evaluation system based on the range in natural variation of soil Db (Landres et al., 1999). Pennock and van Kessel (1997a) used this approach to compare the effects of harvesting on soil organic C and N in the boreal forest in relation to the range of natural conditions from uncut stands. Preharvest Db samples would be collected over a number of years to develop a range of natural variation for soil Db for different ecosites in the boreal forest. Bulk densities from harvested sites would then be compared with the Db established from the range of natural variation for similar ecosites to evaluate whether harvesting has resulted in significant soil compaction.

We must also distinguish between the average condition of the site as a whole and the harvesting effects at individual points within each site. Although the increase in mean Db values (Fig. 1) did not exceed the USDA Forest Service threshold level of 15%, more than 10% of the grid-points at each site had surpassed this threshold and may considerably affect future site productivity. The BM, BE, and BW sites had the highest number of grid-points (45, 30, and 30%, respectively) above this threshold; however, the reasons for this large number of grid-points having an increased Db is unclear. Perhaps harvest operations occurred during moist soil conditions at the BM site, or conventional harvesting techniques resulted in increased machine traffic and areal extent by the line skidders. Williamson and Neilsen (2000) showed that a single machine pass on a dry loamy soil increased Db in the top 10 cm by 22 to 30%, and did not increase significantly after three passes. Reasons for the winter-harvested sites to show greater increases in Db than two of the three summer-harvested sites are also unclear. Harvest took place in December through January and the soil may not have been frozen to a sufficient depth to withstand the pressure exerted by harvesting machines (Shoop, 1995). Sites BE and BW may also be highly susceptible to compaction because of the relatively permanent moist soil conditions of these sites.

The protocol for soil sampling and disturbance measurements developed during this study provided a reliable and efficient means of monitoring the impacts of harvesting operations on soil compaction. Pre and postharvest sampling, however, requires that sites be visited twice in a monitoring program. Our data showed that Db samples collected from adjacent stands at postharvest could be a reasonable surrogate for preharvest sampling and thereby reduce the number of sampling trips and cost of sampling. Adjacent undisturbed stands, however, should be similar in soil type and stand composition to post-harvest areas for valid comparisons and more testing of adjacent site sampling is needed in order for this approach to be completely defensible.


   CONCLUSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSION
REFERENCES
 
This study showed that soil Db and surface disturbance regimes could be used as indicators for monitoring harvesting impacts on soils. Bulk density increased significantly at 10- and 20-cm soil depths for both winter and two of the three summer harvested sites. Surface disturbance was higher in summer-harvested than winter-harvested sites, because of the increased percentage area of roads, landings, and overall machine traffic on unfrozen ground. No significant differences were found in pre and postharvest soil Db between landscape positions. Topography, however, plays a significant role in the redistribution of moisture suggesting that depressions in the landscape are more susceptible to soil compaction because of increased soil moisture content retention in the soil profile. The percentage increase in mean Db from pre to postharvest for the five sites did not surpass the 15% threshold level used by the USDA Forest Service for determining detrimental soil disturbance detrimental to site quality, although three of the five sites had greater than 30% of their sample points that exceeded this level. A possible alternative to the fixed threshold level would be the use of the natural range in variation of Db as a guideline for determining detrimental soil impacts for monitoring programs.


   ACKNOWLEDGMENTS
 
This project was funded by the Prince Albert Model Forest Association. The authors thank B. Anderson, B. Bailey, M. Bock, R. Hangs, S. Lieffers, and P. Krug for their help in the field, D. Jackson for technical and field support, J. Boon of SIAST for GPS data correction, B. Christensen of Weyerhaeuser Saskatchewan Ltd. for site selection and Keith Chaytor of the PAMF for his encouragement and support. Contribution No. R884 of the Saskatchewan Centre for Soil Research.

Received for publication March 8, 2001.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSION
 REFERENCES
 




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Predicting Soil Properties from Organic Matter Content following Mechanical Site Preparation of Forest Soils
Soil Sci. Soc. Am. J., May 1, 2004; 68(3): 943 - 949.
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