Risk analysis of effects of whole-tree harvesting on site productivity

Forest Ecology and Management 282 (2012) 175–184

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Risk analysis of effects of whole-tree harvesting on site productivity Antti Wall ⇑ Finnish Forest Research Institute, Kannus Unit, Box 44, FI-69101 Kannus, Finland

a r t i c l e

i n f o

Article history: Received 6 March 2012 Received in revised form 4 July 2012 Accepted 7 July 2012 Available online 2 August 2012 Keywords: Clear-cutting Thinning Stem-only harvesting Whole-tree harvesting

a b s t r a c t The increased removal of biomass from the forest sites with whole-tree harvesting has raised concern over the sustainability of site productivity. In this study, the results from eighty-six studies that quantify the short-term effects of whole-tree harvesting as compared with stem-only harvesting on soil- and treebased indicators of site productivity were reviewed with the aim of estimating the risks of both negative and positive impacts on site productivity. The risk was defined as the combination of the probability of occurrence of an impact in an indicator of site productivity and the magnitude of the impact. According to risk analysis of this study, soil pH, P, K, Ca, Mg and tree diameter were priority indicators of site productivity on which to act to mitigate risks of site productivity decline following whole-tree harvesting. Following clear-cutting, the probability of occurrence of a negative effect of whole-tree harvesting on these indicators of site productivity was 31–39% and the mean decrease 13–60%. The results showed that the risk level of change in indicators of site productivity following clear-cutting with whole-tree harvesting might be high enough to justify a need for mitigation measures. Following thinning with whole-tree harvesting, the probability of occurrence of the negative effects and the risk levels were lower in comparison to clear-cutting. Therefore, mitigation measures at thinning may not be needed. Ó 2012 Elsevier B.V. All rights reserved.

1. Introduction The increase in demand for fuelwood from silvicultural cleaning, thinning and clear-cutting over the last decade is driven by the global need to decrease the use of fossil fuels for energy. However, the increased removal of biomass and nutrients from forest sites with whole-tree harvesting (i.e. extracting un-delimbed trees to the landing) or logging residue removal after stem-only harvesting has raised concern over the sustainability of site productivity. In contrast, stem-only harvesting is considered to have little impact on site productivity because the nutrient content of the stem wood removed is rather low and nutrient-rich components such as foliage and twigs are left on site. Hereafter the term whole-tree harvesting is used to encompass a range of harvesting practices in which all parts of the tree above the stump are harvested, including removal of logging residues after stem-only harvesting. Simple nutrient budget calculations indicate that whole-tree harvesting could deplete soil nutrient pools and impair site productivity particularly on nutrient poor sites (Carey, 1980; Mälkönen, 1972; Merino et al., 2005; Tritton et al., 1987; White, 1974). Results from retrospective studies also indicate that whole-tree harvesting results in a decrease in soil nutrient pools (Adams and Boyle, 1982; Johnson et al., 1982; Thiffault et al., 2006). Similarly, results from simulation modeling suggest that ⇑ Tel.: +358 10211 3426; fax: +358 10211 3401. E-mail address: antti.wall@metla.fi 0378-1127/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.foreco.2012.07.012

there is a decrease in nutrient pools and tree growth following whole-tree harvesting when compared to stem-only harvesting (Aber et al., 1979; Blanco et al., 2005; Merganicˇová et al., 2005; Paré et al., 2002; Rolff and Ågren, 1999). Whole-tree harvesting also affects nutrient fluxes in the soil compared to stem-only harvesting through release of nutrients from logging residues, increased microbial activity and increased rate of organic matter decomposition in the soil under the residues, and through reduced nutrient uptake by plants (Hendrickson et al., 1989; Rosén and Lundmark-Thelin, 1987; Staaf and Olsson, 1994; Strahm et al., 2005; Titus et al., 1997). Logging residues also have an impact on bulk density, temperature and water content of soil (Carlyle, 1995; Jansson, 1987; O’Connell et al., 2004; Smethurst and Nambiar, 1990b) all of which can potentially affect site productivity. There are a large number of research papers on the impacts of forest harvesting on site productivity, as presented in reviews (Fox, 2000; Grigal, 2000; Kimmins, 1977, 1997; Mälkönen, 1976; Marshall, 2000; Thiffault et al., 2011). Guidelines and regulations for more intensive sustainable biomass removals have been developed based on an understanding of effects of biomass removal on site productivity (Abbas et al., 2011; Stupak et al., 2007). Despite this, much uncertainty remains concerning how whole-tree harvesting affects site productivity. The site productivity of forestland, which is defined as the ability of a site to produce wood biomass per unit area over a given time, is a result of the combined effects of physical, chemical and

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biological site attributes and climate. Tree growth has commonly been used as an index of site productivity. Alternatively, instead of directly measuring soil attributes that are needed to support site productivity, soil attributes can be inferred from measured soil properties that serve as soil indicators of productivity (Burger and Kelting, 1999; Schoenholtz et al., 2000). When evaluating the effects of forest harvesting on site productivity, the magnitude of the effects and the probability of occurrence of the effects should be among the criteria considered (Grigal, 2000; Worrell and Hampson, 1997). In this paper, these criteria were applied and a method of risk analysis is presented that shows how data from scientifically designed field experiments can be analysed to assist forest managers and stakeholders to judge the risks of both negative (downside) and positive (up-side) impacts of whole-tree harvesting on site productivity when compared to stem-only harvesting. The risk is described by the answers to questions about what can happen, how likely it is to happen, and what the consequences are (Kaplan and Garrick, 1981). Risk is expressed as a combination of the probability of occurrence and the consequences of an adverse event (Commission, 2000). In this paper, only commonly used tree and soil chemical indicators such as plant-available nutrient content, N content, pH and organic matter content of soil were addressed due to availability of information. The presented risk analysis method can also be applied to other potential indicators such as soil physical and biological indicators of site productivity (Knoepp et al., 2000; Schoenholtz et al., 2000) if enough information is available. The aims of this study were (i) to identify and quantify soil- and treebased indicators of site productivity which are potentially subject to changes caused by whole-tree harvesting when compared to stem-only harvesting, and (ii) to estimate the risks of both negative and positive impacts on site productivity associated with a particular indicator. Forest management practices that can be used to mitigate the risk are then discussed.

2. Material and methods In the present paper, the risk analysis method used is based on the concepts of failure mode and effects analysis. It is widely used in a variety of manufacturing industries in various phases of production processes to enhance a product or process safety and reliability. In risk analysis, the identification of a risk source capable of causing adverse effects is one of the first tasks. To identify the potential soil- and tree-based indicators of site productivity subject to change caused by whole-tree harvesting or by removal of logging residues after stem-only harvesting, scientific articles published in international peer-reviewed journals were chosen that fulfilled following requirements: (i) whole-tree harvesting treatment was compared to stem-only harvesting treatment (ii) the study was based on a designed field experiment in which randomization and replication of treatments was applied, and (iii) the response variable was a soil- or tree based indicator of site productivity (i.e. soil property or tree property). The focus of this paper is on field experiments, which have advantages over other research approaches in that treatment effects are unbiased and the degree of uncertainty of the validity of the conclusions is quantifiable (Powers et al., 1994). A total of 86 studies reporting results from 274 field experiments were identified that met the inclusion criteria (Tables 1 and 2). The actual number of field experiments was then reduced because results from the same experiment were sometimes reported in more than one study. The majority of articles reported results following clear-cutting, and only 15 articles involved thinning treatments. Forty-one studies provided results on soil-based indicators of site productivity and 45 on tree-based indicators of site

productivity. Most of the studies reported a short-term response of five years or less. For tree-based indicators of site productivity, tree height, diameter/basal area and stem or stand volume/biomass were used. For soil-based indicators of productivity, the most common ones in the literature were soil organic matter, pH, nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg). Data from the organic layer and mineral soil layers was used. Soil nutrient concentrations and nutrient pools were used as measures of soil nutrients. In nutrient analysis, various techniques were applied for contents of plant available nutrients and total contents. In contrast to other nutrients, results for N are presented separately for total content and plant-available content. Measures of mineral N availability varied from static extractions to net N mineralization assays. The majority of studies focused on organic matter and total N. For the purpose of this study, the result of a statistical test reported in each study regarding the effect of whole-tree harvesting on indicators of site productivity as compared to stem-only harvesting was considered an observation. The observations were classified according to statistical significance of the studied effect, and whether the observed effect was positive or negative. If the study contained more than one experiment and the statistical tests were reported for each experiment, each statistical test result was treated as a separate observation. Similarly, if statistical tests were reported separately for different tree species or in studies with repeated growth measurements for growth periods of four years or more, each statistical test result was treated as a separate observation. Therefore, multiple observations from a single study may have been used in some cases. For soil-based indicators of site productivity, if there were more than one statistically significant effect detected within a soil profile in the study, results for the soil layer with the greatest statistical significance was used. The threshold pvalue in statistical significance testing was 0.05 in most studies. For soil-based indicators of site productivity, there were a total of 78 and 16 observations from clear-cutting and thinning studies, respectively. For tree-based indicators of site productivity, there were a total of 80 and 71 observations from clear-cutting and thinning studies, respectively. The probability of occurrence of the effect of whole-tree harvesting on an indicator of site productivity was estimated as the frequency of the statistically significant difference between whole-tree harvesting and stem-only harvesting among the sampled experiments. For each indicator of site productivity, the probability of occurrence was scaled based on the authors personal judgement from one to four as follows: (i) remote probability when the probability of occurrence was <10% (occurrence score = 1), (ii) occasional probability when the probability of occurrence was 10– 29% (occurrence score = 2), (iii) probable probability, when the probability of occurrence was 30–50% (occurrence score = 3), (iv) frequent probability, when the probability of occurrence was >50% (occurrence score = 4). As a measure of the consequence of the effect of whole-tree harvesting on site productivity, the magnitude of the negative or positive effect was determined as the mean of statistically significant relative differences in an indicator of site productivity between whole-tree harvesting and conventional stem-only harvesting. For thinning, there were not enough observations to estimate the magnitude of the effect of soil-based indicators and their values were substituted with values from clear-cutting experiments. If the relative difference between whole-tree harvesting (WT) and stem-only harvesting (SO) was not presented, it was calculated as (SO – WT)/ SO  100. The relative difference in soil pH between harvesting treatments was calculated from the H+-concentration. The magnitude of the effect was scaled from one to four as follows: (i) minor magnitude when the mean difference was <10% (magnitude

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Table 1 Summary of the effects whole-tree harvesting on soil properties as compared to stem-only harvesting; (n) number of observations, (=) no significant effect, ( ) negative effect, (+) positive effect. Reference

n

Clear–cutting Bélanger et al. (2003) Belleau et al. (2006) Butnor et al. (2006) Carter et al. (2002) Chen and Xu (2005) Hassett and Zak (2005) Huang et al. (2011) Jones et al. (2011) Kabzems and Haeussler (2005) Laiho et al. (2003) Li et al. (2003) Mendham et al. (2002) Mendham et al. (2003) Nzila et al. (2002) Nykvist and Rosen (1985) O’Connell et al. (2004) Olsson et al. (1996a) Olsson et al. (1996b) Piatek and Allen (1999) Saarsalmi et al. (2010) Sanchez et al. (2006a) Sanchez et al. (2006b) Slesak et al. (2010) Slesak et al. (2011) Smaill et al. (2008) Smethurst and Nambiar (1990a) Smethurst and Nambiar (1990b) Smith et al. (1994) Staaf and Olsson (1991) Thiffault et al. (2006) Vanguelova et al. (2010) Vitousek and Matson (1985) Wall (2008) Wall and Hytönen (2010) Walmsley et al. (2009)

1 1 1 2 1 2 6 1 1 2 1 2 2 1 11 2 4 4 1 2 2 5 2 2 4 1 1 1 4 3 1 1 1 1 1

Thinning Brandtberg et al. (2000) Carlyle (1995) Olsson (1999) Rosenberg and Jacobson (2004) Smolander et al. (2008) Smolander et al. (2010)

5 1 4 4 1 1

Organic matter

Total N

Available N

P

K

Ca

Mg

= = =

= = =

=

=

=

= =

=

=

=

=

=

=

=

pH = =

= = =

= = =

= =

= =

= =

=

=

=

= =

= = = =

= + = = = = =

+ =

=

= +

= +

= = =

= =

=

=

= =

= =

= +

=

= +

=

= =

= =

= =

=

=

=

=

= =

=

= =

=+

=

=

=

= =

=

=

=

score = 1), (ii) moderate magnitude when the mean difference was 10–29% (magnitude score = 2), (iii) substantial magnitude when the mean difference was 30–50% (magnitude score = 3), (iv) severe magnitude when the mean difference was >50% (magnitude score = 4). To identify priority indicators of site productivity on which to act to mitigate risks, the risk associated with a specific indicator of site productivity was estimated by calculating the risk priority number (RPN), which is the probability of occurrence score (1–4) multiplied by the magnitude score (1–4). Thus, RPN was used as a measure of risk with a maximum possible value of 16. The indicators of site productivity having higher RPN are assumed to be more important and should be given a higher priority in application of mitigation measures that should be taken to reduce the risk. The focus of this work is negative effects of whole-tree harvesting on indicators of site productivity relative to stem-only harvesting but positive effects of whole-tree harvesting are also considered. In most of the studies reviewed, the harvesting treatments were not intended to mimic operational harvesting practices but were designed to create theoretical extremes in organic matter removal (i.e. total removal). As a result, the recovery rate of logging residues was higher in many studies than that in operational recovery practices. For example, when logging residues of Norway spruce-dom-

=

= =

= =

=

= = +

= =

= = =

=

=

=

=

=

=+

= =

= =

= =

= = =

inated stands are recovered with current harvesting and haulage methods, about 20–40% of the dry mass of the residues is retained on the site (Nurmi, 2007; Peltola et al., 2011). Furthermore, the logging residues in stem-only harvesting treatment were commonly spread uniformly over the experimental plots by hand. Therefore, the risks of site productivity decline from whole-tree harvesting as compared to stem-only harvesting represent the highest risks possible, and risks in actual forest operations will be lower.

3. Results Following clear-cutting, the probability of occurrence of a negative effect of whole-tree harvesting on an indicator of site productivity was greatest in the case of soil Ca (39%), followed by K, Mg, P and tree diameter: over 30% of observations showed a statistically significant decrease in a value when compared to stem-only harvesting (Figs. 1 and 2). A decrease in soil organic matter and tree volume value had the lowest probability of occurrence. The effect of whole-tree harvesting on indicators of site productivity was not consistent: for almost all indicators, there was also a low probability of occurrence of observations with a significant increase in an indicator value.

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Table 2 Summary of the effects whole-tree harvesting on tree properties as compared to stem-only harvesting; (n) number of observations, (=) no significant effect, ( ) negative effect, (+) positive effect. Reference

n

Tree species

Height

Diameter

Clear-cutting Ares et al. (2007) Carneiro et al. (2009) Carter et al. (2006) Egnell (2011) Egnell and Leijon (1999) Egnell and Valinger (2003) Fleming et al. (2006) Harrington and Shoenholtz (2010) Hassett and Zak (2005) Jones et al. (1999) Kabzems and Haeussler (2005) Landhäusser (2009) Mason et al. (2011) Mendham et al. (2003) Nzila et al. (2002) Oliver et al. (2011) Örlander et al. (1996) Proe et al. (1994) Proe et al. (1999) Proe and Dutch (1994) Proe et al. (1996) Proe et al. (2001) Raivonen and Leikola (1980) Roberts et al. (2005) Saarsalmi et al. (2010) Sanchez et al. (2006a) Scott and Dean (2006) Sikström (2004) Smethurst and Nambiar (1990b) Smith et al. (1994) Smith et al. (2000) Tutua et al. (2008) Vanguelova et al. (2010) Wall and Hytönen (2010) Walmsley et al. (2009) Zabowski et al. (2000)

1 1 4 1 4 1 14 2 2 4 2 1 3 2 1 2 4 1 1 1 1 3 1 1 2 2 6 1 1 1 3 1 1 1 1 2

Pseudotsuga menziesii Eucalyptus globulus Pinus taeda Picea abies Picea abies, Pinus sylvestris Picea abies Multiple species Pseudotsuga menziesii Populus tremuloides Eucalyptus globulus Picea glauca, Populus tremuloides Pinus contorta Picea sitchensis Eucalyptus globulus Eucalyptus PF1 Pinus radiata Picea abies Picea sitchensis Picea sitchensis Picea sitchensis Picea sitchensis Picea sitchensis Picea abies Pseudotsuga menziesii Picea abies Pinus taeda Pinus taeda Picea abies Pinus radiata Pinus radiata Pinus radiata Pinus elliottii Picea sitchensis Picea abies Picea sitchensis Pseudotsuga menziesii

= = =

= =

Thinning Carlyle (1995) Egnell and Leijon (1997) Helmisaari et al. (2011) Jacobson et al. (1996) Jacobson et al. (2000) Luiro et al. (2009) Mård (1998) Nord-Larsen (2002) Sterba (1988)

1 8 11 15 16 12 1 4 3

Pinus radiata Picea abies, Pinus sylvestris Picea abies, Pinus sylvestris Picea abies, Pinus sylvestris Picea abies, Pinus sylvestris Picea abies, Pinus sylvestris Picea abies, Petula pendula Picea abies Picea abies

Fig. 1. The probability of occurrence of the positive and negative effects of wholetree harvesting on soil-based indicators of site productivity compared with stemonly harvesting at clear-cutting. The number of observations is presented on top of bars.

=

=

= = = + = = =

Volume

= +

= =

= = =

= +

= =

= =

= =

= =+ = = =

= = = = =

= =

= = = =

= = = =

= = = = = = = =

=

=

=

= =

+

+ = = = = =

Of the studies in which significant negative effects were observed, whole-tree harvesting resulted in the greatest mean decrease (68%) in a value among indicators of site productivity in the case of soil pH when compared to stem-only harvesting (Figs. 3 and 4). For other indicators, the magnitude of the negative effect of whole-tree harvesting varied from 13% to 30% relative to stemonly harvesting. Following clear-cutting, the highest risk based on RPN was estimated for soil pH, followed by soil P, K, Ca, Mg, and tree diameter (Table 3). The risk level of soil P, K, Ca, Mg and tree diameter arise mainly from their probability of occurrence score, whereas the risk level of soil pH arised mainly from its magnitude score. Following thinning, the probability of occurrence of the negative effect of whole-tree harvesting on an indicator of site productivity was greatest (15%) for soil Ca and Mg, followed by tree diameter (14%) when compared to stem-only harvesting (Figs. 2 and 5). For soil P, tree diameter, and volume, there was a low probability of occurrence of observations with a significant increase in an indicator value. There were no observations with a significant change in soil organic matter, total N, pH, and tree height.

A. Wall / Forest Ecology and Management 282 (2012) 175–184

Fig. 2. The probability of occurrence of the positive and negative effects of wholetree harvesting on tree-based indicators of site productivity compared with stemonly harvesting at clear-cutting and at thinning. The number of observations is presented on top of bars.

179

Fig. 4. The magnitude of the positive and negative effects of whole-tree harvesting on tree-based indicators of site productivity compared with stem-only harvesting at clear-cutting and at thinning. S.D presented in bars.

mean decrease in tree diameter and volume was 15% and 12%, respectively (Figs. 4 and 6). The highest risk based on RPN was for soil available N, P, Ca, Mg, tree diameter and stem/stand volume (Table 3).

4. Discussion

Fig. 3. The magnitude of the positive and negative effects of whole-tree harvesting on soil-based indicators of site productivity compared with stem-only harvesting at clear-cutting. S.D presented in bars.

There were not enough observations following thinning to estimate the magnitude of the effect of whole-tree harvesting on soilbased indicators of site productivity. For tree-based indicators, the

According to risk analysis results, soil pH, P, K, Ca, and Mg were priority indicators of site productivity on which to act to mitigate risks of site productivity decline following whole-tree harvesting when compared to stem-only harvesting, whereas soil organic matter and N deserve less attention. The results are in general in agreement with studies comparing the nutrient removal in harvested biomass relative to sizes of plant available or total pools in the soil suggesting that N, P, Mg and especially Ca are the nutrients most likely to be depleted following whole-tree harvesting (Akselsson et al., 2007; Freedman et al., 1986; Merino et al., 2005; Tritton et al., 1987). The negative effects of whole-tree harvesting on tree growth have been attributed to removal of nutrients, especially N, in the tree biomass (Egnell, 2011; Egnell and Leijon, 1999; Proe et al., 1996; Scott and Dean, 2006; Walmsley et al., 2009) and to unfavourable microclimate and competition form weeds (Carter et al., 2006; Proe and Dutch, 1994; Proe et al., 1994).

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Table 3 Risk matrix for the negative effects of whole-tree harvesting on soil- and tree-based indicators of productivity following clear-cutting and thinning. RPN denotes the risk priority number (the highest values in bold). Clear-cutting

Thinning

Probability

Magnitude

RPN

Probability

Magnitude

RPN

Soil properties Organic matter N Available N P K Ca Mg pH

2 2 2 3 3 3 3 2

2 2 2 2 2 2 2 4

4 4 4 6 6 6 6 8

1 1 2 2 1 2 2 1

2 2 2 2 2 2 2 4

2 2 4 4 2 4 4 4

Tree properties Height Diameter Volume

2 3 2

2 2 2

4 6 4

1 2 2

– 2 2

– 4 4

Fig. 5. The probability of occurrence of the positive and negative effects whole-tree harvesting on soil-based indicators of site productivity compared with stem-only harvesting at thinning. The number of observations is presented on top of bars.

Fig. 6. The magnitude of the negative and positive effects of whole-tree harvesting on soil-based indicators of site productivity compared with stem-only harvesting at thinning. S.D presented in bars.

Following clearcutting, the probability of occurrence of positive effects and the upside risk levels from whole-tree harvesting were lower in comparison to negative effects. The positive effects of whole-tree harvesting on tree growth have been attributed to warmer soil temperatures (Landhäusser, 2009; Proe et al., 2001).

Whole-tree harvesting also frequently improves seedling survival and hence stand density indicating a positive effect on stand productivity (Egnell and Leijon, 1999; Fleming et al., 2006; Kabzems and Haeussler, 2005; Landhäusser, 2009). The results show that the risk level of site productivity decline following clear-cutting with whole-tree harvesting might be high enough to warrant a need for mitigation measures. However, it must be taken account when interpreting results that the actual risk levels in industrial forest operations would most likely be lower than those from experimental treatments reviewed here because experimental treatments involved the extremes in biomass removal. Following thinning, the probability of occurrence of negative effects and the risk levels from whole-tree harvesting were lower in comparison to clear-cutting. Low amounts of harvested logging residue in thinning with whole-tree harvesting in relation to clear-cutting (Tritton et al., 1987) may explain lower risk levels. Therefore, mitigation measures at thinning may not be needed. When evaluating the need for mitigation measures to reduce downside risk, a threshold should be established above which risk level merits attention and below which further consideration is not justified. This is a subjective task for forest managers and stakeholders. A criticality matrix can be used to establish a threshold for actions that should be taken according to risk category and for categorization of risks (Table 4). In the criticality matrix, risks are categorized first by the magnitude of their effects (from 1 to 4) and then by their probability of occurrence (from A to D) within each magnitude category. The threshold for action may vary according to the probability of occurrence and magnitude category. For example, mitigation measures may have to be implemented if the magnitude of risk is in the category of 10–29% with a probability of occurrence of 30–50%, but the risk in the magnitude category of 10–29% may be acceptable if its probability of occurrence is less than 9%. There are several possibilities for managing the risk of for site productivity decline from whole-tree harvesting. First, risk avoidance is achieved through choice of sites on which to practice whole-tree harvesting. This option is viable if the risks and the costs for risk mitigation are large but the implementation of the option requires detailed understanding of the site- and tree species-specific mechanisms of site productivity decline. Secondly, the risk can be accepted and budgeted as a cost of harvesting. This option is viable if the risks are small and the costs for risk mitigation are large. Thirdly, the risk can be mitigated by fertilization or by developing harvesting practices which reduce biomass and hence nutrient removals. Various approaches have been developed to mitigate increased nutrient removals in whole-tree harvesting. In the state of Minnesota

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Table 4 Suggested criticality matrix used for categorization of risks associated with whole-tree harvesting. Risk categories (RPN values in parenthesis) determined by probability of occurrence and magnitude of the effect and threshold for actions that should be taken according to risk category. Probability of occurrence categories

Remote (0–9%) Occasional (10–29%) Probable (30–50%) Frequent (>50%)

Magnitude categories Minor (1–9%)

Moderate (10–29%)

Substantial (30–50%)

Severe (>50%)

1A (1) 1B (2) 1C (3) 1D (4)

2A (2) 2B (4) 2C (6) 2D (8)

3A (3) 3B (6) 3C (9) 3D (12)

4A (4) 4B (8) 4C (12) 4D (16)

Acceptable, no measures required: risk category 1A, 1B, 2A. Undesirable, mitigation measures required: risk category 1C, 1D, 2B, 2C, 2D, 3A, 3B, 3C, 4A, 4B. Unacceptable, no harvesting allowed: risk category 3D, 4C, 4D.

in the USA, the preferred mitigation for minimizing negative impacts of forest harvesting on soil nutrients is retaining biomass on site (Grigal and Bates, 1997). Also, trees can be cut and left to dry in the stand before they are removed, which leaves foliage on the harvested site (Stupak et al., 2008). In addition, the amount of foliage remaining on the site following whole-tree harvesting can be increased by topping the trees at the stump or by removal of foliage by mechanical means (Hakkila, 2002). However, leaving the fine, nutrient – rich fraction of logging residues may have no effect on seedling growth and foliar nutrient concentrations in the short-term (Wang et al., 2007) but leaving needles in the forest has been reported to mitigate growth losses 31 years after whole-tree harvesting (Egnell, 2011). Furthermore, there is very little information on correlations between the amount of harvested biomass and changes in soil or tree properties. As a result, there is very little scientific evidence on acceptable harvest levels (i.e. how much residue to leave on-site). A different approach to mitigate increased nutrient removals is to fertilize or recycle wood ash following tree harvesting (Hakkila, 2002). Fertilization has the potential to restore site productivity in an energy-efficient way (Scott and Dean, 2006) and nutrient compensation has been found to be economically feasible (Börjesson, 2000). However, the utility of liming and ashing on mineral soils can be questioned: liming has often resulted in a negative growth response of trees (Derome et al., 1986) and addition of wood ash has resulted in no significant or even negative growth response of trees (Aronsson and Ekelund, 2004; Jacobson, 2003). In addition, the quantities of fertilizers or biomass needed and the specific fertilization requirements to offset nutrient losses are difficult to predict (Eisenbies et al., 2009). Further, the selection of mitigation measures requires site-specific diagnosis and selection of mitigation treatments (Carter et al., 2006). In addition, the preferred mitigation method depends on the element in question (Wang et al., 2010). This decision-making is even more difficult if several risks of site productivity decline occur on the site simultaneously. In the present study, the correlations among the indicators of site productivity were not considered but these correlations may exist on a site. For example, soil pH and base cations are interrelated as the increased acidification of soil following whole-tree harvesting is coupled with reduced base cation pools (Thiffault et al., 2011). Furthermore, a cost-benefit analysis of mitigation measures is needed and should be site-specific. Detailed site information is usually not readily available to forest managers and this information is costly to obtain. Although conventional soil analyses performed before planting were unable to detect differences between harvesting treatments in tropical soil (Laclau et al., 2010), soil analyses could be used to identify sites at risk of harvesting-induced productivity loss (Scott and Dean, 2006). If site-specific information is not available, the presented risk analysis method may assist forest managers to evaluate the risks of both negative and positive impacts of whole-tree harvesting on site productivity and to evaluate the need for risk mitigation

management when planning forest operations. The presented risk analysis method is objective and produces measurable components of risk. However, the method comes with the caveat that the information available influences the quality of the risk analysis and constrains the applicability of the method. Risk analysis is likely to be most reliable when the means by which the risk source causes its adverse effects is understood. This is still a problem concerning the impacts of whole-tree harvesting on site productivity: the cause-and-effect relationship between change in soil properties and tree growth following whole-tree harvesting is largely conceptual rather than based on correlated data. For example, decreased tree growth following whole-tree harvesting was observed in some experiments in Sweden (Egnell and Leijon, 1999) while there was no change in soil properties (Olsson et al., 1996a, 1996b; Staaf and Olsson, 1991). Furthermore, it is likely that not all possible significant adverse impacts of whole-tree harvesting were considered in the present risk analysis. In his evaluation of impacts of extensive forest management on soil productivity, Grigal (2000) suggested that changes in physical properties are a major concern. In support of this suggestion, whole-tree harvesting can increase mean soil temperatures (Devine and Harrington, 2007; Zabowski et al., 2000) and soil bulk density (Carter et al., 2006), and decrease soil–water content (O’Connell et al., 2004; Smethurst and Nambiar, 1990a) all of which can have negative or positive effects on tree growth. However, physical soil properties were not addressed in the present risk analysis due to the few studies available. Studies on the impacts of whole-tree harvesting on site productivity currently report mainly short-term impacts, and information on the duration of long-term impacts is scarce. Temporal changes in the relative importance of whole-tree harvesting to tree growth need to be considered when evaluating the impacts of whole-tree harvesting on site productivity. Most of the studies covered the establishment phase of the development of stands following clear-cutting, when trees are less influenced by nutrient supply and whole-tree harvesting (Thiffault et al., 2011). In addition, short-term results may differ from long-term results. For example, Mason et al. (2011) found discrepancy between results reported 2 years after planting (Proe et al., 2001) and 10-year results. Quantifying the duration of impacts and incorporating it as a risk component for risk analysis would improve information from the risks associated with whole-tree harvesting. Furthermore, the risk analysis carried out in this paper provided information of the risks across a wide range of sites, tree species and climate. Despite the large number of studies on the impacts of whole-tree harvesting on site productivity, it is not yet possible to categorize risk analysis according to tree species, soil type or climatic region due to lack of data concerning the magnitude of impacts. These factors are critical determinants of site sensitivity to whole-tree harvesting (Thiffault et al., 2011) and need to be considered when evaluating the impacts of whole-tree harvesting on site productivity. For example, Thiffault et al. (2006) reported that

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jack pine, black spruce, and balsam fir reacted differently to harvesting intensity in Canada. In this study, data for thinning experiments was almost exclusively from Nordic countries where Norway spruce was observed being more sensitive to harvesting intensity than Scots pine (Helmisaari et al., 2011). The proposed risk analysis method comes with some methodological caveats because the risk ranking method (RPN calculation method) has been criticized for a variety of reasons; for example, the risk components are considered to be equally important, which may not be the case when considering the practical application of risk analysis (Pillay and Wang, 2003). In addition, the probability of occurrence and the magnitude of impacts are influenced by the minimum detectable difference in an indicator value between harvesting treatments. For example, the minimum detectable difference in organic matter and N content are typically large for forest soils and can be 20% (Olsson et al., 1996b) or even over 40% (Homann et al., 2008) of the mean. Finally, it is noteworthy that the statistical significance of treatment differences, which was used here as a criteria for observations, is not equivalent to ecological or economic significance. 5. Conclusions The results of the present risk analysis indicate that soil pH, P, K, Ca, and Mg were priority indicators of site productivity on which to act to mitigate risks of site productivity decline following wholetree harvesting, especially in clear-cutting. Future research efforts should focus on identification of site and soil types at highest risk for site productivity decline following whole-tree harvesting, and identification of sites where it is cost-effective to apply risk mitigation management. Development of dose–response models showing the relationship between amount of harvested biomass and change in soil or tree properties would facilitate the estimation of a threshold for acceptable biomass harvest levels. In addition, the potential of whole-tree harvesting to enhance site productivity needs to be further studied, even though the probability of occurrence of such an event is low. The studies reviewed demonstrate that whole-tree harvesting does not have consistent effects on tree- and soil-based indicators of site productivity, as there are studies finding negative, positive and no effects when compared to stem-only harvesting. Therefore, generalizations regarding the effects of whole-tree harvesting on indicators of site productivity cannot be made. Hence, it may be necessary to examine more specific controls of site productivity to reveal mechanisms that contribute to site-specific responses. In view of the difficulty in acquiring objective assessment of the risks of both negative and positive impacts of whole-tree harvesting on site productivity, the proposed risk analysis method allows risk components to be evaluated in a precise way, and risk priorities identified. Therefore, the proposed approach has the potential to improve policies for forest harvesting practices. However, the applicability of the present risk analysis is constrained by the lack of available information. This paper is confined to considering the risks from whole-tree harvesting when compared to stem-only harvesting. The presented risk analysis method can also be applied to other harvesting treatments. References Abbas, D., Current, D., Phillips, M., Rossman, R., Hoganson, H., Brooks, K.N., 2011. Guidelines for harvesting forest biomass for energy: a synthesis of environmental considerations. Biomass Bioenergy 35, 4538–4546. Aber, J.D., Botkin, J.M., Melillo, J.M., 1979. Predicting the effects of different harvesting regimes on productivity and yield in northern hardwoods. Can. J. For. Res. 9, 10–14. Adams, P.W., Boyle, J.R., 1982. Soil fertility changes following clearcut and wholetree harvesting and burning in central Michigan. Soil Sci. Soc. Am. J. 46, 638– 640.

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