Quantitative Estimates of Coarse Woody Debris and Standing Dead Trees in Selected Swiss Forests

Quantitative Estimates of Coarse Woody Debris and Standing Dead Trees in Selected SwissForestsAuthor(s): N. A. Bretz Guby and M. DobbertinSource: Global Ecology and Biogeography Letters, Vol. 5, No. 6 (Nov., 1996), pp. 327-341Published by: WileyStable URL: http://www.jstor.org/stable/2997588 .

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Global Ecology and Biogeography Letters (1996) 5, 327-34i

Quantitative estimates of coarse woody debris and standing dead trees in selected Swiss forests N. A. BRETZ GUBY and M. DOBBERTIN* Sw iss Federal Institute for Forest, Snow and Landscape Research, Ziircherstrasse 111, CH-8903 Birmensdorf Switzerland

Abstract. Coarse woody debris and standing dead trees play a crucial role in biodiversity and the functioning of forest ecosystems. Little information is currently available concerning the amount and distribution of coarse woody debris in Swiss forests, and little is known about the relative abundance of lying dead trees and standing dead trees in managed and unmanaged forests. In this study, data were collected from eleven sites in order to assess the volume and the decay stages of coarse woody debris and of standing dead trees. There were substantial differences in deadwood volume between sites, but sampling variability was high. The amount of dead wood found

in the study sites was substantially smaller than the estimated amount from studies in virgin forests and in the range of values found for other managed and unmanaged forests in Europe. Most of the dead wood material belonged to young decay states. As expected, there was more dead wood in unmanaged than in managed stands, and in mature stands as compared with young stands. In particular, most unmanaged stands had significantly more standing dead trees than most managed stands, indicating that, in Switzerland, diseased and dead trees are removed by salvage cutting.

Key words. woody debris, dead trees, decay, ecosystem function, biodiversity.

INTRODUCTION

As the ability to utilize the fibre of forest products increases, less material is being left on site after timber harvesting (Graham et al., 1994). Standing and lying dead trees play a critical role in the functioning and productivity of a forest ecosystem (Harmon et al., 1986). Standing snags and large logs on the forest floor affect soil processes, soil fertility, hydrology, and wildlife micro habitat, thereby increasing biological diversity within stands (McCarthy & Bailey, 1994). Woody debris provide shelter for reproduction, cover from predators and a necessary substrate for many invertebrates, and standing snags provide breeding sites for a variety of taxa (Radcliffe et al., 1994). The lack of coarse woody debris (CWD) and standing dead trees, e.g. snags, stumps, logs and large branches, is one of the most crucial factors for the continued survival of many threatened species of hypophytes, lichens, fungi, insects, birds, and other vertebrates

* Corresponding author.

(Samuelsson, Gustafsson & Ingelog, 1994), and is therefore a threat to biodiversity in general. For example dead trees can be used by birds for nesting or as a base for aerial foraging (Bull et al., 1995; Torgersen & Bull, 1995). The systematic elimination of old trees and woody material in forests removes potential habitats and consequently precipitates a decrease in the number of specialized species (Albrecht, 1991). It has been estimated that forty percent of the forest wildlife species are threatened or in danger of extinction in Europe (INSECTA & Zaric, 1995). According to Franklin et al. (1989) a dead tree in a forest ecosystem is, ecologically, as important as a living one. CWD is an influential structural element of forest biodiversity and its presence in a range of forms adds significantly to levels of biodiversity, which develop as the forest approaches maturity (Ratcliffe, 1993).

The purpose of this study was to collect data from selected Swiss forests in order to assess the volume of dead wood present and to compare the ensuing results with those from other countries. The study sites are monitoring plots that have been established for the Swiss 'Long-Term Forest Ecosystem Research'

? 1996 Blackwell Science Ltd 327



328 N. A. Bretz Guby and M. Dobbertin

(LTFER). The LTFER is part of the Swiss Forest Investigation Programme that is conducted by the Swiss Federal Institute of Forest, Snow and Landscape Research in cooperation with the Swiss Federal Forest Administration.

STUDY SITES AND METHODS

Study sites

This study was conducted at eleven different sites, each covering an area of between 0.5 and 2 ha. Sites were located in four of the five main regions of Switzerland (Jura, Swiss Plateau, Prealps, Southside of the Alps) from 450 to 1400m.a.s.l. (Fig. 1). These are the sites of the LFTER project. The LTFER plots were selected according to a number of criteria, including site homogeneity, the abundance and sensitivity of the plant communities to environmental change, the presence of pre-existing data series or monitoring equipment and the willingness of the forest owners to cooperate in the project (Innes, 1995).

The plot characteristics are given in Table 1. The ecosystem and management type vary between sites, as does the stage of development. Stand density per hectare varies from 222 to 661 stems with a diameter at breast height (DBH) 2 12 cm.

Stands were defined as coniferous or deciduous if more than 90% of the trees belong to one or other species group, and as mixed coniferous or mixed deciduous if 50 to 900 of trees belong to one or the other species group. Only the most abundant tree species in a stand is given in the column 'Main species'. 'System of management' was divided into three classes: high forest, coppice and coppice with standards. As all the coppice sites have either been taken out of management or the management has recently changed, the term 'former . . .' has been used in Table 1. For the purposes of comparing results, sites were grouped according either to their current 'Management status' (managed v. not managed) or according to their 'Development stage'. As indicated by the dates in brackets, none of the stands has been unmanaged for more than 50 years. According to the development stage classification used in Switzerland in even-aged stands (Stierlin et al., 1994), our study sites include three different development stages: 'Polewood' (stands with mean diameter at breast height of the hundred biggest trees (DBHdom) between 12cm and 30cm), 'Middle-sized timber tree' (40cm < DBHdom< 50 cm),

and 'Large-sized timber tree' (DBHdom ?50cm). The Alptal site is managed using single tree selection and therefore can not be assigned a development stage according to the diameter of the 100 biggest trees. 'Polewood' is considered a stage on its own for the analysis. The stages 'Middle-sized', 'Large-sized timber tree' and the selection cut site were combined into the category 'Timber tree' (Bettlachstock, Chironico, Lausanne, Neunkirch, Othmarsingen, Vordemwald and Alptal) and compared with 'Polewood' (Isone, Jussy location A, Jussy location B, Novaggio).

Sampling method

Coarse woody debris (CWD) is defined in this study as any dead twigs, branches, stems and boles of trees and shrubs that have fallen and lie on the ground. Standing dead trees or snags (SDT) were sampled only if they were at least 1.3 m tall. A standing dead tree was defined as any dead tree still standing and a snag was defined as 'a standing dead tree or standing portion from which at least the leaves and smaller branches have fallen' (Kaennel & Schweingruber, 1995). Although tree stumps are important, they were not recorded because woody root mass is difficult to estimate accurately.

The sampling method was based on that used in the USA for fuelwood assessments in relation to fire hazards (Brown, 1974). It is important to underline that this so-called 'line intersect method' (Warren & Olson, 1964) assumes CWD is spatially randomly distributed, and randomly oriented. In each stand, sampling design consisted of 20-m long parallel line transects; the mid points of which were systematically distributed on a 20 x 40 m grid. Only CWD with diameter > 5 cm at the intersection with transects was sampled.

The CWD measurements consist of the diameter (to the nearest 1 cm) at each intersection point and the decay class. Decay was ordered into classes following Hunter (1990): (1) bark intact, small branches (<3 cm) present, wood texture intact, log elevated on support points; (2) bark intact, no twigs, log elevated but sagging slightly; (3) trace of bark, no twigs, wood hard, texture with large pieces, log sagging near ground; (4) no bark, no twigs, texture small, wood soft, texture with blocky pieces, all of log on ground; (5) no bark present, no twigs, wood soft and powdery texture, all of the log on ground.

In contrast to CWD sampling, all SDTs with DBH > 12 cm were assessed. The 12-cm threshold was chosen because this is the minimum diameter for (living or

? 1996 Blackwell Science Ltd, Global Ecology and Biogeography Letters, 5, 327-341



Coarse woody debris in Swiss forests 329

I

C Cu

N

I ci, C

C 0

a C)

C -c

is 0.cU

U) 0

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Table I . Description of study sites

No. Site Altitude Area Species Main species Management status Silvicultural Development (m.a.s.l.) (ha) mixture* systemt stage+

1 Alptal 1160 0.6 C Picea abies (L.) Managed HF None Karst.

2 Bettlachstock 1150 1.3 MD Fagus sylroltico L. Unmanaged HF LTT (since 1984)

3 Chironico 1360 2 C Picea abies (L.) Managed HF MTT Karst.

4 Isone 1220 2 D Fagus sylroatica L. Unmanaged Former CS P (since 1950)

5 Jussy A 500 1 D Quercus spp. Unmanaged Former CS P 6 Jussy B 500 1 D Querclus spp. Managed Former CS P 7 Lausanne 800 2 MD Fagus sylcatico L. Managed HF LTT 8 Neunkirch 580 2 D Fagus sjloatica L. Unmanaged Former CS LTT

(since 1950) 9 Novaggio 950 1.5 D Quercus spp. Unmanaged Former CF P

(since 1970) 10 Othmarsingen 480 2 D Fagus syloatica L. Managed Former CS LTT 11 Vordemwald 480 2 MC Abies albo Mill. Managed HF LTT

* C, coniferous; MC, mixed coniferous; D, deciduous; MD, mixed deciduous. t HF, high forest; CS, coppice with standards; CF, coppice forest. + LTT, large-sized timber tree; MTT, middle-sized timber tree; P, polewood.

dead) trees recorded in the forest health inventories on the LTFER-plots. SDT decay was assessed following Hunter (1990), namely: (3) standing dead tree with most of its branches intact, (4) dead tree with few branches left and loose bark, (5) dead tree without branches or bark, (6) broken stem and (7) decomposed broken stem. The number of stems in each decay class were recorded for the entire plot.

Data analysis

Separate analyses were conducted on live trees, CWD and SDT to describe the composition and the structure of each stand. Density (number of live and dead stems ha-' > 12 cm DBH) and percentage of dead trees were determined at each site. Analytical methods for the estimation of the volume of woody fuels and logging residues were based on those developed by Warren & Olson (1964) and Van Wagner (1968).

Assuming that pieces are cylindrical, horizontal and randomly oriented, the volume of CWD can be calculated using Van Wagner's formula (1968):

V= * Yd2I8L,

where V is volume of wood per unit area, d piece diameter, L length of sample line.

The estimated biomass of SDT was converted to volume (m3 per hectare). With diameter at breast height (DBH) being the only available variable, biomass was calculated using Singh's formula (1981, adapted by Krauchi, 1994). Singh showed that the inclusion of tree height added only little to the prediction accuracies and chose to model biomass as a function of DBH:

Biomass = a, + a2DBH + a,DBH2 + a4DBH'

where a, to a4 are the coefficients for calculating wood (without bark) biomass. Volume was calculated using average densities for air-dried wood (0.7 gcm-3 for broad-leaved trees, 0.46 g cm' for coniferous trees; Zimmermann, 1982).

We used two multiple comparison tests that are suitable for comparisons between means with unequal variances (Bonferoni's t-statistics (Miller, 1981) and Tamhane's multiple pairwise comparisons (Tamhane, 1979)). It is known that the Bonferoni method produces relatively conservative estimates of the standard error. Tamhane showed, for simulated data with highly unequal variances, that his test controlled the confidence intervals for pairwise comparisons well being at the same time slightly more liberal than other tests.

?D 1996 Blackwell Science Ltd, Global Ecology aind Biogeographjy Letters, 5, 327-341




Table 2. Live stem density, standing dead trees (total number, 'Yo of all trees, m3), and coarse woody debris (m) per hectare for all study sites

Standing trees Coarse Total woody debris dead wood

Live Dead

(stems ha') (stems ha-') (o) (m3ha') (mha') (- rha')

Alptal 303 0 0.0 0.0 3.9 3.9 Bettlachstock 464 33 7.1 29.2 24.8 54.0 Chironico 379 16 4.2 4.2 21.6 25.8 Isone 647 1 0.2 0.1 0.7 0.8 Jussy A 645 60 9.3 5.9 13.8 19.7 Jussy B 580 9 1.6 1.0 5.3 6.3 Lausanne 297 1 0.2 <0. 1 6.3 6.4 Neunkirch 222 9 3.8 13.8 28.2 42.1 Novaggio 661 10 1.5 0.6 0.6 1.2 Othmarsingen 267 0 0.0 0.0 3.7 3.7 Vordemwald 598 5 0.9 0.8 7.4 8.2

Unmanaged sites* 510 17 3.4 9.3 13.4 22.7 Managed sites* 401 6 1.4 1.1 8.9 10.1

* Area weighted average.

Table 3. Coefficients of variation for coarse woody debris measured with the line transects

Study sites No. of transects Mean CWD volume Standard deviation Coefficient of variation (mhha-') (m'ha- ')C,)

Alptal 9 3.9 5.5 139.7 Bettlachstock 16 24.8 26.2 105.7 Chironico 28 21.6 24.1 111.4 Isone 24 0.7 1.5 205.8 Jussy A 15 13.8 14.3 103.9 Jussy B 12 5.3 5.2 97.7 Lausanne 30 6.3 14.8 234.3 Neunkirch 24 28.2 40.1 142.0 Novaggio 21 0.6 1.6 276.2 Othmarsingen 30 3.7 7.2 196.8 Vordemwald 32 7.4 5.7 76.9

RE S U LTS

While there were substantial differences in CWD volume between the sites, the standard deviations of the transect samples were high (Tables 2 and 3). Only few significant differences between most of the sites could be found at the 5% probability level for CWD

for both methods (Fig. 2a, and Table 4a). As expected Bonferoni's method was slightly more conservative than Tamhane's. We repeated the same procedure for the percentage of dead trees found on the sites using statistics for the sampling for proportions (Cochran, 1977). For SDT more significant differences existed between sites than for CWD (Fig. 2b, and Table 4b).

(C 1996 Blackwell Science Ltd, Global Ecology and Biogeography Letters, 5, 327-341




a) 60-- Unmanaged Managed

50 - T

40-

30-- I - I

20 -

0

u 0 - T

*~ polewoods0ands

10-

14 - naae aae

B 8--f

0- I

m > tg

z bO

* polewood stands

Fig. 2. Bonferoni confidence intervals (-U5nmn) for coarse woody debris (mgha M ) and standing dead tree percentage.

(C 1996 Blackwell Science Ltd, Global Ecology and Biogeograph,y Letters, 5, 327-341




Table 4. Significant differences between sites (oc=5 %) for (a) coarse woody debris (m3ha-') and (b) standing dead tree percentage using Tamhane's multiple pairwise comparison test. (a)

Sites* Neun. Bett. Chir. Jus. A Vor. Lau. Jus. B Alp. Oth. Iso.

Bett. -

Chir. - -

Jus. A - - -

Vor. - - -

Lau. - - - Jus. B - - - - - - Alp. - - + _ Oth. - - + Iso. - + + + + Nov. - + + + + _ _

*, Sites are in descending order for CWD. +, Significant difference. - Non-significant.

(b)

Sites* Jus. A Bett. Chir. Neun. Jus. B Nov. Vor. Lau. Iso. Alp.

Bett. Chir. + Neun. + Jus. B + + - -

Nov. + + + - - Vor. + + + Lau. + + + + - + Iso. + + + + - + - - Alp. + + + + + + 0th. + + + + + +

*, Sites are in descending order for SDT. + Significant difference. -, Non-significant.

Coarse woody debris volume

On average, the unmanaged stands have a greater volume of CWD than managed stands (Figs 2a and 3a), as might be expected. In particular, Bettlachstock, Jussy A and Neunkirch had very high CWD values. However, Isone and Novaggio, both polewood stands, do not follow this pattern, having very little CWD. In contrast, the managed stand at Chironico has a greater volume of CWD than most of the unmanaged stands.

Substantially less CWD was present in polewood stands than in timber tree stands (Figs 2b and 3b). Of the four polewood stands, three have a very low amount of CWD (Isone, Jussy B, Novaggio). In polewood stands the predominant size of CWD may be smaller than the minimum diameter used for the assessment,

and observations made during the fieldwork support this hypothesis.

Percentage and volume of standing dead trees

The percentage of dead trees is significantly higher for the unmanaged sites Jussy A and Bettlachstock than for most other sites (Fig. 2b). The managed sites Alptal, Lausanne, and Othmarsingen, and the unmanged Isone site, have significantly lower dead tree percentages than the unmanaged sites Neunkirch, Bettlachstock, and Jussy A, and the managed Chironico site (Fig. 2b, Table 4b).

Three of the four unmanaged stands and the

(C 1996 Blackwell Science Ltd, Global Ecology and Biogeography Letters, 5, 327-341




16- 16 CWD 14

~~~~~~~E SDT

12

10-

S

4-

2-

unmanaged managed polewood timber tree

Fig. 3. Mean volume (m3ha-') of coarse woody debris and standing dead trees grouped by management method (a) and development stage (b)

managed site at Chironico have more than 3%0 SDT (Neunkirch 3.8%; Bettlachstock 7.10 o; Jussy A 9.3%, Chironico 4.2% o) (Table 2, Fig. 2b). Compared with the 2.71/0 dead trees estimated in the National Forest Inventory for Switzerland (EAFV, 1988) the managed sites Alptal, Lausanne, Othmarsingen, and Vordemwald and the unmanaged Isone site have significantly fewer dead trees than is the norm for Switzerland, and the unmanaged sites at Bettlachstock and Jussy A have significantly more.

The average volume of SDT is also much higher in unmanaged than in managed stands (Fig. 3a), even though three of the five unmanaged stands were polewood stands and polewood stands have less SDT than timber tree stands (Fig. 3b).

Coarse woody debris diameter classes (Table 5a)

A notable feature of the distribution and abundance of CWD in the forests is the absence of larger diameter logs (i.e. >35 cm) (Table 5a). The greatest amount of dead wood (number of pieces) is provided by small diameter pieces (5cm < CWD <10 cm). This is the case for all plots except for Chironico and Alptal. On average, there is more CWD in higher diameter classes

(>20 cm) in unmanaged than in managed stands (Fig.4a). More CWD in the smallest diameter class was observed in polewood stands as compared with timber tree stands (Fig.4b).

Standing dead tree diameter classes (Table 5b)

Generally, most dead trees belonged to the smaller diameter classes. However, at Bettlachstock and Neunkirch, the majority of the dead trees were in the diameter class greater than 35 cm. The main difference between management types was the low number of SDT found in the larger diameter classes in managed stands even though only one of the six managed sites was not a timber tree stand. In unmanaged timber tree stands 61'YO of all observed dead trees had a DBH of more than 35 cm as compared to only 7% in the managed timber tree stands.

Coarse woody debris decay classes (Table 5a)

Decay class (4) was infrequent and only observed in a few plots, decay class (5) was only found at Vordemwald. Decay class (2) was the most common





80r unmanaged | polewood 80

managed timber tree 70-7

60

50

40

30 /

c cn 6 cs c m

Fig. 4. Percentage of coarse woody debris pieces by diameter classes grouped by management method (a) and development stage

(b).

out of the five classes in all sites. The decay class distribution did not differ between stands dominated by polewood and timber trees. Managed stands had more CWD in higher decay classes than unmanaged stands, but this may be due to interactions with altitude, tree species, size of CWD, or stand density.

Standing dead tree decay classes (Table 5b)

The most frequent decay class for SDT is class (4). Decay class (7) is found in only a few stands. The percentage of SDT in decay class (4) is higher in managed stands (70%0) than in unmanaged stands (58%).

DISCUSSION

Although a large number of papers describe the importance of CWD in the forest ecosystems, surprisingly few papers describe how it should be assessed. Consequently, there are no widely accepted methods for its inventory. The standard deviations for CWD assessed on the transects varied for the study sites between 80% and 280% of the mean volume (Table

3). This is not surprising because some sites had very little CWD and two of them nearly none. Excluding these two sites, the average coefficient of variation was 1 300%.

For infrequent sampling on long-term monitoring sites, the line intersect method is a convenient and relatively cheap method to estimate CWD volume. However, many transects may be necessary to achieve a sufficiently small sampling error if relatively small changes in time need to be detected. For example, if a target standard error of 20% of the mean is to be set, which would help to better distinguish between sites, at least forty-two transects in each plot would have to be sampled.

The study sites used here were not selected to provide representative estimates for Switzerland, and this is confirmed by the difference (for SDT) with the results of the National Forest Inventory (EAFV, 1988). The results can not therefore be extrapolated to all Swiss forests. In the study sites, there was an average of 9.3 m3ha-' SDT in unmanaged stands and only 1.1 m3ha ' SDT in managed stands. The Swiss National Inventory (EAFV, 1988) estimated the volume of SDT for Swiss forests to be 3 m3ha- '. No distinction between managed and unmanaged stands was made in the





Table 5. Number of coarse woody debris pieces (a) and standing dead trees (b) and their percentage distribution for diameter and decay classes (a)

No. Coarse woody debris (%) pieces

Diameter classes (cm) Decay classes

5-9 10-14 15-19 20-24 25-29 30-34 ?35 1 2 3 4 5

Alptal 5 40 60 0 0 0 0 0 40 20 40 0 0 Bettlachstock 35 40 29 17 14 0 0 0 23 34 29 14 0 Chironico 72 40 45 11 3 0 0 1 11 40 35 14 0 Isone 6 83 17 0 0 0 0 0 50 17 33 0 0 Jussy A 47 81 15 2 0 2 0 0 21 55 19 5 0 Jussy B 21 90 10 0 0 0 0 0 10 33 48 9 0 Lausanne 22 64 27 0 0 5 4 0 9 46 36 9 0 Neunkirch 95 79 15 1 1 1 0 3 24 47 21 8 0 Novaggio 5 100 0 0 0 0 0 0 0 100 0 0 0 Othmarsingen 28 79 18 3 0 0 0 0 15 64 14 7 0 Vordemwald 71 85 15 0 0 0 0 0 32 17 24 20 7

(b)

No. dead Standing dead trees (%) trees

Diameter classes (cm) Decay classes

12-14 15-19 20-24 25-29 30-34 ? 35 4 5 6 7

Alptal 0 0 0 0 0 0 0 0 0 0 0 Bettlachstock 42 9 12 12 5 14 48 39 39 22 0 Chironico 32 28 44 3 9 6 9 60 31 3 6 Isone 2 0 50 50 0 0 0 50 0 0 50 Jussy A 60 50 23 12 12 2 1 92 7 1 0 Jussy B 9 11 56 22 11 0 0 89 11 0 0 Lausanne 1 100 0 0 0 0 0 100 0 0 0 Neunkirch 17 0 6 0 0 0 94 38 50 12 0 Novaggio 15 60 33 7 0 0 0 47 13 33 7 Othmarsingen 0 0 0 0 0 0 0 0 0 0 0 Vordemwald 11 46 36 9 0 9 0 82 0 18 0

National Inventory analysis, and neither CWD volume nor decay classes were assessed.

As expected, the management status plays an important role in the occurrence of dead wood. Most managed stands have less dead wood than the unmanaged stands. One possible reason is that in Switzerland, in addition to regular management practices, diseased and dead trees are removed by salvage cutting. The diameter distributions suggest that in managed stands, it is mainly the large dead trees that have been removed. Exceptionally large amounts of dead wood were found in the managed stand at

Chironico. The stand is not easily accessible and therefore management activities may be less intensive than in the other managed stands. It is probably no coincidence that this plot is the nesting site of a pair of black woodpecker (Drycopus maritius). While the nest holes are in the stem of a living silver fir, there is plenty of evidence of woodpecker activity on the SDT, CWD, and the dead stumps on the plot.

Two of the unmanaged sites (Isone and Novaggio) have very little CWD. Possible reasons include development stage (both are polewood), removal of dead wood for domestic use, and fire history (both are





located in southern Switzerland where fire constitutes a significant hazard to forests). There is evidence that the stands are within an area subject to fires in the past, which may have reduced CWD mass. This hypothesis is currently being examined using dendroecological methods. Forest development stage also influences the results: differences were found between the younger stage ('Polewood') and the older stages (defined in this study as 'Timber tree'). These results are comparable to those obtained in mixed-hardwood stands in the central Appalachians in Western Maryland (McCarthy & Bailey, 1994).

As indicated above, the lower quantities of CWD in polewood forests may be the result of the minimum diameter used in the sampling design. There is very little information about the development of the CWD fraction during forest development, although it is known that the amount of woody litterfall increases through a succession at any particular site (Long, 1982). Bormann & Likens (1994) suggest that the CWD fraction in a clear-felled forest initially declines, but returns to pre-cutting values after about 50 years of regeneration. This model may not, however, be appropriate for a coppiced forest developed following the cessation of management.

For our sites we found very few CWD pieces and SDT in higher decay classes. One possible explanation is that the rate of decay varies between classes, so that the residence time of a piece of wood in a given class also varies. For example, Bormann & Likens (1994) suggest that wood decay follows a delayed exponential form: slow initially, fast in the middle stages of decay and then slowing again in the more advanced stages of decay. Such a sequence would have an impact on the sampling probability, but would not explain the lack of wood in the highest decay classes. The hypothesis of differential decay rates through time remains to be tested, and it is not clear whether decay rates determined in, for example, the northeast USA (Spaulding & Hansbrough, 1944), are relevant to the climatic conditions of Switzerland or to forests where casual removals of CWD by humans may be significant. Alternatively, the selective felling of SDTs for sanitation purposes will reduce the amount of woody litterfall that reaches the ground in a decayed state, thereby reducing the amount of debris that directly enters the high decay classes (c.f. Boddy & Rayner, 1983). Another possibility is that wood in the higher decay classes may have fallen below the minimum sampling diameter size.

Managed stands showed slightly more CWD in

higher decay stages than unmanaged stands. A possible explanation is that managed stands have a more open canopy, which accelerates wood decay. A second reason may be that CWD pieces are on average smaller in managed stands and therefore decay faster. Yet another possibility is that initial decay rates of woody debris are higher in managed stands (particularly after a thinning) but then slow down as the canopy becomes denser. This would occur because of changed microclimatic conditions at the forest floor, including increased soil temperature, increased moisture availability and increased nutrient availability (Covington, 1976, cited in Bormann & Likens, 1994). On the other hand, managed stands have less SDT in higher decay stages than unmanaged stands, possibly because management practices in Switzerland may not allow standing dead trees to reach high decay classes.

The lack of CWD with a diameter in excess of 35 cm is remarkable, given the presence of mature broad- leaved trees at a number of the sites. There was no indication of a peak in the 10-20cm size classes, as has been found in Swedish forests (Samuelsson et al., 1994). This may be related to differential decay rates of woody material, with larger material decaying faster as a result of increased attack by a variety of insects (Edmonds & Eglitis, 1989). However, in Switzerland, the preponderance of dead wood in the smallest diameter classes almost certainly reflects the intensive human exploitation of forests that has occurred in the past and which still occurs in some forests today. This is a significant habitat for many species, and its absence suggests that the fauna that depend on it may be impoverished in many Swiss forests. It is possible that the amount of dead wood in the plots may increase through time, particularly in the forest reserves, and the quantities present will be monitored at regular intervals (every 5 years).

Comparison with other studies

Results vary so much from one study to another that comparisons are difficult: the minimum size of the assessed CWD and the minimum diameter at breast height of SDT differ, units for calculating volume, biomass and area are not constant. More often, the information that is given is insufficient to make comparisons, and frequently CWD and SDT are not distinguished or are unavailable. Therefore CWD volume, SDT volume, and total dead wood volume have been presented separately in this study (Table 6).

Mean volume of lying dead wood in the managed





Table 6. Comparison between dead wood amounts at various sites within a range of countries

Location Forest type Management Min. SDT Min. CWD Total dead References method* diameter (m3ha') diameter (m3ha') wood

(cm) (cm) (m3ha -)

Europe Switzerland

This study Various M 12 1 5 9 10 This study Various U 12 9 5 13 22.5 Derborence Virgin silver fir U 8 60-171 Leibundgut

(1993) Laupersdorf Various M 8 3-4.5 8 1-2 4-6.5 Leuba (1996) Laupersdorf Various U 8 10 8 4 14 Leuba (1996)

Great Britain England Deciduous M <5 <5 12-23 Kirby, Webster

& Antckzak (1991)

Finland

Old spruce M 5 5 8 Siitonen (1994) Old spruce U 5 5 32 Siitonen (1994)

Sweden Coniferous U 7 Albrecht (1991)

Poland Deciduous M <5 <5 10 Kirby et al.

(1991)

Deciduous U <5 <5 94 Kirby et al. (1991)

Germany Various U 50-200 Albrecht (1991) Various M 1-5 Albrecht (1991)

Bavaria Deciduous U 10-54 15-54 9-108 Detsch, Kolbel & Schulz

(1994) Bavaria Coniferous <6 3 <6 5 8 Burschel (1992)

Eastern part Slovakia Silver-fir-beech U 34-46 Leibundgut

(1993) Bosnia Silver-fir-beech U 38-222 Leibundgut

(1993) Slovenia Silver-fir-beech U 157-422 Leibundgut

(1993) USA

Central Deciduous M 2.5 2.5 40 McCarthy & Appalachians Bailey (1994) Pacific Douglas fir 15 150-635 15 300-570 450-1405 Harmon et a! Northwest (1986)

Douglas fir 250-534 Albrecht (1991) Various U 60-200 Albrecht (1991)

Asia Kashmir Coniferous U <6 7-78 <6 17-197 31-222 Burschel (1992)

* M, managed; U, unmanaged.





stands is lower than reported for selected English forests, which range from 12 to 23 m3ha-1 (Kirby et al., 1991), but higher than reported for managed forest in Germany (I to 5 m3ha -l; Albrecht, 1991). The results for the total amount of deadwood in the present study correspond, in order of magnitude, to the results found for selected Finnish forests, both for managed and unmanaged stands (32 m3ha - and 8 m3ha1 (minimum diameter of dead material 5cm; Siitonen, 1994)). A recent study in the Laupersdorf forest district in Switzerland found between 1-2 m3ha-l CWD and 3-4.5 m3ha-' SDT for various managed forests and 4m3ha-' CWD and 10m3ha-1 SDT for unmanaged stands (Leuba, 1996). These CWD values are lower than those in our study, whereas SDT for managed stands is higher and SDT for unmanaged stands is similar to our results.

Results from temperate rain forests in the USA reveal values fifty times higher than those of this study. A study in the Pacific Northwest USA by Harmon et al. (1986) gave the following range of results for Douglas fir forests: volume of logs (? 15 cm of diameter) 309 to 574 m3ha-1 and volume of snags (? 15 cm of diameter) 153 to 635 m3ha-l. Other studies in Douglas fir forests (Radcliffe et al., 1994) found 423 m3ha-l in the young stage, 250 m3ha-l in the mature stage and 534 m3ha-1 in the old stage. For a number of virgin forests in the south of Europe, volume of SDT was found to be between 20 and 422 m3ha-1 (Leibundgut, 1993), depending on development stage and forest type. Virgin and semi-natural temperate German forests had a volume of dead wood up to eight times greater than unmanaged stands in this study: 50 to 200m3ha-1 in Germany (Albrecht, 1991) and only 22.7 m3ha-1 in this study. A silver fir (Abies alba Mill.) virgin forest in Derborence (Switzerland) had between 60 and 171 m3ha-1 SDT (Leibundgut, 1993), which is still substantially higher than that found in unmanaged stands in this study. All these results show that different amounts of volume can be found depending on the forest type, development stage and management practice.

CONCLUSION

Since dead wood has been recognized as a key element for biodiversity (IUS, 1992), spatial distribution, volume and decay estimates of CWD and SDT can be used as indicators of biodiversity and stability of forest ecosystems (Ratcliffe, 1993). It has been proposed that

there should be a minimum volume of dead wood in forests (Ammer, 1991; Steventon, 1994). For example, Ammer (1991) suggests a total dead wood volume of 5-10 m3ha - as a target for German forests, with optimal amounts between 15 and 30 m3ha-1. Of the eleven sites in our study, seven would reach this target and four sites would have optimal amounts of deadwood. In addition, spatial distribution and tree species composition play an important part in the ecological value of dead wood (Utschick, 1991; Rauh & Schmitt, 1991). For example, many organisms, particularly bryophytes, are better suited to logs with larger diameters (Samuelsson et al., 1994). Other studies have shown that cavity nesting birds select trees with larger than average diameters (Raphael & White, 1984).

This study suggests that in order to define meaningful management objectives for dead wood, and to provide ecological and silvicultural interpretations of dead wood inventories, more qualitative and quantitative studies are needed for various forest types, local site conditions, development stages, and sylvicultural treatments. While there has been a limited amount of work done on the extent of dead wood in different ecosystems, the importance of dead wood as a habitat for a great variety of species suggests that much greater attention should be given to it. In particular, more information is required on the variation in dead wood quantities between ecosystems, variations in its distribution at a local scale and information on its rates of decay under differing environmental conditions. There is also an urgent need for more studies linking structural studies such as this with studies of the actual organisms that use the dead wood as a habitat, since the volume of dead wood is only a proxy for investigations of the species that depend on it.

ACKNOWLEDGMENTS

We are grateful to John Innes, Michele Kaennel, Norbert Krauchi, and the anonymous reviewers for their helpful comments during the preparation of this manuscript, to Urs Zehnder for his help and information in the field, and to Carmen Frank for the preparation of Fig. 1.

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Quantitative Estimates of Coarse Woody Debris and Standing Dead Trees in Selected Swiss Forests