Legacies from natural forest dynamics: Different effects of forest management on wood-inhabiting fungi in pine and spruce forests

Jogeir N. Stokland; Karl-Henrik Larsson

Studies on the relation of the diversity of wood-decaying fungi to elevation are scarce, and their results are not consistent. We found that the elevation gradient and structural characteristics of a Picea abies forest underlie changes in the species richness and composition of wood-decomposing fungi. The occurrence of macrofungal sporocarps on logs on the ground was recorded over 3 years in 12 study plots (total area 2.4 ha) on a mountain slope (1,220–1,335 m) in the Bohemian Forest, Czech Republic. The majority of species was more abundant in plots with a high mean volume of logs. The mean volume of logs was negatively related to elevation, which in turn had a negative influence on the occurrence of fungi. A negative relation of the high total volume of standing snags to the occurrence of fungi may be due to recent mortality caused by a bark beetle outbreak, albeit followed by the input of fresh logs that favoured a limited group of species. The diversity of fungi was also explained by the mean volumes of logs separated into decay classes. Numbers of red-listed species increased with the mean volume of logs and decreased with elevation. Large logs in later stages of decay provide essential habitat for the formation of sporocarps of red-listed species.

Wood-decaying fungi are essential for the functioning of forest ecosystems. They provide habitat for many other organisms and enable the regeneration of forests throughout the world. Since wood decomposition is a decisive process in nutrient recycling, soil formation and the carbon budget of forest ecosystems, it is receiving increasing attention from forest ecologists, pathologists and managers. Research has focussed on the factors driving the species-richness of wood-decomposing organisms and is moving on to analyse the effects of this species-richness on ecosystem functioning. Coarse woody debris (CWD) and its associated wood-decaying organisms have been drastically reduced in abundance and diversity by forestry and so these features often have potential as conservation indicators. Protective measures at a landscape level are needed for threatened wood-inhabiting fungi. These include restricting salvage operations in windthrow stands, actively encouraging the accumulation of deadwood in forests, and facilitating decay in standing trees by inoculating them with fungi. Here, we aim to collect and summarize recently produced work on deadwood ecology, pointing out research gaps and perspectives.

Forest Ecology and Management 261 (2011) 1707–1721 Contents lists available at ScienceDirect Forest Ecology and Management journal homepage: www.elsevier.com/locate/foreco Legacies from natural forest dynamics: Different effects of forest management on wood-inhabiting fungi in pine and spruce forests Jogeir N. Stokland a,b,∗ , Karl-Henrik Larsson a a b Natural History Museum, University of Oslo, P.O. Box 1172 Blindern, N-0318 Oslo, Norway Norwegian Institute of Forest and Landscape, Høgskoleveien 8, NO-1432 Ås, Norway a r t i c l e i n f o Article history: Received 16 September 2010 Received in revised form 21 December 2010 Accepted 4 January 2011 Available online 2 March 2011 Keywords: Coarse woody debris Boreal forest Polypore Corticoid Wood-decaying fungi Saproxylic a b s t r a c t The species composition of wood-inhabiting fungi (polypores and corticoids) was investigated on 1138 spruce logs and 992 pine logs in 90 managed and 34 natural or near-natural spruce and pine forests in SE Norway. Altogether, the study included 290 species of wood-inhabiting fungi. Comparisons of logs with similar properties (standardized tree species, decay class, dimension class) in natural and managed forests showed a significant reduction in species number per log in managed spruce forests, but not in managed pine forests. The species number per log in managed spruce forests was 10–55% lower than on logs from natural spruce forests. The reduction was strongest on logs of large dimensions. A comparison of 200–400 spruce logs from natural and managed forests showed a 25% reduction in species richness corresponding to a conservative loss of ca. 40 species on a regional scale. A closer inspection revealed that species confined to medium and very decayed spruce logs were disfavored in managed forests, whereas species on early decay classes and decay generalists were unaffected. Similarly, species preferring large spruce logs were disfavored in managed forests. Forest management had strongest impact on low-frequent species in the spruce forests (more than 50% reduction), whereas common species were modestly affected. Corticoid fungi were more adversely affected than polypore fungi. These results indicate that wood-decaying fungi in pine forests are more adapted to forest disturbances than spruce-associated species. Management measures securing a continuous supply of dead wood are more important in spruce forests than in pine forests. © 2011 Published by Elsevier B.V. 1. Introduction Forest management in Fennoscandia has profoundly changed the structure and dynamics of boreal forests. These changes comprise reduced abundance and diversity of decaying wood as well as major shifts in the spatio-temporal dynamics of dead wood. The total volume of dead wood has declined by more than 90% compared to the amount in corresponding natural forests (Siitonen, 2001). Over-mature forests where large-dimension dead wood is naturally created has declined to less than 10% of the total forest area in Fennoscandia (Stokland et al., 2003) and the amount of oldgrowth natural forests, where dead wood is abundantly present, has declined even more, for example to 1–2% of the forest area in southern Finland (Virkkala et al., 2000). In addition to this large-scale ∗ Corresponding author at: Natural History Museum, University of Oslo, P.O. Box 1172 Blindern, N-0318 Oslo, Norway. Tel.: +47 22851884. E-mail addresses: j.n.stokland@nhm.uio.no (J.N. Stokland), k.h.larsson@nhm.uio.no (K.-H. Larsson). 0378-1127/$ – see front matter © 2011 Published by Elsevier B.V. doi:10.1016/j.foreco.2011.01.003 loss of habitats and substrates, there have been major changes in forest dynamics and dead wood dynamics. These changes include an effective suppression of forest fires, especially in pine forests (Linder and Östlund, 1998; Granström, 2001) and a shorter rotation in spruce-dominated forests. Thus, the forest landscape has changed from more or less continuous natural forests to a situation where such forest occurs as fragments embedded in a matrix of managed forests with low CWD abundance and reduced diversity of different dead wood qualities. The reduction in dead wood abundance has a major impact on the species diversity of wood-inhabiting fungi. In Fennoscandia there are many examples of species that show strong population declines due to the reduction of natural forests and dead wood abundance (Edman et al., 2004a; Penttilä et al., 2004; Stokland and Kauserud, 2004; Penttilä et al., 2006). In Sweden, about 50% of the red-listed forest species, including several hundred fungal species, depend upon dead wood (Gärdenfors, 2005). Wood-inhabiting fungi are very diverse and more than 2000 species of wood-inhabiting fungi are known from the Nordic countries (Stokland and Meyke, 2008). The polypores and corticoid fungi 1708 J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 that are the focal organisms of this study play essential functional roles in the forest ecosystem: several species are important disturbance agents, they are principal wood decayers that facilitate essential nutrient recycling and they release and mobilize resources for a large number of wood-inhabiting invertebrates as well as other wood-inhabiting fungi. Nearly all wood-inhabiting fungi exhibit specific adaptations to utilize different dead wood qualities (different tree species, decay stages and dimension classes), and these adaptations have evolved during million of years under natural forest dynamic regimes (Stokland, 2011). In this study, we explicitly take such adaptations into account when assessing the effects of forest management. The importance of dead wood is now acknowledged by the forestry sector (Raivio et al., 2001). Management actions like key habitat protection, green tree retention and coarse woody debris retention all contribute to increase the amount of dead wood. These actions will improve the situation but it will take many decades (Ranius and Kindvall, 2004). It is probably not sufficient to simply increase the amount of dead wood as such. It is also important to realize that dead wood is a collective term that covers a wide diversity of qualities - in particular different tree species, dimension classes and decay phases (see Stokland et al., 2004). Almost all wood-inhabiting species exhibit clear preferences for these qualities and in addition they have developed alternative strategies to utilize different types of dead wood. It is therefore important to adopt a detailed approach when assessing effects of forest management on wood-inhabiting species and developing strategies to successfully counteract unwanted side-effects such as species extinctions. In this study we adopt such a refined approach and incorporate several important aspects. The aim this study is to assess whether boreal wood-inhabiting fungi confined to different qualities of dead wood are equally sensitive to forest management. More specifically, we ask whether species confined to the following types of dead wood respond differently: (1) pine- versus spruceassociated species, (2) species associated with different decay stages, (3) species confined to different dimension classes. We also ask whether species belonging to (4) different fungal groups (polypore versus corticoid fungi) and (5) species with different degree of abundance (rare, uncommon, common) respond differently to forest management. These questions are illuminated by comparing the occurrence of wood-inhabiting fungi on standardized amounts of dead wood in natural forest with their occurrence on similar amounts of dead wood in managed forests with different degree of management intensity. We repeat this comparison in pine-dominated and spruce-dominated forests across several vegetation zones and thereby cover a wide regional extent. 2. Forest history of the study area 2.1. Study area This study has been carried out on a regional scale in SE Norway. The investigated area is ca 250 km × 400 km and covers four biogeographical zones from the hemi-boreal zone in the south to the north boreal zone in the north and west (Fig. 1). This is the main forest region in Norway and comprises about 60% of the productive forest in the country. The climatic variation is mainly caused by altitudinal difference from the sea level to the coniferous tree line (altitude of ca. 950 m) close to the mountain range in north and west. Several large valleys cut through the area that often has a rather rugged terrain. This produces distinct local gradients from dry hill ridges to moist valley bottoms, and sun-exposed south-west facing slopes and shady north-east facing slopes. These local gradients are reflected in a Fig. 1. Location of the sample plots in the study area. mosaic of pine- and spruce-dominated forests with pine forests in dry, sun-exposed sites and spruce forests in mesic and shady sites. Birch and aspen are common subordinate broad-leaved trees in coniferous forests in all vegetation zones. Broad-leaved forest dominated by temperate tree species (especially Quercus robur, but also Tilia cordata, Acer platanoides and Corylus avellana) are common in the lowland hemi-boreal zone, especially on south-facing slopes. 2.2. Human impact The study area has a 500 years history of systematic resource utilization and it is the region in Fennoscandia with longest large-scale timber extraction. This was facilitated by a natural transport system of many large rivers running through the area. During the 1500s the export of timber to Europe increased considerably (Tveite, 1964) and timber from this region contributed to expand large cities like Copenhagen, Amsterdam and London. The initial logging took place around the shipping harbors and along the lower parts of the main rivers, but the floating infrastructure expanded and logging reached the tree line by the end of the 1700s. Dimension logging, i.e. extraction of timber with a minimum diameter, was the prevailing method during most of this period. The timber resources were gradually depleted until a critical lack of resources was reached in the early 1900s (Fig. 2). This initiated the national forest inventory (NFI) in 1919 and caused a complete shift in the forest management practices, where dimension logging was prohibited in 1932 and stand replacing (clear-felling) gradually took over and prevailed from the 1950s (Rolstad et al., 2002). This shift in management practices has led to a steady increase in standing volume. This historical development in standing volume must have caused a corresponding, but delayed development in dead wood abundance since the decomposition of coarse wood debris takes 70–200 years depending on climatic zone (Hytteborn and Packham, 1987; Hofgaard, 1993). In Norway, the historical low level in dead J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 the nearest 10% coverage). A team of field biologists measured all downed logs within the plot and sampled fungus fruit-bodies on all or a subset of these logs (see details below). 160 Volume (m 3/ha) 140 120 Standing volume 3.3. Log measurements 100 NFI 80 60 1709 Natural reference level Dead wood 40 20 0 1600 1650 1700 1750 1800 1850 1900 1950 2000 year Dimension logging Stand mgmt. Fig. 2. Tentative historical development (1600–2000) of average standing volume and dead wood in spruce forests in the study area. Dotted lines represent calculated values and expert assessments, solid line represent measured values. The historical development in standing volume has been recalculated from statistics on timber export from Norway (Rolstad et al., 2002) and from National forest inventory (NFI) statistics since 1921. The natural reference level of dead wood is calculated as the same level found in natural forests today (in this study). The historical development in dead wood abundance is derived from the standing dead wood with a time delay due to decomposition time. wood abundance probably occurred some 50 years after the standing volume, i.e. around the 1970s–1980s. Today, the dead wood abundance is increasing from an unpreceded historical low level. It is also of interest to notice that the largest dimension has had the longest period of extraction, whereas systematic logging of trees with basal diameters below 30 cm began during the second half of 1800s. 3. Material and methods 3.1. Sample plots This study is based on 64 pine plots and 60 spruce plots from SE Norway (59–62◦ N). Most plots (n = 107) were chosen as a balanced stratified random sample among 3000 pre-established national forest inventory (NFI) plots in a 3 km × 3 km grid. The stratification variables were development class – 5 classes from clear-cuts to overmature stands; altitude – 300 m intervals from the sea level to the tree line at 900 m; and dominating stand tree – pine (57 plots) or spruce dominance (50). The additional 17 plots were selectively established in over-mature or old-growth pine (7) or spruce (10) stands. These plots were deliberately positioned in sites with a high abundance of dead wood in all decay classes; i.e. there had been a continuous supply of dead wood for several tree generations. The 124 plots make up the majority of a larger study of 159 sample sites that also included sites dominated by deciduous trees. Each plot normally had a size of 0.5 ha. In sites with very high CWD abundance, the plot size was reduced to 0.25 ha. In sites where the CWD abundance was very low (<15 logs/0.5 ha), the plot size was increased in a predefined stepwise manner until minimum 15 logs were encountered or the plot size reached an upper limit of 1.0 ha. 3.2. Plot measurements In all plots (randomly and selectively established) the staff from the NFI classified forest type (tree species composition) based on visual assessment of crow coverage of individual tree species (to Within the plots we measured all downed logs with maximum diameter larger than 10 cm and length larger than 60 cm. The measurements taken were: length (in dm) basal diameter (in mm) and mid diameter (in mm). The volume of the logs were calculated according to the formula volume = l*r2 , where l is the length of the log, and r is the mid diameter of the log. In the following text, the diameter or diameter classes always refer to the basal (maximum) diameter. For each log we identified the tree species and subjectively classified the decay into one of the following 5 classes (the remaining proportions of initial dry density are interpreted based on data from Næsset (1999): D1, recently dead. Bark normally attached to the wood. Hardly any fungus mycelium developed under patches of loose bark. 100–95% of the initial dry density. D2, weakly decayed. Loose bark, normally well developed mycelium between bark and wood. The rot extends less than 3 cm radially into the wood (as measured by pushing a knife into the wood). Approximately 95–75% of the initial dry density. D3, medium decayed. Rot extends more than 3 cm into the wood, but the log still has a hard core and it is supported by stones, humps, etc. on the forest floor. Approximately 75–50% of the initial dry density. D4, very decayed; rotten throughout the log. The log is formed by the contours of the forest floor and the cross-section often has an ellipsoid form. Approximately 50–25% of the initial dry density. D5, almost decomposed; the log is section-wise completely decomposed, and the log outline is strongly fragmented. The remains are often overgrown. Approximately 25–5% of the initial dry density. The total numbers of spruce and pine logs in the investigated sites are summarized in Table 1. Notice that we did not investigate all logs in sites with high dead wood abundances (see fungus sampling, further down). Thus, one cannot calculate the average abundance of logs in different site categories based on Table 1 and the area of the investigated plots. 3.4. Dead wood profile and forest history Prior to the data analysis, we summarized the volume of downed wood for each site in a dead wood profile (Stokland, 2001). This is a 2× 2 cross-table separating the downed logs in small (10–30 cm) or large (>30 cm) diameters, and in little to medium decayed (decay classes 1–3) or very decayed logs (decay classes 4–5). For each of the 4 cells in the profile, we divided the volume by the plot area in order to estimate the volume/ha. Subsequently, we classified the CWD profile into one of the following categories reflecting different forest history: Strong CWD continuity. Dead wood was abundantly present in all four cells (>3 m3 /ha in each cell, often very much more). Altogether 12 plots with a total area of 3.4 ha in spruce forests and 8 plots with a total area of 2.8 ha in pine forests. Weak CWD continuity. Dead wood was abundantly present in each of the two cells with little-medium decayed logs (>3 m3 /ha in each cell). The total volume of very decayed wood (both small and large dimensions) is 1–3 m3 /ha. Altogether 8 plots with a total area of 3.4 ha in spruce forests and 6 plots with a total area of 1.6 ha in pine forests. Managed forest, recent CWD increase. Very decayed wood virtually absent (total volume of very decayed wood <1 m3 /ha). Little to medium decayed wood was present with more than 1 m3 /ha, often J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 1710 Table 1 Number of logs inspected for fungi in the natural or near-natural forests, managed forests with recent increase in dead wood (managedRI ), managed forests with low dead wood abundance (managedLA ). D12, D3 and D45 indicate little decayed logs, medium decayed logs, and very decayed logs, respectively. Natural Pine 10–20 cm 20–30 cm >30 cm Sum Spruce 10-20 cm 20-30 cm >30 cm Sum ManagedRI ManagedLA D12 D3 D45 D12 D3 D45 D12 27 9 7 43 61 46 35 142 66 45 29 140 123 38 9 170 114 29 7 150 63 12 0 75 44 11 4 59 81 27 13 121 46 31 15 92 625 248 119 992 106 49 41 196 49 39 32 120 57 52 37 146 226 49 17 292 108 20 7 135 39 15 3 57 45 6 4 55 58 21 7 86 30 13 8 51 718 264 156 1138 very much more. Altogether 21 plots with a total area of 8.9 ha in spruce forests and 26 plots with a total area of 12.5 ha in pine forests. Managed forest, low CWD abundance. These plots had less than 1 m3 /ha of dead wood in all 4 cells. Altogether 19 plots with a total area of 11.8 ha in spruce forests and 24 plots with a total area of 16.1 ha in pine forests. In the following text we refer to the sites with strong and weak continuity as natural forests. Most of the plots with weak continuity (near-natural forests) showed clear signs of logging operations, either old selective logging in presently mature or over-mature forests, or relatively recent clear-cut logging in forests where much of the dead wood had originated before the clear-felling (as judged from their diameter and decay stage). The managed forests with recent CWD increase typically occurred in mature or over-mature stands where recently fallen trees in decay class D1 and D2 had not been removed. The managed stands with low CWD abundance occurred in all age classes from recent clear-cuts to over-mature stands. Here dead wood has probably been extracted during management operations until the present. No quantitative information was obtained from the forest matrix surrounding the sample plots. But the natural forests with strong continuity typically occurred in old-growth forest in nature reserves often several kilometers from nearest forest road, or they were surrounded by steep terrain inaccessible for mechanized forestry operations. The plots with weak continuity typically occurred many kilometers from the main road network and farms but they were often easily accessible from recent forest roads. Here the surrounding landscape was characterized by a mixture of (over) mature forests and new or recent clear-cuts. The managed forests typically occurred close to the main road network and farms. They were embedded in a landscape characterized by managed forests presumably with several hundred years of regular timber extraction. 3.5. Fungus sampling and species diversity In each plot a field team of biologists sampled fruit-bodies of wood-inhabiting fungi once during 20 August to 30 October in either of 1995, 1996 or 1997. We always sampled fungi on minimum 15 logs (except in 2 plots where we found less than 15 logs in 1.0 ha). In plots with many logs (30–150 logs/plot), we sub-sampled a stratified random selection of the logs (95–33%) so that the composition of tree species, decay classes and diameter classes in the sub-sample was similar to that of the plot. The species number per individual log was the number of identified species based on fruit-body occurrence. The actual number is higher because we probably overlooked some fruitbodies. The tendency of overlooking species probably increased D3 D45 Sum with increasing log size because we could easily turn over small logs whereas larger logs were more difficult to inspect along the underside where fruit-bodies typically occur. This means that the species richness per log is increasingly more conservative for larger log size. There is no reason to assume any difference in fruitbody detection on similar logs situated in natural or managed forests. The species richness per unit area was calculated in the following manner. For each site we produced a curve of cumulative species richness as a function of number of sampled logs (averaged over 10 replicates for each number of logs). Next, we calculated the number of logs per 0.1 ha and derived the number of species for this area from the cumulative species curve. 3.6. Definition of species groups The fungus species were classified according to five criteria. These classifications were based on the full data set from the 159 sites that included 1112 pine logs, 1462 spruce logs, 1512 hardwood logs, and 59 unidentified logs. Host preference. We used 80% as a threshold value to define host tree preference. A species is said to prefer pine, spruce or hardwood trees if more than 80% of the records were made on these hosts, respectively. Similarly, we classified a species as a coniferous species if more than 80% of the records were made on pine or spruce logs, but with no clear preference for either tree species. The remaining species were considered as host tree generalists. Fifteen species that occurred on the pine or spruce logs had a preference for wood from broad-leaved trees. These species are included in Table 2, but otherwise they were removed from the dataset prior to the analyses. Decay preference. We used the average decay frequency on logs of the preferred host tree(s) as the criterion to define decay preference. We classified the species as an early decay species if the average was smaller than 2.0. Similarly, we classified the species as a late decay species if the average decay was larger than 3.5. For the remaining species, we classified the species as a medium decay species if the average decay deviation was less than 0.75 (i.e. more than 50% of the records were within an interval of 1.5 on the decay scale). The species with a wider dispersion were classified as decay generalists. Dimension preference. We used the frequency in five diameter classes from 10 to 20 cm to more than 50 cm. These frequencies were based on logs of the preferred host tree(s). A species was classified to prefer small to intermediate dimensions if the average frequency in the classes below 30 cm was more than 3 times higher than the average in the classes above 30 cm. Vice versa, a species was classified to prefer large dimensions if the average fre- J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 1711 Table 2 The number of species found on pine logs (P) and spruce logs (S). See Section 3 for definitions of different fungus groups. Host tree preference Pine Spruce Coniferous Broad-leaved Generalist Sum Decay preference P S 53 7 70 9 69 208 10 54 69 9 90 232 Diameter preference Frequency P S P S Early Medium Late Indifferent 15 108 33 52 14 119 39 60 Small–medium Large Indifferent 53 38 117 56 54 122 Rare Occasional Common Sum 208 232 Sum 208 232 Sum quency above 30 cm was more than 3 times higher than below 30 cm. The remaining species were classified as indifferent with respect to dimension preference. General frequency. We used the records on the 4145 logs as a basis for a pragmatic classification of species frequency. A species was classified as rare if it was recorded on 10 or fewer logs, occasional if it was found on 11–30 logs and common if it was found on more than 30 logs. Fungus group. Two fungal groups were investigated in this study – polypores and corticoids. Both groups are paraphyletic and represent a traditional morphological classification. The polypores are ecologically homogenous from a functional point of view and comprise principal saprophytes. The polypores are generally more long-lived compared to corticoids and some of them have fruitbodies lasting for several years, even more than 30 years (Niemelä, 2005). Most (94%) of the corticoid species are wood decomposers, but a few are functionally distinct by being ectomycorrhiza species that position their fruit-bodies on the surface of dead logs. The corticoids are characterized by short-lived fruit-bodies and they generally differ from the polypores by having a more ephemeral occurrence. 3.7. Statistical analysis and species curves The statistical analyses of species number on individual logs were carried out with the R package (version 2.12.1). In these analyses we considered the sample plots to be independent observation units but the individual logs within each plot to be spatially correlated. Because of this hierarchical nature of the data, and the advantages of using mixed effects modelling on unbalanced repeated data, we used a linear mixed effects (LME) model to account for random effects at the sample sites. All models were fitted using maximum likelihood. In order to quantify responses of different fungal groups, we established species curves in the following manner. First, we sorted all logs in three site groups based on the CWD profile: (a) the natural forest sites (strong and weak continuity), (b) the managed forests with recent CWD increase and c) the managed forests with low abundance. Next, we drew 100 random samples of 1, 10, 20 . . . up to 200 logs from each site group, and for each sample we counted the number of species in different fungus groups. Finally, we calculated the average number of species for each fungus group across the 100 replicated samples and present these averages as species curves. The 2.5 and 97.5 percentiles of these replicated averages were used as a 95% confidence interval. The qualitative composition of logs differed somewhat between the three site groups (Table 1). We wanted to compare similar logs from each site group when assessing species responses across three site groups. For this purpose, we established replicated samples of 50 logs in the same manner as for the species curves, but we now sorted the logs in standardized decay and diameter classes within each site groups. For each class of logs, we calculated the average species number for each fungus group and presented these results in a table format. P S 81 51 76 98 55 79 208 232 4. Results Altogether, the data set included 290 species of which 56 were polypores and 234 were corticoids (Appendix A). On the 992 pine logs we found 208 species (39 polypores, 169 corticoids). The corresponding numbers on the 1138 spruce logs were 232 species (40 polypores, 192 corticoids) (Table 2). 4.1. Species richness per unit area In the pine forest we found a highly significant reduction in species richness from 43.8 species per 0.1 ha in the natural forests to 24.9 species in the managedRI forests and 10.8 species in the managedLA forests (ANOVA, p < 0.0001). Similarly, in the spruce forests, we found a highly reduced species richness from 63.4 species per 0.1 ha in the natural forests to 29.1 species in the managedRI forests and 11.0 species in the managedLA forests (ANOVA, p < 0.0001). The reduction in species richness per area unit in managed forests corresponded closely to a reduction in average number of logs per unit area: from 1886 logs/ha in unmanaged pine forests to 50.1 logs/ha in managed pine forests, and from 2049 logs/ha in unmanaged spruce forests to 68.7 logs/ha in managed spruce forests. 4.2. Species richness on individual logs The reduced species richness per area in managed forests is quite expected due to the reduced amount of substrate. In order to investigate additional effects of forest history on the species diversity of fungi, we grouped the logs with respect to tree species, decay classes and dimension classes. Then, we compared the species richness on logs with similar properties but under different management regimes. The species richness per log exhibited several statistically significant patterns. The species richness increased from the little decayed logs to the medium decayed logs, and dropped again on very decayed logs (Table 3). This effect of decay was highly significant on both spruce and pine logs (Table 4). Furthermore, the species number per log increased with increasing diameter class (Table 3), and the effect was highly significant on both spruce and pine logs. There was a highly significant effect of the CWD profile (i.e. forest history) on the spruce logs, but this effect was absent on the pine logs (Table 4). This effect caused a reduced species number per log in managed forest compared to the logs in natural forests (Table 3, the two rightmost columns). Furthermore, we found a significant interaction effect between the CWD profile and diameter class on the spruce logs (Table 4). This interaction effect corresponded to a stronger reduction in species richness with increasing diameter class in the managed forests compared to the natural forests (Table 3, the two right columns). J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 1712 Table 3 Average number of species (polypores and corticoids pooled) per log in localities with different forest history: natural forests, managed forests with recent increase in dead wood (managedRI ), managed forests with low dead wood abundance (managedLA ). D12, D3 and D45 indicate little decayed logs, medium decayed logs, and very decayed logs, respectively. The two right columns show the species number on logs in ManagedRI sites and ManagedLA sites as percentagesa of the species number on corresponding logs in the natural forests. The number of logs per category is shown in Table 1. Natural Pine 10–20 cm 20–30 cm >30 cm Spruce 10–20 cm 20–30 cm >30 cm a ManagedRI ManagedLA MRI MLA D12 D3 D45 D12 D3 D45 D12 D3 D45 3.4 5.4 5.1 3.9 5.0 5.3 3.1 4.0 5.3 3.1 4.6 5.1 4.3 5.2 8.9 4.1 4.0 – 3.3 5.3 5.2 3.7 4.3 4.4 3.4 4.4 5.2 107% 94% 128% 99% 98% 92% 3.0 3.9 5.9 5.1 7.9 9.1 4.5 6.3 7.9 2.8 3.9 4.6 4.2 5.2 5.6 4.2 5.1 5.3 3.4 3.7 1.8 4.2 4.4 4.1 4.1 5.3 4.1 90% 89% 72% 94% 71% 45% The percentage is calculated as the weighted average of 3 percentages from comparisons of logs in similar decay classes, i.e. D12, D3 and D45. Table 4 Linear mixed effect (LME) models of species number per log, comparing the groups of logs in Table 3. CWD profile denotes the three management treatments (natural, managedRI , managedLA ). df Pine logs Factor Decay class Diameter class CWD profile CWD: diameter interaction CWD: decay interaction 2 2 2 4 4 Spruce logs F-value p-value F-value p-value 10.9 37.6 1.8 1.6 1.4 0.0001 0.0001 ns ns ns 59.2 49.9 28.9 7.0 6.8 0.0001 0.0001 0.0001 0.0001 0.0001 4.3. Cumulative species richness The average reduction (sometimes increase) of a few species per individual logs in managed compared to natural forests added up to remarkable differences when we pooled several logs from sites with different forest history. Furthermore, we found clear differences between polypores and corticoid fungi. In the pine forests there was no systematic difference in overall species richness when comparing 10–200 logs from natural forests and similar number of logs from managed forests (Fig. 3). A closer examination of rare versus common species neither revealed any strong difference. There was perhaps a slight difference in that occasional species became somewhat more frequent in managed forests but the confidence bands of the species curves overlapped substantially (Fig. 4). In the spruce forests there was a clear reduction in overall species richness when comparing an increasing number of logs from natural forests and similar number of logs from managed forests. The reduction was about 25%, corresponding to a loss of 38 species when comparing 200 logs (Fig. 3) and 45 species when comparing 450 logs (not shown in Fig. 3). There was no systematic difference in overall species richness when comparing similar number of logs from the two groups of managed forests (Fig. 3). When the species curves were separated in curves for common, intermediate and rare species, it turned out that the main difference between natural and managed spruce forests was caused by the rare species. When comparing 200 logs from natural and man- Pine logs Spruce logs 160 160 Natural ManagedRI 140 140 Number of species ManagedLA 120 120 100 100 80 80 60 60 40 40 20 20 0 0 0 50 100 150 Number of logs 200 250 0 50 100 150 200 250 Number of logs Fig. 3. Average cumulative number of fungal species with increasing number of logs from natural forests, managed forests with recent increase in dead wood (managedRI ) and managed forests with low abundance of dead wood (managedLA ) in pine forests (left) and spruce forests (right). The thin and dotted lines represent 95% confidence interval for the average number in natural forests and managed forests, respectively. J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 Pine logs 80 Spruce logs 80 Common species 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 0 50 100 150 200 Common species 0 150 200 100 150 200 100 150 200 100 Occasional species Occasional species Number of species 50 40 40 30 30 20 20 10 10 0 1713 0 0 50 100 150 200 50 0 50 50 Rare species Rare species 40 40 30 30 20 20 10 10 0 0 0 50 100 150 200 Number of logs 0 50 Number of logs Fig. 4. Average cumulative number of species from Fig. 3 subdivided into common, occasional and rare species. The symbology is identical to that of Fig. 3. aged forests, there was a net reduction of 5 common species, 10 intermediate species and 23 rare species (Fig. 4). 4.4. Responses of fungi in spruce forests Decay preferences. Species with different decay preferences responded quite differently to forest management. The number of species that prefer early decay stages showed very small differences between logs in natural and managed forests (Table 5). The number of species that prefers medium decay logs, on the other hand, showed a clear decline in managed forests (Table 5). This reduction was evident already on little decayed logs where such species start to appear, and the reduction increased to ca 30% on logs with optimal decay status, while it was smaller on strongly decayed logs (Table 5). Also the late decay species showed a reduced species richness in managed forests and they had about 35% species loss on strongly decayed logs (Table 5). The species without clear decay preferences showed moderately reduced species richness in managed forests and their species numbers were 10–25% lower on logs in different decay phases (Table 5). Dimension preferences. The species that preferred small to medium-sized logs occurred equally frequent in natural and managed forests (Table 6). Some of the species with preference for large-dimension logs occurred on logs smaller than 20 cm and more frequently so in natural than managed forests. A larger proportion of these species occurred on medium-sized (20–30 cm diameter) logs in natural forests but not in managed forests (Table 6). A conspicuous loss of large diameter species was evident when comparing logs larger than 30 cm in diameter. In the natural forest the number of large-diameter species was almost three times higher on such large logs, corresponding to a reduction of 65% (Table 6). Also among the species without strong preference for diameter classes, there was a 7–20% reduction in species numbers in managed compared to natural forests (Table 6). 1714 J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 Table 5 Average number of fungal species in 50 logs, randomly selected with 100 replicates from 6 groups of logs: three decay classes, each from natural forests and managed forests (managedRI and managedLA pooled). The two numbers in parenthesis represent 95% confidence interval for the average. Spruce logs Sum, all species Early decay species Mid decay species Late decay species Indifferent decay species Small-medium preference Large preference Indifferent Rare Occasional Common Polypores Corticoids Pine Spruce Coniferous Generalist Pine logs Sum, all species Early decay species Mid decay species Late decay species Indifferent decay species Small-medium preference Large preference Indifferent Rare Occasional Common Polypores Corticoids Pine Spruce Coniferous Generalist a Little decayed logs (D1–D2) Medium decayed logs (D3) Very decayed logs (D4–D5) Natural Managed Natural Managed Natural Managed 58.9 (50, 68) 6.2 (4, 8) 30.7 (24, 37) 0.4 (0, 2) 21.6 (16, 27) 1.7 (0, 3) 13.5 (9, 18) 43.7 (36, 51) 3.9 (0, 7) 10.8 (6, 15) 44.2 (39, 51) 12.7 (10, 15) 46.2 (37, 54) 0.2 (0, 1) 10.6 (7, 13) 23.1 (18, 29) 25.0 (20, 31) 49.4 (39, 57) 4.9 (3, 6) 23.4 (17, 30) 0.1 (0, 1) 21.1 (15, 27) 4.2 (1, 8) 5.4 (2, 10) 39.9 (32, 47) 2.8 (0, 6) 5.8 (2, 10) 40.8 (31, 49) 10.2 (6, 13) 39.3 (31, 46) 0.4 (0, 1) 7.1 (4, 11) 18.6 (12, 24) 23.3 (17, 29) 93.6 (83, 106) 4.2 (2, 6) 48.6 (42, 56) 9.6 (5, 13) 31.3 (27, 35) 7.8 (3, 12) 18.8 (13, 23) 67.0 (59, 75) 16.5 (11, 23) 18.5 (13, 21) 59.2 (54, 64) 20.7 (15, 25) 72.9 (65, 81) 3.8 (1, 7) 19.3 (15, 24) 36.3 (30, 41) 34.3 (29, 39) 66.8 (54, 76) 3.7 (2, 6) 34.3 (25, 41) 3.9 (1, 7) 24.9 (20, 30) 6.6 (2, 10) 9.1 (5, 14) 51.1 (43, 57) 6.0 (3, 11) 10.1 (5, 14) 49.9 (43, 55) 13.6 (10, 17) 53.2 (42, 62) 1.9 (0, 4) 9.8 (7, 13) 27.0 (19, 32) 28.1 (21, 35) 86.3 (69, 98) 0.3 (0, 1) 32.9 (23, 40) 19.0 (14, 24) 34.0 (29, 40) 6.8 (4, 11) 20.7 (13, 28) 58.8 (50, 64) 17.1 (8, 23) 16.5 (10, 22) 52.7 (44, 59) 10.5 (6, 14) 75.8 (61, 85) 3.2 (0, 6) 15.8 (10, 20) 32.4 (26, 38) 34.9 (23, 42) 67.4 (57, 75) 1.3 (0, 2) 26.4 (22, 32) 12.0 (8, 15) 27.7 (24, 31) 6.4 (2, 10) 7.6 (5, 10) 53.5 (47, 59) 7.7 (3, 12) 11.5 (8, 16) 48.2 (44, 53) 9.7 (7, 12) 57.8 (50, 66) 2.4 (1, 4) 9.2 (6, 12) 29.5 (24, 35) 26.4 (21, 31) 64.0a (–, –) 7.5a (–, –) 32.0a (–, –) 1.1a (–, –) 25.5a (–, –) 10.6a (–, –) 6.2a (–, –) 48.8a (–, –) 10.2a (–, –) 10.4a (–, –) 44.6a (–, –) 14.4a (–, –) 52.6a (–, –) 15.3a (–, –) 1.0a (–, –) 29.4a (–, –) 20.4a (–, –) 57.8 (49, 67) 7.5 (5, 10) 26.2 (18, 33) 0.9 (0, 3) 23.2 (18, 27) 7.6 (3, 12) 4.1 (0, 7) 46.1 (38, 52) 7.2 (3, 12) 10.1 (5, 14) 40.5 (32, 47) 12.2 (7, 17) 45.6 (38, 53) 9.2 (4, 13) 1.3 (0, 3) 23.8 (17, 29) 23.5 (18, 28) 71.8 (63, 81) 0.4 (0, 1) 32.5 (27, 39) 12.8 (7, 16) 26.1 (22, 30) 7.1 (2, 10) 11.6 (7, 15) 53.1 (47, 60) 12.2 (7, 18) 13.7 (10, 18) 46.0 (41, 50) 11.1 (7, 14) 60.7 (53, 70) 19.2 (15, 23) 0.4 (0, 1) 31.2 (26, 37) 21.0 (16, 25) 73.5 (62, 86) 2.1 (0, 4) 34.5 (27, 42) 9.2 (5, 13) 27.7 (23, 34) 11.0 (6, 15) 7.9 (4, 12) 54.6 (47, 62) 9.6 (5, 16) 16.2 (11, 22) 47.7 (42, 54) 12.8 (8, 18) 60.7 (50, 71) 19.2 (13, 25) 0.7 (0, 2) 29.3 (22, 35) 24.2 (20, 32) 54.6 (46, 65) 0.0 (0, 0) 19.9 (13, 28) 13.1 (8, 16) 21.7 (18, 25) 5.1 (2, 8) 9.5 (6, 13) 40.1 (31, 47) 6.6 (1, 10) 11.4 (8, 15) 36.7 (30, 43) 5.1 (2, 9) 49.6 (41, 58) 12.5 (9, 16) 0.9 (0, 2) 25.0 (18, 32) 16.3 (13, 20) 70.0 (58, 80) 0.5 (0, 1) 28.3 (19, 35) 12.8 (8, 17) 28.4 (23, 32) 10.3 (5, 14) 9.5 (5, 13) 50.2 (42, 58) 9.5 (6, 14) 15.3 (8, 20) 45.2 (38, 51) 10.5 (5, 15) 59.5 (50, 67) 15.1 (11, 20) 1.0 (0, 2) 31.2 (25, 37) 22.7 (18, 27) Extrapolated from 40 logs. Species frequency. The loss of rare species in managed forests was distributed quite differently across logs with different attributes. The strongest reduction was related to log size as the loss increased both in absolute and relative terms from small logs with ca 40% loss to large logs with 100% loss (Table 6). The trend was the same for occasional and common species, but for these species, the reduction was lower (Table 6). When relating the loss of rare species to decay phases, the reduction was strongest on logs in the mid decay phase that had ca 65% fewer species in managed forests compared to similar logs in natural forests (Table 5). Also on the strongly decayed logs the reduction was marked, whereas the loss was insignificant on little decayed logs where very few rare species occurred (Table 5). The loss of occasional and common species followed the same trend as the rare species but with smaller differences (Table 5). Fungus groups. Both polypores and corticoids showed a clear loss of species when comparing logs in natural and managed forests. The reduction was strongest for corticoids both in relative and absolute terms. When relating the reduction to diameter classes, the loss of corticoids increased from 13% to 40% from small to large logs, while the corresponding loss of polypores was 11–12% (Table 6). When relating the loss to decay phases, the loss was highest on medium decayed logs for both groups (Table 5). The corticoids also showed a 25% reduction on strongly decayed logs, whereas the polypores showed very small differences in this decay phase (Table 5). Host preference groups. The spruce specialists accounted for most of the differences between natural and managed spruce forests (Tables 5 and 6). Also the conifer species and host tree general- ists showed a difference whereas a few pine species that occurred on the spruce logs did not show any differences. 4.5. Responses of fungi in pine forests In general, the species on pine logs showed much smaller differences between natural and managed forests and in most cases the average number of species on logs in managed forests fell within the 95% confidence interval of the corresponding average in natural forests, and vice versa (Tables 5 and 6). Furthermore, the species that were pine specialists seemed to differ very little between natural and managed forests (Tables 5 and 6). 5. Discussion We found a strong reduction in local species richness of polypores and corticoids per unit area when comparing natural and managed pine- and spruce forests. This was mainly an effect of reduced substrate abundance. We also found a significant reduction in species richness per substrate units when comparing individual logs with similar qualities situated in natural and managed spruce forests, but no such effect in pine forests. This difference translated to a substantial cumulative effect when we considered a large number of logs on a regional scale. The conservation ecology of polypores has recently been reviewed by Junninen and Komonen (2010). Our findings partly confirm their review of previous studies (e.g. that the local species diversity in managed forests is lower than in natural forests and that rare species are largely missing J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 1715 Table 6 Average number of fungal species in 50 logs, randomly selected with 100 replicates from 6 groups of logs: three diameter classes, each from natural forests and managed forests (managedRI and managedLA pooled). The two numbers in parenthesis represent 95% confidence interval for the average. 10–20 cm logs Spruce logs Sum, all species Early decay species Mid decay species Late decay species Indifferent decay species Small-medium preference Large preference Indifferent Rare Occasional Common Polypores Corticoids Pine Spruce Coniferous Generalist Pine logs Sum, all species Early decay species Mid decay species Late decay species Indifferent decay species Small-medium preference Large preference Indifferent Rare Occasional Common Polypores Corticoids Pine Spruce Coniferous Generalist a 20–30 cm logs >30 cm logs Natural Managed Natural Managed Natural Manageda 67.5 (57, 76) 3.8 (2, 5) 29.4 (22, 36) 7.0 (3, 11) 27.4 (22, 31) 5.6 (1, 10) 10.3 (7, 14) 51.5 (45, 58) 7.3 (3, 13) 10.2 (4, 15) 49.9 (42, 55) 11.6 (8, 16) 55.9 (48, 64) 1.2 (0, 3) 8.5 (5, 12) 29.0 (23, 34) 28.8 (21, 34) 59.0 (47, 70) 4.3 (3, 6) 26.8 (20, 33) 2.7 (0, 6) 25.2 (20, 31) 4.3 (1, 8) 6.8 (2, 11) 47.9 (40, 56) 4.1 (1, 8) 7.7 (3, 12) 47.1 (39, 53) 10.3 (7, 14) 48.6 (39, 58) 1.3 (0, 4) 7.7 (4, 11) 23.8 (18, 28) 26.2 (20, 33) 85.7 (76, 95) 4.8 (3, 6) 35.5 (30, 41) 13.4 (8, 18) 32.1 (27, 37) 6.5 (4, 10) 13.4 (10, 17) 65.8 (58, 75) 11.2 (6, 15) 16.0 (10, 21) 58.5 (52, 64) 14.7 (10, 19) 71.0 (61, 81) 2.9 (0, 6) 14.5 (9, 18) 33.2 (27, 39) 35.1 (30, 41) 66.4 (53, 75) 4.9 (4, 5) 31.3 (24, 38) 7.2 (3, 11) 23.0 (19, 27) 7.4 (2, 12) 6.4 (4, 8) 52.6 (43, 58) 6.6 (3, 11) 11.2 (6, 16) 48.6 (43, 53) 12.9 (9, 16) 53.5 (43, 62) 0.8 (0, 2) 11.1 (7, 13) 27.7 (21, 33) 26.8 (21, 31) 98.7 (84, 108) 6.3 (4, 8) 47.3 (38, 54) 11.8 (6, 16) 33.4 (28, 38) 2.3 (0, 4) 32.2 (25, 39) 64.2 (57, 71) 18.5 (12, 24) 21.0 (15, 27) 59.2 (55, 64) 18.6 (15, 22) 80.1 (68, 89) 3.5 (1, 6) 22.2 (18, 26) 37.2 (28, 42) 35.8 (30, 41) 65.1 (–, –) 4.0 (–, –) 32.2 (–, –) 5.0 (–, –) 23.8 (–, –) 3.0 (–, –) 11.5 (–, –) 50.5 (–, –) 0.0 (–, –) 13.6 (–, –) 51.5 (–, –) 16.5 (–, –) 48.5 (–, –) 2.0 (–, –) 9.2 (–, –) 29.1 (–, –) 24.7 (–, –) 63.5 (52, 73) 2.9 (1, 4) 27.6 (17, 34) 9.1 (4, 13) 23.9 (18, 28) 6.7 8.1 (3, 11) 48.7 (40, 56) 6.4 (1, 10) 12.9 (8, 16) 44.2 (37, 50) 9.3 (5, 13) 54.2 (46, 62) 13.2 (8, 18) 1.1 (0, 3) 30.3 (21, 35) 18.9 (14, 23) 66.8 (52, 75) 5.3 (2, 8) 29.5 (20, 36) 6.2 (2, 11) 25.8 (21, 30) 10.4 (5, 15) 5.5 (2, 8) 51.0 (39, 58) 8.1 (3, 13) 13.6 (8, 19) 45.1 (34, 50) 11.3 (6, 16) 55.5 (45, 62) 14.5 (10, 20) 0.6 (0, 2) 28.7 (18, 34) 23.1 (17, 28) 76.3 (68, 82) 2.2 (0, 3) 30.2 (25, 34) 15.1 (11, 19) 28.8 (25, 32) 10.7 (6, 14) 10.0 (7, 13) 55.5 (51, 60) 12.7 (9, 16) 13.1 (10, 16) 50.5 (47, 55) 11.6 (8, 14) 64.7 (54, 70) 20.0 (14, 23) 1.0 (0, 2) 33.3 (28, 37) 22.0 (19, 26) 80.4 (71, 90) 6.0 (3, 7) 35.8 (30, 42) 10.0 (4, 14) 28.7 (22, 33) 11.3 (7, 15) 7.9 (3, 12) 61.2 (51, 67) 10.6 (6, 15) 17.8 (10, 24) 52.0 (45, 57) 15.9 (10, 21) 64.4 (57, 73) 18.0 (12, 24) 1.7 (0, 3) 34.6 (29, 40) 26.2 (22, 31) 75.2 (64, 83) 5.1 (2, 6) 32.8 (26, 38) 11.6 (9, 13) 25.7 (23, 28) 2.5 (0, 4) 14.1 (10, 16) 58.6 (46, 64) 12.2 (6, 16) 14.2 (10, 17) 48.8 (43, 52) 14.3 (10, 17) 60.9 (50, 66) 19.1 (14, 22) 0.0 (0, 0) 34.8 (28, 38) 21.2 (16, 24) 89.5 (–, –) 7.3 (–, –) 37.9 (–, –) 13.5 (–, –) 31.5 (–, –) 1.9 (–, –) 20.7 (–, –) 67.0 (–, –) 10.3 (–, –) 25.4 (–, –) 53.6 (–, –) 16.5 (–, –) 73.4 (–, –) 21.7 (–, –) 2.9 (–, –) 38.9 (–, –) 26.7 (–, –) Extrapolated from 45 logs. from managed forests) and partly add significant new knowledge about fungal responses to forest management (especially that the response is very different in spruce and pine forests, and one should not generalize forest management effects across these forest types). Furthermore, we demonstrate that corticoid fungi are even more sensitive than polypores concerning their response to forest management in spruce forests. 5.1. Trivial and non-trivial reduction in species richness The reduction in species diversity we have demonstrated in this study relates to different aspects of habitat loss. According to Hanski (1999), habitat loss comprises three major components: net habitat loss, increasing fragmentation of remaining habitat and deterioration of habitat quality. It is obvious that when the amount of dead wood is reduced by more than 90% in managed forests compared to natural forests there must be a corresponding loss in local species richness of wood-inhabiting species. This loss takes the form of reduced species richness per unit area and it has been demonstrated repeatedly in spruce and pine forests in Fennoscandia (Bader et al., 1995; Lindblad, 1998; Sippola and Renvall, 1999; Sippola et al., 2001; Penttilä et al., 2004; Junninen et al., 2006). The reduction in species richness per unit area is, however, a trivial effect if all species maintain their frequency of occurrence on the remaining suitable logs at a landscape or regional level. In other words, the species richness drops locally because there are fewer logs per unit area, but the species richness is maintained in managed forests on a landscape or regional level if all dead wood qualities are represented and all species utilizes the remaining suitable logs equally frequent as in natural forests. In this study we found an additional effect, namely reduced species richness when comparing logs of the same quality (tree species, dimension class and decay stage) situated in natural and managed forests. Furthermore, the loss increased with increasing intensity of forest management (Table 3). This loss of species per substrate unit corresponds to the fragmentation effect, i.e. that an increasing proportion of remaining habitat patches becomes unoccupied when they are spaced increasingly more apart. The design of our study is not suitable, however, to sort out at which spatial scale the fragmentation effect is operating. When considering pools of many logs on a regional scale, it turned out that a rather large number of species were affected (as measured by the difference between curves in Fig. 3). The species reduction in managed spruce forests was about 25%, or a net loss of ca. 40 species. This is clearly a conservative measure since the pool of sites and logs from natural forests was smaller than the corresponding pools from managed forests. On the other hand we also observed that some species increased in managed spruce forests (e.g. Heterobasidion annosum and Gloeophyllum sepiarium). 5.2. Spruce versus pine forests We found very strong effects of forest management in spruce forests, but not in pine forests. A similar trend was found by Penttilä et al. (2006). They assessed the fragmentation effect on sensitive spruce species by contrasting them with more common habitat 1716 J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 generalists that also utilize the matrix of managed forests. But they did not specifically discuss the difference between spruce- and pine-associated species. We suggest that the different responses in spruce and pine forests are caused by different species composition in these forest types and that these species groups have different dispersal abilities. More specifically we suggest that fungi occurring in pine forests have evolved under a fire dynamics regime whereas spruce-associated species to a large extent have escaped this selection pressure. Today, forest fires are almost totally suppressed in Fennoscandian forests, but from historical records in the region we know that natural fire return intervals differ greatly between pine and spruce forests. Pine forests have a fire return interval of 20–100 years (Zackrisson, 1977; Engelmark, 1984; Niklasson and Drakenberg, 2001). The fire return interval in spruce forests is much longer and can vary from a few hundred to several hundred years (Ohlson et al., 1997; Ohlson and Tryterud, 1999) or fires may even be totally absent (Tryterud, 2003). Pine- and spruce forests also differ in their productivity and input rates of dead wood. Pine forests typically occur on shallower and drier soils and are therefore less productive with a lower standing volume and input rate of dead wood per unit area. Spruce forests typically occur on mesic-moist sites and deeper soils. They are generally more productive and standing volume, input rates of dead wood and dead wood abundances are higher compared to those of pine-dominated forests. Thus, from nature’s side the pine forests are characterized by a relatively low average input rate of dead wood that fluctuates greatly with time, whereas spruce forests are characterized by a higher average input rate of dead wood that varies little for periods of several hundred years. In other words, the average minimum distance between similar spruce logs is shorter and rather constant with time compared to the minimum distance between pine logs. This creates very different selection pressures for dispersal ability among wood-inhabiting organisms in these forest types. Unfortunately, we have little quantitative information about differences in dispersal range between spruce- and pine-associated fungi. Only a few spruce-associated species have been investigated concerning their wind-dispersal ability (Nordén and Larsson, 2000; Edman et al., 2004b) but no pine-associated species. It is also possible that wood-inhabiting insects can be important dispersal agents. Many wood-inhabiting insects are hairy and a large number of species are attracted to sporulating fruit-bodies where they feed on the hymenium or are predators on other insects (Hågvar, 1999). If there was any overall effect in pine forests, it was rather so that the species richness on a standardized amount of substrate increased in managed forests (Fig. 4, occasional species). This corresponds to the results of Junninen et al. (2006) who found that both fire and logging increased the local species richness of polypores and corticoid fungi immediately after the disturbance event. There is a potential source of error in our study as we had few representations of truly natural pine forest. It might be that sensitive species confined to well-developed natural pine forests have not been captured by this study, or that they only occur as occasionalrare species while they are more common in pine forests driven by natural fire dynamics. Antrodia crassa and A. albobrunnea are examples of such species probably being more frequent in natural, fire-dominated forests. in natural forests (we typically observed 4–6 m3 /ha in managed spruce forests compared to 70–80 m3 /ha in natural spruce forests). These seemingly robust species are characterized by being host generalists or pine-associated species (but sometimes occurring on spruce logs), common species, species confined to little decayed logs, and species with a preference for small-medium sized logs. It should be mentioned that even some of the common spruce species that still occur scattered in managed forests actually can be quite sensitive to forest management. In a detailed analysis of a particular species in this dataset, Stokland and Kauserud (2004) showed that Phellinus nigrolimitatus has a strongly reduced frequency on suitable logs in managed forests compared to their frequency on similar logs in natural forests. 5.3.1. Sensitive species in spruce forests A closer inspection of species attributes revealed that the sensitive species in spruce forests shared some characteristics. There was a higher reduction of spruce specialists (in contrast to host tree generalists) when comparing logs in natural and managed forests. Furthermore, these species preferred large diameter logs. An explanation for this is that there is a stronger reduction in this diameter fraction in managed forests compared to smaller logs. Furthermore, the reduction of this diameter fraction has lasted for a longer time, cfr. the dimension logging during the 1600s–1800s that predominantly extracted trees larger than 30 cm in diameter. Examples of such sensitive spruce-associated species are Antrodiella citrinella, Phlebia centrifuga, P. subulata, several Paullicorticium species (especially P. allantosporum), Tubulicrinis chaetoporus and T. confusus. It is well documented that many spruce-associated polypore species are sensitive to forest management (Sippola et al., 2001; Penttilä et al., 2004; Stokland and Kauserud, 2004; Penttilä et al., 2006) in Fennoscandia. A few easily identified corticoids (e.g. Phlebia centrifuga, Cystostereum murraii) are often included in polypore inventories, which have revealed that these species are sensitive to management. But hardly any study has documented the response to forest management for a wide range of corticoid fungi (but see Junninen et al., 2006). In this study we have investigated more than 200 species of corticoids and demonstrated that these wood-inhabiting fungi are even more sensitive to forest management than the polypores are. Both in terms of the proportion of species being negatively influenced and the absolute number of species being lost, the corticoids appeared more sensitive than the polypores (Tables 5 and 6). 5.3. Robust and sensitive species 5.3.2. Are pine species unaffected? We found rather small differences in overall species richness between natural and managed pine forests. But there was a pattern suggesting that some species became more frequent in managed forests, e.g. species preferring early to medium decay stages without any preference for large dimensions, like Trichaptum fuscoviolaceum, Phlebiopsis gigantea and Dacryobolus karstenii. On the other hand, some pine species had lower frequency on suitable substrates in managed forests compared to similar substrates in natural forests: e.g. Tubulicrinis hirtellus, Odonticium romellii, Physodontia lundellii and Antrodia albobrunnea. All these species are confined to large diameter logs and medium or late decay stages. There was also several rare species that were only found in natural or near-natural pine forests. On the other hand there were equally many rare species that were only found in managed pine forests. We have documented that a minimum 25% of spruce species are “lost” in the managed forests compared to the natural forests. The flip side of this result is that the majority of the fungal species occur regularly on the remaining dead wood in the managed forests even when the abundance of dead wood is less than 10% of that found 5.3.3. Species adaptations The substrate preferences of wood-inhabiting fungi has to a small extent been used to explain why some species are vulnerable to forest management whereas others are less affected (but see Junninen et al., 2006). Instead, it is common to demonstrate J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 that some species are more sensitive than others to logging and that this corresponds with their red-list status (e.g. Stokland, 2001; Penttilä et al., 2004). Although it is important to document that redlisted species actually are sensitive to forest management, we do not learn from this why some species are sensitive while others are not. In this study, we disregard the red-list status of the species and instead interpret their occurrences in light of their ecological traits. There are two dynamic aspects that are especially important in this context: the dynamic in decay development of individual logs and the stand and landscape dynamics in dead wood input under different disturbance regimes as discussed above. When a conifer tree dies, it goes rapidly through the initial decay stages, typically 1–3 years for decay stage D1 and 5–20 years for D2 in boreal forests (Næsset, 1999), while medium (D3) and late decay stages (D4–D5) probably endures 20–30 years and more than 50 years, respectively. Both among polypore and corticoid fungi there is a rapid turnover in species composition from recently dead (decay stages D1 and partly D2) to little-medium decayed wood (D2–D3). The first arriving species are ruderal or r-strategy species with poor competitive ability and short-lived mycelia and fruit-bodies. Later arriving species are more K-strategy species with stronger competitive ability and long-lived fruit-bodies. These differences in life history strategies are best documented for temperate wood-decaying fungi associated with broad-leaved trees (Rayner and Boddy, 1988; Boddy and Heilmann-Clausen, 2008), but we can see the same pattern for closely related species confined to coniferous trees. Furthermore, it is well documented that conifer-associated polypores are increasingly more competitive from early to late decay stages (Holmer et al., 1997; Holmer and Stenlid, 1997). The specific dispersal ability among these species is not known, but judged from the duration of different decay stages (and thereby average distance between suitable logs), it seems logical that early colonizers experience a stronger selection pressure for dispersal. This corresponds well with their rapid production of fruit-bodies at the cost of competitive ability. Thus, it is likely that species confined to early decay species are better dispersers and this might explain why they are not so sensitive to management. In summary, it seems that pine-associated species are more disturbance-selected and adapted to utilize a low-abundant and irregular occurrence of different dead wood qualities. Also spruce- 1717 associated species that are confined to early decay stages might be adapted to a similar disturbance regime (although not so irregular dynamic as fire-dominated pine forests). These species therefore seem to be robust with respect to the disturbance regime imposed by forest management. Also substrate generalists seem to be robust with respect to forest management because they can utilize most of the dead wood that is present in managed forests. The species most prone to forest management are spruce specialists that are confined to medium and very decayed logs, and especially those that also are confined to large-dimension logs. These species are adapted to a forest dynamic regime where their substrate is continuously present within short dispersal distances. But in managed forests their substrate occurs with a much lower abundance and in pulses (resulting from natural mortality during the short time windows when the forest approach logging maturity), or even worse that their substrate is virtually absent (in the case of species confined to dimensions developing well after logging maturity). Acknowledgements We want to thank the persons in the field team that contributed with great working effort in quantifying dead wood and fungus sampling: Heidi Andersen, Arne Heggland, Marianne Iversen, Håvard Kauserud and Gunnar Kristiansen. We also want to thank the staff from the National Forest Inventory for accurate work in measuring stand characteristics in the plots. Maria Nuñez and Leif Ryvarden are warmly thanked for having identified most of the polypore specimens. Finally, we want to thank two anonymous referees for valuable comments on an earlier version of this manuscript and Clara Antón Fernández for help with statistical analyses. The study was funded by the Norwegian Research Council, grant no. 107887. Appendix A. List of species with the classifications used in this study (see Section 3.6). The numbers in the right part represent number of logs the species was recorded on in different forest types and forest history. Taxon Species Frequency Host trees Decay Diameter C C C C C C C C C C C C C C C C C C C C C C C C C C Aleurodiscus lividocaeruleus Amphinema byssoides Amphinema diadema Amyloathelia crassiuscula Amylocorticium cebennense Amylocorticium pedunculatum Amylocorticium subsulphureum Amylostereum chailletii Asterodon ferruginosus Asterostroma laxum Athelia acrospora Athelia arachnoidea Athelia bombacina Athelia decipiens Athelia epiphylla Athelia fibulata Athelia fuciformis Athelia sibirica Athelia subovata Athelicium stridii Athelopsis glaucina Athelopsis lacerata Athelopsis lembospora Athelopsis lunata Athelopsis subinconspicua Botryobasidium botryosum Rare Common Rare Rare Common Rare Rare Occasional Occasional Rare Rare Rare Occasional Common Common Common Rare Occasional Rare Rare Occasional Rare Rare Occasional Common Common Spruce Generalist Spruce Conif Conif Generalist Spruce Spruce Generalist Generalist Spruce Generalist Conif Conif Generalist Generalist Conif Generalist Generalist Generalist Generalist Conif Generalist Pine Conif Generalist Late Generalist Late Medium Medium Late Medium Early Medium Late Early Early Late Medium Generalist Generalist Late Medium Generalist Medium Medium Late Late Medium Generalist Generalist Small Generalist Small Small Generalist Generalist Small Small Generalist Generalist Large Generalist Generalist Large Generalist Generalist Large Small Small Large Large Small Small Generalist Large Generalist Pine, natural 0 19 0 1 2 2 0 0 0 1 0 0 3 5 11 6 0 0 0 0 0 1 0 1 0 65 Pine, managed 0 41 0 1 13 2 0 0 3 1 0 2 8 6 21 8 3 0 0 1 0 3 0 23 1 165 Spruce, natural 0 80 1 1 5 1 0 4 3 0 2 1 4 24 11 4 1 3 0 1 7 1 1 0 11 174 Spruce, managed 2 47 0 1 11 0 1 13 13 2 0 0 4 6 12 16 0 4 1 1 1 0 0 0 1 230 J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 1718 Taxon Species Frequency Host trees Decay Diameter C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C Botryobasidium candicans Botryobasidium conspersum Botryobasidium ellipsosporum Botryobasidium intertextum Botryobasidium obtusisporum Botryobasidium subcoronatum Botryohypochnus isabellinus Brevicellicium exile Byssocorticium lutescens Byssocorticium pulchrum Byssocorticium terrestris Byssomerulius albostramineus Cejpomyces terrigenus Ceraceomyces cystidiatus Ceraceomyces eludens Ceraceomyces microsporus Ceraceomyces nova species Ceraceomyces serpens Ceraceomyces sp. Ceraceomyces eludens Ceraceomyces micosporus cfr. Ceraceomyces tessulatus Ceraceomyces violascens Cerinomyces crustulinus Chaetoderma luna Clavulicium macounii Conferticium ochraceum Coniophora arida Coniophora fusispora Coniophora olivacea Coniophora puteana Corticium nova-species Cristinia helvetica Cystostereum murraii Cytidiella albo-mellea Dacryobolus karstenii Dacryobolus sudans Fibricium lapponicum Fibricium rude Galzinia incrustans Globulicium hiemale Gloeocystidiellum furfuraceum Granulocystis flabelliradiata Hymenochaete fuliginosa Hyphoderma argillaceum Hyphoderma capitatum Hyphoderma cremeoalbum Hyphoderma definitum Hyphoderma obtusiforme Hyphoderma obtusum Hyphoderma pallidum Hyphoderma praetermissum Hyphoderma sibiricum Hyphoderma subdefinitum Hyphoderma velatum Hyphodontia abieticola Hyphodontia alutacea Hyphodontia alutaria Hyphodontia aspera Hyphodontia breviseta Hyphodontia cineracea Hyphodontia halonata Hyphodontia hastata Hyphodontia pallidula Hyphodontia subalutacea Hypochnicium bombycinum Hypochnicium cymosum Hypochnicium eichleri Hypochnicium erikssonii Hypochnicium geogenium Hypochnicium karstenii Hypochnicium lundellii Intextomyces contiguus Irpicodon pendulus Jaapia argillacea Jaapia ochroleuca Kavinia alboviridis Rare Occasional Rare Common Common Common Common Occasional Rare Rare Rare Rare Rare Rare Rare Rare Rare Occasional Common Rare Rare Occasional Occasional Occasional Occasional Rare Occasional Common Occasional Common Occasional Rare Rare Occasional Rare Occasional Common Rare Rare Occasional Common Common Rare Common Common Rare Rare Common Occasional Rare Common Common Occasional Rare Rare Occasional Common Common Common Common Occasional Rare Common Common Common Rare Rare Common Occasional Occasional Rare Rare Rare Rare Rare Occasional Rare Generalist Generalist Generalist Conif Generalist Generalist Generalist Generalist Generalist Generalist Conif Pine Spruce Pine Conif Generalist Pine Generalist Conif Conif Pine Generalist Generalist Conif Pine Spruce Generalist Conif Conif Conif Generalist Pine Generalist Spruce Pine Pine Conif Spruce Generalist Generalist Conif Spruce Generalist Conif Generalist Pine Spruce Pine Generalist Spruce Generalist Generalist Conif Generalist Conif Conif Conif Generalist Generalist Conif Generalist Pine Conif Conif Generalist Generalist Pine Generalist Generalist Generalist Pine Generalist Generalist Pine Conif Conif Generalist Medium Medium Medium Generalist Generalist Generalist Generalist Generalist Late Medium Generalist Medium Medium Medium Medium Medium Medium Medium Medium Medium Medium Generalist Generalist Late Medium Late Generalist Medium Medium Generalist Generalist Medium Medium Medium Medium Medium Medium Late Medium Medium Medium Medium Medium Medium Medium Medium Medium Medium Medium Medium Generalist Generalist Generalist Medium Late Medium Generalist Generalist Medium Medium Medium Medium Medium Generalist Generalist Early Medium Medium Generalist Generalist Medium Medium Generalist Early Medium Medium Late Generalist Large Large Large Generalist Generalist Generalist Large Generalist Large Small Small Small Small Generalist Generalist Small Generalist Generalist Small Small Generalist Small Generalist Generalist Large Generalist Generalist Small Generalist Large Small Small Large Small Small Generalist Small Small Generalist Generalist Generalist Small Large Generalist Large Large Small Generalist Large Generalist Generalist Generalist Large Generalist Generalist Generalist Large Generalist Generalist Small Small Generalist Large Generalist Generalist Small Generalist Large Large Small Large Large Small Small Generalist Large Pine, natural 0 0 0 12 20 60 0 0 0 0 0 1 0 0 2 1 0 0 34 3 0 1 0 1 11 0 2 12 2 10 0 0 0 0 0 2 3 0 0 0 55 0 0 7 3 0 0 8 0 0 2 52 2 0 2 2 0 1 11 26 0 2 15 2 8 0 0 4 0 1 1 0 0 0 0 4 0 Pine, managed 0 0 0 14 52 101 0 0 0 2 5 2 0 2 1 2 1 3 73 0 1 7 4 11 7 0 1 18 11 13 5 1 0 0 1 14 11 0 0 2 46 0 0 16 3 1 0 16 2 0 4 85 4 3 1 2 12 0 19 58 1 1 40 4 49 4 1 29 2 0 1 0 1 1 2 10 0 Spruce, natural 1 3 2 35 19 42 4 1 0 1 0 0 0 0 2 0 0 1 40 0 0 2 0 3 1 2 6 12 1 28 5 0 0 9 0 0 4 2 0 3 77 10 0 50 58 0 3 2 0 1 5 46 9 2 2 5 17 15 44 99 4 0 10 76 26 0 0 12 0 3 0 1 1 0 2 7 1 Spruce, managed 0 0 0 12 49 72 5 1 1 0 2 0 1 0 0 0 0 2 59 0 0 1 3 4 0 0 4 13 2 20 3 0 1 8 0 0 10 0 2 1 43 13 1 11 32 0 3 2 1 0 1 56 5 1 1 2 11 0 31 118 2 0 50 33 17 0 0 13 2 3 0 2 0 0 0 2 0 J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 Taxon Species Frequency Host trees Decay Diameter C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C Kavinia himantia Laurilia sulcata Leptosporomyces galzinii Leptosporomyces mutabilis Leptosporomyces septentrionalis Leucogyrophana mollusca Leucogyrophana romellii Leucogyrophana sororia Litschauerella clematitis Lobulicium occultum Luellia recondita Luellia recondita var. furcata Merulicium fusisporum Metulodontia nivea Odonticium romellii Paullicorticium allantosporum Paullicorticium ansatum Paullicorticium delicatissimum Paullicorticium nova species Paullicorticium pearsonii Peniophora pini Peniophora pithya Phanerochaete galactites Phanerochaete laevis Phanerochaete sanguinea Phanerochaete sordida Phanerochaete velutina Phlebia centrifuga Phlebia cornea Phlebia cretacea Phlebia femsioensis Phlebia firma Phlebia lilascens Phlebia livida Phlebia segregata Phlebia serialis Phlebia subcretacea Phlebia subserialis Phlebia subulata Phlebia tristis Phlebiella borealis Phlebiella christiansenii Phlebiella grisella Phlebiella lloydii Phlebiella pseudotsugae Phlebiella subflavidogrisea Phlebiella tulasnelloidea Phlebiella vaga Phlebiopsis gigantea Physodontia lundellii Piloderma bicolor Piloderma byssinum Piloderma lanatum Pseudoxenasma verrucisporum Repetobasidium vestitum Repetobasidium vile Resinicium bicolor Resinicium furfuraceum Scytinostroma praestans Scytinostromella heterogenea Scytinostromella nannfeldtii Serpula himantioides Sistotrema alboluteum Sistotrema albopallescens Sistotrema brinkmannii Sistotrema citriforme Sistotrema coroniferum Sistotrema diademiferum Sistotrema muscicola Sistotrema oblongisporum Sistotrema octosporum Sistotremastrum suecicum Sistotremella perpusilla Sphaerobasidium minutum Stereum sanguinolentum Trechispora byssinella Rare Rare Common Rare Rare Rare Common Occasional Rare Rare Occasional Rare Rare Rare Occasional Rare Occasional Rare Rare Rare Rare Common Rare Common Common Common Occasional Rare Occasional Common Rare Rare Rare Occasional Common Rare Occasional Rare Rare Rare Rare Rare Rare Rare Occasional Rare Occasional Common Occasional Rare Common Common Occasional Rare Rare Rare Common Common Rare Rare Rare Rare Rare Rare Common Rare Rare Rare Occasional Rare Occasional Common Rare Common Common Rare Generalist Spruce Generalist Pine Generalist Conif Conif Conif Spruce Spruce Generalist Spruce Spruce Generalist Pine Spruce Spruce Generalist Spruce Conif Pine Conif Spruce Generalist Conif Generalist Generalist Spruce Pine Pine Spruce Pine Conif Conif Conif Spruce Conif Conif Spruce Conif Pine Generalist Pine Pine Conif Conif Generalist Generalist Conif Pine Generalist Generalist Generalist Spruce Spruce Spruce Generalist Conif Generalist Spruce Generalist Conif Generalist Generalist Generalist Pine Generalist Generalist Generalist Generalist Generalist Pine Generalist Conif Conif Conif Medium Medium Generalist Medium Late Generalist Generalist Late Medium Late Generalist Late Early Late Late Late Late Generalist Medium Medium Medium Early Medium Generalist Medium Medium Generalist Medium Medium Generalist Medium Medium Medium Medium Late Medium Late Medium Late Medium Medium Generalist Medium Medium Medium Medium Medium Generalist Early Late Generalist Generalist Generalist Medium Medium Medium Generalist Generalist Generalist Late Generalist Early Late Late Early Late Medium Generalist Generalist Early Generalist Generalist Medium Late Early Medium Large Small Generalist Generalist Generalist Small Generalist Generalist Small Generalist Large Large Small Generalist Large Generalist Generalist Small Large Small Large Generalist Small Generalist Generalist Generalist Generalist Large Generalist Generalist Small Small Large Generalist Generalist Small Generalist Small Generalist Small Small Generalist Small Small Large Small Generalist Generalist Generalist Large Generalist Generalist Large Generalist Small Small Generalist Generalist Small Large Large Generalist Generalist Small Generalist Small Small Generalist Small Small Large Generalist Large Generalist Generalist Small Pine, natural 0 0 35 4 2 1 20 12 0 0 0 0 0 0 13 0 2 2 0 0 0 6 0 0 12 2 0 0 6 19 0 0 1 0 4 0 1 0 0 0 0 0 0 0 7 3 0 61 1 6 89 24 1 0 0 0 3 27 0 0 0 2 0 0 1 1 0 1 0 0 1 46 0 5 8 2 1719 Pine, managed 0 0 29 1 2 2 29 3 0 0 0 0 0 1 4 0 0 0 0 2 1 29 0 1 43 5 1 0 5 14 0 2 3 0 2 0 12 4 0 1 6 0 1 1 4 2 0 143 15 2 124 53 1 0 0 0 13 75 0 0 0 2 1 0 10 0 0 4 6 2 0 79 1 8 51 0 Spruce, natural 1 0 1 0 0 2 2 2 0 4 6 1 0 0 0 6 7 1 1 1 0 41 1 8 4 5 5 6 0 0 0 0 2 7 7 1 4 0 3 0 0 1 0 0 8 1 1 97 5 0 69 61 1 5 1 0 38 12 0 1 0 0 1 2 8 0 0 0 4 0 3 4 0 19 36 0 Spruce, managed 0 2 4 0 0 0 2 1 1 1 2 0 1 0 0 0 4 0 0 1 0 89 0 7 13 13 3 0 0 0 1 0 0 4 7 0 4 1 0 1 0 1 0 0 1 0 2 158 1 0 76 40 1 0 0 1 32 12 2 0 1 2 0 0 12 0 1 1 3 0 2 3 0 5 76 3 J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 1720 Taxon Species Frequency Host trees Decay Diameter Pine, natural Pine, managed C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C P P P P P P P P P P P P P P P P P P P P P P P P P P P P P P P P P P P P P P P Trechispora cohaerens Trechispora confinis Trechispora farinacea Trechispora hymenocystis Trechispora incisa Trechispora kavinioides Trechispora laevis Trechispora microspora Trechispora minima Trechispora minutum Trechispora stellulata Trechispora subsphaerospora Trechispora tenuicula Trechispora verruculosa Tubulicrinis accedens Tubulicrinis angustus Tubulicrinis borealis Tubulicrinis calothrix Tubulicrinis chaetophorus Tubulicrinis confusus Tubulicrinis effugiens Tubulicrinis evenii Tubulicrinis glebulosus Tubulicrinis globisporus Tubulicrinis hirtellus Tubulicrinis inornatus Tubulicrinis medius Tubulicrinis propinquus Tubulicrinis regificus Tubulicrinis sororius Tubulicrinis strangulatus Tubulicrinis subulatus Tylospora asterophora Tylospora fibrillosa Uthatobasidium fusisporum Veluticeps abietina Vesiculomyces citrinus Anomoporia kamtschatica Antrodia albobrunnea Antrodia gossypina Antrodia heteromorpha Antrodia serialis Antrodia sinuosa Antrodia sitchensis Antrodia xantha Antrodiella citrinella Antrodiella parasitica Ceriporiopsis jelicii Ceriporiopsis mucida Dichomitus squalens Diplomitoporus lindbladii Fomitopsis pinicola Fomitopsis rosea Gloeophyllum odoratum Gloeophyllum sepiarium Gloeoporus taxicola Heterobasidion annosum Ischnoderma benzoinum Junghuhnia collabens Junghuhnia luteoalba Leptoporus mollis Oligoporus caesius Oligoporus fragilis Oligoporus hibernicus Oligoporus lateritius Oligoporus leucomallellus Oligoporus rancidus Oligoporus rennyi Oligoporus septentrionalis Oligoporus sericeomollis Oligoporus stipticus Oligoporus tephroleucus Phellinus chrysoloma Phellinus ferrugineofuscus Phellinus nigrolimitatus Phellinus pini Occasional Occasional Common Common Rare Rare Common Occasional Occasional Rare Occasional Common Rare Rare Common Rare Common Common Rare Rare Occasional Rare Common Occasional Common Occasional Common Occasional Rare Rare Rare Common Common Common Occasional Common Common Rare Rare Rare Rare Common Common Rare Common Rare Rare Rare Rare Rare Common Common Occasional Rare Common Rare Common Occasional Rare Occasional Rare Common Rare Common Rare Rare Rare Occasional Rare Common Rare Occasional Rare Common Common Rare Generalist Generalist Generalist Generalist Spruce Spruce Generalist Generalist Conif Generalist Generalist Conif Pine Conif Conif Conif Conif Conif Conif Spruce Pine Pine Pine Pine Pine Conif Pine Pine Generalist Conif Conif Conif Generalist Generalist Generalist Spruce Generalist Pine Pine Pine Spruce Spruce Conif Pine Pine Spruce Generalist Spruce Generalist Pine Generalist Generalist Spruce Spruce Conif Pine Spruce Conif Conif Pine Spruce Spruce Spruce Conif Pine Pine Pine Conif Spruce Pine Spruce Generalist Spruce Spruce Spruce Pine Medium Generalist Generalist Late Late Medium Late Late Late Late Medium Generalist Medium Medium Generalist Medium Medium Medium Medium Medium Late Medium Generalist Late Late Late Medium Generalist Late Medium Medium Medium Generalist Generalist Late Medium Generalist Late Medium Medium Early Medium Medium Late Medium Medium Medium Medium Medium Medium Medium Generalist Medium Medium Medium Medium Medium Medium Medium Medium Medium Medium Medium Generalist Medium Medium Medium Medium Medium Late Medium Medium Medium Medium Late Medium Generalist Generalist Generalist Generalist Large Small Generalist Generalist Small Generalist Small Generalist Large Large Generalist Generalist Generalist Generalist Large Large Large Generalist Small Generalist Large Generalist Generalist Generalist Small Large Generalist Generalist Generalist Generalist Generalist Large Generalist Large Generalist Small Large Generalist Generalist Small Generalist Large Small Generalist Generalist Large Small Generalist Large Small Generalist Small Generalist Large Large Generalist Large Generalist Small Generalist Generalist Small Small Large Small Large Large Generalist Generalist Large Large Large 0 0 112 0 0 0 4 0 5 0 1 8 1 2 13 2 7 6 1 0 12 1 7 10 41 8 30 3 0 3 1 16 2 2 1 1 2 2 5 0 0 1 8 2 8 0 0 0 0 0 7 2 0 0 6 0 0 0 1 2 0 0 0 7 3 1 0 5 0 28 0 0 0 0 1 1 1 0 135 0 0 0 9 3 3 1 2 27 0 2 16 2 24 17 0 0 6 1 24 11 17 2 22 8 0 2 1 77 2 13 0 0 7 0 2 1 0 7 32 2 24 0 0 0 1 1 11 19 0 0 14 2 0 5 0 10 0 2 1 16 1 2 1 4 0 12 0 3 0 0 3 0 Spruce, natural 1 0 56 14 1 1 8 2 1 3 1 15 0 2 11 1 34 19 2 2 0 0 2 3 0 1 4 0 1 0 2 54 13 44 3 13 20 0 0 0 1 65 15 0 2 4 0 2 1 0 2 61 11 1 17 0 8 3 1 0 3 35 1 4 0 0 0 0 0 4 2 3 5 20 61 0 Spruce, managed 0 1 38 2 0 1 4 1 0 1 1 20 0 0 5 1 33 26 0 0 0 0 3 2 0 1 2 1 0 1 1 38 10 48 2 18 13 0 0 0 0 42 11 0 2 0 1 0 0 0 8 51 4 1 113 0 27 3 0 0 1 35 5 4 0 0 0 3 1 2 1 4 0 6 10 0 J.N. Stokland, K.-H. Larsson / Forest Ecology and Management 261 (2011) 1707–1721 Taxon Species Frequency Host trees Decay Diameter P P P P P P P P P P P P P P P P Phellinus viticola Physisporinus sanguinolentus Physisporinus vitreus Skeletocutis albocremea Skeletocutis alutacea Skeletocutis amorpha Skeletocutis biguttulata Skeletocutis carneogrisea Skeletocutis chrysella Skeletocutis kuehneri Skeletocutis lenis Skeletocutis papyracea Skeletocutis stellae Skeletocutis subincarnata Trichaptum abietinum Trichaptum fuscoviolaceum Common Rare Rare Rare Rare Rare Occasional Occasional Rare Occasional Rare Rare Rare Rare Common Occasional Conif Generalist Spruce Spruce Pine Conif Pine Spruce Spruce Conif Generalist Pine Conif Pine Conif Pine Medium Generalist Medium Medium Late Medium Medium Medium Medium Medium Medium Late Medium Medium Early Early Generalist Generalist Large Small Small Small Small Generalist Small Generalist Generalist Small Small Small Generalist Generalist References Bader, P., Jansson, S., Jonsson, B.G., 1995. Wood-inhabiting fungi and substratum decline in selectively logged boreal spruce forests. Biological Conservation 72, 355–362. Boddy, L., Heilmann-Clausen, J., 2008. Basidiomycete community development in temperate angiosperm wood. In: Boddy, L., Frankland, J.C., van West, P. (Eds.), Ecology of Saprotrophic Basidiomycetes. Elsvier, pp. 211–237. Edman, M., Gustafsson, M., Stenlid, J., Ericson, L., 2004a. Abundance and viability of fungal spores along a forestry gradient – responses to habitat loss and isolation? Oikos 104, 35–42. Edman, M., Gustafsson, M., Stenlid, J., Jonsson, B.G., Ericson, L., 2004b. Spore deposition of wood-decaying fungi: importance of landscape composition. Ecography 27, 103–111. Engelmark, O., 1984. Forest fires in the Muddus National Park (Northern Sweden) during the past 600 years. Canadian Journal of Botany 62, 893–898. Granström, A., 2001. Fire management for biodiversity in the European boreal forest. Scandinavian Journal of Forest Research 16 (Suppl 3), 62–69. Gärdenfors, U., 2005. The Red List of Swedish Species. Uppsala. Hanski, I., 1999. Metapopulation ecology. Oxford University Press. Hofgaard, A., 1993. 50 years of change in a Sedish boreal old-growth Picea abies forest. Journal of Vegetation Sience 4, 773–782. Holmer, L., Renvall, P., Stenlid, J., 1997. Selective replacement between species of wood-rotting basidiomycetes, a laboratory study. Mycological Research 101, 714–720. Holmer, L., Stenlid, J., 1997. Competitive hierarchies of wood decomposing basidiomycetes in artificial systems based on variable inoculum sizes. Oikos 79, 77–84. Hytteborn, H., Packham, J.R., 1987. Decay rate of Picea abies logs and the storm gap theory: a re-examination of Sernander plot III, Fiby urskug, central Sweden. Arboricultural Journal 11, 299–311. Hågvar, S., 1999. Saproxylic beetles visiting living sporocarps of Fomitopsis pinicola and Fomes fomentarius. Norwegian Journal of Entomology 46, 25–32. Junninen, K., Komonen, A., 2010. Conservation ecology of boreal polypores: a review. Biological Conservation. doi:10.1016/j.biocon.2010.07.010. Junninen, K., Similä, M., Kouki, J., Kotiranta, H., 2006. Assemblages of woodinhabiting fungi along the gradient of succession and naturalness in boreal pine-dominated forests in Fennoscandia. Ecography 29, 75–83. Lindblad, I., 1998. Wood-inhabiting fungi on fallen logs of Norway spruce: relations to forest management and substrate quality. Nordic Journal of Botany 18, 243–255. Linder, P., Östlund, L., 1998. Structural changes in three mid-boreal Swedish forest landscapes, 1885–1996. Biological Conservation 85, 9–19. Niemelä, T., 2005. Käävät — puiden sienet (Polypores — lignicolous fungi). Museum of Natural History, Helsinki. Niklasson, N., Drakenberg, B., 2001. A 600-year tree-ring fire history from Norra Kvills National Park, southern Swed implications for conservation strategies in the hemi-boreal zone. Biological Conservation 101, 63–71. Nordén, B., Larsson, K.-H., 2000. Basidiospore dispersal in the old-growth forest fungus Phlebia centrifuga (Basidiomycetes). Nordic Journal of Botany 20, 215–219. Næsset, E., 1999. Relationship between relative wood density of picea abies logs and simple classification systems of decayed coarse woody debris. Scandinavian Journal of Forest Research 14, 454–461. Ohlson, M., Söderström, L., Hörnberg, G., Zackrisson, O., Hermansson, J., 1997. Habitat qualities versus long-term continuity as determinants of biodiversity in boreal old-growth swamp forests. Biological Conservation 81, 221–231. Pine, natural 15 0 0 0 0 0 2 0 0 4 1 0 1 0 10 1 1721 Pine, managed 13 0 0 0 3 1 19 3 0 15 0 1 1 8 66 15 Spruce, natural 42 1 2 0 0 0 1 8 1 4 1 0 1 0 73 0 Spruce, managed 57 0 0 1 0 0 1 4 0 4 0 0 0 0 153 0 Ohlson, M., Tryterud, E., 1999. Long-term spruce forest continuity – a challenge for a sustainable Scandinavian forestry. Forest Ecology and Management 124, 27–34. Penttilä, R., Lindgren, M., Miettinen, O., Rita, H., Hanski, I., 2006. Consequences of forest fragmentation for polyporous fungi at two spatial scales. Oikos 114, 225–240. Penttilä, R., Siitonen, J., Kuusinen, M., 2004. Polypore diversity in managed and oldgrowth boreal Picea abies forests in southern Finland. Biological Conservation 117, 271–283. Raivio, S., Normark, E., Pettersson, B., Salpakivi-Salomaa, P., 2001. Science and the management of boreal forest biodiversity – forest Iindustries’ views. Scandinavian Journal of Forest Research 16 (Suppl. 3), 99–104. Ranius, T., Kindvall, O., 2004. Modelling the amount of coarse woody debris produced by the new biodiversity-oriented silvicultural practices in Sweden. Biological Conservation 119, 51–59. Rayner, A.D.M., Boddy, L., 1988. Fungal Decomposition of Wood. Its Biology and Ecology. John Wiley & Sons Ltd. Rolstad, J., Framstad, E., Gundersen, V., Storaunet, K.O., 2002. Naturskog i Norge. Definisjoner økologi, og bruk i norsk skog-og miljøforvaltning (in Norwegian). Aktuelt fra skogforskningen 1, 1–53. Siitonen, J., 2001. Forest management, coarse woody debris and saproxylic organisms: Fennoscandian boreal forests as an example. Ecological Bulletins 49, 11–41. Sippola, A.-L., Lehesvirta, T., Renvall, P., 2001. Effects of selective logging on coarse woody debris and diversity of wood-decaying polypores in eastern Finland. Ecological Bulletins 49, 243–254. Sippola, A.-L., Renvall, P., 1999. Wood-decomposing fungi and seed-tree cutting: a 40-year perspective. Forest Ecology and Management 115, 183–201. Stokland, J.N., 2001. The coarse woody debris profile: an archive of recent forest history and an important biodiversity indicator. Ecological Bulletins 49, 71–83. Stokland, J.N., 2011. Evolution of saproxylic organisms. In: Usher, M. (Ed.), The Biological Diversity in Dead Wood. Cambridge University Press. Stokland, J.N., Eriksen, R., Tomter, S., Korhonen, K., Tomppo, E., Rajaniemi, S., Söderberg, U., Toet, H., Riis-Nielsen, T., 2003. Forest biodiversity indicators in the Nordic countries Status based on the national forest inventories. TemaNord 514, 1–106. Stokland, J.N., Kauserud, H., 2004. Phellinus nigrolimitatus – a wood-decomposing fungus highly influenced by forestry. Forest Ecology and Management 187, 333–343. Stokland, J.N., Meyke, E., 2008. The saproxylic database: an emerging overview of the biological diversity in dead wood. Revue d’Ecologie (Terre Vie) Suppl. 10, 37–48. Stokland, J. N., Tomter, S., Söderberg, U., 2004. Development of dead wood indicators for biodiversity monitoring: experiences from Scandinavia. In: Marchetti, M. (Ed.), Monitoring and indicators of forest biodiversity in Europe – from ideas to operationality, pp. 207–226. Tryterud, E., 2003. Forest fire history in Norway: from fire-disturbed pine forets to fire-free spruce forests. Ecography 26, 161–170. Tveite, S., 1964. Skogbrukshistorie. In: Seip, H.K. (Ed.), Skogbruksboka. Bind 3: Skogøkonomi. Skogforlaget, Oslo, pp. 17–75. Virkkala, R., Korhonen, K.T., Haapanen, R., 2000. Protected forests and mires in forest and mire vegetation zones in Finland based on the 8th National forest inventory. Soumen Ympärist 395, 1–52. Zackrisson, O., 1977. Influence of forest fires on North Swedish boreal forest. Oikos 29, 22–32.

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Legacies from natural forest dynamics: Different effects of forest management on wood-inhabiting fungi in pine and spruce forests

Legacies from natural forest dynamics: Different effects of forest management on wood-inhabiting fungi in pine and spruce forests

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