Epiphytic lichen diversity in late-successional Pinus sylvestris forests along local and regional forest utilization gradients in eastern boreal Fennoscandia

Forest Ecology and Management 259 (2010) 883–892

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Epiphytic lichen diversity in late-successional Pinus sylvestris forests along local and regional forest utilization gradients in eastern boreal Fennoscandia Sampsa Lommi a, Ha˚kan Berglund b, Mikko Kuusinen c, Timo Kuuluvainen d,* a

Botanical Museum, Finnish Museum of Natural History, P.O. Box 7, FI-00014 University of Helsinki, Helsinki, Finland Department of Ecology, Swedish University of Agricultural Sciences, P.O. Box 7044, SE-750 07 Uppsala, Sweden c Ministry of Environment, Kasarmikatu 25, P.O. Box 35, FI-00023 Helsinki, Finland d Department of Forest Ecology, P.O. Box 27, FIN-00014 University of Helsinki, Helsinki, Finland b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 10 August 2009 Received in revised form 19 November 2009 Accepted 23 November 2009

Pinus sylvestris-dominated forests have been heavily utilized across all of boreal Fennoscandia and the remaining natural forests are generally highly fragmented. However, there are considerable local and regional differences in the intensity and duration of past forest utilization. We studied the impact of human forest use on the diversity of epiphytic and epixylic lichens in late-successional Pinus sylvestrisdominated forests by assessing species richness and composition along both local and regional gradients in forest utilization. The effects of local logging intensity were analysed by comparing three types of stands: (i) near-natural, (ii) selectively logged (in the early 20th century) and (iii) managed stands. The effects of regional differences in duration and intensity of past forest use were analysed by comparing stands in two contrasting regions (Ha¨me and Kuhmo–Viena). The species richness of selectively logged stands was as high as that of near-natural stands and significantly higher in these two stand categories than in managed stands. Species richness increased with the density of small understorey Picea, which correlated strongly with decreasing intensity of local forest use and increasing structural complexity of selectively logged and near-natural stands. Stands in the Ha¨me region hosted a lower number of species, and were less likely to host many old-growth indicator species than the Kuhmo–Viena region, suggesting that species have been lost from stands in the Ha¨me region due to a longer history of intensive forest use. We conclude that selectively logged stands, along with near-natural stands, are valuable lichen habitats particularly for species confined to old-growth structures such as coarse trees and deadwood. In landscapes where natural forests have become fragmented, the management or restoration of the remaining late-successional Pinus-dominated forests, e.g. through the use of fire, should be carefully planned to avoid adverse effects on lichen species richness. ß 2009 Elsevier B.V. All rights reserved.

Keywords: Picea Succession Extinction debt Conservation planning Coarse woody debris

1. Introduction Structurally complex late-successional forests are a predominant landscape element under natural conditions in boreal Fennoscandia (Kuuluvainen, 2002; Pennanen, 2002). The multistorey Scots pine (Pinus sylvestris L.)-dominated stands on dry and semi-dry sites provide an example. The structure and dynamics of these forests are shaped by occasional surface fires that kill understorey trees but leave large pines alive to provide a seed source (Kuuluvainen et al., 2002). Stand structural complexity after fire is increased by increasing the abundance of understory with Norway spruce (Picea abies (L.) H. Karst.) and deciduous trees

* Corresponding author. Tel.: +358 919158116; fax: +358 919158100. E-mail addresses: Sampsa.Lommi@helsinki.fi (S. Lommi), [email protected] (H. Berglund), Mikko.Kuusinen@ymparisto.fi (M. Kuusinen), Timo.Kuuluvainen@helsinki.fi (T. Kuuluvainen). 0378-1127/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2009.11.028

¨ stlund, 2001; Lilja and (Linder et al., 1997; Axelsson and O Kuuluvainen, 2005). However, intensive and prolonged forest utilization has greatly reduced both the area of such natural forest and the overall availability of key structural elements such as coarse old trees and deadwood in managed forests (Kouki et al., 2001; Siitonen, 2001; Lilja and Kuuluvainen, 2005). In addition, intensified forestry has largely decoupled forest habitats from their natural disturbance processes and successions, mainly due to systematic fire suppression. However, there are important local and regional variations in the history of forest use. For example, there is an overall decreasing gradient in the intensity and duration of forest use from the southwestern to northeastern parts of Finland (Lilja and Kuuluvainen, 2005). The simplification of forest structural complexity brought about by forest management based on clear-cut harvesting is considered as the main reason for the decline of many forest species (Hanski, 2000; Rassi et al., 2001). For example, epiphytic and epixylic

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lichens are directly affected by changes in forest structure because they are dependent on trees or dead wood as physical structures and growing surfaces (Esseen et al., 1996; Dettki and Esseen, 2002; Paltto et al., 2008). Some species are specialized for growing on specific host trees, dead standing trunks or burned wood that rarely occur in managed forests (Timdal, 1984; Kuusinen and Siitonen, 1998). Furthermore, several red-listed lichen species are apparently sensitive to edge effects and unable to utilize host substrates other than those available in forests where moist and stable old-growth conditions prevail. In addition, several studies suggest that dispersal limitations may be common among epiphytic lichens (Sillett et al., 2000; Hilmo and Ott, 2002). Hence, some species may be regionally declining because of a high risk of local extinctions (Pyka¨la¨, 2004), edge effects (Moen and Jonsson, 2003) and low connectivity of their core habitats (Gu et al., 2002). In southern Finland air pollution probably has negatively affected the abundance of the most sensitive pendulous lichens such as Usnea and Bryoria spp. (Kuusinen et al., 1990). The aim of this study was to analyse how lichen species richness and composition vary along local and regional gradients of forest use, with an emphasis on the occurrence of species mainly utilizing pines (Pinus) as the host trees. At the local scale, we compared lichen communities between mature managed, selectively logged (in the early 20th century) and near-natural stands. We also assessed potential regional effects by comparing the lichen diversity in two geographic regions: the Ha¨me region in southwestern Finland, characterized by a long history of intensive forest utilization, and the Kuhmo–Viena region in the border zone between Finland and Russia in northeastern Fennoscandia, with a more recent history of forest utilization and still characterized by near-natural forest. In this study we used a subset of a larger set of sample plots previously used for analysing the impacts of forest use on stand structures of dead and living trees in late-successional Pinus-dominated forests (Rouvinen et al., 2002; Lilja and Kuuluvainen, 2005).

2. Methods 2.1. Study regions The stands studied were located within two different regions in the middle boreal zone: (1) the Ha¨me region in southwestern Finland and (2) the Kuhmo and Viena areas in the border zone between Finland and Russia in eastern Fennoscandia. Since the Kuhmo and Viena areas are geographically close and have similar geology, climate and land-use history, they were treated together and hereafter referred to as the Kuhmo–Viena region (Fig. 1). The annual precipitation is the same in both study regions (650 mm) and the temperature sum is 1100 8C in Ha¨me and app. 900–950 8C in Kuhmo–Viena (Anonymous, 1992). The forests in both regions are mostly dominated by P. sylvestris or P. abies. The most common forest site types sensu Cajander (1926) are the mesic Vaccinium-Myrtillus and the semi-dry Empetrum-Vaccinium types (Rouvinen et al., 2002). In the Ha¨me region slash-and-burn cultivation was practised until the early 20th century (Heikinheimo, 1915). In the Kuhmo– Viena region, slash-and-burn cultivation has also been an important source of livelihood (Virtaranta, 1978), which probably affected the past fire regime of forests (Lehtonen and Kolstro¨m, 2000). In Finland, both Ha¨me and Kuhmo are located within forest areas formerly subjected to intensive tar extraction (Kaila, 1931). Tar-burning was actively practised especially in Kuhmo from the mid-19th century until as late as the early 20th century (Heikkinen, 2000). In Russian Viena, large-scale tar production

has not been practised although some tar was produced in every village (Hautala, 1956). Selective logging was applied in the study regions before the mid-20th century. The period of intensive selective logging was longest in Ha¨me, due to its higher population density and its location in the vicinity of the forest industry in southern Finland. In Kuhmo, slash-and-burn cultivation and tar-burning were common activities and continued for longer periods than in Ha¨me, but from the mid-19th century selective logging also became an important source of livelihood (Heikkinen, 2000). Selective logging has also been practised in Russian Viena, as indicated by the presence of cut stumps, but this was mostly for local purposes (Karjalainen and Kuuluvainen, 2002). Thus, there is a gradient of decreasing human impact on forests from Ha¨me in south-central Finland toward the more remote Kuhmo–Viena region in the Finnish-Russian border area. In both regions, large areas of forests, previously impacted by scattered selective cuttings, have become more fragmented due to clearcuttings performed during recent decades. In Finland, modern silvicultural practices, such as thinning and removal of understory Picea and deciduous trees, have also been used to treat stands to become managed production forests. However, on the Russian side of the Kuhmo–Viena region, no modern silvicultural treatments have been employed, and even the domestic use of wood has been low, due to the abandonment of the nearby small villages during the Soviet era. 2.2. Site selection and sampling 2.2.1. Site selection This study is based on 62 sample plots, which are a subset of a larger set of 116 sample plots used previously for examining human impacts on stand structures of dead and living trees in latesuccessional Pinus-dominated forests (Rouvinen et al., 2002; Lilja and Kuuluvainen, 2005) (Fig. 1). The sampling of stands was stratified across three forest stand categories representing a local gradient of increasing human forest use: (1) near-natural stands, (2) stands selectively logged in the early 20th century and not treated since, and (3) managed stands. The classification of stands was based on the number of cut stumps per hectare and stand structure. Near-natural stands had no or 5 cut stumps per hectare and the stand structure was heterogeneous and typically unevenly sized. In selectively logged stands there were no signs of modern silvicultural practices but cut stumps from selective loggings of Pinus in the early 20th century were more frequently encountered (more than five cut stumps per hectare) and stands were characterized by uneven tree-size structure. In contrast, the managed stands were subjected to silvicultural treatments during the late 20th century, such as thinning from below, and their spatial structure was homogenized and the trees were similarly sized. The 62 stands were randomly selected to include stands representing each stand category in both study regions: 30 in Ha¨me (4 near-natural, 8 selectively logged and 18 managed stands) and 32 in Kuhmo–Viena (2 near-natural, 17 selectively logged and 7 managed stands in Kuhmo, and 3 near-natural and 3 selectively logged stands in Viena). The uneven number of stands in the forest utilization intensity categories was due to constraints set by logistics and availability of suitable stands (see Lilja and Kuuluvainen, 2005). In the Ha¨me region, near-natural forest stands were selected from protected forest areas and selectively logged and managed stands from the surrounding managed forests. Selectively logged stands were also sampled from previously managed forests now included in the protected areas. We used the same strategy to select stands on the Finnish side in the Kuhmo region. Additional near-natural and selectively logged stands were sampled within

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Fig. 1. Map showing the location of the sample plots (i.e. stands) in the two study regions Ha¨me and Kuhmo–Viena.

Viena on the Russian side. Here the sample plots were placed randomly along five 4-km lines running in an east-west direction at 1-km intervals in a north-south direction (for details see Karjalainen and Kuuluvainen, 2002; Rouvinen et al., 2002). Sample plots of 0.2 ha (20 m  100 m) were randomly established in each stand. In all plots, 1–3 dominant trees were cored at the stem base to indicate the age of the oldest trees. All living and dead trees (height 1.3 m) were recorded by species and their diameters at breast height (DBH) were measured. The height was measured for trees with DBH 30 cm for estimation of volume. For volume calculation methods, see Rouvinen et al. (2002) and Lilja and Kuuluvainen (2005).

2.2.2. Lichen inventory The occurrence of epiphytic and epixylic lichens were inventoried in three 20-m  20-m sample quadrates in each of the 20-m  100-m plots (i.e. the first, third and last segments). The sampling of epiphytic and epixylic lichens included all fruticose and foliose species, except Cladonia species. However, for crustose lichens we had to restrict the sampling to a list of preselected species, due to limited time and resources. We sampled (i) all lichenized calicioids, and (ii) 32 additional crustose lichen species that could be identified in the field. To assess the proportion of the total epiphytic and epixylic lichen flora sampled, we performed total inventories of lichens (including also Cladonia species and all

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crustose lichen species) in seven plots in the Kuhmo–Viena region (including two plots in managed forests). The occurrence of each lichen species was recorded separately on different tree species (including dead standing and downed logs). In addition, we inventoried the occurrence of lichens on stumps, snags, and logs of Pinus. Species were recorded on basal parts (2 m in height) of standing trees and downed logs. Dwarf shrubs and seedlings <1.3 m in height were excluded from the data, except juniper (Juniperus communis L.) bushes 0.5 m in height. In the analyses, we pooled the data on species occurrences from the three sample quadrates within each sample plot. 2.3. Statistical analysis The species composition was analysed with nonmetric multidimensional scaling (NMDS). This method ordinates the data in a given number of dimensions so that the distances between the sample plots (i.e. stands) in the ordination reflect their similarity or dissimilarity in species composition. The inter stand similarity in species composition was calculated with the Bray-Curtis similarity measure. The NMDS was computed, using 1–3 dimensions and 100 random starts. We used a maximum of 50 iterations and the iteration procedure was ended at a stress reduction ratio of 0.999. The final stress was 11.0. We included all species in the ordinations. Similar results were achieved when species found in only one plot were excluded, indicating the robustness of the data. Since most of the inter stand variation in species composition was explained by the first two dimensions, a two-dimensional solution was selected. Centroids for each species were calculated as weighted averages of their ordination scores. Representative species were then chosen and added to the ordination plot (Fig. 2). To analyse the relationships between stand variables and species richness, we used generalized linear models (GLMs). We derived five different estimates of epiphytic lichen species richness per stand and performed separate analyses of each estimate. We treated (i) the number of all recorded species as one estimate and defined it as total species richness. Furthermore, the numbers of species within the subgroups (ii) macrolichens and (iii) calicioids were treated as two different estimates. Finally, we estimated the number of species recorded on three different types of substrates: (iv) Pinus, (v) Picea and (vi) deadwood (standing dead trees, snags, stumps and logs). Since the response variables were species counts, the error distribution was Poisson or, when overdispersion occurred, quasi-Poisson. The model link function was logarithmic. Two groups of stand variables were tested as explanatory variables in the GLMs: (1) the fixed main factors, including (i) the degree of human impact, indicated by the three stand categories and (ii) the region, indicated by the two region identities, and (2) the continuous covariables, i.e. the measured stand structure variables. When the GLMs were developed, we first separately tested the effects of the two main factors and their two-factor interaction on average species richness while not including the covariables. Likewise, we separately tested the effects of the covariables used while not including the main factors. Both main factors and covariables were finally included simultaneously in the full models. Four different covariables were used to control for inter stand variation in substrate availability for lichens. They were the number of small (DBH <10 cm) Picea and Pinus trees per hectare and the number of large (DBH 10 cm) Picea and Pinus trees per hectare. In each class, the estimated density of trees included the sum of both living and dead standing trees. We had two reasons for choosing these four covariables. Firstly, they indicated the densities of potential host trees within four distinct tree quality classes, small understorey trees and large canopy trees of the two conifer tree species dominating the forests studied. Secondly,

Fig. 2. Two-dimensional solution of the nonmetric multidimensional scaling ordination of epiphytic and epixylic lichen species composition in 62 plots (i.e. stands) sampled in mature managed, selectively logged and near-natural forests in the Ha¨me and Kuhmo–Viena regions in boreal Finland. The occurrence of some selected species is indicated with abbreviations of species names (species associated with Pinus, including dead and charred wood; bryfre: Bryoria fremontii, calgla: Calicium glaucellum, calpar: C. parvum, caltra: C. trabinellum, chabru: Chaenotheca brunneola, hypant: Hypocenomyce anthracophila, hypcas: H. castaneocinerea. Other lichens shown; alesar: Alectoria sarmentosa, brynad: B. nadvornikiana, bryfus: B. fuscescens, evemes: Evernia mesomorpha, hypsca: H. scalaris, and; hypfar: Hypogymnia farinacea.

principal component analysis of the measured stand variables showed that the density of Pinus, but especially of Picea, were the most important factors for explaining differences in stand characteristics between the forests studied. However, when the number of species recorded on dead wood were analysed, we also built GLMs with three covariables describing the availability of deadwood, the density of small (DBH <10 cm) and large (DBH 10 cm) dead standing trees and the density of downed logs. To test the effect of the main factors and covariables on lichen species richness, we used type III analysis of deviance; the additional effect of each variable was tested after first including all other variables (Fox, 2002). The x2 (chi-square likelihood ratio) values were used as the test statistic in Poisson GLMs and the Fvalue in quasi-Poisson GLMs. The unbalanced design was considered when interpreting the results. First, the analyses revealed a significant effect of local human impact on species richness since the species richness in managed stands (n = 25) was significantly lower than in selectively logged (n = 28) and near-natural stands (n = 9). However, the inference was considered valid, primarily because the number of managed stands was comparable to that of selectively logged stands. Second, the analyses also revealed a regional effect, i.e. stands in the Ha¨me region hosted a lower number of species than the stands in the Kuhmo–Viena region. In this case the inference were complicated owing to the higher number of managed stands in Ha¨me (n = 18) than in Kuhmo–Viena (n = 7). Thus, in order to assess the sensitivity of the analyses of the regional effect, we also fitted models based on data from only the selectively logged and near-natural stands. In addition, we analysed the occurrence of four individual epiphytic lichen species associated with Pinus by constructing multiple logistic regression models. These lichens were known to be strongly dependent on Pinus as the host tree. Two of the species studied, Bryoria fremontii and Calicium parvum, utilize living Pinus

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trees (Krog et al., 1994; Tibell, 1999). The two other species were the crustose lichens Hypocenomyce anthracophila and H. castaneocinerea. They grow mainly on charred deadwood of Pinus (Timdal, 1984). The R software (version 2.6.0) was used for the statistical analyses (R Development Core Team, 2007) with the add-on packages MASS version 7.2-36 and vegan version 1.8-8. 3. Results 3.1. Stand characteristics The following stand characteristics concern the 62 plots in which the lichen inventory was carried out (cf. Lilja and Kuuluvainen, 2005). The average age of the dominant canopy trees in selectively logged and near-natural stands in both the Ha¨me and Kuhmo–Viena regions was over 175 years (Table 1). This also held for managed stands in Kuhmo–Viena, but those in Ha¨me were somewhat younger with an average age of 111 years. This difference was probably because the managed stands in Kuhmo– Viena have slowly grown unthinned until recently. The average total tree volume (both living and dead trees) in the near-natural stands of the Ha¨me region (401 m3 ha1) was clearly higher than in any other stand category, followed by selectively logged stands in Ha¨me (301 m3 ha1) and in Kuhmo–Viena (281 m3 ha1). The lowest total volumes were found in the managed stands, averaging 169 m3 ha1 in Ha¨me and 180 m3 ha1 in Kuhmo–Viena (Table 1). As could be expected, Pinus comprised most of the total volume of trees in both geographic regions and in each stand category (range 52–89%). However, Picea were important as subdominant tree species in both selectively logged and near-natural stands (range 31–39%). Deciduous trees comprised app. 15% of the total tree volume in selectively logged and near-natural stands in the Kuhmo–Viena region and less than 6% in the other stands (Table 1). The volume of deadwood was highest in the near-natural forests in Ha¨me and Kuhmo–Viena (67 and 71 m3 ha1, respectively). The deadwood volume was lowest in the managed stands in Ha¨me (7 m3 ha1), followed by the managed stands in Kuhmo– Viena (22 m3 ha1; cf. Rouvinen et al., 2002). In the selectively logged and near-natural stands in both regions, the diameter distribution was such that the number of trees decreased with increase in diameter. By contrast, the managed stands showed a bimodal diameter distribution, with

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two peaks representing the small understorey trees (DBH <10 cm) and the large canopy trees (DBH 10 cm). However, the average density of the small understorey trees in the managed stands (423  157 trees per hectare) was still clearly lower than in the selectively logged stands (648  192) and near-natural stands (594  147 trees per hectare; F2,59 = 11.6, p < 0.001). This difference was most likely an effect of thinning from below performed in the managed stands, e.g. the removal of understorey Picea. In fact, Picea and deciduous tree species comprised 50% of the small understorey trees in 29 of the 37 selectively logged and near-natural stands. The average density of small Picea was significantly lower in managed stands (52  64 trees per hectare) compared to selectively logged (358  213 trees per hectare) and near-natural stands (314  183 trees per hectare; F2,59 = 24.4, p < 0.001). Hence, the density of small Picea correlated significantly with several other stand structure variables reflecting the degree of human impact. It increased with the density of logs (r = 0.44, p < 0.001) and decreased with the density of cut stumps (r = 0.47, p < 0.001). The density of small Picea was also correlated with the density of large Picea (r = 0.53, p < 0.001) and the density of small Pinus (r = 0.45, p < 0.001). 3.2. Lichen species composition and richness In all, 50–107 species per plot were found in the seven stands that were subjected to detailed inventory of the occurrence of all epiphytic and epixylic lichen species. About 43–58% of all species present were captured by restricting the sampling to the lichens selected (i.e. all macrolichens except Cladonia species. and the preselected subset of crustose lichens, see Section 2). With the restricted set of species and across all stands studied, we recorded a total of 86 species. More than half of them (n = 47) were species on the preselected list of crustose lichens, while the remaining species (n = 39) were macrolichens (excluding Cladonia species). The majority of recorded species (79%) occurred more frequently in the selectively logged and near-natural stands than in the managed stands. A majority of species (67%) also occurred more frequently in the Kuhmo–Viena than in the Ha¨me region. A total of 31 species (36% of all species recorded) were found in the selectively logged and/or near-natural stands but not in the managed stands (Fig. 2). Only one of the recorded species (Cyphelium inquinans) was unique for managed stands, but it was found only once. In all, 25 species were recorded only in the Kuhmo–Viena region, where a total of 81 species were observed.

Table 1 Stand characteristics in the near-natural (N), selectively logged (S) and managed (M) stands in the Ha¨me and Kuhmo–Viena regions. Data are means and standard deviations (in parentheses). Ha¨me

Kuhmo–Viena

N

S

M

N

S

M

Stand age (years) Range in stand age

210.0 (34.6) 180–260

175.4 (45.0) 116–260

110.9 (13.7) 90–140

178.0 (22.2) 155–215

191.2 (23.4) 142–230

180.9 (14.3) 159–199

Total volume (m3 ha1) Pinus Picea Deciduous Range in total volume

400.6 (104.0) 240.8 (47.3) 155.4 (126.0) 4.3 (4.0) 307.8–537.4

301.2 (104.4) 192.9 (68.4) 92.6 (60.1) 15.6 (17.3) 157.5–430.6

168.6 (60.9) 140.0 (51.1) 19.5 (18.6) 9.1 (15.8) 82.9–334.1

254.4 (77.7) 132.0 (12.0) 79.5 (74.0) 37.2 (23.3) 171.2–360.7

281.0 (41.2) 149.4 (50.1) 88.2 (54.9) 37.3 (21.7) 210.9–400.3

180.4 (25.7) 161.0 (28.0) 11.5 (30.4) 5.4 (7.2) 145.0–215.5

Volume of living trees (m3 ha1) Pinus Picea Deciduous Range in total volume

333.3 (93.3) 189.4 (54.1) 140.7 (111.0) 3.2 (4.2) 239.0–449.8

254.9 (74.8) 152.5 (47.2) 87.7 (55.9) 14.7 (16.9) 142.9–329.9

161.3 (58.5) 134.3 (49.9) 18.9 (18.5) 8.1 (13.5) 81.0–320.0

183.7 (69.8) 85.5 (21.5) 70.6 (61.5) 27.7 (16.5) 93.9–276.2

223.3 (41.0) 116.0 (41.6) 80.6 (48.5) 26.7 (14.6) 143.7–335.5

158.4 (20.0) 145.0 (37.1) 10.1 (26.6) 3.3 (4.6) 137.2–197.1

Volume of dead trees (m3 ha1) Pinus Picea Deciduous Range in total volume

67.3 (15.2) 51.4 (11.5) 14.8 (16.5) 1.1 (1.1) 52.0–87.6

46.3 (34.1) 40.4 (28.6) 5.0 (7.9) 0.9 (1.1) 6.0–100.9

70.6 (20.0) 46.6 (16.7) 8.9 (18.1) 9.5 (7.2) 35.3–84.5

57.8 (25.4) 33.4 (24.7) 7.6 (8.8) 10.6 (10.0) 20.1–124.3

22.0 (23.0) 16.0 (14.8) 1.5 (3.8) 2.1 (5.1) 3.1–66.5

7.4 (5.2) 5.7 (4.0) 0.6 (0.9) 1.0 (2.4) 1.7–19.5

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Table 2 Differences in epiphytic lichen species richness between managed (M), selectively logged (S) and near-natural (N) stands within Ha¨me (H) and Kuhmo–Viena (KV) regions in boreal Finland-Russia. Generalized linear model fits are given for (i) total species richness, (ii) number of species in two lichen subgroups (i.e. macrolichens and calicioids) and (iii) number of species recorded on three different substrate types (i.e. Pinus, Picea and dead wood). Results are given for full models, i.e. when main factors and covariables are simultaneous included. The x2 (chi-square likelihood; or F-values in case of overdispersion) and its significance level show the additional effect of each variable in each model after first including all other variables (i.e. type III analysis of deviance). Significance codes for model coefficients and deviance (or variance) changes are given (*** <0.001; ** <0.01; * <0.05). The symbols z and y indicate variables with a significant effect (p  0.05) or a weakly significant effect (p = 0.05–0.10) on species richness when the two classes of variables (i.e. covariables and main factors, respectively) are tested separately. All species Coeff. (SE)

Subgroups

x

2

Macrolichens

Calicioids

Coeff. (SE)

x2

Coeff. (SE)

x2

1

Large trees (no. ha ) Pinus (104) Picea (104)

1.0 (1.2) 0.6 (0.5)

0.8 1.4

0.5 (1.5) 0.2 (0.7)

0.1 0.1

1.0 (3.7) 1.2 (1.3)

0.1 0.9

Small trees (no. ha1) Pinus (104) Picea (104)

2.4 (1.8) 2.2 (1.6)z

1.7 1.9z

0.5 (2.4) 0.01 (2.2)

0.04 <0.001

4.0 (4.9) 7.4 (4.3)z

0.7 2.9z

Impact (M as reference) S N

0.14 (0.08)z 0.24 (0.10)z*

6.4z* –

0.12 (0.11) 0.16 (0.13)

1.7 –

0.13 (0.26) 0.52 (0.27)z

3.4z –

Region (H as reference) KV

0.06 (0.09)

0.4

0.04 (0.12)

0.1

0.20 (0.31)

0.4

Impact:Region S:KV N:KV

0.36 (0.12)z** 0.25 (0.14)y

10.3z** –

0.23 (0.15) 0.15 (0.19)

2.2 –

1.06 (0.37)z** 0.58 (0.40)

9.2z** –

No. of species recorded on substrates Pinus Coeff. (SE)

Picea

x2

Coeff. (SE)

Dead wood F

1

Coeff. (SE)

F

(103)

2.3 (1.7)z

1.9z

(103) (103)

0.25 (0.33) 0.9 (0.7)

0.6 1.3

1

Large trees (no. ha ) Pinus (104) Picea (104)

0.9 (1.3) 0.3 (0.6)

0.5 0.2

2.3 (2.7) 0.002 (0.87)

0.8 <0.001

Small trees (no. ha1) Pinus (104) Picea (104)

2.7 (2.2) 0.4 (2.1)

1.4 0.03

2.0 (3.3) 2.7 (3.0)z

0.4 0.8z

Impact (M as reference) S N

0.06 (0.11) 0.15 (0.12)

1.5 –

0.20 (0.15)z 0.39 (0.17)z*

2.7z –

Impact (M as reference) S N

0.52 (0.15)z*** 0.66 (0.20)z**

7.3z**

Region (H as reference) KV

0.01 (0.11)

0.02

0.65 (0.21)z**

10.7z**

Region (H as reference) KV

0.15 (0.18)

0.7

Impact:Region S:KV N:KV

0.01 (0.14) 0.05 (0.17)

0.1 –

0.92 (0.25)z*** 0.72 (0.28)z*

8.1z*** –

Impact:Region S  KV N  KV

0.03 (0.22) 0.02 (0.25)

0.01

Five species were found only in the Ha¨me region, but usually at low frequencies (i.e. Hypogymnia farinacea in 19 stands, Lecanactis abietina in four stands, Lopadium disciforme in one stand, Chaenotheca stemonea in one stand, Ramalina farinacea in two stands). The NMDS ordination showed a division of the sample plots into two groups (Fig. 2). Managed stands formed one group and nearnatural and selectively logged stands the other. Species common to all stands, e.g. Bryoria fuscescens and Hypocenomyce scalaris, were located in the middle of the ordination plot. Differences in species composition between stands were mainly due to the occurrence of specific species. Pendulous species that grow mainly on conifers, and are considered to be associated with old-growth conditions (Hallingba¨ck, 1995; Esseen et al., 1996; Kuusinen and Siitonen, 1998), e.g. Alectoria sarmentosa, B. fremontii, B. nadvornikiana, Evernia divaricata and E. mesomorpha, were most abundant in selectively logged and near-natural stands and in the Kuhmo– Viena region. Species associated with Pinus and/or dead and charred wood also followed the same pattern; e.g. H. anthracophila and H. castaneocinerea, were usually located in less managed stands (see also below).

Dead wood (no. ha Standing Small trees Large trees Downed (logs)

)

The total species richness varied between 18 and 59 species per plot in the 62 stands studied; the overall average and the standard deviation was 36.3  9.7 species per plot. The average total species richness in the selectively logged stands (42.8  7.7) did not differ from that in the near-natural stands (41.4  4.7). But the average species richness in managed stands (27.4  4.7) was significantly lower than in the other two stand categories (x2 = 6.4, p = 0.042) although the effects of the covariables were taken into account (Table 2, Fig. 3). Most species richness estimates exhibited this pattern of differences in average values between stand categories. In addition, the interaction effect was significant (x2 = 10.3, p = 0.006); the average total species richness was also significantly higher in the Kuhmo–Viena (41.4  10.2) than in the Ha¨me region (31.0  5.3). The interaction between the main factors also showed a strong significant effect on the number of calicioids and the number of species recorded on Picea (Table 2, Fig. 3); the species richness was higher in the selectively logged and the near-natural stands in the Kuhmo–Viena region than in the other stands. The average numbers of species on dead wood were significantly higher in the selectively logged (21.3  5.2) and the nearnatural stands (25.8  4.6) than in the managed stands (11.2  4.9; F2,53 = 7.3, p = 0.002), but there was no difference between Ha¨me

S. Lommi et al. / Forest Ecology and Management 259 (2010) 883–892

889

Fig. 3. Relationship between three different estimates of lichen species richness and density of small understorey Picea trees (DBH <10 cm) per hectare in late-successional Pinus-dominated forests; i.e. managed (open squares), selectively logged (filled diamonds) and near-natural (filled circles) stands in boreal Finland. Note that different scales on the y-axis are used in the three diagrams.

Table 3 Multiple logistic regression models of the occurrence of the four Pinus-associated epiphytic and epixylic lichen species in managed (M), selectively logged (S) and near-natural (N) stands within the Ha¨me (H) and Kuhmo–Viena (KV) regions in boreal Finland-Russia. The x2 (chi-square likelihood) and its significance level show the additional effect of each variable in each model after first including all other variables (i.e. type III analysis of deviance). Significance codes for model coefficients and deviance changes are given (*** <0.001; ** <0.01; * <0.05). The symbols z and y indicate variables with a significant effect (p  0.05) or a weakly significant effect (p = 0.05–0.10) on species’ occurrence when the two classes of variables (i.e. main factors and covariables, respectively) are tested separately. The site occupancy (%) of each species is given within parentheses. Site occupancy Species on living trees

Species on dead wood

B. fremontii (61%) Coeff. (SE)

C. parvum (82%)

x2

Large trees (no. ha1) Pinus 0.002 (0.002)y Picea 0.0002 (0.001)

0.8z 0.02

Small trees (no. ha1) Pinus 0.002 (0.003) Picea 0.011 (0.005)z* Impact (M as reference) S 0.5 (1.4)z N 1.2 (1.6)z Region (H as reference) KV 3.8 (1.1)z***

Coeff. (SE)

H. anthracophila (19%)

x2

0.004 (0.008) 0.001 (0.001)

0.4 1.3

0.33 7.5z**

0.006 (0.004) 0.003 (0.004)

2.8 0.6

1.7z

0.04 (1.2) 1.2 (1.6)

1.1

17.8z***

1.9 (0.9)z*

5.2*

(16.3  7.8) and Kuhmo–Viena (19.4  7.1; F1,53 = 0.7, p = 0.401) in this respect. In addition, the average number of species recorded on Pinus did not differ between the near-natural (23.4  2.1), selectively logged (22.1  3.1) and managed stands (20.8  2.2; x2 = 1.5, p = 0.470) or between Ha¨me (21.5  2.4) and Kuhmo–Viena (22.0  3.1; x2 = 0.02, p = 0.890; Table 2, Fig. 3). Likewise, the average number of macrolichens did not differ between the stand categories or regions. When the effects of the covariables were tested separately, the density of small Picea (DBH <10 cm) was positively related to four of six lichen species richness estimates: (i) the total species richness (x2 = 24.0, p < 0.001), (ii) the number of calicioids (x2 = 19.7, p < 0.001), (iii) the number of species recorded on Picea (F1,57 = 8.9, p = 0.004), and; (iv) the number of species recorded on deadwood (F1,57 = 25.4, p = 0.001; Table 2, Fig. 3). When the data from only the selectively logged and near-natural stands were used, region alone had a nearly significant effect on the total species richness (x2 = 3.0, p = 0.081); the number of species tended to be higher in the Kuhmo–Viena than in the Ha¨me region. Near-natural stands tended to host higher numbers of species recorded on Picea than the selectively logged stands (F1,30 = 4.5, p = 0.043). In addition, the interaction between the main factors remained nearly significant in the model for the number of species recorded on Picea (F1,30 = 3.7, p = 0.064).

H. castaneocinerea (39%)

x2

Coeff. (SE)

x2

Dead wood (no. ha1) Small trees 0.003 (0.013) Large trees 0.003 (0.003)

0.1 0.9

0.005 (0.013) 0.004 (0.003)

0.2 1.3

Logs

0.1

0.016 (0.008)y*

5.6y*

3.2y

0.8 (1.0) 2.6 (1.3)z

4.9z

Coeff. (SE)

0.003 (0.007)

Impact (M as reference) S 2.0 (1.2)z N 1.4 (1.5) Region (H as reference) KV 0.5 (0.9)

0.3

1.4 (0.8)

3.1

The density of small Picea had a nearly significant effect only on the number of species recorded on Picea (x21;32 ¼ 3:1, p = 0.080), but still only while not including the main factors in the model. In the logistic regression models of Pinus-associated species occurrence, the effect of local human impact was nearly significant in the model for H. castaneocinerea (x2 = 4.9, p = 0.085), while the effects of the covariables were significant in the models for B. fremontii and H. castaneocinerea (x2 = 5.6–7.5, p = 0.006–0.018; Tables 3 and 4). In addition, the effect of region remained significant in the models describing the occurrence of B. fremontii and C. parvum (x2 = 5.2–17.8, p = 0.022 and <0.001). 4. Discussion 4.1. Importance of stand-level factors The lichen communities of stands selectively logged in the past (in the early 20th century) were as species-rich as the communities in the near-natural, unlogged stands, for at least two reasons. Firstly and most likely past selective loggings have been light, removing only relatively small amounts of timber. In the absence of subsequent human intervention, the development of stand structures has converged with that of unlogged stands (Lilja and Kuuluvainen, 2005). For example, Rouvinen et al. (2002) found that

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890

Table 4 The number of Pinus-dominated forest stands investigated and the frequency of occurrence (%) of four epiphytic lichen species across a gradient in human impact and two geographical regions. Bryoria fremontii and Calicium parvum are known to mainly grow on living Pinus trees (branches and bark, respectively) while both species of Hypocenomyce are known to mainly grown on charred, dead standing Pinus wood. Frequency of occurrence (%) No. of stands

‘‘Species on living trees’’

‘‘Species on dead wood’’

B. fremontii

C. parvum

H. anthracophila

H. castaneocinerea

Impact Managed Selectively logged Natural

25 28 9

28 82 89

84 79 89

8 29 22

28 36 78

Region Ha¨me Kuhmo–Viena

30 32

30 91

73 91

20 19

40 38

Total

62

61

82

19

39

the coarse deadwood characteristics often did not differ between selectively logged and near-natural old Pinus-dominated stands. Secondly, the stands classified as near-natural may actually have been affected by some type of human intervention that was not detected (Uotila et al., 2001). This may be the case, especially in the Ha¨me region, where forests have been used more intensively and for a longer time than in the Kuhmo–Viena region. The differences in species richness between stands were mainly due to variation (i) within specific lichen species subgroups, including crustose lichens such as the calicioids, and (ii) among lichens growing on specific substrates, such as Picea and deadwood (cf. Table 2, Fig. 3). Thus, the variation in species richness was not primarily due to the variation in species richness among macrolichens, and – somewhat surprisingly – not to the variation in the number of species recorded on Pinus (cf. Table 2, Fig. 3). This suggests that many macrolichens, like most species found on Pinus, are fairly resistant to habitat alterations induced by forestry practices. However, as the results also demonstrate, analyses focusing on species richness may mask important differences among species in their vulnerability to such changes (Nascimbene et al., 2007; Rogers and Ryel, 2008). The probability of occurrence of individual Pinus-associated species among both macrolichens and crustose lichens (e.g. B. fremontii, Hypocenomyce species) varied significantly not only along the gradient in local human impact, but also between the two study regions (cf. Fig. 3, Tables 3 and 4). The strong relationship detected between species richness and the density of small Picea indicates that understorey Picea have a positive effect on lichen diversity (Fig. 2, Table 2). Suppressed understorey Picea can be very old and thus provide a stable longlasting substrate for lichens. However, since understorey trees are commonly removed from managed stands, it is more likely that the density of small Picea is just an indicator (proxy) for the degree of human impact. Thus, both species richness and the density of small Picea increased with the overall increase in habitat complexity, e.g. increasing densities of large-diameter trees, deciduous trees and deadwood. These are the characteristics typical of selectively logged and near-natural stands (Lilja and Kuuluvainen, 2005). In fact, widespread species were generally recorded on understorey Picea, while rare species that mainly occurred in the selectively logged and near-natural stands were primarily found on other substrates, i.e. old trees and deadwood (SL, personal observation). Importantly, the selectively logged and near-natural stands appear suitable not only for Pinus-associated species but for several epiphytic lichens that are considered to be associated with oldgrowth habitats (Hallingba¨ck, 1995; Esseen et al., 1996; Kuusinen and Siitonen, 1998). For instance, A. sarmentosa, B. nadvonikiana, and E. mesomorpha had higher frequencies of occurrence in the

selectively logged and near-natural stands than in the managed stands (cf. Fig. 2). 4.2. Regional differences The most species-rich lichen communities were found in selectively logged and near-natural stands in the Kuhmo–Viena region (cf. Figs. 2 and 3, Table 2). Even when only the data from the selectively logged and near-natural stands were used, we still detected weak or significant effects of region, or the interaction factor, on species richness. The frequency of occurrence of several old-growth associated lichens (also the Pinus-associated B. fremontii and C. parvum) was higher in the Kuhmo–Viena than in the Ha¨me region (cf. Fig. 2, Tables 3 and 4). Some species were only recorded in Kuhmo–Viena (e.g. E. mesomorpha). These results indicate that additional factors, besides the stand-level effects of logging intensity and local substrate availability, may play a role in the distribution of lichens. In the Ha¨me region in south-central Finland, forest exploitation has been more intense and long-lasting than in the Kuhmo–Viena region. An indication of this is that the proportion of old-growth forests in southern boreal Finland is currently less than 1% of the forested land (Virkkala et al., 2000), while large tracts of fairly intact natural or near-natural forest still remain in the border region of Finland and Russia. Species may therefore have been lost from Ha¨me due to longer periods of higher local risks of extinction in small, isolated forest patches affected by adverse edge effects. At the same time, local extinctions are less likely to be balanced against re-colonization due to the low connectivity (i.e. larger isolation) of suitable forest habitats (Pyka¨la¨, 2004). Poor dispersal and establishment are likely to limit the distribution of many epiphytic lichens (Sillett et al., 2000; Hilmo and Ott, 2002; Johansson, 2008). If population development of some species is limited by dispersal, then it may also partly explain the significantly lower number of lichen species recorded on Picea in Ha¨me than in Kuhmo–Viena. The importance of Picea has probably increased in the Pinus-dominated forests studied in both regions due to succession in the absence of fire. Postfire succession has probably been ongoing for the longest period in the Ha¨me region, where fire suppression has been intense (Lilja and Kuuluvainen, 2005). However, due to the low connectivity of potential propagule sources, the accumulation of old-growth-associated lichen species on Picea has been significantly lower in Ha¨me than in Kuhmo– Viena. Further, following the habitat fragmentation, species are likely to become extinct in the remaining isolated habitat patches even in the absence of further perturbations (Gu et al., 2002; Burnett et al., 2003). Considering the long lifetime and low turnover rates of

S. Lommi et al. / Forest Ecology and Management 259 (2010) 883–892

lichens, and the fact that modern forestry practices were initiated in Kuhmo–Viena region less than 50 years ago, it might be possible that the populations of several currently rare species are still in a transient state, destined to decline. This conclusion is supported by studies in the Kuhmo–Viena region, indicating that the occurrence of wood-inhabiting fungal species tracks the landscape changes with a noticeable time lag (Gu et al., 2002; Penttila¨ et al., 2006). In these studies, the historical record of the recent old-growth forest fragmentation in the Kuhmo–Viena region in general significantly explained the current species occurrences while the present landscape structure did not. Differences in climate may also play a role in the regional effects on species richness and composition. However, this appears less likely since the climate is relatively comparable between the regions and the study areas are located within the same vegetation zone (Kalela, 1961; Ahti et al., 1968). It appears unlikely that differences in geographical ranges among individual species could have substantially affected the patterns observed. The occurrence of the great majority of lichen species studied is not limited to a particular boreal region (Ahlner, 1948; Ahti, 1977). Although macroclimate and biogeography may explain the distribution of some species, it seems unlikely that these factors are responsible for the observed regional differences in lichen diversity. The same also applies to the potential effects of air pollution, because it markedly affects only the most sensitive species (Kuusinen et al., 1990). 4.3. Management implications Our results suggest that selectively logged, late-successional Pinus-dominated stands are valuable lichen habitats and should be taken into account, together with unlogged stands, when planning rehabilitation of old-growth-associated lichen species richness. But should we or how should we manage such forests? Since their past structure, dynamics and diversity were influenced by fires, cutting of subdominant tree species (i.e. Picea) or prescribed burnings are usually encouraged as adequate biodiversity conservation actions (e.g. Nilsson, 2005). However, our results point out that, particularly in landscapes where oldgrowth stands represent isolated habitats these treatments may cause local extinctions of rare lichen species. Therefore, such treatments need to be carefully planned, possibly based on inventories of lichen flora. Perhaps most preferably, managers should consider using fire outside remnant old-growth areas to avoid adverse effects on lichen species richness and to promote the regeneration of Pinus and to restore early-successional natural-like postfire habitats. Acknowledgements We thank Raimo Heikkila¨, director of the Friendship Park Research Centre in Kuhmo, for supporting the research, and Sergei Tarkhov and Boris Kashevarov from the Kostomuksha Nature Reserve for fieldwork support in the Vienansalo wilderness. The inhabitants of Venehja¨rvi Village, especially Santeri Lesonen, are acknowledged for their help with the practical arrangements. We are also grateful for the field work assistance from Ilona Oksanen, Vellamo Ahola, Riina Ala-Risku, Meri Ba¨ckman, Eeva-Riitta Gyle´n, Minna Kauhanen, Keijo Luoto, Marjaana Lindy, Mari Niemi, Anne Muola, Tuuli Ma¨kinen, Juho Pennanen, Timo Pulkkinen, Jani Juntunen, Pauli Juntunen, Eija Kallio, Jorma Kyllo¨nen, Marko Kalela, Anne Leppa¨nen and Matti Va¨lima¨ki. This research was financed by the Academy of Finland and is part of the Finnish Biodiversity Research Programme FIBRE (1997–2002). HB acknowledges a postdoctoral research grant from the Swedish Research Council Formas.

891

Appendix A List of the 31 crustose lichen species other than Calicioids used in the inventory. Lepraria species were mapped on generic level only. Arthonia incarnata Th.Fr. ex Almq. Arthonia leucopellaea (Ach.) Almq. Bacidia subincompta (Nyl.) Arnold Cliostomum leprosum (Ra¨s.) Holien & To¨nsb. Dimerella pineti (Ach.) Veˆzda Hypocenomyce anthracophila (Nyl.) P. James & G. Schneider Hypocenomyce castaneocinerea (Ra¨s.) Timdal Hypocenomyce scalaris (Ach. ex Lilj.) M. Choisy Icmadophila ericetorum (L.) Zahlbr. Lecanactis abietina (Ach.) Ko¨rber Lecidea erythrophaea Flo¨rke Lepraria spp. Lopadium disciforme (Flot.) Kullhem Loxospora elatina (Ach.) Massal. Micarea melaena (Nyl.) Hedl. Mycobilimbia carneoalbida (Mu¨ll. Arg.) Printzen Mycobilimbia epixanthoides (Nyl.) Printzen Mycoblastus affinis (Schaerer) Schauer Mycoblastus alpinus (Fr.) Kernst. Mycoblastus sanguinarius (L.) Norman Ochrolechia alboflavescens (Wulf.) Zahlbr. Ochrolechia androgyna (Hoffm.) Arnold Ochrolechia microstictoides Ra¨s. Parmeliella triptophylla (Ach.) Mu¨ll.Arg. Pertusaria amara (Ach.) Nyl. Pertusaria coccodes (Ach.) Nyl. Pertusaria ophthalmiza (Nyl.) Nyl. Phlyctis argena (Sprengel) Flotow Protopannaria pezizoides (G. Weber) P.M. Jo¨rg. & S. Ekman Rinodina turfacea var. cinereovirens (Vain.) H. Mayrhofer Varicellaria rhodocarpa (Ko¨rber) Th. Fr.

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