Linköping University | Department of Physics, Chemistry and Biology Master thesis, 60 hp | Biology programme: Physics, Chemistry and Biology Fall term 2020 and spring term 2021 | LITH-IFM-x-EX--21/3965--SE

How do saproxylic beetles differ in spruce (Picea abies) forests of different age?

A comparison between nature reserves and production forests, in county of Östergötland.

Rebecca Petersen

Examinor, György Barabas, IFM Biology, Linköpings universitet Supervisor, Nicklas Jansson, IFM Biology, Linköpings universitet

Table of contents

1 Abstract ...... 3

2 Introduction ...... 3

3 Material and methods ...... 5

3.1 Study sites ...... 5

3.2 Sampling design ...... 6

3.3 Sorting species ...... 8

3.4 Ecological variables ...... 8

3.4.1 Basal area ...... 8

3.4.2 Dead wood ...... 9

3.4.3 Vegetation cover ...... 10

3.4.4 Canopy openness ...... 10

3.5 Statistical analyses ...... 11

4 Results ...... 11

4.1 Differences between sites ...... 11

4.1.1 Sampling results ...... 11

4.1.2 Species composition ...... 14

4.2 Ecological variables ...... 15

4.2.1 Correlations ...... 15

4.2.2 Impact ...... 15

5 Discussion ...... 17

5.1 Differences between sites ...... 17

5.2 Ecological variables ...... 18

5.3 Improvements of management ...... 19

5.4 Conclusions ...... 19

5.5 Societal & ethical considerations ...... 19

6 Acknowledgment ...... 20

7 References ...... 21

8 Appendix ...... 25

2 1 Abstract Today, old growth forests are continuously decreasing, due to deforestation, threatening species to extinction. Species dependent on dead wood, different stages of decaying wood, large trees, and forest cover continuity have a particularly high risk of extinction, such as saproxylic beetle species. The aim of this study was to explore effects of forest management and some ecological factors on saproxylic beetles in spruce dominated forests, in County of Östergötland in Sweden. Sampling was done by mounting 175 window traps in 35 study sites of different age, around the county. Results showed that nature reserves had the highest number of species, individuals, and threatened species, while production forest, 15-25 years old, had the lowest. Production forests, 65-85 years old, had similarities in species composition with nature reserves, probably due to historical reasons. To some extent, these kinds of forests provide habitat for threatened species at a landscape level and could provide habitat for more threatened species in the future, with the right management. Quantity and quality of dead wood, basal area/ha, and vegetation cover increased species richness and number of individuals. Suggestions to generate a successful long-term conservation is to increase total amount of dead wood, improve diversity of dead wood, leave more large-sized trees during retention and a mixture of tree species in production forests. This will probably aid species dependent on later successional stages, increase vegetation complexity, habitat heterogeneity, and probably increase both number of individuals- and saproxylic beetle species in production forests in the future.

Keywords: Composition; Conservation management; County of Östergötland; Ecological variables; Forest management; Saproxylic beetle species; Species richness; Spruce forests.

2 Introduction Old growth forests are continuing to decrease, due to our growing population’s rising demand for forest products, leading to deforestation and conversion to production forests (Fox, 2000; Kulha et al., 2020; Paillet et al., 2010). The long period of intensive forest management has created production forests consisting of even-aged, even-structured trees of different successional stages, with less volume and a less diverse quality of dead wood compared to old growth forest (Koivula & Vanha-Majamaa, 2020; Similä et al., 2003). This is problematic since old growth forests provide ecosystem services, such as soil protection, air and water purification, wildlife habitat, noise control, various types of recreation, and carbon storage (Cannell, 1999; Huettl & Zoettl, 1992; Keith et al., 2014; Luyssaert et al., 2008). Carbon storage in production forests compared to old growth forests is a subject constantly up for debate, where some scientists have argued that production forests store more carbon than old growth forests when including both biomass and its use for biomaterials and bioenergy (Schulze et al., 2020). However, other scientists have argued that old growth forests store a much higher amount of carbon than production forests, working as a global carbon sink, potentially mitigating climate change (Kun et al., 2020; Luyssaert et al., 2008; Mildrexler et al., 2020; Rodríguez-Soalleiro et al., 2018).

3 Globally, boreal forests contribute to 33 % of Earth´s forested area, creating the largest terrestrial carbon source, and provides important habitat for a lot of forest-dependent species (Jacobsen et al., 2020). However, boreal forests are an important source of timber and pulp wood, causing deforestation which leads to habitat loss and fragmentation, generating a major threat to biodiversity (Aune et al., 2005; Kouki et al., 2001; Pohjanmies et al., 2017; Seibold et al., 2015) Today, species dependent on large trees, forest cover continuity, dead wood and different stages of decaying wood have a particularly high risk of extinction (Paillet et al., 2010; Seibold et al., 2015; Söderström, 1988).

In Sweden, human activities have changed the landscape on a large scale since beginning of 1930, for instance replacing old-growth forests with production forests (Björse & Bradshaw, 1998; Dahlström et al., 2006). Today, 8.7 % of Sweden’s forest area is formally protected forests, consisting of national parks, nature reserves, habitat protection areas, eco parks and Natura 2000 areas (Naturvårdsverket, 2020). In total, around 60 000 species exist in Sweden today, whereas 50 % are estimated to live in forests, and 50 % of all red listed species are estimated to live in forests, demonstrating that deforestation is a big threat to biodiversity (Eide et al., 2020; SLU Artdatabanken, 2020). However, only 1 % of forest landscape in Sweden have been identified as woodland key habitats (WKH), where red-listed species occur or may occur, most of those are small and isolated patches (Aune et al., 2005).

To aid forest-dependent species relying on dead wood for survival, forest companies in Sweden have been required to leave some dead wood in harvested stands, since the mid-1990s (Gustafsson et al., 2010; Jonsell & Weslien, 2003). However, the increase of dead wood in Swedish forests has been small and mostly depends on storm events, rather than dead wood retention (Jonsson et al., 2016; Kapusta et al., 2020). Generally, protected areas have a larger amount of dead wood (20.4 m3/ha) compared to the non-protected areas (7.9 m3/ha) (Sandström et al., 2015; Sveriges lantbruksuniversitet, 2020). Dead wood retention often consists of high stumps and some coarse woody debris (CWD), providing substrate for early-successional saproxylic species, and those saproxylic species adapted to natural disturbances, resulting in a higher survival of forest-dependent species than without retention (Gustafsson et al., 2010, 2020; Jonsell & Weslien, 2003; Lindhe & Lindelöw, 2004). However, since large-sized CWD (known to support rich communities of saproxylic species) are underrepresented in dead wood retention, more beetle species have been found in WKH than in retention areas (Djupström et al., 2008; Kapusta et al., 2020). Further, a significantly greater number of red-listed species have been found in WKH than in retention areas (Djupström et al., 2008).

Saproxylic beetles compose a significant part of the boreal forest biodiversity and play a key role in forest dynamics since they contribute to degradation of wood, nutrient cycling, and soil fertility (Grove, 2002; Hardersen & Zapponi, 2018; McGeoch et al., 2007). Although saproxylic beetles play an important role in forests, they are threatened by deforestation since abundance and richness of saproxylic beetles are dependent on quality and quantity of dead wood as well as abiotic conditions, such as canopy openness (Kozák et al., 2020; McGeoch et al., 2007; Seibold & Torn, 2018). Old-growth forests support a higher number of individuals and a higher species diversity of saproxylic beetles compared to production forests (Grove, 2002; Hardersen et al., 2020; Martikainen et al., 2000). Further, amount of logs and snags (standing and recumbent dead wood), especially log volume, significantly increases species richness of saproxylic beetles, while amount of stumps does not (Seibold & Thorn, 2018). In Sweden, 50% of all saproxylic species are associated with deciduous trees, 27% are found only on coniferous trees, and 11% are generalists occurring on both deciduous and coniferous trees (Dahlberg & Stokland, 2004). Approximately half of the saproxylic species appear on wood > 20cm, and 15% of all species occur on wood in late stages of decomposition (Dahlberg & Stokland, 2004).

4 In Sweden, the number of red-listed beetles has increased from 2015 to 2020 due to changing environmental conditions in both farmlands and forests (Eide et al., 2020). Of all red-listed species in Sweden, around 25% are saproxylic (Dahlberg & Stokland, 2004). Measures to save important species, such as saproxylic beetles, needs to be implemented before more species become extinct, affecting the entire ecosystem. A clear understanding of important habitat features for saproxylic beetles is needed to aid and facilitate conservation management (Hardersen et al., 2020). A management approach, such as the Swedish one, to conserve beetles in boreal forest landscapes including production forestry is largely untested (McGeoch et al., 2007). Therefore, the aim of this project is to explore the effects of forest management and ecological factors on saproxylic beetles, to contribute with valuable knowledge for both forestry and conservation management. Window traps were used to sample saproxylic beetles in spruce forests of nature reserves and production forests of different age, in the county of Östergötland. Simultaneously, measurements on ecological variables were done around each trap. With this information I tried to answer:

• How do saproxylic beetles differ between spruce forests in nature reserves and production forests of different age? • How much do environmental factors affect saproxylic beetles?

3 Material and methods Saproxylic beetles were sampled in their flying phase by window traps mounted at each study site, consisting of nature reserves and production forests of different ages, in the county of Östergötland. Saproxylic beetles were sorted out from sampled material and sent to specialists in identification of beetle species to estimate species composition and richness. Measurements on the ecological variables basal area, dead wood, vegetation cover, and canopy openness were taken around each trap. The ecological variables were compared to biomass, species composition, number of individuals, and richness of saproxylic beetles, to find out how and how much the environmental factors affected the saproxylic beetles.

3.1 Study sites I chose 35 spruce (Picea abies) dominated coniferous study sites for this study. Five were old nature reserves (Storpissan omberg, Lysings, Ycke, Säby västerskog, and Marielund), and six were new nature reserves (Göstrings, Åbobranterna, Stockmossen, Högboda, Hjälmstorpenäs, and Rödgölen). For the production forests six study sites were chosen for each age of plantation, 1-6 years old (clear-felled area), 15-25 years old, 35-45 years old, and 65-85 years old, in a distance of three kilometres from the nature reserves (Figure 1).

5

Figure 1. Map of where in the county of Östergötland each study site was situated. 1). Storpissan omberg. 2). Lysings. 3). Göstrings. 4). Åbobranterna. 5). Ycke. 6). Säby västerskog. 7). Stockmossen. 8). Högboda. 9). Hjälmstorpenäs. 10). Rödgölen. 11). Marielund. (Sources: Esri, DeLorme, HERE, TomTom, Intermap, increment P Corp., GEBCO, USGS, FAO, NPS, NRCAN, GeoBase, IGN, Kadaster NL, Ordnance Survey, Esri Japan, METI, Esri China (Hong Kong), swisstopo, MapmyIndia, and the GIS User Community).

3.2 Sampling design

I sampled saproxylic beetles in their flying phase by mounting five window traps in each of the 35 study sites. A total of 175 window traps were set up (Appendix 1). Each trap was placed in spots where the habitat was representative for the specific study site and placed at least 25 metres (m) from the locations border or other uncharacteristic habitat. Traps were often placed between two spruce trees and near dead wood. The area around each trap (4 m in diameter and 1.5 m in height) was cleared from bushes and tree twigs, to create a similar surrounding for each trap, and a good flying path for beetles. Each trap was set up by a wire tightened between the trees, and a transparent plexi-glass board hanging from the wire with a loaf pan underneath (Figure 2). The loaf pan was filled with a mix of water, propylene glycol (concentrated anti-freeze), methylated spirits, and dish soap. Glycol was to conserve insects who ended up in the loaf pan, dish soap was to eliminate surface tension, and methylated spirits was to prevent either animals or children from drinking the liquid. To inform people, a note was installed on a tree nearby each trap. To avoid animals destroying traps, a shred was mounted under the trap and a repellent was sprayed on it (methylated spirits).

6

Figure 2. Picture of a finished window trap, representing traps in new- and old nature reserves, as well as production forests in age 15-25 years old, 35-45 years old, and 65-85 years old.

This procedure was repeated for all traps, the only exception was traps mounted in clear cuts (Figure 3). In those areas, no living trees were available and therefore wooden sticks was used to hang the traps in. In the same areas, traps were strengthened from wind by attaching the loaf pan tight to a stick beneath with two steel wires.

Figure 3. Picture of a finished window trap, representing traps located in production forests 1-6 years old.

7 When emptying traps, the loaf pan was dissembled from the trap and the liquid was poured into a pot through a fine meshed strainer. All insects found in the strainer was further poured over to a can and conserved with concentrated propylene glycol. The liquid was then poured back into the loaf pan, which was mounted back on the trap. If there was only a small amount of liquid left or if the liquid was diluted by too much rainwater, the loaf pan was either concentrated with new glycol or refilled with new liquid.

All traps were mounted between 1-6 may and emptied a first time between 8-12 June and a second time between 13-18 July. Simultaneously as the second time the traps were emptied, each trap was disassembled.

3.3 Sorting species All traps were emptied twice, which resulted in a total number of 350 collected samples. The samples were stored in small plastic cans with concentrated propylene glycol. I sorted out beetles from each of these cans.

To sort out all beetles, I emptied the samples into a tray, which was filled with water to remove coniferous needles and leaves, making it easy to sort out the beetles. After sorting, I poured the beetles into a strainer, immersed them in ethanol, and held them tilted above the ethanol until there were five seconds between the drops, then I weighed them on a Sartorius M-prove scale. The weighed sample was poured back into a tray, and all beetles were sorted out. The removed beetles were added into a plastic screw cape tube (50 ml or 8ml) with ethanol, marked with site, trap, and a number (1-350) specific for that sample. The screw cape tube was sent to specialists in beetle identification (See acknowledgement).

The specialists identified most of the saproxylic beetles to species level, but some to genus level. All beetles were divided into red listed or not (according to Swedish red-list 2020), nature value indicators or not (if they are or have been red listed sometime between 1993-2020), and to functional groups (Appendix 2):

- Obligate saproxylic beetles = Beetles exclusively dependent on dead wood or wood- inhabiting fungi for development - Facultative saproxylic species = Beetles that may breed in other habitats but are associated with dead wood or wood-inhabiting fungi.

3.4 Ecological variables To measure if and how much ecological variables affected saproxylic beetles, measurements on basal area, dead wood, vegetation cover, and canopy openness were taken around every trap. Methods and equations for all measurements, except canopy openness, were in line with those from the National forest inventory (Riksskogstaxeringen, 2020), with a few modifications.

3.4.1 Basal area

Basal area/hectar (h) was calculated for trees 10cm or larger in diameter at breast heigh (dbh), and 1.3m or above in height, within a circle of 10m in radius from the position of the trap. Basal area/ha was also calculated for trees between 4-10cm in dbh, and 1.3m or above in height, within a circle of 3.5m in radius. Species and diameter at breast height were measured for each tree who fulfilled the terms. Basal area (B) for each tree was calculated from dbh: 휋 푩 = (푑푏ℎ ∗ 0.01)2 ∗ ( ) (1) 4

8 (∑푩푥) After calculating basal area for each tree, basal area/ha (G) was calculated as: 푮 = , ( 2 ) ℎ h was 0.0314 for trees within a circle of 10m in radius, and 0.003848 for trees within a circle of 3.5m in radius.

3.4.2 Dead wood

Snags and logs, with a height of 1m or more and a width of 5cm in dbh or more, was measured within a circle of 10m in radius from the traps. I recorded species of tree, and if the tree had a visible root or not. Each log was also assigned to a class between 1-5 depending on the stage of decay, classification was done by using a knife (Riksskogstaxeringen 2020).

1 Raw: Logs or snags with green leaves or coniferous needles, and with a raw cambium. 2 Hard: If 10 % of the log or the snag has decayed. 3 Somewhat decaying: If 11-25 % of the log or the snag has decayed. 4 Decayed: If 26-75 % of the log or the snag has decayed. 5 Very decayed: If 76-100 % of the log or the snag has decayed. If the tree had a visible root, it was assumed to be in full length, and in that scenario dbh was the only measurement in field. Therefore, height (H) of the tree was later estimated for each tree with an assumed full length, using Rune Ollas h25 height functions (Equation 3-4; Ollas, 1980). However, in those scenarios when the tree did not have a visible root, height of the tree was measured in field together with diameter at both ends of the tree.

Rune Ollas h25 height function (spruce trees)

푯 = 9.022 − 6.454 ∗ 퐿푂퐺10(푑푏ℎ) − 1.256 ∗ 21.5 + 1.613 ∗ 21.5 ∗ 퐿푂퐺10(푑푏ℎ) (3)

Rune Ollas h25 height function (pine- and deciduous trees)

푯 = 1.518 − 1.086 ∗ 퐿푂퐺10(푑푏ℎ) − 0.518 ∗ 21,5 + 1.086 ∗ 21,5 ∗ 퐿푂퐺10(푑푏ℎ) (4)

For trees without a visible root, diameter at breast height was estimated by using interpolation between the diameters at both ends of the tree. Because of an underestimation, due to a bigger taper on the top of the tree, the equation was multiplied with 1.15 to correct the underestimation. The estimated diameter at breast height was used to calculate volume dead wood (V) of that 푑푏ℎ 2 tree: 푽 = (휋 ∗ ( ) ∗ ℎ푒𝑖𝑔ℎ푡) ∗ 1.15 (5) 2

For trees with a visible root, volume of dead wood (V) for standing and recumbent trees was estimated by using “Näslunds mindre volymfunktioner för Södra Sverige”, with different equations for different types of trees (Equation 6, 7, 8; Näslund, 1947). The equation for birch (Betula) trees were used for all deciduous trees since they could be assumed to have equal characteristics.

Näslunds equation for spruce trees

0.01104 ∗ 푑푏ℎ2 + 0.01925 ∗ 푑푏ℎ2 ∗ ℎ푒𝑖𝑔ℎ푡 + 0.018158 ∗ 푑푏ℎ ∗ ℎ푒𝑖𝑔ℎ푡2 − 0.04936 ∗ ℎ푒𝑖𝑔ℎ푡2 (6) 푽 = 1000 Näslunds equation for pine trees

0.1072 ∗ 푑푏ℎ2 + 0.02427 ∗ 푑푏ℎ2 ∗ ℎ푒𝑖𝑔ℎ푡 + 0.007315 ∗ 푑푏ℎ2 ∗ ℎ푒𝑖𝑔ℎ푡2 푽 = (7) 1000

9 Näslunds equation for birch trees

0.1432 ∗ 푑푏ℎ2 + 0.008561 ∗ 푑푏ℎ2 ∗ ℎ푒𝑖𝑔ℎ푡 + 0.0218 ∗ 푑푏ℎ ∗ ℎ푒𝑖𝑔ℎ푡2 − 0.0663 ∗ ℎ푒𝑖𝑔ℎ푡2 (8) 푽 = 1000 The species, diameter, and height of all stumps within a circle of 10 m in radius from the trap was measured. Calculations for volume of dead wood (V) in stumps was the same as equations above, with the exception that stumpdiameter was transformed to dbh, since dbh is smaller than stumpdiameter: 풅풃풉 = (푠푡푢푚푝푑𝑖푎푚푒푡푒푟) ∗ 0.82 (9)

3.4.3 Vegetation cover

I divided vegetation cover into three layers (shrub layer, field layer, and bottom layer). Shrub layer consisted of Hazel (Corylus), Rowan (Sorbus), Raspberry (Rubus) and Rose bushes (Rosaceae). Field layer included Blueberry (Cyanoccus), Cowberry (Vaccinum vitis-ideae), Heather (Calluna vulgaris), Horsetail (Equisetum), Rockcap ferns (Polypodium), Rush family (Juncaceae), herbs, small- and broad grass, and the families Ferns, and Lycopodiophyta. Bottom layer included mosses and lichens. Shrub layer was measured within a circle of 10 m in radius from the trap, and both field- and bottom layer was measured within a circle of 5.6 m in radius from the trap. In all layers, coverage of each species or family were estimated from 1- 100 m2. If the coverage was less than 1 m2 it was counted as 0 m2 coverage.

The requirement to be counted as a bush and not a tree was a dbh under 5 cm, except for Rowan, which had to have a dbh under 2 cm according to Riksskogstaxeringen 2020. However, Juniper tree (Juniperus communis) were always counted as a bush (Riksskogstaxeringen, 2020).

3.4.4 Canopy openness

Canopy openness was measured using hemispherical photographs of forest canopies. A Nikon D90 camera with a Sigma EX DG 8mm (fisheye lens) was used for taking pictures, with the north direction on top of each photo. The package CIMES-FISHEYE were used to analyse and extract canopy openness from each photo.

The program ImageJ was used to process each picture. From using all colours (blue, green, and red), each picture was fragmented, and only the blue colour was used in the pictures (recommended in the CIMES-FISHEYE package). ImageJ also yielded a threshold-value for each photo.

Each processed picture and threshold-value was used in the core program (GFA) of the package CIMES-FISHEYE. GFA extracted gap fraction and gap size data from the digital image in BMP format. With given information from GFA, the program Canopy openness extracted a value for canopy openness.

10 3.5 Statistical analyses I used a generalized linear model (GLM) to analyse the relationship between dependent variables (biomass, species richness, and number of individuals) and forest type. The model was also used to analyse the relationship between the dependent variables and the independent variables (Basal area, dead wood, vegetation cover, richness of trees, canopy openness), to find out if the independent variables affected the dependent variables, and how they affected. Further, I used a principal component analysis (PCA) to describe how composition of saproxylic beetle species differed between different types of forest, how large of an impact each independent variable had, and to examine which forest type each variable leaned towards. All analyses were done in R version i386 4.0.2 using (package = “Tidyverse” and = “Vegan”).

Since GLM allows independent variables with distributions other than normal, it was a suitable method for this study (Faraway, 2016). However, GLM assumes that variables are uncorrelated with each other (Faraway, 2016). Therefore, PCA was a suitable compensatory method, since PCA is independent of correlation between variables (Abdi & Williams, 2010).

4 Results 4.1 Differences between sites 4.1.1 Sampling results

The highest amount of dead wood was found in nature reserves and old reserves, while the lowest amount was found in production forests 15-25 years old (Figure 4a). Additionally, the highest variety of dead wood was found in nature reserves and old reserves, while all production forests had a very low variety of dead wood (Figure 4b, 4c, 4d).

Figure 4. Diversity of dead wood in different types of forests. Data was log-transformed. New = Nature reserve, Old = old nature reserve. A). Total volume of dead wood. B). Volume of snags and logs. C). Volume of different decaying stages of dead wood. D). Volume of different sizes of dead wood.

11 From the 350 samples, a total of 74.493 individuals and 478 saproxylic beetle species were sampled, whereas 329 was obligate-, 138 was facultative saproxylic, 24 was red listed, and 75 were classified as nature value indicators (Appendix 3). The sampled species Latridius porcatus, was a newly discovered species in the county of Östergötland (Appendix 3). The highest number of red-listed-, obligate-, and facultative saproxylic beetle species were found in nature reserves and old reserves, while the lowest number were found in production forest 15- 25-, and 35-45 years old (Table 1).

Table 1. Average number of red-listed saproxylic beetles sampled, nature value indicators, obligate saproxylic beetles sampled, and facultative saproxylic beetles sampled within the different forest types.

Production forest Nature reserve Clear-cut 15-25 35-45 65-85 New Old Red-listed 2 0.33 0.33 2.6 3.8 3.6 Nature value 6 2.6 4 10.5 12.5 13 indicators Obligate 81 53.8 67 91 103 97.6 Facultative 33.8 30.5 41.7 55.5 62 47.8

New nature reserves and old nature reserves had the highest number of species and individuals, while production forests 15-25 years old had the lowest amount (Figure 5). Comparing production forests 15-25 years old (intercept) to the other types of forest, nature reserves, old reserves, and production forests 65-85 years old had a higher number of species and individuals (Table 2). Further, clear-cuts had less species and individuals than the intercept, however, for species the result was not significant (Table 2).

A B

C D

Figure 5. A & C). Total number of saproxylic beetle species and number of individuals grouped by area and forest type. B & D). Total number of nature value indicator species and number of individuals grouped by area and forest type.

12 Table 2. Results from GLM with number of saproxylic species and individuals as the dependent variables and type of forest as factor. The intercept represents 15-25 years old.

Species Individuals Estimate Std. Error P-value Estimate Std. Error P-value 13.88 0.53 0.000 Intercept 10.05 2.04 0.000

-3.80 0.62 0.000 Clear-cut -2.29 2.40 0.341

0.37 0.06 0.000 35-45 0.51 0.27 0.059

1.83 0.22 0.000 65-85 2.04 0.86 0.018

1.73 0.15 0.000 Nature reserve 1.92 0.60 0.014 11. 08 0.39 0.000 Old reserve 5.91 1.44 0.000

Comparing biomass of saproxylic beetles between production forests 15-25 years (intercept) and other types of forest, clear-cuts had the highest amount (Figure 6; Table 3). However, both new nature reserves and old nature reserves could potentially have had a higher biomass than the intercept (Table 3).

Table 3. Results from GLM with biomass of saproxylic beetles as the dependent variable and type of forest as factor. The intercept represents production forests 15-25 years old.

Biomass Estimate Std. Error P-value

Intercept 745.74 539.80 0.197 Clear-cut 1321.87 571.55 0.043 35-45 282.16 156.52 0.101 65-85 406.69 243.53 0.125 Nature reserve 404.84 202.03 0.072 Old reserve 484.98 309.39 0.088

Figure 6. Total amount of biomass of saproxylic beetles for each forest type. Data is log-transformed (log (K)).

13 4.1.2 Species composition

Clear-cuts had a different composition of saproxylic beetle species than other forest types. Species composition in production forests 65-85 years old had some similarities with composition of nature reserve (Figure 7A). Further, six of the species with highest absolute value had a relatively strong connection to nature reserves, while three of the species had a strong connection to clear cuts (Figure 7B).

A B

Figure 7. A PCA of saproxylic beetles in different forest types. Red plusses stand for species, and black or grey dots stand for composition of species in each site. PC1 explains 30% of the variation and PC2 explains 11% of the variation. Black circles are composition of species in a specific forest type. A). Composition of saproxylic beetle species for different forest types. Data used in this analysis was log-transformed (log(1+k)). B). Occurrence of the 10 saproxylic beetle species with the highest absolute value. Data used in this analysis was standardized (scale = TRUE), to give all species the same influence independent of number of individuals. The percentage value presented next to the species name is proportion of individuals existing in specific type of forest.

For nature value indicator species, nature reserves and old reserves leaned mostly towards the PC1-axis, and old reserves differed in composition of species compared to the others (Figure 8A). Most species with highest absolute value were found in old reserves (Figure 8B).

A B

Figure 8. A PCA of nature value indicator species in different forest types. Red plusses stand for species, and black or grey dots stand for composition of species in each site. PC1 explains 36% of the variation and PC2 explains 11% of the variation. Black circles are composition of species in a specific forest type A). Composition of nature value indicator species for different forest types. Data used in this analysis was log-transformed (log(1+k)). B). Occurrence of the 10 nature value indicators, with more than 1 individual, with the highest absolute value. Data used in this analysis was standardized (scale = TRUE), to give all species the same influence independent of number of individuals. The percentage value presented next to the species name is proportion of individuals existing in specific type of forest. 14

4.2 Ecological variables 4.2.1 Correlations

Quantity and quality of dead wood, basal area/ha and vegetation cover had a positive correlation for both number of saproxylic beetle species and individuals (Figure 9). Decaying stage 5 had a negative correlation with number of individuals but a positive correlation with species richness (Figure 9).

Figure 9. Correlation between dependent variables (biomass, species richness and number of individuals) and independent variables. Points represent T-value for biomass, and Z-value for species richness and number of individuals, from the GLM analysis. A point outside of the dotted lines represents a p-value <0.05, and a probable conjunction between the dependent variable and the independent variable.

4.2.2 Impact

For all saproxylic beetle species, canopy openness, amount of stumps, coverage of shrub-, bottom-, field layer, richness of both small and large living trees, amount of logs, and basal area/ha of large trees was the variables impacting species composition (Figure 9). Canopy openness, amount of stumps, coverage of field-, and shrub layer increased towards clear-cuts (Figure 9). Logs increased towards old reserves and production forests 35-45 years old (Figure 9).

15

Figure 9. A PCA of saproxylic beetles in different types of forest. Red plusses stand for species, and black dots stand for composition of species in each site. PC1 explains 30% of the variation and PC2 explains 11% of the variation. Size of arrow indicate how much each variable impact composition of saproxylic beetles, and direction of arrow indicate in which direction they have the largest impact. The variables shown are those significant from the environmental fit-test (Envfit()) in R.

Amount of dead wood (in total and in different decaying stages) indicated an increase towards old reserves, except for amount of dead wood in decaying stage 1, which indicated an increase towards nature reserves and production forests 65-85 years old (Figure 10).

Figure 10. A PCA of saproxylic beetles in different types of forest. Red plusses stand for species, and black dots stand for composition of species in each site. PC1 explains 30% of the variation and PC2 explains 11% of the variation. Size of arrow indicate how much each variable impact composition of saproxylic beetles, and direction of arrow indicate in which direction they have the largest impact. The variables shown are not significant from the environmental fit-test (Envfit()) in R.

16 5 Discussion Results from this study indicate that new nature reserves and old nature reserves provide habitats for a higher number of saproxylic beetle species and individuals, as well as a higher number of threatened species than production forests in all stages. Species composition of saproxylic beetles was somewhat similar between production forests 65-85 years old and nature reserves. This indicates a current presence of valuable habitats for threatened species in production forests 65-85 years. These stands could provide habitat for more threatened species in the future if allowed to grow older, with the right management. Moreover, composition of saproxylic beetles was completely different in clear-cuts, confirming a different habitat in clear- cuts. However, there were some species, including threatened species, only sampled in clear- cuts, which indicate the importance of the habitat. Thus, note that species sampled from the window traps in this study, only show occurrence of species and not if the species originated from dead wood within the site. Further, quantity and quality of dead wood, and canopy openness, probably increased number of individuals but might have decreased number of species and biomass. On the other hand, vegetation cover, basal area and type of dead wood seems important for a higher number of species and a higher biomass.

5.1 Differences between sites Several earlier studies have found that old-growth forests support a higher number of individuals, and a higher species diversity of saproxylic beetles compared to production forests (Grove, 2002; Hardersen et al., 2020; Martikainen et al., 2000; Stenbacka et al., 2010). As expected, this study found a similar pattern which further strengthens this theory (Figure 5). Some studies believed that a higher number of beetle species was to be found in areas with large-sized CWD (Djupström et al., 2008; Kapusta et al., 2020), and maybe that could also be true here, since new nature reserves and old nature reserves had the highest number of large- sized CWD (Figure 4). Additionally, Djupström et al. (2008) found a higher number of red- listed species in WKH than in retention areas. Seeing that nature reserves and old reserves had a higher number of red-listed species than production forests in this study, that theory could also be confirmed (Table 1).

Species composition was somewhat similar between production forests 65-85 years old and new nature reserves. Such resemblances have been reported in earlier studies (Albert et al., 2021; Stenbacka et al., 2010). Clearly, number of individuals, richness-, and composition of species have not been considerably reduced due to forestry, therefore, they are important for conservation of saproxylic beetle species. Stenbacka et al. (2010) believe that the similarities depend on matching diversity of dead wood at a landscape level, since Similä et al. (2003) argued that the diversity of dead wood was more important for beetle assemblage composition than the amount of dead wood. However, in this study, diversity of dead wood was not similar between the two types of forests (Figure 4b, 4c, 4d). Albert et al., (2021) thought that negative effects of production forests might partly be alleviated if the planted trees had native congeners or traits that are like those from native tree species. Production forests 65-85 years old in this study, have the same historical background as the nature reserves but are slightly younger. As Albert et al., (2021) argued, the relatedness between the forests probably alleviates the negative effects and generate the similarities of species composition between production forests 65-85 years old and new nature reserves. However, one need to remember that these forests are continuously logged, consequently, measures to improve conditions after logging are needed to generate a successful long-term conservation.

17 Production forests 15-25 years old and production forests 35-45 years old had a low amount of saproxylic beetle species, number of individuals, as well as a low volume- and diversity of dead wood (Figure 4:5). Considering these results, how will these types of forest be when reaching their oldest age class? Will they have similar species composition and ecological factors as today’s production forests 65-85 years old? Without a similar historical background as nature reserves and production forests 65-85 years old, together with the low numbers and amounts, these forests will probably not be able to provide habitat for many- or threatened species during their felling maturity. To improve future conditions, one should plant a mixture of tree species, possibly increasing vegetation complexity and habitat heterogeneity, which will have a positive effect on the diversity of saproxylic beetle species and most animal taxa (Lassau et al., 2005; Parisi et al., 2020; Tews et al., 2004).

Results showed a low number of individuals, saproxylic beetle species in clear-cuts, as well as a different species composition. This is the same results as in Stenbacka et al. 2010, which argued that the differences depended on the reduced amount of dead wood, and the changed habitat/microclimatic conditions. My results indicate on the same thing, since clear-cuts had a lower amount of dead wood, a lower amount of large-sized dead wood, and a lower diversity of decaying dead wood than nature reserves and production forests 65-85 years old (Figure 4). Previous studies have found that stumps and slash (piles of dead wood) provide substrates for early-successional saproxylic beetles, that are good dispersers and use fresh substrate, and for those adapted to natural disturbances (Gustafsson et al., 2010, 2020; Jonsell & Weslien, 2003; Lindhe & Lindelöw, 2004; Stenbacka et al., 2010). However, Jonsell et al. (2007) found that clear-cuts could provide habitat for a diverse fauna of saproxylic beetle species, as well as red- listed species. Additionally, in this study, several red-listed species were sampled from clear- cuts, and some were only found there. Thus, a clear-cut with suitable substrates could be beneficial for saproxylic beetles, which is why dead wood management on clear-cuts is of great importance. Further, most of the red-listed species found in clear-cuts were connected to deciduous trees, for example Xyletinus pectinatus, Cerylon deplanatum, and Xylotrechus antilope, showing the importance of a mixture of tree species but also leaving deciduous trees during retention.

5.2 Ecological variables Results from GLM analysis show that a higher quantity and quality of dead wood, a higher basal area/ha, and vegetation cover increase saproxylic beetle species and individuals. This was expected as previously studies have found the same pattern ((Kozák et al., 2020; McGeoch et al., 2007; Seibold & Torn, 2018). However, results from this study contradicts Seibold & Thorn (2018), who found that amount of logs and snags significantly increased species richness of saproxylic beetle species while amount of stumps did not. Instead, this study found that logs, snags, and stumps increased species richness. Probably, the differences depended on measurements. For example, they used number of stumps instead of volume, which I choose for this study.

Results from PCA analysis indicates that amount of dead wood and decaying stages of dead wood lean towards old reserves, as well as the opposite for canopy openness. These results might imply that those variables are typical for an old nature reserves and that they are important for some saproxylic beetle species and individuals not existing in production forests. Further, these results possibly fortify that species dependent on forest cover continuity, dead wood, and different stages of decaying wood have a particularly high risk of extinction (Paillet et al., 2010; Seibold et al., 2015; Söderström, 1988).

18 5.3 Improvements of management Based on my results, I recommend increasing total amount and improving diversity of dead wood in production forests, to improve survival of saproxylic beetle species. Further, a higher number of trees in late decaying stages, and large-sized trees should be retained, to aid species dependent on later successional stages rather than earlier successional stages, and to maintain potential for large decaying wood in the future (Similä et al., 2003). Moreover, future plantations should contain a mixture of tree species, to increase vegetation complexity and habitat heterogeneity (Lassau et al., 2005; Parisi et al., 2020; Tews et al., 2004). This will not only improve survival rate of saproxylic beetles, but will also promote important ecosystem services, such as soil protection, air and water purification, noise control, various types of recreation, and carbon storage (Cannell, 1999; Huettl & Zoettl, 1992; Keith et al., 2014; Luyssaert et al., 2008).

A way for forestry management to achieve these goals would be to use a continuous cover forestry model instead of a forestry with regeneration through clear-felling. This model would naturally create an uneven-aged forest with different types of tree species, and dead wood in different sizes, proven to increase number of saproxylic beetle species. In addition, the model could naturally and continuously increase total amount of dead wood, as well as wood in different decaying stages, since some trees might be a victim in storm events, and those trees will have different sizes but could also be in different decaying stages.

5.4 Conclusions Nature reserves provided habitat for a higher number of saproxylic beetle species and individuals than production forests, probably because they comprised substrates important for species dependent on both late- and early successional stages. To some extent, production forests 65-85 years old provide habitat for threatened species at a landscape level and could provide habitat for more threatened species in the future, with the right management or if left unaffected. Therefore, they are important for conservation management. The similarities in species composition between nature reserves and production forests 65-85 years old, are probably due to historical reasons i.e., originating from a period when many forests were more open and grazed, a period before spruce forests were planted. Quantity and quality of dead wood, basal area/ha, and number of small trees are ecological variables important to increase number of saproxylic beetle species and individuals. Therefore, to generate a successful conservation in a long-term, both an increase in total amount of dead wood, and diversity of dead wood together with a mixture of tree species needs to be improved in production forests.

5.5 Societal & ethical considerations Purpose of this study was to explore the effects of forest management and ecological factors on saproxylic beetles, to perhaps contribute with new and valuable knowledge for both forestry- and conservation management. Measures to save saproxylic beetle species is important to save entire ecosystems, since they have an important role contributing with degradation of wood, nutrient cycling, and soil fertility.

19 Sampling of species in this study, was conducted by killing all organisms that ended up in the trap. Another way of sampling species was difficult to conduct as saproxylic beetle species are a versatile category of species, where some crawl while others fly. Moreover, identification of saproxylic beetle species would be almost impossible with a living beetle, since small details could be the difference between some species, only seen with a microscope. Further, number of individuals not collected far outweighs the number of individuals that was collected in this study. Therefore, to save saproxylic beetles in the long-term, and by that, saving important ecosystems, some individuals need to be sacrificed.

6 Acknowledgment I would like to show my gratitude to my supervisor Nicklas Jansson for his guidance, mentoring, coordination of all people included, and his help with choosing location, collecting samples, as well as details in the report. I thank my co-supervisors Karl-Olof Bergman, Lars Westerberg, and Per Milberg for their help with the statistical and analytical part. I thank my co-worker Angelica Weisner for her help with mounting traps and collecting data.

I appreciate all efforts from Stanislav Snäll and Gunnar Sjödin for species identification of the entire sampled material, and I also appreciate the help from Stanislav with mounting all traps. I Thank Johan Bergstedt for his guidance and help with calibrating myself to do measurements the same way as Riksskogstaxeringen do. I appreciate the efforts from Bertil Westerlund to help me with calculation of ecological variables.

This study was funded by County administration board of Östergötland, Linköpings university, Holmen, Boxholms skogar, Stiftet, Sveaskog, Baroniet, the Entomological organisation of Östergötland, and the Entomological organisation of Uppland. In addition, Eva Siljeholm, Jens Johannesson and Mikael Burgman from County administration board of Östergötland provided several potential nature reserves to my report, and therefore I am grateful. I am also grateful to Holmen, Boxholms skogar, Stiftet, Sveaskog, and Baroniet for providing potential spruce dominated production forests in different ages on their properties, close to the nature reserves.

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24 8 Appendix

A B

C D

25 E F

G H

26 I J

K

Appendix 1. Maps of where in the locations each trap was placed. A). Cluster around Göstrings nature reserve. B). Cluster around Åbobrantens nature reserve. C). Cluster around Stockmossens nature reserve. D). Cluster around Högbodas nature reserve. E). Cluster around Hjälmstorpenäs nature reserve. F). Cluster around Rödgölens nature reserve. G). Storpissan. H). Lysings. I). Ycke. J). Säby. K). Marielund. (Sources: Esri, DeLorme, HERE, TomTom, Intermap, increment P Corp., GEBCO, USGS, FAO, NPS, NRCAN, GeoBase, IGN, Kadaster NL, Ordnance Survey, Esri Japan, METI, Esri China (Hong Kong), swisstopo, MapmyIndia, and the GIS User Community).

27 Appendix 2. Total number of individuals sampled for each saproxylic beetle species red-listed 2020 during the entire period, divided into different types of forests. Species only existing in one type of forest are highlighted in yellow.

Managed forest Nature reserve Red-listed Total status number of 2020 Species Clear-cut 15–25 35–45 65–85 New Old individuals NT Platysoma lineare 0 0 0 0 0 1 1 NT Liodopria serricornis 0 0 0 1 4 15 20 NT Amphicyllis globiformis 0 0 2 4 4 5 15 VU Carphacis striatus 0 0 0 20 41 9 70 NT Thamiaraea hospita 0 0 0 7 9 0 16 NT Ampedus praeustus 0 0 0 0 1 0 1 VU Drapetes mordelloides 1 0 0 0 0 0 1 NT Xyletinus pectinatus 1 0 0 0 0 0 1 NT Stagetus borealis 5 1 0 1 1 1 9 NT Rhizophagus picipes 0 0 0 0 1 0 1 NT Silvanus bidentatus 0 0 0 2 0 4 6 NT Triplax rufipes 1 0 0 0 1 1 3 NT Cerylon deplanatum 2 0 0 1 0 0 3 NT Corticaria interstitialis 4 8 0 1 1 0 14 NT Cis rugulosus 0 0 1 0 0 0 1 NT Mycetophagus decempunctatus 0 0 0 2 0 0 2 NT Mycetophagus fulvicollis 0 0 0 1 0 1 2 NT Orchesia fasciata 0 0 0 0 1 0 1 NT Zilora ferruginea 0 0 0 0 1 2 3 VU Tragosoma depsarium 0 0 0 0 1 0 1 NT Pachyta lamed 2 0 0 0 0 0 2 NT Obrium brunneum 0 0 0 0 1 0 1 NT Xylotrechus antilope 6 0 0 0 0 0 6 NT Pissodes harcyniae 0 0 0 1 2 0 3

Total number of individuals 22 9 3 41 69 39

Total number of species 8 2 2 11 14 9 Appendix 3. Total number of individuals sampled for each saproxylic beetle species during the entire period, divided into different types of forests. Further, information about red listed-status, facultative (F) saproxylic species, and obligate (O) saproxylic species are included.

Red- Nature listed conserv Catalogus status ation Saproxylic number Total number 2020 species class 1995 Species of individuals LC O 151 Tachyta nana 1 LC F 344 Dromius agilis 4 LC F 349 Dromius quadrimaculatus 1 LC F 644 Sphaerites glabratus 90 LC * O 652 Plegaderus caesus 1 LC F 672 Gnathoncus nannetensis 34 LC F 674 Gnathoncus buyssoni 11 LC F 678 Dendrophilus pygmaeus 1 LC O 680 Paromalus flavicornis 4 LC * O 681 Paromalus parallepipedus 8 LC O 702 Platysoma angustatum 1 NT * O 703 Platysoma lineare 1 LC * O 729 Ptenidium turgidum 1 LC O 842 Anisotoma humeralis 245 LC O 843 Anisotoma axillaris 121 LC O 844 Anisotoma castanea 166 LC O 845 Anisotoma glabra 102 LC O 846 Anisotoma orbicularis 39 NT * O 847 Liodopria serricornis 20 NT * F 849 Amphicyllis globiformis 15 LC F 852 Agathidium varians 16 LC * F 854 Agathidium mandibulare 1 LC F 857 Agathidium rotundatum 1 LC F 858 Agathidium confusum 12

2 LC * F 860 Agathidium nigrinum 11 LC F 863 Agathidium nigripenne 74 LC F 865 Agathidium seminulum 26 LC F 866 Agathidium laevigatum 40 LC O 868 Agathidium pisanum 4 LC F 942 Nevraphes coronatus 1 LC O 948 Stenichnus godarti 17 LC F 950 Stenichnus bicolor 1 LC * O 952 Microscydmus nanus 3 LC F 994 Gabrius splendidulus 99 LC F 1016 Bisnius fimetarius 108 LC F 1020 Philonthus politus 84 LC F 1021 Philonthus succicola 6 LC F 1022 Philonthus addendus 7 LC O 1030 Bisnius subuliformis 4 LC * F 1101 Quedius dilatatus(1 3 LC F 1105 Quedius mesomelinus 17290 LC O 1106 Quedius maurus 9 LC F 1107 Quedius cruentus 7 LC F 1117 Quedius scitus 8 LC F 1118 Quedius xanthopus 521 * O 1121 Quedius plagiatus 3 LC O 1162 Nudobius lentus 8 LC O 1179 Atrecus longiceps 7 LC O 1330 Bibloporus bicolor 24 LC F 1340 Euplectus piceus 1 LC F 1349 Euplectus karsteni 4 LC O 1350 Euplectus mutator 3 LC F 1382 Tyrus mucronatus 4 LC F 1395 Proteinus brachypterus 4 LC F 1407 Acrulia inflata 7

3 LC F 1412 Phyllodrepa melanocephala 35 LC F 1416 Phyllodrepa (Hapalaraea) floralis 6 * * O 1419 Phyllodrepa linearis 4 LC F 1430 Omalium rivulare 97 LC O 1443 Phloeostiba plana (Phloeonomus planus) 22 LC O 1444 Phloeostiba lapponica 1 LC O 1446 Phloeonomus sjobergi 2 LC F 1448 Xylodromus depressus 1 LC F 1459 Deliphrum tectum 1 LC O 1494 Scaphidium quadrimaculatum 8 LC F 1495 Scaphisoma agaricinum 58 LC O 1496 Scaphisoma inopinatum 6 LC O 1500 Scaphisoma boreale 31 LC O 1501 Scaphisoma assimile 3 LC F 1538 Oxytelus laqueatus 3 VU * O 1623 Carphacis striatus 70 LC F 1624 Lordithon thoracicus 1 LC F 1625 Lordithon exoletus 2 LC F 1628 Lordithon lunulatus 295 LC F 1633 Bolitobius inclinans (=Parabolitobius) 1 LC F 1634 Sepedophilus littoreus 75 LC * F 1640 Sepedophilus bipunctatus 1 LC F 1688 Aleochara sparsa 40 LC F 1689 Aleochara stichai 12 LC F 1698 Aleochara moerens 4 LC F 1734 Oxypoda recondita 1 LC F 1735 Oxypoda alternans 107 LC F 1773 Dexiogyia forticornis 1 LC * F 1781 Haploglossa gentilis 4 LC F 1782 Haploglossa villosula 49 LC F 1785 Haploglossa marginalis 3

4 LC O 1798 Phloeopora testacea 29 LC O 1801 Phloeopora concolor 1 LC O 1859 Dadobia immersa 1 LC F 1898 Atheta subtilis 75 LC F 1910 Atheta dadopora 11 LC F 1925 Atheta sodalis 8 LC F 1926 Atheta gagatina 5 LC F 1930 Atheta trinotata 1 LC F 1964 Atheta laevana 3 LC F 1989 Atheta pilicornis 4 LC F 1994 Atheta (para-)crassicornis 464 LC F 1998 Atheta euryptera 1 * F 2001 Atheta nigricornis 267 LC F 2002 Atheta harwoodi 4 LC F 2009 Atheta picipes 59 LC O 2028 Dinaraea linearis 4 LC O 2054 Thamiaraea cinnamomea 61 NT * O 2055 Thamiaraea hospita 16 * F 2070 Zyras cognatus 3 * F 2071 Zyras lugens 45 * F 2072 Zyras laticollis 97 LC F 2082 Gyrophaena affinis 2 LC F 2087 Gyrophaena gentilis 2 LC F 2088 Gyrophaena poweri 1 * O 2099 Gyrophaena angustata 1 LC O 2101 Gyrophaena boleti 1 LC F 2106 Bolitochara pulchra 1 LC O 2109 Leptusa pulchella 1 LC O 2111 Leptusa fumida 11 LC O 2120 Anomognathus cuspidatus 3 LC O 2127 Placusa complanata 3

5 LC O 2128 Placusa depressa 6 LC O 2129 Placusa tachyporoides 144 LC O 2130 Placusa incompleta 18 LC O 2133 Placusa atrata 3 LC * O 2197 Prionocyphon serricornis 7 LC F 2290 Cetonia aurata 654 LC * O 2291 Protaetia marmorata 1832 LC F 2292 Protaetia metallica (cuprea) 9 LC O 2296 Trichius fasciatus 13 LC * O 2299 Platycerus caprea 9 LC O 2300 Platycerus caraboides 6 LC O 2302 Sinodendron cylindricum 1 LC O 2328 Dictyoptera aurora 52 LC O 2329 Pyropterus nigroruber 5 LC O 2333 Lygistopterus sanguineus 13 LC O 2368 Malthinus biguttatus 7 LC O 2369 Malthinus punctatus 1 LC O 2373 Malthinus frontalis 4 LC O 2374 Malthodes flavoguttatus 5 LC O 2378 Malthodes fuscus 5 LC O 2380 Malthodes guttifer 12 LC O 2381 Malthodes marginatus 2 LC O 2384 Malthodes spathifer 6 * * O 2391 Lacon fasciatus 1 LC F 2404 Athous subfuscus 1379 LC O 2410 Denticollis linearis 46 LC O 2437 Ampedus sanguineus 12 LC O 2442 Ampedus pomorum 12 LC O 2447 Ampedus balteatus 194 NT * O 2449 Ampedus praeustus 1 LC O 2451 Ampedus tristis 26

6 LC O 2453 Ampedus nigrinus 101 LC O 2458 Melanotus villosus 279 LC O 2459 Melanotus castanipes 146 LC F 2465 Ectinus aterrimus 1 LC O 2469 Cardiophorus ruficollis 192 LC O 2479 Microrhagus pygmaeus 5 LC O 2483 Hylis procerulus 1 LC * O 2484 Hylis cariniceps 4 LC * O 2486 Hylis olexai 7 LC * F 2489 Aulonothroscus brevicollis 6 VU * O 2489 Drapetes mordelloides 1 LC O 2496 Buprestis rustica 3 LC O 2508 Anthaxia similis (=A.morio) 1 LC O 2509 Anthaxia quadripunctata 20 * O 2521 Agrilus roberti 1 LC O 2522 Agrilus betuleti 1 LC O 2523 Agrilus viridis 2 LC O 2524 Agrilus suvorovi 1 LC F 2552 Dermestes murinus 1 LC F 2566 Attagenus pellio 2 LC F 2579 Megatoma undata 272 LC O 2581 Ctesias serra 119 LC O 2615 Ptinus dubius 8 LC O 2617 Ptinus rufipes 1 LC F 2619 Ptinus fur 48 LC O 2622 Ptinus subpillosus 258 * O 2625 Hedobia imperialis 5 LC O 2627 Dryophilus pusillus 51 LC O 2633 Ernobius mollis 5 LC O 2634 Ernobius angusticollis 2 LC F 2635 Ernobius abietinus 14

7 LC F 2636 Ernobius abietis 35 LC O 2641 Anobium punctatum 1 LC * O 2646 Cacotemnus (Anobium) thomsoni 1 LC * O 2647 Microbregma emarginata 10 LC O 2648 Hadrobregmus pertinax 40 LC O 2651 Ptilinus pectinicornis 1 LC * O 2652 Ptilinus fuscus 3 NT * O 2656 Xyletinus pectinatus 1 NT * O 2664 Stagetus borealis 9 LC O 2667 Dorcatoma chrysomelina 20 LC * O 2669 Dorcatoma punctulata 3 LC O 2670 Dorcatoma dresdensis 52 LC * O 2671 Dorcatoma robusta 8 * O 2674 Hylecoetus dermestoides 224 * O 2679 Ostoma ferruginea 45 LC O 2680 Thymalus limbatus 14 LC * O 2682 Grynocharis oblonga 3 LC O 2684 Nemozoma elongatum 1 LC * O 2687 Tillus elongatus 3 LC O 2691 Thanasimus formicarius 84 LC O 2692 Thanasimus femoralis 2 LC * O 2700 Aplocnemus impressus 1 LC O 2701 Aplocnemus nigricornis 27 LC O 2708 Dasytes obscurus 48 * O 2709 Dasytes cyaneus 4 LC O 2710 Dasytes niger 577 LC O 2712 Dasytes plumbeus 6727 LC O 2713 Dasytes fusculus 1 LC O 2725 Malachius bipustulatus 3 LC F 2742 Carpophilus marginellus 1 LC F 2745 Epuraea melanocephala 17

8 LC * O 2746 Epuraea guttata 21 LC O 2748 Epuraea neglecta 8 LC O 2749 Epuraea pallescens 17 LC O 2750 Epuraea laeviuscula 1 LC O 2753 Epuraea angustula 1 LC O 2757 Epuraea boreella 5 LC O 2759 Epuraea marseuli 283 LC O 2760 Epuraea pygmaea 396 LC F 2762 Epuraea binotata 1 LC F 2764 Epuraea terminalis 4 LC O 2768 Epuraea biguttata 12 LC F 2769 Epuraea unicolor 343 LC F 2770 Epuraea variegata 4 LC O 2771 Epuraea muehli 1 * F 2774 Epuraea testacea (aestiva) 2 LC F 2775 Epuraea melina 61 LC F 2776 Epuraea rufomarginata 135 LC O 2825 Soronia punctatissima 22 LC O 2826 Soronia grisea 139 LC * O 2827 Ipidia binotata 18 LC F 2832 Cychramus variegatus 529 LC F 2833 Cychramus luteus 1151 LC O 2834 Cryptarcha strigata 11 LC * O 2835 Cryptarcha undata 2 LC * O 2836 Glischrochilus quadriguttatus 38 LC F 2837 Glischrochilus hortensis 1660 LC O 2838 Glischrochilus qudripunctatus 769 LC F 2838b Glischrochilus quadrisignatus 1 LC O 2839 Pityophagus ferrugineus 432 LC F 2841 Sphindus dubius 55 LC F 2842 Aspidiphorus orbiculatus 75

9 LC O 2846 Rhizophagus depressus 12 LC O 2847 Rhizophagus ferrugineus 141 NT * O 2850 Rhizophagus picipes 1 LC F 2851 Rhizophagus dispar 35 LC O 2852 Rhizophagus bipustulatus 229 LC O 2853 Rhizophagus nitidulus 4 LC O 2855 Rhizophagus (fenestralis) parvulus 118 LC * O 2856 Rhizophagus cribratus 5 NT * O 2871 Silvanus bidentatus 6 LC F 2873 Silvanoprus fagi 40 LC * O 2877 Dendrophagus crenatus 4 LC O 2888 Cryptolestes abietis 5 LC O 2889 Leptophloeus (Cryptolestes) alternans 1 LC O 2890 Cryptolestes corticinus 1 LC F 2900 Henoticus serratus 3 LC * O 2902 Pteryngium crenulatum 24 LC F 2905 Micrambe abietis (=Cryptoph.abietis) 247 LC F 2907 Cryptophagus acutangulus 87 LC O 2912 Cryptophagus badius 112 LC * F 2913 Cryptophagus populi 1 LC F 2921 Cryptophagus pubescens 140 LC * O 2922 Cryptophagus micaceus 21 LC F 2923 Cryptophagus saginatus 82 LC F 2928 Cryptophagus dentatus 178 LC F 2930 Cryptophagus dorsalis 91 LC F 2931 Cryptophagus distinguendus 62 LC F 2933 Cryptophagus scanicus 1075 LC F 2939 Cryptophagus denticulatus (pillosus) 82 LC F 2953 Atomaria morio 31 LC F 2954 Atomaria ornata 150 LC F 2962 Atomaria fuscata 42

10 LC * O 2994 Atomaria subangulata 6 LC O 3001 Atomaria bella 28 LC F 3004 Atomaria atrata 22 LC O 3009 Tritoma bipustulata 43 LC O 3010 Triplax aenea 10 LC O 3011 Triplax russica 38 NT * O 3013 Triplax rufipes 3 LC O 3015 Dacne bipustulata 111 LC O 3036 Cerylon fagi 16 LC O 3037 Cerylon histeroides 38 LC O 3038 Cerylon ferrugineum 23 NT * O 3040 Cerylon deplanatum 3 LC * O 3051 Mycetina cruciata 48 LC O 3052 Endomychus coccineus 7 LC F 3126 Orthoperus atomus 2 LC O 3127 Orthoperus corticalis 3 LC O 3134 Latridius hirtus 4 LC F 3135 Latridius consimilis 26 LC F 3136 Latridius porcatus (Ny ÖG) (anthracinus) 2 LC F 3137 Latridius minutus 12 LC O 3143 Enicmus fungicola 177 LC O 3146 Enicmus rugosus 798 LC O 3147 Enicmus testaceus 494 LC F 3148 Enicmus transversus 18 * F 3150 Dienerella elongata 1 LC F 3157 Stephostethus lardarius 6 LC F 3159 Stephostethus pandellei 370 LC O 3162 Stephostethus alternans 4 LC F 3163 Stephostethus rugicollis 29 LC F 3164 Thes bergrothi 2 LC F 3166 Aridius nodifer (=Cartodere nodifer) 245

11 LC F 3168 Cartodere constricta 71 LC * O 3177 Corticaria lapponica 13 LC F 3179 Corticaria serrata 76 LC F 3182 Corticaria abietorum (=longicornis) 52 NT * F 3183 Corticaria interstitialis 14 LC F 3185 Corticaria rubripes 109 LC F 3188 Corticaria longicollis 139 LC O 3191 Corticaria lateritia 30 LC F 3197 Cortinicara gibbosa 162 LC F 3198 Corticarina similata 89 LC O 3215 Cis jacquemartii 34 * O 3219 Cis hispidus 21 LC O 3222 Cis boleti 16 NT * O 3223 Cis rugulosus 1 LC O 3224 Cis quadridens 19 LC O 3225 Cis punctulatus 14 LC O 3228 Cis dentatus 38 LC O 3230 Ennearthron cornutum 64 LC O 3234 Orthocis alni 6 * O 3237 Orthocis vestitus 4 * O 3238 Orthocis festivus 8 * O 3240 Sulcacis affinis (=Cis nitidus) 7 LC O 3242 Ropalodontus perforatus 9 LC O 3249 Synchita humeralis 2 LC O 3252 Bitoma crenata 5 LC O 3257 Litargus connexus 98 LC * O 3260 Mycetophagus quadripustulatus 14 LC * O 3261 Mycetophagus piceus 15 NT * O 3262 Mycetophagus decempunctatus 2 LC O 3265 Mycetophagus multipunctatus 8 NT * O 3266 Mycetophagus fulvicollis 2

12 LC O 3267 Mycetophagus populi 1 LC O 3273 Chrysanthia viridissima 229 LC O 3274 Chrysanthia geniculata 25 LC O 3279 Calopus serraticornis 8 LC O 3291 Pytho depressus 1 LC O 3294 Pyrochroa coccinea 6 LC O 3295 Schizotus pectinicornis 68 LC O 3300 Rabocerus foveolatus 1 LC O 3302 Sphaeriestes castaneus 20 LC O 3307 Salpingus planirostris 32 LC O 3308 Salpingus ruficollis 61 LC O 3313 Euglenes pygmaeus 1 LC O 3315 Anidorus nigrinus 14 LC O 3340 Bolitophagus reticulatus 6 LC O 3343 Diaperis boleti 1968 LC F 3364 Palorus depressus 1 LC O 3403 Pseudocistela ceramboides 4 LC O 3406 Mycetochara flavipes 7 LC * O 3407 Mycetochara axillaris 1 LC O 3417 Anaspis frontalis 715 LC O 3419 Anaspis marginicollis 77 LC O 3420 Anaspis thoracica 419 LC O 3424 Anaspis rufilabris 11864 LC O 3425 Anaspis flava 410 LC O 3427 Tomoxia bucephala 77 LC F 3430 Mordella aculeata 136 LC F 3431 Mordella holomalaena 14 LC O 3433 Curtimorda maculosa 4 LC * O 3448 Mordellistena variegata 9 LC O 3450 Mordellochroa abdominalis 23 LC * O 3454 Tetratoma fungorum 3

13 LC O 3457 Hallomenus binotatus 26 LC * O 3458 Hallomenus axillaris 6 LC O 3459 Orchesia micans 1 NT * O 3462 Orchesia fasciata 1 LC O 3463 Orchesia undulata 8 LC * O 3466 Abdera flexuosa 1 * * O 3467 Abdera triguttata 2 LC * O 3470 Phloiotrya rufipes 1 LC O 3472 Xylita laevigata 21 LC * O 3474 Serropalpus barbatus 13 NT * O 3477 Zilora ferruginea 3 VU * O 3486 Tragosoma depsarium 1 LC O 3489 Arhopalus rusticus 3 LC O 3491 Asemum striatum 2 LC O 3493 Tetropium castaneum 52 LC O 3494 Tetropium fuscum 10 LC O 3498 Rhagium mordax 319 LC O 3499 Rhagium inquisitor 61 LC O 3500 Oxymirus cursor 9 NT * O 3502 Pachyta lamed 2 LC O 3505 Gaurotes virginea 10 LC O 3511 Cortodera femorata 12 LC O 3513 Grammoptera ruficornis 13 LC O 3514 Alosterna tabacicolor 32 * O 3518 Anoplodera maculicornis 22 LC O 3519 Stictoleptura (Anoplodera) rubra 3 LC O 3521 Anastrangalia sanguinolenta 68 LC O 3522 Anastrangalia reyi 3 LC O 3524 Judolia sexmaculata 41 LC O 3528 Leptura quadrifasciata 4 * O 3530 Leptura melanura 194

14 LC * O 3533 Necydalis major 1 NT * O 3540 Obrium brunneum 1 LC O 3542 Molorchus minor 48 LC O 3556 Phymatodes testaceus 18 LC * O 3558 Poecilium alni 8 * O 3559 Xylotrechus rusticus 4 NT * O 3561 Xylotrechus antilope 6 LC O 3562 Clytus arietis 38 LC O 3564 Plagionotus arcuatus 5 LC O 3577 Pogonocherus hispidulus 4 LC O 3580 Pogonocherus fasciculatus 9 LC O 3595 Saperda scalaris 2 LC O 3600 Stenostola dubia 1 LC O 3604 Tetrops praeusta 1 LC O 3914 Dissoleucas niveirostris 3 LC O 3915 Platystomos albinus 9 LC O 3918 Anthribus nebulosus 115 LC O 4296 Rhyncolus ater 12 LC O 4298 Rhyncolus sculpturatus 4 LC O 4304 Magdalis phlegmatica 5 LC O 4305 Magdalis nitida 1 LC O 4306 Magdalis linearis 2 LC O 4308 Magdalis frontalis 1 LC O 4309 Magdalis violacea 3 LC O 4311 Magdalis carbonaria 2 LC O 4313 Magdalis barbicornis 1 LC O 4313 Magdalis duplicata 2 LC O 4315 Magdalis ruficornis 3 LC O 4319 Hylobius abietis 54 LC O 4320 Hylobius pinastri 1 LC O 4325 Pissodes castaneus 13

15 LC O 4326 Pissodes pini 6 LC O 4327 Pissodes gyllenhalii 1 NT * O 4329 Pissodes harcyniae 3 LC O 4330 Pissodes piniphilus 3 LC O 4446 Hylurgops palliatus 42 LC O 4448 Hylastes brunneus 166 LC O 4449 Hylastes cunicularius 5573 LC O 4450 Hylastes attenuatus 659 LC O 4452 Hylastes opacus 30 * O 4456 Hylesinus fraxini 1 LC O 4458 Xylechinus pilosus 6 LC O 4460 Tomicus minor 3 LC O 4461 Tomicus piniperda 6 LC O 4462 Dendroctonus micans 3 LC O 4464 Phloeotribus spinulosus 37 LC O 4465 Polygraphus subopacus 2 LC O 4466 Polygraphus poligraphus 9 NE O 4475 Scolytus laevis 1 LC O 4480 Pityogenes chalcographus 141 LC O 4484 Pityogenes trepanatus 1 LC O 4485 Pityogenes quadridens 24 LC O 4486 Pityogenes bidentatus 12 LC O 4489 Orthotomicus suturalis 13 LC O 4496 Ips typographus 479 LC * O 4500 Dryocoetes villosus 13 LC O 4502 Dryocoetes autographus 451 LC O 4504 Crypturgus subcribrosus 17 LC O 4505 Crypturgus cinereus 7 LC O 4506 Crypturgus pusillus 4 LC O 4507 Crypturgus hispidulus 97 LC O 4508 Trypodendron domesticum 25

16 LC O 4510 Trypodendron lineatum 194 LC O 4511 Trypodendron signatum 4 LC O 4512 Anisandrus (Xyleborus) dispar 159 LC O 4514 Xyleborus cryptographus 1 LC * O 4516 Xyleborinus saxesenii 3 * O 4524 Cryphalus abietis 16 LC O 4524 Cryphalus asperatus 22 LC O 4525 Cryphalus saltuarius 9 LC O 4526 Pityophthorus micrographus 15 Acrotrichis sp. 170 Atomaria sp 20 Orthoperus sp. 1 Cis sp. 22 Corticaria sp. 42 Cryptophagus sp. 39 Gabrius sp. 6 Malthodes sp. 1 Orthotomicus sp. 26 NE Scolytus sp. 1 Trixagus sp. 1

Total number of individuals 74493

Total number of species 478

17