COMPARING THE COMPOSITION OF SAPROXYLIC BEETLE FAUNA ON OLD HOLLOW OAKS BETWEEN TWO TIME PERIODS

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Linköping University | Department of Physics, Chemistry and Biology Master thesis, 60 hp | Educational Program: Physics, Chemistry and Biology Spring term 2019| LITH-IFM-A-EX—19/3611--SE

COMPARING THE COMPOSITION OF SAPROXYLIC BEETLE

FAUNA ON OLD HOLLOW OAKS BETWEEN TWO TIME

PERIODS

CHIPANGO KAMBOYI

Examiner: LARS WESTERBERG Supervisor: NICKLAS JANSSON

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Page | 2

Datum

Date: 23 May 2019

Avdelning, institution

Division, Department

Department of Physics, Chemistry and Biology Linköping University

URL för elektronisk version

ISBN

ISRN: LITH-IFM-A-EX--19/3611--SE

_____________________________________________________________ ____

Serietitel och serienummer ISSN

Title of series, numbering ______________________________

Språk Language Svenska/Swedish Engelska/English ________________ Rapporttyp Report category Licentiatavhandling Examensarbete C-uppsats D-uppsats Övrig rapport ____________ _ Titel

Title: Comparing the composition of saproxylic beetle fauna on old hollow oaks between two time periods.

Författare

Author: Chipango Kamboyi

Keyword: Saproxylic beetles, Guilds, Species composition, Canopy Cover, Forest Regrowth, Trunk Circumference, Cavity size. Species turnover

Sammanfattning

Abstract

Oak habitats are rich in saproxylic species, but the habitat is declining with loss of diversity due to encroachment which decrease the vitality of oaks. The present explorative study compared results from a study conducted in 1994, with present species communities to observe if there has been change in species composition and what factors that can explain species diversity and composition. The results revealed that the overall species composition between 1994 and 2018 has changed. There were 130 species recorded in 2018 compared to 108 species in 1994 (31 new species were recorded in 2018, and 9 species lost from the study in 1994). There was a high species turnover recorded per individual tree, and the species composition between the living and encountered dead trees did not differ. Species composition was affected by canopy cover, and trunk circumference (CCA P-value 0.001 and 0.014 respectively). Unlike 1994, there were no variables in 2018 that could explain the association with species numbers. Warmer conditions recorded during the sampling period have probably led to increased flight activity of beetles and therefore increasing chances of capturing more species and individuals. The warmer conditions possibly shadowed the effects of the explanatory variables in explaining the changes in species numbers. Perhaps the change in species composition could also be attributed to existing management interventions that may be supporting an increasing species number of saproxylic beetles, however no strong conclusions could be drawn. Management interventions such as the recruitment of new oaks should be encouraged and intensified in order to provide habitats and support stable populations as the loss of oaks may lead to increased risk of extinction of the saproxylic beetles in the study area.

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Oak habitats are rich in saproxylic species, but the habitat is declining with loss of diversity due to encroachment which decrease the vitality of oaks. The present explorative study compared results from a study conducted in 1994, with present species communities to observe if there has been change in species composition and what factors that can explain species diversity and composition. The results revealed that the overall species composition between 1994 and 2018 has changed. There were 130 species recorded in 2018 compared to 108 species in 1994 (31 new species were recorded in 2018, and 9 species lost from the study in 1994). There was a high species turnover recorded per individual tree, and the species composition between the living and encountered dead trees did not differ. Species composition was affected by canopy cover, and trunk circumference (CCA P-value 0.001 and 0.014 respectively). Unlike 1994, there were no variables in 2018 that could explain the association with species numbers. Warmer conditions recorded during the sampling period have probably led to increased flight activity of beetles and therefore increasing chances of capturing more species and individuals. The warmer conditions possibly shadowed the effects of the explanatory variables in explaining the changes in species numbers. Perhaps the change in species composition could also be attributed to existing management interventions that may be supporting an increasing species number of saproxylic beetles, however no strong conclusions could be drawn. Management interventions such as the recruitment of new oaks should be encouraged and intensified in order to provide habitats and support stable populations as the loss of oaks may lead to increased risk of extinction of the saproxylic beetles in the study area.

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Page | 5 1 INTRODUCTION

Oak trees across Europe are considered important because they have been known to provide a variety of functions to humans, such as preventing erosion, considered a source of good quality timber and cork (Hartel et al. 2015). From a biodiversity perspective, oak woodland habitats provide microhabitats to thousands of species living and dependent on old hollow oaks (Micó, 2018). One such species rich group are saproxylic insects. Speight (1989), defines saproxylic species as those that depend on, during some part of their life cycle, upon the dead or dying wood of moribund or dead trees (standing or fallen), upon wood-inhabiting fungi, or upon the presence of other saproxylic species. Saproxylic beetles are considered to be ecosystems engineers as they are shaping habitats and affecting ecological processes (Micó et al. 2015; Romero et al. 2014).

In Sweden the number of species associated with oak trees is estimated to be more than 880 species, and beetles are considered among the organism groups with the highest number of classified species association with host trees (Sundberg et al 2019). In a separate study, Palm (1959), estimated that more than 500 saproxylic beetle species are associated with oak trees. These are significant species numbers and is an indication of how important oak trees are, as habitat for the many threatened species (e.g. Götmark et al. 2011; Ranius and Jansson, 2000; Ohsawa, 2007; Bouget et al. 2011; Bakke, 1999). For some species, one oak may maintain a local population and that distance between oaks in a patch is important to maintain a metapopulation (Hanski, 1999; Hanski and Ovaskainen, 2000). For other species, oak areas harbor a local population and loss of oak patches increase isolation. As oaks or oak patches disappear, local populations vanish which simultaneously decrease the total population size, decrease connectivity, decrease genetic diversity and increase the risk of extinction (Trail et al. 2007).

The conditions within and around the tree are important predictor variables in determining local species richness of oak beetles, (Franc et al. 2007: Widerberg et al. 2012: Ranius, 2007; Sundberg et al. 2019; Chiari et al. 2013; Siitonen and Ranius, 2015). Low canopy cover and surrounding forest regrowth, and large girth oaks have previously been identified as correlated with high diversity (Ranius and Jansson, 2000). It is hypothesized that, as oak areas are over-grown, local factors change and diversity decrease, thus management is needed. By comparing results from a study by Ranius and Jansson (2000) with present species communities, this explorative study focuses on checking if diversity patterns are stable over the years. We revisited oaks that have, on average, been managed similarly. So, by revisiting a saproxylic

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Page | 6 hotspot, we would therefore expect similar patterns in species composition between the two years mainly determined by local conditions, assuming the local conditions have remained the same.

In order to understand this, species turnover i.e. probing whether new species have been included in the local population or not, for the saproxylic beetle assemblages was analysed. Furthermore, an assessment of the conditions around the trees i.e. tree characteristics, was undertaken to identify key drivers possibly influencing change in species composition (if any). Some studies seem to suggest that the species composition may be explained by habitat requirements and ecological characteristics (Belskaya and Kolesnikova, 2011; Micó et al. 2015; Ranius 2002b; McGeoch et al. 2007), therefore comparisons were also made on ecological characteristics based on feeding habits.

The findings of this study aim to increase our understanding of the species composition structure for purposes of making it easier in the successful planning of the conservation of saproxylic beetle fauna at a habitat level and further gives an opportunity to identify appropriate conservation-oriented management interventions.

2 MATERIALS AND METHODS 2.1 Study area and study site.

This study was conducted in eight areas, situated 20-30 km south of Linköping city in southern Sweden, on the property of some large landowners in Bjärka Säby, Stavsätter, Hovetorp and Sturefors (Fig. 1). The location of trees from the old study were identified in these areas (Ranius & Jansson 2000). The landscape is known to have a considerably higher number of mature hollow oaks (mostly Quercus robur), some of the older oaks at the studied sites have been estimated to be around 400-600 years old (unpublished data). It is thus a hotspot for old oak dependent saproxylic species. A study made by Ranius et al. (2009) showed that at the age of 200 – 300 years, 50% of the oaks develop hollows in the trunks. Other trees found in the landscape were; ash (Fraxinus excelsior), aspen (Populus tremula), birch (Betula pendula), Norway spruce (Picea abies) and Pine trees (Pinus spp).

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Figure 1: Maps showing the positions for the study sites in Sweden and the county Östergötland.

2.2 The studied trees and their surrounding

A total of 51 oak trees from the 1994 study were revisited and sampled for saproxylic beetles. For purposes of this study, canopy cover was described as the amount of open/closed sky visible around the tree as result of cover from mature and old trees i.e. while ignoring the cover produced by young trees that had invaded once open areas. Forest regrowth was the amount of bushes or trees growing around the sampled tree, and trunk circumference as the distance around the tree trunk, while cavity size as the opening of the hollow in the tree and finally cavity height as the position from the ground the where cavity started to form.

Canopy Cover assessment was done using a simple three class categorisation assessment, the same as the one used in the 1994 study, where 0 - 24% is totally open, 25 - 75% is open with patches of closed sky and 75 - 100% is less than 25% open sky (Ranius and Jansson, 2000). When assessing the Forest Regrowth, bushes or trees more than 4 m in height, and were either within a distance of 5 m from the edges of the crown were considered as regrowth. Using the tree as a central reference point, 4 imaginal directional segments were created around the tree, were classification 4 meant = all directions (i.e. segments) around the tree were covered with regrowth of younger trees or larger bushes. The shadowing as a result of the bushes/trees on the main tree in any one segment needed to be more than ca 50% to be considered as classification 1 or 1 segment of regrowth. Cavity entrance size (i.e. length & width), distance

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Page | 8 from ground to hollow and trunk circumference were measured using a measuring tape. Out of the 51 revisited trees, six trees had died between 1994 and 2018.

2.3 Sampling methods

Saproxylic beetles were captured using a flight interception method (i.e. transparent Plexiglas 30 cm * 60 cm also known as window traps), with an aluminum tray placed underneath. The aluminum tray was filled with propylene glycol and water mixture, in the ratio 1:1, for the purpose of preserving the trapped beetles and eliminating surface tension. Cleaning detergent and alcohol with a strong taste was also added to avoid animals drinking from the traps. The traps were put at a minimum height of 2 m from the ground and positioned adjacent or slightly above the cavity entrance opening and not more than 2 m away. The traps were placed in the beginning of May and emptied every third week starting from June 1st until August 25th, 2018. The trapping method was the same as the one used in the 1994 study (Ranius & Jansson, 2002). Sorting of samples and identification of species was done in the lab under a dissecting microscope.

Species identification was mostly done with the help of two experienced coleopterologist. The species identification was restricted to the beetle families identified in the 1994 study. The taxonomy used is following fauna europaean nomenclature (De Jong, et al. 2014). The number of individuals captured per trap were converted into absence, a single observation and more than one individual (i.e. 0’s, 1’s and 2’s respectively, as this system was used in the 1994 study) Species known to be non-oak living were excluded in the analysis and only the saproxylic species were included.

2.4 Ecological groups

The feeding habits of species larval stage followed Ranius and Jansson (2000; Table 1).

Table 1: Species classification according to ecological groups (Ranius and Jansson, 2000)

Classification Description

ROT Rotten wood in any part of the trunks except in hollows HOLLOW Rotten wood and wood mold in trunk hollows

FUNGI Mold on wood surface or fruiting bodies of saproxylic fungi

DRY Dead dry wood in trunks

BRANCH Branches of old oaks

NEST Animal nests in tree hollows or other saproxylic habitats BARK In/under bark or at sap runs

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Page | 9 2.5 Statistical analysis

The explanatory variables for the study were trunk circumference, canopy cover, forest regrowth, cavity entrance size, height from ground, while species number or species composition was the response variables.The correlation between explanatory variables revealed that canopy cover and forest regrowth were highly correlated, while trunk circumference and canopy cover had a low correlation value despite being statistically significant. Therefore, canopy cover and forest regrowth could not be used at the same time in the analysis to avoid collinearity (Table 2). All statistical analysis was carried out in R software (R Core Team, 2018).

Table 2: Correlation analysis of the main tree characteristics (i.e. explanatory variables) in 2018.

Explanatory variable(s) Cor. value p - value

Canopy Cover & Forest Regrowth 0.616** 1.451e-06

Trunk Circumference & Canopy Cover -0.337** 0.016

Cavity size & Forest regrowth -0.250 0.077

Cavity size & Cavity height from ground -0.255 0.071

Cavity size & Canopy cover -0.173 0.224

Trunk Circumference & Forest regrowth -0.211 0.138

Trunk Circumference & Cavity size 0.094 0.512

Ordination was used to show the relationship of species found and the sampled trees while at same time factoring in the measured explanatory variables (Oksanen, 2019; Ramette, 2007). Detrended Correspondence Analysis (DCA) was used to analyse species data for both years in order to find the main gradient. Canonical Correspondence Analysis (CCA) was used to explain the species data for both years, using canopy cover, trunk circumference and cavity size as explanatory factors. (Oksanen, 2019; Gauch, H. G., 1982). Further, a generalised linear model was fitted to determine the association between canopy cover, trunk circumference and cavity size with species number.

3. RESULTS

A total of 18,775 individuals belonging to 130 species of saproxylic beetles were found on the 51 revisited trees in 2018, compared to 108 species on the same trees in 1994. Overall, 139 species made up the total species community between the two years. Further, six standing dead trees were encountered among the revisited trees, and it was observed that the species composition on these dead trees did not differ much compared to the living trees (Appendix

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Page | 10 II). In addition, 93 species increased in occurrence (i.e. number of host trees) and 36 species decreased in 2018 (Appendix IV).

3.1 Ecological groups

There were more species in each guild in 2018 compared to 1994, with more BARK and ROT feeding species recorded in 2018 (Fig. 2).

Figure 2: Comparison of total number of species based on feeding preferences at larval stage for species

caught in window traps on 51 old hollow oaks for 1994 and 2018. 3.2 Changes in Explanatory variables

There seemed to be moderate shifts among the explanatory between the two years, perhaps implying the environment in the saproxylic hotspot has not changed much.

Table 3: Comparison of explanatory variables in 1994 and 2018 for 51 sampled trees Year Trunk Circum. (cm)

Mean ± SD Cavity Size (cm) Mean ± SD Canopy Cover Average 1994 332 ± 106 840 ± 1826 1 2018 355 ± 115 3541 ± 7623 1

3.3 Species turnover and species association with explanatory variables

There were 99 (71% ) shared species between 1994 and 2018, 31 (22%) new species recorded in 2018 and 9 (6%) species lost from the study in 1994. Among the 31 new species (Appendix IV), 11 species were singletons and 20 species were represented by 354 individuals, adding up to a total of 365 new individuals (i.e. ca 1.9 % of the total number of individuals found in 2018). The average number of shared species per individual tree was 11 species (t = -7.27, df = 98.8, p = 1.657e-10). The number of species found per tree in 2018 i.e. 31 species, was more compared to species found in 1994 (Table 4; Appendix III).

0 5 10 15 20 25 30 35 co u n t o f sp ec ies Guild classes 1994 2018

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Table 4: Results show number of species per tree between 1994 and 2018.

Year Species number per tree Mean ±SD Shared species per tree Mean ±SD Shared species per Ind. tree

Number of species found 1994 22 ± 7 11 ± 4 25% 27 2018 31 ± 6 48

The number of unique species for 2018 was more than the number of unique species in 1994 combined with the shared species, thus it may assumed that there was an influx new species (Table 4). The number of shared species (i.e. overlap) per tree was smaller (Appendix III) therefore suggesting the majority of captured species (additional new species) in the tree were from elsewhere other than the tree itself, thus implying a high turnover.

The DCA and CCA mainly analyzed the joint composition of 1994 and 2018. However, as was seen from the CCA analysis, the arrow for cavity size pointed to 2018 indicating that holes are larger now than in 1994. The other two arrows for canopy cover and trunk circumference did not coincide with year (Appendix I). Thus, they indicated that differences in composition between samples is more related to those factors than differences between year. Only 7% of the variation could be attributed to CCA2, i.e. canopy and trunk circumference (Appendix I). In summary, canopy cover and trunk circumference only explained change in species composition but could not explain change in species number

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Figure 3: DCA analysis for 1994 and 2018 together, investigating similarities in species composition. The red circles are the species and the black circles are

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Page | 13 The pattern in which the sites were clustered along the DCA 1 axis (Fig. 3), was an indication that the effect of the year had the strongest gradient.

The permutation test of the CCA showed that canopy cover and trunk circumference (p-value 0.004, 0.014 respectively), had a statistically significant effect on species composition. This probably meant there might be species e.g. Anisoxya fuscula, Dasytes aeratus, that consistently prefer large trees/low canopy cover (Table 5; Appendix I). The factor of year (p-value 0.001) was also statistically significant, an indication that the observed difference in species composition was also explained by the different years.

Table 5: Multivariate analysis (CCA) permutation test, testing for the association of explanatory

variables in 1994 and 2018, with species composition as the response variable.

Explanatory Variable Df ChiSquare F Pr(>F)

Canopy Cover 2 0.0537 1.6202 0.004 **

as. Factor (Year) 1 0.1933 5.8360 0.001 ***

Cavity Size 1 0.0311 0.9392 0.508

Trunk Circumference 1 0.0459 1.3859 0.014 *

Residual 96 3.2122

However, the general association between explanatory variables and species number in 2018 did not reveal any statistically significant effect, therefore it was not known how each factor influenced the observed change in species number (Table 6).

Table 6: Generalised Linear Model fitted with explanatory variables in 2018 to investigate how each

factor influenced species number as the response variable (df=47, p=0.130, residual SE=5.768, adjusted R2_=0.056)

Estimate Std. Error T - value Pr(>|t|)

Intercept 2.437e+01 3.543e+00 6.877 1.26e-08 ***

Trunk circumference 1.495e-02 7.583e-03 1.972 0.055

Cavity size 1.438e-04 1.096e-04 1.312 0.196

Canopy cover 6.636e-01 1.289e+00 0.515 0.609

4. DISCUSSION

The results revealed that species composition for the two periods was different, with higher species numbers, more individuals and higher occurrence for 93 species recorded in 2018. Probably so because the sampling period was characterized by very warm temperatures as compared to the same period in 1994 (Fig. 4). Studies have shown that higher temperatures (i.e. increased sun exposure and a warmer microclimate around the trees) increases the flying

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Page | 14 activity of beetles thereby increasing the possibility of capturing more species (Gossner et al. 2016; Ranius and Jansson, 2000). It is therefore a possible reason why more species were captured during this period.

Figure 4: A comparison of average monthly mean temperatures for the same study sites between 1994

(blue) and 2018 (brown). Grey bars are the average temp. for all the years between 1994 and 2018.

Source: Swedish Meteorological and Hydrological Institute (SMHI-2018).

Notably, the months during the sampling period for 1994 were below and or slightly above the average for the years in-between 1994 and 2018 during the same period in comparison to 2018 and further supports the justification that 2018 was much warmer (Fig. 4).

4.1 Local species turnover

The high local species turnover that was observed in individual trees was perhaps as a result of the warmer conditions, coupled with close proximity of sampled trees to other trees, and also probably because of competition for resources in other surrounding trees i.e. individuals leaving their host trees and spreading to other trees (Chase et al. 2002; Menge and Sutherland, 1976). This may have allowed new species being trapped at another tree and thereby increasing the species turnover. In addition, the window trapping method used is known to be effective in capturing high number of species compared to methods like pitfall trapping and wood mould sampling, (Ranius and Jansson, 2002).

It is also possible and could be assumed that there were probably more species in the tree in 1994 but perhaps low temperatures observed in 1994 compared to 2018, probably meant individuals were not active, and thus window traps may have not been effective in capturing all the species in the tree during that time.

As the window traps can catch all flying species passing by, it may have been more useful in this study to use pitfall traps as they catch the species from the specific trees to a higher degree i.e. less sensitive if trees are close together or if high temperatures make species fly more.

9,8 13,4 20,5 16,7 15,4 16,7 21,3 17,8 10,8 14,5 17,0 _16,2 0 5 10 15 20

May June July August

T em p . 0C Sampled Months

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Page | 15 What could also be inferred from the results was, there seemed to be an increase in the number of individuals that were found in 1994, which we assume in turn increased the probability of detecting new species (Appendix IV). It should be noted that the new species could either have been completely new to the area or previously present but not captured because e.g. they didn’t move that much. For instance, the occurrence of a completely new species E. ferrugineus seemingly corresponded with the increase in the presence of O. eremita (Appendix IV). This makes sense because the presence of O. eremita is known to correlate with the occurrence of

E. ferrugineus, (Ranius, 2007; Ranius and Hedin, 2001; Andersson et al. 2014; Svensson et al.

2004; Ranius, 2002a).

4.2 Species richness and composition.

The variation in total number of species in 2018 could not be attributed to either canopy cover, cavity size or trunk circumference (Table 6). However, species composition for 1994 and 2018 combined was affected by canopy cover and trunk circumference. The occurrence of Rhyncolus

sculpturatus, Cerylon histeroides and Tenebrio molitor was associated with increasing canopy

cover. While the occurrence of Anisoxya fuscula and Xyletinus pectinatus seemed to be affected by increasing trunk circumference (Appendix I). It could not be seen from the results how canopy cover, cavity size and trunk circumference influenced species number. Therefore, it can be said that, species richness pattern for 2018 is different from 1994 and cannot be explained by explanatory factors but is perhaps the result of a homogenizing effect of higher mobility (as above). The joint composition of species composition in 1994 and 2018 showed that variation attributed to canopy cover and trunk circumference was independent from difference between years. However, the composition was to a rather small extent (7%) generally affected by these variables. For example, the species Hypebaeus flavipes could be associated with increase in trunk circumference and decreasing canopy cover (Appendix I). This result differs from observations made in the 1994 study, where species richness was said to be high in stands with large (high circumference), free-standing (low canopy cover) trees (Ranius and Jansson, 2000). The result implies that there could be possibly other factors that may be influencing increase in species number such as patch size, availability of resources (Pilskog et al. 2016), and proximity to other old oaks, unfortunately the scope of this study did not extend beyond comparing species composition of the two years.

However, Baselga (2008), identified determinants of species richness and mentions that species richness can mostly be explained by climatic variables such as temperature. The study suggested that it is more likely to have a high species turnover in warm conditions than in cold

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Page | 16 seasons, additional species can be detected at higher temperatures. The observations made for that study in a way agree with the findings of this study, where the sampling period was warmer, and a high local species turnover was recorded (Table 4; Appendix III). This seems to suggest that it is better to assess species composition and richness when conditions are warm as there is high probability of sampling all species which may indicate the representative assemblage. However, this must be done while ensuring there is sufficient data that has been collected consistently between the years for easy comparisons and observing the trends, unlike having information only for two time periods i.e. 1994 & 2018, in order to avoid interpretation problems such as those encountered in this study.

Furthermore, higher number of species were represented in each ecological group (Fig. 2) in 2018 than in 1994, with most of the species being ROT and BARK feeding species. The occurrence of E. ferrugineus may also be confirmation that 2018 was more species rich than 1994 as the species is considered an indicator of species richness and has been described to co-occur with many red listed saproxylic beetles, (Andersson et al. 2014; Ranius, 2002a). The high number of shared species in the total community between the two years (Appendix IV), can also further be one indication that this was the representative assemblage

4.3 Species occurrence on dead oaks

The similarity in species composition between the living and the standing dead trees was an uncommon result. The findings of this study contradict other studies (Franc, 2007; Milberg et al. 2015), that showed that dead trees usually have high species number and constitute saproxylic habitats that differs from that of living trees. However, the species composition on encountered dead trees was not different from living trees, but they were in the early stages of dying and had not reached advanced stages which attracts high species numbers or attracts other kind of species (Micó 2018; Ranius, 2002; Milberg et al. 2015). In line with previous arguments, if the general activity of beetles was higher and they turn up in other traps on other trees, this would make the recorded species compositions more similar. Thus, dead trees might have other composition, but visitors from living trees blur the image.

In addition, yearly mortality was estimated to be at six trees for every 25 years and extrapolating that to 100 years into the future, 25 more trees would be dead and in turn threatened saproxylic beetles would also vanish. The number of trees that have died should also be considered as a warning signal for future increase in habitat fragmentation i.e. decreased patch size, and isolation from other oak patches on species richness and risks the stability of species composition in the local ecological units.

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Page | 17 5. CONCLUSIONS AND IMPACTS FOR CONSERVATION

It can be said for this study that, the species composition has changed between 1994 and 2018, with more species recorded in 2018 compared to 1994. It seems as if higher temperature could have resulted in higher activity of beetles which homogenize the composition in 2018. As a result, canopy cover and trunk circumference could no longer explain species numbers in 2018. Depending on the management objective, saproxylic beetles are particularly useful as indicators because of their sensitivity to habitat changes and can be used to weigh the abundance and presence of resources that show the general ecosystem productivity (Siitonen, 2001; Grove 2002). Taking the example of the occurrence of E. ferrugineus as an indicator for species richness (Andersson et al. 2014). New records of Elater ferrugineus in 2018 compared to the none in 1994 (Appendix IV), can perhaps be looked at as a good indication that the current management interventions were favouring an increasing number of species, as the species itself is considered to be most susceptible among saproxylic beetles to habitat fragmentation (Ranius, 2002b), however it is hard to make strong conclusions for this study due to warmer conditions experienced.

Considering there was no observed difference in species composition between the living and dead trees, this means that dead oaks contribute in a landscape level to the species living on living old hollow trees. It is therefore important for conservationists to ensure that dead trees are included in the same area when planning for the conservation of saproxylic beetles as it contributes to species richness in the living trees.

6. SOCIETAL AND ETHICAL CONSIDERATIONS

In keeping with societal norms, permission was sought from landowners to erect the traps, and also from the county administrations board to conduct the study because the chances of capturing rare and protected species. With regards to ethical considerations, window traps randomly trap species, meaning the rarest species are caught more seldom. Also, the use of the window traps to capture saproxylic beetles inadvertently meant other non-saproxylic species were trapped. However, in comparison to other capturing methods such as the use eclector traps where all individuals including hatchlings from the hollows are usually killed, the use of window traps is considered more ethically preferable as only few species are caught. With the eclector traps, many species that are classified either as threatened, vulnerable or near threatened would be trapped as bycatch. When such species are caught, it is a draw back on the efforts being made to restore populations to meaningful numbers in conservation of insect biodiversity.

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Page | 18 Expansion and development of the society in the 20th_{century is inevitable as the demand for}

social and economic needs increase. Therefore, for this expansion to be considered sustainable, the need to conserve biodiversity and protect the environment is key. The aims and results of this study speak very well to the UN’s sustainable development goal number 15 (Life on Land), whose goal is to protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, halt and reverse land degradation and halt biodiversity loss. ACKNOWLEDGEMENTS

My sincere and profound appreciations go to my supervisor Nicklas Jansson! your counsel, kindness and love for the beetles was inspiring to me in many unexplainable ways. I remain eternally grateful. I thank my field partner and classmate Olof Widen, for helping me understand many parts of my thesis work and also for driving us all the time to the field, you are a good man. I am also grateful to Lars Westerberg and Karl-Olof Bergman, for the counsel and guidance rendered during the planning, analysis and write up phase of the thesis, I have learnt key and fundamental academic principles. Many thanks to the Entomology society of Östergötland for funding part of the research work. The landowners for giving permission to conduct research on their property. To my classmates and all other people who helped me in various ways, I salute your help. I Further thank the Swedish Institute Scholarships for funding my studies, you have left an indelible mark in my life.

To my big big God, thank you for the grace you continue to give me and the paths you show. My love Sephora Kitenge, your support and love have made this possible. Mum Astridah Katebe and dad Frank Kamboyi, we are almost at the top, I dedicate this work to you, Love you all.

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Page | 23 APPENDIX

Appendix I: Canonical Correspondence Analysis (CCA)

Figure 5: Canonical Correspondence Analysis (CCA) showing species occurrence over a gradient of canopy cover, trunk circumference and cavity size. The

years is added as a categorical factor. Species are represented by red crosses (+) and the sampled trees in black circles. 35% of the variation was explained by the constrained variables. Eigenvalues for constrained axes CCA1=0.208 and CCA2=0.071

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Page | 24

Appendix II: DCA Analysis standing dead and living trees:

Figure 6: The boundaries for the living & dead trees (HjS5, Ska3, Orr1.2, Orr2.2, LovE1 and Lab1) overlap, an indication that they have similar species

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Page | 25 Apeendix III: Number of species per tree (turnover)

Figure 7: Species number per tree for 1994 and 2018. Species number(s) in 1994 (blue), 2018 (green), and shared species (red).

1 10 9 17 6 13 11 12 21 9 11 21 12 8 7 10 14 8 16 13 6 8 12 10 14 14 7 10 11 13 9 18 11 18 10 1 5 15 4 16 15 26 9 8 12 10 8 13 13 6 12 10 8 ₈ 16 13 17 11 8 6 9 6 15 15 17 ₁₆ 10 16 12 9 20 5 12 12 8 9 11 4 17 11 12 11 15 5 12 10 9 6 7 5 10 7 10 7 10 10 16 7 12 8 11 9 30 14 18 18 16 16 21 20 17 23 21 12 23 21 23 34 18 23 20 11 16 18 26 13 20 18 18 22 18 16 14 18 25 18 19 21 27 27 27 18 23 14 16 20 19 36 22 23 26 20 18 0 10 20 30 40 50 60 Su n 5 Su n 4 Su n 3 Su n 2 Su n 1 St u S4 St u S1 St u N 4 St u N 2 Sk a5 Sk a4 Sk a3 Sk a1 O rr 3.5 O rr 3.2 O rr 3.1 O rr 2.5 O rr 2.3 O rr 2.2 O rr 2.1 O rr 1.3 O rr 1.2 O rr 1.1 Lo vE 3 Lo vE 2 Lo vE 1 Lo n 5 Lo n 3 Lo n 2 Lo n 1 La b 5 La b 4 La b 2 La b 1 KaH 5 KaH 4 KaH 3 KaH 2 KaH 1 H u mp 4 H u mp 3 H jS 5 H jS 3 H jS 2 H jS 1 H jN 4 H jN 3 H jN 2 H jN 1 Bj a3 Bj a1 N o . o f Spe ci e s Tree.ID

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Page | 26

Appendix IV: Results showing number of trees in which species were recorded. The asteriks mean; *

all species lost since the study in 1994, ** new species recorded in 2018. All other species were shared between the two years.

Species Guild Classification Number host trees 1994 Number host trees 2018

Agrilus biguttatus BARK 1 1

Agrilus convexicollis ** BARK 0 1

Agrilus laticornis BARK 2 1

Agrilus sulcicollis BARK 4 1

Allecula morio HOLLOW 13 30

Alosterna tabacicolor 6 7

Ampedus balteatus ROT 3 8

Ampedus cardinalis HOLLOW 1 19

Ampedus hjorti HOLLOW 6 32

Ampedus pomorum ROT 1 2

Ampedus praeustus ** ROT 0 2

Anaspis flava ** ROT 0 1

Anaspis frontalis ROT 13 11

Anaspis marginicollis ROT 9 21

Anaspis rufilabris ROT 23 31

Anaspis thoracica ROT 35 8

Anisotoma humeralis FUNGI 5 9

Anisoxya fuscula ** ROT 0 1

Anobium nitidum DRY 8 16

Anobium rufipes DRY 2 5

Anthrenus museorum NEST 17 13

Anthrenus scrophularie NEST 4 6

Anthribus nebulosus LOG 19 1

Atomaria fuscata * FUNGI 4 0

Atomaria morio NEST 10 5

Atomaria nigrirostris FUNGI 1 1

Atomaria ornata FUNGI 1 1

Attagenus pellio ** NEST 0 35

Calambus bipustulatus BRANCH 1 10

Cerylon ferrugineum BARK 3 4

Cerylon histeroides BARK 3 1

Conopalpus testaceus BRANCH 9 10

Corticeus fasciatus ** DRY 0 2

Cryptarcha strigata BARK 20 47

Cryptarcha undata BARK 47 45

Cryptophagus badius * HOLLOW 1 0

Cryptophagus confusus * ROT 2 0

Cryptophagus dentatus FUNGI 3 18

Cryptophagus denticulatus * ROT 5 0

Cryptophagus labilis ** ROT 0 1

Cryptophagus micaceus NEST 26 44

Cryptophagus pilosus ** BARK 0 2

Cryptophagus populi ROT 2 5

Cryptophagus pubescens ** FUNGI 0 2

Cryptophagus quercinus * HOLLOW 1 0

Cryptophagus saginatus BARK 1 1

Cryptophagus scanicus HOLLOW 27 45

Ctesias serra NEST 38 48

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Appendix IV cont’d:

Species Number host trees 1994 Number host trees 2018

Dasytes aeratus ** BARK 0 16

Dasytes cyaneus ** BARK 0 7

Dasytes niger BARK 23 1

Dasytes plumbeus BARK 44 43

Dendrophilus corticalis HOLLOW 6 1

Dermestes lardarius NEST 3 2

Diaperis boleti FUNGI 18 37

Dorcatoma chrysomelina ROT 37 47

Dorcatoma flavicornis ROT 26 39

Elater ferrugineus ** HOLLOW 0 6

Eledona agaricola FUNGI 2 5

Euglenes oculatus ROT 34 34

Gastrallus immarginatus BARK 12 17

Glischrochilus hortensis BARK 9 19

Glischrochilus quadripunctatus * BARK 2 0

Globicornis nigripes NEST 11 17

Gnathoncus buyssoni/nannetensis NEST 24 21

Gnathoncus nidorum NEST 1 11

Grammoptera ustulata BRANCH 4 13

Grynocharis oblonga ** HOLLOW 0 11

Hadrobregmus pertinax DRY 1 2

Hallomenus binotatus FUNGI 2 2

Hapalaraea pygmaea HOLLOW 5 7

Hedobia imperalis DRY 8 7

Hypebaeus flavipes HOLLOW 9 3

Hypulus quercinus ** ROT 0 2

Korynetes caeruleus ** ROT 0 12

Leiopus linnei BARK 4 3

Liocola marmorata HOLLOW 3 38

Litargus connexus ** BARK 0 7

Lymexylon navale DRY 7 19

Margarinotus sp NEST 1 10

Megatoma undata NEST 19 34

Melanotus castanipes ROT 4 4

Melanotus villosus ROT 4 15

Mycethophagus quadriguttatus ** FUNGI 0 1

Mycetochara axillaris HOLLOW 1 5

Mycetochara flavipes ROT 1 3

Mycetochara humeralis HOLLOW 11 16

Mycetochara linearis ROT 13 16

Mycetophagus multipunctatus ** FUNGI 0 7

Mycetophagus piceus ROT 37 2

Mycetophagus populi ROT 1 2

Nemadus colonoides NEST 2 5

Orchesia micans FUNGI 5 9

Orchesia undulata FUNGI 2 3

Osmoderma eremita HOLLOW 1 8

Palorus depressus NEST 1 2

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Appendix IV cont’d:

Species Number host trees 1994 Number host trees 2018

Paromalus parallelepipedus ** HOLLOW 0 2

Pediacus depressus ** BARK 0 1

Pentaphyllus testaceus ROT 2 5

Phloiotrya rufipes BRANCH 1 6

Phymatodes testaceum * BARK 11 0

Platystomus albinus ** BARK 0 2

Poecilium alni ** BARK 0 1

Pogonocherus hispidulus ** BARK 0 1

Prionychus ater HOLLOW 10 12

Procraerus tibialis HOLLOW 5 31

Pseudocistela ceramboides HOLLOW 9 26

Ptilinus pectinicornis ** DRY 0 1

Ptinus fur ROT 21 10

Ptinus rufipes ROT 31 20

Ptinus sexpunctatus ** NEST 0 7

Ptinus subpilosus ROT 48 25

Pyrrhidium sanguineum ** BARK 0 1

Rhizophagus bipustulatus BARK 9 17

Rhizophagus cribratus ** ROT 0 1

Rhyncolus sculpturatus DRY 1 1

Salpingus planirostris BARK 10 5

Salpingus ruficollis BARK 16 15

Saperda scalaris BARK 4 3

Scraptia fuscula NEST 27 34

Sinodendron cylindricum ROT 2 2

Soronia grisea BARK 39 49

Tenebrio molitor NEST 2 1

Tenebrio opacus ** HOLLOW 0 5

Tillus elongatus DRY 6 15

Trichoceble floralis ROT 16 5

Trichoceble memnonia ROT 27 16

Triplax aenea * FUNGI 2 0

Triplax rufipes ** FUNGI 0 4

Triplax russica ** FUNGI 0 1

Tritoma bipustulata ** FUNGI 0 1

Trox scaber NEST 2 3

Uloma culinaris * ROT 1 0

Velleius dilatatus NEST 20 22

Xestobium rufovillosum DRY 5 24

Xyletinus longitarsis DRY 1 3

COMPARING THE COMPOSITION OF SAPROXYLIC BEETLE FAUNA ON OLD HOLLOW OAKS BETWEEN TWO TIME PERIODS