Research Collection

Master Thesis

Vegetation dynamics after forest fire in comparison to the pre- fire state

Author(s): Temperli, Christian

Publication Date: 2007

Permanent Link: https://doi.org/10.3929/ethz-a-005517791

Rights / License: In Copyright - Non-Commercial Use Permitted

This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use.

ETH Library

Vegetation dynamics after forest fire in comparison to the pre-fire state Diploma thesis, department of environmental science ETH, Zürich, carried out at the Swiss Research Institute WSL

Christian Temperli December 2007

Reference: Co-reference:

Prof. Dr. Harald Bugmann Dr. Thomas Wohlgemuth ETH Zürich WSL Swiss Federal Research Institute Institut f. Terrestrische Ökosysteme Disturbance Ecology Universitätstrasse 16 Zürcherstr. 111 CH-8092 Zürich CH-8903 Birmensdorf Switzerland Switzerland

The regeneration of vegetation after the forest fire above Leuk, VS, Switzerland in 2003: Comparison to the pre-fire state and analyses with respect to climate, fire intensity and CWD.

Cover picture: Fire patch above Leuk, VS, Switzerland on August 1, 2007.

Abstract

Christian Temperli (2007): Vegetation dynamics after forest fire in comparison to the pre-fire state. Diploma thesis, departement of Environmental Science ETH, Zürich.

A wild fire caused by arson destroyed in August 2003 300 ha of forest above the central alpine town of Leuk, Switzerland. The burned montane to sub-alpine forest ranged from 800 m.a.s.l. up to the timberline at 2100 m.a.s.l. at the south facing slope of the Valais main valley. As the succession processes along the large ecological gradient are of great interest in times of increased wild fire frequency they have been monitored since 2004. Additionally the local climate has been recorded by means of temperature and precipitation sensors installed in the fire patch. In line with this diploma thesis the vegetation data was compared to the pre-fire state and mainly analysed with respect to climate and fire intensity. Most species (re-)colonised the fire patch in the first two post-fire years. The highest species richness and vegetation covers were recorded at the most humid sites at high altitudes where temperatures and fire intensity were low. Until 2007 also the unfavourable hot and dry sites at lower altitudes where most of the soil was combusted by the fire were colonised by many species. The vegetation is still sparse at these sites though. The development of the species richness depends strongly on the scale in consideration. Whereas the species richness one year after the fire was surprisingly nearly as high as before the fire at a scale of 25 a it took four years to reach the pre-fire state on the small scale of 0.3 a. In the past two years high dominances of Epilobium angustifolium and Calamagrostis varia at higher altitudes and Conyza canadensi s and Rubus sp . at lower altitudes have developed. These species do not impede the regeneration of early colonising trees ( Populus tremula, Salix sp . and Betula pendula ). In contrary, the number of tree saplings found at the favourable sites at high altitudes was very high and regular succession climaxing in Norway spruce and Larch forest can be expected. Below 1200 m.a.s.l. the direction of the succession tends to Oak forest though.

Keywords: Biodiversity, forest, regeneration, climate, fire, Valais .

Contents

ABSTRACT ...... 3 CONTENTS ...... 4 1. INTRODUCTION ...... 6 2. METHODS ...... 9

2.1. STUDY AREA ...... 9 2.1.1. Geography ...... 9 2.1.2. Climate ...... 10 2.1.3. Soils ...... 11 2.1.4. Vegetation ...... 11 2.1.5. Fire impact on soils and vegetation ...... 12 2.2. DATA COLLECTION ...... 13 2.2.1. Vegetation data ...... 13 2.2.2. Geographical data ...... 14 2.2.3. Climate data...... 15 2.3. DATA PREPARATION ...... 17 2.3.1. Vegetation data ...... 17 2.3.2. Climate data...... 19 2.4. DATA ANALYSIS ...... 21 2.4.1. Statistical methods ...... 21 2.4.2. Used measures ...... 21 3. RESULTS ...... 25

3.1. BIODIVERSITY ...... 25 3.2. HERB LAYER COVER ...... 26 3.3. HETEROGENEITY OF THE VEGETATION ...... 27 3.3.1. Patchiness ...... 27 3.3.2. Similarity within plots ...... 28 3.4. SPECIES COMPOSITION ...... 29 3.4.1. Similarity between post- and pre-burn species composition ...... 29 3.4.2. Ecological groups ...... 30 3.5. DOMINANT SPECIES ...... 35 3.5.1. Dominance-diversity relation ...... 35 3.5.2. Species richness and Epilobium angustifolium cover ...... 36 3.5.3. Effect of Epilobium angustifolium cover on the cover of other species ...... 37 3.5.4. Regeneration of trees and Epilobium angustifolium cover ...... 37 3.5.5. Species richness and Rubus sp. cover ...... 38 3.5.6. Effect of Rubus sp. cover on the cover of other species ...... 38 3.5.7. Tree regeneration and Rubus sp. cover...... 38 3.6. TREES BEFORE AND AFTER THE FIRE ...... 38 3.6.1. Tree layer before the fire in 1996 ...... 38 3.6.2. Tree regeneration ...... 39 3.7. ELEVATION ...... 42 3.7.1. Species richness ...... 42 3.7.2. Herb layer cover ...... 42 3.7.3. Tree regeneration ...... 43 3.8. CLIMATE ...... 44

3.8.1. Climate model ...... 44 3.8.2. Thermal photography data ...... 45 3.8.3. Climate and species richness ...... 46 3.8.4. Climate and herb layer cover ...... 47 3.8.5. Climate and tree regeneration ...... 48 3.9. FIRE ...... 49 3.9.1. Fire and elevation ...... 49 3.9.2. Fire intensity and species richness ...... 49 3.9.3. Fire intensity and herb layer cover ...... 50 3.10. COARSE WOODY DEBRIS (CWD) ...... 51 4. DISCUSSION ...... 52

4.1. BIODIVERSITY ...... 52 4.1.1. Biodiversity before and after the fire ...... 52 4.1.2. Biodiversity and climate ...... 52 4.1.3. Biodiversity and fire intensity...... 52 4.2. VEGETATION COVER ...... 53 4.2.1. Developing of the herb layer cover from the pre-fire state to 2007 ...... 53 4.2.2. Vegetation cover and climate ...... 53 4.2.3. Vegetation cover and fire intensity ...... 54 4.2.4. Vegetation cover and height and CWD ...... 54 4.3. VEGETATION STRUCTURE AND SPECIES PROPAGATION ...... 55 4.4. SPECIES COMPOSITION ...... 55 4.5. DOMINANT SPECIES ...... 58 4.6. TREE REGENERATION ...... 59 4.6.1. Tree regeneration at different conditions ...... 59 4.6.2. Tree species ...... 59 4.7. REMARKS ON THE CLIMATE MODELS ...... 61 5. CONCLUSION ...... 63 6. ACKNOWLEDGMENTS ...... 64 7. REFERENCES ...... 65 APPENDIX...... A-1

A 1 SURVEY FORM ...... A-1 A 2 SITE INFORMATION OF PLOT LOCATIONS AND CLIMATE STATIONS ...... A-3 A 3 CORRECTIONS MADE TO SPECIES LIST AND RELEVÉS ...... A-5 A 4 NEW AND LOST SPECIES ...... A-9 A 5 SPECIES LISTS ...... A-12 A 6 TREE REGENERATION ...... A-20 A 7 CLIMATE MODEL GRAPHS AND R-OUTPUTS ...... A-21

1. Introduction

In August 2003 a wildfire caused by arson destroyed 300 ha of forest above the central-alpine town of Leuk in the canton of Valais, Switzerland. The exceptionally hot and dry summer weather in 2003 did its part so that the fire could proceed from just above Leuk at an elevation of 800 m.a.s.l. up to the timberline at 2100 m.a.s.l. Out of the 800 wildfires in the canton of

Valais in the past 100 years this was by far the largest (GIMMI et al . 2004) and according to

SCHÖNENBERGER UND WASEM (1997) the occurrence of wildfires in Switzerland increased recently. The lower part of the burned forest protected the town of Leuk from rock slide. To maintain the stability of the bare slopes measures have been taken but still a great interest exists to know how and how fast the forest regenerates. The burned area ranges over an elevation of 1300 m and therefore includes the montane and sub-alpine vegetation zone. In 1995 and 1996 the forested area between the localities of Albinen, Leuk and Guttet which includes the area burned in 2003 was surveyed and floristically well documented by

GÖDICKEMEIER (1998). She described the original vegetation as a continuous gradient characterised by three larger units: Pine-forest (Pinus sylvestris ) between 1000 and 1550 m.a.s.l., spruce-forest (Picea abies ) ranging from 1400 to 1800 m.a.s.l. and open larch-forest

(Larix decidua ) from above 1800 m.a.s.l. up to the timberline. The re-colonisation of plants into the burned area proceeds differently depending on the elevation and the fire intensity

(WOHLGEMUTH et al. 2005). The further study of the regeneration processes could therefore provide results that can help to understand the fire ecology of a large part of the central Alps. For these reasons the Swiss Federal Institute for Forest Snow and Landscape Research (WSL) decided in 2004 to start the research project “Forest fires in the Valais” (“Waldbrand im Wallis”) as part of the research program “Forest dynamics”. Several subprojects to assess the regeneration from different points of view have been set up: A representative vegetation monitoring, an assessment of the invertebrate diversity, the fire impact on soil properties, a local climate model and the continuous surveillance by means of aerial photographs.

(WOHLGEMUTH et al . 2005) The aim of the project is the assessment of the speed of re- colonisation and the ecological resilience with respect to biological and environmental factors such as mycorrhiza infestation and climatic influences.

In 2004, one year after the fire, sparse but surprisingly diverse pioneer vegetation was documented by KÜTTEL (2004) in line with his diploma thesis. When SERENA (2005) was on the fire patch during the field work of her diploma thesis in 2005, the second year after the

fire, the vegetation has exploded. The species richness even exceeded the pre-fire state on a large scale and the vegetation cover multiplied compared to the year before.

Also in the fourth year after the fire significant changes in the upcoming vegetation were expected. Therefore the stratified sampling plots defined by GÖDICKEMEIER (1998) have been surveyed again. To be able to explain developments by measured climatic environmental factors rather than proxy site factors such as elevation, aspect and slope as it has been done in the precious studies (KÜTTEL 2005 and SERENA 2005) the data of 12 climate stations installed on the fire patch in spring 2005 should be incorporated additionally. Except for that data on species and vegetation should be analysed by similar objectives as in 2005:

These are a) the development of the species composition, richness and abundance from the time before the fire until 2007 with respect to three plot scales. b) The species composition with regard to spatial variable climate, fire intensity and cover of burned trees and woody litter (CWD) and c) the regeneration of tree species over time and in respect to climate and CWD. Based on these objectives the following working-hypotheses have been set up:

• The biodiversity is higher in 2007 than in 2005 and it varies with climatic influences and fire intensity. I expect more species to have colonised the fire patch. As the fire intensity still affects the species diversity negatively and decreased with

altitude (WOHLGEMUTH et al. , 2005) the species richness increases with elevation. • The vegetation cover is denser than in 2005 and varies with climatic influences, fire intensity and CWD. Very hot and dry conditions impede the establishment of a dense herb layer. I expect the vegetation to be taller at sites of high CWD that seems to provide protection from strong wind, radiation and precipitation and therefore mitigates soil erosion. • At the small scale the vegetation became more heterogeneous (patchier) as more competitive species could supersede or overgrow other less competitive species. On a larger scale i.e. the whole study area a homogenisation of the species composition is expected as species have spread and re-colonised sparsely vegetated places like ridges and knolls. • The species composition changed compared to 2005. It is more similar to 1996 than it was in 2005. The species richness and cover of different ecological groups

(L ANDOLT 1991) will change compared to the previous years.

• Dominant species influence the species richness and composition and the regeneration of trees. Dense Rubus sp . thickets grew larger and impede other species in general and the establishment of tree saplings in particular. In contrast high abundances of Epilobium angustifolium seem to facilitate the establishment of trees. • There are more tree saplings and root sprouts in 2007 than in 2005 and their distribution is determined by temperature, humidity and fire intensity. There are more recorded tree saplings of early colonising tree species ( Salix sp., Populus tremula, Betula pendula ) than in 2005 expected. Heat and low humidity prevents the regeneration of trees. Furthermore a shift from the former montane Pinus sylvestris -forest towards a forest consisting of Oak species ( Quercus sp. ) is expected.

2. Methods

2.1. Study area

615000 616000 617000

55 71 57 ! ! <

80 ! 54 67 ! < 56 89 ! <

91 ! 53

104 ! 250 !!251 109 !

115 ! 257 !

131000 52 131000 51

! !!129 ! 262 107 ! 263 106 ! ! 138! 135 ! 139 147 ! 144 145 ! 148 ! 151 ! 49 ! !141 <269 ! 128 ! 50 152 !

272 !!273 ! ! 163 48 164 ! 150 < 47 277 !

130000 Legend 130000

615000 616000 617000 0250 500 1.000 ± Meters

Figure 1: Locations of the precipitation and temperature measuring climate stations and the survey plots defined by GÖDICKEMEIER (1998) on the forest fire patch above Leuk, VS (Reproduced with authorisation of Swisstopo: BA071737).

2.1.1. Geography

The forest fire patch is situated on the southern aspect slope of the east-west orientated Valais main valley. The study area is defined as the forested area that was burned above Leuk, VS, in 2003 (46°20’N, 7°39’E). The area comprises 300 ha of forest within the communities of Leuk, Guttet-Feschel and Albinen, VS, Switzerland (Figure 1). The 60 ha area designated as “Bannwald” in the lower part of the fire patch protected the community of Leuk from rock slide and avalanches. The area is laterally bordered by two ridges that most likely prevented the fire from spreading to the adjacent forest. The fire started below “Bannwald” above the 9

locality of Leuk Stadt at 800 m.a.s.l. and within several hours climbed up the channel like terrain to the timberline at 2100 m.a.s.l. The fire patch is accessible from several forestry and hiking tracks and the road from Thel to Albinen.

2.1.2. Climate

The climate at the valley bottom is characterised by high daily and annual temperature variations. Cold winters, hot summers, low precipitation and a distinct wind system are the main properties of the continental climate of the Valais valley at low elevations. With ascending altitude the continental climate fades to a typical high mountain climate of low mean annual temperatures and high precipitation (KIENAST 1985). The comparison of the climate graphs of the meteorological stations next to the study area illustrates this (Figure 2).

Figure 2: Climate graphs of Sierre and Leukerbad, VS (based on WERNER 1994, p 14).

The available precipitation and temperature measurements on the fire patch allow the following statements on the local climate:

30 Station 47 (1020 m.a.s.l) 25 Station 50 (1215 m.a.s.l)

20 Station 52 (1435 m.a.s.l)

15 Station 53 (1690 m.a.s.l) Precipitation [mm] Precipitation

10 Station 55 (1865 m.a.s.l) Station 58 (2085 m.a.s.l) 5

0 01.06.2005 08.06.2005 15.06.2005 22.06.2005 29.06.2005 06.07.2005 13.07.2005 20.07.2005 27.07.2005 03.08.2005 10.08.2005 17.08.2005 24.08.2005 31.08.2005 07.09.2005 14.09.2005 21.09.2005 28.09.2005

Figure 3: Daily precipitation measured from the 1.6.2005 to the 30.9.2005 at six climate stations set up along the elevation gradient in the fire patch. 10

In the period between Mai 2005 and April 2007 the hottest day on the fire patch was the 28.7.2005 with an average temperature of 26 °C at an elevation of 1020 m.a.s.l. and 18 °C at 2085 m.a.s.l. Ground temperatures around 50 °C have been measured throughout the whole study area though. The coldest day was on the 28.12.2005 when the daily mean at 1020 m.a.s.l was -8.5 °C and -17 °C at 2085 m.a.s.l. The precipitation sum in summer 2005 (June to September) at 1020 m.a.s.l. was 278 mm and 367 mm at an altitude of 2085 m.a.s.l.

35 Air temperature [°C] 35 Ground temperature [°C] 35 Soil temperature [°C] 30 30 30 25 25 25 Station 47 20 20 20 (1020m.a.s.l.) 15 15 15 Station 52 (1435m.a.s.l.) 10 10 10 Station 58 5 5 5 (2058m.a.s.l.) 0 0 0 01.06.2005 30.09.2005 01.06.2005 30.09.2005 01.06.2005 30.09.2005

Figure 4: Temperatures above ground (2 m), at surface (5 cm above ground) and in the soil (5 cm depth) during the vegetation period 2005 (1.6.2005 – 30.9.2005) on three altitudinal levels.

As displayed on Figure 4 the air, ground and soil temperatures show high daily variations. They are most distinct just above ground whereas the soil absorbs those fluctuations. The mean temperature on the fire patch during the vegetation period is 13.5 °C in the air, 15.5 °C at surface and 16 °C in the soil.

2.1.3. Soils

The bedrock in the study area is predominated by limestone (B URRI 1992) and at lower elevations Quaternary rock debris (GÖDICKEMEIER 1998) and moraine material (Tom Wohlgemuth, pers. comm.). The soils developed after the last ice age on carbonatic rocks. Before the burning between 900 and 1500 m.a.s.l. rendzina soils with the lime limit on the surface and therefore slightly alkaline topsoil were present. The spruce forest between approximately 1500 and 2000 m a.s.l. grew on cambisols topped by a slightly acidic humus layer. Near the timberline above 2000 m a.s.l. the cambisols were podsolised and the topsoil in the larch forest is acidic which only allowed the formation of a minor humus layer only

(GÖDICKEMEIER 1998 and WERNER 1994).

2.1.4. Vegetation

Before the fire the vegetation showed the typical characteristics of the montane (800 to 1500 m.a.s.l.) and the subalpine (1500 to 2200 m.a.s.l.) vegetation zones of the central part of the

Valais main valley as described in WERNER (1994) (Figure 5). Thus, at the very bottom of the 11

study area the colline oak fo rests merged in to the montane S cotch pine forest th at stretched to an approximate altitude of 1500 m.a.s.l. Norway s pruces and near the timberline E uropean larches formed then the subalpine forest. GÖDICKEMEIER (1998) structured the vegetation according to the dominating tree species and came to similar results. In summary, overlapping Scotch pine (Pinus sylvestris ), Norway spruce (Picea abies ) and E uropean larch ( Larix decidua ) forests formed a vegetational gradient ranging from 800 m.a.s.l. at the bottom of the study area up to the timberline .

Figure 5: Nord-south profile of the Valaisian Alps showing the theoretical altitudinal vegetation zones (Based on WERNER 1994, p. 27).

2.1.5. Fire impact on soils and vegetation

According to WOHLGEMUTH et al . (2005) the fire combusted 80% of the o rganic top soil. The mixture of remaining ash with mineral soil compartments raised the pH about 1.5 units. Nutritional elements essential for plant growth such as P, K, Mg, Ca, and N were oxidised by the fire and are now available for the upcoming vegetat ion (BERLI 1996). Furthermore chemical processes formed a hydrophobic top layer that promoted water runoff that in turn led to soil erosion.

Except for a few groups of trees mainly at the top of the study area the fire destroyed the whole tree layer. Most of t he burned trees still stand upright. In the lower part some tree s were felled perpendicular to the slope to prevent rock slide, avalanches and soil erosion . Mould attacked others (mainly Scotch pines) which were then felled by squalls though. The veget ation cover on the ashy soils was sparse one year after the fire. Nevertheless, t he total number of species at a scale of 25 a was surprisingly nearly as high as before the fire whereas at the small scale only half of the pre-fire species richness was reached. The species richness increased with elevation as it did in the original forest vegetation. KÜTTEL (2004) also found 12

the vegetation to be more similar to the pre-fire state at high elevations and explained it by the decreasing fire intensity in high altitudes. In the second year after the burning the species richness already exceeded the pre-fire state at a scale of 5 a. At lower altitudes the vegetation development in general and the tree regeneration in particular is thought to be influenced if not limited by drought and heat. The high fire intensity in the middle part of the fire patch between 1200 and 1600 m.a.s.l. is clearly visible in the vegetation development that lags behind strongly at these sites (SERENA 2005 and WOHLGEMUTH et al . 2005).

2.2. Data collection

2.2.1. Vegetation data

To be able to compare the data to the previous studies by SERENA (2005), KÜTTEL (2004) and

GÖDICKEMEIER (1998) the sampling design has been adapted.

2.2.1.1. Sampling design

GÖDICKEMEIER (1998) defined two sample designs. To be able to capture the full floristic range of her study area the whole ecological space had to be covered. To achieve this she applied a stratification method using the site parameters altitude, slope and aspect which have been calculated by means of a 25 m grid digital elevation model (SWISSTOPO ). The second sampling design was defined systematically and based on a 250 m grid. The coordinates were calculated based on the projected coordinate system Swiss Grid (CH1903+LV95).

In 2004, KÜTTEL surveyed the 53 samples located in the fire patch and marked them with a labelled T-profile bar for future surveyors. For analysis he eliminated 13 of these 53 sample plots (restricted sample) as they came to lie in unburned forest patches or edges, on the timberline or on tracks. According to KÜTTEL (2004) the fire did not affect the vegetation at these places enough so that it could be reckoned as a vegetational shift in comparison to the pre-fire vegetation. SERENA (2005) surveyed the plots of the restricted sample (n=40) and analyses in this study refer to this sample. The coordinates of the sampling sites are listed in the appendix (Table A 1). To reveal the relevance of the considered scale at each sample site, vegetation data on a sample plot was collected within concentric circles of 0.3, 2 and 5 a. In 1996 and 2004 an additional circle of 25 a was surveyed. As the cover and diversity of the vegetation has increased drastically in the past 3 years the workload would not have been manageable in the field season.

2.2.1.2. Survey methods

Three concentric circles spanning areas of 0.3 a, 2 a and 5 a, respectively, were delineated at each sample site using 30 m measuring tapes and flags. The following parameters were recorded:

• The average height and the cover of the tree (was except for one living tree inexistent), shrub, and herb layer in meters and percentages of the observed area, respectively. The

tree layer is made up of trees (phanerophytes as in LAUBER and WAGNER 2001) with a minimum height of 5 m. The shrub layer consists of trees and shrubs (nano- phanerophytes) and woody chamaephytes with a maximum height of 0.5 to 5 m whereas the herb layer includes all herbaceous and gramineous species. Phanerophytes, nano-phanerophytes and woody chamaephytes less than 0.5 m in height contributed to the herb layer.

• The presence and cover of all vascular plants and ferns according to BRAUN -

BLANQUET (1964): Plants were determined to the level of sub- or semi-species using

the following literature: HESS et al . (1998), LAUBER and WAGNER (2001), EGGENBERG

and MÖHL (2007) and KRÜSI (2006). If determination was not possible the next higher

taxon was recorded. The nomenclature refers to Flora Helvetica by LAUBER and

WAGNER (2001)

• CWD as a percentage of the observed area.

• The number of tree saplings and root sprouts distinguishable into one of the following height classes: 0-20 cm, 20-50 cm, 50-100 cm, 100-150 cm and >150 cm.

All field data were collected between the 25.6.2007 and the 10.8.2007 by Christian Temperli and Nicklaus Hardegger.

2.2.2. Geographical data

The coordinates of the sample sites were adopted from GÖDICKEMEIER (1998). At each sample site aspect and slope were measured by KÜTTEL (2004) and incorporated in this study too. The coordinates of the climate stations (cf. chapter 2.2.3.1. Climate station) were defined by Ueli Wasem whereas aspect and slope were derived from coordinates by means of the ® digital elevation model DTM-AV (SWISSTOPO ) using ESRI ArcMap™ 9.2.

2.2.3. Climate data

2.2.3.1. Climate station

In spring 2005 twelve climate stations were installed on the fire patch. As displayed on Figure 1 stations were placed at six elevation levels (two replications per level). On each level one is equipped with precipitation measuring instruments additionally to the digital iButton ® temperature data loggers. The iButtons ® of the type DS1922L, programmable sensors with a built in battery, suit very well for temperature measurements at a high number of different locations and over long time periods as they work automatically and are relatively cheap in ® acquisition as well. According to GEHRIG (2004) this type of iButton guaranties a measurement accuracy of 0.5 °C in a temperature range of -10 °C to 65 °C. The air temperature is measured in 2 m height underneath a shelter by two iButtons ®, the ground temperature 5 cm above ground by one iButton ® facing upwards and another facing downwards and the soil temperature is measured in 5 cm depth with one iButton ® (Figure 6 and Figure 7).The temperature and precipitation sums are recorded hourly.

Figure 6: Temperature and precipitation measuring Figure 7: iButtons® facing upwards (left) and station located in the fire patch above Leuk, VS (by G. downwards (right) measuring the ground Schneiter, 5.10.2005). temperatures in the fire patch above Leuk, VS (by G. Schneiter, 5.10.2005). 2.2.3.2. Thermal photography

On the 15.8.2007 Tom Wohlgemuth and Daniel Scherrer shot between 10 and 15h every minute one thermal photograph of the fire patch from the top of the opposite mountainside (Illhorn, 46°15’46”N, 7°36’58”O). The sky was cloudless during the whole day (Tom Wohlgemuth, pers. comm.).

615000 616000 617000 The thermal photographs were geographically referenced using ESRI®

!! ! 132000 132000 ! ! ArcMap™ 9.2 (Figure 8). Landmarks like !

! ! road intersections, roofs, rocks and forest ! !! ! ! edges visible on an already geo-referenced !

131000 ! 131000 ! !!! ! aerial photograph of 2005 and on the ! ! ! ! ! ! ! ! ! ! ! ! ! ! 1:25:000 topographical map (SWISSTOPO ) !!! ! ! Legend ! ! Gödickemeier plot locations that could clearly be allocated to structures

130000 Fire patch 130000 Temperature [°C] High : 27,115 on the thermal photograph served as Low : 12,901 control points. Having selected 15 points 615000 616000 0617000250 500 1.000 ± Meters an automatic spline transformation was Figure 8: Geo-referenced thermal image shot from applied to the thermal photographs so that “Illhorn” by T. Wohlgemuth and D. Scherrer showing the ground temperatures of a large part of the fire pixels with temperature information fitted patch on the 15.8.2008 at 13.00h with a resolution of 7meters (Reproduced with authorisation of SWISSTOPO : to the underlying projected coordinate BA071737). system “Swiss Grid” (CH1903+LV95) with a resolution of approximately 7 m.

2.2.3.3. Available data

Table 1: Gaps in temperature time series. Listed are the For this thesis the hourly temperatures of affected stations (Figure 1) and data loggers: Air temperature (ATA, ATB), ground temperature iButton® all stations and data loggers from the facing upwards (GTU) and downwards (GTD) and soil temperature (ST). 21.5.2005 to the 30.4.2007 and daily

Station number/data No data available from precipitation records from the 21.5.2005 to logg er the: 51/ATA, ATB, GTU, GTD, 1.10.2005 – 4.10.2005 the 31.5.2006 have been available. The 60 51/GTDST 21.6.2006 – 30.4.2007 52/ST 22.6.2006 – 30.4.2007 (5 data loggers on twelve stations) 52/GTU 5.10.2005 – 30.4.2007 temperature and the six precipitation time 54/GTU 29.9.2005 – 30.4.2007 53/GTD 31.3.2007 – 30.4.2007 series were checked for gaps and measuring errors. Table 2: Time periods of lacking or implausible precipitation sums. The gaps in the temperature measurements Station number No data on the: are according to Gustav Schneiter (pers. 53, 55 31.12.2005 and 16.2.2006 comm.) due to yet unsolved technical 58 31.12.2005 – 19.2.2006 53 4.3.2006 – 21.3.2006 problems reading the data from the loggers 53 9.5.2006 – 11.5.2006 to the storage device (Table 1). 55, 58 4.3.2006 – 31.5.2006 16

The precipitation time series were compared in order to find time periods with lacking data and to check plausibility in precipitation sums (Table 2).

The measuring errors of the precipitation sensors concerned the top three stations above 1690 m.a.s.l. and occurred in wintertime. Due to snow pressure the precipitation collecting containers were damaged and the measurements were either stopped or falsified (Gustav Schneiter, pers. comm.). The presence of snow was also visible in the temperature time series during winter and spring. Ground and soil temperature loggers measured temperatures around 0 °C for days to weeks due to the insulating effect of snow cover.

After revision, temperature and precipitation time series were complete for all stations and data loggers from the beginning of the measurements till 29.9.2005. The air temperature was recorded at all stations for the whole measuring period except for a minor interruption of four days at station 51 (Table 1).

In addition, the ground temperatures covering the study area continuously were at hand. With respect to this spatial data, the south-eastern part, the tip in the very south and some rather large part in the North and West of the fire patch are excluded (Figure 8).

2.3. Data preparation

2.3.1. Vegetation data

2.3.1.1. Digitalisation and corrections

The field data available on paper forms (Figure A 1) were digitised and vegetation tables were created using VEG 4.12 1. For further processing the vegetation tables were exported to Microsoft ® Office Excel ® 2007. In a first step the original vegetation tables of 1996, 2004, 2005 and 2007 were joined. Then the list of species determined during the four survey periods was corrected: The determined taxa were brought to the same level. Taxa according to

WELTEN and SUTTER (1982, 1984) and WAGNER (1994) not present in the study area were replaced by a reasonable substitute. The list of species recorded on the fire patch by 2 WOHLGEMUTH et al. (based on the survey of 153 quadrates of 200 m from 2004 to 2006) served as reference. As the species list of the previous survey was available for each plot uncertainties with respect to doubtful determinations could be tracked down directly in the

1 Version 4.12, 5.9.2004, developed by Hans Märki, Märki Informatik (www.maerki.com). The software is free of charge in terms of the “GNU Gerneral Public License”, cf. www.gnu.org. 17

field. In a second step the four relevés of each plot were compared. Incompletely or doubtfully determined species were corrected.

Furthermore the species aggregates “ Salix appendiculata/caprea Grp. ” and “ Epilobium montanum/collinum Grp.” were defined and the “ Hieracium murorum Grp.” aggregate was adapted from GÖDICKEMEIER (1998). The following specifications explain the introduction of these aggregates:

Salix appendiculata/caprea Grp. was defined because GÖDICKEMEIER (1998) and KÜTTEL

(2004) determined Salix caprea throughout the study area; SERENA (2005), I and Nicklaus Hardegger (2007) determined most likely the same individual trees as Salix appendiculata ; S. caprea and S. appendiculata show the same morphological characteristics together with S. bicolor , S. Starkeana and S. laggeri which can be excluded from the study area geographically though (HESS et al. 1998, WELTEN and SUTTER 1982, 1984 and WAGNER , 1994).

Epilobium montanum/collinum Grp . was defined as Epilobium montanum and Epilobium collinum were not distinguishable with a satisfactory certainty.

Species of the genus Hieracium similar to Hieracium murorum were aggregated to

Hieracium murorum Grp . by GÖDICKEMEIER (1998). The affected species and the aggregation statements are listed in Table A 3 besides all corrections made to the original species lists.

The corrections of the individual relevés are listed in Table A 4.

After all revisions a final vegetation table uniting the 0.3, 2 and 5 a relevés of 1996, 2004, 2005 and 2007 served as basis for further vegetation analysis.

2.3.1.2. Ecological grouping

To analyse changes in species compositions plant species were allocated to ecological groups as used in the Red List of threatened ferns and flowering plants (LANDOLT 1991). This classification is rather rough as a lot of species populate a wide range of different ecological niches but should nevertheless be adequate enough to show the change in habitat characteristics formed by the fire and the subsequent succession process. Within this study neophytes, crop plants and plants that could not be determined to the species level were

pooled to an additional group called “Others”. Group specific properties are described in

LANDOLT (1991) and SERENA (2005).

2.3.1.3. Cover transformations

Table 3: Transformation of the ordinal Braun-Blanquet As the cover of single plant species had cover values to percentages of the observed area. been estimated according to the ordinal Braun-Blanquet Percentage of the cover value observed area Braun-Blanquet scale the values were 0 0 r 0.05 transformed to the percentage of the + 0.5 observed area as shown in (Table 3). Those 1 3 percentages were used to calculate 2 15 3 37.5 abundances of individual species and the 4 62.5 cover of ecological groups. As a second 5 87.5 measure of the herb layer cover accumulated cover percentages of all species in the herb layer of an observed area were used (accumulated B-B.).

2.3.2. Climate data

Due to the limited data availability and due to the fact the growing season and therewith most climate sensitive season for plants being from April to October (WERNER 1994) temperature and precipitation data from the 1.6.2005 to the 30.9.2005 were used for further analysis. To this period of time it is referred as “vegetation period” in this thesis.

2.3.2.1. Bioclimatic parameters

The temperature time series of the vegetation period 2005 have been aggregated to a set of 28 parameters such as mean temperatures, degree sums, maxima, minima and number of heat hours (above 25 and 40 °C). The two air temperature measurements were averaged; same holds for the two ground temperature measurements of upwards and the downwards facing iButtons ®. An explorative procedure of correlating the parameters among each other and to elevation, aspect and slope was conducted to eliminate those of bad topography dependency and redundant information content. This resulted in a set of four temperature parameters presented in Table 4.

Besides the precipitation sum of the vegetation period (P) the ratio of precipitation and potential evapotranspiration (P/PE) was used as a parameter for humidity: Following the instructions of THORNTHWAITE and MATHER (1957) PE was calculated from monthly air temperature means and geographical latitude for each station. BIGLER et al. (2006) used this rather simple measure in their study on drought effects on Scots pine ( Pinus sylvestris ) stands in the Valais, too, and found it appropriate even after comparison with more sophisticated measures.

Table 4: Bioclimatic parameters used for modeling.

Parameter Unit Mean air temperature of the vegetation period °C Mean ground temperature of the vegetation period °C Mean soil temperature of the vegetation period °C Number of hourly measures > 40°C Precipitation sum of the vegetation period mm Precipitation/potential evapotranspiration of the vegetation period (P/PE)

2.3.2.2. Climate models

In a first step regression models were calculated using elevation and aspect as predictors. The kind of relations of the climate parameters with the site parameters were evaluated by consulting scatter plots and searching for the best describing regression models whereas p- values and determination coefficients (R 2) served as quality criterion.

Secondly the climate parameters were spatially interpolated to the sample site locations using the calculated model formulas.

As spatially continuous temperature values of the study area were available a regression model with the temperatures of the five heat pictures as dependent and elevation and aspect determined by means of the digital elevation model DTM-AV as explanatory variables were calculated for improvement of the climate models based on the climate measuring stations. The spatially high resolution of temperature data were expected to allow a more accurate modelling of the temperature-aspect relation.

2.4. Data analysis

2.4.1. Statistical methods

The used t-tests and linear regression model fits were computed using the language environment R version 2.5.1 2. All tests were conducted on the 95% confidence level ( α=0.05).

2.4.2. Used measures

2.4.2.1. Biodiversity

As a measure of biodiversity the species richness, Shannon’s diversity index and the evenness were applied. The species richness is defined as the number of species on a given area and Shannon’s diversity index and the evenness were calculated as follows:

Shannon’s diversity index:

= ln () : Shannon’s diversity index : proportion of the cover of species i on the herb layer cover (accumulated B-B.) as a measure of the relative abundance.

S: Number of species

Evenness:

= ln() E: Evenness

: Shannon’s diversity index S: Number of species

The evenness is a measure of how evenly abundances of single species are distributed within a species community. It ranges from Emin =0 to Emax =1. Emax stands for the hypothetical case of

a uniform distribution of all species in a community and Emin would be a community of one dominating species with the abundance of other species approximating zero.

Shannon’s diversity index can be expressed as

. = ln() × This measure of diversity is consequently a combination of the species richness and the evenness of the distribution of the species abundances.

2.4.2.2. Similarity measures

To compare species compositions the coefficient of van der Maarel and Jaccard’s coefficient were used as a measure of similarity. They were calculated as follows:

Van der Maarel’s coefficient:

= + − : Van der Maarel’s coefficient a, b : Vectors representing relevé a that is to be compared with relevé b. Because the vegetation data is available as vegetation table vector a and b have the same length and contain cover values of the species i present and zeros for species not present in the respective relevé.

Jaccard’s coefficient:

= + + : Jaccard’s coefficient m: The number of species only present in relevé m. n: The number of species only present in relevé n. j: The number of species present in both relevés m and n.

Van der Maarel’s coefficient accounts for both presence and abundance (percentage of the Braun-Blanquet cover value) of the species of two communities whereas Jaccard’s coefficient only considers species presences. 22

2.4.2.3. Measures of vegetation heterogeneity/homogeneity

A lot of plant species propagate stoloniferously and form dense lawns, cushions or even thickets. Some of them reach densities that exclude other species. In the upcoming vegetation thickets of Rubus sp . and large patches of tall-growing Epilobium angustifolium established. Furthermore stands of Calamagrostis varia , Calamagrostis villosa and Brachypodium pinnatum aggr . and cushions of Saponaria ocymoides, Securigera varia and Helianthemum nummularium s.l. were noticed on the fire patch just to name some examples. These patches and cushions extend over areas of half a meter to several meters in diameter. As noticed during the fieldwork the 0.3 a plot circle could be dominated by only one or two of those patches whereas only a small amount of other species was found in or next to them and a lot more species were found in the next larger circle of 2 a in area. Therefore this small scale heterogeneity (patchiness) of the vegetation was measured by the percentage of the number of species found on 0.3 a on the number of species found on 2 a. The smaller that fraction the higher the heterogeneity is and vice versa : If all species would be distributed perfectly even the number of species on the 0.3 a and the 2 a plot circle would be the same or the percentage value 100.

The large scale (regarding the whole fire patch) homogeneity of the vegetation was measured by the similarity between the 40 plots. The more evenly species are distributed across the fire patch or, in other words, the larger the fraction of the fire patch’s area species could colonise the more similar the relevés would be within each other. As similarity measure Jaccard’s coefficient has been used. Similarity matrices of 40 rows by 40 columns have been calculated and then the resulting 1600 values were averaged. The resulting values of each year were compared. The higher the mean similarity the higher is the homogeneity in terms of species composition.

2.4.2.4. Fire intensity

WOHLGEMUTH et al. (2005) measured the depth of the ash layer in 2004 as an indicator of fire intensity. Unfortunately the systematically aligned sample plots (n=153) used within their study does only correspond partially with the sample design used in this thesis. For this reason the herb layer cover differences between 2004 and 2005 were used as an indirect fire intensity measure that considers plant colonisation being related to fire intensity. Due to the lack of top soil and seed bank that was burned at various extents by the fire (WOHLGEMUTH et al. 2005)

the vegetation would be less developed in 2005 on plots where the fire was more intense as on plots where low fire intensities prevailed (SCHIMMEL and GRANSTRÖM 1996).

− = sin 1 − 100 F: Fire intensity

: Accumulated percentages of the Braun-Blanquet herb layer species cover of , 2004 and 2005, respectively.

The transformation was applied to gain normally distributed data. sin ()

3. Results

The development of the biodiversity, herb layer cover, heterogeneity, species composition, dominant species and tree regeneration from the pre-fire state to 2007 is presented first (Chapter 3.1 to 3.6). The dependencies of species richness, herb layer cover and tree regeneration on elevation, climate and fire intensity are shown in chapters 3.7 to 3.9. Finally, the impact of CWD on the herb layer cover and height is shown in chapter 3.10.

3.1. Biodiversity

The mean species richness on the sampling plots was approximately halved one year after the fire. Until 2007 the species richness recovered to an extent that it reaches the values of 1996 on the 0.3 a plot circle and exceeds the 1996 values at the larger scales. Figure 9 and Figure 10 show the rise of the species richness i.e. the number of species after the fire. The species richness is highly depending on the scale in consideration i.e. the plot area. It increases with larger plot area. At the small scale of 0.3 a the mean number of species of 2007 does not differ significantly from the one in 1996. In 2005 this could only be stated regarding the 2 a plot area where the mean number of species did not differ significantly from the one in 1996. The majority of new species colonised the plots between 2004 and 2005 (58, 80 and 81 species per 0.3, 2 and 5 a sample). From 2005 to 2007, the number of species joining the established flora was much smaller (19, 15 and 20 species, respectively).

1996 280 2004 260 1996 2005 242 238 2004 2007 227 2005 55.1 218 2007

46.1 179 171 40.8 40.1 162 152 147 34.2 31.5

23.9 94 Numberspecies of 18.7 19.9 Meanspecies number of 14.8 16

7.5 0 50 100 150 200 250 300 0 20 40 60 80 abca abac abcd 0.3a 2a 5a 0.3a 2a 5a

Plot area Plot area

Figure 9: Mean number of plant species in 1996, 2004, Figure 10: Pooled numbers of species before (1996), 2005 and 2007 on 0.3, 2 and 5 a labeled above columns. one (2004), two (2005) and four (2007) years after the Error bars indicate standard errors of means (SEM) and fire on 40 plots of 0.3, 2 and 5 a. characters indicate significant differences between years (paired t-test, n=40). 25

The species recorded the first time each year and the species that have been lost from one year to another are listed on Table A 5 et sqq .

The diversity measured with Shannon’s index in 2007 is higher than in 2005 on all plot sizes (Figure 11). Same as with species richness the diversity exceeded the values of 1996 expect for the 0.3 a relevés where both reached the same level. Shannon’s diversity was in contrary to the species richness also on 2 a higher in 2005 than in 1996. On 2 and 5 a the evenness was higher in 2005 than in 2004. From 2005 to 2007 the evenness did not change significantly. On 5 a it even tended to decrease slightly. The very high variations especially in 2004 are due to the fact that on some plots the number of species was zero or one which resulted in values of evenness of 1 or 0, respectively.

5a 2a 0.3a

Mean evenness Mean 5a 2a

Mean Shannon-index Mean 2a 0.3a species Mean richness 0.3a

a b c d a b c d a a b b a b c d a b a c a a b b 0a 1 2b 3c 4 a 0 10a 20 30 40b 50 60 c a a a a a 0.70 0.75 0.80 0.85 0.90 0.95 1.00

1996 2004 2005 2007 1996 2004 2005 2007 1996 2004 2005 2007

Figure 11: Mean Shannon-index, mean species richness and mean evenness and in 1996, 2004, 2005 and 2007 on 0.3, 2 and 5 a. Error bars: SEM, characters: sign. diff. years (paired t-test, n=40). 3.2. Herb layer cover

On all scales the mean estimated herb layer cover and the accumulated B-B. cover (and therefore the cover estimation methods) do not differ significantly (Figure 12). For analyses the accumulated B-B. covers were used as it was done in the previous study by SERENA 2005.

1996 Mean estimated cover 2004 79.8 Mean accumulated B-B. cover 2005 72.1 70.9 2007 64.4 54.4 56

33 Cover[%] Cover[%] 32.4 25.9

3.4 4.2 5.1 0 20 40 60 80 100 0 20 40 60 80 100 a a a a a a abca abca abca 0.3a 2a 5a 0.3a 2a 5a

Plot area Plot area

Figure 12: Comparison of the cover estimation Figure 13: Barplot showing the mean accumulated B-B. methods. Black: Mean estimated herb layer cover and covers of 1996, 2004, 2005 and 2007, respectively. Error white: Mean accumulated B-B. covers in 2007 on 0.3, 2, bars: SEM, characters: sign. diff. years (paired t-test, and 5 a, respectively. Error bars: SEM, characters: sign. n=40). diff. years (paired t-test, n=40). Figure 13 shows the development of the herb layer cover. The mean cover tends to be higher if estimated for larger scales. The mean cover of the herb layer in 1996 was 54, 72 and 80%, respectively. After the fire only 3 to 5% of the ground was covered with vegetation. In 2005 the mean herb layer cover was 26, 33 and 32% which is about the eightfold of the previous year. Two years later in 2007 the mean cover has duplicated again and showed values of 56, 64 and 71%, respectively. In 2007 the herb layer cover did not differ significantly anymore from the one in 1996.

3.3. Heterogeneity of the vegetation

3.3.1. Patchiness

As displayed in Figure 14 the ratio of species richness on 0.3 a of the species richness on 2 a in 2004 is smaller than in 1996. The vegetation has therefore become patchier as before the fire in 1996. In 2005 the percentages tended to be smaller as in 2004. The differences are not significant though. Two years later, the ratio is higher again and not significantly different to the values in 2004. The vegetation in 2007 is therefore less patchy as in 2005 and as patchy as in 2004.

1996 2004 2005 2007 0 20 40 60 80 100 a b b c c 0.3a species richness fraction of 2a [%] 2a speciesof 0.3a richness fraction 2a-0.3a

Figure 14: Ratio [%] of species richness at small plots (0.3 a) and medium plots (2 a) in 1996, 2004, 2005 and 2007. Smaller percentages reflect higher patchiness. Error bars: SEM, characters: sign. diff. years (paired t-test, n=40).

3.3.2. Similarity within plots

Figure 15 shows the homogeneity of the species composition in terms of similarity within 40 relevés of 0.3, 2 and 5 a in 1996, 2004, 2005 and 2007. In general the vegetation is more homogenous the larger the plot area is taken in account. After the fire in 2004 the species composition on the fire patch was less homogenous as in 1996. In 2005 it became more homogenous again and exceeded the values of 1996 regarding the 2 and 5 a relevés. Considering the 0.3 a relevés the vegetation is more homogenous than in 2004 though but less as in 1996. In 2007 the species composition is more homogenous than in 2005 but the similarity between the 0.3 a relevés still does not exceed the 1996 state.

5a 2a 0.3a Mean Jaccard coefficient Jaccard Mean a b c d a b c d a b c d 0.0 0.1 0.2 0.3 0.4

1996 2004 2005 2007 Year

Figure 15: Similarity within the 40 relevés in 1996, 2004, 2005 and 2007 on 0.3, 2 and 5 a shown as mean Jaccard’s coefficients. Error bars: SEM, characters: sign. diff. years (paired t-test, n=1600).

3.4. Species composition

3.4.1. Similarity between post- and pre-burn species composition

Considering van der Maarel’s similarity on Figure 16 (left) the species composition was in 2005 more similar to thepre-fire state than in 2004. In 2007 the vegetation was equally similar to 1996 as in 2005 regarding the 0.3 and 2 a relevés. On 5 a the similarity to 1996 was smaller in 2007 than in 2005.

Jaccard’s similarity (Figure 16, right) undergoes no significant change from 2004 to 2007 regarding 2 and 5 a plot circles. On 0.3 a, though, the species composition in 2007 is more similar to 1996 than in 2005.

5a 2a 0.3a

5a 2a 0.3a Mean Jaccard coefficient Jaccard Mean

Mean van der Maarel coefficient Maarel der vanMean a b c a a a a b b a a a a b b a a b 0.00 0.05 0.10 0.15 0.20 0.25 0.00 0.05 0.10 0.15 0.20 0.25

1996 to 2004 1996 to 2005 1996 to 2007 1996 to 2004 1996 to 2005 1996 to 2007

Period of time Period of time

Figure 16: Similarity between the relevés of 1996 and 2004, 2005 and 2007, respectively, shown as mean van der Maarel’s coefficients (left) and mean Jaccard’s coefficients (right) on 0.3, 2 and 5 a. Error bars: SEM, characters: sign. diff. years (paired t-test, n=40).

3.4.2. Ecological groups

In 1996 woodland plants, mountain plants and dry grassland plants were the most species rich groups (Figure 17) with 75, 54 and 50 species, respectively. The remaining groups were represented with relatively small numbers of species. After the fire in 2004 the number of woodland, mountain and dry grassland plants was decreased to 49, 27 and 36 species, respectively. The ruderal plants more than doubled in species richness (27 species). The species richness of the remaining groups did not change much (Figure 18). Two years after the fire in 2005 the species richness of all groups was higher than in 2004. The woodland and dry grassland species reached a similar species richness as in 1996 (68 and 45 species, respectively). Mountain, lowland pioneer and ruderal plants were then represented with 40, 24 and 44 species, respectively. In 2007 the number of woodland, mountain, dry grassland and ruderal plant species was increased to 69, 45, 55 and 48 species, respectively. The species richness of other groups remained constant.

75 1996 2004 69 68 2005 2007

55 54

50 49 48

45 45 44

Number of species of Number 27 27

24 24 22 21

17 15 14 13 12 12 11 10 8 7 7 5 3 0 10 20 30 40 50 60 70 80 Woodland plants Dry grassland plants Low land pioneer plants Others Mountain plants Plants of rich pastures Ruderal plants Wetland plants

Ecological group

Figure 17: Pooled number of species of different ecological groups (LANDOLT 1991) in 1996, 2004, 2005 and 2007 on 40 plots of 5 a. Undetermined species were allocated to “Others”.

Change in number of species Change in cover [%] -30 -25 -20 -15 -10 -5 0 -60 -50 -40 -30 -20 -10 0

1996 to 2004 1996 to 2004

Ruderal plants 14 -0.12 Ruderal plants Plants of rich pastures 2 -1.78 Plants of rich pastures -2 Low land pioneer plants -3.16 Low land pioneer plants -2 Wetland plants -0.09 Wetland plants -4 Others -1.54 Others -14 Dry grassland plants -8.94 Dry grassland plants -26 Woodland plants -52.13 Woodland plants -27 Mountain plants -6.95 Mountain plants

2004 to 2005 2004 to 2005

Woodland plants 19 Woodland plants 6.13 Ruderal plants 17 Ruderal plants 5.62 Mountain plants 13 Mountain plants 1.91 Low land pioneer plants 12 Low land pioneer plants 5.7 Dry grassland plants 9 Dry grassland plants 5.89 Plants of rich pastures 5 Plants of rich pastures 1.29 Wetland plants 4 Wetland plants 0.1 Others 2 Others 0.6

2005 to 2007 2005 to 2007

Dry grassland plants 10 Dry grassland plants 11.61 Mountain plants 5 Mountain plants 0.25 Ruderal plants 4 Ruderal plants 6.3 Woodland plants 1 Woodland plants 6.43 Others 1 -0.11 Others Low land pioneer plants 0 Low land pioneer plants 12.2 Wetland plants 0 Wetland plants 0.21 -1 Plants of rich pastures Plants of rich pastures 1.69

0 5 10 15 20 0 3.25 6.5 9.75 13 Change in number of species Change in cover [%]

Figure 18: Change in number of species (left) and cover (right) of ecological groups (LANDOLT 1991) from 1996 to 2004, 2004 to 2005 and 2005 to 2007, respectively, on 5a. Undetermined species were allocated to “Others”.

Figure 19 shows the sums of covers of the species allocated to ecological groups. In 1996 the forest floor was mainly covered by woodland plants and to small extents with mountain, dry grassland and lowland pioneer plants (53.5, 7.2, 10.9 and 3.9 %, respectively). In 2004 the cover of all groups was very low. Relatively high covers showed woodland, dry grassland, and pioneer plants (1.4, 2 and 0.8%, respectively). In 2005 the covers of woodland, dry grassland, lowland pioneer and ruderal plants was higher than the year before (7.5, 7.9, 6.5 and 5.9% respectively) whereas covers of other groups remained relatively low. In 2007 the cover of the dominating woodland, dry grassland, lowland pioneer, and ruderal plants was again increased compared to 2005 with 14, 19.5, 18.7 and 12.2%, respectively. The cover of other groups remained low again.

1996 2004 53.5 2005 2007 Cover[%]

19.5 18.7

14 12.2 10.9

7.9 7.5 7.2 6.5 5.9 3.9 3.1 2.2 2.4 2 1.4 1.9 1.4 1.8 0.8 0.9 0.7 0.3 0.1 0.4 0.3 0.3 0.1 0 0.1 0.4 0 10 20 30 40 50 60 Woodland plants Dry grassland plants Low land pioneer plants Others Mountain plants Plants of rich pastures Ruderal plants Wetland plants

Figure 19: Averaged accumulated B-B. covers of species with respect to different ecological groups (LANDOLT 1991) in 1996, 2004, 2005, and 2007 found on 40 plots of 5 a. Undetermined species were allocated to “Others”.

Before the fire the species richness was mainly consisted of woodland, mountain and dry grassland plants (Figure 20). In 2004 14 new ruderal species could colonise the fire patch (Figure 18). In the subsequent years the species richness proportions of the ecological groups remained relatively stable.

100% 100% Wetland plants 90% 90% 80% 80% Others 70% 70% Ruderal plants 60% 60% 50% 50% Lowland pioneer plants 40% 40% Plants of rich pastures 30% cover 30% 20% 20% Dry grassland plants of species of 10% 10% Mountain plants 0% 0%

Proportion Proportion of herb layer Woodland plants 1996 2004 2005 2007 1996 2004 2005 2007 Proportion Proportion of total number

Year Year

Figure 20: Species richness split into Figure 21: Accumulated B-B. covers split into ecological groups ecological groups of 1996, 2004, 2005 and (LANDOLT 1991) in 1996, 2004, 2005 and 2007 of 40 plots of 5 a. 2007 (LANDOLT 1991) of 40 plots on 5 a. Undetermined species were allocated to “Others”. Undetermined species were allocated to “Others”.

Before the burn (1996) woodland plants were most abundant. Furthermore mountain and dry grassland plants contributed to the herb layer. Species of other groups were only marginally represented. After the fire in 2004 the vegetation was dominated by dry grassland, woodland and lowland pioneer plants whereas dry grassland plants were in terms of coverage most abundant. Two years after the fire (2005) the cover proportion of ruderal plants was much higher than 2004. The cover proportion of lowland pioneer plants increased gradually from 2004 to 2007.

In 1996 the species richness of woodland and dry grassland plants were evenly distributed along the elevation gradient (Figure 22). More mountain plant species occurred at high altitudes. Four years after the fire woodland, dry grassland and ruderal plants showed a similar and along the elevation gradient evenly distributed species richness. Same as before the fire mountain plants were mainly present at high altitudes.

1996 2007

Wetland plants Others Ruderal plants Lowland pioneer plants Plants of rich pastures Dry grassland plants Number of species Number of Mountain plants

0 20 40 60 80 100 Woodland plants

1000 1200 1400 1600 1800 1000 1200 1400 1600 1800

Elevation [m.a.s.l]

Figure 22: Number of species per ecological group (LOWESS-smoothed, f=0.5) on 5 a in 1996 and 2007 vs. elevation (n=40).

Before the fire woodland plants and dry grassland plants made up to herb layer at altitudes below 1500 m.a.s.l. At higher altitudes mountain plants replaced woodland plants. Four years after the fire dry grassland plants were abundant at all altitudes. Ruderal plants occurred predominantly at lower and lowland pioneer plants at higher altitudes.

1996 2007

Wetland plants Others Ruderal plants Lowland pioneer plants Plants of rich pastures Cover[%] Dry grassland plants Mountain plants

0 20 40 60 80 100 Woodland plants

1000 1200 1400 1600 1800 1000 1200 1400 1600 1800 Elevation [m.a.s.l]

Figure 23: Accumulated B-B. covers per ecological group (LOWESS-smoothed, f=0.5) on 5 a in 1996 and 2007 vs. elevation (n=40).

The evolution in abundance of the most abundant species from the pre-fire state to 2004, 2005 and 2007 are shown in Figure 24. The most striking change in cover showed Epilobium angustifolium and Saponaria ocymoides . Before the fire E. angustifolium was only present on 17.5% of the plots with a mean cover of 0.04% (cf. also Table A 8 et sqq. ). It was the most dominant species on the fire patch in 2005 and covered 3.4% of the ground. In 2007 its average cover was more than tripled to 13.6% and it was present on 97.5% of the plots. Having spoken of lowland pioneer plant covers in 2005 and 2007, it referred to E. angustifolium and Calamagrostis varia that contributed together most of this groups coverage (85 and 89%, respectively). Whereas in 1996 Arctostaphylos uva-ursi , Carex humilis and Melampyrum sylvaticum were the most dominant woodland species this ecological group was in 2007 mainly represented by Rubus idaeus , Rubus caesius and Rubus saxatilis with 55 % of the woodland plants’ cover. The ruderals Conyza canadensis , Cirsium arvense and Arenaria serpyllifolia aggr. that were little dominant in 1996 became important two years after the fire in 2005. In 2007 this group was predominantly represented by Conyza canadensis that was present on 82.5% of the plots with an average cover 4.4%. The dry grassland species Saponaria ocymoides , Euphorbia cyparissias (in 2004 the most dominant species), Brachypodium pinnatum aggr. and Teucrium chamaedris accounted for cover of dry grassland species with 65%. S. ocymoides was already frequent (presence: 60%) before the fire but only covered 0.5% of the forest floor whereas in 2007 it was present on 92.5% of the plots with an average cover of 10.4%.

1996 2004 2005 2007 Mean species cover [%] 0 5 10 15 20 0 2 0 5 0 5 10 15 17

Arctostaphylos uva-ursi ( W ) 14.64 0.01 0.32 0.34 Carex humilis ( W ) 12.35 0.05 0.24 0.3 Melampyrum sylvaticum ( W ) 4.64 0 0.01 0.06 Calamagrostis varia ( P ) 2.94 0.46 2.1 3.08 Melampyrum pratense ( W ) 2.81 0 0 0 Calamagrostis villosa ( W ) 2.4 0.07 0.1 0.19 Hieracium murorum Grp. ( W ) 1.9 0.02 0.16 0.2 Euphorbia cyparissias ( D ) 1.54 0.59 1.11 0.86 Brachypodium pinnatum aggr. ( D ) 1.54 0.17 0.68 1.07 Teucrium chamaedrys ( D ) 1.38 0.22 0.28 0.26 Laserpitium siler ( M ) 0.9 0.04 0.53 0.6 Saponaria ocymoides ( T ) 0.48 0.42 1.65 10.43 Rubus idaeus ( W ) 0.47 0.03 0.59 3.86 Rubus saxatilis ( W ) 0.45 0.46 0.85 0.85 Arenaria serpyllifolia aggr. ( R ) 0.15 0.04 0.64 0.59 Rubus caesius ( W ) 0.09 0.39 1.5 2.95 Cirsium arvense ( R ) 0.07 0.06 0.55 0.69 Campanula rotundifolia ( D ) 0.05 0 0.04 0.04 Epilobium angustifolium ( P ) 0.04 0.08 3.39 13.6 Centaurea scabiosa s.l. ( D ) 0.03 0.06 0.6 0.14 Populus tremula ( W ) 0.01 0.03 0.68 0.69 Conyza canadensis ( R ) 0 0.01 0.89 4.38

Accumulated proportion 61% 63% 52% 64% of herb layer cover

(W) Woodland plants (D) Dry grassland plants (M) Mountain plants (R) Ruderal plants (P) Lowland pioneer plants

Figure 24: Mean cover of the most dominant species of 1996, 2004, 2005 and 2007 on 40 plots of 5 a. The species selection is the set union of the species that contribute a minimum of 50% to the herb layer cover of 1996, 2004, 2005 and 2007, respectively. Labels: Averaged species covers, error bars: SEM (n=40). 3.5. Dominant species

3.5.1. Dominance-diversity relation

In 1996 the forest plants Arctostaphylos uva-ursi , Carex humilis and Melampyrum sylvaticum showed the highest dominances in the herb layer (Figure 25). A wide range of species showed medium and a small amount very low dominance which leads to an approximately sigmoid curve form. In 2004, after the fire, the dominances of all species were very low and the number of species was reduced as well which results in a dominance-diversity curve approximating geometric series. In 2005 the species richness increased considerably but the dominances were still low compared to 1996. The dominance-diversity curve is of sigmoid form again. In 2007 the pioneer plants Epilobium angustifolium and Conyza canadensis , and the dry grassland plant Saponaria ocymoides became very dominant (and frequent). The dominances in 2007 are similar to those before the fire.

100

1996 2004 2005 2007

Arctostaphy los uv a-ursi Epilobium angustif olium Carex humilis 10 Saponaria ocy moides

Melampy rum sy lv aticum Cony za canadensis Epilobium angustif olium Rubus idaeus Calamagrostis v aria Calamagrostis v aria Saponaria ocy moides 1 Euphorbia cy parissias Calamagrostis v aria Saponaria ocy moides

Abundance 0.1

0.01

0.001

238 species 179 species 260 species 280 species

Rank

Figure 25: Dominance-Diversity curves of 1996, 2004, 2005 and 2007. Ranked species covers on 5 a vs. ranks. The most abundant species are labeled.

3.5.2. Species richness and Epilobium angustifolium cover

In 5 a circle plots, the species richness increased with high E. angustifolium cover. The number of species was higher on places where E. angustifolium covered more than 25 % of the surface than on places where it covered less than 5%. This effect cannot be observed on 0.3 and 2 a circle plots (Figure 26).

Epilobium angustifolium on 0.3a Epilobium angustifolium on 2a Epilobium angustifolium on 5a

a a a a a a a a a b b a a a Number of species of Number species of Number species of Number 30 40 50 60 40 50 60 70 80 90 10 15 20 25 30 35

0 r, + 1 2 3, 4 0, r, + 1 2 3, 4 0, r, + 1 2 3, 4 Braun-Blanquet cover code Braun-Blanquet cover code Braun-Blanquet cover code

Figure 26: Number of species vs. Epilobium angustifolium cover on 0.3, 2 and 5 a. Error bars: SEM, characters: sign. diff. means of cover classes (t-test).

3.5.3. Effect of Epilobium angustifolium cover on the cover of other species

On 2 a circle plots the accumulated cover of all species other than E. angustifolium was smaller on places where E. angustifolium covered more than 25 % in comparison with places it covers 5 to 25 % (t-test: p=0.041). This effect only exists on 2a.

3.5.4. Regeneration of trees and Epilobium angustifolium cover

The analyses could only be conducted with the data of the 2 and 5 a relevés because on the 0.3 a plots not enough saplings were present to undertake reasonable calculations. As displayed on Figure 27 on 2 a a trend to more number of tree saplings with higher Epilobium angustifolium cover is visible. On plots where E. angustifolium covered more than 25 % more tree saplings were counted than on plots where it covered less than 1 % cover. On 5 a the dependency is more distinct. More tree saplings were found on plots where E. angustifolium covered more than 25 % than on plots with lower E. angustifolium cover.

Epilobium angustifolium on 2a Epilobium angustifolium on 5a

c c c b b b b a a a a Number of tree saplings tree of Number saplings tree of Number 2 4 6 8 10 0 1 2 3 4 5

0, r, + 1 2 3, 4 0, r, + 1 2 3, 4 Braun-Blanquet cover code Braun-Blanquet cover code

Figure 27: Number of tree saplings (ln(y) transformed) vs. Epilobium angustifolium cover on 2 and 5 a. Error bars: SEM, characters: sign. diff. means of cover classes (t-test).

3.5.5. Species richness and Rubus sp . cover

The species richness does not vary with the cover of Rubus sp. The number of species does not differ on plots with different Rubus sp . cover

3.5.6. Effect of Rubus sp . cover on the cover of other species

On the 0.3 and 2 a plot circles with Rubus sp. covers of more than 25 % the accumulated cover of all other species is lower than on plots Rubus sp. covered less than 25 %. On 5 a the cover of Rubus sp. had no effect on the accumulated cover of all other species.

Rubus sp. on 0.3a Rubus sp. on 2a Rubus sp. on 5a

a a a b a a a b a a a a Cover of all other speciesother Cover[%] all of speciesother Cover[%] all of speciesother Cover[%] all of 20 40 60 80 100 120 0 20 40 60 80 100 20 40 60 80 100

0 r, + 1, 2 3, 4, 5 0, r, + 1 2 3, 4 0, r, + 1 2 3, 4 Braun-Blanquet cover code Braun-Blanquet cover code Braun-Blanquet cover code

Figure 28: Accumulated cover of all other species vs. Rubus sp . cover. Error bars: SEM, characters: sign. diff. means of cover classes (t-test).

3.5.7. Tree regeneration and Rubus sp . cover

The cover of Rubus sp. has no effect on the regeneration of trees. The amount of tree saplings found at different Rubus sp. covers did not differ.

3.6. Trees before and after the fire

3.6.1. Tree layer before the fire in 1996

The tree layer was formed by Norway spruce ( Picea abies ), Scotch pine ( Pinus sylvestris ) and European larch ( Larix decidua ). Norway spruces were recorded on 37, Scotch pines on 28 and larches on 18 of 40 plots (Table A 12). As displayed on Figure 29 Norway spruce was present throughout the study area mainly with covers of 15 and 37.5%. Scotch pines were recorded with covers of 3 to 37.5% predominantly in the lower parts of the fire patch up to an altitude of about 1500 m.a.s.l. Larch trees eventually were found from around 1200 m.a.s.l. up to the timberline mainly with covers of 0.5 to 15 %. Silver firs ( Abies alba , on eight plots), oaks

(Quercus sp ., on three plots) and Willows ( Salix appendiculata/caprea Grp ., on one plot) were also recorded in the tree layer.

2 2 2 0 0 0 Picea abies 0 0 Larix decidua 0 0 Pinus sylvestris 0 0 !! ! !! ! B-B. cover B-B. cover B-B. cover ! ! ! ! ! ! 1 ! 1 ! ! 1 + 8 8 + 8 0 1 0 0 ! 0 0 0 1 ! 16 ! ! 16 ! ! 16 00 ! 2 00 1 00 ! ! ! 2 ! ! 3 ! 2 ! ! ! ! ! ! ! ! ! 3 1 1 3 1 ! 4 4 4 00 00 00 ! 4 ! ! ! ! ! 5 ! ! ! ! ! ! ! !! ! ! ! ! ! ! 1! ! ! 1! ! ! 1 ! ! 20! 0 ! ! ! 2!00 ! ! 200 ! ! ! ! ! ! ! ! ! ! ! ! !!! ! !! ! ! ! 10 10 10 00 ! 00 00

Figure 29: Tree layer in Braun-Blanquet cover classes of the three most frequent tree species Picea abies , Pinus sylvestris and Larix decidua in 1996 .

3.6.2. Tree regeneration

In 2007 the average number of tree saplings on 5 a was significantly higher than in 2005 (28.6 and 22.1, respectively; paired t-test: p= 0.026).

2005 2007

Mean number of saplings 0 5 10 15 0 5 10 15

Populus tremula 9.93 10.62 Salix appendiculata/caprea Grp. 8.97 10.7 Picea abies 1 1.3 Larix decidua 0.7 0.3 Quercus sp. 0.35 0.8 Betula pendula 0.33 3.67 Populus alba 0.28 0.47 Sorbus aria 0.25 0.2 Acer pseudoplatanus 0.15 0.2 Mean number tree saplings tree number Mean Abies alba 0.07 0.03 Fraxinus excelsior 0.03 0 Juglans regia 0 0.03

0 5 10 15 20 25 30 35 Populus nigra 0 0.17 Prunus avium 0 0.07 2005 2007

Figure 30: Mean number of tree Figure 31: Mean number of tree saplings found on 5a in 2005 and 2007. saplings on 5a in 2005 and 2007. Error Error bars: SEM (n=40). bars: SEM (n=40). As displayed on Figure 31 Aspen (Populus tremula ) and Willow (Salix appendiculata/caprea Grp. ) are by far the most frequent tree species on the fire patch. In 2005 approximately ten Aspens and nine Willows have been counted on average on 5 a. Even more individuals of both species were found in 2007, making the mean number of saplings on 5 a increase to values between ten and eleven. Before the fire these two species were rare on the fire patch and only present in the herb and shrub layer (Table A 12). In 2005 the vast majority of Aspens

and Willows were below one meter in height. In the two years until 2007 individuals of both species have grown remarkably and occur now with growth heights ranging from 50 cm to 1 m and above.

Bewildering is the more than tenfold increase of the mean number of Silver birch ( Betula pendula ) saplings between 2005 and 2007 (cf. Discussion: 4.6 Tree regeneration). Silver birches could mainly be found in small height classes although some individuals taller than 150 cm were recorded.

These three species can be found throughout the fire patch with highly variable abundances. The number of Willow saplings counted on 5 a ranges from zero to 96 (plot no. 67 at 1860 m.a.s.l.). Aspen sapling numbers ranged from zero to 52 (plot no. 251 at 1620 m.a.s.l.) and the highest numbers of Silver birch saplings of 13 were recorded on plot number 128 and 263 at 1200 and 1320 m.a.s.l., respectively.

Twelve more saplings of Norway spruce have been found in 2007. In 2005 the 40 individuals were all below 20 cm in height whereas in 2007 seven of 52 could be recorded in the next higher height class of 20-50 cm. No Norway spruce saplings were found on plots below 1200 m.a.s.l. (Figure 32).

The number of oak saplings more than doubled between 2005 and 2007. In 2005 the 14 oak saplings were below 20 cm in height except for one that has been recorded with a height between 50 cm and 1 m (Figure 33). Two years later the 32 oak saplings were distributed to all height classes whereas most of them were smaller than 20 cm. Oaks were found up to an altitude of 1300 m.a.s.l.

Salix appendiculata/ 2 2 2 caprea Grp. 0 0 Betula pendula 0 0 Populus tremula 0 0 0 0 0 ! ! ! ! ! ! ! ! ! ! ! 1 - 4 ! 1 - 5 1 - 3 ! ! ! ! ! ! ! 1 ! ! 1 1 ! 4 - 8 8 5 - 8 8 6 - 10 8 0 0 0 0 0 ! 0 ! ! ! ! ! 9 - 15 16 16 9 - 13 16 00 ! 11 - 20 00 ! 00 ! ! 16 - 27 ! 21 - 28 ! ! ! ! ! ! ! ! 28 - 96 ! ! ! ! 1 29 - 52 1 14 ! 40 ! 40 ! 0 0 ! 0 ! 0 ! ! ! ! ! ! ! ! ! ! ! ! ! !!! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 12 ! ! 12 ! 120 ! ! 00 ! 00 ! 0 ! ! ! ! ! ! ! ! ! ! !

! ! !! !! ! ! ! 1 1 1 000 000 000

2 2 0 0 Picea abies 0 Quercus sp. 0 0 0 ! ! ! ! ! 1 - 2 1 ! ! ! 1 ! 1 2 - 4 8 3 - 6 8 0 0 0 0 ! 16 16 5 - 10 00 ! 00 ! 11 - 21 !

14 14 00 00 ! ! ! !!

! ! 12 12 ! ! ! 00 00 ! ! !

! !! ! ! 10 10 00 ! 00

Figure 32: Plot locations where Salix appendiculata/caprea Grp ., Populus tremula , Betula pendula, Picea abies and Quercus sp. were found in 2007. The size of the dots refers to the number of saplings recorded on 5 a plot circles.

2005 2007

Salix appendiculata/caprea Grp. Salix appendiculata/caprea Grp. Populus tremula Populus tremula Betula pendula Betula pendula Picea abies Picea abies Quercus sp. Quercus sp. Number of saplings of Number saplings of Number 0 50 100 150 200 0 50 100 150 200

0-20cm 20-50cm 50-100cm 100-150cm >150cm 0-20cm 20-50cm 50-100cm 100-150cm >150cm

Height class Height class

Figure 33: Number of saplings of the five most frequent (2007) tree species in five height classes on 5 a plot circles.

3.7. Elevation

3.7.1. Species richness and elevation

In 1996 the species richness on 5 a plots circles increased with elevation continuously. After the fire in 2004 the species richness did not show the same distinct elevation dependency anymore. The lowest numbers of species were recorded at around 1300 m.a.s.l. At the top most plot location (plot no. 234) the number of species of 59 is massively higher than the average of 24 species. In 2005 the species richness was highest at the top most plot locations. Again the lowest species richness was recorded at an elevation around 1300 m.a.s.l. From 2005 to 2007 the species richness increased also at the lower altitudes. The species richness in 2007 is apart from plot no. 234, 71 and 67 more or less evenly distributed along the elevation gradient. At the plot locations around 1300 m.a.s.l. the lowest numbers of species were recorded.

1996 2004 2005 2007

234 234 71 71 67 71 67

234 234

67 67 71 Number of species Number of species Number of species Number of species Number of

2 2 2 2 R = 0.58 R = 0.41 R = 0.64 R = 0.46 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100

1000 1200 1400 1600 1800 1000 1200 1400 1600 1800 1000 1200 1400 1600 1800 1000 1200 1400 1600 1800

Elevation [m.a.s.l] Elevation [m.a.s.l] Elevation [m.a.s.l] Elevation [m.a.s.l] 5a 5a 5a 5a

Figure 34: Species richness on 5 a in 1996, 2004, 2005 and 2007 vs. elevation. Points referring to the plot locations at highest altitude are labelled. Curve fits and R 2s refer to quadratic regression models (n=40; 1996: y=85-0.10x+0.00005x 2, p=9.3e-8; 2004: y=154-0.21x+0.00008x 2, p=5.4e-5; 2005: y=224-0.29x+0.0001x 2, p=5.8e-9; 2007: y=216-0.25x+0.00009x 2, p=1.1e-5).

3.7.2. Herb layer cover and elevation

The herb layer cover dependency on elevation is rather low or inexistent. As shown on Figure 35 the pre-fire herb layer cover was increased at higher altitudes. In 2004 there was no cover- elevation dependency (p=0.31). In 2005 sparse covers of around 20% have been measured at an elevation of around 1300 m.a.s.l. whereas at the top most plot locations the herb layer cover was more than 50%. In 2007 the herb layer cover was only marginally related to elevation. The covers increased with elevation from approximately 50 to 80%.

1996 2004 2005 2007

2 2 2 R = 0.06 R = 0.45 R = 0.2

R2 = 0.22 Cover [%] B-B.) (accumulated Cover [%] B-B.) (accumulated Cover [%] B-B.) (accumulated Cover [%] B-B.) (accumulated 0 50 100 150 0 5 10 15 0 50 100 150 0 50 100 150

1000 1200 1400 1600 1800 1000 1200 1400 1600 1800 1000 1200 1400 1600 1800 1000 1200 1400 1600 1800

Elevation [m.a.s.l.] Elevation [m.a.s.l.] Elevation [m.a.s.l.] Elevation [m.a.s.l.] 5a 5a 5a 5a

Figure 35: Accumulated B-B. covers on 5 a in 1996, 2004, 2005 and 2007 vs. elevation. Curve fits and R 2s refer to quadratic regression models (n=40; 1996: y=-63+0.15x-0.00003x 2, p=0.01; 2004: y=29-0.036x+0.00001x 2, p=0.31; 2005: y=190-0.26x+0.0001x 2, p=1.3e-5; 2007: y=-45+0.13x-0.00003x 2, p=0.02).

3.7.3. Tree regeneration and elevation

R2 = 0.31 Number of saplings of Number ln(Number of saplings) ln(Numberof R2 = 0.31 1 2 3 4 5 0 50 100 150

1000 1200 1400 1600 1800 1000 1200 1400 1600 1800

Elevation [m.a.s.l] Elevation [m.a.s.l] 5a 5a

Figure 36: Number of tree saplings (left) and ln(y)-transformed number or tree saplings (right) in 2007 on 5 a vs. elevation. Curve fits and R2s refer to a linear regression model (n=40; ln(y)=-0.31+0.0023x, p=1.9e-4).

Figure 36 shows the number of tree saplings counted on 5 a plot circles in 2007 plotted against elevation. At low elevations from 1000 to 1200 m.a.s.l. the number of saplings ranged from 3 to 20 and the highest numbers of saplings of more than 150 were recorded at the top most plot locations. The variance of the number of saplings increases with increasing altitude.

3.8. Climate

3.8.1. Climate model P/PE Precipitation [mm] Precipitation Air temperature [°C] temperature Air 10 12 14 16 18 0.6 0.8 1.0 1.2 1.4 200 250 300 350 400

1000 1200 1400 1600 1800 2000 2200 1000 1200 1400 1600 1800 2000 2200 1000 1200 1400 1600 1800 2000 2200 Elevation [m.a.s.l.] Elevation [m.a.s.l] Elevation [m.a.s.l]

Figure 37: Measured air temperature, precipitation and humidity. Line fits refer to the regression models specified in 2 Table 5. (left: n=12, y=24.6-0.0065x 1-0.0041x 2, p=1.31e-10; centre: n=6, y=94.9+0.2236x-4.41e-5x , p=6.34e-4; left: n=6, y=0.46+1.97e-7x2, 1.72e-6).

The measured mean air temperature of the vegetation period 2005 is closely linearly related to the elevation (p=1.91e-10). As the aspect has a significant but only slight influence (p=0.046) on air temperature, too, it was integrated to the regression models (Table A 13 et sqq. ). This was done analogous to all temperature parameters. The mean air temperature decreases 0.65 °C per 100 m of altitude and 0.41 °C with a 100 ° change in aspect. Keeping in mind that the aspect of the plot locations ranges from 121 ° to 256 ° this is only a very slight change (cf. also Figure 49). The number of heat hours decreases by an amount of 14 per 100 m of altitude. The effect of the aspect is more distinct with this parameter. A 100 ° aspect change results in a decrease of 51 heat hours.

Table 5: Climate model characterisation: Climate parameters, Model formulas, regression coefficients, multiple R 2s and p-values. Elevation in meters above sea level (E) and the aspect of the slope in degrees (A) were used as predictors. P/PE refers to the ratio of precipitation and potential evapotranspiration as an indicator of humidity.

Climate parameter ( y) Model formula (Multiple) R 2 p-value Air temperature [°C] 24.6 -6.51e-3 -4.14e-3 0.9936 1.31e-10 Ground temperature [°C] = + + 29.8 -6.76e-3 -0.0166 0.8839 6.18e-5 Soil temperature = + + 28.8 -5.62e-3 -0.0202 0.8675 1.12e-4 No. of heat hours = + + 434 -0.1420 -0.5057 0.7023 4.29e-3 Precipitation [mm] = + + 94.9 0.2236 -4.41e-5 0.9926 6.34e-4 P/PE = + + 0.46 1.97e-7 0.9979 1.72e-6 = +

The precipitation increases with elevation (Table 5). At lower altitudes the precipitation increase is higher than at high elevations (Figure 37, centre). No significant relation with

aspect can be stated (p=0.25). The humidity (P/PE) behaves different along the elevation gradient. With higher altitude the P/PE increases more. A humidity value of more than 1 corresponds to a positive water balance which implies more water to be available due to precipitation than the amount of water that is lost as evapotranspiration during the vegetation period. As the evapotranspiration decreases with altitude due to decreasing temperatures more of the precipitated water remains at surface at higher altitudes. Same as precipitation the aspect has no significant influence on the humidity (p=0.33).

3.8.2. Thermal photography data

Figure 38: Temperatures extracted from the heat picture shot at 13.00h on August 15, 2007 vs. elevation (left) and aspect (right).

The relation of the temperature with elevation and aspect could not be described better by means of thermal photography. The determination coefficients of the regression models calculated for those dependencies are R 2=0.37 for elevation and R 2=0.21 for aspect. For this reason those data have not been incorporated in further modelling or analyses.

3.8.3. Species richness and climate Number of species of Number species of Number species of Number

2 2 2 R = 0.27 R = 0.25 R = 0.28 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100

11 12 13 14 15 16 17 18 0 50 100 150 200 250 0.6 0.7 0.8 0.9 1.0 1.1 1.2

Air temperature [°C] No. of heat hours P/PE 5a 5a 5a

Figure 39: Number of species on 5 a in 2007 vs. air temperature, number of heat hours and humidity (P/PE). Line fits and R2s refer to linear regression models (n=40; left: y=109-3.6x, p=5.34e-4; middle: y=-11.9+0.21x, p=5.13e-3; right: y=18.7+43.7x, p=4.25e-4).

All climate parameters show significant influences on the species richness on 2 and 5 a plot circles. The species richness decreased with all temperature parameters and increased with precipitation and humidity (P/PE). Air temperature, no. of heat hours and P/PE (Figure 39) proved to explain most of the species richness’ variance as linear regression analyses testing those predictors revealed the best determination coefficients (R 2) (Table 6). With increasing scale in consideration the R 2 of the regression models show higher values. The influence of all climate parameters on the species richness on 0.3 a is not significant. The climate parameters explain less of the species richness’s variation than the proxy factor elevation does as the R 2s of those models are smaller than the R 2 the regression model using elevation revealed (Table 6 and Figure 34).

Table 6: R 2s and p-values of regression models testing linear influences of the climate parameters and the quadratic influence of elevation on the number of species in 2007 on 0.3, 2 and 5 a.

0.3a 2a 5a Climate parameter( y) R2 p-value R2 p-value R2 p-value Air temperature [°C] 0.0766 0.0838 0.2164 2.49e-3 0.2736 5.34e-4 Ground temperature [°C] 0.0539 0.1496 0.1936 4.50e-3 0.2366 1.46e-3 Soil temperature 0.0182 0.4064 0.1161 0.0314 0.1641 9.51e-3 No. of heat hours 0.0733 0.0911 0.2119 2.80e-3 0.2518 9.72e-4 Precipitation [mm] 0.02391 0.3407 0.1489 0.0139 0.1871 5.13e-3 P/PE 0.0644 0.1141 0.22 2.27e-3 0.2818 4.25e-4 Elevation [m.a.s.l.] 0.25 4.88e-3 0.3382 4.83e-4 0.461 1.08e-5

3.8.4. herb layer cover and climate

2 2 2 Cover[%] (accumulatedB-B) Cover[%] (accumulatedB-B) Cover[%] (accumulatedB-B) 40 60R = 800.22 100 40 60 80 100 R = 0.2 40 60 80 100 R = 0.21

11 12 13 14 15 16 17 280 300 320 340 360 0.7 0.8 0.9 1.0 1.1

Air temperature [°C] Precipitation [mm] P/PE 5a 5a 5a

Figure 40: Accumulated B-B. covers on 5 a in 2007 vs. air temperature, precipitation and humidity (P/PE). Line fits and R 2s refer to linear regression models (n=40; left: y=168-6.42x, p=2.35e-3; centre: y=-67.1+0.44x, p=3.72e-3; right: y=9.0+74.1x, p=3.27e-3).

The dependency of the herb layer cover (accumulated B-B.) on 5 a on the climate parameters is low but significant (Table 7). The influences of air temperature, precipitation and humidity turned out to be the strongest (R 2s≈ 0.2) and are displayed in Figure 40. The herb layer cover increased with decreasing air and ground temperatures and no. of heat hours and increasing precipitation and (P/PE). The higher the scale in consideration the better the determination coefficients and p-values turned out. The R 2 of the quadratic regression model elevation was used as predictor was ~0.2. The elevation therefore explains about the same proportion of the herb layer’s variance as the climate parameters do.

Table 7: R2s and p-values of linear regression models testing linear influences of the climate parameters and the quadratic influence of elevation on accumulated B-B. covers in 2007 on 0.3, 2 and 5 a plot circles.

0.3a 2a 5a Climate parameter( y) R2 p-value R2 p-value R2 p-value Air temperature [°C] 0.0579 0.1348 0.123 0.0265 0.2186 2.35e-3 Ground temperature [°C] 0.0412 0.2092 0.1088 0.0377 0.1515 0.0131 Soil temperature 0.0177 0.4133 0.0460 0.1839 0.0947 0.0535 No. of heat hours 0.0520 0.1572 0.1182 0.0299 0.1592 0.1371 Precipitation [mm] 0.054 0.1490 0.1206 0.0281 0.201 3.72e-3 P/PE 0.0522 0.1562 0.1098 0.0367 0.206 3.27e-3 Elevation [m.a.s.l.] 0.0487 0.1713 0.1071 0.0392 0.1962 4.21e-3

3.8.5. Tree regeneration and climate ln(Number of saplings) of ln(Number saplings) of ln(Number saplings) of ln(Number

2 2 2 1 2R = 30.32 4 5 1 2 3 4 5 R = 0.31 1 2 3 4 5 R = 0.32

11 12 13 14 15 16 17 280 300 320 340 360 0.7 0.8 0.9 1.0 1.1

Air temperature [°C] Precipitation [mm] P/PE 5a 5a 5a

Figure 41: ln(y)-transformed number of tree saplings on 5 a in 2007 vs. air temperature, precipitation and humidity (P/PE). Line fits and R 2s refer to linear regression models (n=40; left: ln(y)=7.9-0.34x, p=,1.55e-4; centre: ln(y)=- 4.7+0.024x, p=2.04e-4; left: ln(y)=-0.56+4.0x, p=1.55e-4).

On Figure 41 the number of tree saplings on 5 a in 2007 against air temperature, precipitation and humidity (P/PE) is displayed. The numbers of tree saplings were transformed (ln(y)) to gain normal distributed data. The number of saplings found on 5 a plot circles increased with decreasing temperature and increasing precipitation and humidity (P/PE). The three climate parameters air temperature, precipitation and humidity (P/PE) turned out also in this case to be the most influential (Table 8). The climate parameters air temperature, precipitation and P/PE explain approximately 31% of the number of tree saplings’ variance which is about the same as elevation does.

Table 8: R 2s and p-values of linear regression models testing the linear influences of the climate parameters and the quadratic influence on the ln(y)-transformed number of tree saplings in 2007 on 5a.

5a Climate parameter( y) R2 p-value Air temperature [°C] 0.3172 1.55e-4 Ground temperature [°C] 0.3014 2.44e-4 Soil temperature 0.2454 1.16e-3 No. of heat hours 0.2959 2.86e-3 Precipitation [mm] 0.3076 2.04e-4 P/PE 0.3171 1.55e-4 Elevation [m.a.s.l.] 0.31 1.91e-4

3.9. Fire

3.9.1. Fire and elevation

As shown on Figure 42 the fire intensity increased along the elevation gradient from 1000 to approximately 1300 m.a.s.l. where it reached its maximum. At higher altitudes the fire was less intense and minimal at the very top of the fire patch. Fire intensity Fire

2 = 0.6 0.8R 1.00.43 1.2

1000 1200 1400 1600 1800

Elevation [m.a.s.l.] 5a

Figure 42: Fire intensity vs. elevation. Curve fit and R 2 refer to a quadratic regression model (n=40; y=-0.5+0.0026x-1e-6x2, p=3.32e-5).

3.9.2. Species richness and fire intensity

As shown on Figure 43 the species richness in 2007 on 5 a plot circles decreased with increasing fire intensity. The fire intensity was lowest at the plot locations 234 and 67 and relatively low at 71. At these locations also by far the highest species richness was recorded. Regarding the species richness on 0.3 a plot circles the fire intensity has no influence as the p- value of the regression analysis is higher than 0.05. On 2 a the effect is only marginal but significant (Table 9).

234 67 71 Number of species of Number

40 50R 60= 700.44 80 90

0.6 0.8 1.0 1.2

Fire intensity (added B-B) 5a

Figure 43: Number of species vs. fire intensity. Points referring to the plot locations at highest altitude are labelled. Line fit and R 2 refer to a linear regression model (n=40, y=100.7-44.1x, p=3.65e-6).

Table 9: R 2s and p-values of linear regression models testing the influence of the fire intensity on the species richness.

0.3a 2a 5a R2 p-value R2 p-value R2 p-value Fire intensity 0.065 0.12 0.183 5.94e-3 0.435 3.65e-6

3.9.3. Herb layer cover and fire intensity

The herb layer cover on 5 a in 2007 was higher where the fire intensity in 2003 was low and vice versa (Figure 44). Considering the R 2s of the regression analyses the effect is only significant regarding 5 a plot sizes (Table 10).

40 60R 80= 100 0.33 Cover (accumulated B-B.) [%] B-B.) (accumulated Cover

0.6 0.8 1.0 1.2

Fire intensity 5a

Figure 44: Herb layer cover (accumulated B-B.) vs. fire intensity. Line fit and R 2 refers to a linear regression model (n=40; y=150-76.6x, p=9.92e-5).

Table 10: R2s and p-values of a linear regression model. Tested was the influences of the fire intensity on the accumulated B-B. herb layer cover on 5 a.

0.3a 2a 5a R2 p-value R2 p-value R2 p-value Fire intensity 0.166 0.010 0.133 0.021 0.332 9.92e-5

3.10. Coarse woody debris (CWD)

The CWD percentages were allocated to classes of low (less than 10%) and high (10% and more) CWD. Figure 45 shows the mean cover (accumulated B-B.) of the herb layer in 2007 at sites of low and high CWD. A trend to higher herb layer covers with high CWD cover has been detected although the differences are not significant.

On Figure 46 the height of the herb layer in summer 2007 at sites of low and high CWD, respectively, is displayed. At all plot sizes the mean layer height is higher at sites CWD was 10% or more. The differences are only significant at 0.3 and 5a plot sizes though.

Herb layer height with CWD < 10% Cover with CWD < 10% Herb layer height with CWD >= 10% Cover with CWD >= 10% Cover[%] Herblayerheight [m] 0 20 40 60 80 100 a a a a a a 0.0 0.2a 0.4 0.6b 0.8 a a a b 0.3a 2a 5a 0.3a 2a 5a Plot area Plot area

Figure 45: Mean cover (accumulated B-B.) of herb layer Figure 46: Mean height of herb layer in plots with more in plots with more and less than 10% CWD. Error bars: and less than 10% CWD. Error bars: SEM and SEM and characters: sign. diff. means at the same plot characters: sign. diff. means at the same plot area (t- area (t-test). test).

4. Discussion

4.1. Biodiversity

4.1.1. Biodiversity before and after the fire

In the two years since the vegetation on the fire patch was surveyed by SERENA (2005) the biodiversity increased again. After the depression in 2004 the biodiversity has recovered to an extent that exceeds the numbers before the fire on the scale of 2 and 5 a and reaches the same level on a small scale of 0.3 a. As plants spread over the fire patch and colonised the remaining open patches of ground the species diversity increased at shrinking scales in consideration. The phenomenon of boosting species richness after forest fires has been well documented by previous studies before (HOFMANN et al. 1998, TANDE 1979 and ZACKRISSON 1977). Well known is also the species richness peak a few years after the disturbance

(HOFMANN et al. 1998). This is becoming apparent at the moment on the fire patch above Leuk. The species richness increased in the past two years though but not as much as in the year between 2004 and 2005. WENDELBERGER and HARTL (1969) recorded the highest species richness after a wild fire in the forest of Aletsch situated in the upper Valais after eight years. I assume the maximum number of species on the fire patch above Leuk has already this year or will be reached sooner than that if the species richness development continues like this.

4.1.2. Biodiversity and climate

The highest numbers of species were recorded above 1800 m.a.s.l. where the lowest mean summer temperatures and the most rainfall has been measured. Although the temperatures increase and the precipitation decreases continuously towards the lower parts of the fire patch in this year the species richness below 1800 m.a.s.l. is more or less evenly distributed. As between 2005 and 2007 the species richness has increased mainly in the lower parts of the fire patch the hot and dry conditions at these sites allow nevertheless a wide range of species to colonise the remaining open patches.

4.1.3. Biodiversity and fire intensity.

SERENA (2005) classified the fire intensity after DOYLE (2004) as “severe” throughout the whole study area. As observed in the field the fire must have burned at varying intensities though. WOHLGEMUTH et al. (2005) measured the depth of the ash layer as an indicator for the fire intensity in 2004. This is indeed a much more direct approach as the difference in herb 52

layer cover of 2004 and 2005 which was used as fire intensity measure in this thesis. Both methods, however, led to similar results. From the bottom of the fire patch to approximately 1300 m.a.s.l. the fire intensity increased and then decreased towards the top of the burned area. SERENA (2005) assumed the fire being higher in the lower to middle parts of the fire patch due to the relatively slim, dense and fast burning Scotch pine-Norway spruce stands in this area (WERNER 1994). The mighty larch trees at higher altitudes, though, grew in more open stands as the forest was used as alpine meadow (GÖDICKEMEIER 1998). This larch forest must have fuelled the fire less so it lost on intensity and eventually faded away at the timberline. This is reflected in the distribution of the species richness of 2007 in a way that above 1800 m.a.s.l. distinctively more species were recorded. At lower altitudes the species richness was only marginally affected by the fire intensity. Explanations for the diffuse relation could lie in the already indirect and approximate character of the fire intensity measure itself or simply by the fact, that four years after the fire the fire intensity did not affect the species richness a lot anymore.

4.2. Vegetation cover

4.2.1. Developing of the herb layer cover from the pre-fire state to 2007

Four years after the fire the vegetation on the fire patch covered on average 71% of the ground if measured on 5 a sampling plots. The accumulated Braun-Blanquet cover values ranged from 24 to 116%. It more than doubled in the past two years and is impressive if keeping in mind the very sparse cover of only 5% one year after the fire. The vegetation has recovered to such an extent that the herb layer cover is now as high as GÖDICKEMEIER (1998) measured in 1996. The speed of the vegetation regrowth in Leuk is comparable to what

SCHÖNENBERGER and WASEM (1997) observed after a forest fire above the central alpine village of Müstair. On that fire patch situated between 1800 and 2200 m.a.s.l. the herb layer cover (mainly dominated by Calamagrostis villosa and Epilobium angustifolium ) averaged at 68% three years after the burning.

4.2.2. Vegetation cover and climate

The low determination coefficients (R 2≈0.2) resulting from the regression analyses conducted with herb layer cover and climate parameters suggest low dependencies. The covers measured on the fire patch vary a lot along the elevation gradient. Anyhow, tendencies can be made out. The highest covers were measured at places where low to medium temperatures prevail and

the lowest covers occurred at locations with hotter mean temperatures. With higher rainfall and humidity (ratio of precipitation and potential evapotranspiration) the vegetation tends to cover more of the ground. As observed in the field the covers are determined by a micro- climate that varies on scales too small for being captured by the climate model used in this study (cf. also chapter 4.7 Remarks on the climate models). Patches shaded by dead trees or rocks bore much higher covers than sun exposed ground covered by rock debris for example. Also the water availability is increased at topographic structures like trenches or hollows in comparison to top of knolls or to bare rock. Moreover the depth of the soil and the sun exposure contribute among others factors to variations in the water balance.

4.2.3. Vegetation cover and fire intensity

The fire intensity is reflected by the vegetation cover rather distinctively. Where the fire burned most severely the vegetation cover is still much lower than where it burned less. The more intense the fire burned the more of the topsoil it combusted (WOHLGEMUTH et al . 2005). This was clearly visible on the fire patch at altitudes of 1200 to 1400 m.a.s.l. where the ground is partially covered by rock debris and only little humus. The establishment of plants is still inhibited at these places.

4.2.4. Vegetation cover and height and CWD

The vegetation tends to cover more of the surface and is significantly taller where CWD was 10 % or more. In the field higher covers and vegetation were observed uphill of logs perpendicular to the slope and underneath felled trees. I assume those logs to affect soil density that results in water and nutrient retention which in turn produces better conditions for plant growth. Furthermore thin branches of felled trees possibly prevent the lightly constructed herbal vegetation from damage caused by wind, heavy rainfall or snow pressure. Another explanation could be that the ground covering wood debris forces plants to grow larger to reach optimal sun light supply. Due to the high uncertainty of the CWD measurements and the aggregation of the percentages to only two classes the results are very general and of little explanatory power. This is also because the underlying mechanisms shortly delineated above could not be examined within this study and base on assumptions and subjective field observations.

4.3. Vegetation structure and species propagation

Before the fire the species were more evenly distributed at the small scale as after the fire (Figure 14). When in 2004 the ground was barely covered with vegetation the distribution of species was more structured i.e. patchy. This patchiness consolidated slightly in 2005 but vanished again two years later. The values of 2004, 2005 and 2007 do not differ much between each other and therefore do not allow the claim of a distinct oriented development. Although the patchiness of the herb layer was observed rather distinctively during the fieldwork it was surprising how many species have been found underneath or between the dense occurrences of Epilobium angustifolium for example. The density and the structure of patches itself is very different depending on the species. The legumes Securigera vari a, Lathyrus pratensis and Astragalus monspessulanus formed large cushions of low density allowing a lot of species growing between them. The species of the genus Rubus , in contrast, grow in much denser thickets shading out the ground completely with broad leaves which limits other plants to grow in considerable abundances (cf. chapter 4.5 Dominant species). Whether the ratio of species richness at a small (0.3 a) and medium scale (2 a) was a good measure of patchiness, is debatable. As the size of those vegetation patches ranges from several decimetres to more than ten meters in diameter the highly variable and diverse vegetation structure is presumably not captured adequately by the differences in the species richness between the constant 0.3 a and 2 a plot circle.

The species have further propagated on the fire patch since 2005. The relevés recorded shortly after the fire in 2004 differed most within each other in terms of species composition. Therefore the species at this state were distributed more heterogeneously over the fire patch as before the burning. In 2005 the relevés were more similar within each other thus species have spread and colonised areas where they were not present in 2004. To a smaller extent this happened again in the time between 2005 and 2007. The similarities within relevés are smaller with smaller plot sizes in consideration and this mainly in the year 2005. This reflects the small scale variations of the vegetation described above which is most distinct in 2005.

4.4. Species composition

The low similarity of the vegetation in 2004 with the pre-fire state that was calculated after Van der Maarel is striking compared to Jaccard’s coefficient which is relatively stable over the post-fire years (Figure 16). Van der Maarel’s coefficient is taking the species’ covers into account whereas Jaccard’s does not. This makes the difference between those similarity 55

measures in 2004. Therefore it can only be said that the species composition did not become more similar to the pre-fire state in the past four years except for the fact that between 2004 and 2005 the species’ covers became more similar to 1996. A change in species composition has nevertheless occurred as the changes in number of species and covers of different ecological groups and single species show.

The herb layer underneath the closed canopy of the intact tree layer before the fire was typically dominated by the woodland plants Arctostaphylos uva-ursi , Carex humilis and Melampyrum sylvaticum whereas they were joined at higher altitudes by the dry grassland plants Euphorbia cyparissias , Brachypodium pinnatum aggr. and Teucrium chamaedrys and mountain plants such as Laserpitium siler . Due to the destruction of the tree layer and the dramatic change of soil properties such as water detention, nutrient availability and pH the growth conditions for plants changed dramatically and new ecological niches were created. The high radiation, the lack of possible competitors and the high nutrient availability

(WOHLGEMUTH et al. 2005 and BERLI 1996) on the fire patch in 2004 favoured mainly plants of dry grass land such as Euphorbia cyparissias and Saponaria ocymoides , the pioneer plant Calamagrostis varia and the forest plants Rubus saxatilis at higher and Rubus caesius at lower altitudes. High abundances of ruderals have not been recorded until 2005 when Cirsium arvense , Arenaria serpyllifolia aggr . and Conyza Canadensis could spread at mainly lower altitudes. At this time high abundances of the pioneer herb Epilobium angustifolium were measured the first time. Calamagrostis varia and the dry grassland plant Saponaria ocymoides and the Rubus species could gain on abundance as well. From 2005 to 2007 the dominances had mainly increased and consolidated. The dominance-diversity curve (Figure 25) shows this development nicely on a graphical way. The species Epilobium angustifolium , Saponaria ocymoides , Conyza canadensis and the Rubus species virtually boosted and multiplied their abundances. I assume the propagation of Epilobium angustifolium and Saponaria ocymoides to reach a peak soon and then loose on abundance slowly as the upcoming Willows (Salix appendiculata/caprea Grp. ), Aspens (Populus tremula ) and Silver birches (Betula pendula ) start to shade out the herb layer and the released nutrients are either going to be washed away or turn into less plant available organic forms. SCHÖNENBERGER and

WASEM (1997) reported this decline in Epilobium angustifolium abundance six years after the fire above Müstair and DELARZE and WERNER (1985) noted Saponaria ocymoides abundances to decline after two years only.

According to DELARZE and WERNER (1985) several stages in the process of herb layer recovery of Scotch pine (Pinus sylvestris ) forests in the Valais have been described in previous studies (WERLEN 1968 and CHEVRIER 1978). That is: A stage of “pyrophythes” (characterised by species usually occurring temporarily in high abundances shortly after fires), a stage of legumes and Saponaria ocymoides , a stage of gramineous plants, a stage of deciduous pioneer trees and finally a pre-climax Scotch pine forest. DELARZE and WERNER (1985) described the herb layer three years after a fire at the south facing slope between Leuk and Gampel, VS. Similar to their findings the vegetation of the fire patch is four years after the fire also characterised by those succession stages that could be made out during the fieldwork. Even though they all occur at the same time, overlap and can sometimes not clearly be distinguished from each other.

A stage of “pyrophytes” characterised by Epilobium angustifolium , Cirsium arvense , Verbascum thapsus s.l. and Brachypodium pinnatum aggr . was observed in the middle part of the study area.

At places with dry conditions on shallow soils the legumes and Saponaria ocymoides stage was noticed. At these sites located predominantly at lower altitudes and steep slopes also thickets of Rubus caesius and cushion forming plants such as Teucrium chamaedris were recorded. The legumes were mainly represented by Securigera varia, Hippocrepis comosa and Astragalus monspessulanus that usually formed cushions of various sizes.

The gramineous stage was existent in a way that on some favourable mostly rather flat parts stands of Calamagrostis varia, Calamagrostis villosa , Poa sp . and Anthoxanthum odoratum mostly together or surrounded by Epilobium angustifolium had been observed. After the fire above Müstair (1800-2200 m.a.s.l.) the Epilobium angustifolium stands were gradually replaced by Calamagrostis villosa (SCHÖNENBERGER and WASEM 1997). In Leuk Calamagrostis varia seems to play that role at the lower altitudes.

Tall growing species such as Epilobium angustifolium , Rubus idaeus and Rubus caesius were also noticed by DELARZE and WERNER (1985). They grow at the most favourable sites in terms of water availability and soil fertility and were found at higher altitudes (above ~1600 m.a.s.l.). These sites contained often high numbers of Willow ( Salix appendiculata/caprea Grp .), Aspen ( Populus tremula ) and Silver birch ( Betula pendula ) saplings and will pass into the stage of deciduous pioneer trees firstly.

4.5. Dominant species

The great change in vegetation from 2005 to 2007 is the increase in dominance of only a few species (Figure 25). The dominance-diversity curve of 1996 was of sigmoid shape typical for most plant communities (WHITTAKER , 1965). A few species dominate, the vast majority shows intermediate covers and some specialists are only rarely represented. After the fire the dominance-diversity curve approximated a geometric series which is according to

WHITTAKER (1965) typical for communities found at harsh environmental conditions. The sigmoid shapes of the dominance-diversity curves of 2005 and 2007 can be seen as an indication for the recovery of the vegetation. The dominances of 2007 are comparable to those in 1996 although the species composition is fundamentally different.

Considering those high dominances of Epilobium angustifolium and the Rubus species, questions of how they impact to the rest of the vegetation arose. Epilobium angustifolium is the most abundant species in terms of coverage and virtually overgrows ares in closed stands. Nevertheless a lot of species were found and the most saplings were counted within the high Epilobium angustifolium stands. These impressions of the fieldwork could be verified statistically to some extent. Places of high Epilobium angustifolium cover hosted more species than places where E. angustifolium was of little abundance. Trends are visible on the small scale, too, but the statistically significant dependency could only be proved on the 5 a plots because the vegetation varies more with smaller scales in consideration. An impact on the abundance of other species could not clearly be detected as E. angustifolium does not grow very densely and as a hemicryptophyte it dies back in winter. This allows plants to develop and spread in the time before E. angustifolium reaches its maximum height and density. A positive relation of E. angustifolium cover and tree regeneration could also be detected.

SCHÖNENBERGER and WASEM (1997) observed this also in Müstair and explained it with the favourable soil and concurrence conditions.

A closer look on the impact of Rubus sp . showed that Rubus sp. thickets indeed suppress other species. Where high covers of Rubus sp. were recorded the cover of all other species was lower. As this could not be shown regarding the 5 a plots this only plays a role on the small scale. This does not astonish as in most cases Rubus sp. thickets do not exceed extensions of approximately 30 m2. An impact of the Rubus sp. cover on species richness and number of tree saplings could not be stated. This is most likely again because of the only small scale affectivity of the Rubus sp . thickets on the vegetation.

4.6. Tree regeneration

4.6.1. Tree regeneration at different conditions

The regeneration of trees proceeds. In 2007 more saplings and root sprouts of trees (phanerophytes) were counted as in 2005. In general, at higher elevations were lower temperatures and more humidity prevailed higher numbers of tree saplings (predominately Aspens and Willows) were counted.

Figure 47: Plot location number 139 at 1235 m.a.s.l. Figure 48: Plot location number 67 at 1860 m.a.s.l. (27.7.2007). (8.8.2007). The photographs above show as an example two plots with extremely different vegetation. Only two saplings were found at plot number 139 (1235 m.a.s.l.) which represents the legumes and Saponaria ocymoides stage (DELARZE and WERNER 1985) grown on a soil that is either absent or very sparsely developed (Figure 47). In contrast, at plot number 67 (1860 m.a.s.l.) which was covered with Epilobium angustifolium and Rubus idaeus representing the typical post-fire vegetation at higher altitudes the highest number of saplings of 165 was recorded (Figure 48). The fire must have left much more of the soil at place like this so that the vegetation including the tree regeneration could develop quicker. SCHÖNENBERGER and

WASEM (1997) explained the positive effect of Epilobium angustifolium cover on the tree regeneration by the lightly shading and therefore prevention of water stress.

4.6.2. Tree species

The vast majority of saplings counted on the fire patch were Aspen ( Populus tremula ), Willow ( Salix appendiculata/caprea Grp .) and Silver birch ( Betula pendula ); the typical fast growing early colonising tree species of the montane and sub-alpine vegetation zone

(BRÄNDLI 1996). In 2005 most Aspen and Willow saplings reached heights from approximately 30 to 80 cm. Two years later most of them reached heights from 80 cm to more

than 1.5 m. The number of Aspen and Willow saplings showing heights of less than 20 cm is relatively small. I assume therefore a “colonisation peak” of the most favourable sites to be over already and other sites of less favourable conditions being colonised more slowly in the future. Aspens seem to be more resistant to water stress than Willows as they were found at higher numbers also at the dry and rocky sites around 1200 m.a.s.l.

The mean numbers of Silver birches counted on a 5 a in 2005 and 2007 differs a lot. In 2005 on average 0.3 and in 2007 3.7 saplings were counted on 5 a plot circle. It is hard to believe all these birches have colonised the fire patch in the past two years especially when regarding the growth heights of a lot of them being between 50 and 150 cm. I assume the Silver birch and Aspens saplings were mixed up in 2005 as they were hard to differentiate at this stage. All these tree species were found throughout the fire patch. Much more Aspens and Willows were counted at higher altitudes though whereas the Silver birch counts were more or less balanced.

The tree species that formed the forest before the fire are regenerating sparsely and slowly. On average 1.3 saplings of Norway spruces (Picea abies ) were counted on a 5 a plot circle in 2007. Two years before it was 1. All saplings were found above an elevation of 1200 m.a.s.l. and the vast majority of them was smaller then 20 cm. The average number of Larch ( Larix decidua ) saplings on a 5 a plot circle was in 2007 with 0.3 even smaller than two years before when 0.7 were counted. A natural regeneration of Scotch pine ( Pinus sylvestris ) could yet not be detected on the observed plots. The conditions for the establishment of conifer seedlings are at this stage due to drought, out shading and competition unfavourable (SCHÖNENBERGER and WASEM , 1997). The regeneration of the forest after all follows the typical succession stages documented earlier in the Valais and in other areas. A conifer forest alike present before the fire can therefore not be expected until several decades in the future. Firstly a shrub stratum dominated by the deciduous pioneer woods is going to shape the fire patch

(SCHÖNENBERGER and WASEM 1997, WENDELBERGER and HARTL 1969, BERGERON and

DANSEREAU 1993).

At the dry and rocky lower elevation sites below 1200 m.a.s.l where Scotch pines predominated before the fire the direction of the forest regeneration is questionable.

DOBBERTIN et al . (2006) documented a displacement of Scotch pines below an altitude of 1200 m.a.s.l. by Oaks ( Quercus pubescens ) in the Valais and related this to climate warming. The lack of Scotch pine regeneration and the Oak saplings recorded exactly at those

elevations below 1200 m.a.s.l. let’s assume an Oak forest to develop. The increased drought and heat presumably limits Scotch pines and Oaks may replace the conifers.

4.7. Remarks on the climate models

The correlations of the vegetation with the climate data show similar results as those conducted with the proxy factor elevation. The climate variables could explain the variances in species richness, cover and tree regeneration better with increasing scale in consideration. Regarding the heat pictures and comparing it with photographs of the fire patch let’s assume a high dependency of the temperatures of the ground surface properties. Rocks seem to reflect a lot of heat whereas the dark open soils absorb it. This shows that although the twelve climate stations are able to record the climate with very high spatial resolution compared to other study areas where one has often to go back to data of networks of the official meteorological institutions the model cannot capture the highly variable climate in the micro-relief of the fire patch that actually determines the vegetation. Furthermore the recorded plots are unfavourably distributed on the fire patch to conduct such analyses. Nearly half (19) of the plots are clumped at an elevation between 1100 and 1400 m.a.s.l., between 1400 and 1900 m.a.s.l. 15 and below 1100 m.a.s.l. six plots are situated. The floristically interesting area above 1900 m.a.s.l. is not represented by this sample at all. This leads to an overrepresentation of the vegetation between 1100 and 1400 m.a.s.l. and therefore “contorts” the vegetation data (Figure 1). (By the way: The benefit of this sample is the available pre-fire vegetation data). Another problem poses the different distribution of the plots and the climate stations aspect-wise. The climate stations are distributed at aspects ranging from South to West whereas the recorded plots cover an aspect ranging from South-East to West (Figure 49). Unfortunately the assumed temperature differences between the South-East and South- West facing slopes could therefore not be modelled.

180°

G. plot locations Climate stations

90° E W 270°

Figure 49: Aspect of the plot locations and the climate stations.

Nevertheless the data was good enough to show the trends of the climate influence on the vegetation. In this study the climate of the vegetation period of 2005 was used to explain variations in the vegetation of 2007. Of course the climate varies a lot over years but the slope of the temperature decrease and the humidity increase with elevation should be stable. For this reason only relative statements such as “more species at lower temperatures” have been made. Furthermore the climate parameters air temperature, precipitation and humidity in terms of the ratio of precipitation and potential evapotranspiration (THORNTHWAITE and MATHER , 1957) turned out best to explain vegetation variances.

One can be very curious on the results revealing the climate dependencies of the vegetation that has been recorded on the systematic sample of 153 plots by Tom Wohlgemuth et al. As the climate time series are now present till end of summer 2007 and the plots cover the whole ecological range of the fire patch these results must be more accurate and will reveal more detailed relations.

5. Conclusion

The fire-disturbed ecosystem regenerates in a way typical for this region. Highly variable, however, is the speed of these succession processes at different places of the fire patch. The fire still affects the vegetation in terms of the edaphic changes it caused. At favourable sites spared from severe soil combustion, drought and high temperatures the ecological resilience in terms of the speed of a disturbed ecosystem to develop towards its initial state seems to be high. Richness in both species and saplings mirror this nicely. After deciduous early colonising trees have established they will eventually be replaced by coniferous forest. Where top-soil is shallow or missing the vegetation became much more species rich in the past two years though but the development towards closed vegetation proceeds very slowly and is only possible in line with soil formation. Whether and when Scotch pine will establish depends on effects that have not been examined yet, e.g. episodical moist years or seed mast years. At the moment, more likely is the formation of Oak forest at these sites.

6. Acknowledgments

Many thanks to Dr. Thomas Wohlgemuth, Dr. Barbara Moser and Tabea Kipfer for supervision, introducing us to the survey methods, botanical and statistical assistance, enriching conversations and sharing good times, Niklaus Hardegger for sharing the fieldwork, good company and many laughs, Ueli Wasem and Christian Ginzler for providing geographical data and assistance concerning GIS, Gustav Schneiter for providing climate data and help analysing and interpreting them and after all the Kounen family providing us with accommodation in Albinen, VS, during the field season, refreshments, information and good fun.

7. References

BERLI , S. 1996. Brandspuren in den Wäldern der Alpensüdseite. Eidgenössische Forschungsanstalt für Wald, Schnee und Landschaft (WSL), Birmensdorf, 123 pp.

BERGERON , Y. and P.-R. DANSEREAU . 1993. Predicting the composition of Canadian southern boreal forest in different fire cycles. Journal of Vegetation Science, 4:827-832.

BIGLER , C., O.U. BRÄKER , H. BUGMANN , M. DOBBERTIN , and A. RIGLING . 2006. Drought as an inciting mortality factor in Scots pine stands of the Valais, Switzerland. Ecosystems 9: 330-343.

BRÄNDLI , U.-B. 1996. Die häufigsten Waldbäume der Schweiz. Berichte der Eidgenössischen Forschungsanstalt für Wald, Schnee und Landschaft 342.

BURRI , M. 1992. Erkenne die Natur im Wallis N° 1: Die Gesteine. Pillet, Martigny. 158 pp.

CHEVRIER , P. 1978. Etude de la végétation de la forêt des Sasses (Bagnes) après incendie. Travail de diplôme, Inst. de sylviculture ETH, Zürich.

DELARZE , R. and P. WERNER . 1985. Evolution après incendie d‘une pelouse steppique et d’une pinède dans une vallée intra-alpine (Valais Central). Phytocoenologia 13: 305-321.

DOBBERTIN M., A. RIGLING , E. GRAF PANNATIER , M. REBETEZ , and T. WOHLGEMUTH . 2006. Die Klimaveränderung bedroht die Föhrenwälder im Wallis. Wald und Holz, 8: 37-39.

DOYLE , K. M. 2004. Early postfire forest succession in the heterogeneous Teton landscape. In: WALLACE , L. L. (E D.). After the fires: The ecology of change in Yellowstone National park. Yale University Press, New Haven: 235-278.

EGGENBERG S. and A. MÖHL . 2007. Flora Vegetativa, Ein Bestimmungsbuch für Pflanzen der Schweiz im blütenlosen Zustand. 1. ed., Haupt, Bern, 679 pp.

GEHRIG , M. 2004. Methoden zur Vitalitätsbeurteilung von Bäumen. Diss. ETH 15341, Zürich. 254 pp.

GIMMI , U., M. BÜRGI , and T. WOHLGEMUTH . 2004. Wie oft brannte der Walliser Wald im 20. Jahrhundert? Schweizerische Zeitschrift für Forstwesen 155, 10: 437-440.

GÖDICKEMEIER , I. 1998. Analyse des Vegetationsmusters eines zentralalpinen Bergwaldgebiets. Diss. ETH 12641, Zürich, 127 p.

HESS , H. E., E. LANDOLT , R. HIRZEL , and M. BALTISBERGER . 1998. Bestimmungsschlüssel zur Flora der Schweiz, 4.ed., Birkhäuser, Basel, 659 pp.

HOFMANN , C., M. CONEDERA , R. DELARZE , G. CARRARO , and P. GIORGETTI . 1998. Effets des incendies de forêt sur la vegetation au Sud des Alpes suisses. Mitteilungen der Eidgenössischen Forschungsanstalt für Wald, Schnee und Landschaft 73: 1-90.

KIENAST , F., 1985. Dendroökologische Untersuchungen an Höhenprofilen aus verschiedenen Klimabereichen. Diss. Univ. Zürich, 137 pp.

KRÜSI , B. O. 2006. Schlüssel zur Bestimmung von Gräsern und Grasartigen im vegetativen Zustand. Typoscript, Hochschule Wädenswil HSW, 38 pp.

LANDOLT , E. 1991. Gefährdung der Farn- und Blütenpflanzen in der Schweiz mit gesamtschweizerischen und regionalen Roten Listen. BUWAL (since 2006 Bafu), Bern.

LAUBER , K. and G. WAGNER . 2001. Flora Helvetica. 3. ed., Haupt, Bern, 1615 pp.

SCHIMMEL , J. and A. GRANSTRÖM . 1996. Fire severity and vegetation response in the Boreal Swedish forest. Ecology 77: 1436-1450.

SCHÖNENBERGER , W. and U. WASEM . 1997. Wiederbewaldung einer Brandfläche in der subalpinen Stufe bei Müstair. Schweizerische Zeitschrift für Forstwesen 148: 405-424.

SWISSTOPO , FEDERAL OFFICE OF TOPOGRAPHY . Digital elevation model DHM 25 and DTM-AV, aerial photograph of Leuk 2005 and Landeskarte der Schweiz 1:25000, map sheet 1287 Sierre, updated 2004, Wabern.

TANDE , G. F. 1979. Fire history and vegetation pattern of coniferous forests of the Mountain West. Canadian journal of botany 57: 1912-1931.

THORNTHWAITE , C.W. and J.R. MATHER . 1957. Instructions and tables for computing potential evapotranspiration and the water balance. Drexel Inst. Tech., Lab. of Climatology. Publ. in Climatology 10:185-311.

WAGNER , G. 1994. Verbreitungsatlas der Farn- und Blütenpflanzen der Schweiz. Nachträge und Ergänzungen, zweite Folge 1994; Zentralstelle der floristischen Kartierung der Schweiz. Systematisch-Geobotanisches Institut der Universität Bern, 156 pp.

WELTEN , M. and R. SUTTER . 1982. Verbreitungsatlas der Farn- und Blütenpflanzen der Schweiz, 2 vols. Birkhäuser, Basel.

WELTEN , M. und R. SUTTER . 1984. Erste Nachträge und Ergänzungen zum Verbreitungsatlas der Farn- und Blütenpflanzen der Schweiz; Systematisch-Geobotanisches Institut der Universität Bern, 48 pp.

WENDELBERGER G. and H. HARTEL . 1969. Untersuchungen im Brandgebiet Aletschwald. Schweizerische Zeitschrift für Forstwesen 120: 435-475

WERLEN , C. 1968. Etude de la végétation des surfaces brûlées de la forêt de Finges suivie de quelques donnés en vue d’un reboisement. Travail de diplôme, Inst. de sylviculture ETH, Zürich. 41 p.

WERNER , P. 1994. Erkenne die Natur im Wallis N o 2: Die Flora. Pillet, Martigny, 262 pp.

WHITTAKER , R.H. 1965. Dominance and diversity in land plant communities. Science 147: 250-260

WOHLGEMUTH , T., P. DUELLI , C. GINZLER , I. GÖDICKEMEIER , S. HADORN , F. HAGEDORN , P. KÜTTEL , P. LÜSCHER , M. MORETTI , G. SCHNEITER , S. SCIACCA , and B. WERMELINGER . 2005. Ökologische Resilienz nach Feuer: Die Waldbrandfläche Leuk als Modellfall. Schweizerische Zeitschrift für Forstwesen 156, 9: 345-352.

ZACKRISSON , O., 1977. Influence of forest fires on the North Swedish boreal forest. Oikos 29: 151- 179.

Appendix

A 1 Survey form

A-1

Figure A 1: Form used for vegetation survey. For each plot a different form has been created showing among other things plot number and coordinates for location and a listing of the species that have been found in the herb layer by SERENA 2005.

A-2

A 2 Site information of plot locations and climate stations

Table A 1: Swiss Grid (CH1903+LV95) coordinates, altitude, slope and aspect of the plot locations.

Plot number Easting [m] Northing [m] Altitude[m.a.s.l.] Aspect [°] Slope [°]

67 617025 131825 1860 256.5 30

71 616850 132000 1870 184.5 33

77 616800 131975 1850 180 32

80 616600 131850 1760 157.5 30

89 616450 131750 1725 175.5 38

91 616225 131550 1625 207 25

104 615925 131325 1530 166.5 32

106 616475 130750 1350 198 27

107 615975 130725 1265 198 28

109 615900 131200 1460 189 28

115 615750 131075 1400 153 36

120 616700 130875 1455 198 30

128 615400 130450 1200 252 36

129 615850 130775 1290 144 13

135 616175 130650 1280 166.5 25

138 615675 130650 1280 162 37

139 615825 130625 1235 184.5 30

140 615950 130550 1205 180 34

141 616025 130475 1180 207 31

144 616350 130625 1285 171 25

145 615700 130575 1215 144 30

147 616000 130600 1225 175.5 32

148 616100 130575 1230 198 30

150 615725 130200 1060 144 20

151 616250 130575 1250 216 33

152 616125 130450 1170 171 32

158 615975 130400 1130 180 31

163 615800 130250 1075 180 10

164 615550 130175 1095 157.5 35

234 617000 132000 1890 198 22

246 617000 131500 1780 225 25

250 616250 131250 1500 220.5 24

251 616750 131250 1620 252 20

257 616500 131000 1465 207 24

262 615750 130750 1290 121.5 32

263 616250 130750 1320 193.5 24

269 616000 130500 1180 216 26

272 615250 130250 1030 211.5 37

273 615750 130250 1075 175.5 16

277 615500 130000 1000 209.7 33

A-3

Table A 2: Swiss Grid (CH1903+LV95) coordinates, altitude, slope and aspect of the climate stations. All stations are equipped with temperature and six with precipitation (“yes”) measuring instruments.

Station number Easting [m] Northing [m] Altitude [m.a.s.l.] Aspect [°] Slope [°] Precipitation 47 615756 129987 1020 167 11 Yes 48 615415 130116 1050 206 38 No 49 615906 130488 1175 193 27 No 50 615486 130399 1215 159 15 Yes 51 615736 130850 1335 105 28 No 52 616515 130897 1435 238 27 Yes 53 616851 131467 1690 271 10 Yes 54 616461 131771 1760 189 24 No 55 616726 131976 1865 187 34 Yes 56 617106 131727 1930 237 35 No 57 617246 131989 2025 252 20 No 58 617286 132253 2085 222 10 Yes

A-4

A 3 Corrections made to species list and relevés

Table A 3: Corrections made to the list of species determined by the four surveyors: G = Iris Gödickemeier (1996), K = Peter Küttel (2004), S = Marianna Serena (2005) and T = Christian Temperli (2007).

Taxon to be corrected “Taxon to be corrected”(“Surveyor”)→”corrected taxon” Reason Specifications/remarks

Alchemilla splendens aggr. Alchemilla splendens aggr. (S) → Alchemilla xanthochlora aggr. Miss-determination

Anthyllis vulneraria alpestris Anthyllis vulneraria alpestris (S) → Anthyllis vulneria s.l. Adjustment of taxon levels

Arenaria leptoclados Arenaria leptoclados (K, S) → Arenaria serpyllifolia aggr. Adjustment of taxon levels

Brachypodium pinnatum Brachypodium pinnatum (G, K, S, T) → Brachypodium pinnatum aggr. Adjustment of taxon levels

Brachypodium rupestre Brachypodium rupestre (G) → Brachypodium pinnatum aggr. Miss-determination Besides morphological differences the species is not present in the study area (Welten und Sutter 1984/1994) Carduus defloratus defloratus Carduus defloratus defloratus (S) → Carduus defloratus s.l. Adjustment of taxon levels

Carex panicea Carex panicea (T) → Carex liparocarpos Miss-determination

Cerastium arvense strictum Cerastium arvense strictum (K, S, T) → Cerastium arvense s.l. Adjustment of taxon levels

Cerastium fontanum vulgare Cerastium fontanum vulgare (S, T) → Cerastium fontanum s.l. Adjustment of taxon levels

Chaerophyllum hirsutum s.str. Chaerophyllum hirsutum s.str. (S) → Chaerophyllum hirsutum aggr. Adjustment of taxon levels

Chaerophyllum villarsii Chaerophyllum villarsii (K, S, T) → Chaerophyllum hirsutum aggr. Adjustment of taxon levels

Epilobium collinum Epilobium collinum (S, T) → Epilobium montanum/collinum Grp. Dubiety of determination The "Epilobium montanum/collinum Grp." aggregate has been formed as the species E. montanum and E. collinum have not been distinguishable certain enough in the field. Epilobium montanum Epilobium montanum (G, K, S, T) → Epilobium montanum/collinum Grp. Dubiety of determination The "Epilobium montanum/collinum Grp." aggregate has been formed as the species E. montanum and E. collinum have not been distinguishable certain enough in the field. Epilobium obscurum Epilobium obscurum (T) → Epilobium hirsutum Miss-determination

Epilobium palustre Epilobium palustre (S) → Epilobium montanum/collinum Grp. Miss-determination

Epilobium parviflorum Epilobium parviflorum(S,T) → Epilobium montanum/collinum Grp. Miss-determination

Erigeron acer acer Erigeron acer acer (S, T) → Erigeron acer s.l. Adjustment of taxon levels

Galium pumilum Galium pumilum (T) → Galium anisophyllon Miss-determination

Geranium rotundifolium Geranium rotundifolium (S) → Galium pyrenaicum Miss-determination

Hieracium bifidum Hieracium bifidum (S, T) → Hieracium murorum Grp. Adjustment of taxon levels Part of the Hieracium murorum aggregate (Hess et al. 1998), Hiercium sp. similar to H. murorum aggr. were grouped by Gödickemeyer (1998). To follow the same taxon levels in all relevés the grouping has been revived in this correction Hieracium lachenalii Hieracium lachenalii (S, T) → Hieracium murorum Grp. Adjustment of taxon levels Hiercium sp. similar to H. murorum aggr. were grouped by Gödickemeyer (1998). To follow the same taxon levels in all releves the grouping has been revived in this correction Hieracium murorum Hieracium murorum (T) → Hieracium murorum Grp. Adjustment of taxon levels

Hieracium pictum Hieracium pictum (S, T) → Hieracium murorum Grp. Adjustment of taxon levels Part of the Hieracium murorum agrregate (Hess et al. 1998), Hiercium sp. similar to H. murorum aggr. were grouped by Gödickemeyer (1998). To follow the same taxon levels in all releves the grouping has been revived in this correction Hieracium pilosella Grp. Hiercium pilosella Grp. (K) → Hieracium pilosella Data entry mistake One determination of Küttel (Plot G135) appears as "Hieracium pilosella Grp." in the vegetation table for an unknown reason. This is being treated as a data entry mistake Juniperus communis s.l. Juniperus communis s.l. (G) → Juniperus communis communis Data entry mistake As the subspecies "Juniperus communis nana" could be determined the subspecies Juniperus communis communis" must have been distinguishable too. Knautia arvensis Knautia arvensis (K, S) → Knautia sp. Adjustment of taxon levels The species of the genus "Knautia" have not been differentiatet by Gödickemeyer (1998) and Temperli (2007) Knautia dipsacifolia Knautia dipsacifolia (K, S) → Knautia sp. Adjustment of taxon levels The species of the genus "Knautia" have not been differentiatet by Gödickemeyer (1998) and Temperli (2007) Leontodon hispidus hispidus Leontodon hispidus hispidus (T) → Leontodon hispidus s.l. Adjustment of taxon levels

Leucanthemum adustum Leucanthemum adustum (G, K, T) → Leucanthemum vulgare aggr. Adjustment of taxon levels

Phleum pratense s.str. Phleum pratense s.str. (T) → Phleum pratense aggr. Adjustment of taxon levels

Poa angustifolia Poa angustifolia (T) → Poa pratensis aggr. Adjustment of taxon levels

A-5

Poa hybrida Poa hybrida (K, S) → Poa chaixii Miss-determination Besides morphological differences the species is not present in the study area (Welten und Sutter) Poa pratensis s.str. Poa pratensis s.str. (S, T) → Poa pratensis aggr. Adjustment of taxon levels

Poa trivialis trivialis Poa trivialis trivialis (S) → Poa trivialis s.l. Adjustment of taxon levels

Potentilla pusilla Potentilla pusilla (G, K, S) → Potentilla neumanniana Miss-determination

Pulmonaria mollis Pulmonaria mollis (G) → Pulmonaria australis Miss-determination Besides morphological differences the species is not present in the study area (Welten und Sutter 1984/1994) Pulsatilla alpina alpina Pulsatilla alpina alpina (S, T) → Pulsatilla alpina s.l. Adjustment of taxon levels

Quercus pubescens Quercus pubescens (G, K, S) → Quercus sp. Adjustment of taxon levels The species Q. pubescens and Q. robur could have not been clearly differentiated in the field Rosa caesia aggr. Rosa caesia aggr. (K) → Rosa sp. Adjustment of taxon levels Gödickemeyer (1998) did not identifie the species of the genus "Rosa" any further than to the level of genus Rosa canina Rosa canina (T) → Rosa sp. Adjustment of taxon levels Gödickemeyer (1998) did not identify the species of the genus "Rosa" any further than to the level of genus. Rosa pendulina Rosa pendulina (S) → Rosa sp. Adjustment of taxon levels Gödickemeyer (1998) did not identifie the species of the genus "Rosa" any further than to the level of genus. S-Salix appendiculata Salix appendiculata (S, T) → Salix appendiculata/Caprea Grp. Dubiety of determination see conglomerate definition in chapter: 2.3.1.1 Digitalisation and corrections, p.17 S-Salix caprea Salix caprea (G, K) → Salix appendiculata/Caprea Grp. Dubiety of determination see conglomerate definition in chapter: 2.3.1.1 Digitalisation and corrections, p.17 Salix appendiculata Salix appendiculata (S, T) → Salix appendiculata/Caprea Grp. Dubiety of determination see conglomerate definition in chapter: 2.3.1.1 Digitalisation and corrections, p.17 Salix caprea Salix caprea (G, K) → Salix appendiculata/Caprea Grp. Dubiety of determination see conglomerate definition in chapter: 2.3.1.1 Digitalisation and corrections, p.17 Solidago virgaurea virgaurea Solidago virgaurea virgaurea (T) → Solidago virgaurea s.l. Adjustment of taxon levels

Stachys recta recta Stachys recta recta (T) → Stachys recta s.l. Adjustment of taxon levels

Stipa pennata aggr. Stipa pennata aggr. (G) → Stipa eriocaulis Could be clearly determined The species occuring on the sites only could be clearly determined in 2007 by Barbara Moser and Christian Temperli Stipa sp. Stipa sp. (S) → Stipa eriocaulis Could be clearly determined The species occuring on two sites only could be clearly determined in 2007 by Barbara Moser and Christian Temperli Trifolium pratense nivale Trifolium pratense nivale (T) → Trifolium pratense s.l. Adjustment of taxon levels

Trifolium pratense pratense Trifolium pratense pratense (T) → Trifolium pratense s.l. Adjustment of taxon levels

Verbascum thapsus crassifolium Verbascum thapsus crassifolium (S, T) → Verbascum thapsus s.l. Adjustment of taxon levels

Verbascum thapsus thapsus Verbascum thapsus thapsus (S, T) → Verbascum thapsus s.l. Adjustment of taxon levels

A-6

Table A 4: Corrections made to the species lists of the single relevés compiled by the four surveyors: G = Iris Gödickemeier (1996), K = Peter Küttel (2004), S = Marianna Serena (2005), T = Christian Temperli (2007).

Plot "Taxon to be corrected" (“Surveyor") → "corrected Reason Specifications/remarks number taxon" ("Surveyor") 67 Alchemilla sp. (K) → Alchemilla xanthochlora aggr. (S, T) Determined more accurately by two surveyors Galium lucidum (S) → Galium anisophyllon (G, T) Determined more accurately by two surveyors 115 Rubus sp. (K) → Rubus idaeus (G, S, T) Determined more accurately by three surveyors Sambucus sp. (T) → Sambucus racemosa (G, K) Determined more accurately by Sambucus sp. only occured at plot no. 115. Sambucus sp. will two surveyors therefore not occur in the species list anymore 120 Arabis sp.(G) → Arabis hirsuta aggr. (K, S) Determined more accurately by two surveyors Carduus sp. (T) → Carduus nutans ssp. platylepis (T) Species was determined after the digitalisation of the field data Poa sp. (K), Poa nemoralis (S) → Poa compressa (T) Miss-determination Poa sp. only occured at plot no. 120. Poa sp. will therefore not occur in the species list anymore Rubus sp. (K) → Rubus idaeus (G, S, T) Determined more accurately by three surveyors 129 Carex sp. (S) → Carex ornithopoda (G, T) Determined more accurately by two surveyors Rubus sp. (K) → Rubus idaeus (G, S, T) Determined more accurately by three surveyors 135 Carex sp. (S) → Carex humilis (G,K, T) Determined more accurately by three surveyors Arabis spec. (G) → Arabis hirsuta aggr. (K, S, T) Determined more accurately by three surveyors Verbascum sp. (G, K,S) → Verbascum thapsus s.l. (T) Determined more accurately by Temperli (2007) 138 Rubus sp. (K) → Rubus idaeus (S, T ) Determined more accurately by two surveyors 139 Carex sp. (S) → Carex humilis (G,T) Determined more accurately by two surveyors 140 Rubus sp. (K) → Rubus idaeus (S, T) Determined more accurately by two surveyors 141 Carex sp. (S) → Carex humilis (G, T) Determined more accurately by two surveyors Festuca ovina (K) → Festuca rubra (S, T) Determined more accurately by two surveyors 144 Carex sp. (S) → Carex humilis (G, T) Determined more accurately by two surveyors 147 Rubus sp. (S) → Rubus caesius (T) Determined more accurately by Temperli (2007) Rubus sp. (G) → Rubus caesius (T) Determined more accurately by Rubus caesius is the only one of the three Rubus species present in Temperli (2007) the study area Gödickemeier (1998) has not yet determined at this site S-Rubus sp.(S) → S-Rubus caesius (T) Determined more accurately by S-Rubus sp. only occured at plot no. 147 and will therefore not occur Temperli (2007) in the species list anymore Carex sp. (S) → Carex humilis (G, T) Determined more accurately by two surveyors Verbascum sp. (S) → Verbascum thapsus s.l.(T) Determined more accurately by Temperli (2007) 148 Arabis sp. (G) → Arabis hirsuta aggr. (S, T) Determined more accurately by two surveyors Verbascum sp. (G, T) → Verbascum lychnitis (K, S) Determined more accurately by two surveyors 150 Carex sp. (S) → Carex humilis (G, K, T) Determined more accurately by three surveyors Rubus sp. (K) → Rubus caesius (S, T) Determined more accurately by two surveyors 151 Carex sp. (S) → Carex humilis (G, T) Determined more accurately by two surveyors Trifolium medium (K, S) → Trifolium pratense s.l. (T) Miss-determination Stipules too short!

Rubus sp. (K) → Rubus caesius (S , T) Determined more accurately by two surveyors 152 Carex sp. (S) → Carex humilis (G, K, T) Determined more accurately by three surveyors Rubus sp. (K) → Rubus idaeus (T) Determined more accurately by Temperli (2007) Rubus caesius (S) → Rubus idaeus (T) Miss-determination

Ononis repens (K) → Ononis pusilla (S, T) Determined more accurately by two surveyors 158 Carex sp. (S) → Carex humilis (G, K, T) Determined more accurately by three surveyors 164 Carex sp. (S) → Carex humilis (G, K, T) Determined more accurately by three surveyors Viola rupestris (S) → Viola reichenbachiana (T) Miss-determination

Verbascum sp. (S) → Verbascum thapsus s.l.(K) Determined more accurately by Küttel (2004) Ononis repens (G, K) → Ononis pusilla (S, T) Determined more accurately by two surveyors 234 Galium lucidum (S) → Galium anisophyllon (G, T) Miss-determination

Galium album (K, S) → Galium anisophyllon (G, T) Miss-determination

A-7

Poa trivialis s.l. (K, S) → Poa pratensis aggr. (T) Miss-determination

246 Viola sp. (G) → V. rupestris (K, S, T) Determined more accurately by three surveyors 250 Arabis hirsuta agg. (S) → Arabis collina (T) Miss-determination

Carex sp. (S) → Carex ornithopoda (G, T) Determined more accurately by two surveyors Sambucus nigra (S) → Sambucus racemosa (T) Miss-determination

251 Carex sp. (S) → Carex ornithopoda (G, K, T) Determined more accurately by three surveyors Verbascum sp. (S) → Verbascum thapsus s.l. (T) Determined more accurately by Temperli (2007) Viola sp. (G) → Viola rupestris (K, S, T) Determined more accurately by three surveyors 257 Ononis repens (G, K, S) → Ononis spinosa (T) Determined more accurately by Thorns! Temperli (2007) Rubus caesius (S) → Rubus idaeus (G, K, T) Determined more accurately by three surveyors 262 Rubus sp. (K) → Rubus caesius (S, T) Determined more accurately by two surveyors Carex sp. (S) → Carex humilis (G, T) Determined more accurately by two surveyors 263 Carex sp.(S) → Carex humilis (G, K, T); Determined more accurately by three surveyors Rubus sp. (K) → Rubus caesius (S , T) Determined more accurately by two surveyors 272 Carex sp (K, S) → Carex humilis (G ,T) Determined more accurately by two surveyors Rubus sp. (K) → Rubus idaeus (G, T) Determined more accurately by two surveyors Rubus caesius (S) → Rubus idaeus (G, T) Miss-determination

Solanum nigrum (S) → Solanum dulcamara (T) Miss-determination Solanum nigrum only occured at plot no. 272 and will therefore not occur in the species list anymore Sedum sp. (S) → Sedum album (T) Determined more accurately by Sedum sp. only occured at plot no. 272 and will therefore not occur in Temperli (2007) the species list anymore 273 Molinia caerulea (G) → M. arundinacea (K, S, T) Miss-determination M. caerulea is a wet land plant!

Ononis pusilla (S) → Ononis spinosa (T) Miss-determination Thorns!

277 Carex sp. (K, S ) → Carex humilis (G, T) Determined more accurately by two surveyors Orobanche sp. (G) Orobanche teucrii (T) Determined more accurately by Temperli (2007) Rubus sp. (G, K) → Rubus caesius (S, T) Determined more accurately by two surveyors

A-8

A 4 New and lost species

Table A 5: Species found the first time (New species) and the species not found (Lost species) in 2004 on the fire patch anymore. The species are ordered after ecological groups (LANDOLT 1991).

New species 2004 Lost species 2004

Woodland plants Ruderal plants Woodland plants Dry grassland plants Digitalis lutea Amaranthus retroflexus Acer campestre Asperula cynanchica Geranium bohemicum Artemisia absinthium Aegopodium podagraria Briza media Peucedanum cervaria Blitum virgatum Agropyron caninum Dianthus carthusianorum s.l. Poa nemoralis Chaenorrhinum minus Anthericum ramosum Himantoglossum hircinum Solanum dulcamara Chenopodium album Carex digitata Juniperus sabina Trifolium alpestre Chenopodium hybridum Carlina vulgaris aggr. Linum tenuifolium Cirsium vulgare Dryopteris filix-mas Origanum vulgare

Mountain plants Conyza canadensis Juniperus communis communis Polygala vulgaris s.l. Laserpitium gaudinii Fallopia convolvulus Ligustrum vulgare Sedum montanum Peucedanum ostruthium Galeopsis ladanum Limodorum abortivum Thlaspi perfoliatum Pulmonaria australis Galium aparine Lonicera xylosteum

Viola biflora Lactuca serriola Melampyrum pratense Plants of rich pastures Malva neglecta Neottia nidus-avis Pastinaca sativa s.l.

Dry grassland plants Poa compressa Odontites viscosus Prunella vulgaris Echium vulgare Senecio vulgaris Orthilia secunda Trifolium dubium Minuartia rubra Sinapis alba Pinus sylvestris

Ononis repens Sinapis arvensis Prenanthes purpurea Lowland pioneer plants Pimpinella saxifraga aggr. Sonchus arvensis s.l. Pyrola chlorantha

Pulsatilla montana Sonchus asper Senecio ovatus Asplenium viride Sorbus aucuparia Polypodium vulgare

Plants of rich pastures Others Salix purpurea s.l.

Alchemilla xanthochlora aggr. Brassica napus Mountain plants

Dactylis glomerata Alchemilla conjuncta aggr. Ruderal plants

Galium album Wetland plants Aster alpinus Potentilla reptans Lolium perenne Hypericum maculatum s.l. Aster bellidiastrum

Medicago lupulina Linum catharticum Botrychium lunaria Others Phleum pratense aggr. Campanula rhomboidalis Arabis sp.

Poa trivialis s.l. Cerastium alpinum s.l. Euphrasia sp.

Cirsium eriophorum s.l. Orobanche sp.

Lowland pioneer plants Crepis conyzifolia Pulmonaria mollis

Campanula rapunculoides Erigeron alpinus

Galeopsis angustifolia Homogyne alpina Wetland plants

Juniperus communis nana Carex flacca

Poa alpina Gymnadenia conopsea

Poa supina Rhinanthus alectorolophus

Rhamnus alpina Trollius europaeus

Sedum alpestre

Sedum annuum

Sempervivum montanum

Sempervivum tectorum s.l.

Sesleria caerulea

Silene rupestris

Number of species 46 Number of species 65 A-9

Table A 6: Species found the first time (New species) and the species not found (Lost species) in 2005 on the fire patch anymore. The species are ordered after ecological groups (LANDOLT 1991).

New species 2005 Lost species 2005

Woodland plants Lowland pioneer plants Woodland plants

Aconitum vulparia aggr. Arabis collina Avenella flexuosa

Astragalus glycyphyllos Arabis nova Galium rotundifolium

Atropa belladonna Calamagrostis epigejos Luzula sylvatica aggr.

Carex montana Epilobium dodonaei Phyteuma spicatum

Colutea arborescens Erigeron acer s.l.

Coronilla coronata Erucastrum nasturtiifolium Mountain plants

Festuca heterophylla Hieracium glaucum Potentilla aurea

Geum urbanum Hieracium staticifolium

Populus alba Ononis natrix Others

Rhamnus cathartica Scleranthus perennis Viola sp.

Sambucus nigra Sedum acre

Viola collina Sedum dasyphyllum

Viola reichenbachiana

Ruderal plants

Mountain plants Artemisia vulgaris

Arabis ciliata Capsella bursa-pastoris

Campanula scheuchzeri Cerastium fontanum s.l.

Dianthus sylvestris Chenopodium bonus-henricus

Geranium rivulare Erophila verna aggr.

Polygala alpestris Isatis tinctoria

Trifolium badium Lappula squarrosa

Veronica fruticulosa Polygonum aviculare aggr.

Setaria verticillata

Dry grassland plants Setaria viridis

Alyssum alyssoides Sonchus oleraceus

Bromus erectus s.l. Stellaria media aggr.

Hieracium lactucella Torilis arvensis

Luzula campestris Tragopogon dubius

Trifolium hybridum

Plants of rich pastures

Bellis perennis Others

Bromus hordeaceus Carex sp.

Medicago sativa Festuca sp.

Pimpinella major Triticum dicoccon

Wetland plants

Epilobium hirsutum

Festuca arundinacea s.l.

Number of species 60 Number of species 6

A-10

Table A 7: Species found the first time (New species) and the species not found (Lost species) in 2007 on the fire patch anymore. The species are ordered after ecological groups (LANDOLT 1991).

New species 2007 Lost species 2007

Woodland plants Lowland pioneer plants Others

Hieracium sabaudum Cystopteris fragilis Rubus sp.

Juglans regia Herniaria glabra Festuca valesiaca s.l.

Lathyrus heterophyllus

Lathyrus sylvestris Ruderal plants

Lonicera nigra Bromus sterilis

Populus nigra s.l. Crepis pulchra

Descurainia sophia

Mountain plants Erigeron annuus s.l.

Fourraea alpina Lactuca virosa

Myosotis alpestris Lappula deflexa

Rumex alpestris Orobanche minor

Veratrum album s.l. Papaver dubium s.l.

Plantago major s.l.

Dry grassland plants Poa annua

Carex liparocarpos Rumex acetosella aggr.

Euphrasia stricta Scorzonera laciniata

Fumana procumbens Solidago canadensis

Inula conyza

Medicago minima Others

Petrorhagia prolifera Carduus sp.

Phleum phleoides Cornus sp.

Turritis glabra Epipactis sp.

Veronica spicata Lappula sp.

Sonchus sp.

Plants of rich pastures

Crepis capillaris Wetland plants

Number of species 20 Number of species 2

A-11

A 5 Species lists

Table A 8: List of species and recorded in the herb layer on 5a by GÖDICKEMEIER (1998) in 1996. Additionally the percentages of number of plots a species has been present and the mean cover it has recorded with is listed.

Species name Presence [%] Mean cover [%] Species name Presence [%] Mean cover [%] Abies alba 42.5 0.355 Laserpitium siler 30 0.904 Acer campestre 2.5 0.001 Lathyrus pratensis 12.5 0.063 Acer pseudoplatanus 15 0.008 Leontodon hispidus s.l. 10 0.028 Achillea millefolium aggr. 7.5 0.026 Leucanthemum vulgare aggr. 40 0.428 Achnatherum calamagrostis 7.5 0.100 Ligustrum vulgare 5 0.003 Acinos alpinus 17.5 0.201 Limodorum abortivum 5 0.003 Acinos arvensis 7.5 0.078 Linum tenuifolium 5 0.003 Aegopodium podagraria 2.5 0.013 Lonicera xylosteum 25 0.069 Agropyron caninum 12.5 0.051 Lotus corniculatus aggr. 57.5 0.390 Agrostis capillaris 20 0.826 Luzula luzulina 12.5 0.040 Agrostis gigantea 2.5 0.075 Luzula nivea 2.5 0.001 Ajuga genevensis 5 0.014 Luzula sylvatica aggr 7.5 0.026 Ajuga pyramidalis 2.5 0.001 Maianthemum bifolium 5 0.025 Alchemilla conjuncta aggr. 2.5 0.013 Melampyrum pratense 65 2.815 Alchemilla sp. 7.5 0.026 Melampyrum sylvaticum 55 4.638 Amelanchier ovalis 25 0.091 Melica ciliata 2.5 0.013 Anthericum liliago 2.5 0.001 Melica nutans 7.5 0.825 Anthericum ramosum 2.5 0.013 Molinia arundinacea 2.5 0.075 Anthoxanthum odoratum aggr. 10 0.039 Mycelis muralis 7.5 0.015 Anthyllis vulneraria s.l. 12.5 0.051 Myosotis sylvatica 2.5 0.013 Aquilegia atrata 7.5 0.100 Neottia nidus-avis 25 0.046 Arabis hirsuta aggr. 7.5 0.038 Odontites viscosus 2.5 0.013 Arabis sp. 27.5 0.093 Ononis pusilla 5 0.014 Arctostaphylos uva-ursi 67.5 14.641 Ononis rotundifolia 12.5 0.051 Arenaria serpyllifolia aggr. 7.5 0.151 Ononis spinosa s.l. 2.5 0.075 Asperula cynanchica 2.5 0.013 Origanum vulgare 2.5 0.013 Asplenium ruta-muraria 10 0.016 Orobanche sp. 2.5 0.001 Asplenium viride 2.5 0.013 Orobanche teucrii 2.5 0.013 Aster alpinus 2.5 0.013 Orthilia secunda 37.5 0.364 Aster bellidiastrum 2.5 0.013 Pastinaca sativa s.l. 2.5 0.001 Astragalus monspessulanus 20 0.140 Peucedanum oreoselinum 17.5 0.065 Avenella flexuosa 2.5 0.075 Phyteuma betonicifolium 10 0.050 Berberis vulgaris 37.5 0.143 Phyteuma orbiculare 10 0.050 Betula pendula 7.5 0.015 Phyteuma spicatum 15 0.115 Biscutella laevigata 2.5 0.001 Picea abies 82.5 0.906 Botrychium lunaria 2.5 0.001 Pinus sylvestris 67.5 0.413 Brachypodium pinnatum aggr. 30 1.539 Plantago atrata 5 0.014 Briza media 2.5 0.075 Plantago lanceolata 2.5 0.001 Calamagrostis varia 40 2.939 Poa alpina 2.5 0.013 Calamagrostis villosa 37.5 2.400 Poa chaixii 22.5 0.215 Campanula barbata 17.5 0.054 Poa pratensis aggr. 2.5 0.013 Campanula cochleariifolia 10 0.175 Poa supina 2.5 0.001 Campanula rhomboidalis 2.5 0.013 Polygala chamaebuxus 82.5 1.129 Campanula rotundifolia 72.5 0.284 Polygala vulgaris s.l. 15 0.053 Carduus defloratus s.l. 42.5 0.293 Polygonatum odoratum 15 0.041 Carex alba 7.5 0.825 Polypodium vulgare 7.5 0.004 Carex digitata 5 0.025 Populus tremula 5 0.014 Carex flacca 7.5 0.038 Potentilla aurea 2.5 0.013 Carex halleriana 5 0.025 Potentilla crantzii 2.5 0.013 Carex humilis 65 12.351 Potentilla grandiflora 7.5 0.038 Carex ornithopoda 50 0.903 Potentilla neumanniana 7.5 0.100 Carlina acaulis 10 0.028 Potentilla reptans 2.5 0.075 Carlina vulgaris aggr. 2.5 0.013 Prenanthes purpurea 5 0.025 Centaurea scabiosa s.l. 5 0.025 Prunella grandiflora 25 0.563 Cephalanthera longifolia 20 0.066 Prunella vulgaris 2.5 0.013 Cephalanthera rubra 30 0.094 Prunus avium 10 0.028 Cerastium alpinum s.l. 2.5 0.013 Pulmonaria mollis 15 0.053 Cerastium arvense s.l. 5 0.025 Pulsatilla alpina s.l. 17.5 0.201 Chaerophyllum hirsutum aggr. 20 0.950 Pyrola chlorantha 27.5 0.115 Cirsium acaule 20 0.066 Quercus sp. 60 0.199 Cirsium arvense 20 0.066 Ranunculus nemorosus aggr. 25 0.165 Cirsium eriophorum s.l. 5 0.003 Reseda lutea 5 0.025 Clematis vitalba 2.5 0.013 Rhamnus alpina 5 0.003 Clinopodium vulgare 7.5 0.026 Rhinanthus alectorolophus 5 0.025 Coronilla minima 2.5 0.001 Rosa sp. 37.5 0.138 Corylus avellana 57.5 0.130 Rubus caesius 5 0.088 Cotoneaster integerrima 22.5 0.788 Rubus idaeus 52.5 0.468 Cotoneaster tomentosa 22.5 0.164 Rubus saxatilis 27.5 0.450 Crepis conyzifolia 2.5 0.013 Rubus sp. 10 0.016 Cuscuta epithymum 7.5 0.038 Salix appendiculata/caprea 15 0.041 Daucus carota 2.5 0.001 Salix purpurea s.l. 2.5 0.001 Dianthus carthusianorum s.l. 5 0.003 Sambucus racemosa 5 0.003 Dryopteris filix-mas 2.5 0.001 Sanguisorba minor s.l. 20 0.254 Epilobium angustifolium 17.5 0.043 Saponaria ocymoides 60 0.483 A-12

Epilobium montanum/collinum Grp. 5 0.014 Saxifraga paniculata 12.5 0.176 Epipactis atrorubens 50 0.149 Securigera varia 12.5 0.040 Epipactis helleborine aggr. 15 0.064 Sedum album 17.5 0.088 Erigeron alpinus 2.5 0.013 Sedum alpestre 2.5 0.075 Erysimum rhaeticum 10 0.005 Sedum annuum 2.5 0.001 Euphorbia cyparissias 90 1.540 Sedum montanum 17.5 0.054 Euphorbia seguieriana 5 0.014 Sempervivum montanum 2.5 0.013 Euphrasia sp. 5 0.025 Sempervivum tectorum s.l. 5 0.003 Festuca ovina aggr. 10 0.028 Senecio doronicum 7.5 0.004 Festuca rubra s.l. 17.5 0.700 Senecio ovatus 5 0.003 Festuca valesiaca s.l. 12.5 0.613 Senecio viscosus 2.5 0.001 Filago arvensis 2.5 0.013 Sesleria caerulea 5 0.014 Fragaria vesca 62.5 0.881 Silene nutans s.l. 65 0.331 Fraxinus excelsior 10 0.005 Silene rupestris 2.5 0.013 Galeopsis tetrahit 2.5 0.001 Silene vulgaris s.l. 17.5 0.201 Galium anisophyllon 27.5 0.126 Solidago virgaurea s.l. 87.5 1.091 Galium lucidum 65 0.456 Sorbus aria 67.5 0.236 Galium rotundifolium 2.5 0.001 Sorbus aucuparia 17.5 0.031 Galium verum s.l. 10 0.050 Stachys recta s.l. 7.5 0.026 Gentiana campestris 5 0.014 Stipa eriocaulis 2.5 0.013 Geranium pyrenaicum 2.5 0.013 Taraxacum officinale aggr. 12.5 0.006 Geranium robertianum s.l. 2.5 0.013 Telephium imperati 2.5 0.001 Geranium sylvaticum 17.5 0.501 Teucrium chamaedrys 67.5 1.378 Globularia cordifolia 10 0.175 Teucrium montanum 15 0.138 Globularia punctata 2.5 0.013 Thesium alpinum 20 0.066 Gymnadenia conopsea 2.5 0.013 Thlaspi perfoliatum 2.5 0.013 Helianthemum nummularium s.l. 42.5 1.103 Thymus serpyllum aggr. 45 0.940 Hepatica nobilis 30 0.638 Trifolium dubium 2.5 0.075 Heracleum sphondylium s.l. 2.5 0.013 Trifolium medium 5 0.388 Hieracium murorum Grp. 100 1.901 Trifolium pratense s.l. 15 0.075 Hieracium pilosella 17.5 0.201 Trifolium repens 5 0.025 Hieracium prenanthoides 10 0.101 Trollius europaeus 2.5 0.013 Himantoglossum hircinum 2.5 0.001 Tussilago farfara 7.5 0.026 Hippocrepis comosa 55 1.126 Urtica dioica 5 0.003 Hippocrepis emerus 32.5 0.140 Vaccinium myrtillus 15 0.625 Homogyne alpina 5 0.014 Vaccinium vitis-idaea 15 1.225 Hypericum perforatum 2.5 0.001 Valeriana tripteris 22.5 0.193 Juniperus communis nana 17.5 0.213 Verbascum lychnitis 2.5 0.001 Juniperus communis communis 42.5 0.145 Verbascum sp. 10 0.005 Juniperus sabina 2.5 0.013 Verbascum thapsus s.l. 2.5 0.001 Kernera saxatilis 5 0.014 Veronica chamaedrys 5 0.025 Knautia sp. 52.5 0.508 Veronica officinalis 15 0.126 Lactuca perennis 10 0.016 Viburnum lantana 10 0.016 Larix decidua 40 0.206 Viola rupestris 5 0.076 Laserpitium latifolium 27.5 0.466 Viola sp. 12.5 0.114

A-13

Table A 9: List of species and recorded in the herb layer on 5a by KÜTTEL (2004) in 2004. Additionally the percentages of number of plots a species has been present and the mean cover it has recorded with is listed.

Species name Presence [%] Mean cover [%] Species name Presence [%] Mean cover [%] Acer pseudoplatanus 5 0.003 Laserpitium siler 30 0.038 Achillea millefolium aggr. 2.5 0.001 Lathyrus pratensis 22.5 0.023 Achnatherum calamagrostis 10 0.101 Leucanthemum vulgare aggr. 20 0.010 Acinos alpinus 12.5 0.006 Linum catharticum 2.5 0.001 Agrostis capillaris 5 0.003 Lolium perenne 2.5 0.001 Alchemilla xanthochlora aggr. 2.5 0.001 Lotus corniculatus aggr. 60 0.075 Amaranthus retroflexus 2.5 0.001 Luzula sylvatica aggr 2.5 0.001 Amelanchier ovalis 2.5 0.001 Malva neglecta 2.5 0.001 Anthyllis vulneraria s.l. 10 0.005 Medicago lupulina 7.5 0.004 Aquilegia atrata 2.5 0.001 Melampyrum sylvaticum 2.5 0.001 Arabis hirsuta aggr. 5 0.003 Melica ciliata 5 0.003 Arctostaphylos uva-ursi 17.5 0.009 Melica nutans 5 0.003 Arenaria serpyllifolia aggr. 17.5 0.043 Minuartia rubra 2.5 0.001 Artemisia absinthium 2.5 0.001 Molinia arundinacea 5 0.014 Asplenium ruta-muraria 5 0.003 Myosotis sylvatica 2.5 0.001 Astragalus monspessulanus 35 0.063 Ononis pusilla 7.5 0.015 Avenella flexuosa 2.5 0.001 Ononis repens 2.5 0.013 Berberis vulgaris 42.5 0.044 Ononis rotundifolia 10 0.005 Betula pendula 2.5 0.001 Ononis spinosa s.l. 2.5 0.001 Biscutella laevigata 5 0.003 Peucedanum cervaria 5 0.003 Blitum virgatum 2.5 0.001 Peucedanum oreoselinum 25 0.069 Brachypodium pinnatum aggr. 25 0.165 Peucedanum ostruthium 2.5 0.001 Brassica napus 2.5 0.001 Phleum pratense aggr. 2.5 0.001 Calamagrostis varia 75 0.456 Phyteuma betonicifolium 7.5 0.015 Calamagrostis villosa 2.5 0.075 Phyteuma spicatum 2.5 0.001 Campanula barbata 5 0.003 Picea abies 17.5 0.009 Campanula cochleariifolia 2.5 0.013 Pimpinella saxifraga aggr. 2.5 0.001 Campanula rapunculoides 5 0.003 Plantago atrata 2.5 0.001 Campanula rotundifolia 80 0.141 Plantago lanceolata 2.5 0.001 Carduus defloratus s.l. 12.5 0.006 Poa chaixii 5 0.014 Carex humilis 35 0.051 Poa compressa 7.5 0.004 Carex ornithopoda 10 0.005 Poa nemoralis 5 0.003 Carlina acaulis 5 0.003 Poa pratensis aggr. 2.5 0.001 Centaurea scabiosa s.l. 15 0.064 Poa trivialis s.l. 7.5 0.015 Cephalanthera rubra 5 0.003 Polygala chamaebuxus 45 0.023 Cerastium arvense s.l. 2.5 0.013 Populus tremula 32.5 0.028 Chaenorrhinum minus 30 0.026 Potentilla aurea 5 0.003 Chaerophyllum hirsutum aggr. 7.5 0.004 Potentilla neumanniana 2.5 0.001 Chenopodium album 20 0.010 Prunella grandiflora 12.5 0.006 Chenopodium hybridum 5 0.003 Pulmonaria australis 10 0.005 Cirsium acaule 15 0.019 Pulsatilla alpina s.l. 5 0.003 Cirsium arvense 32.5 0.061 Pulsatilla montana 2.5 0.001 Cirsium vulgare 12.5 0.006 Quercus sp. 7.5 0.004 Clinopodium vulgare 7.5 0.004 Ranunculus nemorosus aggr. 7.5 0.004 Conyza canadensis 22.5 0.011 Reseda lutea 22.5 0.023 Coronilla minima 5 0.003 Rosa sp. 22.5 0.023 Cotoneaster integerrima 15 0.008 Rubus caesius 12.5 0.391 Cotoneaster tomentosa 2.5 0.001 Rubus idaeus 45 0.034 Cuscuta epithymum 2.5 0.001 Rubus saxatilis 10 0.464 Dactylis glomerata 5 0.003 Rubus sp. 20 0.084 Digitalis lutea 2.5 0.001 Salix appendiculata/caprea 22.5 0.011 Echium vulgare 2.5 0.001 Sambucus racemosa 12.5 0.006 Epilobium angustifolium 55 0.084 Sanguisorba minor s.l. 20 0.010 Epilobium montanum/collinum Grp. 7.5 0.004 Saponaria ocymoides 80 0.419 Epipactis atrorubens 55 0.039 Securigera varia 22.5 0.023 Epipactis helleborine aggr. 27.5 0.014 Sedum album 2.5 0.001 Euphorbia cyparissias 85 0.591 Senecio doronicum 5 0.003 Euphorbia seguieriana 2.5 0.001 Senecio vulgaris 15 0.008 Fallopia convolvulus 2.5 0.001 Silene nutans s.l. 27.5 0.025 Festuca ovina aggr. 2.5 0.001 Silene vulgaris s.l. 15 0.008 Festuca rubra s.l. 27.5 0.036 Sinapis alba 10 0.005 Festuca valesiaca s.l. 5 0.003 Sinapis arvensis 2.5 0.001 Fragaria vesca 17.5 0.009 Solanum dulcamara 12.5 0.006 Galeopsis angustifolia 2.5 0.001 Solidago virgaurea s.l. 12.5 0.006 Galeopsis ladanum 12.5 0.006 Sonchus arvensis s.l. 2.5 0.001 Galeopsis tetrahit 20 0.010 Sonchus asper 2.5 0.001 Galium album 5 0.003 Sorbus aria 7.5 0.004 Galium anisophyllon 5 0.003 Stachys recta s.l. 5 0.003 Galium aparine 2.5 0.001 Taraxacum officinale aggr. 27.5 0.014 Galium lucidum 15 0.041 Teucrium chamaedrys 47.5 0.221 Galium rotundifolium 2.5 0.001 Teucrium montanum 7.5 0.026 Galium verum s.l. 22.5 0.045 Thymus serpyllum aggr. 5 0.003 Geranium bohemicum 2.5 0.001 Trifolium alpestre 5 0.003 Geranium pyrenaicum 7.5 0.004 Trifolium medium 10 0.005 Geranium sylvaticum 7.5 0.004 Trifolium pratense s.l. 17.5 0.009 Globularia cordifolia 2.5 0.001 Trifolium repens 2.5 0.001 Helianthemum nummularium s.l. 45 0.034 Tussilago farfara 15 0.081 Hepatica nobilis 7.5 0.004 Urtica dioica 2.5 0.001 A-14

Heracleum sphondylium s.l. 2.5 0.001 Vaccinium myrtillus 7.5 0.004 Hieracium murorum Grp. 32.5 0.016 Valeriana tripteris 2.5 0.001 Hieracium pilosella 2.5 0.001 Verbascum lychnitis 2.5 0.001 Hippocrepis comosa 37.5 0.030 Verbascum sp. 20 0.010 Hippocrepis emerus 12.5 0.006 Verbascum thapsus s.l. 20 0.010 Hypericum maculatum s.l. 5 0.003 Veronica chamaedrys 2.5 0.001 Hypericum perforatum 2.5 0.001 Veronica officinalis 15 0.008 Knautia sp. 47.5 0.125 Viburnum lantana 2.5 0.001 Lactuca perennis 15 0.019 Viola biflora 2.5 0.001 Lactuca serriola 12.5 0.006 Viola rupestris 25 0.013 Laserpitium gaudinii 7.5 0.004 Viola sp. 7.5 0.004 Laserpitium latifolium 20 0.095

A-15

Table A 10: List of species and recorded in the herb layer on 5a by SERENA (2005) in 2005. Additionally the percentages of number of plots a species has been present and the mean cover it has recorded with is listed.

Species name Presence [%] Mean cover [%] Species name Presence [%] Mean cover [%] Abies alba 5 0.014 Hieracium staticifolium 2.5 0.013 Acer pseudoplatanus 12.5 0.018 Hippocrepis comosa 45 0.191 Achillea millefolium aggr. 22.5 0.079 Hippocrepis emerus 30 0.139 Achnatherum calamagrostis 20 0.191 Hypericum maculatum s.l. 5 0.025 Acinos alpinus 22.5 0.101 Hypericum perforatum 7.5 0.026 Acinos arvensis 12.5 0.063 Isatis tinctoria 17.5 0.128 Aconitum vulparia aggr. 2.5 0.001 Knautia sp. 57.5 0.379 Agrostis capillaris 17.5 0.054 Lactuca perennis 57.5 0.254 Ajuga pyramidalis 12.5 0.051 Lactuca serriola 85 0.454 Alchemilla sp. 2.5 0.001 Lappula squarrosa 2.5 0.001 Alchemilla xanthochlora aggr. 5 0.025 Larix decidua 12.5 0.051 Alyssum alyssoides 5 0.025 Laserpitium gaudinii 7.5 0.026 Amaranthus retroflexus 5 0.014 Laserpitium latifolium 35 0.141 Amelanchier ovalis 2.5 0.001 Laserpitium siler 40 0.529 Anthericum liliago 5 0.025 Lathyrus pratensis 27.5 0.178 Anthoxanthum odoratum aggr. 2.5 0.013 Leontodon hispidus s.l. 10 0.039 Anthyllis vulneraria s.l. 12.5 0.051 Leucanthemum vulgare aggr. 40 0.178 Aquilegia atrata 5 0.025 Linum catharticum 2.5 0.013 Arabis ciliata 2.5 0.013 Lolium perenne 5 0.014 Arabis collina 2.5 0.013 Lotus corniculatus aggr. 65 0.365 Arabis hirsuta aggr. 20 0.078 Luzula campestris 2.5 0.001 Arabis nova 5 0.025 Luzula luzulina 2.5 0.001 Arctostaphylos uva-ursi 67.5 0.315 Luzula nivea 2.5 0.013 Arenaria serpyllifolia aggr. 30 0.638 Maianthemum bifolium 2.5 0.013 Artemisia absinthium 7.5 0.015 Medicago lupulina 20 0.089 Artemisia vulgaris 2.5 0.013 Medicago sativa 2.5 0.001 Asplenium ruta-muraria 12.5 0.029 Melampyrum sylvaticum 7.5 0.015 Astragalus glycyphyllos 2.5 0.001 Melica ciliata 10 0.039 Astragalus monspessulanus 35 0.153 Melica nutans 5 0.025 Atropa belladonna 7.5 0.004 Minuartia rubra 2.5 0.013 Bellis perennis 2.5 0.001 Molinia arundinacea 5 0.088 Berberis vulgaris 32.5 0.129 Mycelis muralis 12.5 0.029 Betula pendula 20 0.033 Myosotis sylvatica 5 0.014 Biscutella laevigata 7.5 0.026 Ononis natrix 2.5 0.001 Blitum virgatum 57.5 0.254 Ononis pusilla 12.5 0.040 Brachypodium pinnatum aggr. 30 0.678 Ononis repens 2.5 0.013 Bromus erectus s.l. 12.5 0.114 Ononis rotundifolia 17.5 0.139 Bromus hordeaceus 2.5 0.013 Ononis spinosa s.l. 5 0.076 Calamagrostis epigejos 2.5 0.013 Peucedanum cervaria 10 0.028 Calamagrostis varia 82.5 2.103 Peucedanum oreoselinum 32.5 0.140 Calamagrostis villosa 7.5 0.100 Peucedanum ostruthium 5 0.014 Campanula barbata 7.5 0.038 Phleum pratense aggr. 7.5 0.026 Campanula cochleariifolia 2.5 0.013 Phyteuma betonicifolium 10 0.050 Campanula rapunculoides 7.5 0.038 Phyteuma orbiculare 5 0.025 Campanula rotundifolia 92.5 0.525 Picea abies 25 0.058 Campanula scheuchzeri 7.5 0.026 Pimpinella major 5 0.003 Capsella bursa-pastoris 2.5 0.001 Pimpinella saxifraga aggr. 2.5 0.013 Carduus defloratus s.l. 30 0.156 Plantago atrata 5 0.025 Carex alba 2.5 0.001 Poa chaixii 10 0.028 Carex flacca 2.5 0.001 Poa compressa 30 0.128 Carex humilis 52.5 0.240 Poa nemoralis 2.5 0.013 Carex montana 10 0.039 Poa pratensis aggr. 10 0.050 Carex ornithopoda 7.5 0.038 Poa trivialis s.l. 5 0.088 Carex sp. 17.5 0.088 Polygala alpestris 2.5 0.001 Carlina acaulis 17.5 0.076 Polygala chamaebuxus 40 0.133 Centaurea scabiosa s.l. 27.5 0.603 Polygonatum odoratum 7.5 0.038 Cephalanthera longifolia 2.5 0.013 Polygonum aviculare aggr. 7.5 0.015 Cephalanthera rubra 5 0.014 Populus alba 20 0.033 Cerastium arvense s.l. 12.5 0.051 Populus tremula 82.5 0.680 Cerastium fontanum s.l. 2.5 0.013 Potentilla crantzii 2.5 0.013 Chaenorrhinum minus 52.5 0.218 Potentilla neumanniana 10 0.050 Chaerophyllum hirsutum aggr. 7.5 0.038 Prunella grandiflora 12.5 0.051 Chenopodium album 72.5 0.346 Pulmonaria australis 12.5 0.063 Chenopodium bonus-henricus 2.5 0.001 Pulsatilla alpina s.l. 12.5 0.051 Chenopodium hybridum 7.5 0.038 Quercus sp. 22.5 0.079 Cirsium acaule 7.5 0.026 Ranunculus nemorosus aggr. 10 0.050 Cirsium arvense 77.5 0.553 Reseda lutea 35 0.141 Cirsium vulgare 57.5 0.254 Rhamnus cathartica 2.5 0.013 Clematis vitalba 2.5 0.001 Rosa sp. 25 0.035 Clinopodium vulgare 7.5 0.038 Rubus caesius 40 1.504 Colutea arborescens 5 0.025 Rubus idaeus 70 0.589 Conyza canadensis 92.5 0.888 Rubus saxatilis 12.5 0.850 Coronilla coronata 2.5 0.013 Rubus sp. 5 0.150 Coronilla minima 10 0.016 Salix appendiculata/caprea 65 0.434 Corylus avellana 5 0.014 Sambucus nigra 10 0.028 Cotoneaster integerrima 12.5 0.063 Sambucus racemosa 15 0.041 Cotoneaster tomentosa 7.5 0.015 Sanguisorba minor s.l. 20 0.078 Cuscuta epithymum 2.5 0.013 Saponaria ocymoides 95 1.650 A-16

Dactylis glomerata 10 0.016 Scleranthus perennis 2.5 0.001 Daucus carota 7.5 0.026 Securigera varia 40 0.229 Dianthus sylvestris 2.5 0.013 Sedum acre 2.5 0.001 Digitalis lutea 2.5 0.001 Sedum album 15 0.041 Echium vulgare 2.5 0.013 Sedum dasyphyllum 7.5 0.004 Epilobium angustifolium 85 3.390 Senecio doronicum 5 0.025 Epilobium dodonaei 5 0.003 Senecio viscosus 27.5 0.115 Epilobium hirsutum 10 0.016 Senecio vulgaris 92.5 0.440 Epilobium montanum/collinum Grp. 30 0.105 Setaria verticillata 2.5 0.001 Epipactis atrorubens 80 0.344 Setaria viridis 2.5 0.013 Epipactis helleborine aggr. 30 0.060 Silene nutans s.l. 45 0.169 Erigeron acer s.l. 10 0.028 Silene vulgaris s.l. 15 0.075 Erophila verna aggr. 2.5 0.013 Sinapis alba 10 0.039 Erucastrum nasturtiifolium 2.5 0.001 Sinapis arvensis 7.5 0.038 Erysimum rhaeticum 5 0.014 Solanum dulcamara 40 0.110 Euphorbia cyparissias 90 1.115 Solidago virgaurea s.l. 17.5 0.054 Euphorbia seguieriana 2.5 0.075 Sonchus asper 40 0.121 Fallopia convolvulus 2.5 0.001 Sonchus oleraceus 22.5 0.045 Festuca arundinacea s.l. 5 0.003 Sorbus aria 15 0.041 Festuca heterophylla 12.5 0.051 Stachys recta s.l. 10 0.050 Festuca ovina aggr. 2.5 0.013 Stellaria media aggr. 2.5 0.001 Festuca rubra s.l. 47.5 0.193 Stipa eriocaulis 2.5 0.013 Festuca sp. 2.5 0.001 Taraxacum officinale aggr. 92.5 0.406 Festuca valesiaca s.l. 2.5 0.001 Telephium imperati 10 0.016 Filago arvensis 2.5 0.001 Teucrium chamaedrys 57.5 0.276 Fragaria vesca 25 0.114 Teucrium montanum 12.5 0.114 Fraxinus excelsior 2.5 0.001 Thesium alpinum 12.5 0.051 Galeopsis angustifolia 5 0.025 Thymus serpyllum aggr. 17.5 0.054 Galeopsis ladanum 25 0.125 Torilis arvensis 2.5 0.013 Galeopsis tetrahit 27.5 0.138 Tragopogon dubius 22.5 0.045 Galium album 2.5 0.013 Trifolium alpestre 2.5 0.013 Galium anisophyllon 7.5 0.026 Trifolium badium 5 0.003 Galium aparine 5 0.025 Trifolium hybridum 2.5 0.001 Galium lucidum 27.5 0.126 Trifolium medium 7.5 0.038 Galium verum s.l. 22.5 0.090 Trifolium pratense s.l. 22.5 0.101 Gentiana campestris 2.5 0.013 Trifolium repens 12.5 0.051 Geranium pyrenaicum 7.5 0.038 Triticum dicoccon 2.5 0.013 Geranium rivulare 2.5 0.001 Tussilago farfara 40 0.195 Geranium robertianum s.l. 2.5 0.001 Urtica dioica 15 0.053 Geranium sylvaticum 12.5 0.051 Vaccinium myrtillus 12.5 0.029 Geum urbanum 2.5 0.013 Vaccinium vitis-idaea 10 0.050 Globularia cordifolia 2.5 0.001 Valeriana tripteris 7.5 0.038 Globularia punctata 2.5 0.013 Verbascum lychnitis 22.5 0.101 Gymnadenia conopsea 2.5 0.001 Verbascum sp. 37.5 0.109 Helianthemum nummularium s.l. 50 0.290 Verbascum thapsus s.l. 40 0.376 Hepatica nobilis 12.5 0.051 Veronica chamaedrys 7.5 0.038 Heracleum sphondylium s.l. 2.5 0.001 Veronica fruticulosa 5 0.014 Hieracium glaucum 2.5 0.001 Veronica officinalis 30 0.156 Hieracium lactucella 2.5 0.001 Viburnum lantana 2.5 0.013 Hieracium murorum Grp. 47.5 0.159 Viola collina 10 0.050 Hieracium pilosella 5 0.025 Viola reichenbachiana 10 0.050 Hieracium prenanthoides 5 0.025 Viola rupestris 40 0.166

A-17

Table A 11 List of species and recorded in the herb layer on 5a by TEMPERLI (2007) in 2007. Additionally the percentages of number of plots a species has been present and the mean cover it has recorded with is listed.

Species name Presence [%] Mean cover [%] Species name Presence [%] Mean cover [%] Abies alba 2.5 0.001 Inula conyza 5 0.025 Acer pseudoplatanus 17.5 0.020 Isatis tinctoria 70 0.730 Achillea millefolium aggr. 40 0.178 Juglans regia 2.5 0.001 Achnatherum calamagrostis 45 0.650 Kernera saxatilis 2.5 0.013 Acinos alpinus 25 0.250 Knautia sp. 60 0.278 Acinos arvensis 30 0.213 Lactuca perennis 67.5 0.304 Aconitum vulparia aggr. 2.5 0.013 Lactuca serriola 80 0.389 Agrostis capillaris 20 0.214 Lactuca virosa 2.5 0.001 Agrostis gigantea 2.5 0.013 Lappula deflexa 20 0.066 Ajuga genevensis 7.5 0.038 Lappula sp. 7.5 0.038 Ajuga pyramidalis 2.5 0.013 Lappula squarrosa 10 0.039 Alchemilla xanthochlora aggr. 5 0.025 Larix decidua 15 0.041 Alyssum alyssoides 30 0.150 Laserpitium gaudinii 7.5 0.038 Amaranthus retroflexus 2.5 0.013 Laserpitium latifolium 32.5 0.151 Amelanchier ovalis 2.5 0.001 Laserpitium siler 40 0.603 Anthericum liliago 5 0.025 Lathyrus heterophyllus 2.5 0.013 Anthoxanthum odoratum aggr. 2.5 0.001 Lathyrus pratensis 25 0.313 Anthyllis vulneraria s.l. 17.5 0.076 Lathyrus sylvestris 2.5 0.013 Aquilegia atrata 7.5 0.038 Leontodon hispidus s.l. 7.5 0.026 Arabis collina 2.5 0.013 Leucanthemum vulgare aggr. 32.5 0.163 Arabis hirsuta aggr. 15 0.064 Linum catharticum 5 0.025 Arabis nova 2.5 0.013 Lolium perenne 2.5 0.001 Arctostaphylos uva-ursi 72.5 0.340 Lonicera nigra 2.5 0.001 Arenaria serpyllifolia aggr. 80 0.588 Lotus corniculatus aggr. 72.5 0.613 Artemisia absinthium 17.5 0.031 Luzula nivea 2.5 0.001 Artemisia vulgaris 7.5 0.951 Maianthemum bifolium 2.5 0.013 Asplenium ruta-muraria 12.5 0.040 Medicago lupulina 40 0.251 Astragalus glycyphyllos 5 0.003 Medicago minima 2.5 0.001 Astragalus monspessulanus 30 0.150 Medicago sativa 2.5 0.013 Atropa belladonna 7.5 0.026 Melampyrum sylvaticum 12.5 0.063 Berberis vulgaris 42.5 0.190 Melica ciliata 37.5 0.250 Betula pendula 75 0.319 Melica nutans 5 0.014 Biscutella laevigata 5 0.025 Minuartia rubra 12.5 0.051 Blitum virgatum 92.5 0.793 Molinia arundinacea 5 0.025 Brachypodium pinnatum aggr. 32.5 1.075 Mycelis muralis 20 0.078 Bromus erectus s.l. 17.5 0.553 Myosotis alpestris 2.5 0.013 Bromus hordeaceus 2.5 0.013 Myosotis sylvatica 10 0.039 Bromus sterilis 2.5 0.013 Ononis natrix 5 0.025 Calamagrostis epigejos 12.5 0.063 Ononis pusilla 12.5 0.063 Calamagrostis varia 77.5 3.075 Ononis repens 2.5 0.013 Calamagrostis villosa 12.5 0.188 Ononis rotundifolia 17.5 0.428 Campanula barbata 7.5 0.038 Ononis spinosa s.l. 5 0.025 Campanula cochleariifolia 2.5 0.013 Orobanche minor 2.5 0.001 Campanula rapunculoides 10 0.039 Orobanche teucrii 2.5 0.001 Campanula rotundifolia 95 0.663 Papaver dubium s.l. 7.5 0.004 Campanula scheuchzeri 2.5 0.013 Petrorhagia prolifera 2.5 0.013 Capsella bursa-pastoris 5 0.025 Peucedanum cervaria 12.5 0.018 Carduus defloratus s.l. 20 0.089 Peucedanum oreoselinum 27.5 0.138 Carduus sp. 2.5 0.075 Peucedanum ostruthium 2.5 0.013 Carex alba 2.5 0.013 Phleum phleoides 2.5 0.001 Carex flacca 5 0.025 Phleum pratense aggr. 25 0.165 Carex halleriana 2.5 0.001 Phyteuma betonicifolium 7.5 0.038 Carex humilis 60 0.300 Phyteuma orbiculare 5 0.014 Carex liparocarpos 5 0.025 Picea abies 32.5 0.106 Carex ornithopoda 15 0.075 Pimpinella saxifraga aggr. 2.5 0.013 Carex sp. 15 0.053 Plantago atrata 5 0.014 Carlina acaulis 17.5 0.065 Plantago lanceolata 2.5 0.001 Centaurea scabiosa s.l. 17.5 0.139 Plantago major s.l. 2.5 0.001 Cephalanthera longifolia 5 0.014 Poa annua 2.5 0.013 Cephalanthera rubra 2.5 0.001 Poa chaixii 27.5 0.070 Cerastium arvense s.l. 5 0.025 Poa compressa 40 0.200 Cerastium fontanum s.l. 5 0.003 Poa nemoralis 5 0.014 Chaenorrhinum minus 25 0.091 Poa pratensis aggr. 15 0.138 Chaerophyllum hirsutum aggr. 7.5 0.038 Polygala alpestris 2.5 0.001 Chenopodium album 72.5 0.318 Polygala chamaebuxus 42.5 0.201 Chenopodium bonus-henricus 5 0.014 Polygonatum odoratum 7.5 0.026 Cirsium acaule 5 0.025 Polygonum aviculare aggr. 2.5 0.013 Cirsium arvense 92.5 0.690 Populus alba 30 0.060 Cirsium vulgare 85 0.816 Populus nigra s.l. 2.5 0.013 Clematis vitalba 15 0.041 Populus tremula 85 0.693 Clinopodium vulgare 5 0.025 Potentilla grandiflora 5 0.025 Colutea arborescens 5 0.014 Potentilla neumanniana 10 0.050 Conyza canadensis 82.5 4.375 Prunella grandiflora 15 0.075 Cornus sp. 2.5 0.001 Prunus avium 7.5 0.004 Coronilla minima 5 0.014 Pulmonaria australis 12.5 0.063 Corylus avellana 2.5 0.001 Pulsatilla alpina s.l. 12.5 0.051 Cotoneaster integerrima 12.5 0.063 Quercus sp. 27.5 0.081 Cotoneaster tomentosa 7.5 0.004 Ranunculus nemorosus aggr. 10 0.050 A-18

Crepis capillaris 2.5 0.013 Reseda lutea 27.5 0.115 Crepis pulchra 12.5 0.051 Rosa sp. 32.5 0.118 Cuscuta epithymum 5 0.014 Rubus caesius 37.5 2.950 Cystopteris fragilis 7.5 0.026 Rubus idaeus 80 3.863 Dactylis glomerata 20 0.203 Rubus saxatilis 12.5 0.850 Daucus carota 47.5 0.215 Rumex acetosella aggr. 2.5 0.001 Descurainia sophia 2.5 0.013 Rumex alpestris 2.5 0.001 Dianthus sylvestris 2.5 0.013 Salix appendiculata/caprea 72.5 0.755 Digitalis lutea 2.5 0.013 Sambucus nigra 10 0.028 Echium vulgare 15 0.064 Sambucus racemosa 12.5 0.018 Epilobium angustifolium 97.5 13.601 Sanguisorba minor s.l. 50 0.216 Epilobium dodonaei 5 0.025 Saponaria ocymoides 92.5 10.425 Epilobium hirsutum 40 0.144 Saxifraga paniculata 2.5 0.001 Epilobium montanum/collinum Grp. 32.5 0.129 Scorzonera laciniata 2.5 0.001 Epipactis atrorubens 45 0.203 Securigera varia 32.5 0.538 Epipactis helleborine aggr. 10 0.050 Sedum album 25 0.114 Epipactis sp. 2.5 0.013 Sedum dasyphyllum 7.5 0.026 Erigeron acer s.l. 47.5 0.233 Senecio doronicum 7.5 0.026 Erigeron annuus s.l. 10 0.039 Senecio viscosus 40 0.189 Erucastrum nasturtiifolium 2.5 0.001 Senecio vulgaris 47.5 0.204 Erysimum rhaeticum 5 0.025 Silene nutans s.l. 55 0.326 Euphorbia cyparissias 77.5 0.864 Silene vulgaris s.l. 17.5 0.088 Euphorbia seguieriana 2.5 0.013 Solanum dulcamara 65 0.291 Euphrasia stricta 2.5 0.013 Solidago canadensis 2.5 0.013 Fallopia convolvulus 2.5 0.013 Solidago virgaurea s.l. 45 0.203 Festuca arundinacea s.l. 5 0.014 Sonchus asper 65 0.213 Festuca heterophylla 15 0.075 Sonchus oleraceus 20 0.021 Festuca ovina aggr. 12.5 0.040 Sonchus sp. 2.5 0.013 Festuca rubra s.l. 62.5 0.693 Sorbus aria 17.5 0.020 Festuca sp. 2.5 0.013 Stachys recta s.l. 15 0.064 Filago arvensis 2.5 0.001 Stipa eriocaulis 2.5 0.013 Fourraea alpina 2.5 0.001 Taraxacum officinale aggr. 92.5 0.451 Fragaria vesca 40 0.303 Telephium imperati 10 0.039 Fumana procumbens 5 0.014 Teucrium chamaedrys 52.5 0.263 Galeopsis angustifolia 7.5 0.038 Teucrium montanum 12.5 0.063 Galeopsis ladanum 22.5 0.175 Thesium alpinum 10 0.050 Galeopsis tetrahit 22.5 0.113 Thymus serpyllum aggr. 20 0.163 Galium album 17.5 0.088 Torilis arvensis 10 0.039 Galium anisophyllon 20 0.089 Tragopogon dubius 60 0.266 Galium aparine 22.5 0.079 Trifolium alpestre 2.5 0.013 Galium lucidum 40 0.251 Trifolium badium 7.5 0.038 Galium verum s.l. 25 0.125 Trifolium medium 5 0.025 Gentiana campestris 2.5 0.013 Trifolium pratense s.l. 30 0.389 Geranium pyrenaicum 10 0.050 Trifolium repens 12.5 0.063 Geranium rivulare 2.5 0.013 Turritis glabra 5 0.025 Geranium sylvaticum 10 0.050 Tussilago farfara 40 0.200 Globularia cordifolia 2.5 0.013 Urtica dioica 12.5 0.063 Globularia punctata 2.5 0.013 Vaccinium myrtillus 10 0.039 Gymnadenia conopsea 5 0.014 Vaccinium vitis-idaea 10 0.039 Helianthemum nummularium s.l. 60 0.613 Valeriana tripteris 2.5 0.013 Hepatica nobilis 2.5 0.013 Veratrum album s.l. 2.5 0.001 Heracleum sphondylium s.l. 5 0.003 Verbascum lychnitis 20 0.089 Herniaria glabra 2.5 0.013 Verbascum sp. 20 0.066 Hieracium murorum Grp. 45 0.203 Verbascum thapsus s.l. 40 0.178 Hieracium pilosella 12.5 0.029 Veronica chamaedrys 7.5 0.038 Hieracium prenanthoides 2.5 0.013 Veronica fruticulosa 7.5 0.026 Hieracium sabaudum 2.5 0.013 Veronica officinalis 27.5 0.166 Hieracium staticifolium 2.5 0.013 Veronica spicata 2.5 0.013 Hippocrepis comosa 70 0.464 Viburnum lantana 5 0.014 Hippocrepis emerus 30 0.139 Viola collina 10 0.039 Hypericum maculatum s.l. 2.5 0.013 Viola reichenbachiana 12.5 0.063 Hypericum perforatum 7.5 0.038 Viola rupestris 42.5 0.201

A-19

A 6 Tree regeneration

Table A 12: Presence of tree species in 1996, 2005 and 2007. Indicated are the number of plots a tree species has been recorded in the tree layer (TL), the shrub layer (SL) and the herb layer (HL), respectively. The total number of plots is 40.

1996 2005 2007

Species TL SL HL TL SL HL TL SL HL Abies alba 8 19 17 0 0 2 0 0 1 Acer campestre 0 0 1 0 0 0 0 22 0 Acer pseudoplatanus 0 0 6 0 0 5 0 0 7 Betula pendula 0 4 3 0 0 8 0 0 30 Fraxinus excelsior 0 1 4 0 0 1 0 0 0 Juglans regia 0 0 0 0 0 0 0 0 1 Larix decidua 18 17 16 0 0 5 0 0 6 Picea abies 37 34 33 0 0 10 0 1 13 Pinus sylvestris 28 25 27 0 0 0 0 0 0 Populus alba 0 0 0 0 0 8 0 8 12 Populus nigra s.l. 0 0 0 0 0 0 0 1 1 Populus tremula 0 1 2 0 0 33 0 32 34 Prunus mahaleb 0 2 0 0 0 0 0 0 0 Prunus avium 0 0 4 0 0 0 0 0 3 Quercus sp. 3 8 24 1 1 9 1 4 11 Salix appendiculata/caprea 1 2 6 0 0 26 0 30 29 Salix purpurea s.l. 0 1 1 0 0 0 0 0 0 Sorbus aria 0 15 0 0 1 0 0 4 0 Sorbus aucuparia 0 1 0 0 0 0 0 0 0 Sorbus mougeotii 0 1 0 0 0 0 0 0 0

A-20

A 7 Climate model graphs and R-outputs

Table A 13: R-output of linear regression model used for the prediction of air temperatures at the plot locations. “air_temp” refers to the mean temperature of the vegetation period 1. 6 - 30.9 2005. 10 12 14 16 18 10 12 14 16 18 10 12 14 16 18

Measured airtemperature [°C] 1000 1400 1800 2200 Measured airtemperature [°C] 100 150 200 250 Measured airtemperature [°C] 10 20 30 40

Elevation [m.a.s.l.] Aspect [°] Slope [°] 10 12 14 16 18 10 12 14 16 18 10 12 14 16 18

Predictedair temperature [°C] 1000 1400 1800 2200 Predictedair temperature [°C] 100 150 200 250 Predictedair temperature [°C] 10 20 30 40 Elevation [m.a.s.l.] Aspect [°] Slope [°]

Figure A 2: Measured (top) and predicted (bottom) air temperature [°C] vs. elevation, aspect and slope.

Table A 14: R-output of linear regression model used for the prediction of ground temperatures at the plot locations. “ground_temp” refers to the mean temperature of the vegetation period 1. 6 - 30.9 2005. 12 16 20 12 16 20 12 16 20

1000 1400 1800 2200 100 150 200 250 10 20 30 40 Measured groundtemperature [°C] Measured groundtemperature [°C] PMeasuredground temperature [°C] Elevation [m.a.s.l.] Aspect [°] Slope [°] 12 16 20 12 16 20 12 16 20

1000 1400 1800 2200 100 150 200 250 10 20 30 40 Predicted ground temperature[°C] Predicted ground temperature[°C] Predicted ground temperature[°C] Elevation [m.a.s.l.] Aspect [°] Slope [°]

Figure A 3: Measured (top) and predicted (bottom) ground temperature [°C] vs. elevation, aspect and slope.

A-21

Table A 15: R-output of linear regression model used for the prediction of soil temperatures at the plot locations. “soil_temp” refers to the mean temperature of the vegetation period 1. 6 - 30.9 2005. 10 14 18 22 10 14 18 22 10 14 18 22

Measured soil temperature [°C] 1000 1400 1800 2200 100 150 200 250 Measured soil temperature [°C] 10 20 30 40 PMeasured soil temperature[°C]

Elevation [m.a.s.l.] Aspect [°] Slope [°] 10 14 18 22 10 14 18 22 10 14 18 22

Predictedsoiltemperature [°C] 1000 1400 1800 2200 Predictedsoiltemperature [°C] 100 150 200 250 Predictedsoiltemperature [°C] 10 20 30 40 Elevation [m.a.s.l.] Aspect [°] Slope [°]

Figure A 4: Measured (top) and predicted (bottom) soil temperature [°C] vs. elevation, aspect and slope.

Table A 16: R-output of linear regression model used for the prediction of the number of hourly measures above 40°C (“heat_hours”) at the plot locations. 0 50 150 250 0 50 150 250 0 50 150 250

1000 1400 1800 2200 100 150 200 250 10 20 30 40 Measured numberof heathours Measured numberof heathours Measured numberof heathours

Elevation [m.a.s.l.] Aspect [°] Slope [°] 0 50 150 250 0 50 150 250 0 50 150 250

Predicted numberof heat hours 1000 1400 1800 2200 Predicted numberof heat hours 100 150 200 250 Predicted numberof heat hours 10 20 30 40 Elevation [m.a.s.l.] Aspect [°] Slope [°]

Figure A 5: Measured (top) and predicted (bottom) number of heat hours (number of hourly temperatures above 40°C) vs. elevation, aspect and slope.

Table A 17: R-output of linear regression model used for the prediction of the precipitation at the plot locations. “prec” refers to the precipitation sum in the vegetation period 1. 6 - 30.9 2005. 260 300 340 380 260 300 340 380 260 300 340 380

Measured precipitation[mm] 1000 1400 1800 2200 Measured precipitation[mm] 100 150 200 250 Measured precipitation[mm] 10 20 30 40

Elevation [m.a.s.l.] Aspect [°] Slope [°] 260 300 340 380 260 300 340 380 260 300 340 380

Predicted precipitation[mm] 1000 1400 1800 2200 Predicted precipitation[mm] 100 150 200 250 Predicted precipitation[mm] 10 20 30 40 Elevation [m.a.s.l.] Aspect [°] Slope [°]

Figure A 6: Measured (top) and predicted (bottom) precipitation [mm] vs. elevation, aspect and slope.

A-22

Table A 18: R-output of linear regression model used for the prediction of the water balance quotient at the plot locations. “p.pe” refers to the precipitation sum divided by the potential evapotranspiration in the

Measured P/PE vegetation period 1. 6 - 30.9 2005. 0.6 0.8 1.0 1.2 1.4 0.6 0.8 1.0 1.2 1.4 0.6 0.8 1.0 1.2 1.4

1000 1400 1800 2200 Measuredprecipitation [mm] 100 150 200 250 Measuredprecipitation [mm] 10 20 30 40

Elevation [m.a.s.l.] Aspect [°] Slope [°] PredictedP/PE PredictedP/PE PredictedP/PE 0.6 0.8 1.0 1.2 1.4 0.6 0.8 1.0 1.2 1.4 0.6 0.8 1.0 1.2 1.4

1000 1400 1800 2200 100 150 200 250 10 20 30 40 Elevation [m.a.s.l.] Aspect [°] Slope [°]

Figure A 7: Measured (top) and predicted (bottom) water balance quotient (precipitation/potential evapotranspiration after THORNTHWAITE and MATTERS , 1957) P/PE) vs. elevation, aspect and slope.

A-23