Download Field mapping documentation - Leibniz

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Transcript
HABIT-CHANGE
Field mapping documentation
Output 4.2.2
02/2013
This project is implemented through
the CENTRAL EUROPE Programme
co-financed by the ERDF
Output Number:
4.2.2
Title:
Field mapping documentation
Author:
TUB (Tobias Schmidt, Michael Förster), EURAC (Barbara Stoinschek,
Anastasia Polychronaki, Kathrin Renner), UniB (Anca Sârbu), BUNP (Judit
Cservenka)
Project:
HABIT-CHANGE – Adaptive management of climate-induced changes of
habitat diversity in protected areas
CENTRAL EUROPE
2CE168P3
Project
Programme:
Date:
08/2012
Number:
Start date:
3/2010
Lead Partner:
Leibniz Institute of Ecological and Regional Development (IOER),
Germany
 University of Vienna, Austria
 National Academy of Sciences, Scientific Centre for Aerospace
Research of the Earth, Ukraine
 Thuringian State Institute for Forestry, Game and Fishery, Germany
 Potsdam Institute for Climate Impact Research, Germany
 Technische Universität Berlin, Germany
 Balaton Uplands National Park Directorate, Hungary
 Szent Istvan University, Hungary
 Biebrza National Park, Poland
 Environmental Protection Institute, Poland
 Triglav National Park, Slovenia
 University of Bucharest, Romania
 Central Institute for Meteorology and Geodynamics, Austria
 Danube Delta National Institute for Research and Development,
Romania
 SOLINE Pridelava soli d.o.o., Slovenia
 University of Maribor, Slovenia
 European Academy Bolzano, Italy
Marco Neubert, [email protected], +49 351 4679-274
Sven Rannow, [email protected], +49 351 463-42359
www.habit-change.eu
Project Partner:
Contact:
Further
information
[2]
End date:
2/2013
Contents
1.
Introduction and background
5
2.
The test-site Hainich National Park
5
2.1.
7
3.
4.
2.1.1. Sampling Design
8
2.1.2. Leaf Area Index Measurement
9
2.1.3. Leaf Area Index Calculation
10
2.2.
12
Results
The test-site Bucegi Natural Park
13
3.1.
Data and Methods
13
3.2.
Results
14
The test-site Balaton Upland National Park
4.1.
5.
Data and Methods
Results
The test-site Rieserferner Ahrn
18
19
25
5.1.
Ahrntal
27
5.2.
Gais
28
5.3.
Percha
29
5.4.
Prettau
30
5.5.
Rasen-Antholz
31
5.6.
Sand in Taufers
32
5.7.
Data and Methods
32
5.7.1. Data
33
5.7.2. Methods
33
5.7.3. Description of Habitat-types
34
5.7.4. Ecoregions
35
5.7.5. Structural level
35
5.7.6. Culture type
36
5.7.7. Sprawl
37
5.7.8. Landscape regions
37
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[3]
5.8.
Results field mapping 2010
38
5.8.1. Overview of the existing landscape regions in the Nature Park Rieserferner Ahrn
38
5.8.2. Development of cultural types from 1865 to 2006
42
5.8.3. Development of Habitat-types from 1856 to 2006
44
5.8.4. Mapping of wetlands
44
5.9.
47
Field mapping 2011
5.9.1. Methodology
47
5.9.2. Locations of field mapping
48
5.10. Results from field mapping 2011
69
6.
Conclusions
72
7.
References
73
[4]
1. Introduction and background
Within the framework of WP4 in action 4.2.2, documentation of field mapping of different types and
methods in selected test-sites of the Habit-Change Network is required. This report delivers detailed
descriptions of mapping results and photo documentation. Furthermore, applied methods for
identifying or measuring vegetation were described for some exemplary test-sites.
2. The test-site Hainich National Park
The Hainich is a deciduous wooded ridge area (300 – 500m above sea-level) with an area of about
16,000 ha, and is situated in the Free State of Thuringia in central Germany between the towns
Eisenach, Mühlhausen and Bad Langensalza. The National Park Hainich is situated in the southern
part and covers about 7,500 ha (see Figure 1). With 5,000 ha of unmanaged deciduous woods, this
area is the largest coherent deciduous wood in Germany (Nationalpark Hainich, 2008). Because of
this unique feature a part of the NP was acknowledged by UNESCO in 2011. Beech dominated forest
(see Figure 2) covers about 60% of the overall area (about 3,000 ha) and Oak dominated forests
about 6% (see Figure 3).
Figure 1: Test-site National Park Hainich
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[5]
Figure 2: Asperulo-Fagetum beech forests in NP Hainich
Figure 3: Spatial distribution of the main forest species (Nationalpark Hainich, 2008)
The National Park is also part of the Natura 2000 network of the European Union. The habitat types
in the area are listed in Table 1. The annual average precipitation in the Hainich is 600 - 800 mm,
depending on the terrain height. The annual average temperature varies from 7 to 8°C. There is a
transitional area between the western Atlantic climate zone and the continental eastern European
climate zone. The vegetation reflects this significant west - east zoning.
[6]
Table 1: List of Natura 2000-Habitats in the National Park Hainich (Nationalpark Hainich, 2008
modified)
Habitat
code
9130
9150
9160
9170
9180*
91E0*
91D0*
NATURA 2000 habitats
Area in ha
Asperulo-Fagetum beech forests
2,462
Cover % of
all habitats
72.6
Medio-European limestone beech forests of the
Cephalanthero-Fagion
Sub-Atlantic and medio-European oak or oakhornbeam
forests of the Carpinion betuli
Galio-Carpinetum oak-hornbeam forests
Tilio-Acerion forests of slopes, screes and ravines
Alluvial forests with Alnus glutinosa and Fraxinus
excelsior (Alno-Padion, Alnion incanae, Salicion albae)
Bog woodland
521
15.4
40
1.2
277
41
50
8.2
1.2
1.4
<1
<0.1
2.1. Data and Methods
The aim of the field campaign within the NP Hainich was to measure the Leaf Area Index (LAI) of
deciduous tree types using hemispherical photos and LI-COR LAI-2200 Plant Canopy Analyzer
measurements. In the proposed method both types of derived LAI information should be linked with
remote sensing derived vegetation indices of the RapidEye satellite system (e.g. Normalized
Difference Vegetation Index) in order to quantify the LAI throughout the entire vegetation cycle, so
that changes in vegetation phenology and the conservation status of the habitats can be detected.
The LAI is a key parameter for plants which relates directly to leaf biomass and the photosynthetic
activity of plants. The RapidEye data and the Field data were collected more or less simultaneous to
facilitate the assignment (see Table 2).
Table 2: List of RapidEye data for Hainich National Park
Acquisition
date
Sensor
Resolution
Quality
02.04.2011
23.04.2011
01.05.2011
02.06.2011
28.06.2011
RE4
RE1
RE4
RE3
RE5
5m
5m
5m
5m
5m
small clouds
no clouds
no clouds
no clouds
small clouds
02.09.2011
21.09.2011
09.10.2011
RE4
RE4
RE3
5m
5m
5m
no clouds
small clouds
clouds
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
Usage
Field Trip (LAI data)
yes
yes
yes
04.05 - 06.05.2011
08.06 - 10.06.2011
30.06 - 02.07.2011
21.07 - 23.07.2011
yes
no
22.09 - 24.09.2011
17.10 - 19.10.2011
[7]
2.1.1.Sampling Design
The sampling design for the LAI measurements is based on the forest inventory
(Stichprobeninventur) of the NP. The inventory data contains information about tree species, height
and age in a 200 * 200 meter raster. To ensure the transferability of the LAI to the remote sensing
vegetation indices, a visual interpretation of the RapidEye images was essential to determine areas
with a high amount of beech,a homogenous age structure and low anthropogenic influence. This was
an important step due to the coarse scale of the RapidEye data in relation to the fine scale of the
field measurements. Additionally, low topographic relief was necessary to minimize uncertainties
caused by the occurrence of shadowed areas within the remote sensing data. The field
measurements dates followed the annual cycle of the phenology of beech. A stratified random
design was used to determine sampling unit locations.. In total, four sampling units with a
homogenous beech stock were selected. Each sampling unit contains twelve measuring points (4
columns and 3 rows) 200 meters apart (see Figure 4). To acquire data from different perspectives,
each measuring point was subdivided into 5 sub-measuring points. Around the central point four
additional points were placed in cardinal directions, with a distance of 5 meters (see Figure 5).
Figure 4: Sampling design and localization
[8]
Figure 5: Sampling design of the measuring points
2.1.2.Leaf Area Index Measurement
For this study the LAI was measured with two indirect methods:


LI-COR LAI-2200 Plant Canopy Analyzer
Hemispherical photos
The LI-COR LAI-2200 Plant Canopy Analyzer (see Figure 6) calculates the LAI from light measurements
made with a “fish-eye” optical sensor. Measurements above and below the canopy were used to
calculate the canopy light interception at five zenith angles (see Figure 7).
Figure 6: LI-COR LAI 2200
Figure 7: View Caps
For the reference measurements above the canopy one LI-COR LAI-2200 Plant Canopy Analyzer was
positioned close to an open field (see Figure 8). During the measurement a 180° view cap was used.
The view cap constricted the azimuthal field of view of the optical sensor in order to mask out
undesirable parts of the view. On every sub-measuring point three measurements were made over
15 second intervals to avoid uncertainty. The LAI were finally computed using a radiative transfer
model for vegetative canopies.
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[9]
Figure 8: LAI measurement (left) above canopy and (right) below canopy
The hemispherical photos were made with a Canon EOS 5D Mark II camera with a fish-eye optical
objective. The camera was positioned 1.50 meters above the ground so that no view cap would be
necessary. All photos were taken in the RAW format and with three exposures (see Figure 9).
Figure 9: Hemispherical photos with three different exposures
2.1.3.Leaf Area Index Calculation
The LAI calculations from the LI-COR measurements were done with the software FV 2200. In this
process the above and below canopy measurements were combined and the mean LAI, and the
standard deviations from the three measurements for each sub-measuring point were generated
(see Figure 10).
[10]
Figure 10: Mean LAI values for exemplary measuring points and the related standard deviation
In order to calculate the LAI from the hemispherical photos, two image processing steps were
necessary. In the first step each photo was converted into a binary image to differentiate biomass
and hemisphere (see Figure 11) using an Isodata classification algorithm.
Figure 11: Binary image where red areas are hemisphere and black are biomass
Based on these binary images the LAI were calculated in the second step. For the calculation the
image values from the three exposures were averaged and than weighted into zenith-rings with
different degrees around the central point (see Figure 12). This step was done using an ILD-script.
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[11]
Figure 12: Zenith-rings around the central point for weighting the LAI
2.2. Results
A overall of 4,320 photos were taken for the 48 field plots and the 6 field trip dates (15 images per
date and plot), mentioned in Table 2. First results show on average a clear increase of the LAI
between May and June, followed by a long stable period of LAI values between 5.0 and 6.0. In
September a slight decrease of the LAI can be observed, followed by a rather strong decline in
October. The results can be supported by the LI-COR measurements.
[12]
3. The test-site Bucegi Natural Park
The NP Bucegi is located in the easternmost part of the Carpathian Mountains in the Alpine
biogeographical region (see Figure 13). The NP covers approx. 284 km² and includes 14 strictly
protected sites. This mountainous region host a diversity of habitats from alpine and subalpine
grassland to tall forb habitats, scrub, rock and scree habitats, chasmophyte vegetation on calcareous
rocks, peat bogs, deciduous forests, coniferous forests and mixed deciduous and coniferous forests,
rivers and lakes or communities of hydrophytes along the waterway.
Figure 13: Test-site Natural Park Bucegi
3.1. Data and Methods
The field campaign (duration of 35 days) was done in 2010 (17 days) and 2012 (18 days), during the
optimal vegetation period (May, June, July). Two terrestrial sites were considered for field activity in
Bucegi Natural Park: one location at the plateau level (about 2,506 ha) and the other located along
the Lalomiţa river (about 2,646 ha). In these areas 11 habitat types were identified. A number of 421
plots belonging to the 11 identified Natura 2000 Habitat types were located in the field using GPS
and documented by photos. For 61 of the habitat types an updated characterization from floristic,
phytosociological and conservation (Natura 2000 nomenclature) points of view was also done. A
special field sheet was used (see Figure 14).
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[13]
Figure 14: Location of the study areas in the Natural Park Bucegi
3.2. Results
The photos obtained during the field work were used to support the characteristics of the 11 habitat
types identified in the BNP: 4060 – Alpine and boreal heaths, 4070* – Bushes with Pinus mugo and
Rhododendron myrtifolium, 6150 – Siliceous alpine and boreal grasslands, 6170 – Alpine and
subalpine calcareous grasslands, 6230* – Species-rich Nardus grasslands, on siliceous substrates in
mountain areas (and sub-mountain areas, in Continental Europe), 8120 – Calcareous and calcashist
screes of the montane to alpine levels (Thlaspietea rotundifolii), 8210 – Calcareous rocky slopes with
chasmophytic vegetation, 9110 – Luzulo-Fagetum beech forest, 91V0 – Dacian beech forest, 9410 –
[14]
Acidophilus Picea forests of the montane to alpine levels (Vaccinio-Piceetaea), 6430 – Hydrophilous
tall herb fringe communities of plains and of the montane to alpine levels.
Furthermore the photos were used to support the development of the output 3.1.9. (Map with
actual habitat types from Bucegi Natural Park), and contributed to the development of monitoring
indicators for alpine areas (outputs 4.2.3., 4.2.4., 4.2.5.). For the development of the map of actual
habitat types from BNP, we worked together with project partners from the University of Vienna.
They used multi-temporal RapidEye imagery to assess the habitats in Bucegi Natural Park (BNP). To
support the inter-calibration process which is required in the use of remote sensing, we generated
sample points and terrain photos to support the differentiation of different Land Cover classes,
alpine grassland types (habitat code: 6230 and 6150) and forest habitat types (habitat code: 9110,
91V0, 9410).
The assessment of these habitat types included the following aspects (see Table 3).

species composition

dominant and characteristic species

plant with conservation value

vegetation type

natural and human threats
Table 3: Fieldwork sheet - Example
Habitat type: 9410 Acidophilous Picea forests of the montane to alpine levels (Vaccinio-Piceetaea)
Date: 26.05.2010, 28.06.2010
Location: Left bank of Bolboci Lake
Geographical Coordinates: N 45°20'.409 E 25°26'.229
Attributes
Recorded values/parameters
Altitudes: 1481/1498 m
Comments
Quantity

Investigated area
(approximate)
Species composition
cca. 17 ha

120 taxa

Species richness (attached
list)
Characteristic and
dominant species
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
Picea abies, Vaccinum myrtillus,
Lycopodium selago, Lycopodium
annotinum, Deschampsia flexuosa,
[15]
Oxalis acetosella, Sorbus aucuparia,
Hylocomium splendens, Pleurozium
schreberi, Sphagnum girgensohnii

Rare species
Dactylorhiza fuchsia, Dactylorhiza
maculata, Dactylorhiza incarnata,
Listera ovata, Gymnadenia
conopsea, Ranunculus carpaticus,
Lycopodium annotinum,
Lycopodium selago, Pulmonaria
rubra

Negative impact species
(allochthonous)
Urtica dioica, Glechoma hirsuta,
Rubus idaeus, Veratrum album,
Sisyrinchium montanum
Less than 1% coverage
Vegetation structure

Tree cover
65%

Tree layers
Mosses layer, herbaceous layer,
shrubs layer and trees layer

Age structure of trees
Predominantly mature trees on the
forest edge and in inside appear
juveniles too

Fallen trees/dead
25%

Cover of shrubs
< 1%

Other aspects of vegetation
Along the rivers' bank there is the
habitat 6430 Hydrophilous tall herb
fringe communities of plain and of
the montane to alpine levels
Other characteristics
[16]
In the shrubs layer Rubus
idaeus is present
sporadically at the edge of
the forest and in some
unforested places. Plantlets
of Sorbus aucuparia also
occur at the edge of the
forest.
On 0.01 ha there are cca. 20
dead trees, of which 10 on
feet and 10 fallen

Litter depth
10 cm

Soil surface uncovered by
vegetation
Regeneration
< 5%

Massive and on natural way (h
plantlets = 10-50 cm)
Natural diseases, pests, full
coverage of lichens (Usnea sp.,
Parmelia furfuracea, Parmelia
sulcata)
Threats
Picea abies h = cca. 20 m, tree diameter 28 cm at 1.5 m height, covered with Usnea sp.
In Table 4 plant species which were identified during the field campaign are shown.
Table 4: Species List
1
Adenostyles alliariae
41
Filipendula ulmaria
81
Pleurozium schreberi
2
Aegopodium podagraria
42
Fragaria vesca
82
Poa alpina
3
Ajuga genevensis
43
Geum rivale
83
Poa trivialis
4
Alchemilla reniformis
44
Glechoma hirsuta
84
Polygonatum verticillatum
5
Alnus incana
45
Gnaphalium sylvaticum
85
Polygonum viviparum
6
Antennaria dioica
46
Gymnadenia conopsea
86
Polytrichum formosum
7
Arabis alpina
47
Gymnocarpium dryopteris
87
Populus tremula
8
Arenaria rigida
48
Gyromitra esculenta
88
Potentilla anserina
9
Athyrium filix-femina
49
Hieracium aurantiacum
89
Potentilla erecta
10
Atrichum undulatum
50
Hieracium pilosella s.l.
90
Prunella vulgaris
11
Bruckenthalia spiculifolia
51
Homogyne alpina
91
Pulmonaria rubra
12
Calamagrostis arundinacea
52
Hylocomium splendens
92
Pyrola media
13
subsp.
53
Hypericum maculatum
93
Ranunculus acris s.l.
subsp.
54
Hypnum squarrosum
94
Ranunculus carpaticus
15
Campanula
patula
abietina
Cardamine pratensis
pratensis
Carex leporina
55
Juncus articulatus
95
Ranunculus repens
16
Carex pallescens
56
Juncus effusus
96
Rhytidiadelphus triquetrus
17
Carex rostrata
57
Juniperus communis
97
Rubus idaeus
18
Carum carvi
58
Lamium galeobdolon
98
Salix silesiaca
19
Cerastium arvense s.l.
59
Leucanthemum waldsteinii
99
Saxifraga cuneifolia
20
60
Listera cordata
100
21
Cerastium fontanum subsp.
fontanum
Chaerophyllum hirsutum
61
Listera ovata
101
Saxifraga stellaris
robusta
Senecio ovatum
22
Chrysosplenium alternifolium
62
Luzula campestris
102
Silene latifolia subsp. alba
23
Circaea lutetiana
63
Luzula sylvatica
103
Silene pusilla
24
Crocus vernus
64
Lycopodium annotinum
104
Sisyrinchium montanum
14
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
susbp.
[17]
25
Dactylis glomerata s.l.
65
Lycopodium selago
105
Soldanella hungarica
26
Dactylorhiza fuchsii
66
Mnium affine
106
Sorbus aucuparia
27
Dactylorhiza incarnata
67
Moneses uniflora
107
Sphagnum girgensohnii
28
Dactylorhiza maculata
68
Mycelis muralis
108
Taraxacum officinale
29
Deschampsia cespitosa
69
Myosotis sylvatica
109
Trifolium pratense
30
Deschampsia flexuosa
70
Nardus stricta
110
Trifolium repens
31
Dicranum montanum
71
Oxalis acetosella
111
Tussilago farfara
32
Doronicum austriacum
72
Paris quadrifolia
112
Urtica dioica
33
Dryopteris dilatata
73
Pedicularis verticillata
113
Vaccinium myrtillus
34
Epilobium montanum
74
Phleum alpinum s. str.
114
Vaccinium vitis-idaea
35
Equisetum palustre
75
Phomitopsis pinicola
115
Veratrum album
36
Equisetum ramossisimum
76
Picea abies
116
Veronica beccabunga
37
Equisetum sylvaticum
77
Pinguicula vulgaris
117
Veronica chamaedrys
38
Festua ovina s.l.
78
Plantago lanceolata
118
Veronica officinalis
39
Festuca pratensis s.l.
79
Plantago major
119
Viola biflora
40
Festuca rupicola
80
Plantago media
120
Viola declinata
All the assessed aspects were documented by photos which were included in a database. All
identified and evaluated habitat types from the test site were included with photo documentation.
The photo documentation addressed: habitat features, vegetation type, indicator species, dominant
species, species with conservation value, natural threats and anthropogenic impact. The photo
database includes 1,290 photos, the field sheets associated with all the 11 habitat types and the
ecological categories to which the plants from each habitat type belong. The photo database was
sent to the project coordinator. The most significant photos were included in the draft of a bilingual
(English/Romanian) book, which will be published in the frame of the HABIT-CHANGE project.
4. The test-site Balaton Upland National Park
The Balaton Uplands National Park (BUNP) is situated in the immediate vicinity of Lake Balaton (see
Figure 15). Within the BUNP a area of 11,282 ha constitute a strictly protected core, and 14,397 ha
have been designated a Ramsar Site. The BUNP is known for its extraordinarily diverse character
including several thousand hectares of marshlands at Kis-Balaton, the uniquely fluctuating dolomitelimestone surface of the Keszthelyi Hills and Pécselyi Basin, the dense basalt hills with their
exceptionally interesting shapes in the Tapolca Basin and the surface of the Káli Basin dotted by
volcanic craters, plateaux, stone seas and small lakes. The singularly colourful geological picture is
the fertile background to a flora and fauna of exceptional diversity. This is the region of the
Carpathian Basin where the wildlife typical of the woods and steppes of the plains meet that of the
small hill ranges that stretch to the north of Lake Balaton. The National Park, lying as it does at the
crossroads of several flora areas, is especially rich in protected plant species.
[18]
Figure 15: Test-site Balaton Uplands National Park
4.1. Results
The results of the field work in the Balaton Uplands NP are shown in Figures 16 to 20. The study sites
include a variety of different habitats according to the Habitat Directive, amongst Natural dystrophic
lakes and ponds (3160), several grassland habitats (e.g. Molinia Meadows = 6410), Bogs, Mires and
Fens (e.g. Calcareous fens with Cladium mariscus and species of the Caricion davallianae = 7210) and
alluvial forest types.
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[19]
Figure 16: Habitat Mapping of Balaton Uplands NP for test site 1
[20]
Figure 17: Phytosociological classification of Balaton Uplands NP for test site 2
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[21]
Figure 18: Natura 2000 Habitats of Balaton Uplands NP for test site 1
[22]
Figure 19: Phytosociological classification of Balaton Uplands NP for test site 2
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[23]
Figure 20: Natura 2000 Habitats of Balaton Uplands NP for test site 2
[24]
5. The test-site Rieserferner Ahrn
The Nature Park Rieserferner-Ahrn is situated in the eastern Alps, in the north-eastern part of the
Autonomous Province of Bolzano (Figure 21), Italy. It measures 313 km2 and is characterised by
alpine landscapes and forest zones. Glaciers cover around 5 % of the area and are important water
resources. The area is shaped by numerous streams, rivers, waterfalls and fens. Due to the location in
the inner Alps south of the alpine divide, the climate is moderately dry. The study site covers an
elevation range from 890m to 3,480m above mean sea level. The vegetation reflects this
mountainous character of the nature park. Spruce forests dominate, the timber line is made up of
larch and swiss pine and the following higher vegetation zone is composed of alpine meadows and
sub-alpine and alpine small shrubs and heath. Extreme habitats for plants and animals can be found
in here.
Agriculture in the study site is mostly livestock farming and characterised by the contrast of
intensification and abandonment. The nature park is managed by representatives of communities,
the department of forestry and agriculture, the farmers union and experts from conservation
organisations. The Nature Park is part of the Nature 2000 network of the European Union. For a
detailed description of the study site see HABIT-CHANGE output combined report 4.1.4 + 4.1.5.
Figure 21: Location of the Rieserferner Ahrn study site in the Alps and in Europe
The natural park consists of six municipalities. We planned the field work and ran the analysis for
each municipality separately (Figure 22).
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[25]
Figure 22: The test-site (red boundary line) and its six municipalities (green boundary line)
[26]
5.1. Ahrntal
Figure 23: The geographic extent of the municipality of Ahrntal in the north of the test-site
The municipality Ahrntal is located in the Ahrn Valley. It has 5,876 inhabitants and covers an area of
18,728 ha (ASTAT / AUTONOMOUS PROVINCE OF BOLZANO 2011), of which 3,467 hectares are part
of the natural park (OFFICE FOR NATURE PARKS OF THE AUTONOMOUS PROVINCE OF BOLZANO).
The municipality includes six villages: Luttach, Steinhaus, St. Jakob, St. Johann, St. Peter and
Weissbach. The municipality has existed in this form since 1958. The main settlement of St. Johann is
located at the coordinates 47° 1' N, 12° 3' E at an altitude of 1,054 m (ASTAT / AUTONOMOUS
PROVINCE OF BOLZANO 2011) (Figure 23). Unusually, in Ahrntal one can still find a considerable
number of managed pastures.
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[27]
5.2. Gais
Figure 24: The geographic extent of the municipality of Gais
The municipality Gais is situated in the Tauferer Valley, has 3,146 inhabitants and covers an area of
6,034 ha (ASTAT / AUTONOMOUS PROVINCE OF BOLZANO 2011), of which 2,912 hectares are part of
the park (OFFICE FOR NATURE PARKS THE AUTONOMOUS PROVINCE OF BOLZANO). The municipality
includes five villages: Gais (main settlement), Uttenheim, Mühlbach, Tesselberg and Lanebach. The
village of Gais is located at the coordinates 46° 50' N, 11° 57' E at an altitude of 841 m (ASTAT /
AUTONOMOUS PROVINCE OF BOLZANO 2011) (Figure 24). The area has been inhabited since
prehistoric times, as confirmed by prehistoric monuments such as the “Gaisinger Pipe” (955 m) and
the “Kehlburg” (1,188 m).
[28]
5.3. Percha
Figure 25: The geographic extent of the municipality of Percha
The municipality of Percha is located at the beginning of the upper Puster Valley, has 1,424
inhabitants (ASTAT / AUTONOMOUS PROVINCE OF BOLZANO 2011) and extends over an area of
3,028 ha, of which 2,048 hectares are part of the natural park (OFFICE FOR NATURE PARKS THE
AUTONOMOUS PROVINCE OF BOLZANO). The municipality comprises seven settlements, namely
Aschbach, Litschbach, Nasen, Oberwielenbach, Platten, Unterwielenbach und Wielenberg. The main
village is situated at the coordinates 46° 47' N, 12° 0' E at an altitude of 972 m (ASTAT /
AUTONOMOUS PROVINCE OF BOLZANO 2011) (Figure 25).
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[29]
5.4. Prettau
Figure 26: The geographic extent of the municipality of Prettau
The municipality of Prettau lies at the northeastern tip of the Ahrn Valley, has 596 inhabitants and
covers an area of 8,649 ha (ASTAT / AUTONOMOUS PROVINCE OF BOLZANO 2011), of which 6,293
hectares are part of the park (OFFICE FOR NATURE PARKS THE AUTONOMOUS PROVINCE OF
BOLZANO). The village Prettau is located at 47° 2' N, 12 ° 6' E at an altitude of 1,475 m (ASTAT /
AUTONOMOUS PROVINCE OF BOLZANO 2011) (Figure 26).
[30]
5.5. Rasen-Antholz
Figure 27: The geographic extent of the municipality of Rasen-Antholz
The municipality Rasen Antholz is located in the Antholzer Valley, has 2,882 inhabitants and covers
an area of 12,092 ha (ASTAT / AUTONOMOUS PROVINCE OF BOLZANO 2011), of which 4,584
hectares are part of the park (OFFICE FOR NATURE PARKS THE AUTONOMOUS PROVINCE OF
BOLZAN). The municipality includes six settlements: Neunhäusern, Niederrasen, Oberrasen, Antholz
Niedertal, Antholz Mittertal and Antholz Obertal. The municipality Rasen Antholz is located at 46° 51'
N, 12° 6' E at an altitude of 1,030 m (Figure 27). The municipality Rasen Antholz as we know it today
has existed since 1955. Popular with tourists and locals, at the far end of the Antholzer valley, is the
Antholzer lake, situated between the mountains at an altitude of 1,642 m and covering 44 hectares.
It is the third largest natural lake in South Tyrol.
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[31]
5.6. Sand in Taufers
Figure 28: The geographic extent of the municipality of Sand in Taufers
The municipality is located in the Tauferer Valley, has 5,230 inhabitants and covers an area of 16,447
ha (ASTAT / AUTONOMOUS PROVINCE OF BOLZANO 2011), of which 12,153 hectares are part of the
nature park (OFFICE FOR NATURE PARKS THE AUTONOMOUS PROVINCE OF BOLZANO). The
municipality includes five settlements, namely Campo Tures, Molini di Tures, Kematen, Ahornach and
Riva di Tures. The main village of Campo Tures is located at 46° 55' N, 11° 57' E at an altitude of
865 m (Figure 28). In the past the valley was regularly flooded;thus the valley bottom is covered with
very fertile soil. Today the torrent is regulated. In the past the only possible sites for transport and
settlements were the valley sides, for instance the area of the present castle Tures.
5.7. Data and Methods
Within the framework of WP4 action 4.2.2 EURAC we carried out comprehensive field work in the
HABIT-CHANGE test site Rieserferner Ahrn (South Tyrol, Italy). Orthophoto interpretation and field
work was carried out during the summer months of 2010 and 2011. We collected vegetation samples
for use as reference and validation reference points for the classification of satellite images. The
collected species data was also used as an input for the sensitivity and impact maps developed within
action 4.6.
This report describes in detail the test-site activities we carried out in preparation of and during the
field work . The interpretation of the aerial images for four different dates is also described in this
report as it is closely connected to the field work. We used aerial photo interpretation to derive long-
[32]
term land use changes. For land use/land cover analysis we split the test-site into its six
municipalities and examined each one separately.
In the first phase we carried out a desktop study, gathering reference data and classifying land use
based on aerial imagery. Data was available for the test-site for the years 2006, 1982-85/1989 and
1953. We performed a similar classification based on a historical map from the year 1856. After
georectifying the aerial images we drew land use polygons for each date, using on-screen digitizing.
This aerial interpretation enabled us to analyse and draw conclusions about the land use changes in
the area over the past 150 years
In phase two we went into the field during two summers to identify the various vegetation types at
the test-site, analysing the plant material in the lab and classifying it using specifically created
classes. This primary information could then be used as test and validation reference data for the
remote sensing classification of vegetation types, with the aim to establish a current habitat map and
to derive the conservation status of habitat types.
5.7.1.Data
Habitat classifications were based on aerial photographs of three different dates and one historical
map (Table 5).
Time period
Imagery
Scale
Coverage
2006
Orthophoto (colour)
1:10,000
1982-85/1989
Orthophotos (B/W)
1:25,000
Ahrntal
Antholz
Prettau
97.0%
98.8%
92.7%
1953
Orthophotos (B/W)
1:25,000
Ahrntal
Gais
Prettau
Percha
89.6%
87.0%
93.7%
91.2%
1856
Cultivated land map
1:35,000
100%
100%
Table 5: List of data used and geographic coverage per municipality
5.7.2.Methods
Long-term land use change was investigated using four different time periods: 1856, 1953, 198285/1989 and 2006.
The historical map originates from the Francisco–Josephinian Cartographical Register (third
cartographical register of the Austrian crownlands; 1:25,000) and was created from 1869 to 1887.
The maps depict the different land-use types from forest to lightly used meadows, pastures, larch
meadows, permanent crops, arable land, settlements, and specific landscape features such as rocks,
moors, and rivers. The use of such historical maps is, however, problematic since they are not
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[33]
universally available. The Francisco–Josephinian Cartographical Register is, e.g., available only for the
Habsburg Empire that covers vast areas of Central and Eastern Europe (now Austria, Czech Republic,
Slovakia, Hungary, Slovenia, Croatia, Bosnia-Herzegovina, parts of Romania, Poland, Germany, and
Italy: in total 676,000 km2). In addition, initial tests with other historical maps have shown that the
Siegfried map (1:25,000; drawn between 1870 and 1922 for Switzerland) and the French cadastral
map (‘‘Cadastre napole´onien’’, 1:25,000; drawn until 1813, France and parts of Central Europe) are
also suitable for this purpose. In addition to these, other historical maps are also available-at least in
Europe-and include the Third Cartographic Commemoration of the French Battle for Northern Italy
(1796–1797), the historical maps of Prussia (‘‘Preußische Kartenaufnahme’’ 1:25,000; drawn
between 1836 and 1850) and the Russian topographic map (1896–1917).
For the classification of the time periods 1953 and 1989 georectified aerial photographs (mean scale
between 1:15,500 and 1:25,500) were used. The basis for the 2006 habitat classification was an
orthophoto at the scale of 1:10,000.
This valuable input data enabled a description of landscape development over the past 150 years. In
a GIS the data were interpreted by experts and mapped using on-screen digitizing. To improve the
resulting land-cover maps, meta-level historical data such as agricultural census and village chronicles
were used, as well as free-response interviews with farmers (compare Brandt et al. 2002).
Additionally, the derived land-use maps were reviewed by local farmers in order to ensure accuracy.
In rare cases when different information sources contradicted each other, the most likely past and
present land-use practices were proposed.
An area of 4 ha was used as the minimum mapping unit, which at a scale of 1:25,000 is the minimum
common resolution of the data sources. At that level of detail different land uses can be separated.
However, this level of detail is not suitable for climate protection issues or biotope mapping, which
would require a spatial resolution of 0.1–1 ha. Those requirements could not be fulfilled due to the
insufficient scale of the historical maps. To overcome this problem single landscape indicators (e.g.
degree of crop mixture or structuring degree) were classified. In that way additional details on the
composition and quality of individual areas were able to be gathered.
5.7.3.Description of Habitat-types
Habitat composition is determined by human land use, but is also heavily influenced by the
topography of the site (i.e. altitude, slope and aspect). Therefore, in the case of similar land use,
different habitats can develop. Thus, habitats differ between intensively used grassland in valleys and
in subalpine zones as well as in managed forests of coniferous, mixed, and deciduous trees.
In this approach habitat types are based on phytosociological principles, which are defined in Ruffini
et al. (RUFFINI 2004). The definition includes a hierarchically classified register of natural, nearnatural, and artificial habitats found in the Central and Southern Alps. This register is linked to and
integrated with other international classification registers (e.g. Alpine Convention, EUNIS, the
Habitats Directive), thus enabling the documentation of the entire mountainous region within and
beyond the framework of definitions by the European Landscape Convention. This register,
therefore, is highly flexible and can be amended or extended as required. In the case of very
heterogeneous areas where it is neither possible nor meaningful to delimitate single habitats, they
[34]
are aggregated into habitat complexes (RUFFINI 2004). The most common habitat types and
complexes in South Tyrol are listed in Table 6
Code
Type
Habitat type
Code
Type
Habitat type
100
HC
Lake with littoral and silting 314000
H
Scree slope
500
HC
Rocks
and
scree
slopes
with
322000
H
Natural alpine
zones
111000
H
Lake
322220
H
Dwarf
shrub
snow-packs
grassland
113000
H
Watercourse
411100
H
Fruit
plantation
communities
130000
H
Wetland, moor
411200
H
Vineyard
133000
H
Cane brake
412000
H
Arable farmland
211000
H
Knee timber
421000
H
Rough meadow
212000
H
Green alder shrub
421100
H
Xeric grassland
221000
H
Subalpine coniferous forest
422000
H
Semi-rough
222100
H
Montane spruce-fire forest
423000
H
Fodder
meadowmeadow
222200
H
Pine-forest
451000
H
Orchard meadow
231000
H
Wet forest
452000
H
Larch meadow
232000
H
Thermopile oak forest
470000
H
Hedgerow
234000
H
Mesophilic mixed deciduous 511000
H
Dense urban
310000
H
Alpine
512000
H
Rural
settlement
forest pioneer formation
settlement
311000
H
Glacier and snow-pack
520000
H
Green space in
313000
H
Rock
570000
H
Other
infrastructure
settlement
Table 6: Most common habitat-types and complexes in South Tyrol according to RUFFINI 2004 (H =
Habitat, HC = Habitat complex)
5.7.4.Ecoregions
In another step we identified and compared ecoregions, i.e. landscape units that were created based
site conditions (biotic, abiotic), agricultural and silvicultural use, and settlement and infrastructure
development. A total of ten different ecoregions were differentiated; and for each, changes were
recorded and evaluated separately. Such subdivisions can be used by decision makers and
stakeholders allowing them to make better decisions and implement measures on different levels of
spatial development, e.g. in agriculturally used valley bottom or in agriculturally used pastures.
Ecoregions were defined on the basis of the Francisco–Josephinian Cartographical Register.
According to Mather et al. (1999), the maximum expansion of agricultural land use, i.e. the minimal
extension of forest areas in the Alpine region, occurred around 1850. Therefore, the defined
ecoregions based on data from 1850 were used to set a standardized starting point. We found other
studies that followed the same approach successfully (LOVELAND 2002).
5.7.5.Structural level
Groups of trees, hedges, single trees, slopes, debris and small-area habitats, such as bogs, rocks,
debris and corridors are regarded as structural elements. These elements as a whole provide a
valuable contribution to the landscape structure. They are significant as they break the monotony of,
for example, intensively used cultural landscapes. A very rich structured landscape serves small
animals as a retreat or corridor. The structural level of a surface is therefore an important criteria for
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[35]
describing landscape quality changes (WEINSTOERFFER & GIRARDIN 2000, BRANDT. 2002). The
structure levels range from completely forested areas to forest-free areas. For forest-free areas, the
absolute number is specified by non-connected structural elements. The minimum mapping unit is 4
ha (TASSER 2009).
Areas covered with trees are classified according to their degree of canopy cover. Hence 40 to 70%
tree cover gets classified as a light forest while an area with more than 70% tree cover falls in the
category of a dense forest. Unfortunately it was not possible to derive the structural information for
the year 1856 as the necessary information was not visible on the map.
5.7.6.Culture type
The indicator “culture type” provides information about the heterogeneity or homogeneity of land
use caused by human influence. In general this is based on two types of land use: pure and mixed. In
a monoculture the land is cultivated with one major cultural form in which the proportion of other
cultural forms is below 5% and the proportion of the mixed form to other cultural forms is above 5%
(TASSER 2009).
Figure 29: Different types of homogeneity or heterogeneity of cultivated land (TASSER 2009)
Figure29 visualises the following three cultural types:
a) Represents a grassland area in pure form (the part of other cultural forms is below 5%)
b) grassland area in a mixed form (the proportion of other cultural forms (forest islands, fields) is
between 5% and 25%)
c) grassland area in the mixed form with a proportion of other cultural forms (wine or fruit and field
crops) at 25% to 50%.
Cultural types
Forest 10
Wine or fruit 20
Cropland 30
[36]
Code
Homogeneous
11
Mixed stands (other cultural types 5 – 25%)
12
Mixed stands (other cultural types 25 - 50%)
13
Homogeneous
21
Mixed stands (other cultural types 5 – 25%)
22
Mixed stands (other cultural types 25 - 50%)
23
Homogeneous
31
Mixed stands (other cultural types 5 – 25%)
32
Grassland 40
Fallow land 50
Settlement 60
Not used areas 70
Mixed stands (other cultural types 25 - 50%)
33
Homogeneous
41
Mixed stands (other cultural types 5 – 25%)
42
Mixed stands (other cultural types 25 - 50%)
43
Homogeneous
51
Mixed stands (other cultural types 5 – 25%)
52
Mixed stands (other cultural types 25 - 50%)
53
Homogeneous
61
Mixed stands (other cultural types 5 – 25%)
62
Mixed stands (other cultural types 25 - 50%)
63
Homogeneous
71
Mixed stands (other cultural types 5 – 25%)
72
Mixed stands (other cultural types 25 - 50%)
73
Table 7: Cultural types classification (TASSER 2009)
Vineyards and orchards have in fact no relevance in the test-site as they occupy only a very small
area.
5.7.7.Sprawl
Using sprawl as an indicator allows one to describe settlement activity in the open landscape. We
used a data set containing all buildings exceeding an area of 16 m². The data includes all residential
and commercial buildings, stables, barns and cottages in the test-site. We calculated the density
distribution of the buildings which we subsequently used to draw conclusions about the population
density and settlement distribution.
5.7.8.Landscape regions
Landscape regions served as a tool to better describe landscape development. Landscape regions are
landscape units created by the interaction of different factors (biotic, abiotic) such as agricultural
land use as well as settlement development. Those processes formed a pattern of homogeneous
landscapes within the various municipalities. The major landscape regions are divided into functional
units in order to better understand the development that took place. The landscape units are the
following:
 Montane agricultural valley floor
The mountainous region covers an altitude of about 1000 m to 1600 m. The valley floor is mostly
covered by vegetation, arable and urban areas, but there also exist exceptions such as the
municipality Prettau, where is no agricultural in the valley floor.
 Montane agricultural slope area
These are, as the name suggests, cultivated slopes.
 Montane Forest Region
According to the label this landscape region is characterized by forest. Spruce is prevalent at this
altitude.
 Subalpine agricultural pasture region
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[37]
The subalpine region ranges from 1600 m to about 2300 m. Above the tree line one encounters
cultivated pastures and mountain meadows and pastures.
 Subalpine Forest Region
The subalpine forest region occurs above 1600 m between the montane forest region and the tree
line. The subalpine forest region is formed by spruce, larch, pine and mountain pine.
 Alpine and nivale natural region
The natural alpine and nival region succeeds the forest at 2300 m. It represents a mosaic of many
different large and small habitats; for example pastures, meadows, natural alpine meadows, scree
slopes, rocky areas and also areas which are covered with snow all year (Tasser 2009).
The classification of the landscape regions depends on the altitude and the cultivation type.
5.8. Results field mapping 2010
5.8.1.Overview of the existing landscape regions in the Nature Park Rieserferner Ahrn
In the Nature Park, the vegetation composition is significantly influenced by the siliceous soil, the
mountainous terrain and the inner-alpine-continental climate (AUTONOMOUS PROVINCE OF
BOLZANO 2007). In the six municipalities grassland and arable land are most common in the valleys.
In the following sections the three main vegetation types are defined.
Grassland:
Grassland areas are frequently found in the valley and on the slopes forming the South Tyrolean
landscape. According to Grabherr and Mucina 1993 those grasslands are characterized by
Arrhenatherion (valley-rich meadows and oat fields). The characteristic species are Arrhenaterum
elatius, Campanula patula, Crepis biennis, Galium album, Pastinaca sativa and Pimpinella major. The
plant community includes planar-submontane, fertilized hay meadows in Central Europe on moist to
moderately dry, slightly acidic to neutral soils. The lawns are fertilized with manure, chemical
fertilizer (NPK), and mowed 2-6 times a year. The crop is used as fodder for the farm animals. It is
either consumed directly, stored or dried and fed to the animals in the winter as hay.
Arable land:
In the test-site arable land is mainly found in the valleys and hillside area and is mostly used for
forage crops, e.g. corn. Further arable crops that occur include potatoes, rye, oats, barley and wheat.
Montane spruce forest:
Forest cover a major part of the hillsides. The very widely-spread montane spruce forest extends up
to 1,600 meters and contains the Norway spruce (Picea abies) (Figure 30). In terms of climatic and
edaphic conditions spruce find their climatic optimum in the continental inner Alps (MUCINA 1993).
Montane spruce forest includes vegetation communities such as Oxali-Piceetum montanum or
Luzulo-Piceetum montanum. Due to heavily shaded and acidic soils only very few other species, such
as some grasses, e.g. Luzula luzuloides and different types of Vaccinium, grow in the forest
(AUTONOMOUS PROVINCE OF BOLZANO 2007).
[38]
Figure 30: Montane spruce forest in the Ahrn Valley (Photo: Natalie Messner, EURAC)
Subalpine spruce forest:
From about 1,600 meters and above subalpine spruce forest (Larici Piceetum) (Figure 31) prevails,
which, in some areas, is changing over to larch pine forest or “Krummholz”. Natural mixed tree
species are found in subalpine Norway spruce forest. In particularly sunny and slightly open spots
larch and pine are found. Those two species also form the tree line between 1,900 m and 2,200 m
above mean sea level. Phytosociologically the spruce forest is relatively uniform (Picea abies) with
some larch trees (Larix decidua) (PEER 1995). The transition from montane to subalpine fir forest is
smooth, however the subalpine forest is characterised by its poorer types of shrubs and lichens. Due
to centuries of pasture management or burning, the forest line has shifted downward. In the Ahrn
Valley some slopes were even cleared. Later strict forestry regulations were adopted to restore the
original protective function (AUTONOMOUS PROVINCE OF BOLZANO 2007).
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[39]
Figure 31: Subalpine spruce forest in the Ahrn Valley (Photo: Natalie Messner, EURAC)
Krummholz - dwarf forest
Subsequent to the subalpine fir forest follows the so-called krummholz belt (Figure 32). This often
consists of dwarf stocks and some pine trees. This extensive dwarf forest is found in very extreme
site conditions, especially regarding wind, temperature and snow conditions.
[40]
Figure 32: „Krummholz“ (Pinus mugo) in Bärental in the Ahrn Valley (Photo: Natalie Messner,
EURAC)
Alpine grasslands and pastures
The alpine region begins in the region above the current tree line, and is agriculturally used with
grazing and mowing. In the natural park itself there are about 100 agricultural pastures. Abandoned
areas mainly include the high-altitude alpine areas and those areas that are difficult to access. The
Sieversio-Nardetum alpigenum, which is characterized by a dominant type of grass (Nardus stricta), is
common in alpine pastures. This is due to its resistance to grazing. Functionally, it protects from
erosion and snowslides. In between, there are also species such as the Leontodon hispidus, the
Potentilla aurea, Arnica montana, Carlina acaulis, Campanula barbata, Antennaria dioica, Aconitum
napellus (Figure 33) and Pulsatilla alpina.
Figure 33: Aconitum napellus in Ahrn Valley (Photo: Natalie Messner, EURAC)
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[41]
Carex curvula is dominant on siliceous ground, covering the areas up to the highest points..
Caricetum curvulae grows on acid, enriched and depleted severly decomposed organic soil
components. Carex curvula dominates the meadow associated grasses and are scattered like herbs.
Caricetum curvulae is usually very rich with shrubs and lichens, the lichen greatly surpassing the
phanerogams in biomass (Mucina et al. 1993).
In Prettau we also found Carex rosae. Carex rosae is a subspecies of Carex curvula and the Kenntaxon
of the plant community Elyno-Caricetum rosae. Apart from Carex curvula we also found species such
as Leontodon helveticus, Phyteuma orbiculare, Senecio incanus subsp. carniolicus, Primula glutinosa,
Primula minima, Pulsatilla vernalis as well as various lichens such as Cetraria islandica. Exposed to
strong wind and cold places Elyna myosuroides forms the Alpine meadows, with Leontopodium
alpinum, Artemisia muttelina, Gentiana nana, Dianthus glacialis, Oxytropis sericea, Erigeron uniflorus
or the Potentilla nivea (AUTONOMOUS PROVINCE OF BOLZANO 2007). At about 2,400 m above sea
level, there are places where snow remains until summer, the so-called ‘snow-valleys’. Here we
found species-poor vegetation and surfaces often covered with moss.
Subnival nivale-stage
Scree, rocks and glaciers are extreme habitats for plants, thus only vegetation that has adapted to
the harsh environmental conditions can be found here. These survival specialists include mosses,
algae and lichens or plant communities such as Androsacion alpinae. The latter are found on glacier
forelands, high ridges and mountain tops. Some very durable cushion plants, herbs, trellises and
small woody grasses are predominant here. The cryptogams cover, however, can be very dense,
depending on the substrate grain size, fine earth fraction, snow cover, vegetation period and water
supply. Nival plants invest nearly double the absorbed nutrients into the formation of roots as
opposed to plants in the valley. In this extreme environment the pioneer plants on glacial moraines
are Androsacae alpina, Silene acaulis, Ranunculus glacialis, Saxifraga moschata, Cerastium uniflorum
(MUCINA 1993).
Wetlands
The bogs are valuable ecosystems for specially adapted plants and animal communities. The acidic
and nutrient-poor environment means that the species living there are adapted to this habitat
RUFFINI (2001). Due to the high rainfall in the study area there could be quite a lot of wetlands.
5.8.2.Development of cultural types from 1865 to 2006
Following the photo interpretation, identification and classification of vegetation types that occur in
the test-site, we produced maps for each date in order to derive the development which occurred.
First we mapped and compared the land use for the entire test-site (Figure 34).
[42]
Figure 34: Development in cultural years for the four dates investigated
Secondly we calculated the proportions of land use of the total municipality area and compared
those figures for the four dates (Figure 35).
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[43]
Figure 35: Cultural types in percentage of the municipality area for each date investigated
As a result we found that the test-site has experienced a clear decrease of arable land. Fallow and
settlement areas are increasing. However, it should be noted that the agricultural land use is mostly
not homogeneous, but mixed. Monocultural use is increasing, especially in the municipality of
Prettau.
5.8.3.Development of Habitat-types from 1856 to 2006
We identified a significant increase in forest areas. Regarding the natural alpine meadows both
extensification as well as abandonment of mountain meadows and pastures took place to a large
degree. This is most evident in especially unfavourable locations. In the year 1900 there were still
around 4176 ha of managed grassland in the municipality of Prettau. In 2000 this figure was not even
half. In Ahrntal and Campo Tures pastures have shrunk in recent decades by 30-40%. A visual
comparison of the four different dates is available in HABIT-CHANGE outputs 4.2.3 and 4.2.5.
5.8.4.Mapping of wetlands
Figure 36 shows a clear decrease of wet areas in three municipalities of the test-site.
[44]
Figure 36: Development of wetlands in the municipalities in the Nature park Rieserferner-Ahrn
Figure 37 and 38 highlight those wetlands that were mapped during the fieldwork 2010. They are
located in the municipalities Ahrntal, Sand in Taufers and Percha.
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[45]
Figure 37: Wetlands mapped during the fieldwork 2010
Figure 38: Wetlands mapped in Sand in Taufers and Percha
[46]
5.9. Field mapping 2011
5.9.1.Methodology
The sampling areas within the test-site were defined with the help of the local knowledge of the
Nature Park administration. Biologists of the Institute for Alpine Environment, EURAC (Bolzano)
spent three days each week during the five summer months in the field in order to catalogue the
wide range of vegetation types in the test-site. We made a large number of relevés according to the
Braun-Blanquet method to define the plant communities (grassland ecosystems). Subsequently a
total of 129 specific sites were selected, where parts of plants were cut off. We harvested at 4
different points in time from mid-May to mid-October. The harvested area was bound by a 30x30cm
frame. Plant material was harvested with lawn edging shears. With the permission of the Nature Park
a total of 520 vegetation samples were collected.
We mapped vegetation types along five transects. The transects were selected to represent the
different aspects, elevation ranges (1,600 to 2,603 m a.m.s.l.), geological, morphological and
hydrological conditions that exist in the test site (Figure 38). Remote Sensing specialists also went to
the test site to understand the types of vegetation that can be found and to gain a feel for the
species that can be distinguished using image processing techniques.
Having completed the field work the locations of identified species were mapped in a Geographic
Information System (GIS). In a second step the boundaries of vegetation classes integrating point
locations of plant species were drawn. This data was later used as control data for the image
processing work.
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[47]
5.9.2.Locations of field mapping
In Figure 39 shows the locations of the five transects.
1.Prettau- Windtal (1621m-2603m)
2. Rein in Taufers- Ochsenlenke
(2037m-2544m)
3. Ahornach- Moosstock
(1903m- 2518m)
5. Antholz Niedertal-Grente Alm
(Raingrube) (2012m- 2352m)
4.Percha- Hochnall (1948m- 2323m)
Figure 49: Location of the five transects along which the mapping took place
[48]
Below the five transects are characterised, and examples are shown of a glacier foreland (Figure 40)
and a wetland (Figure 41), as they are found along the transect.
1)
Prettau Windtal (1621m-2603m)
-
northern aspect
-
management in the valley (mowing)
-
at higher elevations grazing by cows and sheep
-
abandoned areas
-
short growing season
-
some calcareus parts
-
decline of the glacier wetlands
-
36 specific sites were found and samples were taken
Figure 40: Glacier foreland below „Rötspitze“
Figure 41: Wetland
Figure 42shows the 44 locations were 36 vegetation samples were taken.
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[49]
Figure 42: Transect „Windtal“ in the municipality of Prettau, 36 points sampled
Figure 42 shows the 36 sampling locations and the polygons that were drawn back in the office
delimiting the vegetation type.
[50]
Figure 43: Transect Windtal (Prettau), the 36 sample sites and polygons mapped in the GIS
Figures 43 to 54 show a selection of the habitats and species found in the Transect Windtal (Prettau).
Figure 44: Eriophoretum scheuchzer
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
Figure 45: Rötspitz, glacier and its foreland
[51]
Figure 46: Wetland
Figure 47: Field mapping
Figure 48: Field mapping
Figure 49: „Pustertaler Sprinzen“ (old livestock variety)
Figure 50:Geranium view Rötspitze
Figure 51: Saxifraga stellaris
[52]
Figure 52: Ranunculus glacialis
Figure 53: Cirsium spinosissimum
Figure 54: Juncus jaquinii
2) Rein in Taufers (Ochsenlenke)
-
Exposure to the East
-
Management in the valley (mowing)
-
At higher elevations grazing by cows and sheep
-
Abandoned areas at higher elevations
-
short growing season
-
Some calcareous parts
-
small wetland area
-
32 specific sites were found and samples were taken
In figures 55 to 58 some of the species we found along the transect Rein in Taufers are visualised.
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[53]
Figure 55: Saxifraga paniculata
Figure 56: Jovibarba arenaria
Figure 57: Saxifraga aizoide
Figure 58: Chamorchis alpine
Figure 59 shows the locations of samples along the Transect Knuttn-Ochsenlenke.
[54]
Figure 59: Transect Knuttn-Ochsenlenke
In figure 60 the final digitised polygons of vegetation types are mapped.
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[55]
Figure 60: Vegetation types polygons digitised in the office after the field work (transect Knuttn)
Figures 61 to 66 show further examples of species found how we carried out the field work.
[56]
Figure 61: Collecting biomass
Figure 62: Gentiana acaulis
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
Figure 63: Saxifraga aizoides
[57]
Figure 64: Saxifraga paniculata
Figure 65: Pedicularis rostrata
Figure 66: Aconitum napellus
Figure 67 shows the result of the field work. First polygons of vegetation types found in the field
were drawn. Subsequently they were merged in one of the 13 classes.
[58]
Figure 67: The vegetation types found in the field were classified in 13 different classes
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[59]
3) Ahornach- Moosstock (1903m- 2518m)
-
Exposure to south
-
Management of the land at lower altitudes
-
Terrain too steep to keep livestock there
-
At higher altitudes, gravel plains with pioneer species
-
Pinus cembra
-
22 specific sites were found and samples were taken
Figures 68 and 69 show typical vegetation along the Ahornach-Moosstock transect.
Figure 68: typical plant communities of Moosstock Figure 69: Rhododendretum ferrugineum (Moosstock)
In figure 70 the 22 sample locations are mapped. Figure 71 shows the final classified polygons.
[60]
Figure 70: Transect: Moosstock (Campo di Tures)
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[61]
Figure 71: Polygons digitised and merged into classes at the Moosstock transect (Campo di Tures)
Figure 72 to 76 display typical sites in Transect Moosstock.
[62]
Figure 72:typical debris of Moosstock
Figure 74:Picea cembra
Figure 73: alpine hut
Figure 75: biomass harvesting
Figure 76: Juncus trifidus
4)
Percha- Hochnall (1948m- 2323m)
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[63]
-
Exposure to the West
-
Grazing by cows and sheep
-
Sharp boundary between plant and remote wind edge
-
dwarf shrubs dominate
-
Small wetland area
-
24 specific sites were found and samples were taken
Figure 77 shows the location of the 24 samples taken at the transect Percha-Hochnall.
Figure 77: Transect Hochnall (Percha)
[64]
In Figure 78 the final polygons displaying the classified vegetation types are shown.
Figure 78: Classified polygons for the Transect Hochnall (Percha)
Figures 79 to 83 show some typical vegetation types in the transect Hochnall and how the field work
was carried out.
Figure 79: identifying plant communities
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
Figure 80: typical scrub-vegetation encroachment
[65]
Figure 81: biomass harvesting
Figure 82:Sieversio-Nardetum typicum
Figure 83: typical shrub vegetation types
5) Antholz Niedertal-Grente Alm (Raingrube) (2012m- 2352m)
-
Exposure to south
-
Grazing by cows
-
Abandoned areas in windless locations
-
14 specific sites were found and samples were taken
Figure 84 shows the digitized polygon boundaries of vegetation types based on the sampling in the
field and in figure 85 the final classified polygons are mapped.
[66]
Figure 84: Transect Grente, Antholzer Valley
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[67]
Figure 85: Transect Grente, Antholzer Valley
Figures 86 to 90 show some examples of species and habitat types found in transect Grente.
Figure 86: Pioneer vegetation
[68]
Figure 87: Primula minima
Figure 88: alpine pasture
Figure 89: alpine pasture
5.10.
Figure 90: Antholzer Valley
Results from field mapping 2011
As a first step we phytosociologically classified the species found in the field according to Ellmauer
and Mucina (Table 8)
Table 8: Species found during field work
1
2
3
4
5
6
7
8
9
10
11
Achillea millefolium
71
Festuca rubra
141
Polytrichum norvegicum
Achillea moschata
72
Festuca varia
142
Potentilla aurea
Aconitum napellus
73
Festuca violacea
143
Potentilla erecta
Agrostis alpina
74
Galium anisophyllon
144
Primula glutinosa
Agrostis capillaris
75
Galium pumilum
145
Primula minima
Alchemilla vulgaris agg.
76
Gentiana acaulis
146
Pritzelago alpina
Androsace alpina
77
Gentiana bavarica
147
Pulsatilla verna
Antennaria dioica
78
Gentiana campestris
148
Ranunculus acris
Anthoxanthum alpinum
79
Gentiana germanica
149
Ranunculus glacialis
Anthoxanthum odoratum
80
Gentiana verna
150
Ranunculus montanus
Anthyllis vulnerabilis
81
Geum montanum
151
Rhinanthus glacialis
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[69]
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
[70]
Arabis alpina
82
Gnaphalium norvegicum
152
Rhododendron ferugineum
Arabis subcoriacea
83
Gnaphalium supinum
153
Rumex acetosa
Arenaria biflora
84
Gymnademia conopsea
154
Rumex acetosella
Arnica montana
85
Helianthemum nummularium
155
Sagina saginoides
Artemisia genipi
86
Helictotrichon versicolor
156
Salix foetida
Aster alpinus
87
Hieracium pilosella
157
Salix glaucocericea
Avenella flexuosa
88
Hieracium sp.
158
Salix herbaceae
Botrychum lunaria
89
Hieracium villlosum
159
Salix reticulta
Briza media
90
Homogyne alpina
160
Salix retusa
Calamagrostis varia
91
Hypericum maculatum
161
Salix winzig
Caluna vulgaris
92
Juncus alpinoarticulatus
162
Salix serpyllifolia
Campanula barbata
93
Juncus filiformis
163
Saxifraga aizoides
Campanula cochleariifolia
94
Juncus jaquinii
164
Saxifraga androsaceae
Campanula glomerata
95
Juncus monanthos
165
Saxifraga bryoides
Campanula scheuchzeri
96
Juncus trifidus
166
Saxifraga oppsitifolia
Cardamine amara
97
Juniperus comunis ssp. nana
167
Saxifraga paniculata
Carex atrata
98
Koeleria hirsuta
168
Saxifraga stellaria
Carex capillaris
99
Larix decidua
169
Sedum alpestre
Carex curvula
100
Leontodon gerupft
170
Sedum atrata
Carex curvula ssp. rosae
101
Scorzoneroides helveticus
171
Sedum gelb
Carex digitata
102
Scorzoneroides hispidus
172
Senecio incanus
Carex halleriana
103
Leucanthemum alpinum
173
Sesleria caerulea
Carex atrata
104
Ligusticum mutellinoides
174
Sesleria sp.
Carex leporina
105
Loiseleuria procumbens
175
Sibbaldia procumbens
Carex montana
106
Lolium perenne
176
Silene acaulis
Carex nigra
107
Lotus alpinus
177
Silene dioica
Carex nigra
108
Lotus corniculatus
178
Silene vulgaris
Carex pallescens
109
Luzula alpinopilosa
179
Soldanella alpina
Carex paupercula
110
Luzula luzuloides
180
Stellaria gelb
Carex sempervirens
111
Luzula spicata
181
Stellaria sp.
Carlina acaulis
112
Luzula sudetica
182
Taraxacum officinalis
Carum carvi
113
Melica nutans
183
Thalictrum aquilegifolium
Cerastium alpinum
114
Minuartia biflora
184
Thesium alpinum
Cerastium fontanum
115
Minuartia verna ssp.
185
Thlaspi alpestre
Cerastium holosteoides
116
Myosotis alpestris
186
Thymus sp.
Cerastium media
117
Myosotis feucht
187
Thymus vulgaris
Cerastium pedunculatum
118
Myosotis sylvatica
188
Tofieldia calyculata
Cerastium uniflorum
119
Nardus stricta
189
Traxacum officinalis
Cerastium alpinum
120
Oxytropis campestris
190
Trichophorum alpinum
Cetraria islandica
121
Parnassia palustris
191
Trifloium montanum
Chamorchis alpina
122
Pedicularis rostrato-capitata
192
Trifolim badium
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
Cirsium spinosissimum
123
Pedicularis sudetica
193
Trifolium alpina
Crepis aurea
124
Phleum alpinum
194
Trifolium pratense
Crocus albiflorus
125
Phleum alpinum
195
Trifolium pratense ssp. nivalis
Deschampsia cespitosa
126
Phleum rhaeticum
196
Trifolium repens
Dryas octopetala
127
Phyteuma betonicifolia
197
Trisetum spicatum
Elyna myosuroides
128
Phyteuma globularifolium
198
Trollius europaeus
Empetrum nigrum
129
Phyteuma hemisphaerica
199
Tussilago farfara
Epilobium anagallidifolium
130
Phyteuma orbiculare
200
Vaccinium gaultheroides
Equisetum fluviatile
131
Phytheuma globularifolium
201
Vaccinium myrtillus
Erica carnea
132
Pimpinella major
202
Vaccinium uva ursis
Erigeron alpinus
133
Pinus cembra
203
Vaccinium vitis ideae
Eriophorum angustifolium
134
Plantago media
204
Veratrum album
Euphrasia minima/montana?
135
Poa annua
205
Veronica alpina
Euphrasia officinalis
136
Poa pratensis
206
Veronica chamaedrys
Festuc halleri
137
Poa violacea
207
Veronica fruticans
Festuca alpina
138
Polygala alpestris
208
Veronica officinalis
Festucaquadriflora
139
Polygala serpyllifolia
209
Veronica serpyllifolia
Festuca valesiaca
140
Polygonum viviparum
210
Viola biflora
Table 9 lists all 34 vegetation types that we found during the entire field work.
Table 9: List fo 34 vegetation types found during field work
Dermatocarpetum rivulorum
Carici curvulae-Nardetum
Juncetum jaquinii
Loiseleurio-Caricetum curvulae
Equisetum fluviatilis
Caricetum curvulae
Caricetum magellanicae
Homogyno discoloris-Loiseleurietum
Caricetum goodenowii
Arctostaphylo-Loiseleurietum
Eriophoretum scheuchzeri
Loiseleurio-Cetrarietum
Alchemillo-Poetum supinae
Dryadetum octopetalae
Deschampsio cespitosae-Poetum alpinae
Seslerio-Caricetum sempervirentis
Poetum alpino-supinae
Trifolio thalii-Festucetum nigricantis
Peucedantemum ostruthii
Rhododendretum ferruginei
Elyno-Caricetum rosae
Rhododendro-Vaccinietum
Gymnomitrio concinnati-Loiseleurietum procumbentis
Rhododendro-Juniperetum
Crepido-Festucetum commutatae
Calluno-Vaccinietum
Polytrichum sexangularis
Empetro-Vaccinietum gaultheiroides
Polytricho juniperini-Soldanelletum pusillae
Sieversio montanae-Nardetum strictae ssp. typicum
Androsacetum alpinae
Sieversio montanae-Nardetum strictae ssp. vaccinietosum
Sieversio-Oxyrietum digynae
Empetro-Vaccinietum gaultherioides
Salicetum herbaceae
Junipero-Arctostaphyletum
Salicetum retuso-reticulatae
Vaccinio-Juniperetea
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[71]
Nardo-Gnaphalietum supini
Salicetum helveticae
Luzuletum spadiceae
Saxifragetum biflorae
Caricetum firmae
Juncetum trifidi
Caricetum sempervirentis
Hygrocaricetum curvulae
Field work was carried out by Silvia Pramstaller, Natalie Messner and Barbara Stoinschek (EURAC).
Photographs and maps were produced by Silvia Pramstaller, Natalie Messner and Barbara
Stoinschek.
6. Conclusions
The report 4.2.2 on field-mapping documentation shows a variety of different methods of
documenting habitats in different natual environments such as forests (Hainich region, Germany),
Alpine areas (Bucegi and Rieserferner Ahrn) and wetlands (Balaton Uplands National Park) for the
HABIT-CHANGE project. As this report is indicating, the methods of mapping and documenting
natural vegetation vary greatly. Three methods can be differentiated within this project:

Biopyhsical parameters from already detected and stratified vegetation types can be
derived. The field campaign with hemisperical photographs and subsequently calculated Leaf
Area Index (LAI) for beech forest in the Natial Park Hainich stands exemplary for this type of
documentation. With the information on the LAI maps indicating the biomass and vitality of
forests can be derived. This is especially valuable when estimating the conservation status
within NATURA 2000 areas. Repeated measurements could indicate possible damages of the
forest due to climate change, even if the changes are very small.

Sample-based mapping can be implemented when a full coverage mapping over a large area
is not possible. Exemplary, the Bucegi Natural Park used this method. Detailed mapping of
small sampling plot (often 2 by 2 meters) are carried out on a stratified sampling. The sample
plots give then a very detailed picture not just about the main habitats, but about species
coverage and information on umbrella and protected species. This sample plots can be used
to extrapolate the information to the full coverage area, which is often problematic, because
the distribution of the habitats is no linear process and relies on many factors. A samplebased mapping can be used as input training samples for further remote sensing analyses (as
implemented in the HABIT-CHANGE project - see combined Output 4.2.3, 4.2.4, 4.2.5, 3.1.9).

Full-coverage mapping of a region, as implemented within the Balaton Uplands National
Park, offers ready-to-use maps of large areas. However, the level of detail of the mapping
process is clearly resuced when using this method. Often, not single species, but merely
vegetation compositions or habitats can be maps. Within this mapping, the photo
documentation is more complicated, since there is no easy (upwards or downwards) nadir
photo which can be taken. Therefore, a documentation via the finished maps can be offered.
[72]
The documentation of all the different types of mapping mentioned above is of high importance. It
gives the chance to validate results and a higher probability of reproducibility. Especially photo
documentations are of a high value for later analyses of the results. Therefore, the presented
methods are of a high value within the protected areas as well as for the subsequent project outputs,
especially in Work Package 4.
A futher development of the presented variety of methods would be a consistent database of photos
and relations to the mapping results (species coverage, LAI, habitat, conservation status etc.).
Although this aim was not implemented within HABIT-CHANGE, the managers in the conservations
areas are utilizing the results in this way and exchanged information about the technical
implementation within the project.
7. References
Brandt JJE, Bunce RGH, Howard DC, Petit S 2002, ‘General principles of monitoring land cover change
based on two case studies in Britain and Denmark, Landscape and Urban Planning, (20), 37-51.
Nationalpark Hainich (2008): Wälder im Nationalpark Hainich – Ergebnisse der 1. Permanenten
Stichprobeninventur 1999-2001. ERFORSCHEN Band
Loveland TR, Sohl TL, Stehman SV, Gallant AL, Sayler KL and Napton DE 2002 ‘A
strategy for estimating the rates of recent United States land-cover changes’, Photogramm
Eng Remote Sens, (68), 1091-1099.
Messner N, 2011, ‘Landschaftsveränderung in den Naturparkgemeinden Rieserferner-Ahrn mit
besonderer Berücksichtigung der Feuchthabitate‘, Master thesis, University of Innsbruck,
unpublished.
Milton EJ 2001 Review of 'Mather, PM 1999, ‘Computer processing of remotely-sensed images. An
introduction’, Chichester: Wiley.'. Progress in Physical Geography, 25, (1), 145-146.
(doi:10.1191/030913301672673414).
Ruffini FV, Brutti E, Martellato L, Kammerer, A, Oberlechner, D 2004, ‘Natura 2000 in Südtirol.
Leitfaden für die Ausführung der Managementpläne‘, Europäische Akademie Bozen, - Bozen.
Tasser E, Ruffini FV, Tappeiner U, 2009, ‘An integrative approach for analysing landscape dynamics in
diverse cultivated and natural mountain areas’, Landscape Ecology, 24, (5), 611-628.
Weinstoerffer J, Girardin P, 2000, ‚Assessment of the contribution of land use pattern and intensity
to landscape quality: use of a landscape indicator’, Ecological Modelling, (130), 95–109.
This project is implemented through the CENTRAL
EUROPE Programme co-financed by the ERDF
[73]