Change from Agricultural to Touristic Use Effects on the Aesthetic Value

Landscape and Urban Planning 187 (2019) 23–35

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Landscape and Urban Planning

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Research Paper Change from agricultural to touristic use: Effects on the aesthetic value of T landscapes over the last 150 years ⁎ Uta Schirpkea,b,1, , Andreas Altzingera,1, Georg Leitingerb, Erich Tassera a Institute for Alpine Environment, Eurac Research, Viale Druso 1, 39100 Bozen/Bolzano, Italy b Department of Ecology, University of Innsbruck, Sternwartestraße 15, 6020 Innsbruck, Austria

GRAPHICAL ABSTRACT

ARTICLE INFO ABSTRACT

Keywords: The demand for cultural ecosystem services (CES) is increasing, and aesthetic values contribute substantially to Cultural ecosystem services attract visitors to mountain regions, enhancing the socio-economic well-being. While most studies focused on the Accessibility assessment of aesthetic values under current conditions, this study aimed to evaluate the historic development of Land use change aesthetic values from the perspective of today by analysing changes in the actual supply of this CES along roads Spatial modelling and paths in Sölden in the Ötztal valley (Austria) since the beginning of tourism. We first mapped roads and Social media paths for five time steps over the last 150 years to then estimate aesthetic values along these infrastructures, using a spatially explicit modelling approach. Furthermore, we compared spatial patterns of visitation preferences derived from social media data with predicted aesthetic values. Our results indicate that an increased access to areas of high aesthetic values was related to general increases in the supply of aesthetic values until 1950. Although the accessibility to high-elevation areas continued to increase until 2017, aesthetic values generally decreased due to landscape changes induced by the shift from mainly agricultural to touristic use. The abandonment of alpine pastures occurred mainly above the forest belt, which coincides with high levels of photo density, as most pictures were taken around mountain huts and on mountain peaks. If carefully planned and managed, mountain regions may actively enhance aesthetic experiences and foster the touristic use by providing good infrastructure, but land use policies and landscape management should support agricultural activities to maintain high levels of aesthetic values.

⁎ Corresponding author at: Viale Druso 1, 39100 Bozen/Bolzano, Italy. E-mail addresses: [email protected] (U. Schirpke), [email protected] (A. Altzinger), [email protected] (G. Leitinger), [email protected] (E. Tasser). 1 Joint first authors. https://doi.org/10.1016/j.landurbplan.2019.03.004 Received 3 September 2018; Received in revised form 15 March 2019; Accepted 16 March 2019 Available online 30 March 2019 0169-2046/ © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/). U. Schirpke, et al. Landscape and Urban Planning 187 (2019) 23–35

1. Introduction important transport route to reach the tourist destinations, but soon, a new tourism infrastructure, such as roads and hotels, was developed Cultural ecosystem services (CES) are commonly defined as non- (Bätzing, 2003). During that time, Alpine Clubs of different countries, material benefits that are generated by human interaction with eco- which are associations focusing on mountain sports, mountaineering systems (Millennium Ecosystem Assessment, 2005). Ecosystems con- and alpinism as well as on related environmental and social issues, did tribute, for example, to aesthetic experiences, recreation, inspiration not only build mountain huts and hiking trails but also access roads to and spiritual enrichment, cultural identity and other cultural values the Alpine valleys (ÖAV, 2011). This increase in tourism infrastructure, that are highly important for physical and mental health and, hence, providing access to new areas, has again positive effects on visitation human well-being (Chan, Satterfield, & Goldstein, 2012; de Vries, van rates (Pomfret, 2011). Dillen, Groenewegen, & Spreeuwenberg, 2013; Triguero-Mas et al., To date, these socio-economic changes have been rarely related to 2015). More leisure time, improved living standards, demographic aesthetic values over a long time span. While few studies analysed the changes and rising concerns about physical and mental health are some effects of past changes of landscape pattern on aesthetic values (e.g., factors that have led, and still are leading, to an increasing demand for Lavorel et al., 2017; Schirpke et al., 2016), the role of accessibility and CES (Guo, Zhang, & Li, 2010). At the same time, in particular, the ex- underlying socio-economic mechanisms have been largely disregarded. tension and intensification of agricultural activities and urban sprawl In this study, we therefore illustrate effects on aesthetic values, origi- result in a decline of ecosystem services and enjoyable environments nating from the shift from agricultural to touristic use since the be- (Metzger, Rounsevell, Michlik, Leemans, & Schröter, 2006). Mountain ginning of tourism, based on the example of the municipality of Sölden regions with an appealing landscape and a high level of near-natural in the Ötztal valley (Austria). Since 4500 BCE, this area has been used habitats are therefore of increasing importance for providing CES, in- as grazing and hunting ground and has later on been settled by people cluding the aesthetic value of the landscape and recreational activities coming from today's region of South Tyrol (Italy) (Haas, Weber, Reiter, (Schirpke, Timmermann, Tappeiner, & Tasser, 2016; Schirpke, Meisch, Wrbka, Prinz, Kaufmann, & Ryffel, 2008). In the 19th century, the Marsoner, & Tappeiner, 2018; Scolozzi, Schirpke, Detassis, Abdullah, & ‘Inner Ötztal valley’ was deployed by a typical agrarian community Gretter, 2015; Tenerelli, Demšar, & Luque, 2016). In this sense, the which relied on livestock farming during summer and on craft activ- aesthetic value is one of the most important values that people associate ities, mainly weaving, during winter. Due to the limited income op- with the landscape and that vitally contributes to human well-being portunities in the agricultural sector, many people emigrated during (Bieling, Plieninger, Pirker, & Vogl, 2014). this time, inducing a decrease in the number of inhabitants from around Landscapes are often used for destination marketing of touristic 200 in 1760 to 39 in 1910. New income sources were found in the mountain locations (Pechlaner, Raich, & Zehrer, 2007). However, the upcoming tourism sector, with the curate and alpinist Franz Senn landscapes of mountain regions all over the world have been and still playing an important role. He was a co-founder of the German Alpine are subject to changes due to altered socio-economic conditions that Club (DAV) and supported the construction of mountain huts and determine the type and intensity of land use (Briner, Elkin, & Huber, hiking trails. Mountain huts are buildings located at high elevations and 2013; Cocca, Sturaro, Gallo, & Ramanzin, 2012; Egarter Vigl, Schirpke, provide food and shelter to mountaineers, climbers and hikers; they are Tasser, & Tappeiner, 2016; Munteanu et al., 2014; Semwal et al., 2004). mostly only accessible by foot. There are also other buildings (Almen) In the European Alps, the fundamental structural change started in the where cattle herders (Senner) live during the summer while they look 19th century, when farming, crafts and mining became less important after grazing livestock. Today, many of these ‘Almen’ also offer food due to the industrial revolution (Bätzing, 2003). Agricultural areas with and beverages for tourists. good climatic conditions and easily accessible with machineries were Accessibility to the Ötztal valley strongly increased with the con- intensified, whereas less accessible areas, especially alpine pastures, struction of the Arlberg railway in 1848 (Meixner & Siegl, 2010) and were often abandoned (Rutherford, Bebi, Edwards, & Zimmermann, the enlargement and paving of paths (Meleghy, Preglau, & Walther, 2008; Tasser, Ruffini, & Tappeiner, 2009; Zimmermann, Tasser, 1982; Portnov, Axhausen, Tschopp, & Schwartz, 2011). This is also Leitinger, & Tappeiner, 2010). Consequently, the agriculturally used reflected in the increase in tourists. In 1863, around 100 tourists were area in the Alps decreased from almost 50% in 1850 to 28% in 2000 counted in Obergurgl (Meixner & Siegl, 2010). From 1951, the number (Egarter Vigl et al., 2016). This decline of the traditional cultural of overnight stays increased from 100,000 (Austrian Central Statistical landscape results in altered landscape patterns and affects the provision Office, 1953) to more than 2.5 million in 2016 (Statistics Austria, of ecosystem services (Garbarino, Sibona, Lingua, & Motta, 2014; 2016). In contrast, a sharp decline in the number of farmers (from 230 Lavorel et al., 2017; Navarro & Pereira, 2012). Roughly at the same farmers in 1951 to 18 full-time farmers in 1999) caused a decrease in time as the beginning decline in farming, first economic activities re- managed grassland and arable land by 63%, resulting in an increase in lated to tourism started in some parts of the Alps (Kariel & Kariel, natural grassland, forest and shrub areas. Such socio-economic devel- 1982). After a period of stagnation caused by two world wars, tourism opments are by no means unique to the Ötztal Valley; similar trends are increased dramatically after the 1950s due to economic growth documented for many other European regions (Hamre, Domaas, (Bätzing, 2003). Nowadays, in many Alpine regions, income from Austad, & Rydgren, 2007; Schermer et al., 2016; Zimmermann et al., tourism is often more important than that from farming, and a similar 2010). As the socio-economic conditions of the Ötztal Valley are typical development pattern can be observed in many mountain regions for large parts of the Central Alps, especially for the Austrian, Swiss and worldwide (Price, 2013). In particular, trekking-related tourism is northern Italian parts (Tappeiner, Tappeiner, Hilbert, & Mattanovich, currently a fast-growing sector in developing countries, with numerous 2003), this study site provides a generic case that is representative of a direct and indirect effects on the environment and on the local economy wide range of regions. (Geneletti & Dawa, 2009; Pęksa & Ciach, 2015; Rinzin, Vermeulen, & In the light of the above described developments, we hypothesise Glasbergen, 2007). The increasing touristic use also may negatively that areas of high aesthetic values were made accessible through new influence aesthetic values (Beza, 2010; Gundersen & Vistad, 2016; Lynn infrastructure, resulting in changes in the actual supply of CES. We refer & Brown, 2003) and may lead to conflicts among recreationists or here to the actual supply of CES, i.e. the CES that are accessible via wildlife (e.g., Koemle & Morawetz, 2016; Peters et al., 2015). Together roads and paths and therefore usable, while the potential supply in- with the development of tourism, an increase in infrastructure can be cludes the entire area disregarding whether it can be used or not observed, as visitation rates are considerably determined by accessi- (Burkhard & Maes, 2017). Moreover, we hypothesise that recent land bility (Ala-Hulkko, Kotavaara, Alahuhta, Helle, & Hjort, 2016; Baró, cover changes may affect aesthetic values, as reported by recent studies Gómez-Baggethun, & Haase, 2017; McKercher, Chan, & Lam, 2008). In (Egarter Vigl et al., 2016; Schirpke et al., 2016). We therefore evaluated the European Alps, the railway network was initially the most changes in aesthetic values from the perspective of today, analysing

24 U. Schirpke, et al. Landscape and Urban Planning 187 (2019) 23–35 how the actual supply of aesthetic values has evolved along roads and Messager, & Miller, 2009). In our study site, we used such spatially paths in Sölden since the beginning of tourism. Specifically, we mapped explicit modelling approach that links human preferences to landscape roads and paths for five time steps over the last 150 years. Based onthe properties to estimate aesthetic values (Schirpke et al., 2016). We used resulting maps, we modelled aesthetic values using a spatially explicit recently gathered information on landscape preferences not only to modelling approach that relies on human perception (Schirpke et al., estimate this CES for present time, but also for past times, as it was not 2016) and examined the changes in the actual supply of aesthetic values possible to directly collect such data nor to estimate changes in per- in relationship to accessibility and land-cover changes. Moreover, we ceptions from literature. Rather, this study illustrates how aesthetic evaluated the spatial patterns of visitation preferences derived from values have evolved in the landscape from the perspective of today. social media, with predicted aesthetic values to compare the actual In addition to the stated preferences methods, aesthetic values were supply with the actual demand of this CES. Finally, we discuss our recently assessed using indirect methods to reveal people’s preferences findings in the light of current trends (particularly related to climate such as crowd-sourced information from social media (e.g. Langemeyer, change; e.g., Braun, 2008; Lieskovský, Rusňák, Klimantová, Izsóff, & Calcagni, & Baró, 2018; Sonter, Watson, Wood, & Ricketts, 2016; Gašparovičová, 2017; Pröbstl-Haider, Dabrowska, & Haider, 2016; Tieskens, Van Zanten, Schulp, & Verburg, 2018). These data can be Stoffel, Tiranti, & Huggel, 2014) and management implications (i.e. used to measure aesthetic values through the spatial distribution of managing impacts on the environment and CES; e.g., Marion, 2016; photographs of the natural environment, assuming that people take Migoń & Pijet-Migoń, 2017; Pickering & Hill, 2007) as well as metho- more pictures at places they prefer. We therefore included such data in dological limitations. this study to analyse hotspots of recent activity and to evaluate spatial patterns of visitation preferences (demand) in relationship with esti- 2. Materials and methods mated aesthetic values (actual supply) for the year 2017 (Fig. 2).

2.1. Conceptual framework 2.2. Mapping roads and paths

Various frameworks and classifications of ecosystem services refer The development of roads and paths provides insights into the use of to ‘aesthetic values’ (e.g. Boyd & Banzhaf, 2007; De Groot, Wilson, the landscape. In our study site, the municipality of Sölden in Austria Boumans, 2002; Haines-Young & Potschin, 2018; Millennium (Fig. 2), we distinguished the following three types: asphalt roads, non- Ecosystem Assessment, 2005), but no common definition of this term asphalt roads and paths. Non-asphalt roads can be main roads in the exists. Most of these frameworks mention related values such as past, e.g. in 1915. After 1950, such roads were mainly used by forestry ‘beauty’, ‘enjoyment’ ‘amenity and fulfilment’ and give examples of use and agriculture. Paths include footpaths in settlement areas, paths such as decorative elements, artistic inspiration or labelling as scenic outside of villages, mainly for agricultural purposes, and paths for routes. In line with most studies on ecosystem services, we use the term touristic use. Furthermore, we analysed hiking trails, i.e. specific parts ‘aesthetic values’ referring to scenic beauty, aesthetic experiences and of all above-mentioned road types, which were specifically classified in appreciation of the landscape. Moreover, aesthetic values are con- hiking maps by the Austrian Alpine Club. As the hiking trails were not sidered as strongly related to recreational ecosystem services, as the indicated in the historical maps, senior mountain guides, senior aesthetic enjoyment of the landscape contributes to the selection of farmers, a chronicler and other locals were asked to draw historical locations to practice recreational activities (van Zanten et al., 2016). hiking trails on historical maps during a workshop. The assessment of aesthetic values, however, continues to be diffi- The mapping of the roads and paths was done by onscreen digita- cult because they are only partially defined by the biophysical char- lisation of different historical maps (Table 1). To make the maps acteristics of the landscape (e.g. type of vegetation, spatial pattern) that comparable, only categories of roads and important/highly frequented can be described quantitatively (Burkhard & Maes, 2017; Daniel et al., paths which occurred in each map were digitalised. This means that, for 2012). Indeed, they are generated from the interaction between the example, interrupted footpaths (paths used by hunters and shepherds) landscape and the human observer (Daniel, 2001). Human perceptions mapped in the maps from the Alpine Club were not digitalised as they are subjective, influenced by personal experiences and values, andare did not occur in other maps. therefore difficult to standardise or generalise (Lothian, 1999). Studies report, for example, some differences in preferences between different 2.3. Modelling and analysing the aesthetic value groups of age, social or cultural background (e.g. Hunziker et al., 2008; Tveit, 2009; Schirpke, Tappeiner, Tappeiner, & Tasser, 2019; Soliva, The aesthetic value was estimated along the roads and paths using a Bolliger, & Hunziker, 2010; Zoderer, Stanghellini, et al., 2016; Zoderer, spatially explicit modelling approach (Schirpke, Tasser, & Tappeiner, Tasser, Erb, Lupo Stanghellini, Tappeiner, 2016). Nevertheless, many 2013; Schirpke et al., 2016). This approach relates human landscape studies found substantial agreement in preferences indicating that preferences obtained from a photo-based survey to landscape char- variations among landscapes are greater than the differences in people’s acteristics derived from maps by regression analysis (Fig. 3). judgments (Daniel, 2001). Human perceptions are mostly gathered on site or by photo-based surveys (Grêt-Regamey, Bishop, & Bebi, 2007; 2.3.1. Assessment of human preferences Hunziker et al., 2008; Junge, Schüpbach, Walter, Schmid, & The perception survey used a photo-based questionnaire, including Lindemann-Matthies, 2015; Zoderer, Stanghellini, et al., 2016). 24 panoramic pictures. The pictures represented major landscape types Thereby, the use of photos offers visual stimuli that match real-life of the Central Alps such as alpine grassland, forest, agriculturally used experience of the landscape quite well (Natori & Chenoweth, 2008), as landscapes, and urbanised landscapes (Fig. 4). The pictures covered a photos show the landscape in a holistic way. Perception-based assess- full 360° panorama, allowing to evaluate the entire visual environment ments reach a high level of reliability and are deemed suitable to of a viewpoint (Meitner, 2004) and were taken in four different areas in capture people’s landscape preferences (Daniel, 2001). the Central Alps in July: the Stubai Valley (Austria), Lech Valley Preferences from perception surveys have been related to biophy- (Austria), Pustertal (Italy), and the Vinschgau (Italy). For each pa- sical properties of landscapes (2016; Dramstad, Tveit, Fjellstad, & Fry, noramic picture, four single pictures were taken using a tripod, and a 2006; Franco, Franco, Mannino, & Zanetto, 2003; Schirpke, Hölzler, focal length of 50 mm, representing the view east, west, north, and et al., 2013), allowing to model the aesthetic value for any location in south. The four pictures were then assembled into one panoramic pic- the landscape (Fig. 1). By measuring the biophysical characteristics of ture with Adobe PhotoShopTM CS5. Where necessary, corrections were landscapes as well as their spatial arrangement, the visual character of made to obtain uniform exposure. The panoramic pictures were sorted the landscape can be described quantitatively (Ode, Fry, Tveit, randomly and inserted into a short questionnaire.

25 U. Schirpke, et al. Landscape and Urban Planning 187 (2019) 23–35

Fig. 1. Conceptual framework to assess changes in the supply of aesthetic values, hypothesising that areas of high aesthetic values were made accessible through new infrastructure, but that recent land cover changes may have negative impacts on these aesthetic values (Egarter Vigl et al., 2016; Schirpke et al., 2016). White boxes indicate input data or aggregated indicators, the grey box refers to the used modelling approach according to Schirpke et al. (2016) and coloured boxes are intermediate or final results. Roads and paths (1) as well as land use/cover (3) differs for each time step, whereas human preferences (2) and socialmediadata(4) refer only to the last time step and represent current preferences.

Fig. 2. Location of the study site Sölden and distribution of ecoregions. Sölden is located in the southern part of the Ötztal valley of Tyrol, Austria. Elevation ranges from 1,285 m a.s.l. on the valley floor to 3,768 m a.s.l. at the highest peak, the Wildspitze. The Ötztal valley belongs to the inner Alpine dry valleys, andaroundtwo thirds of the study area are covered with glaciers or high mountain ranges with little or no vegetation. The other third can be divided in managed grassland, arable land, natural grassland, shrub, forest and settlement areas.

The respondents were asked to evaluate them according to their out. own appraisal from 1 (=I don’t like it at all) to 10 (=I like it very The survey was carried out in the same areas as the pictures were much). Furthermore, questions regarding personal information such as taken (Stubai Valley (Austria), Lech Valley (Austria), Pustertal (Italy), gender, age, and nationality were included. The questionnaire was the Vinschgau (Italy)) during August and September. Winter tourists prepared in German and Italian and it took about 5 to 10 min to fill it were also interviewed during November and December in Bozen (Italy).

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Table 1 Data used to map the roads and paths for the different time steps.

Year Scale Dataset Data source

1860 1:25,000 Francisco-Josephinian Cartographical Register (third cartographical register of the Austrian Austro-Hungarian Monarchy crownlands) 1914 1:200,000 Map sheet “Innsbruck”, Festungsgeneralstabsreise 1914 (fourth cartographical register of the Austro-Hungarian Monarchy Austrian crownlands) 1950 1:25,000 Map sheet “Hochstubei” (year 1937), map sheet “Gurgl” (year 1949), map sheet “Weißkugel- Austrian and German Alpine Club Wildspitze” (year 1951) 1970 1:50,000 Map sheets 172 (year 1965), 173 (year 1970) and 174 (year 1967) BEV (Bundesamt für Eich- und Vermessungswesen Verlag) 2017 1:25,000 Map sheets 30/1 (year 2008), 30/2 (year 2013) 31/1 (year 2011) and 30/5 (year 2013) Austrian Alpine Club

Except for the winter tourists, which were interviewed in the city thematic resolution for three distance zones (near zone 0–1.5 km, centre, the interviews took place in the four study areas at frequented middle zone 1.5–10 km, far zone 10–50 km; Table 3). These distance places like mountain huts, parking areas, along hiking routes and in the zones were delimitated accounting for the high variability of landscape villages. The respondents were chosen randomly and included local pattern and relief properties of the Central Alps (Schirpke, Hölzler, people as well as tourists. et al., 2013). In a first step, the visible area from an observer point was Overall, 967 people filled out the questionnaire. The evaluation derived from a digital surface model (DSM) using ArcGIS 10.4 (ESRI, results for each picture are presented in Table 2. Redlands, CA, USA) for each distance zone. The DSM was derived from a digital elevation model (DEM), which was modified accounting for 2.3.2. Landscape characteristics and regression analysis the height of forest and buildings. The visible area for each distance The obtained result from the perception survey represents the aes- zone was then overlaid with the land cover, using different datasets for thetic value of the landscape perceived from a specific observer point in each zone. From the three resulting maps, a single map was built with a a 360° view. The regression model from Schirpke et al. (2016) can be spatial resolution of 30 × 30 m and a maximum number of 30 different applied to estimate the aesthetic value for any observer point in the land cover types (e.g. forest, grassland, settlement, rock, water and Central Alps. We therefore applied always the same model in our study glacier) resulting from the mapping of habitats and land cover types in area for five time steps (1860, 1915, 1950, 1970 and 2017), ashuman the Ötztal Valley (Table 3). Based on this map, landscape metrics were preferences could not be gathered for the past. To calculate the aes- calculated using FRAGSTATS version 4.2.1. (McGarigal, Cushman, thetic value, we needed to place observer points along all roads and Neel, & Ene, 2002) to quantify landscape patterns. Additionally, the paths. We chose a distance of 200 m between the observer points to presence or absence of specific landscape features (settlements, roads, account for the high variability of aesthetic values among different forest, water) was recorded for each map. Finally, the aesthetic value locations on the one hand and stay in a feasible computing time on the was estimated applying the regression model from Schirpke et al. other hand. This resulted in 10,536 observer points for all time steps (2016). Further details on the methodology can be found in Schirpke, (ranging from 690 observer points for 1860 to 3,599 for 2017). Land- Tasser, et al. (2013), Schirpke et al. (2016). scape characteristics were calculated for each observer point as input for the regression model. As distance influences the perceived size, 2.3.3. Analysis of changes in aesthetic values shape and colour of landscape features, resulting in less distinguishable To relate the changes in accessibility and landscape pattern to detail (Bishop, 2003; Germino, Reiners, Blasko, McLeod, & Bastian, aesthetic values, we calculated mean aesthetic values for each time 2001), the modelling approach used input data with diverse spatial and step. These mean values represent the actual supply of aesthetic values

Fig. 3. Conceptual scheme of the spatially explicit modelling approach for estimating aesthetic values in mountain areas for a specific observer point (adapted from Schirpke et al., 2016). The approach relates biophysical characteristics of the visible landscape from a specific observer point (1) with human preferences froma photo-based survey for the same location (2) via regression analysis.

27 U. Schirpke, et al. Landscape and Urban Planning 187 (2019) 23–35

Fig. 4. Pictures of the questionnaire from Schirpke et al. (2016).

Table 2 originated through the interactions of site conditions (biotic, abiotic), Sample size (N), mean, standard deviation (SD) in the evaluation of the pictures agricultural and silvicultural use as well as settlement and infra- of the questionnaire (modified from Schirpke et al., 2016). structure development. They were defined based on the Francisco- Picture N Mean SD Main landscape features in the foreground Francisco-Josephinian Cartographical Register because at this time, the maximum expansion of agricultural land use and the minimal extension 1 964 6.94 2.29 alpine pastures, lake of forest areas in the Alpine region occurred (see Mather, Fairbairn, & 2 963 6.87 2.28 timberline zone Needle, 1999). In this study, we distinguished a total of seven different 3 963 7.53 2.15 alpine pastures, single trees 4 960 7.15 2.18 meadows with hedges ecoregions (Fig. 1), and for each, we recorded and evaluated changes 5 958 4.59 2.36 orchard plantation separately by overlaying the ecoregions with the roads, paths and 6 960 8.09 1.84 mixture of subalpine forest and grassland aesthetic values. Furthermore, we assessed the land cover distribution 7 960 4.29 2.28 village for each ecoregion to analyse landscape dynamics. 8 962 7.03 2.09 alpine pastures 9 962 5.76 2.64 alluvial forest 10 961 7.5 1.99 alpine pastures 2.4. Analysing visitation preferences in relationship to aesthetic values 11 963 6.27 2.25 alpine hut, forest and forest road 12 964 7.66 1.92 alpine meadows, single trees 13 963 4.74 2.22 intensively used meadows, houses, street Crowd-sourced information from social media can be considered as 14 964 8.26 1.78 steep meadows, rocks, trees, lake a measure for landscape appreciation (Langemeyer et al., 2018; Sonter 15 960 6.43 2.24 intensively used meadows, single trees et al., 2016; Tieskens et al., 2018), indicating differences in visiting 16 964 6.84 2.42 scree slopes, rocks preferences (Tenerelli et al., 2016; van Zanten et al., 2016). Especially 17 962 6.62 2.08 forest, forest road in mountain areas, most pictures of the online photo-sharing website 18 959 7.39 1.96 alpine pastures, meadows, trees 19 958 6.41 2.45 river, gravel bars, rocks, forest Flickr are associated with CES (Oteros-Rozas, Martín-López, Fagerholm, 20 960 7.09 2.13 alpine grassland, dwarf shrubs, young trees Bieling, & Plieninger, 2017; Schirpke et al., 2018). To identify places 21 962 6.94 2.11 timberline zone, alpine pasture from where pictures were frequently taken, we used metadata linked to 22 959 4.47 2.15 street, forest, village, grassland photographs of the Flickr database, which we downloaded via the 23 962 6.06 2.33 dense spruce forest Flickr’s public Application Programming Interface (API). Of all geo- 24 963 6.29 2.36 spruce forest, underground grassland tagged public photographs that were located within the boundaries of the study area with the highest accuracy level (street level) and up- for each time step for the entire study site, allowing the authors to loaded until June 2017, we stored longitude, latitude, date, identifi- analyse changes over the last 150 years from a toady’s perspective, i.e. cation number, the photographer's identification number and the image based on current perceptions. Mean values were calculated distin- URL. All data were imported into a spatial database in ArcGIS and fil- guishing between road types as well as ecoregions and Dunnett-T3 post- tered for pictures that were taken only between May and September to hoc test was applied to identify significant differences. As landscape exclude winter pictures. The final number of photographs used for changes do not take place at the same rate everywhere within the analysis was 3,321 uploaded by 221 different users. Most pictures mountains, we subdivided the study area into ecoregions, as proposed (83%) were taken in July and August. To evaluate the differences in by Tasser et al. (2009). Ecoregions are landscape units that have visitation preference along roads and paths, we mapped the photo density for each observer point used to estimate the aesthetic value by

28 U. Schirpke, et al. Landscape and Urban Planning 187 (2019) 23–35

counting the number of pictures taken within 300 m from the observer point. The resulting map was rescaled to values from 0 to 100 for further analysis. Mean values were calculated for the different road types as well as ecoregions and compared to aesthetic values by correlation analysis to analyse whether the photo density was related to aesthetic value. Furthermore, hotspots of photo densities were examined by visual photo analysis and by overlaying further spatial data such as mountain huts and alpine passes.

3. Results

3.1. Development of the roads and paths Shuttle Radar Topography Mission (SRTM) ( Jarvis, Reuter, Nelson, & Guevara,European 2008 ) Environment Agency (2016) Shuttle Radar Topography Mission (SRTM) ( Jarvis et al., 2008 ) European Environment Agency (2016) Data source Tyrolean Information System (tiris, ©Land Tirol) Own mapping Own mapping ( Tasser et al., 2009 ) The total length of the roads and paths significantly increased from 138 km in 1860 to 720 km in 2017 (Figs. 5 and 6). Before 1950, paths and some roads were mainly located at the bottom of valleys connecting settlements as well as providing access to alpine pastures or neigh- bouring valleys. A dramatic increase in road length can be observed for 1950, when the first roads were asphalted in the valley bottom and numerous new paths at higher elevations appeared, often connecting mountain huts with the settlements. More asphalt roads were con- structed mainly between 1950 and 1970, e.g. the pass road ‘Timmels- joch’ and the high alpine road ‘Ötztaler Gletscherstraße’. The length of non-asphalt roads increased especially after 1970 with the construction of new forestry and agricultural roads. This enlargement or asphalting of former paths has resulted in a shift of the roads and paths from lower to higher elevations. The road length in the valley bottom increased by only 20% from 1860 to 2017, with the largest increase at higher elevations, in particular within the agriculturally used alpine pastures, which account for 48% of all roads and paths. The first hiking trails Schirpke, Tasser, et al., 2013, Schirpke et al., 2016 ). were declared in 1915, and their length increased sharply until 2017. A Digital elevation model (DEM) CORINE Land Cover (CLC) 2012,into version six 18.5.1. classes: Aggregated forest, grassland,glacier settlement, rock, water and CORINE Land Cover (CLC) 2012,into five version classes: 18.5.1. forest, Aggregated grassland, settlement, water and glacier Roads and paths for theHabitat maps five with time max. steps 24 habitatthe types five in time the steps Ötztal Valley for major part of the hiking trails (100% in 1915 and 85% in 2017) were located on paths, smaller parts also on non-asphalt and asphalt roads.

3.2. Effects of accessibility and land-cover change on aesthetic values 1 × 1 km 100 × 100 m Digital elevation model (DEM) Spatial resolution Dataset Mean aesthetic values along roads and paths generally increased significantly until 1950 and decreased afterwards (Figs. 5 and 6, Table S1 in the supplementary material). Although remaining at a similar level after 1950, aesthetic values of paths were higher than those of asphalt and non-asphalt roads. For non-asphalt roads, the decrease of aesthetic values occurred only after 1970, while asphalt roads had a constant increase in aesthetic values. Generally, aesthetic values were higher with increasing elevation but lowest in the forest belt, located between the agriculturally used valley bottom and the alpine pastures. As hiking trails matched mostly paths at higher elevations, they represented the highest level of aesthetic values. These changes in aesthetic values occurred in different locations: new paths to mountain peaks or connections between mountain huts provided access to areas with a high aesthetic value (pink to blue colours), resulting in an overall increase in the supply of aesthetic values until 1950; a decline of aesthetic values occurred after 1915, mainly within settlement areas (change from orange to yellow colour). A more differentiated picture shows the results of the analysis of aesthetic values in relationship to the land cover changes within each ecoregion (Fig. 7, Table S2 in the supplementary material). In the agriculturally used valley bottom, the aesthetic value decreased by al- and outline of the landformspace still play a major role for the perception of a village Effects of distance on visual characteristics most 17% from 1860 to 2017, while the area covered by settlements increased especially after 1970, and arable land was mainly replaced by managed grassland and settlements after 1915. Similarly, the aesthetic value decreased by 14% in agriculturally used valley slopes, whereas forest and settlements increased in particular after 1970. Compared to the other ecoregions, the montane forest belt had the lowest aesthetic value, with a negative trend (4%) between 1860 and 2017. In the subalpine forest belt, the aesthetic value peaked in 1915 and decreased Far zone: 10–50 km The number of perceivable land-cover classes decreases, whereas edge Near zone: 0–1.5 km Details of single features such as trees or buildings are clearlyMiddle identifiable zone: 1.5–10 km 30 × Single elements merge, e.g. single trees form a forest or buildings make up 30 m Digital elevation model (DEM) Distance zone

Table 3 Effects of distance on visual characteristics, input data and data sources for the three distance zones (adapted from afterwards by almost 9% with the increase of forest and the decline of

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Fig. 5. Development of a) road length and b) aesthetic values for different road types. Changes in c) road length and d) aesthetic values of ecoregions. grassland. In agriculturally used alpine pastures, it increased slightly ecoregion level, photo density was positively related to aesthetic values until 1950 and declined afterwards by 3%. In 1950, managed grassland (R2 = 0.834 for all roads; R2 = 0.806 for hiking trails). was largely abandoned, resulting in a shift to forest. A similar trend for changes in the aesthetic value occurred in natural alpine grassland, but aesthetic values were generally at higher level as in natural alpine 4. Discussion grassland. While managed grassland almost disappeared in 1950 and the area covered by glaciers continuously decreased, the area covered 4.1. Effects of accessibility and land use changes on aesthetic values by natural grassland and shrubs increased. The nival belt had the highest aesthetic value compared to all other ecoregions, and the level While CES have been assessed mostly for recent times (Cooper, remained high throughout the entire period. In 1860, the road length Brady, Steen, & Bryce, 2016; Junge et al., 2015; Tieskens et al., 2018; was too short to calculate a representative value, and land cover van Zanten et al., 2016), this study examined changes in the actual changes mainly referred to the replacement of glaciers (−53%) with supply of aesthetic values from the perspective of today in relationship little or no vegetation. to accessibility and land cover changes. Our results indicate that the supply of aesthetic values is strongly influenced by accessibility, landscape changes and human perceptions. The improvement of road and 3.3. Relationship between aesthetic values and visitation preferences path infrastructures over time together with a growing motorization of people contributed significantly to the socio-economic development Photo density along roads and paths varied considerably (Fig. 8a). and with some delay to a changed use of landscape (Portnov et al., Hotspots of photo density were mainly located in proximity to moun- 2011), which is reflected in our results with a general increase inaes- tain huts, mountain peaks, alpine passes or places with particular at- thetic values until 1950. This increase can be explained by the expan- tractions (e.g. spectacular suspension bridges). Mean photo density at sion of roads and paths, while land use and landscape patterns only the level of ecoregions was very high for alpine grassland (ecoregions 5 slightly changed. Especially areas at higher elevations, such as alpine and 6) and the nival belt, whereas fewer photos were taken in the pastures that are characterised by high aesthetic values, became more montane forest belt as well as in the valley bottom (Fig. 8b). At the accessible. Accordingly, new paths were mostly built at higher

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(Meleghy et al., 1982). Travel time is a decisive factor for accessibility (Ala-Hulkko et al., 2016; McKercher et al., 2008); accordingly, roads connecting settlements were asphalted and new scenic roads were built in our study site. Moreover, paths often were transformed into roads to provide access with machineries for forestry and agriculture (Allan, 1986). The increase in visitors to Sölden was parallel to the increase in accessibility: whereas in 1856 only 20 overnight stays were counted, in 1875 already 5000, in the 1930s around 30,000 and today more than 2,500,000 overnight stays per year were listed (Meixner & Siegl, 2010). Although the construction of new roads and paths continued after 1950 until 2017, further increasing the accessibility to areas of high aesthetic values, the decline of agriculture and the related land use changes led to altered landscape patterns and affected aesthetic values. The general decrease in aesthetic values in the valley bottom can be explained by a higher amount of settlements and infrastructure in recent times, with negative impacts on aesthetic values (Grêt-Regamey et al., 2007; Schirpke, Hölzler, et al., 2013). Furthermore, the densifi- cation of the formerly open forests also has a negative impact on aesthetic values (Zoderer, Tasser, et al., 2016). The abandonment of pastures and the subsequent reforestation processes negatively affect aesthetic values at higher elevations (Schirpke et al., 2016). Due to the high elevation of our study area and the persistence of agricultural activities, these landscape changes are still at a moderate level compared to other regions in the Alps or other mountain ranges (Egarter Vigl et al., 2016; Price et al., 2017), where large areas of abandoned pastures are already forest or will be converted into forest in the near future (Navarro & Pereira, 2012; Price et al., 2017). This suggests that tourism may rather have positive effects on the maintenance of the agriculturally used landscape and traditional extensive land-use systems, which help to preserve high landscape and biodiversity values that are appreciated by tourists (Cocca et al., 2012).

4.2. Current trends and management implications

Against the background of the recent landscape changes and a ra- pidly changing climate, the supply of aesthetic values will be affected in the future even more severely due to the increase in forest and the decline of glaciers as attractive landscape features (Lieskovský et al., 2017). Additionally, the accessibility to landscapes of high aesthetic values may decrease as a result of increasing temperatures mainly due to two factors. Firstly, the frequency and intensity of natural hazards are expected to increase, especially in permafrost areas (Stoffel et al., 2014), which also increases the probability that especially casual mountain tourists may less frequently use the affected hiking trails (Pröbstl-Haider et al., 2016). Secondly, it will be more difficult and expensive to maintain hiking trails from alpine pastures to mountain tops (Braun, 2008). Consequently, the length of hiking trails is likely to decrease in the future, and the reduced access to areas of high aesthetic values will also reduce the aesthetic experience. Considering these recent and future developments, which may lead to a concentration of visitors in the agriculturally used alpine pastures (ecoregion 5), it is important to counteract the abandonment of alpine grassland by supporting agricultural activities in these areas to main- Fig. 6. Changes in roads and paths as well as in aesthetic values from 1860 to tain high aesthetic values as well as other ecosystem services (Briner 2017. et al., 2013; Schirpke et al., 2016, 2017). The comparison between estimated aesthetic values and photo density suggested that ecoregions elevations as hiking trails, while paths at lower elevations, formerly at higher elevations, in particular the agriculturally used alpine pas- used for agricultural purposes, were increasingly used as hiking trails. tures with mountain huts and the nival belt with mountain peaks, are These results coincide with the findings of other studies that emphasise preferred over the valley bottom and the forest belt (see Tenerelli et al., the importance of accessibility, allowing people to benefit from CES 2016; van Zanten et al., 2016). In addition to natural assets, the spatial (Baró et al., 2017; Langemeyer et al., 2018; Schirpke et al., 2018). In pattern of photo density suggests that mountain huts are important for fact, the Ötztal valley was difficult to reach in the past; in 1848, the touristic use as they provide access, shelter and catering. This implies Arlberg railway and the Ötztal railway station at the beginning of the that high aesthetic values only are not sufficient to attract visitors, but valley were built, which simplified the journey (Meixner & Siegl, 2010). that mountain regions need to focus on accessibility and tourism in- The railway, however, did not reach Sölden and people had to use an frastructure at higher elevations if they intend to enhance aesthetic uneven path until 1936, when Sölden could first reached by car experiences.

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(1) 100% 10 (2) 100% 10

80% 9 80% 9 value 60% 8 value 60% 8 distributio n distributio n 40% 7 40% 7 Aesthetic Aesthetic 20% 6 20% 6 Land cover Land cover 0% 5 0% 5 1860 1915 1950 1970 2017 1860 1915 1950 1970 2017 Year Year

(3) 100% 10 (4) 100% 10

80% 9 80% 9 value 60% 8 value 60% 8 distributio n distributio n 40% 7 40% 7 Aesthetic Aesthetic 20% 6 20% 6 Land cover Land cover 0% 5 0% 5 1860 1915 1950 1970 2017 1860 1915 1950 1970 2017 Year Year

(5) 100% 10 (6) 100% 10

80% 9 80% 9

60% 8 value 60% 8 value distributio n distributio n 40% 7 40% 7 Aesthetic Aesthetic 20% 6 20% 6 Land cover Land cover 0% 5 0% 5 1860 1915 1950 1970 2017 1860 1915 1950 1970 2017 Year Year

(7) 100% 10

80% 9

60% 8 value distributio n 40% 7 Aesthetic 20% 6 Land cover 0% 5 1860 1915 1950 1970 2017 Year

Fig. 7. Landscape changes and mean aesthetic values for each ecoregion: (1) agriculturally used valley bottom, (2) agriculturally used valley slopes, (3) montane forest belt, (4) subalpine forest belt, (5) agriculturally used alpine pastures, (6) natural alpine grassland and (7) nival belt.

The maintenance of aesthetic values is particularly important con- of recreational activities may be reduced if places are too crowded, with sidering the increasing demand for CES (Guo et al., 2010), and recent increasing conflicts between different user groups such as cyclists and numbers indicate the high importance of summer tourism not only in hikers (Koemle & Morawetz, 2016; Scolozzi et al., 2015). Moreover, the study area, but in the entire Alpine region (Alpine Convention, increasing visitor numbers cause higher disturbances of wild animals 2013). However, the high number of visitors may have negative effects and the degradation of vegetation and soil (Pęksa & Ciach, 2015; on aesthetic values along hiking trails due to increased soil erosion, Pickering & Hill, 2007). In particular, the increased accessibility col- muddiness, vegetation damage, litter and fire rings (Beza, 2010; Lynn & lides with the habitat needs of large wild animals (Peters et al., 2015). Brown, 2003) as well as an increase in large and well-prepared roads Hence, a tailored visitor management may be required, offering easy that are highly used for recreational activities but less appreciated vi- access to specific areas of high aesthetic values, for example, through sually than more natural trails (Gundersen & Vistad, 2016). Higher viewing platforms (Migoń & Pijet-Migoń, 2017), and providing separate visitation rates may also influence other CES; for example, the quality trails for cyclists and hikers (Koemle & Morawetz, 2016). In this way,

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a) b) 0.10 10.0 0.08 8.0 ndex) ndex) ndex) ndex) (i (i 0.06 6.0 0.04 4.0 density 0.02 2.0 Photo

0.00 0.0 value Aesthetic (1) (2) (3) (4) (5) (6) (7)

Photo density Photo density - hiking trails Aesthetic value Aesthetic value - hiking trails

Fig. 8. a) Mean density of photos taken between June and September, derived from the Flickr database along roads and paths in 2017; b) mean index values for the ecoregions in comparison to aesthetic values (location of ecoregions, see Fig. 2; (1) agriculturally used valley bottom, (2) agriculturally used valley slopes, (3) montane forest belt, (4) subalpine forest belt, (5) agriculturally used alpine pastures, (6) natural alpine grassland and (7) nival belt). people can more easily benefit from CES, and conflicts between bene- The mapping and classification of the roads and paths before 1950 ficiaries and biodiversity may be largely avoided (Marion, 2016). was difficult due to the limited information content of the available maps. Although the maps were revised with local experts, some uncertainties are related to the precise location of the roads and in terms 4.3. Methodological issues of road type, in particular for 1860. Nevertheless, our analyses ade- quately capture the overall trend of aesthetic values as we used a high The used modelling approach is suitable to assess changes in aes- number of observer points and summarised our results at the ecoregion thetic values as it can be applied at any location and time, but some level. limitations and uncertainties need to be considered. Crowd-sourced information demonstrates great potential to reveal We used the results of the questionnaire from Schirpke et al. (2016), differences in the aesthetic appreciation of the landscape (Langemeyer which concentrated on the cultural landscape at generally lower ele- et al., 2018; Sonter et al., 2016; Tieskens et al., 2018). Nevertheless, vations, whereas the influence of large glaciers on aesthetic values was several limitations are related to their representativeness (Oteros-Rozas not specifically analysed. Glaciers as natural landscape elements and et al., 2017; Schirpke et al., 2018; Tenerelli et al., 2016; Wood, Guerry, highly appreciated features (Lieskovský et al., 2017). This may have led Silver, & Lacayo, 2013). People sharing their photographs via social to lower aesthetic values in this study area, where still 15% of the total media are often characterised by a frequent use of digital technologies, area were covered by glaciers in 2017. Furthermore, the pictures of the higher income, higher level of education and are living in urban en- questionnaire did not include lifts and ski slopes, but infrastructure has vironments; therefore, they may not represent the population as a rather negative impacts on perceived aesthetic values (Grêt-Regamey whole (Li, Goodchild, & Xu, 2013; Liao et al., 2018). Furthermore, the et al., 2007). Further research is therefore needed to account for the type of activity may determine whether people take photos and where influences of all landscape features on human preferences. Further- (Wood et al., 2013). Indeed, the hotspots of pictures in our study often more, although the predictive power of the regression model was very correspond to resting areas such as huts or mountain peaks rather than high, the relationships between aesthetic values and landscape char- to hiking trails. These problems might be reduced if the Flickr data can acteristics cannot necessarily be assumed as linear (Schirpke et al., be combined with different crowd-sourced information (Hausmann 2019), and the used predictive model may not correctly estimate all et al., 2018). variations. This study used information on landscape preferences representing today’s perceptions for estimating aesthetic values in the past. 5. Conclusions However, even though the stated preferences between age groups dif- fered only slightly from each other (Schirpke et al., 2016, 2019), the Analysing the actual supply of aesthetic value confirmed the im- perceptions of people more than a century ago may be different from portance of accessibility to benefit from CES. Especially the large in- those today (e.g. Drexler, 2013; Turner, 2006). In particular, differences crease in paths at high elevations can be linked to an increase of aes- in preferences may be related to the type of interaction with the thetic values and can be actively steered by decision makers and landscape (e.g. agricultural or recreational use) or to peoples' en- landscape planners. The change from agricultural to touristic use, vironmental value orientation (Kaltenborn & Bjerke, 2002; Natori & however, has considerable effects on aesthetic values, and land use Chenoweth, 2008), which are likely to be different for people in 1850 policies should support agricultural activities in mountain areas to or 1950 and today. Similarly, it seems that increasing knowledge, for maintain the attractiveness of the landscape at high levels. As similar example, on the ecological value of the landscape, may lead to different developments occur in many regions in the European Alps as well as in perceptions and aesthetic experiences (Gobster, Nassauer, Daniel, & other mountain regions all over the world, our results provide a valu- Fry, 2007). Thus, as agricultural use was prevalent before 1950 and able information basis allowing to enhance aesthetic experiences and conservation values may have been less important, our results may not indicating the implications of increasing tourism and declining agri- be fully representative for historical dates. Nevertheless, we deemed the cultural activities. use of the same perceptions over time as suitable to evaluate the in- Spatial assessment of CES needs to relate landscape properties with fluence of changes in accessibility and landscape pattern on the actual human perceptions, and our modelling approach supports the estima- supply of aesthetic values as an ecosystem service. tion of aesthetic values at any location to identify changes over time.

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