Mountain forests and climate change-induced forest dieback

Mountain forests are very important for nature and humans, because they provide a wide range of ecosystem services. They not only regulate climate, e.g., due to carbon storage (Seidl et al. 2014), and provide a habitat for flora and fauna as well as a home and recreational space for humans (Richins 2016; Korner 2019), but they also protect against erosion, floods and avalanches (Schirpke et al. 2019). Moreover, mountain forests produce resources like timber, non-wood forest products (Langner et al. 2017) as well as drinking and irrigation water (Seidl et al. 2019). About 23% of the global lowland population is predicted to depend decisively on runoff contributions from mountains by the mid-twenty-first century (Viviroli et al. 2020).

However, forest ecosystems are strongly sensitive to climatic conditions, and they are thus distinctly affected by climate change (Turner et al. 2003; Seidl et al. 2011; Yousefpour and Hanewinkel 2016; Laurent et al. 2020). As the period from 2015 to 2019 is the warmest five-year period ever recorded (WMO 2019), it is unsurprising that climate change already affects mountain forests through a shift of growing seasons (IPCC 2020), vegetation boundaries (Hartl-Meier et al. 2014), and tree species composition (Köhl et al. 2017). Mountain forests also face an increasing risk of climate-induced dieback. Forest dieback—defined as tree mortality above usual levels—is documented on a global (Allen 2009; Senf et al. 2018; George et al. 2022) and local scale, as in the case of small mountainous areas in Central Europe (Bałazy et al. 2019).

For forests in the German federal state of Bavaria, forest experts list climate change as the most important influencing factor from a mid- and long-term perspective (Sacher and Mayer 2019). Especially in the Bavarian Forest and the German Alps in the southeast/south of Germany, the summers of 2018 and 2019 were characterized by heat and drought (Meinert et al. 2019). Forest fires were even reported in the usually humid German Alps (Süddeutsche Zeitung 2018). Vegetation and soils were directly affected by—for example—drought in the summer 2015 (StMELF 2017) and storm events in August 2017 (Klemmt et al. 2018). Additionally, bark beetle infestations affect large areas (Müller et al. 2008; Seidl et al. 2014; Thorn et al. 2017). Since ecosystem services of mountain forests are affected by climate change and resulting forest dieback, adaptation measures are essential. Adaptation—as defined by Moser (2010, p. 466)—involves “various responses by or interventions in a system, varying along a spectrum of relatively superficial adjustments to deep systemic changes, that allow a system to avert or minimize the negative consequences of a perturbation or take advantage of beneficial ones arising from it.” Adaptation measures in forestry can reduce the vulnerability of forests and strengthen resilience and resistance for example by changing forest composition and structures with short- and long-term actions (Bolte et al. 2009; Keenan 2015; Yousefpour et al. 2017). Especially, forests at a high climate risk like spruce monocultures need to be adapted (Ammer 2009; Ruhm 2017). However, such adaptation measures are usually only realized if actors perceive these problems, are aware of their relevance and have the necessary resources (knowledge, power, networks, money) (Deuffic et al. 2020).

The role of public perception for climate change adaptation in a forest context

Choosing adequate climate change adaptation strategies and implementing the required measures accordingly requires incorporating public perceptions within a forest context. The literature includes the following reasons: First, Akerlof et al. (2013) note that public perceptions of local risks from global warming are increasingly important as communities face decisions about how to adapt most effectively to emerging changes. Therefore, Capstick et al. (2015) urge research attention to examine prospective trends and patterns in public perceptions across multiple regions. Second, climate change perceptions (e.g., Van der Linden 2015) have an influence on climate policies and are important to generate support for adaptation as well as mitigation initiatives (Lujala et al. 2015). In many cases, the ways in which societies, individuals and decision-makers respond to climate change relies on public perceptions about its causes, consequences and wider implications (Pidgeon and Fischhoff 2011; Lujala et al. 2015; Ruiz et al. 2020; Guo et al. 2021; Wang et al. 2022).

As forest dieback is one of the consequences of climate change posing a serious risk to forests as well as for the provision of ecosystem services (Allen 2009; Lindner et al. 2010), social science research about understanding the perceptions of climate change and related forest dieback in mountain areas is much needed. There are numerous reasons for decision-makers and researchers of all disciplines to take the population’s perception of climate change and related forest dieback into account, such as developing effective and socially fair climate protection and adaptation measures (Grothmann et al. 2011; Sacher et al. 2017) or advancing the understanding of social-ecological climate change impacts (Morris et al. 2017). A high ratio of private forest owners with small-sized forest parcels in the Bavarian Forest and the German Alps makes it increasingly important to investigate climate change and forest dieback perceptions, because these private forest owners need to be involved in determining adaptation measures, and understanding expected impacts on local finances, landscape aesthetics, and identity. Moreover, residents are active users of forest ecosystem services and need to participate in the process of finding suitable adaptation measures because—for instance—climate change adaptation measures in their preferred forests might influence their recreational ecosystem services (Sacher et al. 2022). As residents are often deeply attached to “their” forests (e.g., Müller 2011), perceivable forest dieback caused by climate change could be interpreted by them as a concrete warning signal in the wake of the aggravating climate crisis (Deuffic et al. 2020; Brahic et al. 2022). In turn, this could increase people’s support for the necessary, stricter climate protection measures as their direct environment is also affected by climate change impacts (Rudman et al. 2013). In addition, taxpayers must bear the costs of adaptation measures in case of public forests and support potential subsidies for private forest owners to incentivize them to adapt their forests.

However, while there are many studies summarizing public and/or stakeholders’ perceptions of forest ecosystem services (e.g., European Commission 2009; Grilli et al. 2016; Ranacher et al. 2017), relatively few studies deal with mountain forests and ecosystem services (e.g., Rüdisser et al. 2019; Seidl et al. 2019). The public’s forest dieback perception has been studied through pest outbreaks (McFarlane et al. 2012; Urquhart et al. 2017), on a limited number of species such as Norway Spruce (Chang et al. 2009) and Ash (Fellenor et al. 2019) and after extreme weather events (Urquhart et al. 2017). For instance, in their qualitative study Deuffic et al. (2020) focused on forest owners and not on the population as a whole. In addition, while researchers postulate climate change as a possible trigger for forest dieback, it is still unclear how the public perceives the link between both phenomena (Brahic et al. 2022). Thus, the perception of forest dieback in mountain forests among the local population is seldom investigated so far, reflecting a major research gap. Frick et al. (2018) note that information is urgently needed about how forests are perceived by residents and what preferences and demands they express. This is relevant for the following reasons: First and foremost, local residents are a crucial stakeholder group in forest ecosystem service management (Agbenyega et al. 2009) as forests constitute a “central part of almost all residents’ everyday landscape” (Frick et al. 2018, p. 335) and as such are “highly valued by residents as part of their everyday living and recreational environment.” (ibid.). Second, local residents’ perceptions and attitudes about forests might differ significantly from those of forest owners, as Agbenyega et al. (2009) report regarding forest ecosystem services. These divergences could also lead to conflict. These questions are not only worth investigating to advise current policies but should also be monitored over time.

Of course, perception and awareness are not sufficient for adaptation measures. These notions need to be translated into concrete adaptation actions which also consider barriers to adaptation including lack of knowledge and information (Sousa-Silva et al. 2018; Hengst-Erhard 2019). Public support of adaptation measures is also decisive for making mountain forests resilient against climate change effects as studies have found evidence that public support is crucial for forest managers to implement adaptation measures. In general, public support is becoming increasingly significant for spatially relevant decisions and actions (Kemp et al. 2015; von Ruschkowski and Nienaber 2016; Peterson St-Laurent et al. 2018; Job et al. 2021).

Therefore, the aim of this contribution is to analyze local people’s perception of mountain forest dieback in relation to climate change and their preferences regarding adaptation strategies. We use a quantitative online survey based on a representative sample examining local residents’ forest dieback and climate change perceptions for the example of two mountain forest areas in Southern Germany, the German Alps and the Bavarian Forest. The two regions have similar proportions of forest areas, whereas the German Alps reach higher altitudes (2962 m asl at maximum), and the Bavarian Forest lower altitudes (1456 m asl at maximum). Both areas are affected by climate change-induced forest dieback.

We address the following research questions: (1) Do respondents perceive changes in the forests, e.g., forest dieback or other forest damages? (2) Are these changes perceived to be related to climate change, and how do respondents perceive climate change in general? (3) Which factors have an impact on the perception of forest dieback and climate change? (4) Which silvicultural adaptation strategies are favored by the public?

We underpin our results by using the theoretical model of van der Linden (2015), which was originally used in a climate risk perception context and is now tested for the first time in a forest dieback context while combining it with separate perceptional processes. Further, this model should serve to explain the complex perceptional processes behind the public’s preference for silvicultural adaptation measures, which has not been tested by other researchers so far. In this way, we try to close the identified research gap about forest dieback and climate change perceptions of local inhabitants in mountain areas in contrast to the much more prominently covered forest managers and owners.

Climate change risk perception model

The climate change risk perception model (CCRPM) of van der Linden (2015) serves as the theoretical foundation of this study to better understand the social-psychological determinants of risk perception in a forestry context.

The CCPRM (see Fig. 2 in section "Perception of forests and forest dieback") includes psychological influencing factors on the risk perception of climate change. The model describes four key dimensions: (1) cognitive, (2) experiential processing, (3) socio-cultural and (4) socio-demographic factors.

  1. 1.

    Cognitive factors refer to the subjective estimation of the probability that global warming is likely to happen and the severity of the associated consequences. Knowledge about climate change is generally seen as a cognitive aspect of risk judgments (Sundblad et al. 2007). In addition, analyses of public perceptions have indicated that climate change is perceived as being psychologically distant on temporal, social, geographical scales, and uncertainty dimensions (Spence et al. 2012). However, cognitive knowledge plays only one part in explaining perceptions and behavior, while other factors such as heuristics, emotions, social and cultural norms and context conditions in which knowledge arises or is situated are equally relevant in many cases (Helgeson et al. 2012).

  2. 2.

    Experiential processing could be described by emotions and affect as well as personal experiences. Emotional reactions to climate change have been recognized as playing a key role in public risk perception (Taylor et al. 2014). The media and news reporting has an immediate influence on climate change perception (Keller 2011). However, emotional reactions to climate change risks are likely to be conflicted and muted because climate change can be seen as being beyond the control of individuals, communities, and—quite possibly—science and technology. Strong negative emotions can have a counterproductive consequence on risk protection behavior because fear and anxiety lead to avoidant behaviors and defensive denial (Witte and Allen 2000), besides the fact that climate change is not perceptible and concern about climate change is mostly experience-driven (Grothmann and Patt 2005). The personal experience with natural hazards and personal damage caused by climate-related events is seen as a main factor explaining people’s climate change perception (Lujala et al. 2015; Frondel et al. 2017)—that means, direct (negative) experiences can increase risk perceptions.

  3. 3.

    Socio-cultural influences refer to the role of competing social and cultural structures in shaping individual risk perception (Jackson et al. 2006). According to the conceptual typology of risk culture and its “grid-group” system (van der Linden 2015), the relative position of the cultural types is determined by the extent to which individuals feel bounded by feelings of belonging and solidarity (group) and the amount of control and structure that maintain social roles (grid). However, while a few studies have found significant relationships between cultural worldviews and risk perception of climate change (Akerlof et al. 2013; Smith and Leiserowitz 2012), others have shown a low explanatory power (Oltedal et al. 2004). In addition, the political ideology plays a role within perception process (Leiserowitz 2006; Smith and Leiserowitz 2012). Conservatives have been found to be less concerned about climate change compared to liberals (Goldberg et al. 2020).

  4. 4.

    Socio-demographics: Some studies reveal that gender influences climate change risk perception (Menny et al. 2011; Poortinga et al. 2019). Males tend to have lower risk perceptions than females (Brody et al. 2007; Sundblad et al. 2007; Fulda and Hövermann 2020). Moreover, Echvarren et al. (2019) report that people with higher education levels have stronger concerns about climate change in European countries that are more vulnerable to floods and droughts. Furthermore, Blennow et al. (2016) demonstrate that the risk perception in terms of the strength of belief in the local effects of climate change is higher for Swedish and German forest owners with a university education compared with those without. While gender and education are able to shape risk perception, it is less clear if other factors like income and age influence climate change risk perception (Brody et al. 2007; Sundblad et al. 2007; Milfont 2012; Poortinga et al. 2019).

While Soucy et al. (2021) found the CCRPM model to be valid in a forestry context, we extended the model by a forest dieback risk perception variable to better adapt the model to the forest dieback and climate change discourse and the regional context. Climate change is a slow-onset hazard which is rather perceivable by its impacts like forest damages than by itself. However, lay people (Brahic et al. 2022) or forest stakeholders (Deuffic et al. 2020) may not always relate forest dieback to climate change or are uncertain about the causes of forest damages. Therefore, it may be insufficient to only test a climate change perception variable in this specific context. With the integration of a second perceptional variable, we see the potential to (1) better describe the determinants of both perceptional variables as well as to identify differences and to (2) test whether respondents perceive a link between climate change and forest dieback perception.

Material and methods

Study areas

Both study areas—the Bavarian Forest and the German Alps—are located in southern Germany (Fig. 1a, b). The German Alps are a relatively small part of the European Alps (3.5%) located along the southern German border to Austria with a West-to-East extension of 250 km and a north-to-south extension of only 20–35 km (Mayer and Job 2014; Fickert 2018). Nevertheless, with its highest mountain ranges of the Wetterstein (Zugspitze, 2962 m asl), the Allgäuer Alps, the Karwendelgebirge as well as the Berchtesgaden Alps, it reaches high alpine areas. The study area in the German Alps includes communities in the German Alps as well as in their flat foreland in the north. The Bavarian Forest is a densely forested low-mountain range (Großer Arber, 1456 m asl) located along the border between Germany and the Czech Republic in the southeast of Germany (Mayer 2013). This second study area is about half the size of the study area in the German Alps and their foreland and also includes some of the population centers at the river Danube (Table 1).

Fig. 1
figure 1

a, b Maps of the survey areas

Table 1 Comparison of the study areas

The Bavarian Forest is located in a transition region from the continental to the oceanic climatic zone with low temperatures and high precipitation at high altitudes (Burger 2003). The annual precipitation increases from West to East, with 650 mm at a minimum and 1850 mm at a maximum (Bässler 2008). The mean temperature is between 4 °C at high altitudes and 6 °C at low altitudes (Walentowski and Kopp 2006). The climate in the German Alps is characterized by low temperatures in winter and precipitation all year round within the cool-temperate zone (Bätzing 2015; Fickert 2018). The mean temperature is between 1 °C at high altitudes and 8.5 °C at low altitudes. The annual precipitation varies between 900 and 2500 mm (StMELF 2016).

The share of forest area reaches 47% in the Bavarian Forest (Destatis 2019) and 50% in the German Alps (StMELF 2016). The main tree species are spruce, beech and fir, whereby this co-occurrence is typical of mountain forests due to climatic conditions (LWF 2001; Ellenberg and Leuschner 2010). However, both mountain forest areas have a higher than natural share of spruce (at least 50%) due to anthropogenic influences. For instance, spruce was favored by forest management in the past due to its economic potential and relatively high growth rates. Moreover, climate change affects the growing conditions in both study areas through higher average temperatures and less average annual precipitation (Kölling et al. 2007; Hartl-Meier et al. 2014).

Both study areas are affected by climate-induced forest dieback, which is associated with a change in small-scale climatic conditions, an increase in the frequency of extreme events, and a shift in phenological phases (e.g., Kölling et al. 2007; Müller et al. 2008; StMUV 2015; StMELF 2017; Klemmt et al. 2018).

Regarding the socioeconomic structure both survey areas are regarded as rural areas according to the Federal Institute on Building, Urban Affairs and Spatial Development (BBSR 2018), with the exception of the district of Rosenheim in the German Alps. The districts of the Bavarian Forest survey area are even characterized as sparsely settled districts (except for Passau) as are five of the districts in the German Alps. This corresponds to the well below average population densities (Table 1) compared to the German average of 237 inhabitants per km2 in 2018 (Statista 2023). The population development in the German Alps is overall positive (with exceptions of more peripheral municipalities), driven by attractive living conditions as well as commuting to the agglomeration of Munich and other perialpine cities. The economic structure is typical for post-modern service economies but with a still strong manufacturing sector and local tourism hotspots (Mayer and Job 2014, LfSta 2023a). As for the GDP per inhabitants the districts of the German Alps have a mean rank of 55.7 among the 96 Bavarian districts (own calculations based on LfStA 2023b), underlining the rural character. The demographic structure of the Bavarian Forest survey area is less positive, with higher shares of municipalities losing inhabitants, especially in the Inner Bavarian Forest (districts Freyung-Grafenau and Regen). The districts of the Bavarian Forest survey area reach a mean rank of 64.2 among the 96 Bavarian districts in terms of GDP/capita (own calculations based on LfStA 2023b) which indicates an overall less dynamic economic development and a less affluent population. Nevertheless, the economic structure of the Bavarian Forest has improved considerably since the Second World War, turning the former “poorhouse of the nation” into attractive rural areas with a broad mixture of industries (manufacturing, tourism) and commuting possibilities to employers like BMW. Due to its economic history, forestry, wood processing and wood-based industries still have a strong position in the mindset of the local population despite a much reduced economic relevance in the last decades (Mayer 2013; Garms 2021).

Survey design and measures of the model

To perform a quantitative analysis of residents’ forest dieback and climate change perception, we used a standardized questionnaire, which included questions about the general relation to mountain forests, environmental worldviews in general, perceptions and attitudes regarding climate change and forest damages in the mountain forests and questions about the preference of adaptation measures as well as socio-demographic characteristics. However, we focused on the analysis of perceptions. The questionnaire was ordered thematically. First, respondents were asked about forest-related topics, e.g., preferred activities and valued characteristics of a forest. Second, we asked them to name potential risks to forests (open question format) and, next, to rank potential threats to forests (among them climate change). In the questionnaire, respondents were not informed about climate change before. Thus, these questions assess the respondents’ problem awareness as well as if they identify the potential link between forest threats and climate change. Third, questions about climate change and adaptation to forest dieback and climate change were asked. In addition to single- and multiple-choice questions, five-point Likert-type scales and ranking tasks were used.

Table 2 describes measures for each construct of the CCRP model. The cognitive factor is measured by the respondents’ self-assessed degree of knowledge concerning climate change and forest dieback. The variable experiential processing is identified by asking the respondents if they were already personally affected by climate change. The socio-cultural factor is summarized by environmental worldviews and the respondents’ deadwood attitude. The scale of Farjon et al. (2016) takes into account the normative dimension or values of nature and was originally used to identify the European citizens’ support for nature policies. The authors distinguish three dominant environmental worldviews (ecocentric, anthropocentric and holistic) which are based on a set of six propositions (see Table 2). For instance, respondents grouped into the ecocentric worldview appreciate the intrinsic value of nature and respondents grouped into the anthropocentric worldview agree with a utilitarian value of nature. Moreover, we integrated a deadwood attitude variable in our model as forest dieback is immediately combined with the occurrence of unusual high amounts of deadwood and past research indicate that deadwood attitude has an impact on the respondents’ forest perception (see, e.g., Sacher 2020; Sacher et al. 2022). The socio-demographic factor is described by the variables age, education, gender, income class, profession and professional relation to forestry.

Table 2 Measures and survey instruments for the CCRPM model

Data collection and analysis

A renowned market research company representatively recruited the respondents based on pre-set quotas (gender, age groups) from an online panel. The survey was presented online, and the pre-test was implemented in August 2018 with 54 participants. The full survey was launched between August and September 2018 and included 709 participants, comprising 305 residents of the study area Bavarian Forest and 404 residents of the study area German Alps. The latter can be differentiated again into 303 respondents of the Alpine municipalities and 101 respondents of the Alpine foreland. The data were weighted based on socio-demographic characteristics (gender, age and administrative district) and can be therefore regarded as representative for the survey areas. Due to very few statistically significant differences in the answers given in each study area, in the following both samples are analyzed together and existing differences between the regions are highlighted.

We analyzed the dataset with IBM SPSS Statistics 22, with the chosen level of significance of α = 0.05. In particular, comparisons of means (t test, ANOVA) between groups of respondents and tests of statistical relationships (chi-square test, Spearman’s correlation analysis) were used. In some cases, the respondents were asked to classify the four most relevant responses according to their personal assessment, from rank one as the most important to rank four as the least important. For further statistical analyses, these questions have been recoded (0 = not chosen, 4 = ranked 1, i.e., not important at all to 4 most important).

In addition, the environmental worldview was analyzed based on Farjon et al. (2016). A factor analysis (Table 5 in Appendix) resulted in an extraction of three components from six items (λ1 = 1.45; λ2 = 1.34; λ3 = 1.09) that explain 64.7% of the total variance. They imply an anthropocentric, holistic and ecocentric environmental worldview.

To evaluate the theoretical model, aggregated variables were calculated. The new variable perception of forest dieback is a construct of the questions concerning threats to forests and forest dieback impacts on the forests. The scale ranges from one reflecting “not at all impacted” to five denoting “extremely impacted.” A reliability check shows the internal consistency of the questions with a Cronbach’s alpha score of 0.67. The variable climate change perception was generated based on the questions concerning climate change consequences in the study area, current climate change impact on the forests and future impact of climate change on the forests. The scale ranges from one marking “not at all” to five representing “extremely.” A Cronbach’s alpha score of 0.79 illustrates the internal consistency of the questions. Spearman correlations (respectively, Cramer’s V tests for nominal-scaled variables) were used to analyze the relations between the components of the CCRP model, adaptations strategies and potential socio-demographic influences (see Fig. 2).

Fig. 2
figure 2

Source: Own draft based on van der Linden (2015)

Correlations between perceptions of forest dieback and climate change. Notes: Consistent lines show significant correlations; dashed lines mark nonsignificant results, likewise gray-shaded adaptation strategies; variables without lines do not meet the requirements for checking the correlations.

Finally, a cluster analysis was conducted to aggregate preferred mountain forest adaptation strategies. Therefore, the Ward method was applied on eight adaptation strategies. As a last step, we related the resulting clusters to climate change and forest dieback perception as well as to the environmental worldview clusters and socio-demographics.


Socio-demographic characteristics of the respondents

On average, the respondents are 51 years old. The weighted sample contains slightly more women than men (Table 6 in Appendix). Most respondents reached a secondary educational level (43.2%) had a professional qualification or a university degree (70.9%) and a monthly net household income of between 2000€ and 2499€ (16.0%). The largest group of respondents are retirees or pensioners (29.5%), followed by other officials, and employees (25.8%). Most respondents have no professional relation to forestry (96.5%) and do not own forests (91.9%), while 17.5% are members of an association (e.g., nature protection, hunting/fishing, forest owners).

Perception of forests and forest dieback

Respondents of both study areas reported that they had visited forests at least once a month over the past 12 months. On average, they were more frequently in the forests than once a month. Regarding the question of how informed the respondents feel about forests, 35.9% answered that they feel well to very well informed (Table 3). The most frequent answer (50.9%) was to feel moderately informed. Forest owners assess their knowledge level as significantly higher (mean 3.86; SD 0.59) than non-forest owners (mean 3.19; SD 0.75; t-value 7.37***).

Table 3 Perception of forests and forest dieback (in percentages)

The most popular characteristic of the forests in both study areas is mixed forests (top-two box valuesFootnote 1 58.0%; mean 2.5, scale from 0 = not chosen to 4 = most popular; SD 1.5), followed by paths (40.5%; mean 1.9; SD 1.5) and richness of flora and fauna (41.5%; mean 1.9; SD 1.5). The least popular characteristic is deadwood (86.8% not chosen; mean 0.2; SD 0.7). Regarding the functions of the forests, the respondents had to choose four out of nine categories and sort them based on their subjectively perceived relevance (Table 3). The most frequent category ranked first is preserving the air and soil quality and water resources (50.2%; mean 2.3; SD 1.5), while the least frequent function is producing wood (80.6% not chosen; mean 0.4; SD 0.8). In the Bavarian Forest, being a cultural heritage (t-value = 3.3***), providing beautiful landscapes (t-value = 3.7***), producing wood (t-value = 2.1*) and being a recreational area (t-value = 4.7***) are more relevant. In the German Alps, the functions of preserving the air and soil quality and water resources (t-value = − 2.6**), mitigating global warming (t-value = − 3.0**) and protecting people from natural hazards (t-value = − 6.1***) are more relevant.

In an open question, we asked respondents about the three main risks for forests without having referred to climate change in any sentence of the questionnaire before. Among the multiple answers (n = 1201) 27.1% of the answers referred directly to climate change and its abiotical impacts (e.g., drought/heat, more storms, extreme weather events, forest fires) while 16.5% referred to bark beetle impacts (a biotic impact which could be triggered by climate change). However, a significant share of respondents (11.3%) also sees tourism (e.g., deforestation for ski slopes) and unsuitable behavior of recreationists as main forest risks—much more than, for instance, environmental/air pollution (9.4%) or monocultures (4.2%).

Asked with closed questions, the large majority of the respondents perceive abiotic (top-two box values 77.4%; mean 4.0; SD 0.9) as well as biotic changes (73.8%; mean 4.0; SD 0.9) and increasing forest dieback (60.2%; mean 3.6; SD 1.0) in the study areas since 1980 (Table 3). More than half of the respondents in both study areas think that the forests are endangered (54.1%; mean 3.5) and currently affected by forest damages (57.2%; mean 3.6). Pests, diseases and invasive species are mentioned as the main risks to the forests (41.2%; mean 1.92; SD 1.5). Climate change was listed as the second most important risk (37.4%; mean 1.76; SD 1.6). The most strongly manifested impacts of forest dieback at present are a disappearance of protected species (63.2%; mean 3.8; SD 1.1) and an increasing volume of deadwood (65.8%; mean 3.8; SD 0.9). A recession of forest economic activities due to increased forest dieback holds the least concern for the respondents (38.4%; mean 3.2; SD 1.1). The new aggregated variable perception of forest dieback shows that nearly two-thirds of the respondents perceive moderate to strong forest dieback (top-two box values 64.7%; mean 3.73; SD 0.76), while only three respondents (0.5%) do not perceive forest damages at all. There is no significant difference in perception of forest dieback between the Bavarian Forest (mean 3.72; SD 0.80) and the German Alps (mean 3.74; SD 0.75; t-value = − 0.27). Forest owners perceive forest dieback more strongly (mean 3.89; SD 0.8) than non-forest owners (mean 3.72; SD 0.8; t-value = 1.44). However, this tendency is not significant, which might be due to the small sample size of forest owners (n = 48).

The upper part of Fig. 2 shows the relationship between forest dieback perception and the dimensions of van der Linden’s (2015) CCPRM model. Regarding the cognitive dimension, the higher that respondents estimate their state of knowledge about both climate change and forests, the more they perceive forest dieback. Experiential processing plays an important role: the stronger participants themselves state being affected by climate change—i.e., having already individually experienced climate change—the more they perceive forest dieback. In terms of the socio-cultural dimension, the more ecocentric the respondents’ environmental worldview, the more they perceive forest damage, while the more that participants agree with anthropocentrism, the less they perceive forest damage. If the respondents see deadwood as a source of danger for forest visitors and as ecologically important, they perceive forest dieback more strongly. The factors of the socio-demographic dimension are not significantly correlated with forest dieback perception. Finally, an approval of the adaptation strategy to plant spruce only on suitable stands positively correlates with the forest dieback perception.

Perception of climate change

The overwhelming majority of respondents (93.8%) think that climate change is real (Table 4). The level of information about climate change is rather high in the sample, as 40.6% answered that they feel rather well to very well informed. The most frequent answer (49.1%) was to feel moderately informed. However, by contrast, only a minority of the respondents (28.7%) have already been personally affected by climate change. More than 90% of this subgroup mentioned weather extremes as an example, while about half of the respondents mentioned heat and drought. Regarding personal experience with climate change, forest owners state that they were affected significantly more often by climate change than non-forest owners (χ2 (N = 590) = 8.790**; Phi = 0.136**).

Table 4 Perception of climate change (in percentages)

More than half of the respondents (top-two box value 52.0%) state that there are already consequences of climate change in the study area. This notion significantly correlates with the personal experience with climate change ((χ2 (N = 452) = 33.4***; Cramérs V = 0.271***).

In the study areas, especially drier summers (82.4%) and warmer winters (76.1%) were strongly recognized. More forest fires were least noticed, nevertheless reaching a 50.1% top-two box value. Focusing on the forests in the study areas, forest damages in mountain forests are not a new phenomenon and they were already perceived in the past in the Bavarian Forest as well as the German Alps (72.3%). This high level of consciousness notwithstanding, about one-quarter of the respondents (23.2%) state that forest damages have not occurred until today. In relation to climate change, 46% of the respondents think that the forests in the study areas in particular are currently affected by climate change, with an additional 36.5% opting for the answer category “medium” and only less than one-fifth (17.5%) denying climate change impacts on the forests.

The most strongly perceived climate change impacts on forests at present are damages caused by insects or pest outbreaks (69.6% top-two box values; mean 3.87; SD 0.98), an increase in tree mortality (57.1%; mean 3.55; SD 1.02) and forest landscape degradation (57.0%; mean 3.52; SD 1.02). Asked whether they think that forests in the survey area will be affected by climate change from now to 2050, 85.7% (strongly) agree, while only 3.3% reject this notion.

This is in line with the aggregated variable climate change perception, which shows that the respondents are quite aware of climate change (60.8%; mean 3.60; SD 0.71), with the largest shares for the answer categories of "quite" (55.0%) and "partly" (32.5%). Only one respondent does not perceive climate change at all. There are no significant differences in climate change perception between the Bavarian Forest (mean 3.55; SD 0.72) and the German Alps (mean 3.62; SD 0.70; t-value = − 1.047).

The lower part of Fig. 2 depicts the relationship between climate change perception and the dimensions of van der Linden’s (2015) CCPRM model: Similar to the forest dieback perception, both the cognitive dimension and the experiential processing are positively related to the climate change perception: the higher the state of knowledge about climate change and the stronger that participants individually perceive climate change, the stronger the aggregated climate change perception. Regarding the socio-cultural dimension, an ecocentric environmental worldview positively coincides with climate change perception, while by contrast an anthropocentric environmental worldview is negatively related. The socio-demographic dimension is not significantly correlated with climate change perception.

Finally, Fig. 2 also illustrates that there is a highly significant and medium to strong positive correlation between both aggregated constructs, climate change and forest dieback perception (rs = 0.600***). This means that the stronger the forest dieback perception, the stronger the perception of climate change, and vice versa.

Preferences regarding mountain forest adaptation strategies

According to the respondents, mixing several tree species in the same stand (selected by 84.4% of the respondents; mean 2.55; SD 1.45) and introducing new suitable native tree species (70.8%; mean 1.79; SD 1.47) are the most preferred adaptation strategies against forest dieback (Fig. 3). Having forests with trees of different ages reaches a mean of 1.62 (64.4%; SD 1.47). The least preferred strategies are salvage logging, i.e., removing damaged wood as fast as possible (37.0%; mean 0.88; SD 1.33), shortening rotation periods (27.0%; mean 0.60; SD 1.19) and introducing new non-native tree species (10.8%; mean 0.26; SD 0.84).

Fig. 3
figure 3

Ranking of adaptation strategies against forest dieback (based on frequency of mention). Note: N = 590; rank 1 = most important to rank 4 = least important; mean calculation: 0 = not important at all to 4 = most relevant

Planting spruces only on better-suited sites was ranked as less relevant by forest owners (mean 0.48; SD 0.92) than by non-forest owners (mean 0.81; SD 1.08; t-value = − 2.33*). Salvage logging was ranked by forest owners as more relevant (mean 1.62; SD 1.62) than by non-forest owners (mean 1.11; SD 1.45; t-value = 2.29*).

A cluster analysis of the respondents (Fig. 4) resulted in three quite different groups. Respondents grouped in cluster 1 (n = 261; 44.3% of the sample) prefer rather nature-oriented forestry including having the strongest preferences for mixed forests, cultivating native tree species, having forests with trees of different ages as well as spruce only on suitable stands. The fast removal of infested trees and salvage logging are least supported compared to the other clusters.

Fig. 4
figure 4

Cluster of respondents based on preferred forest adaptation strategies. Note: N = 590; rank 1 = most important to rank 4 = least important; mean calculation: 0 = not important at all to 4 = most relevant; * indicates that values are not significantly different at the p < 0.05 level according to Tamhane T2 post-hoc test

Members of the largest cluster 2 (n = 285; 48.4%) prefer a more traditional forestry including mixed forests as most preferred strategy, while the quick removal of infested trees is nearly as important, followed by salvage logging (“to clear cut as soon forests are dying”). Cultivating native tree species are only ranked fourth. The shortening of rotation periods has the highest level of agreement in this cluster. In contrast to cluster 1, members of this cluster agree significantly more with anthropocentric environmental worldview, while their climate change perception is lowest, marking a significant difference compared to cluster 3. Members of cluster 2 have a slightly lower educational and income level compared to clusters 1 and 3.

Cluster 3 is a rather small group (n = 43; 7.3%), whose members strongly prefer introducing new non-native tree species (e.g., Douglas fir) in contrast to clusters 1 and 2. For the strategies ranked second to fourth, cluster 3 members show similar preferences to cluster 2. Regarding the removal of infested trees, salvage logging and shortening of rotations, these strategies are least preferred similarly to cluster 1. Cluster 3 members have the highest climate change perception.

Regarding the forest dieback perception, no significant differences could be revealed between the clusters. Similarly, we found no differences between forest owners and the other respondents regarding cluster membership (but between members of forest owner associations and non-members), while the two survey areas show slight divergences (Cramer’s V 0.160, p < 0.001): Bavarian Forest inhabitants are overrepresented in clusters 2 and 3, while respondents from the German Alps are overrepresented in cluster 1.

Discussion and conclusion

We contribute to the literature by closing the research gap about the nexus between public perceptions of forest dieback and climate change by providing empirical evidence from two Southern German mountain areas. Our results show that forest dieback is not perceived as a new phenomenon in the Bavarian Forest and the German Alps. However, climate change is now perceived as the second most important influencing factor on forests, preceded by pests, diseases and invasive species, which are themselves fostered by climate change. This is in line with the results of a Delphi study by Sacher and Mayer (2019) in which forest experts named climate change as the most important influencing factor on forest development in Bavaria for the next three to six decades. The higher perception of pests, disease and invasive species in the Bavarian Forest fits very well with the long-term issue of bark beetle outbreaks in the same region (Kölling 2008; Müller et al. 2008; Binder and Höllerl 2011; Triebenbacher and Lobinger 2020). Given the setting in two mountain areas, our results indicate that climate change is not only perceived by urban elites but also in rural, partly peripheral and economically disadvantaged regions. Forest dieback seems to serve as means for inhabitants of rural, forest-dominated regions to experience the impacts of climate change. The climate change perception of rural residents might be crucial for their approval of the transition to renewable energies with considerable landscape impacts especially in rural areas (e.g., massive increase in wind turbines and solar power stations etc.).

While public risk perceptions are clearly complex and multi-dimensional (Renn and Rohrmann 2000), past research has suggested that risk perceptions of climate change are primarily influenced by four key dimensions, namely experiential processing, cognitive, socio-cultural, and socio-demographic factors (van der Linden 2015). Our study underpins both forest dieback and climate change perception by several variables of the theoretical CCRP model (van der Linden 2015). Experiential processing plays an important role: the more strongly that participants state being affected by climate change—i.e., having already individually experienced climate change—the more they perceive forest dieback. Soucy et al. (2021) derived similar results for forest stakeholders, with knowledge about climate change, personal experience and social norms being key determinants of climate change risk perception.

More than 90% of the respondents think that climate change is real, even though the majority of them have not yet been personally affected by climate change. Thus, the proportion of respondents in the Bavarian Forest and the German Alps who regard climate change as real is higher than in 2013 (Osberghaus et al. 2013), and consistent with a survey in 2021, where 91.8% of respondents state climate change as real (Frondel et al. 2021). Frondel et al. (2021) found an increase in the perceived importance of climate change issues in Germany from 2015.

Climate is a statistical phenomenon that describes average weather conditions over a period of 30 years and therefore cannot be easily and accurately identified by the lay public (Weber 2010; IPCC 2013). Thus, climate and climate change are mainly perceivable by secondary indicators such as drier summers and warmer winters, drought (Iglesias 2021), glacier melt (Salim et al. 2023) and an increase in forest damages and tree mortality in the forest dieback context. This indicates that experiential processing is important for human climate change perception. This result is in line with, e.g., Diakakis et al. (2021), who found that climate-related disaster experience influences climate change perception for the Eastern Mediterranean (Greece). Iglesias (2021) revealed that a local experience-driven risk perception supports adaptation actions. Further, Sousa-Silva et al. (2018) even found a weak but significant positive association between forest owners’ and managers’ individual experiences with climate change and the silvicultural adaptive response, which is also shaped by the perception of climate change. Thus, our results underline that forest dieback serves as a sign of climate change and increases its perception by serving as a catalyst of climate change perception.

In addition to experiences in and with the environment, influencing factors like environmental worldview or information level affect the perception. Due to moral obligations and responsibility, ecocentric respondents perceive climate change and its effects stronger than respondents with an anthropocentric environmental worldview (Heimann 2019). Moreover, Whitmarsh (2011) demonstrates that climate change beliefs are fundamentally linked to values and worldviews and that citizens with low pro-environmental values tend to be more skeptical about the reality and severity of climate change. In an EU-wide study on images and values of nature, Farjon et al. (2016) summarize that the majority of the European population have an ecocentric attitude (60%) and one-quarter an anthropocentric attitude. However, in most cases, respondents did not show a strong preference for a particular environmental attitude. In the Bavarian Forest and the German Alps, the majority of respondents (55%) can also be classified as ecocentric, and about 19% can be classified as anthropocentric. However, there are no clear preferences for a particular environmental worldview either.

Regarding the cognitive dimension, the better that respondents estimate their state of knowledge about both climate change and forests, the more that they perceive forest dieback. This fact makes sense as forest dieback is not always noticeable upon first glance and knowledge about forests and climate change and regular visits are required to assess the state of the forests. In some cases, forest dieback looks like a slow-burning crisis (Staupe-Delgado 2019). Blennow et al. (2016) found that forest stakeholders with a high educational level were more concerned about climate change than those without. Moreover, Archie (2014) found that the more informed that respondents were about climate change, the higher their concern about and belief in climate change, and the more likely they were to report current adaptation planning or implementation.

If the respondents regard deadwood as a source of danger for forest visitors and ecologically important, they perceive forest dieback more strongly. Thus, it seems that the perception of forest dieback does not depend on an either negative or positive overall attitude towards deadwood but on differing aspects of the complex attitudes towards deadwood (see also Sacher 2020). Müller (2011) highlights that people often identify with the visual image of a “thick, green forest” landscape that creates a shared sense of place and belonging. The author argues that it is unsurprising when forest disturbances and resulting high amounts of deadwood have profound social repercussions. Indeed, the occurrence of deadwood as a result of bark beetle outbreaks has led to various emotional debates and conflicts in the Bavarian Forest National Park over recent decades (see, e.g., Liebecke et al. 2011; von Ruschkowski and Mayer 2011). By contrast, several more recent studies also indicate that deadwood in general does not have a negative image among the population (Rathmann et al. 2020; Sacher 2020; Sacher et al. 2022).

The cluster analysis revealed three quite different groups: Respondents with a preference for rather nature-oriented forestry, a more traditional forestry, and those who strongly prefer introducing new non-native tree species. However, mixed forests is the most important strategy in two of the three clusters. Bavarian Forest inhabitants are overrepresented in the second cluster, while respondents from the German Alps are overrepresented in the first cluster, possibly due to the more pronounced forest dieback and bark beetle outbreaks in the Bavarian Forest and/or the important role of forestry and wood-processing industries there in the past (see section “Study areas”). Cultivating a mixed and uneven-aged forest is not a new concept but is gaining new attention with the climate change discourse (Matthes et al. 2014; Juutinen et al. 2020). While inhabitants prefer the prospective forest state with mixed, structured forests with native species—which is also recommended by forest policies (BMEL 2021) and researchers (Hilmers et al. 2020)—forest stakeholders realize several obstacles to adaptation like a lack of knowledge and information (Sousa-Silva et al. 2018; Hengst-Erhart 2019; Mostegl et al. 2019; Deuffic et al. 2020; Pröbstl-Haider et al. 2020). Peterson St-Laurent et al. (2018) found greater levels of support for rehabilitation strategies, and lesser levels for conservation-focused strategies, in contrast to enhanced forest management strategies by the British Columbian public. As we found in our study, the support for forest management strategies is thereby affected by environmental worldviews and risk perception, but also by socio-demographic factors.

We conclude that the public in the Bavarian Forest and the German Alps largely appreciates mixed, diverse and structured forests with native tree species. In this way, our results support the current Bavarian forest policy programs (StMELF 2019, 2020) and the German Federal Forest Strategy 2050 (BMEL 2021) and are in line with a recent quantitative study in Bavaria by Sacher et al. (2022) and the opinion of pro-active forest stakeholders (Deuffic et al. 2020; Garms 2021). By contrast, forest policies like the declaration of Moritzburg (German Forestry Ministers 2019)—which suggest “salvage logging” of damaged trees to prevent bark beetle impacts—are at odds with the public’s preferred forest adaptation strategies towards climate change and thus could lead to conflicts. In addition, such strategies might lead to negative impacts on forest biodiversity (Thorn et al. 2019).

Our findings underline the importance of understanding local perceptions of forest dieback and climate change as we found that these perceptions are affected by individual experiences with climate change, the knowledge level about forests and climate change, and the environmental worldviews and deadwood attitudes. Similarly, the support for forest management strategies is affected by environmental worldviews and risk perception, but also by socio-demographics. All these influencing factors could vary considerably between different regions. This implies for forest management seeking acceptance and support for climate change adaptation measures that decision-makers of all spatial levels (federal state, state forests, local foresters, forest owner associations) must transparently inform the (local) population about their strategies and measures and should tailor their outreach to the different stakeholder groups keeping in mind their differing perceptions of nature. This need for targeted communication strategies is further highlighted by our results which also reveal important misconceptions held by the public: Given that a considerable share of the respondents named tourism and recreationists’ behavior as main risks to forests, all relevant forest stakeholders need to better inform the public about the climate change related risks for forests, which are overall much more salient and severe compared to the rather locally concentrated negative impacts of tourism on forests. It should be explained to lay people how climate change and its direct and indirect consequences impact forests already now and will do so even more in the future and which adaptation strategies leading to which effects and landscape consequences are being pursued by decision-makers. An important prerequisite for an environment that promotes learning is to create situations which are characterized by openness, in which parties (e.g., forest owners, public) exchange valuations and assessments, and thereby fill in their personal knowledge maps (Blennow et al. 2014). One example of such targeted communication could be that the forest owners (often mountain farmers but also the regional state forest agencies, see Eriksson 2017) regularly offer short hiking tours through forest areas especially impacted by forest dieback or where adaptation measures already take place. In this way, they could share first-hand their experiences about the impacts of climate change on the local mountain forests, explain their strategies and discuss the pros and cons with the participants. This format may be also an ideal way to promote discussion and exchange under small scale forest owners and forestry experts providing advisory services (e.g., forest owner associations and authorities). Blennow et al. (2014) and Vulturius et al. (2020) found that especially peers are valuable in connecting information about climate risks and adaptation to the actual forest property. Female forest owners and foresters could organize special gatherings to communicate forest dieback issues to the female population otherwise potentially put off by the male dominance in the forest sector (Süddeutsche Zeitung 2023). In addition, short videos highlighting current issues could be produced by the forestry actors and shared on social media and with teachers to reach the younger generations in the mountain municipalities and beyond. Moreover, commonly used information sources like articles in local newspapers may be a good way to reach a broader audience (including small scale forest owners, see Soucy et al. 2020).

To sum up, the implemented CCRP model has been validated by similar studies (e.g., Grothmann and Patt 2005; Whitmarsh 2011; Soucy et al. 2021) and enables the combined analysis of climate change and forest dieback perception. Nearly two-thirds of the respondents in two mountain areas of Southern Germany perceive moderate to strong forest dieback in mountain forests and relate it to the similar strongly perceived climate change. Consequently, forest dieback and climate change perception are positively correlated. Thus, it could be interpreted that forest dieback serves as an indicator for hardly perceivable long-term impacts of climate change. Nevertheless, the causal relation between both constructs must be object of further research as it may well be the case that the perception of both constructs is driven by similar antecedents (e.g., values, experiences). However, the correlations in the CCRP model are rather weak (which should be reanalyzed in future research), possibly caused by a too low level of knowledge of the respondents (lay people, not forestry experts)—Agbenyega et al. (2009) also address this lack of knowledge among forest stakeholders. Further reasons could be that some of our variables are not salient regarding risk perceptions and would need to be replaced in future studies. Further limitations of this study are its setting in two specific rather rural areas, whereby its results may not be generalizable to the whole of Bavaria or Germany. In addition, our survey was conducted in summer/fall 2018, when attention to drought and climate change in Germany was not as pronounced as in the following years (Lübke 2021), among others due to the media attention to the “Fridays for Future” youth protest movement. Thus, perceptions of forest dieback and climate change are likely to have changed in the meantime.

While the theoretical model of van der Linden (2015) was able to explain the perceptional process of climate change and forest dieback, we found no correlations between the perceptions and the preferences for silvicultural adaptation measures which should be reexamined by future research. Respondents support nature-based forest adaptation strategies over intense measures but show a considerable heterogeneity in their preferences as revealed through a cluster analysis. Based on this study, further research could focus on other mountain forests or other regions in general to enable a comprehensive analysis of forest dieback and climate change perception in and beyond mountain areas.