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Article

Evaluating Forest Visitors’ Place Attachment, Recreational Activities, and Travel Intentions under Different Climate Scenarios

1
Innovation and Development Center of Sustainable Agriculture, Department of Forestry, National Chung Hsing University, 145 Xingda Rd., South Dist., Taichung City 40227, Taiwan
2
International Bachelor Program of Agribusiness, National Chung Hsing University, Taichung City 40227, Taiwan
*
Author to whom correspondence should be addressed.
Forests 2021, 12(2), 171; https://doi.org/10.3390/f12020171
Submission received: 6 December 2020 / Revised: 13 January 2021 / Accepted: 29 January 2021 / Published: 2 February 2021
(This article belongs to the Special Issue Economic Analysis of Land-Use Change and Deforestation)

Abstract

:
Climate change leads to a variety of extreme weather conditions such as heat waves, unusual cold weather, and heavy rain, which always ends up with serious disasters. It could have a tremendous impact on a lot of industries in the world. The tourist industry, that plays a vital role in the global economy, has faced serious impacts from climate change in many tourist attractions, e.g., national parks, mountain areas, and beaches. The travel behavior of visitors has been changed under various climate change conditions. To understand the influence degrees of tourists on climate change factors, this study aimed to analyze whether there is difference in the influence of climate change on socio-demographic background, travel activities, travel intention, and the revisit intention attitude of tourists with different degrees of place attachment to Wuling National Forest Recreation Area. This study further investigated whether the climate change adaptation strategies offered by the park manager would have a positive influence on travel intention of tourists. The results of this study showed that except for heat waves, events related to climate change such as stronger typhoon, heavy rain, unusual cold weather condition, mud sliding, forest fire, and the appearance of mosquitos would have a negative influence on travel intention, especially for the tourists with a low degree of place attachment. In addition, if the park manager offers strategies to adapt to climate change conditions, these strategies would have a positive influence on travel intention.

1. Introduction

Global climate change is a problem of grave concern. The General Assembly of the United Nations (UN) identified it as the most pressing issue that the world must address this century. The frequency of extreme weather conditions such as heatwaves, droughts, rainstorms, and hurricanes has increased [1]. These factors affect the time and location of outdoor tourism and nature sightseeing activities [2,3]. As global climate conditions continue to be worsened in the foreseeable future, tourism resources will inevitably become subject to the effects of climate conditions, altering tourists’ frequency and travel intention [4,5,6]. Climate change has different consequences across different parts of the world, which results in the variation of tourism destination attractiveness and tourist activities [5]. Earlier research studied how tourism demand in different locations would be affected by climate change conditions, such as in national parks [7,8], mountain trails and ski resorts [9,10,11], and beaches and shorelines [12,13]. Any change in the flows of tourists and their expenditure would create effects economically and socially for different locations. For instance, on a global scale, a warmer climate would attract people to destinations situated in higher-latitude locations, bringing benefits to the tourism industries there. Conversely, the same climate change effect would have negative consequences on the tourism industry near the equator [14]. The frequency of tourism travel would potentially affect business strategies and operations in different regions. Therefore, it is essential to take the tourism behavior of future tourists into account to address the consequences of global climate change [6].
Tourists can adapt to climate change and local weather conditions in tourism areas by substituting their desired activities [15]. Iso-Ahola’s theory of substitutability states that when people recognize the necessity of potential alternatives, they would be willing to change their original plans. Therefore, weather prediction and preplanning of recreational activities would affect the intention of many tourists because they may adapt to circumstances and change their plans [6]. Climate change also affects various aspects of society, including people’s perception of tourist locations. According to research by Amundsen [16], tourists with different degrees of place attachment will respond in various ways when faced with similar environmental problems. Park managers must likewise take appropriate measures in response to the effects of climate change. Rising sea levels and more hurricane strikes are leading to an increased probability of coastal flooding. Local communities have resorted to improving the rain- and waste-water drainage system, alongside other measures, and must bear the enormous costs spent on these measures, which may only be of benefit in a few critical situations unless the effects of climate change worsen [17]. Because it is tourists who express their travel intention as part of their ultimate decision, communities ought to gauge how tourists react to relevant measures before executing projects and study how these measures correlate with tourists’ place attachment to that specific locale [18]. This research explored the relationship between place attachment and recreational activities, as well as the effects of global climate change on tourists’ travel intention. In addition, this research studied whether the implementation of climate-change adaptational policies would influence tourists’ willingness to engage in recreational activities.
The three focus questions for this research were as follows: (1) Do different degrees of place attachment affect the types of recreational activities in which tourists partake in a recreational forest area? (2) Would tourists with different degrees of place attachment differ in their sociodemographic background, intention to revisit, and tourist intention? (3) Will tourists’ travel intention rise significantly because of park managers’ adaptational policies to global climate change and related issues? This study’s findings will help business owners in the tourist industry, tour planners, and tour service providers to better grasp the nuances that could generate tourists’ revisit intention when considering the effects of climate change. This study hopes to serve as a reference for administrators formulating managing strategies in recreational forest areas in response to climate change. This research also hopes to assist the management of recreational forest areas and national parks, enabling administrators to identify different groups according to differing degrees of place attachment and increase tourists’ travel demand.
When people identify with a particular area, or when they develop a sense of attachment to the area’s culture [19,20], a space-specific significance will form [21]. Place attachment describes why people have a particular attachment to a specific area [22]. It reflects the intrinsic value that people assign to each place [23], as well as a range of place-specific emotional attachments that are engendered [24,25]. Although place attachment tends to increase proportionally with the number of tourist visits [26,27], people may still develop place attachment if they recognize a location’s overall importance and symbolism without having ever visited [20]. Place attachment is a multi-faceted concept with two relatively more conventional indicators: place identity and place dependence [26]. Place identity describes the emotional attachment of a person to a specific place, and place dependency is a person’s reliance on bonding with a specific location [24]. Place identity forms when someone develops an emotional bond or perception toward a specific place [28,29]. If we consider the fact that some places have specialized attractions (e.g., scenery, habitat, culture, and spots) that shape visitors’ expectations of specific activities and target goals [24], place dependency refers to the functional aspect of attachment. Place attachment is assessed by focusing on specific activities and goals to assess the degree of dependency compared with other substitutable places [26,30]. To establish acceptable reliability for the two indicators, researchers have used four- to six-question formats to conduct interviews (e.g., Reference [24]).
Recently, many scholars have introduced other indicators to measure place attachment such as place belonging [31], place loyalty [32,33], place familiarity [34], and place benefit [35,36]. Crucial for validity and reliability purposes is that two conventional indicators (place dependency and place identity) form the basis of place attachment assessment exercises within a basket of concepts for analytical purposes. It is notable, however, that Hammit et al. [34] found models with more indicators to have higher degrees of validity than do analyses that only consider two indicators, highlighting place belonging. Therefore, for this study, place belonging, place dependency, and place identity were selected to serve as indicators for studying place attachment. Place belonging is an indicator that describes people feeling they have achieved immersion in a locality, or that they have attained a sense of having become a part of the local community [37]. Place belonging is an important indicator and differs from place identity [38]. Tourists who visited Wuling National Forest Recreation Area in Taiwan may develop a strong sense of place belonging because of the number of revisits and unique natural scenery of the area. Earlier studies have indicated that place attachment affects tourists’ attitude and behavior [39,40], and place attachment would also have land- and visitor-management applications. Furthermore, many studies have shown that national parks have relatively more natural resources and would be more likely to generate place attachment than would other places [27,41,42]. Increased place attachment brings many benefits to a local area; for example, it induces environmentally friendly behavior [35], compliance with park rules and fees [43,44], and the intention to revisit [45]. Tourists with a high degree of place attachment exhibit interest in the administrative policies of their target location, therefore, it could help managers understand and meet the expectations of tourists [26]. Studies have also shown that tourists’ place attachment would affect their environmental consciousness, awareness of environmental issues [46], and ultimately their behaviors [35,46,47]. The stimulation of environmentally friendly behavior could reduce the negative impact associated with tourists following the increase in their place attachment [48].
Visitors’ activities during their stays are correlative to their place attachment. A case study on tourism in Maine, USA, demonstrated that tourists with higher degrees of place attachment tend to participate in more diversified tourism activities, such as those related to natural sightseeing and cultural recreation [49]. Another study on the city parks of Georgia, USA, identified a correlation between tourists’ environmental attachment and their recreational activities, and tourists engaged in trekking or hiking activities exhibited the highest degree of place attachment [50]. These studies indicate a complex mix of results between recreational activities and place attachment, and further studies are required for more powerful and compelling evidence and reasoning. Investigations on the effect that place attachment has on future intention to revisit are growing. Revisiting tourists are crucial for the operational revenue of businessowners in the tourist industry because retaining old customers is economically more beneficial than attempting to attract new ones. Furthermore, if tourists attain a higher degree of place attachment, they will tend to attract more tourists to join them on their visits [51]. Some studies have identified that place attachment is a positive factor for future intention to travel [45,49,52]. Moreover, Neuvonen, Pouta, and Sievänen [53] indicated that place attachment increased tourists’ intention to revisit Finland’s national parks, economically benefiting local communities. Therefore, increasing place attachment is of vital importance in bringing economic sustainability to tourist areas with fewer visitors. However, less research has discussed whether place attachment-induced future intention to travel would be affected by climate change. Because the degree of place attachment would vary across different locations, this study chose a famous tourism site in central Taiwan, overlapping Shei-Pa National Park. The focus of this study was on tourists’ place attachment to this region.
As for the climate change trends in Taiwan, under the effects of global climate change, regions worldwide are bearing the brunt force of many climate-related hazards, and Taiwan is no exception. Climate change does not only affect floral and faunal ecosystems [54] but also exists in Taiwan’s public health system, socioeconomic development, and infrastructure [55]. In Taiwan, the average sea-level rise between 1993 and 2003 was 5.7 mm per year, or 50 times faster than previous measurements [56]. According to the same report by the Intergovernmental Panel on Climate Change [57], the global average is 0.75 ℃ higher than that in the previous century. In Taiwan, between 1911 and 2009, the annual temperature has risen by 1.4 ℃, and in the past 30 years, the rate of temperature increase has been particularly significant [56]. In terms of precipitation in Taiwan, the main period of rainfall is between May and October, with the monsoon and typhoon seasons being the two primary weather systems that cause precipitation in Taiwan [58]. Numerous studies [55,56,58,59,60,61,62] have indicated that heavy rainfall in Taiwan will become more frequent. The Xueshan and Central Mountain Ranges are particularly hard hit [58], with typhoons being the primary source of heavy rainfall. In recent years, the generation and strike probability of typhoons have increased [58], leading to a considerable amount of precipitation in Taiwan. Climate change is causing annual temperatures to rise globally, with many research findings [56,63,64,65,66,67,68,69] indicating that the number, intensity, and frequency of heatwaves in the past decades has been growing. Conversely, for the past decades, because of the polar vortex, mid-latitude regions have shown a significant increase in the probability and intensity of occasional cold waves [57,70,71]. In Taiwan, the cold wave that occurred on 23 January 2016 resulted in the lowest temperatures on record for the past 70 years [72], accompanied by many adverse economic and security effects. The frequency of sudden heavy rainfall has also been rising, causing many sewage systems in Taiwan to clog and be unable to discharge overflow. Clogged sewers have become breeding grounds for biting midges, the population of which has been significantly increasing. According to a study conducted by Tsai et al. [73], global climate change affects the functions of natural habitats, leading to disease-bearing arthropods coming into frequent contact with animal hosts and even human activities, in turn leading to severe outbreaks of insect-borne diseases.
In short, global warming is causing natural disasters with increased frequency and adverse effects. Typhoon strikes, rainstorms, heatwaves, and cold waves are disruptive to people’s everyday lives. Recreational activities would undoubtedly be affected by the rising probability of these climate-related conditions, leading to a drop in people’s intention to visit natural recreational areas. More seriously, if landslides, forest fires, and zoonotic influenza threaten the safety of tourists, governments and tourism areas would need to take appropriate policy measures to ensure the quality of recreational activities and sustain tourists’ travel intention.

2. Materials and Methods

2.1. Research Area

The research area for this study was primarily Wuling National Forest Recreation Area (24°24′–24°40′ N, 121°18′–121°30′ E) [74], which is part of Taiwan’s system of National Forest Recreation Areas. The recreational area is situated within Shei-Pa National Park [75] and is a renowned national forest recreational area in Taiwan. Its geographical location includes unique alpine habitats and has much relict flora and fauna, along with glacier formations, which are quite rare in the subtropical zone. Furthermore, Wuling National Forest Recreation Area is upstream of the Da-Jia River, hence a critical aquatic source for the greater Taichung region. Qijiawan Creek, situated within the area, is where the population of the Formosan Landlocked Salmon (Oncorhynchus masou formosanus), an ice-age relict, is located [76]. The Formosan Landlocked Salmon is considered a national treasure and its primary habitat is Qijiawan Creek. It has considerable traction with tourists, drawing them to visit Wuling National Forest Recreation Area. In addition to its unique ecosystem, the area has a famous hiking route that leads to the second highest elevation in Taiwan, Xueshan peak. The hiking route also boasts the “Four Scenes of Wuling,” which offer visitors a unique glimpse of Taiwan’s natural beauty. The two trail systems happen to be the best routes in Xueshan National Park, with unique glacial cirque formations, the highest mountain lake in Taiwan (Cuichi Lake), and Taiwan’s only Abies forest (the so-called “Black Forest”). Wuling National Forest Recreation Area not only provides the opportunity to enjoy and experience natural scenery but also has many relict formations from the last ice age.
Extreme weather events such as heat- and cold-waves attributable to climate change are gradually altering the travel experiences of tourists. More adverse factors such as landslides and forest fires would not only affect tourist safety but also cause permanent damage to many pristine and natural ecosystems and sceneries. Moreover, because Wuling National Forest Recreation Area is situated deep in the mountainous interior of Taiwan, foreign visitors wishing to visit must be prepared to spend considerable time on traveling there. Climate change effects will surely have an impact on tourists’ intention to travel [2,11,14].

2.2. Questionnaire Design and Sampling Method

The instrument development of this study, including the item statements in the questionnaire, was established based on an extensive review of the extant literature regarding place attachment, including place identity, belonging, and dependency. There were seven sections in the research questionnaire, including a survey on visitors’ recreational experience, a place-attachment assessment, the intention to travel under climate change conditions, an evaluation of the preference of climate change response policies, travel intention following a review of adaptational policies, the interviewee’s revisit intention, and the interviewee’s sociodemographic background. This research not only considered the recreational experience of visitors to Wuling National Forest Recreation Area, but also the activities in which they participated, their estimated duration of stay, and the frequency of their everyday engagement in recreational activities in the natural environment. The responses were used as reference data for subsequent research analyses. In addition, this study conducted a visitor place attachment and satisfaction survey based on recommendations from earlier studies [31,34]. Respondents were asked to indicate their level of agreement or satisfaction with place attachment and satisfaction on a five-point Likert scale, ranging from 1 (strongly disagree/dissatisfied) to 5 (strongly agree/satisfied). A summary of the three primary indicators and 14 item statements of the observed variables are presented in Table 1.
A combination of sampling methods was used to select visitors as representative of the targeted forest recreation area population. This research first adopted a two-stage cluster sampling design. The first stage was simple probability random sampling, where dates and locations to administer a questionnaire were selected. The second stage was systematic random sampling, which was conducted when visitors were present on site [77]. With the systematic random sampling method, this study attempted to avoid bias in this survey research. The first stage took place in the following six survey locations which encompass the entire Wuling National Forest Recreation Area at different sites, including the visitor center, the camping grounds, the Xueshan and “Four Scenes of Wuling” hiking trail entrances, scenic spots, and the Formosan Landlocked Salmon Habitat Center. Specifically, the reason for these selections was the relative abundance of visitors in the locations, which are primary recreational sites people visit the most in Wuling National Forest Recreation Area. The targeted age group and locations where the questionnaire would be administered were evenly distributed to ensure the validity of the research results.
To gauge the effects of climate change on travel intention, this study asked visitors whether different climate and hazard conditions would affect their future decision to travel. To avoid interference caused by the interviewees’ perception of climate change, this study provided questionnaire instructions before conducting the survey. The contents were as follows: “Before responding to this section, please recollect the circumstances under which you visited Wuling National Forest Recreation Area. Please describe your intention or decision to travel if these climate and environmental conditions had occurred.” The following 5-point scale was used to describe the interviewees’ decisions: (1) very reluctant to travel, (2) reluctant to travel, (3) average, (4) willing to travel, (5) very willing to travel. This study listed different climate change-related scenarios that could occur in Taiwan based on the Taiwan Climate Change Science Report [78]. For instance, there are usually several typhoons striking Taiwan in summer, but none struck in 2020. Moreover, the record-breaking high temperature of 40.2 ℃ was recorded in Taitung, Taiwan, in July of 2020.
The degree of preference of visitors toward climate change adaptation policies was assessed by listing nine potentially suitable strategies for Wuling National Forest Recreation Area [79,80,81]. These were listed alongside existing measures. Furthermore, tourist satisfaction was used for analysis, and tourists’ travel intention following the implementation of climate change adaptation strategies was assessed based on how the nine listed strategies would influence tourists’ decisions. To understand what tourist activities may be most affected, this study listed 12 activities in Wuling National Forest Recreation Area that tourists can participate in. The research questionnaire investigated which activities visitors had partaken in and asked them to list their three favorite activities. The contents of this questionnaire are shown in the Supplementary Materials, Table S1.
This research used descriptive statistics to present the questionnaire results to reflect the interviewees’ sociodemographic background and recreational experience. According to the visitors’ degree of place attachment to Wuling National Forest Recreation Area, this study used three indicators (place identity, place dependency, and place belonging) to analyze place attachment. This study employed SPSS 23.0 to perform a multivariate two-step cluster analysis, in which visitors were separated into three clusters based on their differences in place attachment. A four-question format with question-and-answer (Q&A) analysis was used to gauge place identity and place belonging, whereas place dependency was determined using a six-question format with Q&A analysis, as seen in Table 1. Each place attachment indicator was quantified and presented in the form of averages. The questionnaire design of this research was tested for internal consistency using Cronbach’s reliability analysis for testing purposes.
Tourists were separated into three clusters, namely low (n = 35), medium (n = 111), and high (n = 61) degrees of place attachment. Each interviewee’s evaluation was based on place-attachment categorization results, and their sociodemographic background, recreational experience, intention to revisit, adaptative policy, and travel intention were sorted and compared. Chi-square tests and analysis of variance (ANOVA) were used to investigate the significance of groups with different place attachment. This study had three or more clusters, each of which exhibited a disparate numerical discrepancy. As a result, Levene’s test for comparing two or more variances was deployed to gauge homoscedasticity. For homoscedastic variables, this research used ANOVA and Scheffe’s post-hoc test for further testing. For variables that did not exhibit homoscedasticity, this research used Welch’s ANOVA analysis and the Games–Howell post-hoc test as testing procedures [82]. A paired-sample t-test was used to analyze tourists’ travel intention before and after the implementation of adaptational policies to determine significance.

3. Results

The questionnaire survey was conducted between 4 August and 6 August 2018, at Wuling National Forest Recreation Area, and web-based questionnaires were administered between 15 August and 29 August 2018. A total of 230 questionnaire copies were distributed, with 207 returned, for a return rate of 90%. A total of 155 questionnaires were distributed onsite, and 57 were distributed as web-based questionnaires. The results of interview demographics are described in Table 2. Interviewees were predominantly male (54.1%), and primarily married (74.9%), and the core age group was 30–49 years (53.2%). Interviewees were generally well-educated, with 80.6% possessing a college degree or above, and the professions were diverse, including agriculture, forestry, fishery, and animal husbandry. Their monthly income was mainly between NT$40,000 and 60,000 (28.0%). They participated in nature-related recreational activities 1–3 times per month (45.4%). There are other vocations and varied recreational experiences presented as activity counts. Visitors to Wuling National Forest Recreation Area mostly arranged a 3-day/2-night schedule (45.4%), and they had not joined environmental groups (89.9%).
This study used Cronbach’s α to test reliability of the questionnaire, and the results showed that the evaluation of the interviewees’ place attachment had a high degree of reliability (α = 0.852; Table 3). The indicator analysis by category achieved similar results, with place identity registering α = 0.838, place belonging α = 0.808, and place dependency α = 0.659, all showing high reliability. Additionally, high reliability existed for visitors’ intention to travel before and after the implementation of climate change adaptational policies. The α value before implementation was α = 0.845 and that after adaptation was α = 0.883. The adaptational policies and revisit intention categories extrapolated from the questionnaire also achieved high reliability. The adaptational policies category registered α = 0.723 and revisit intention α = 0.837. In sum, the questionnaire design of this research yielded considerably reliable results.
This research investigated the preferred activities of visitors at Wuling National Forest Recreation Area. To obtain a deeper understanding of the participatory experience of visitors in recreational activities, thereby providing interviewees with the correct pathway to choose the right activities for their engagement, the survey was presented using multiple-choice questions, and Table 4 presents the results. The primary visitor activities were found to include camping (71.5%), forest bathing (64.7%), and trail walking (58.9%). The preferred recreational activities are shown in Table 5. The most popular choices included forest bathing (78.3%) and camping (69.6%). This research also found that many activities—such as ecology education, flora appreciation, agriproduct purchasing, and Formosan Landlocked Salmon observation—differed significantly from activities with higher visitor preference scores and participation rates. For example, 21.3% of visitors had partaken in ecology education activities, but only 9.2% enjoyed this activity. Furthermore, 21.3% of visitors had purchased agriproducts at points of sale situated within the recreation area, but only 3.9% liked this activity. By contrast, while only 64.7% of visitors had participated in forest bathing, 78.3% of visitors expressed a liking for this activity.
Regarding the tourists’ place attachment, this study used three indicators (place identity, place belonging, and place dependency) to conduct a comprehensive analysis of place attachment. Cluster sorting was performed by deriving the average of the three indicators, which was then subject to two-step cluster analysis. The results are presented in Table 6. The degree of place attachment was highest in terms of place identity, whereas place dependency had the lowest mark, a result comparable to previous research findings [6,31,49]. In proportional terms, the medium place-attachment cluster had the most visitors (111), followed by the high place-attachment cluster (61) and low place-attachment cluster (35). The averages of the low and high place-attachment clusters had larger differentials. All average scores of the indicators in the high place-attachment clusters exceed 4, whereas the low place attachment cluster registered less than the normal score (3) in terms of place belonging and place dependency. The results indicated that significant differences existed between clusters.

3.1. Sociodemographic Backgrounds and Recreational Experiences Based on Place-Attachment Score Clusters

The 207 interviewees who participated in this research were sorted into low, medium, and high place-attachment score clusters based on the place-attachment evaluation. The data extrapolated were then analyzed using ANOVA and Chi-square methods, and the results are shown in Table 7. In terms of the level of education attainment, the majority of interviewees had received degrees in tertiary education or above. They also had marked differences in sociodemographic backgrounds, such as age (p = 0.014), profession (p = 0.011), and duration of stay (p = 0.002). In particular, tourists scoring high in place attachment tended to spend longer periods of recreational time at Wuling National Forest Recreation Area. The results showed that the high-score cluster would remain in the recreation area for more than 2 days and 1 night, which differed significantly from the low-score cluster (11.4%), who tended to remain only for 3 h or less. These results are comparable to those of research conducted by Ednie et al. [49] and Urioste-Stone et al. [6]. Tourists in medium- to high-score clusters had an average age (40 years) that is significantly higher than that of the low place-attachment cluster (33.3 years old). This difference indicated that younger tourists with high place attachment are fewer in number. The interviewees’ profession also showed a significant difference. The low place-attachment cluster primarily comprised students (37.1%), but students only accounted for around 15.0% within the mid- to high-score clusters, which primarily comprised military servicemen, public servants, and teachers, who exhibited high degrees of place attachment. In terms of income, the results indicated that the higher the income of tourists, the higher their place attachment scores. In the low-score cluster, 37.1% of tourists had a monthly income of less than NT$20,000, whereas in the high-score cluster, 41.0% of tourists had an income between NT$40,000 and 60,000. Second, different clusters exhibited significantly different frequencies in terms of participation in nature-related activities. For example, tourists in the low-score cluster only participated in approximately eight nature-related recreational activities per month, indicating that tourists with different degrees of place attachment differ significantly in terms of their daily recreational activities.

3.2. Tourists’ Recreational Activities Based on Place-Attachment Score Clusters

The place-attachment clusters served as the basis for further analysis of the tourists’ activity participation and attitudes toward activities. The results showed that tourists in different place-attachment clusters expressed different views of camping (p = 0.001) and mountain trail walking (p = 0.043; Table 8). Kirkpatrick et al. [83] studied Tasmania in Australia and found that 52% of interviewees who developed place attachment attributed their bonding to the local natural environment, whereas 41% attributed it to the local scenery. This indicated that nature-related activities in which tourists participate have a positive correlation with their sense of place attachment, which is comparable with the results of this research. The study by Urioste-Stone et al. [6] regarding Maine in the USA reported similar results, indicating that tourists behave differently in nature-related activities when observed from a graded place-attachment point of view.
This study’s analysis of the intention to revisit Wuling National Forest Recreation Area was also based on the place-attachment score clusters and is presented in Table 9. The results indicated that different score clusters differed in their intention to revisit (p < 0.001). Tourists in the low-score cluster yielded a score of no more than 4 in terms of their intention to revisit, falling into neutral territory. By contrast, visitors with high place attachment scores showed higher revisit intention, scoring approximately 4.5. These results indicated that low- and high-score clusters differed in terms of their preference to revisit.
Tourist clusters with different degrees of place attachment were compared for their opinions on the necessity of climate change adaptational strategies. The results shown in Table 10 indicate that, among all the strategies listed, only “Building unique buildings in the area as a supplement to damaged natural scenery” scored lower than 3 points in all clusters, indicating that the tourists did not identify with this adaptational policy. Views toward other adaptational policies scored higher; in particular, “Enhancing habitat conservation” and “Establishing a wildlife conservation district within the recreational area” received the most support and recognition among all visitors. There was also wide support for visitor safety- and security-related policies. Examples included “Improving soil and water conservation within the recreation area to ensure the security of visitors” and “Providing accurate instant weather forecasts and environmental safety-related messages within the recreation area”.
This study used ANOVA to compare the attitudes that interviewees with different degrees of place-attachment had toward climate change adaptational policies and performed differential analysis. The results are presented in Table 10. Among the nine adaptational policies listed by this research, one in particular elicited significant differences in opinion among tourists with different degrees of place attachment. Interviewees’ responses showed high disparity (p = 0.014) toward the policy of “Enhancing soil and water protection within the recreation area to ensure visitors safety”. Tourists with a high degree of place attachment expressed more support for the soil and water protection policy. Apart from these, an observable agreement existed among interviewees for climate change adaptational policies, with each policy scoring 3 points or above. There was apparent support from the general public for park managers implementing policies and executing administrative duties related to climate change. According to Lee [46], place attachment is positively correlated with individuals’ support for environmental protection-related policies. The research results by Altinay [84] indicated that support for policies that mitigate climate change effects is significantly correlated with people’s perceptions of climate change. This study proposed that because of increasing awareness among people worldwide toward the hazardous effects of climate change [85], tourists to Wuling National Forest Recreation Area exhibited homogeneity instead of significant differences under the cluster analysis.

3.3. Travel Intention under Climate Change Effects

This study assumed that tourists with different degrees of place attachment would develop varying degrees of travel intention when confronted with various climate change factors. As shown in Table 11, the increased frequency of heatwaves was the only factor that did not adversely affect visitors’ intention to travel. According to research by Fisichelli et al. [8], climate change has led to rising annual average temperatures, affecting the number of visits to 95% of national parks across the United States. The results showed that because of the rise in annual average temperature, a significant increase in the number of visits will occur between 2041 and 2060. By contrast, among climate change factors, landslides cause the most dramatic effect on graded place-attachment clusters, with scores of 2 or below, indicating that visitors consider landslides in mountainous regions the most threatening event. A comparison of the differences in travel intention expressed by tourists with different degrees of place attachment indicated that typhoons (p = 0.003), landslides (p = 0.015), rainstorms (p = 0.016), heatwaves (p = 0.006), and biting midges (p = 0.045) led to different results. This indicates that tourists with low place-attachment scores would lower their intention to travel when confronted with climate change-related conditions. Following post-hoc testing, the results indicated that, while visitors with high place attachment tended to have higher travel intention, climate change would still negatively affect the travel intention among potential tourists to Wuling National Forest Recreation Area.
Under the effects of climate change, if the managers of the forest recreation area implement the climate change adaptational strategies described above, then visitors’ travel intention following policy implementation would be as described in Table 12. Most results before the implementation of climate change adaptational policies were similar. The only difference was that when the heatwave frequency increased, a slight increase in visitors’ intention to travel under such circumstances was observed. Other weather conditions led to the opposite effect. Tourists with different degrees of place attachment changed their travel intention when they considered climate change factors in the post-implementation phase. Among the low and medium place-attachment score clusters, landslides were the most severe climate change factor with a negative impact. However, what affected visitors with a high degree of place attachment the most was the increased frequency of forest fires. A comparison between clusters with different place attachment scores indicated that heatwaves (p = 0.002), zoonotic influenza (p = 0.017), and growth in the number of biting midges (p = 0.035) differed in their degree of impact. Tourists with different degrees of place attachment following the implementation of adaptational policies held no homogenous views toward these factors that were not related to climate change. In addition, this research found that under hypothetical conditions post-implementation, tourists with different place-attachment scores responded with discrepancy in opinions in three categories, down from five categories before adaptation. The reason is likely that the climate change factors hypothesized in this research are all adverse impact-bearing effects, and hence following the implementation of adaptational policies, the score distribution trended toward 3 (neutral), leading to less discrepancy between individual clusters. Following post-hoc testing, the adoption of relevant adaptational policies by administrators caused visitors with high degrees of place attachment to exhibit higher travel intention. Travel intention among visitors with lower place attachment would be more adversely affected when they encounter climate change effects.

3.4. Travel Intention after Adaptational Policy Implementation

This research used paired-sample t-tests to study the travel intention differences among tourists before and after adaptational policy implementation by park managers. The results are presented in Table 13. The research results showed that a significant increase occurred in each of the climate change factors before and after the implementation of climate change adaptational policies. All had a p-value of 0.000 in the t-test, indicating significance. In particular, tourists’ travel intention increased more significantly when there was an increase in the frequency of typhoons, with the average difference value reaching 0.4010. When compared with the growth of biting midges, the average difference value was 0.2271 post-adaptational policy implementation, indicating that the growth of biting midges has a direct effect on the quality of some of the visitors’ favorite activities, such as camping and forest bathing. The increased frequency of typhoons, on the other hand, had no long-term effects on recreational quality. Typhoons occur between summer and autumn, overlapping with this popular tourism season. Tourists have more information on typhoon forecasts, and typhoons have a relatively short impact period. Hence, people interested in visiting the recreation area could choose different points in time to visit. Landslides remain the most severe climate change factor for tourists with place attachment. Still, the implementation of adaptational policies (such as soil improvement and water conservation) led to a significant increase in the travel intention of interested tourists. Pre- and post-implementation average scores had a difference of 0.3623.
During the questionnaire survey, interviewees were encouraged to provide recommendations and raise questions regarding the recreation area. This survey found that many respondents held negative views toward the hygiene of the local living quarters (such as camping grounds). Complaints included too many flies, unclean restrooms, and too few garbage collection locations. Furthermore, interviewees mentioned deteriorating recreational quality during the tourism season when the number of tourists peaked, leading to traffic congestion. Moreover, they considered the roads of the recreation area to be too narrow, further contributing to the traffic congestion. Along these lines, some people worried that such road conditions would cause significant difficulties and hurdles during an evacuation should sudden natural disasters or incidents occur. Lastly, many tourists favored camping activities, which attract the local monkey population to approach and vie for food, altering their natural behaviors.

4. Conclusions

This research discussed the travel intention of tourists to Wuling National Forest Recreation Area, taking climate change factors into account. This study sought to assist park managers in implementing adaptational policies to address climate change by conducting a questionnaire survey and analysis. Interviewees were sorted into clusters based on their place-attachment scores to enable managers to target different visitor clusters and implement appropriate measures. Tourism is a quintessential industry in the nation’s economy, and the quickening rise in tourism development has enabled the industry to assume an essential role in the economy. Furthermore, as the rate of climate change picks up speed, adverse conditions caused by climate change are becoming increasingly severe. Heatwaves and rainstorms as well as increasing typhoon frequency and intensity join a gradually widening combination of hazardous events such as landslides, zoonotic influenza, and increased numbers of biting midges. Therefore, it is vital to understand how future tourism managers and operators could counteract the effects of climate change on visitor behavior.
This research found that many of the area’s nature-related recreational activities (such as forest bathing, camping, and trail walking) may be conducive to strengthening the place attachment of tourists. Moreover, tourists with high degrees of place attachment were found to be older than visitors with low place attachment, and they also tended to spend more time in the recreation area. To better impress visitors with lower place attachment, the park managers of Wuling National Forest Recreation Area are recommended to provide guided tours focusing on the nature-related activities there. This measure may be conducive to building younger tourists’ intention to revisit. Concerning recreational activities on site, this research found that tourists who partake in ecological education sessions and purchase local agriproducts may exhibit a significant discrepancy between the degree of participation in activities and degree of interest in them. Park managers are suggested to improve the quality of ecological education sessions and agriproducts on offer at points of sale in the recreation area. Furthermore, research findings showed that 60% of visitors come from northern Taiwan. Thus, park managers are recommended to offer more promotional campaigns and special packages to potential visitors based in central and eastern Taiwan.
As the effects of climate change worsen, the tourism industry will face increasingly threatening weather conditions. According to the results of this research, a general decline in travel intention occurred among tourists when they were confronted with the effects of climate change. Landslides were the severest climate change-induced factor highlighted by all interviewees. Support for adaptational policies addressing landslides indicated that the general public is eager for solutions that lead to landslide prevention as well as soil and water conservation, which also reflects the deep concern of tourists over the risks of landslides. On the other side of the coin, because Wuling National Forest Recreation Area is situated in a high-altitude region, heatwaves would instead lead to a significant increase in visitors’ intention to travel, because summer is tourist season in Taiwan. The substantial increase in visitor numbers during summer tends to cause overcrowding in the recreation area. This study recommends that park managers engage in wildlife conservation maintenance and intensive management of human-generated waste as part of its measures to prevent environmental destruction resulting from the overcrowding of visitors and their poor behavior. The numerous uncertainties associated with climate change-induced effects on tourists with varying degrees of place attachment prompted this research to consider natural hazards, including typhoons, landslides, and rainstorms. The results suggested that when the occurrence probability of natural hazards increases, tourists with varying degrees of place attachment react differently. Park managers are thus recommended to focus on protection and prevention measures associated with climate change-induced dangers to increase tourists’ revisit intention and address tourism volatility.
According to the results of this research, tourists with different degrees of place attachment did not exhibit significant differences in their responses to adaptational policies related to climate change. A consensus also existed in support of and in agreement with adaptational policy implementation. This study proposed that, because of the universal awareness of climate change worldwide, the general public is happy to accept relevant adaptational policies. Therefore, this study assumed that when managers fully implement applicable adaptational policies, the results will include a significant increase in tourists’ intention to travel regardless of their degree of place attachment. This phenomenon is likely correlated with tourists’ generally supportive attitude toward adaptational policies, and the difference for tourists with lower place attachment scores would also shrink. Therefore, this study strongly recommends that park managers implement relevant adaptational policies. Moreover, they ought to clearly and publicly demonstrate the results of their implementation for tourists to be made aware of the measures in place.
As for future research, this study recommends that in the questionnaire design phase, researchers can provide fuller and more detailed descriptions of the conditions of climate change factors to instruct the public on the associated weather conditions. For example, definitions of weather conditions could be added, or photos could be provided to inform interviewees about the specific climate change-induced conditions in question. This study also recommends that future research could include surveys that clarify the interviewees’ understanding of climate change topics or their attitudes toward the environment, to ensure higher-quality reference data for analytical purposes when studying tourists’ attitudes toward adaptational policies. Additionally, it is recommended that in future research, park managers should be interviewed to understand the operational aspects at work as well as managerial attitudes toward adaptational policy changes. Interviewing managers could have further benefits, such as providing subsequent research with directions and broadening the scope of discussion. Furthermore, it could contribute to identifying more practical suggestions and opinions regarding operation and management issues. Other research could focus on how to improve place attachment among tourists. This would not only encourage environmentally friendly behavior [86] but also boost visitors’ travel intention and mitigate the adverse effects of climate change on nature-based tourism.

Supplementary Materials

The following are available online at https://www.mdpi.com/1999-4907/12/2/171/s1, Table S1: Questionnaire.

Author Contributions

Three co-authors contributed to the completion of this article together. W.-Y.L. was the first author and contributed to conceptualizing the research framework, data analysis, the results and conclusion, and editing; H.-W.Y. mainly contributed to the conduction of research investigation, data analysis, and results and conclusion; C.-M.H. acted as a corresponding author on their behalf throughout the review, editing, results confirmation, and submission process. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Taiwan Ministry of Science and Technology, Reference No. MOST 108-2410-H-005-045-MY2, and MOST 107-2410-H-005-043-MY2.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to containing information that could compromise the privacy of research participants.

Conflicts of Interest

The authors declare no conflict of interest.

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Table 1. Indicators by category for assessing place attachment.
Table 1. Indicators by category for assessing place attachment.
Place Attachment IndicatorsQuestions by Indicators
Place identity
(Defined as the emotional attachment of a person to a specific place) [24]
I like Wuling National Forest Recreation Area very much.
Wuling National Forest Recreation Area is very important to me personally.
I have a strong sense of identity with the Wuling National Forest Recreation Area.
Wuling National Forest Recreation Area can reflect my personal characteristics and personality.
Place belonging
(Defined as people feel that they have achieved immersion in a locality, or that they have attained a sense of having become a part of the local community) [37]
I think I am part of the Wuling National Forest Recreation Area.
I think on the spiritual level, I have a certain degree of connection with the Wuling National Forest Recreation Area.
I feel that I can relax in Wuling National Forest Recreation Area.
I am happy to go to Wuling National Forest Recreation Area for recreation.
Place dependency
(Defined as a person’s reliance on bonding with a specific location) [24]
For me, I will give priority to traveling in Wuling National Forest Recreation Area compared to other places.
Satisfaction with tourism in Wuling National Forest Recreation Area is much more satisfactory than other forest recreation areas.
No other area can be compared with the Wuling National Forest Recreation Area
No other area can replace Wuling National Forest Recreation Area.
Wuling National Forest Recreation Area is a place where I can do things I like.
Wuling National Forest Recreation Area is my favorite place to come.
Table 2. Sociodemographic background of visitors and statistics of their recreational experiences.
Table 2. Sociodemographic background of visitors and statistics of their recreational experiences.
VariablesCategoryNumbersPercentage (%)
GenderMale11254.1
Female9545.9
MarriageMarried15574.9
Single5225.1
AgeUnder 18167.9
18–293918.2
30–4910953.2
50–644320.7
Level of EducationMiddle School42.0
High School3617.4
Undergraduate11656.0
Above Graduate5124.6
OccupationStudents3918.8
Public Employees2914.0
Industrial3717.9
Business3416.4
Service3215.5
Freelance2813.5
Agriculture, Forestry, Animal Husbandry31.5
Retried52.4
Salary
(New Taiwan dollar, NTD;
1 NTD = 0.03571 US dollar)
<20 thousand4320.7
20–40 thousand3818.8
40–60 thousand5828.1
60–80 thousand3516.9
80–100 thousand136.3
>100 thousand199.2
Place of ResidencyNorthern Taiwan12660.9
Central Taiwan5325.6
Southern Taiwan199.2
Eastern Taiwan94.3
Parks, Forest, Natural Environmental for Leisure ActivitiesLess than once a month6933.3
1–3 times a month9445.4
Once a week2110.1
2–3 times a week167.8
Above 4 times a week73.4
Expected time visiting in Wuling3 h94.3
5 h62.8
7 h62.8
2 days, 1 night8842.3
3 days, 2 nights9445.4
>4 days52.4
Participating Environmental Protection GroupYes2110.1
No18689.9
Table 3. Reliability analysis results.
Table 3. Reliability analysis results.
SectionsIndicatorsNumbers of QuestionCronbanch’s α Value
Place AttachmentPlace Identity40.838
Place Belonging40.808
Place Dependency60.659
Travel Intention Before Adaptational Strategy Implementation 80.845
Adaptation Policies 90.723
Travel Intention After Adaptational Strategy Implementation 80.883
Revisit Intention 30.837
Total 420.825
Table 4. Tally and ratio of activities participated in by tourists.
Table 4. Tally and ratio of activities participated in by tourists.
Recreational ActivitiesNumbersPercentage * (%)
Camping14871.5
Picnicking4722.7
Forest Bathing13464.7
Ecology Education4421.3
Researching73.4
Flora Appreciation7737.2
Agriproduct Purchasing4421.3
Trail Walking12258.9
Formosan Landlocked Salmon Observation7536.2
Alpine Hiking Trail4421.3
Bird Watching3315.9
Note 1: * This was a multiple-choice question, and hence the sum exceeds 100%.
Table 5. Tally and ratio of preferred tourist activities.
Table 5. Tally and ratio of preferred tourist activities.
Recreational ActivitiesNumbersPercentage * (%)
Camping14469.6
Picnicking5124.6
Forest Bathing16278.3
Ecology Education199.2
Researching52.4
Flora Appreciation4019.3
Agriproduct Purchasing83.9
Trail Walking7938.2
Formosan Landlocked Salmon Observation3918.8
Alpine Hiking Trail4119.8
Bird Watching167.7
Note 1: * This is a multiple-choice question, and hence the sum exceeds 100%.
Table 6. Results of place attachment grouping.
Table 6. Results of place attachment grouping.
CategoryLow DegreeMedium DegreeHigh DegreeTotal Sample
Numbers3511161207
Percentage (%)16.953.629.5100
Place Identity *3.013.854.693.96
Place Belonging *2.913.824.513.87
Place Dependency *2.653.544.373.63
Note 1: * Five-point scale results.
Table 7. Sociodemographic background and recreational experience based on place-attachment clusters.
Table 7. Sociodemographic background and recreational experience based on place-attachment clusters.
Sociodemographic Background & Recreational ExperiencePlace Attachment Level (%)ANOVA F/Chi Squaredfp Value
Low (n = 35)Medium (n = 111)High (n = 61)
Sex X2 = 0.17120.918
Male57.153.254.1
Female42.946.845.9
Age F = 4.37820.014 *
Average33.340.439.1
Level of Education X2 = 9.26980.320
Middle School5.70.91.6
High School17.113.524.6
Undergraduate54.356.855.7
Above Graduate22.928.818.1
Occupation X2 = 28.795140.011 *
Student37.115.314.8
Public Employee0.015.319.7
Industrial5.718.923.0
Business28.611.718.0
Service17.118.98.2
Freelance8.615.313.1
Agriculture, Forestry, and Animal Husbandry2.90.91.6
Retried0.03.71.6
Salary (NTD) F = 2.30320.160
<20 thousand37.120.711.5
20–40 thousand22.919.814.8
40–60 thousand11.426.141.0
60–80 thousand17.118.014.8
80–100 thousand2.96.38.2
>100 thousand8.69.19.7
Marriage X2 = 3.57620.167
Married68.680.268.9
Single31.419.831.1
Place of Residency X2 = 10.09960.121
Northern Taiwan60.060.462.3
Central Taiwan31.421.629.5
Southern Taiwan5.714.41.6
Eastern Taiwan2.93.66.6
Participating Environmental Protection Group X2 = 0.33920.844
Yes11.49.011.5
No88.691.088.5
Parks, Forest, Natural Environmental for Leisure Activities X2 = 10.50980.231
Less than once a month40.032.431.1
1–3 times a month40.044.150.8
Once a week20.09.76.6
2–3 times a week0.09.78.2
Above 4 times a week0.04.13.3
Expected time visiting in Wuling a F = 6.70320.002 **
3 h11.44.50.0
5 h8.62.70.0
7 h11.40.90.0
2 days, 1 night34.343.245.9
3 days, 2 nights31.445.952.5
>4 days2.92.81.6
Source: Study Archive. Note 1: * p < 0.05; ** p < 0.01. Note 2: a Welch’s analysis of variance (ANOVA) and Games–Howell post-hoc analysis.
Table 8. Tourist recreation activities based on place-attachment clusters.
Table 8. Tourist recreation activities based on place-attachment clusters.
Recreational ActivitiesPlace Attachment Level (%)Chi Squaredfp ValueCramer’s V
Low (n = 35)Medium (n = 111)High (n = 61)
Camping45.773.982.015.00620.001 **0.001
Picnicking17.119.831.13.62120.164
Forest Bathing62.959.575.44.45220.108
Ecology Education11.420.727.93.63220.163
Researching5.73.61.61.16620.558
Flora Appreciation31.439.636.10.81520.665
Agriproduct Purchasing11.422.524.62.53120.282
Trail Walking54.358.662.30.60420.739
Formosan Landlocked Salmon Observation28.635.142.62.02520.363
Alpine Hiking Trail34.315.324.66.29620.043 *0.043
Bird Watching17.114.418.00.43020.807
Note 1: * p < 0.05; ** p < 0.01. Note 2: This is a multiple-choice question, and hence the sum exceeds 100%.
Table 9. Revisit intention based on place-attachment clusters.
Table 9. Revisit intention based on place-attachment clusters.
Revisit IntentionPlace Attachment LevelANOVA F dfp Value
Low (n = 35) Medium (n = 111) High (n = 61)
Willing to visit Wuling again3.664.234.5618.02420.000 ***
Willing to recommend others to visit Wuling3.714.244.6218.48320.000 ***
Wuling is one of the priority attractions3.203.964.4434.37420.000 ***
Source: Study Archive. Note 1: *** p < 0.001.
Table 10. Attitudes toward adaptational policies based on place-attachment clusters.
Table 10. Attitudes toward adaptational policies based on place-attachment clusters.
Adaptation PoliciesTotal AveragePlace-Attachment LevelANOVA Fdfp Value
Low (n = 35)Medium (n = 111)High (n = 61)
Reduce park admission and accommodation cost3.233.433.193.200.62820.535
Set up more pavilions in the park to avoid tourists from heat stroke3.493.513.433.570.32120.726
Provide tourists with more indoor recreation opportunities3.253.173.233.330.23220.793
Strengthen the implementation of conservation Formosan Landlocked Salmon projects in the park4.274.174.214.442.06420.130
Building unique buildings in the area as a supplement to damaged natural scenery2.812.772.752.930.41420.661
Free shuttle bus to Wuling National Forest Recreation Area3.593.863.433.722.53420.082
Improving soil and water conservation within the recreation area to ensure the security of visitors a4.574.314.564.724.32320.014 *
Enhancing habitat conservation and Establishing a wildlife conservation district within the recreational area4.594.374.634.622.37220.096
Providing real-time weather forecast and environmental safety information within the recreation area4.504.294.554.532.33020.100
Note 1: * p value < 0.05. Note 2: a Welch’s ANOVA and Games–Howell post-hoc analysis.
Table 11. Tourists’ travel intention under pre-adaptational policy conditions based on place-attachment score clusters and climate factors.
Table 11. Tourists’ travel intention under pre-adaptational policy conditions based on place-attachment score clusters and climate factors.
Climate FactorsPlace Attachment LevelANOVA Fdfp Value
Low (n = 35)Medium (n = 111)High (n = 61)
Typhoon1.6572.1532.2305.83720.003 **
Landslides1.5141.9461.9844.25520.015 *
Heavy Rain1.6291.9732.1154.19820.016 *
Heatwave3.1713.8023.8365.27720.006 **
Coldwave2.4002.6312.7211.11920.329
Forest Fire1.8002.1352.1152.01920.135
Zoonotic Influenza a2.1432.4682.5742.76820.068
Biting Midges1.9432.2252.4923.14820.045 *
Note 1: * p < 0.05; ** p < 0.01. Note 2: a Welch’s ANOVA and Games–Howell post-hoc analysis.
Table 12. Tourists’ travel intention under pre-adaptational policy conditions based on place-attachment score clusters and climate factors.
Table 12. Tourists’ travel intention under pre-adaptational policy conditions based on place-attachment score clusters and climate factors.
Climate FactorsPlace Attachment LevelANOVA Fdfp Value
Low (n = 35)Medium (n = 111)High (n = 61)
Typhoon2.2862.5052.5901.18920.307
Landslides1.9712.2342.4262.46520.088
Heavy Rain2.1142.2972.4751.68820.187
Heatwave3.4864.1264.1806.57920.002 **
Coldwave2.2892.9822.9180.31120.733
Forest Fire2.1712.4052.4100.79720.452
Zoonotic Influenza2.2862.7302.9024.15820.017 *
Biting Midges2.2002.4232.7543.40620.035 *
Source: Study Archive. Note 1: * p < 0.05; ** p < 0.01.
Table 13. Average difference values of travel intention before and after the implementation of adaptational policies.
Table 13. Average difference values of travel intention before and after the implementation of adaptational policies.
Climate FactorsAverage Difference ValueStandard Deviationtdfp Value
Typhoon0.40100.7231−7.9782060.000 ***
Landslides0.36230.7031−7.4142060.000 ***
Heavy Rain0.36230.6455−8.0762060.000 ***
Heatwave0.32850.8351−5.6602060.000 ***
Coldwave0.31880.6422−7.1432060.000 ***
Forest Fire0.29470.6863−6.1782060.000 ***
Zoonotic Influenza0.26090.6306−5.9522060.000 ***
Biting Midges0.22710.6322−5.1672060.000 ***
Note 1: *** p < 0.001.
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Liu, W.-Y.; Yu, H.-W.; Hsieh, C.-M. Evaluating Forest Visitors’ Place Attachment, Recreational Activities, and Travel Intentions under Different Climate Scenarios. Forests 2021, 12, 171. https://doi.org/10.3390/f12020171

AMA Style

Liu W-Y, Yu H-W, Hsieh C-M. Evaluating Forest Visitors’ Place Attachment, Recreational Activities, and Travel Intentions under Different Climate Scenarios. Forests. 2021; 12(2):171. https://doi.org/10.3390/f12020171

Chicago/Turabian Style

Liu, Wan-Yu, Hung-Wen Yu, and Chi-Ming Hsieh. 2021. "Evaluating Forest Visitors’ Place Attachment, Recreational Activities, and Travel Intentions under Different Climate Scenarios" Forests 12, no. 2: 171. https://doi.org/10.3390/f12020171

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