Previous CES studies that have used photographs from social media have treated them as homogenous indicators of cultural interest. The CES framework emphasizes the need for identifying beneficiaries, as well as identifying visitors in order to create non-homogenized recreation maps. Photograph content analysis enables the identification of a variety of cultural purposes. Flickr data analysis demonstrated spatial and temporal visitation patterns of distinct groups of users, which could contribute to better identification of CES beneficiaries. Applied approach for mapping the spatial distribution of CES on the Lithuanian coast has two advantages: 1) neutrality in terms of place, groups, and seasons and 2) cost and effort effectiveness. These levels of spatial detail are compatible with the scale of much environmental management, which commonly considers several single sites(Peh et al. 2020).
Our sample of photographs showing CES engagements in the study area, is likely to provide a good overview of CES engagement dynamics in the Lithuanian coastal part. Compared to previous studies, the number of photographs sampled in our research is considered robust (Richards and Friess 2015; Tenkanen et al. 2017). Other coastal studies, that used crowdsourced photographs, all specified a maximum of two thousand photographs per area. The high number of photographs collected in our research is remarkable given the limited land's strip and likely reflects the coastal zone's importance for tourism, since the number of photographs taken inside an area is known to correlate with the number of visitors(Hausmann et al. 2018) (Tenkanen et al. 2017; Wood et al. 2013).This is also evident from the temporal distribution of photographs, with user activity concentrated in the months of heavy tourism during the summer season, especially around popular travel holidays, summer holidays, and specific celebrations or events. While we recognize that care should be taken when interpreting temporal trends and visitor dynamics from social media data, these results were generally expected and reaffirm the potential of social media data analyses to provide insights on visitation patterns to coastal areas(Tenkanen et al. 2017; Wood et al. 2013).
Photographs have been distributed along the entire coast of Lithuania, with spots that have been identified in the major cities such as Klaipėda, Palanga, Nida and Juodkrantė that clearly emerge as the most important hotspots. This can be explained by the development of tourist and urban areas along the coast, with some of the main tourist attractions. This trend is likely to be partly driven by convenience and proximity to hotels, campsites, beaches, tourist sites, and historical monuments. Another relevant factor may be the presence of well-developed infrastructure for visitors in these areas: road net, walking paths, parking places Several activities for tourist have taken place in these areas; specifically, in Klaipeda, for example, tourist boat trips to the Curonian Spit or Curonian lagoon are available for visitors. This supports other recent studies showing an association between visitor infrastructure and photograph density(Ghermandi 2016; Richards and Friess 2015).
Birds and nature are predominant attractions in the northern part of the study area where the Baltic Sea Thalassologic Reserve is located, which explains the high concentration of photographs illustrating birds and plants. Other studies have confirmed that bird watching is a fast-growing recreational activity and has been described as a new variant of niche tourism, attracting often unsuspecting tourists(Connell 2009). The appreciation of landscape, being an important aspect, marked the largest percentage of photography (68.7%), followed by social recreation, where meeting with friends and family, leisure, visiting tourist places, and general social activities are the most important (44.9%). Identifying and attracting these tourists can be beneficial to the local economy. For example, about 98 million adults engage in activities such as bird watching, wildlife photography, hunting, and fishing and spend $59.5 billion a year in the United States alone(Özcan et al. 2009).
Our analysis has successfully captured the overlapping spatial dynamics of natural engagements and social leisure (Fig. 7). The clear spatial association of the different types of CES engagements is not surprising given that many types of CES are clustered along the study area(Ament et al. 2017; Plieninger et al. 2013; Raudsepp-hearne, Peterson, and Bennett 2010). CES analysis of bundles could potentially be used as an effective way to inform local management of opportunities to improve CES commitments or manage potential conflicts due to their spatial overlap. This information can be used to plan and keep track of ways to control visitor flow, like by building infrastructure assets(Jepson et al. 2017), or by putting spatial and temporal restrictions in place for better management.
Regional attractions are also important for visitors(Chazée and Valat 2016). The study also contains a comparative process between the number of photographs taken annually, and the number of annual visitors to Lithuania. Both graphs (Fig. 10) showed an assimilable trendline. The number of visitors, as well as the number of photographs taken, has grown from 2016 to 2019. The tourism economy has been hit hard by the coronavirus pandemic and by the measures that have been adopted to limit the spread of the virus, which has also impacted the number of visitors. This shock has led the international tourism economy to contract by 60–80% in 2020, which explains the huge drop in the number of visitors as well as the number of photographs taken annually. The curve resumed its growth in 2021. This rise is explained by the decision to lift the closure measures on recreational areas for leisure and relaxation, beaches and tourist attractions.
4.1 Supporting protected area management with social media data
Our findings suggest that data collected from social media may be used to better understand and monitor the extent to which CES involvement occurs in coastal regions across geographical and temporal dimensions. Additionally, such data may be utilized to determine which biophysical assets are associated with CES delivery(Retka et al. 2019). This is particularly true for services that do not correlate well with any other CES. Managers may utilize this data to determine the non-substitutability of CES(Valck et al. 2016), and integrate this information into more effective management strategies(Tenerelli, Demšar, and Luque 2016). According to(Daniel et al. 2012) promoting value-generating practices linked to unique CES can help people connect more deeply with nature, which could help them support biodiversity conservation and sustainable natural and coastal resource management in the long-term.
The long-term viability of coastal regions is highly reliant on community support. Identifying synergy between societal values and environmental aims may help managers develop effective communication methods that result in beneficial conservation results (Whitehead et al. 2014). In this context, social media data could be an additional tool to communicate the beneficial impacts of management actions and stimulate communication and interaction with coastal area staff to enhance relationships with community members. Additionally, it may be beneficial to monitor community-based initiatives to restore biodiversity, which often result in the provision of CES such as educational and recreational opportunities(Krasny et al. 2014).
4.2 Model Limitation
The Flickr analysis enabled the identification of distinct actor groups that are important for coastal managers; nevertheless, it must be emphasized that particular actors were not as numerous as other CES groups. Several CES categories were underrepresented in the current study, including natural objects and monuments, religious activities, and fishing. This is unlikely to reflect the true value of the Lithuanian coast for these types of CES, given that the fisheries and aquaculture sectors (which are primarily derived from processing activities) account for less than 0.5 percent of Lithuania's GDP and that the majority of Lithuania's fishing ports are located in coastal cities (Klaipėda, Nida and Šventoji). Fishing activities, as well as natural buildings and monuments, are unlikely to be documented by Flickr, since neither the participants nor any passing viewers may believe they are worthy of recording. A similar problem may occur with religious/spiritual emotions and appreciation, since photographing and sharing religious moments or devotional behaviors on public social media accounts may be seen disrespectful. In this regard, social media data should be seen as a complement to (rather than a substitute for) more conventional social survey methods. Recent work has tried to establish approaches for incorporating diverse data sources (Vieira et al., 2018) in order to allow the inclusion of other social groups in CES analyses, although further work in this area is certainly required. Finally, as mentioned before, the quality and endurance of photographic data collected through the internet may be compromised as a result of changes to user privacy settings or platform modifications, such as Application Programming Interfaces(Ladle et al. 2016). Despite the enormous potential for social media data to contribute in coastal area management and monitoring, Flickr data is biased by variables that are always changing, such as the platform's popularity, user demographics, and location(Sessions et al. 2016). Flickr is widely used in the United States and Western Europe(Noam Levin,Salit Kark n.d.), and hence was an appropriate choice for our research. There are other popular photo-sharing social media platforms, including Flickr, Panoramio, and Instagram(Gibbons 2015), however Instagram presently has the greatest user base and seems to be the most accurate representation of visitor numbers (Tenkanen et al. 2017). However, subsequent changes to the Instagram API and Terms of Service have restricted researchers' access to photographs, which will likely limit the platform's usability for comparable future studies. Similar adjustments and limits apply to other sites, restricting researchers' access to publicly published pictures. This is likely to bias samples toward privileged actors and engagements of a certain sort(Hirons, Comberti, and Dunford 2016). For instance, the Lithuanian coast receives hundreds of thousands of visits each year, but only a few hundreds of them were included in our sample, which is presumably driven in part by variables related to technology availability and adoption. Additionally, some kinds of interactions with natural environments are more prevalent on particular social media platforms than on others(Hausmann et al. 2018), implying that a thorough evaluation of CES engagements may need cross-platform study.