Integrating cultural dimensions into the ecosystem service framework is essential for appraising non-material benefits stemming from different human-environment interactions.This study investigates how the actual provision of cultural services is distributed across the landscape according to spatially varying relationships. The final aim was to analyse how landscape settings are associated to people's preferences and perceptions related to cultural ecosystem services in mountain landscapes. We demonstrated a spatially explicit method based on geo-tagged images from popular social media to assess revealed preferences. A spatially weighted regression showed that specific variables correspond to prominent drivers Accepted to Ecological Indicators (Dec 2015)2 of cultural ecosystem services at the local scale. The results of this explanatory approach can be used to integrate the cultural service dimension into land planning by taking into account specific benefiting areas and by setting priorities on the ecosystems and landscape characteristics which affect the service supply. We finally concluded that the use of crowdsourced data allows identifying spatial patterns of cultural ecosystem service preferences and their association with landscape settings.Keywords: non-material ecosystem benefits; cultural service preferences; social perceptions; photoseries analysis; spatially varying relationships; land use planning; recreational choice. Highlights Revealed preferences of ecosystem service can be acquired from online platforms  Spatially varying relationships were analysed trough a geographically weighted regression  Environmental and opportunity settings are locally related to cultural services  Habitat, accessibility, and view-points have a major impact on the service supply  Spatial statistical models can be used to identify priority for land use planning

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In the Mediterranean Region, habitat loss and fragmentation severely affect coastal wetlands, due to the rapid expansion of anthropogenic activities that has occurred in the last decades. Landscape metrics are commonly used to define landscape patterns and to evaluate fragmentation processes. This investigation focuses on the performance of a set of landscape pattern indices within landscapes characterized by coastal environments and extent below 1,000 ha. The aim is to assess the degree of habitat fragmentation for the monitoring of protected areas and to learn whether values of landscape metrics can characterize fine-resolution landscape patterns. The study areas are three coastal wetlands belonging to the Natura 2000 network and sited on the Adriatic side of Apulia (Southern Italy). The Habitat Maps were derived from the Vegetation Maps generated integrating phytosociological relevés and Earth Observation data. In the three sites, a total of 16 habitat types were detected. A selected set of landscape metrics was applied in order to investigate their performance in assessing fragmentation and spatial patterns of habitats. The final results showed that the most significant landscape patterns are related to highly specialized habitat types closely linked to coastal environments. In interpreting the landscape patterns of these highly specialized habitats, some specific ecological factors were taken into account. The shape indices were the most useful in assessing the degree of fragmentation of habitat types that usually have elongated morphology along the shoreline or the coastal lagoons. In all the cases, to be meaningful, data obtained from the application of the selected indices were jointly assessed, especially at the class level.

Interactions between people and ecological systems, through leisure or tourism activities, form a complex socio-ecological spatial network. The analysis of the benefits people derive from their interactions with nature—also referred to as cultural ecosystem services (CES)—enables a better understanding of these socio-ecological systems. In the age of information, the increasing availability of large social media databases enables a better understanding of complex socio-ecological interactions at an unprecedented spatio-temporal resolution. Within this context, we model and analyze these interactions based on information extracted from geotagged photographs embedded into a multiscale socio-ecological network. We apply this approach to 16 case study sites in Europe using a social media database (Flickr) containing more than 150,000 validated and classified photographs. After evaluating the representativeness of the network, we investigate the impact of visitors’ origin on the distribution of socio-ecological interactions at different scales. First at a global scale, we develop a spatial measure of attractiveness and use this to identify four groups of sites. Then, at a local scale, we explore how the distance traveled by the users to reach a site affects the way they interact with this site in space and time. The approach developed here, integrating social media data into a network-based framework, offers a new way of visualizing and modeling interactions between humans and landscapes. Results provide valuable insights for understanding relationships between social demands for CES and the places of their realization, thus allowing for the development of more efficient conservation and planning strategies.

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