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Natural water treatment systems have long been recognized as sources of ancillary benefits in the form of cultural ecosystem services. To date, there is a lack of quantitative understanding of the extent and welfare impact of such benefits. This paper investigates 166 natural treatment systems worldwide and provides the first quantitative assessment of their recreational and educational benefits. The public use is highly influenced by the type of recreational activities, presence of recreational and educational facilities, and accessibility of the systems. Using value transfer techniques, we estimate the mean and median monetary values of recreational benefits in 8397 and 530 €/ha/year, respectively. We compare such value flows with operation and management costs and other ecosystem services provided by these systems. [ABSTRACT FROM AUTHOR]

• We characterize direct human-nature interactions with geotagged SNS data. • We investigate visitation in 568 protected areas in Israel and West Bank. • Combining multiple SNS sources improves fit with observed data and predictive power. • Photo content analysis reveals visitors' interests and differences among SNSs. • Photogenic sites and inland waters are over- and under-represented in SNS data. Recent advances in geotagging, sharing and automatically analyzing online content from Social Networking Sites (SNS) offer unprecedented opportunities for the analysis of human-nature interactions. Previous studies in this field, however, offer limited insights regarding the benefits of automated content analysis especially at large scales, biases arising from the selection of SNS sources, and the predictive power of visitation models based on SNS data. We explore quantitative and qualitative aspects related to intensity, interests and sentiments associated with on-site experiences in 568 protected areas in Israel and the Palestinian Authority. We analyze counts and content of >100,000 photographs and tweets from four different SNSs, calibrate visitation models and predict visitation in unmonitored sites, cluster sites based on the typology of human-nature interactions reflected in online photographs, and characterize the polarity of sentiments associated with experiences in individual sites and clusters thereof. We find benefits in combining data from multiple sources and controlling for biases related to sites' photogenicity and type of human-nature interactions. Our results suggest that current best estimates of visitation in unmonitored sites underestimate by 39% the actual number of visits. We discuss how the techniques and findings in this study are applicable in the broader context of the management and conservation of sites of environmental or cultural interest. [ABSTRACT FROM AUTHOR]