Correction to: Status and trends of circumpolar peregrine falcon and gyrfalcon populations

While collating contributions and comments from 36 researchers, the coordinating authors accidentally omitted Dr. Suzanne Carrière from the list of contributing co-authors. Dr. Carrière’s data are described in Tables 1 and 3, Figure 2 and several places in the narrative. The new author list is thus updated in this article.     

Exploring human–nature interactions in national parks with social media photographs and computer vision

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human–nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human–nature interactions can be extracted from user-generated photographs with computer vision. The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.     

A framework for investigating illegal wildlife trade on social media with machine learning

Article impact statement: Machine learning can be used to automatically monitor and assess illegal wildlife trade on social media platforms.     

Benchmark Criteria: A Tool for Selecting Appropriate Models in the Field of Water Management

A milestone in the field of European water protection policy is the European Union’s Water Framework Directive (WFD), which came into force in December 2000 and which integrates the management of European waters in many ways. In this study, we start by focusing on management issues connected to the implementation of the WFD and pose a question: “what type of models would be the most suitable for use in the context of the WFD?” With this question in mind, we aim to establish a set of operational and functional selection criteria for (computer) models whose application is intended to support decision-making related to a particular water management issue. These so-called “benchmark criteria” should help water managers and other model users in choosing appropriate models, e.g., for the WFD implementation purposes. We first describe models and their use in general and then propose an approach for setting the benchmark criteria for models, basing it on the concept of uncertainty management, while keeping firmly in mind the important role of citizens and citizen organizations in water management. The suggested benchmark criteria are in the form of 14 questions through which each model can be evaluated. Finally, the process for testing and refining the benchmark criteria is highlighted.     

Strategic accident reduction in an energy company and its resulting financial benefits

This study provides a case example of an energy company that prioritized occupational safety and health and accident reduction as long-term, strategic development targets. Furthermore, this study describes the monetary benefits of this strategic decision. Company-specific accident indicators and monetary costs and benefits are evaluated. During the observation period (2010–2016), strategic investments in occupational safety and health cost the company EUR 0.8 million. However, EUR 1.8 million were saved in the same period, resulting in a 2.20 cost–benefit ratio. The trend in cost savings is strongly positive. Annual accident costs were EUR 0.4 million lower in 2016 compared to costs in 2010. This study demonstrates that long-term, strategic commitment to occupational safety and health provides monetary value.     

Status and trends of circumpolar peregrine falcon and gyrfalcon populations

Ambio - The peregrine falcon (Falco peregrinus) and the gyrfalcon (Falco rusticolus) are top avian predators of Arctic ecosystems. Although existing monitoring efforts are well established for both...