Pokémon Go, an augmented reality (AR) smartphone game, replicates many aspects of real-world wildlife watching and natural history by allowing players to find, capture, and collect Pokémon, which are effectively virtual animals. In this article, we consider how the unprecedented success of Pokémon Go as a smartphone game might create opportunities and challenges for the conservation movement. By encouraging players to go outside and consider various aspects of virtual species' biology, the game could increase awareness and engagement with real-world nature. However, interacting with Pokémon could alternatively encourage exploitation of wildlife or replace players' desire to interact with real-world nature. We suggest a number of ways in which Pokémon Go could be adapted to increase its conservation impact, and how new conservation-orientated AR games could be created. We conclude that Pokémon Go sets a precedent for well-implemented AR games from which the conservation movement could borrow a number of ideas.

Modern conservation operates at the nexus of biological and social influences. While the importance of social and cultural factors are often mentioned, defining, measuring and comparing them remains a significant challenge. Here, we explore a novel method to quantify cultural interest in all extant reptile species using Wikipedia-a large, open-access online encyclopaedia. We analysed all page views of reptile species viewed during 2014 in all of Wikipedia's language editions. We compared species' page view numbers across languages and in relationship to their spatial distribution, phylogeny, threat status and various other biological attributes. We found that while the top three species with respect to page views are shared across major language editions, beyond these, page view ranks of species tend to be specific to particular language editions. Interest within a language is mostly focused on reptiles found in the regions where the language is spoken. Overall, interest is greater for reptiles that are venomous, endangered, widely distributed, larger sized and that have been described earlier. However, within individual families not all the above factors predict page views. Most families contain at least one species in the top 5% of page views, but 29 families (with 1450 species) have no 'high interest species' in them. Overall, our analyses elucidate novel patterns of human interests in nature over large geographical, cultural and taxonomic spectra using big-data techniques. Such approaches hold much promise for incorporating social perceptions in future conservation practices.

Phenology plays an important role in many human–nature interactions, but these seasonal patterns are often overlooked in conservation. Here, we provide the first broad exploration of seasonal patterns of interest in nature across many species and cultures. Using data from Wikipedia, a large online encyclopedia, we analyzed 2.33 billion pageviews to articles for 31,751 species across 245 languages. We show that seasonality plays an important role in how and when people interact with plants and animals online. In total, over 25% of species in our data set exhibited a seasonal pattern in at least one of their language-edition pages, and seasonality is significantly more prevalent in pages for plants and animals than it is in a random selection of Wikipedia articles. Pageview seasonality varies across taxonomic clades in ways that reflect observable patterns in phenology, with groups such as insects and flowering plants having higher seasonality than mammals. Differences between Wikipedia language editions are significant; pages in languages spoken at higher latitudes exhibit greater seasonality overall, and species seldom show the same pattern across multiple language editions. These results have relevance to conservation policy formulation and to improving our understanding of what drives human interest in biodiversity.

Digital Data Sources and Methods approaches to explore connections between topics, time-series analysis for temporal data, and spatial modeling to highlight spatial patterns. Outstanding challenges associated with culturomics research include issues of interdisciplinarity, ethics, data biases, and validation. The practical guidance we offer will help conservation researchers and practitioners identify and obtain the necessary data and carry out appropriate analyses for their specific questions, thus facilitating the wider adoption of culturomics approaches for conservation applications.

Conservation strategies based on charismatic flagship species, such as tigers, lions, and elephants, successfully attract funding from individuals and corporate donors. However, critics of this species-focused approach argue it wastes resources and often does not benefit broader biodiversity. If true, then the best way of raising conservation funds excludes the best way of spending it. Here we show that this conundrum can be resolved, and that the flagship species approach does not impede cost-effective conservation. Through a tailored prioritization approach, we identify places containing flagship species while also maximizing global biodiversity representation (based on 19,616 terrestrial and freshwater species). We then compare these results to scenarios that only maximized biodiversity representation, and demonstrate that our flagship-based approach achieves 79−89% of our objective. This provides strong evidence that prudently selected flagships can both raise funds for conservation and help target where these resources are best spent to conserve biodiversity.

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The recent growth of online big data offers opportunities for rapid and inexpensive measurement of public interest. Conservation culturomics is an emerging research area that uses online data to study humannature relationships for conservation. Methods for conservation culturomics, though promising, are still being developed and refined. We considered the potential of Wikipedia, the online encyclopedia, as a resource for conservation culturomics and outlined methods for using Wikipedia data in conservation. Wikipedia's large size, widespread use, underlying data structure, and open access to both its content and usage analytics make it well suited to conservation culturomics research. Limitations of Wikipedia data include the lack of location information associated with some metadata and limited information on the motivations of many users. Seven methodological steps to consider when using Wikipedia data in conservation include metadata selection, temporality, taxonomy, language representation, Wikipedia geography, physical and biological geography, and comparative metrics. Each of these methodological decisions can affect measures of online interest. As a case study, we explored these themes by analyzing 757 million Wikipedia page views associated with the Wikipedia pages for 10,099 species of birds across 251 Wikipedia language editions. We found that Wikipedia data have the potential to generate insight for conservation and are particularly useful for quantifying patterns of public interest at large scales.