Opportunistic reporting of species occurrences by members of the public has become a major source of biodiversity data, due in part to advances in technologies that allow volunteers to easily record species observations in online databases. This method of data collection, which is part of the broader citizen science movement, has great potential to inform research into spatial and temporal patterns in species distributions. But the unsystematic way that these data are collected creates challenges for data analysis. Among other issues, citizen science species occurrence data tend to be presence-only. Additionally, opportunistic sampling is often characterized by unknown spatial, temporal, and taxonomic biases. Many recent studies have focused on improving statistical approaches for analyzing presence-only citizen science data, but there has not yet been an effort to develop a systematic map of the different approaches used to analyze this type of data or to assess the connectedness and impact of these various methods through bibliometric analysis.
Results/Conclusions
We have developed a systematic map of the literature to inventory and categorize the statistical approaches used to analyze presence-only occurrence data. Further, we have implemented bibliometric analyses to characterize the relationships between these approaches. We expect that the results of our review will be useful for researchers using presence-only data to address ecological questions as well as for researchers working to develop new statistical approaches for this type of data. By identifying the characteristics of and connections between the diverse approaches to the analysis of presence-only species occurrence data, our results may also help citizen science practitioners to design citizen science programs which produce data that are well-suited for current analysis approaches.