Forecasting the future of life in Antarctica

Antarctic ecosystems are under increasing anthropogenic pressure, but efforts to predict the responses of Antarctic biodiversity to environmental change are hindered by considerable data challenges. Here, we illustrate how novel data capture technologies provide exciting opportunities to sample Antarctic biodiver-sity at wider spatiotemporal scales. Data integration frameworks, such as point process and hierarchical models, can mitigate weaknesses in individual data sets, improving confidence in their predictions. Increasing process knowledge in models is imperative to achieving improved forecasts of Antarctic biodiversity, which can be attained for data-limited species using hybrid modelling frame-works. Leveraging these state-of-the-art tools will help to overcome many of the data scarcity challenges presented by the remoteness of Antarctica, enabling more robust forecasts both near-and long-term.

Automated summary

Antarctic ecosystems are facing increasing anthropogenic pressure, and predicting the impact of environmental change on Antarctic biodiversity is challenging due to data limitations. However, new data capture technologies provide opportunities to sample Antarctic biodiversity at broader scales. Integration of data sets through frameworks such as point process and hierarchical models can improve predictions and increase confidence. Further improvement in models through increased process knowledge and the use of hybrid modeling frameworks can enhance forecasts for data-limited species. Leveraging these advanced tools can overcome data scarcity challenges in Antarctica and facilitate more robust short-term and long-term forecasts.