Using ancient sedimentary DNA to forecast ecosystem trajectories under climate change

Area of Science:

• Paleoecology
• Ecology
• Climate Change Science

Background:

• Ecosystem dynamics are complex and difficult to forecast.
• High-quality historical species abundance data is crucial for ecological models.
• Sedimentary ancient DNA (sedaDNA) offers a novel approach to reconstructing past ecosystems.

Purpose of the Study:

• To outline the potential of sedaDNA for forecasting ecosystem changes.
• To demonstrate how sedaDNA time series can inform ecological models.
• To highlight the integration of sedaDNA with modeling for robust predictions.

Main Methods:

• Utilizing sedaDNA to generate high-resolution time series of past species abundance.
• Analyzing sedaDNA data for taxonomic resolution beyond traditional microfossils.
• Combining sedaDNA-derived paleo-time series with process-based and inverse modeling.

Main Results:

• SedaDNA provides species-level abundance data, particularly for vascular plants and mammals.
• Paleo-time series from sedaDNA allow quantification of biotic interactions and dispersal rates.
• Integration of sedaDNA with modeling enables characterization of underlying biotic and abiotic processes.

Conclusions:

• SedaDNA significantly enhances our ability to document past ecosystem dynamics.
• Dynamic models informed by sedaDNA can provide robust forecasts of future ecosystem responses to climate change.
• This approach moves beyond contemporary data limitations for ecological prediction.