Merging theory and experiments to predict and understand coextinctions.

Area of Science:

• Ecology
• Conservation Biology
• Biodiversity Science

Background:

• Ecological extinction cascades, where the loss of one species triggers further extinctions, are a growing concern in the face of mass extinction.
• Current simulation models often fail to accurately predict the real-world outcomes of extinction cascades, highlighting a gap between theoretical predictions and empirical observations.
• Species removal experiments reveal unexpected ecological interactions, further complicating predictions based solely on simulations.

Purpose of the Study:

• To evaluate the predictive accuracy of extinction simulation studies by validating them with observational and experimental data.
• To introduce a novel framework that integrates both simulation and empirical approaches for a more comprehensive understanding of extinction cascades.
• To identify new avenues for connecting ecological theory with real-world data in the study of species loss.

Main Methods:

• Reviewing and comparing predictions from extinction cascade simulations with findings from observational studies.
• Analyzing data from species-removal field experiments to identify discrepancies and novel interactions not captured by simulations.
• Developing a unified theoretical framework that incorporates both simulation modeling and empirical evidence.

Main Results:

• A significant mismatch exists between the outcomes predicted by extinction cascade simulations and empirical observations, including field experiments.
• Species removal experiments have demonstrated the occurrence of novel ecological interactions following species loss, which are often absent in simulation models.
• The proposed integrated framework offers a more robust approach to studying and predicting extinction cascades.

Conclusions:

• The predictive value of current extinction simulation studies is limited due to a lack of validation with empirical data.
• Integrating simulation models with observational and experimental data is essential for accurately understanding and predicting the consequences of species loss.
• The developed framework provides a pathway to bridge the gap between ecological theory and empirical research, enhancing our ability to address biodiversity loss.