Predictive ability of a process-based versus a correlative species distribution model.

Area of Science:

• Ecology
• Evolutionary Biology
• Biogeography

Background:

• Species distribution models (SDMs) are crucial in ecology and evolution.
• Evaluating SDM transferability to new regions is essential but infrequently performed.

Purpose of the Study:

• To contrast the transferability of process-based and correlative SDMs.
• To assess model performance in native versus adventive ranges.

Main Methods:

• Compared MaxEnt (correlative) and TTR-SDM (process-based) models.
• Used 664 Australian eucalypt and acacia species data.
• Trained models in Australia and tested predictions in adventive ranges.

Main Results:

• MaxEnt performed better within the training domain (Australia).
• TTR-SDM demonstrated superior predictive ability outside Australia.
• Process-based models showed higher transferability.

Conclusions:

• Process-based models may be more suitable for predicting species distributions in novel environments.
• Correlative models may be less reliable for projections beyond their training data domain.
• Further case studies are needed to confirm these findings.