Using multispecies occupancy models to improve the characterization and understanding of metacommunity structure

Area of Science:

• Ecology
• Conservation Biology
• Statistical Modeling

Background:

• Metacommunity ecology and occupancy modeling are key ecological frameworks.
• These frameworks have historically developed independently, despite complementary goals.
• The Elements of Metacommunity Structure (EMS) framework relies on accurate species occurrence data, which is often compromised by imperfect detection.

Purpose of the Study:

• To integrate multispecies occupancy models with the EMS framework to address imperfect detection.
• To develop a new framework, detection error-corrected EMS (DECEMS), for more accurate metacommunity structure analysis.
• To improve the understanding of species distributions and their relationship to environmental gradients.

Main Methods:

• Reviewed the existing Elements of Metacommunity Structure (EMS) framework.
• Introduced and applied a multispecies occupancy model.
• Integrated occupancy modeling with EMS to create the DECEMS framework, using repeated surveys to estimate occupancy and detection probabilities.

Main Results:

• Detection error in traditional EMS analyses often leads to misclassification of metacommunity structure.
• DECEMS significantly reduces bias by disentangling occupancy and detection probabilities.
• DECEMS can reduce structure misclassification rates by over 20%, even with low detection error.

Conclusions:

• Integrating occupancy models with the EMS framework provides a more robust and accurate method for ecological analysis.
• DECEMS enhances the ability to link species-level responses to environmental covariates with metacommunity-wide patterns.
• This integrated approach leads to more accurate descriptions of metacommunity structure and a better understanding of ecological mechanisms.