Predicting the Threat Status of Mosses Using Functional Traits.

Area of Science:

• Botany
• Conservation Biology
• Ecology

Background:

• Mosses represent an early plant lineage with significant ecosystem roles, yet many face extinction threats.
• Global assessment of moss extinction risk is limited, with only ~300 of 13,000 species evaluated by the IUCN Red List.
• Functional traits are established predictors of extinction risk in other plant groups.

Purpose of the Study:

• To evaluate the predictive power of functional traits for moss extinction risk.
• To develop models for assessing extinction risk in moss species.
• To identify traits indicative of threatened moss species.

Main Methods:

• Compiled a dataset of 15 functional traits for 723 moss species globally.
• Utilized binary generalized linear models to analyze trait-extinction risk relationships.
• Applied predictive models to Data Deficient (DD) species to prioritize assessments.

Main Results:

• Monoicous species showed higher extinction risk compared to dioicous species.
• Traits such as the presence of a sporophyte, vegetative reproduction, and erect capsules reduced extinction risk.
• Longer capsules, setae, stems, and broader substrate ranges were associated with lower extinction risk.
• Effective predictive models were developed using a limited set of traits.

Conclusions:

• Functional traits effectively predict extinction risk in mosses, offering a novel conservation tool.
• These models can accelerate IUCN Red List assessments and identify species most in need of conservation.
• The study introduces novel traits for moss conservation research, enhancing future efforts.