Comparative analysis of organismal trait variation in benthic cnidarians
Journal
Coral Reefs
ISSN
0722-4028
1432-0975
Date Issued
2025-12-21
Author(s)
Abstract
Trait-based approaches compare organisms based on their attributes, providing insights into species’ responses to stressors and roles in community dynamics. In coral reefs, such approaches have often focused on individual taxonomic groups—e.g., scleractinians, fishes, or algae—limiting opportunities for cross-taxa comparisons and broader ecological interpretation. Here, we present a framework for comparing energy-related response traits (traits reflecting organisms’ responses to their environment) across 13 benthic cnidarian taxa (three classes, seven orders), accounting for individual variation. By constructing a unified trait space, we characterize performance niches and identify ecological strategies that underpin resilience or vulnerability. Integrating an existing dataset further demonstrates the framework’s scalability and adaptability, enhancing trait space resolution and enabling robust cross-species comparisons when sample sizes permit. The thirteen taxa occupy distinct regions of the trait space, indicating niche partitioning. The addition of new individuals improves interpretation of taxa performance, revealing species-specific responses in Psammocora profundacella and Stylophora pistillata, which highlight how environmental conditions filter individuals and drive trait-based selection. Two main strategies emerge: (i) primarily autotrophic reef builders with high functional diversity and (ii) more or fully heterotrophic non-reef builders with low trait variability, reflecting different energy flow pathways among benthic cnidarians and their potential implications for disturbance response. As photosynthetically dependent taxa appear increasingly threatened under global change, heterotrophic species may gain dominance on degraded reefs. Further validation of trait proxies for energy flow, along with expanded taxonomic, spatial, and temporal coverage, is essential to advance predictions of community function and reef trajectories
Subjects
Coral reef
Energy flow
Individual variation
Niche partitioning
Response trait
Trait-based approach
SDGs
Publisher
Springer Science and Business Media LLC
Type
journal article