Habitat structural complexity metrics improve predictions of fish abundance and distribution. Issue 7 (4th December 2017)

• Record Type: Journal Article
• Authors: Ferrari, Renata; Malcolm, Hamish A.; Byrne, Maria; Friedman, Ariell; Williams, Stefan B.; Schultz, Arthur; Jordan, Alan R.; Figueira, Will F.
• Is Part Of: Ecography. Volume 41:Issue 7(2018)
• Page Start: 1077
• Page End: 1091
• Publication Date: 2017-12-04
• Subjects: Ecology -- Periodicals; Biodiversity -- Periodicals; 574.5
• DOI: 10.1111/ecog.02580
• Languages: English
• ISSNs: 0906-7590

Abstract

Abstract : Habitat structural complexity influences biotic diversity and abundance, but its influence on marine ecosystems has not been widely addressed. Recent advances in computer vision and robotics allow quantification of structural complexity at higher‐resolutions than previously achieved. This provides an important opportunity to determine the ecological role of habitat structural complexity in marine ecosystems. We used high‐resolution three‐dimensional (3D) maps to test multiple structural complexity metrics, depth and benthic biota as surrogates of fish assemblages across hundreds of meters on subtropical reefs. Non‐parametric multivariate statistics were used to determine the relationship between these surrogates and the entire fish assemblage. Fish were divided into functional groups, which were used to further investigate the relationship between surrogates and fish abundance using generalized linear models. Fish community composition and abundance were strongly related to habitat complexity metrics, benthic biota and depth. Surface rugosity and its variance had a significant positive influence on the abundance of piscivores and sediment infauna predators, and a negative effect on the abundance of predators, herbivores, planktivores and cleaners. Final models for fish functional groups explained up to 68% of the variance. The best metrics to explain the variance in fish abundance were benthic biota (25 ±7.5% of variance explained, mean ± SE) and complexity metrics (16 ±6.6%, mean ± SE). Our results show that high‐resolution 3D maps and derived metrics can predict a large percentage of variance in fish abundance and potentially serve as useful surrogates of fish abundance across all functional groups in spatially dynamic reefs.