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Dryad

Invertebrate abundance sampled by benthic trawl and grab from common sites

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Aug 10, 2023 version files 34.51 KB

Abstract

Aim: Long-term monitoring of offshore benthic communities provides data which are essential for effective marine management. Due to the expense and difficulty of sampling the seafloor comprehensively, monitoring is often limited to one sampling method targeting a specific community. In these cases, biological surrogacy is a useful monitoring approach and can be based on more easily sampled community diversity indices or assemblage patterns across the monitoring sites. This study aimed to quantify marine benthic invertebrate cross-community congruence and test surrogate effectiveness.

Location: Southern Benguela Shelf ecoregion on the west coast of South Africa.

Methods: We compared two benthic biological datasets collected from the same 24 sites: epifauna sampled by demersal research trawl and infauna sampled by grab. This study utilised co-correspondence analysis (CoCA) to test for congruence in assemblage patterns between communities and test community surrogacy.

Results: Significant linear relationships were found between epifauna and infauna species abundance, richness (d), and diversity (H’loge). Symmetric co-correspondence analysis (sCoCA) found the common variance captured by the first four axes to explain 40% and 24% of the total epifauna and infauna assemblage variation, respectively. Environmental gradients played a key role in structuring these similarities in broadscale biodiversity patterns. Predictive co-correspondence analysis (pCoCA) showed that epifauna assemblage structure did not significantly predict infauna assemblage structure, but infauna did predict 14% of the variation in epifauna assemblage structure.

Main conclusions: Epifauna and infauna communities were structured similarly but do not predict each other; community congruence does not imply effective surrogacy. These findings should be considered when including different benthic biological datasets into ecosystem classification and mapping, and provides a statistical framework for testing community congruence and surrogate effectiveness.