Modelling interactive effects of biological and environmental factors on fine-scale coral settlement patterns

Research output: Contribution to journalArticlepeer-review

Abstract

For sessile organisms with dispersive propagules, the habitat in which propagules settle plays a key role in determining post-settlement survival, which is fundamental for the maintenance and recovery of populations. Corals provide an interesting example, as an array of bio-physical settlement cues, along with other environmental conditions such as current flow and habitat distribution, can influence where larvae settle. The ways in which these processes interact to influence spatial patterns of coral settlement remain largely unexplored, due to the difficulty in directly observing and measuring the dispersal and settlement of tiny (≤ 1 mm) larvae in-situ. To help address this knowledge gap, we developed a mechanistic simulation model to explore how three overarching factors — (1) the attractiveness of reef substrates, (2) local hydrodynamics and (3) the spatial distribution of reef substrates — might interact to influence fine-scale (centimetres to metres) spatial patterns of settlement. Through scenario exploration, we found that interactions among these three factors can lead to contrasting, and sometimes counterintuitive, spatial patterns of settlement. By simulating common field survey methods (settlement tiles and quadrat sampling) we show that interactions among biological and environmental factors could lead to incorrect conclusions, regarding, for example, the substrates larvae prefer for settlement. Lastly, with a case study from Ningaloo Reef, Western Australia, we illustrate how the model can help explore mechanisms underlying patterns of settlement within complex benthic landscapes and highlight key gaps in knowledge for future empirical research. Our results have implications for understanding and sampling spatial recruitment patterns in not only corals, but any organism with both dispersing and sessile life stages.

Original languageEnglish
Article number111037
Pages (from-to)1-13
Number of pages13
JournalEcological Modelling
Volume502
Early online date6 Feb 2025
DOIs
Publication statusPublished - Mar 2025

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