Among-site variability in the stochastic dynamics of East African coral reefs

TL;DR

This study analyzes 22 years of reef data to understand how variability among sites affects long-term reef composition predictions, highlighting the importance of among-site variability for conservation planning.

Contribution

It introduces a Bayesian state-space modeling approach that incorporates among-site variability to improve long-term reef dynamics predictions.

Findings

Among-site variability contributes more to long-term reef variability than temporal factors.

Individual reef sites are more predictable than previously believed.

Identified potential climate refugia with high conservation value.

Abstract

Coral reefs are dynamic systems whose composition is highly influenced by unpredictable biotic and abiotic factors. Understanding the spatial scale at which long-term predictions of reef composition can be made will be crucial for guiding conservation efforts. Using a 22-year time series of benthic composition data from 20 reefs on the Kenyan and Tanzanian coast, we studied the long-term behaviour of Bayesian vector autoregressive state-space models for reef dynamics, incorporating among-site variability. We estimate that if there were no among-site variability, the total long-term variability would be approximately one third of its current value. Thus among-site variability contributes more to long-term variability in reef composition than does temporal variability. Individual sites are more predictable than previously thought, and predictions based on current snapshots are informative about long-term properties. Our approach allowed us to identify a subset of possible climate refugia sites with high conservation value, where the long-term probability of coral cover <= 0.1 was very low. Analytical results show that this probability is most strongly influenced by among-site variability and by interactions among benthic components within sites. These findings suggest that conservation initiatives might be successful at the site scale as well as the regional scale.