Early Ecosystem Function Recovery at the Restoration Site
Early Ecosystem Function Recovery at a Coral Restoration site Revealed Through Process-Based Monitoring Indicators
Coral reef restoration is increasingly implemented worldwide, yet monitoring commonly focuses on structural endpoints such as survival or coral cover rather than ecological function. This study evaluates early signals of ecosystem function recovery at a coral restoration site established on a degraded rubble reef within the Nusa Penida Marine Protected Area, Indonesia. Monitoring was conducted across 76 artificial reef structures using diver observations and orthogonal photography to quantify benthic composition, structural development, recruitment pathways, trophic interactions, and transplant health. Relationships among monitoring indicators were examined using Spearman correlation analysis to identify linkages between ecosystem characteristics at both the restoration structure and colony levels. Live hard coral and soft coral cover increased significantly with structure age (ρ = 0.60 and 0.50 respectively, p < 0.001), indicating early benthic succession. Coral recruitment showed a strong positive association with coral genus richness (ρ ≈ 0.57), suggesting that more taxonomically diverse restoration structures supported greater establishment of new colonies. Recruitment was dominated by retained fragments (77%) rather than larval settlement (23%), highlighting the importance of fragmentation during early site development. Host-specific analyses further revealed relationships between predator abundance, colony size, and tissue loss within Acropora colonies that were not detectable when all coral genera were analysed together. Mortality estimates derived from colony counts and image-based cover were strongly correlated (ρ = 0.80, p < 0.001), indicating redundancy between these monitoring metrics. These findings demonstrate that analysing relationships among monitoring indicators can reveal early ecosystem development at restoration sites while identifying practical metrics suitable for long-term monitoring programs.
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