High‐frequency variability dominates potential connectivity between remote coral reefs

Abstract

Coral larval dispersal establishes connectivity between reefs, but larval fluxes vary over timescales from daily to multidecadal due to oceanographic variability. Using a 2‐km‐resolution ocean model, we simulate daily spawning events from 1993 to 2019 and assess the potential connectivity between all reefs in the tropical southwest Indian Ocean. Although there is a significant seasonal cycle in potential connectivity, day‐to‐day variability generally dominates. Larval dispersal pathways on any particular day provide limited information about the dispersal pathways a few days later. The magnitude of this high‐frequency variability depends on the local geography and oceanography, with small and isolated reefs generally subject to the most variability. Stochastic oceanographic variability introduces considerable uncertainty to dispersal predictions, imposing fundamental limitations on what simulations can tell us about inter‐reef connectivity. Protracted spawning over only a few days can significantly reduce variability associated with the likelihood of a larva settling. The duration of spawning is therefore a more important parameter in modeling coral connectivity than the exact timing of spawning onset. Finally, we find that a small proportion of spawning events account for the majority of settling larvae, particularly at remote islands, and demonstrate that a time‐mean picture of dispersal may be inappropriate for predicting demographic and genetic connectivity. Given the diversity of coral reef environments in the southwest Indian Ocean, we expect that these results will apply to inter‐reef coral connectivity across the tropics more broadly, as well as other weakly swimming reef taxa with the potential for long‐distance dispersal.

Integration of population genetics with oceanographic models reveals strong connectivity among coral reefs across Seychelles

“…In line with previous studies 59 – 61 , we model coral larvae as positively buoyant, otherwise passive particles that drift according to surface currents, as part of the SECoW system 25 . We use surface currents from the multidecadal Western Indian Ocean Simulation, WINDS-M 24 , covering the entire tropical southwest Indian Ocean at a 2 km spatial and 30-min temporal resolution.…”

“…Second, the discrepancy may be due to stochastic variability in ocean currents, which can cause short- to mid-term potential connectivity to vary over several orders of magnitude 25 . In this model, such uncertainty is considerable, and can fully explain the mismatch between gene flow and potential connectivity for reefs that are reasonably close together (< 200 km; Fig.…”

“…We simulate virtual spawning events every day from 1993 to 2019 across all coral reefs within 20 m depth identified from 4.5 m resolution satellite imagery 34 , and advect particles for up to 120 days using OceanParcels 31 , 32 . Each particle represents a large number of larvae, which attain and lose competency, settle, and die according to the following equations 25 , 41 : where and respectively refer to the proportion of larvae represented by a particle that are precompetent (1) and competent (2); is the competency acquisition rate, and is zero before a minimum competency period ; is the competency loss rate; is the time-varying mortality rate; is the settling rate; and is the proportion of the grid cell occupied by the particle that is covered by coral reef.…”

“…Analysis of the temporal variability of potential connectivity revealed a significant dependence on the monsoonal cycle, particularly for the outer islands (Figure S3 25 ). Since corals in the southwest Indian Ocean tend to spawn between the months of October and March (e.g.…”

“…We used genome-wide SNP analysis to estimate: (1) the degree of genetic admixture between the Inner and Outer islands; and (2) the extent of gene flow among reef sites. We then used a 2 km-resolution regional ocean simulation 24 coupled with a larval dispersal model 25 to predict the flow of larvae between reef sites. Finally, we determined whether the empirical and modelling approaches returned congruent information about population connectivity, and in doing so, assessed whether oceanographic modelling studies are a robust compliment to genomic studies for large-scale coral reef connectivity mapping.…”