Table 1.
Definitions for the main technical terms used in this study, with references.
Fig 1.
Modelling approach to explicitly test the influence of seascape composition and configuration on genetic structure.
The relative influence of the various input parameters (e.g., habitat distribution and type, dispersal distance or pelagic larval duration) on genetic connectivity can be assessed quantitatively by performing sensitivity analyses of these parameters on the match between observed and simulated genetic divergences.
Fig 2.
Location of New Caledonia and Vanuatu in the Pacific Ocean and of the 23 sites sampled for genetic analysis.
The area extends from Efate (EFA, Vanuatu) in the East to the Chesterfield islands (CHE) in the West. Location names and sampling effort per location is available in Table 2. Land and reef maps are from the Millennium Coral Reef Mapping Project [31]. Dark grey stands for land and light grey for coral reefs.
Table 2.
Location names and number of specimen collected (n) per location for genetic analyses.
Fig 3.
Illustration of how habitat composition and configuration were taken into account in this study.
(A), (B), and (C) are habitat maps for south BOU (see Fig 2) established according to reef typology levels L3, L2, and L1, respectively (see Table 3). (D) Estimated abundance of T. maxima for each habitat patch. Abundance is the product of habitat surface and density per habitat (the figure displayed here was established on the basis of the L3 level, Table 3). Note that lower abundances were predicted in the south east part of New Caledonia and Vanuatu.
Table 3.
Typologies of reef geomorphology considered in this study.
Table 4.
Summary of all scenarios tested in this study and the corresponding correlations between the simulated and observed genetic structure.
Fig 4.
Connectivity matrices between all habitat patches considering an IBD dispersal kernel (A and C) or an IBOD dispersal kernel (B and D).
A) and B) display all habitat patches (see Fig 3D), while C) and D) only display habitat patches that were sampled for genetic analyses (see Fig 2).
Fig 5.
Comparison between observed and simulated genetic structures for Tridacna maxima.
A) Observed genetic distances from empirical data, obtained from 15 microsatellite loci. B) Genetic distances simulated by the isolation by distance (IBD) model. C) Genetic distances simulated by the isolation by oceanographic distance (IBOD) model. Genetic distances are Cavalli-Sforza & Edwards’s genetic distances [53], normalized to have maximum of 1.
Fig 6.
Correlations between observed and simulated genetic structures for the various scenarios of landscape composition and configuration.
Landscape composition was determined by the three levels of the reef typology described in Table 2. Landscape configuration is determined by habitat fragmentation (0% refers to the initial habitat maps, while 20%, 40%, 60% and 80% refer to reduction levels of habitat area compared to the initial habitat map). The coefficient of correlation is the Mantel coefficient of matrix correlation. We used the dispersal kernel that provided the best congruence between the observed and simulated genetic distances (IBD). Bars are medians and error bars are quantile 95%.