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Connectivity Matrices from biophysical modelling studies for A. millepora coral larvae in the Great Barrier Reef (Australia); present day and future scenarios

Citation

Thomas, Christopher et al. (2021), Connectivity Matrices from biophysical modelling studies for A. millepora coral larvae in the Great Barrier Reef (Australia); present day and future scenarios, Dryad, Dataset, https://doi.org/10.5061/dryad.4f4qrfjbk

Abstract

These data contain connectivity matrices from biophysical modelling simulations of the dispersal of Acropora millepora coral larvae in the southern Great Barrier Reef (Australia), under present-day and future climate scenarios. The connectivity matrices represent modelled strength of larval transfer from one reef to another, and were obtained using a coupled reef-scale, high-resolution, depth-integrated finite element hydrodynamic model (SLIM) of water currents in the Great Barrier Reef, and Individual-Based particle tracking module. Biological parameters to model larval acquisition and loss of competency and mortality were based on the results of experiments detailed in the related journal article. We include connectivity matrices for 2 different water temperature scenarios representing current and future climates, for three different recent spawning seasons (2008, 2009, 2010), and also for scenarios where low-frequency currents through the domain are modulated to mimic the likely effects from future changes to large-scale circulation extracted from CMIP5 global climate models.

We also include files summarising the relative changes, per reef, to certain key connectivity metrics between the 2 temperature scenarios (dispersal distance, local retention, number of incoming connections, "source index", and present day "source index" - all metrics are defined in the related journal article and Methods section of this metadata), averaged over all 3 spawning seasons modelled, as plotted in Figs 1a-e in the related journal article. Additionally, we include a separate file summarising changes to reef recovery times following a disturbance to coral cover between the 2 temperature scenarios, per reef, as modelled using the meta-population model described in the related journal article, and as shown in Fig 2 of the article.

Methods

These connectivity matrices were generated by an Individual-Based (Lagrangian) Model to simulate the dispersal of coral larvae during different spawning seasons in the Great Barrier Reef. Details of the Hydrodynamic and Individual-Based models can be found in the linked journal article. The matrices themselves have been normalised by the total number of particles seeded in each simulation. As well as the connectivity matrices describing the (normalised) strength of larval dispersal from source reef (indexed by the matrix row) to the destination reef (matrix column), we include an associated matrix giving the (normalised) quantity of larvae seeded at each reef, again normalised by the total number of larvae seeded; all matrices are therefore directly equivalent.

The present-day matrix was obtained using hydrodynamics calibrated to present-day conditions, and an assumed water temperature of 27 degrees Celsius; the 29 degree Celsius matrix was obtained assuming the effects of a 2 degree Celsius increase in water temperature with respect to the present day scenario. The future hydrodynamics scenarios, with modulated water inflow quantities, were carried out using biological parameters for 27 degree Celsisus water temperature. Each scenario is repeated for the 3 spawning seasons. Validation plots and metrics for the hydrodynamic model are detailed in the related journal article.

To calculate changes in connectivity metrics (such as local retention, or dispersal distance) with respect to the present day, we advise looking at the difference separately for each of the 3 spawning seasons and then averaging, such that each season is given equal weight, to make the results more robust to particular annual changes in larval dispersal patterns, whether on a small scale affecting only a small number of reefs, or at the larger, regional scale.

We also include 2 additional files containing the data represented in the 2 main plots in the related journal article - Figs 1a-e and Fig 2, which respectively show relative percentage changes between the 2 temperature scenarios, by reef, to certain key connectivity metrics, and to recovery times following disturbances, averaged over the 3 spawning seasons. The data for Figs 1a-e were created by processing the connectivity matrices in the way described in the journal article, specifically:

  • dispersal distance is calculated as the average distance between source and destination reefs, averaged over all larvae released at the source reef which settled on any other reef during the simulation. This is calculated and shown by source reef.
  • local retention is calculated as the proportion of larvae released over the source reef which settled over that same reef during the course of the simulation.
  • number of incoming connections is the number of reefs from which a reef has received settlers (i.e. settled larvae) during the course of the simulation.
  • source index is defined as the product of the number of larvae released at a given reef which settled on any other reef, and the number of outgoing connections from this reef to any other reef; it is designed to measure the relative importance of a reef as a source of larvae to other reefs. The data contain the source index averaged over the 27C simulation, to show the geographical distribution of the most important reefs under "present day" conditions, as well as the relative change in source index, by reef, between the 27C and 29C simulations. The source index is normalised by the value of the reef with the highest source index in the domain so it varies between 0 and 1, since it is purely a relative measure to compare different reefs within the same simulation domain.

The data file for "Fig 2" contains the relative percentage changes to recovery times following a) single-reef and b) multi-reef simultaneous disturbances in initial coral cover, by reef, using the methodology described in the related journal article to simulate the evolution of coral cover in time following these initial disturbances. Reefs which never fully recovered initial coral cover do not contain any value.

Relative changes for all data in the Figs 1a-e and Fig 2 datasets are first calculated by reef and by spawning season, and then averaged, by reef, over all three spawning seasons to obtain single value by reef. They represent the percentage change at 29C relative to the 27C temperature scenario.

Usage Notes

Please refer to the 2 README files for specific details about the content of the individual files included and a description of the file naming convention used. The 00_README file describes the connectivity matrices, whilst the 01_README_Figs1and2_data file describes the "Figs 1 and 2" datasets in more detail.

Note that some rows of the connectivity matrix are blank; any rows/columns which are blank in both the connectivity matrix and the associated "reefs seeded" matrix should be ignored, as these were not included in the simulations. We also include a file containing the geographical coordinates of the central position of each reef referred to in the connectivity matrix (same indexing, ie the coordinates in row N correspond to row N/column N in the connectivity matrices); these can be used to compute dispersal distances.

Funding

Fédération Wallonie-Bruxelles, Award: ARC 10/15-028

Australian Research Council, Award: DP110101168

Queensland Government, Award: Smart Futures Fellowship