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Dryad

Hurricanes enhance coral connectivity but also superspread coral diseases: Connectivity matrices

Cite this dataset

Dobbelaere, Thomas et al. (2024). Hurricanes enhance coral connectivity but also superspread coral diseases: Connectivity matrices [Dataset]. Dryad. https://doi.org/10.5061/dryad.0cfxpnw98

Abstract

Climate change poses an existential threat to coral reefs. A warmer and more acidic ocean weakens coral ecosystems and increases the intensity of hurricanes. The wind-wave-current interactions during a hurricane deeply change the ocean circulation patterns and hence affect the dispersal of coral larvae and coral disease agents. Here we assessed the impact of major hurricane Irma (Sept. 2017) on coral larval and stony coral tissue loss disease connectivity in Florida’s Coral Reef. We coupled high-resolution coastal ocean circulation and wave models to simulate the dispersal of virtual coral larvae and disease agents between thousands of reefs. While being a brief event, our results suggest the passage of hurricane Irma strongly increased the probability of long-distance exchanges while reducing larval supply. It created new connections that could promote coral resilience but also probably accelerated the spread of the coral disease by about a month. As they become more intense, hurricanes’ double-edged effect will become increasingly pronounced, contributing to increased variability and an accelerated rate of change within coral reef ecosystems.

README: Hurricanes enhance coral connectivity but also superspread coral diseases: connectivity matrices

https://doi.org/10.5061/dryad.0cfxpnw98

Connectivity matrices obtained from the simulated dispersal of coral larvae and stony coral tissue loss disease (SCTLD) agents in Florida's Coral Reef before and after the landfall of Hurricane Irma (2017).

Description of the data and file structure

hydro_outputs_irma_gcb_2024.zip contains the simulated currents used to compute the connectivity matrices:

  • These currents can be visualized by opening slim.xdmf with Paraview.
  • The output models are stored as binary files (.abin extension). The metadata associated to each binary file (size, data type) are stored in the corresponding .ameta files.(formatted text format).
  • The coordinates of the mesh nodes are stored in slim/mesh/geometry.* and the mesh topology in slim/mesh/topology.*.
  • The simulated sea surface elevation and depth-averaged currents are respectively stored in slim/data/eta.* and slim/data/uv.*.

connectivity_matrices_irma.zip contains the connectivity matrices used to estimate and compare the connectivity indicators at each reef:

  • reef_map: the shape file of the reefs used for the simulation.
  • larvae: the connectivity matrices obtained from the dispersal of coral larvae before and after the landfall of Irma. The rows and columns of the matrices correspond to the polygons of the reef map. The cm_*.npz files the number of larvae exchanged between all pairs of reefs. The n_seeded_*.npy give the number of larvae released on each reef polygon
  • sctld: same as "larvae" for SCTLD agents, but matrices rows are already normalized by the number of released agents on each reef polygon

Sharing/Access information

The data is also (currently) available here

Code/Software

The matrices were obtained using the high-resolution unstructured-mesh model SLIM, whose interface is implemented in Python.

  • .npz files can be read using the scipy.sparse
  • .npy files can be read using numpy
  • .abin files can be read as memory maps using numpy.memmap using the information of the .ameta files

Methods

Connectivity matrices were computed by simulating the dispersion of virtual particles using the high-resolution unstructured-mesh coupled wave-ocean model SLIM (https://www.slim-ocean.be)