Network metrics and spatial distribution of seagrass in the central Great Barrier Reef

Spatial layer of the seagrass meadows used in Grech, A., Hanert, E., McKenzie, L., Rasheed, M., Thomas, C., Tol, S., Wang, M., Waycott, M., Wolter, J. and Coles, R. (In Press). Cumulative effects of multiple disturbance events on seagrass connectivity. Global Change Biology.

Attribute table contains information on the network metrics, derived using the network analysis software Gephi 0.9.2.

    Data Record Details
    Data record related to this publication Network metrics and spatial distribution of seagrass in the central Great Barrier Reef
    Data Publication title Network metrics and spatial distribution of seagrass in the central Great Barrier Reef
  • Description

    Spatial layer of the seagrass meadows used in Grech, A., Hanert, E., McKenzie, L., Rasheed, M., Thomas, C., Tol, S., Wang, M., Waycott, M., Wolter, J. and Coles, R. (In Press). Cumulative effects of multiple disturbance events on seagrass connectivity. Global Change Biology.

    Attribute table contains information on the network metrics, derived using the network analysis software Gephi 0.9.2.

  • Other Descriptors
    • Descriptor

       Attribute table (also in attached zip file):

      Title: Network metrics and spatial distribution of seagrass in the central Great Barrier Reef

      Custodian: Dr Alana Grech

      Layer name: Meadows_Network_Metrics

      Data format: GIS Shapefile

      Brief description: Spatial layer of the seagrass meadows used in Grech et al. (in review). Attribute table contains information on the network metrics, derived using the network analysis software Gephi 0.9.2.

      Search Words: connectivity, cumulative effects, seagrass, Great Barrier Reef, graph theory, networks

      Currency: July 2013 – October 2017

      Co-ordinate system: GCS GDA 1994

      Access constraint: Need a DOI for review, searchable but not retrievable without my permission

      Attribute table key:  

      FNF: Indicates whether the meadow contains Foundation (F) or non-foundation (NF) species.

      Node: Unique identifier. Nodes represent discrete seagrass meadows that can be connected to other meadows by weighted edges of the number of ‘virtual’ propagules.

      Area_km2_: Area (km2) of meadow.

      Community: Unique identifier of the node’s community. Communities were detected using modularity to measure the strength of division of the network into groups.

      Betweeness: Betweeness centrality. A measure based on the number of shortest paths between any two nodes that pass through a particular node. Nodes around the edge of the network would typically have a low betweenness centrality. A high betweenness centrality might suggest that the node is connecting various different parts of the network together. 

      PageRank: A measure of a nodes importance as a source or sink that takes into account the full topology of the network.

      Closeness: Closeness centrality. The sum of the minimum path lengths connecting a node to all other nodes. A low closeness centrality indicates a node’s isolation from the network.

      Local_Rete: Local retention. The proportion of ‘virtual’ propagules that remain within the seagrass meadow.

      Degree: Number of unweighted edges incident to that node. A high degree indicates network hubs.

      In_Degree: Number of nodes supplying ‘virtual’ propagules to the node.

      Out_Degree: Number of nodes that the node is supplying ‘virtual’ propagules too.

      Weighted_D: Weighted degree. The sum of the number of ‘virtual’ propagules incident to that node.

      Weighted_I: Weighted in-degree. The sum of the number of ‘virtual’ propagules coming into the node.

      Weighted_O: Weighted out-degree (or Out-flux). The sum of number of ‘virtual’ propagules coming out of the node.

      Weighted_1: Weighted out-degree (or Out-flux) – local retention. The sum of number of ‘virtual’ propagules coming out of the node minus the number of ‘virtual’ propagules that remain within the node.

      Abstract [Related Publication]: The rate of exchange, or connectivity, among populations effects their ability to recover after disturbance events. However, there is limited information on the extent to which populations are connected or how multiple disturbances affect connectivity, especially in coastal and marine ecosystems. We used network analysis and the outputs of a biophysical model to measure potential functional connectivity and predict the impact of multiple disturbances on seagrasses in the central Great Barrier Reef World Heritage Area (GBRWHA), Australia. The seagrass networks were densely connected, indicating that as modelled seagrasses are resilient to the random loss of meadows. Our analysis identified discrete meadows that are important sources of seagrass propagules and that serve as stepping stones connecting various different parts of the network. Several of these meadows were close to urban areas or ports and likely to be at risk from coastal development. Deep water meadows were highly connected to coastal meadows and may function as a refuge, but only for non‐foundation species. We evaluated changes to the structure and functioning of the seagrass networks when one or more discrete meadows were removed due to multiple disturbance events. The scale of disturbance required to disconnect the seagrass networks into two or more components was on average > 245 kilometres; about half the length of the metapopulation. The densely connected seagrass meadows of the central GBRWHA are not limited by the supply of propagules, therefore management should focus on improving environmental conditions that support natural seagrass recruitment and recovery processes. Our study provides a new framework for assessing the impact of global change on the connectivity and persistence of coastal and marine ecosystems. Without this knowledge, management actions, including coastal restoration, may prove unnecessary and be unsuccessful.

      The full methodology is available in the publication shown in the Related Publications link below.

       

       

    • Descriptor type Full
  • Data type dataset
  • Keywords
    • connectivity
    • cumulative effects
    • seagrass
    • Great Barrier Reef
    • graph theory
    • networks
    • ARC Centre of Excellence for Coral Reef Studies
  • Funding source
  • Research grant(s)/Scheme name(s)
  • Research themes
    Tropical Ecosystems, Conservation and Climate Change
    FoR Codes (*)
    • 050202 - Conservation and Biodiversity
    • 050102 - Ecosystem Function
    SEO Codes
    • 960808 - Marine Flora, Fauna and Biodiversity
    Specify spatial or temporal setting of the data
    Temporal (time) coverage
  • Start Date 2013/07/01
  • End Date 2017/10/25
  • Time Period
    Spatial (location) coverage
  • Locations
    • Central Great Barrier Reef, Queensland, Australia
    Data Locations

    Type Location Notes
    Attachment Meadows_Network_Metrics.zip GIS shape file (zip archive)
    The Data Manager is: Alana Grech
    College or Centre
    Access conditions Open: free access under license
  • Alternative access conditions
  • Data record size
  • Related publications
      Name Grech, Alana, Hanert, Emmanuel, McKenzie, Len, Rasheed, Michael, Thomas, Christopher, Tol, Samantha, Wang, Mingzhu, Waycott, Michelle, Wolter, Jolan, and Coles, Robert (2018) Predicting the cumulative effect of multiple disturbances on seagrass connectivity. Global Change Biology, 2018 (24). pp. 3093-3104
    • URL https://doi.org/10.1111/gcb.14127
    • Notes
  • Related websites
      Name
    • URL
    • Notes
  • Related metadata (including standards, codebooks, vocabularies, thesauri, ontologies)
  • Related data
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    • Notes
    Citation Grech, Alana (2017): Network metrics and spatial distribution of seagrass in the central Great Barrier Reef. James Cook University. https://doi.org/10.4225/28/59fbbefa1337c