Data

Marine plant dispersal and connectivity measures differ in sensitivity to biophysical model parameters (associated files)

James Cook University
Schlaefer, Jodie ; Grech, Alana ; Choukroun, Severine ; Carter, Alexandra ; Coles, Robert ; Rasheed, Michael ; Tol, Samantha ; Critchell, Kay ; Lambrechts, Jonathan
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25903/3pe4-9n65&rft.title=Marine plant dispersal and connectivity measures differ in sensitivity to biophysical model parameters (associated files)&rft.identifier=10.25903/3pe4-9n65&rft.publisher=James Cook University&rft.description=Biophysical models simulate dispersal and connectivity in marine environments by combining numerical models that represent water circulation with biological parameters that define the attributes of species. The effects of parameters on model outputs, such as the number of particles released to simulate the trajectories of individual organisms, is potentially large but is rarely tested. In this study, we develop a framework to measure the optimal number of particles required to capture variability in dispersal and connectivity of the marine plants, seagrasses. The study location was Torres Strait. Spatial (geographic information system [GIS]) layers of seagrass distribution in Torres Strait were sourced from Carter et al. (2014, 2016). These layers were supplemented with information on the potential distribution of seagrass in the unmapped area between Badu and Boigu Islands derived from a model of dugong distribution and relative abundance (Marsh et al. 2015). The biophysical model data were generated with the SLIM model. The hydrodynamic simulation ran from September 2011, the start of the peak reproductive period of seagrasses in Torres Strait, to February 2012, the end of the window of viability. Analyses were conducted in Python3 (version 3.6.5) and Gephi 0.9.2. Seagrass shapefile, model run files, model output analysis files, and analysis results are provided on Research Data JCU. Additionally, the raw model outputs are provided at: Schlaefer, Jodie; Grech, Alana; Choukroun, Severine; Carter, Alexandra; Coles, Robert; Rasheed, Michael; Tol, Samantha; Kay, Critchell; Jonathan, Lambrechts (2021): Marine plant dispersal and connectivity measures differ in sensitivity to biophysical model parameters. James Cook University. (dataset) https://doi.org/10.25903/1vje-6c38 Software/equipment used to create/collect the data: The Second-generation Louvain-la-Neuve Ice-ocean Model (SLIM; Lambrechts et al. 2008)  Software/equipment used to manipulate/analyse the data: Python3 (version 3.6.5) and Gephi 0.9.2.&rft.creator=Schlaefer, Jodie &rft.creator=Grech, Alana &rft.creator=Choukroun, Severine &rft.creator=Carter, Alexandra &rft.creator=Coles, Robert &rft.creator=Rasheed, Michael &rft.creator=Tol, Samantha &rft.creator=Critchell, Kay &rft.creator=Lambrechts, Jonathan &rft.date=2021&rft.relation=https://research.jcu.edu.au/tropwater/publications/technical-reports/&rft.relation=https://nesptropical.edu.au/index.php/2016/04/27/assessment-of-key-dugong-and-turtle-seagrass-resources-in-north-west-torres-strait/wp-content/uploads/2016/04/NESP-TWQ-3.5-FINAL-REPORT.pdf&rft.relation=http://dx.doi.org/10.1016/j.biocon.2015.10.007&rft.relation=https://www.sciencedirect.com/science/article/pii/S0272771408001364&rft.coverage=140.890754,-11.027472 140.890754,-9.123792 143.658328,-9.123792 143.658328,-11.027472 140.890754,-11.027472&rft.coverage=&rft_rights=&rft_rights=CC BY-NC 4.0: Attribution-Noncommercial 4.0 International http://creativecommons.org/licenses/by-nc/4.0&rft_subject=biophysical model&rft_subject=connectivity&rft_subject=dispersal&rft_subject=Lagrangian particles&rft_subject=Individual Based Models&rft_subject=seagrass&rft_subject=ARC Centre of Excellence for Coral Reef Studies&rft.type=dataset&rft.language=English Access the data

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Biophysical models simulate dispersal and connectivity in marine environments by combining numerical models that represent water circulation with biological parameters that define the attributes of species. The effects of parameters on model outputs, such as the number of particles released to simulate the trajectories of individual organisms, is potentially large but is rarely tested. In this study, we develop a framework to measure the optimal number of particles required to capture variability in dispersal and connectivity of the marine plants, seagrasses.

The study location was Torres Strait. Spatial (geographic information system [GIS]) layers of seagrass distribution in Torres Strait were sourced from Carter et al. (2014, 2016). These layers were supplemented with information on the potential distribution of seagrass in the unmapped area between Badu and Boigu Islands derived from a model of dugong distribution and relative abundance (Marsh et al. 2015).

The biophysical model data were generated with the SLIM model. The hydrodynamic simulation ran from September 2011, the start of the peak reproductive period of seagrasses in Torres Strait, to February 2012, the end of the window of viability. Analyses were conducted in Python3 (version 3.6.5) and Gephi 0.9.2. Seagrass shapefile, model run files, model output analysis files, and analysis results are provided on Research Data JCU. Additionally, the raw model outputs are provided at:

Schlaefer, Jodie; Grech, Alana; Choukroun, Severine; Carter, Alexandra; Coles, Robert; Rasheed, Michael; Tol, Samantha; Kay, Critchell; Jonathan, Lambrechts (2021): Marine plant dispersal and connectivity measures differ in sensitivity to biophysical model parameters. James Cook University. (dataset) https://doi.org/10.25903/1vje-6c38

Software/equipment used to create/collect the data: The Second-generation Louvain-la-Neuve Ice-ocean Model (SLIM; Lambrechts et al. 2008) 

Software/equipment used to manipulate/analyse the data: Python3 (version 3.6.5) and Gephi 0.9.2.

Created: 2021-07-23

Data time period: 09 2011 to 29 02 2012

This dataset is part of a larger collection

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140.89075,-11.02747 140.89075,-9.12379 143.65833,-9.12379 143.65833,-11.02747 140.89075,-11.02747

142.274541,-10.075632

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Identifiers
  • Local : https://research.jcu.edu.au/data/published/3fa443ab1228316dc51fada2033f8634
  • DOI : 10.25903/3pe4-9n65