Data

Marine plant dispersal and connectivity measures differ in sensitivity to biophysical model parameters

James Cook University
Schlaefer, Jodie ; Grech, Alana ; Choukroun, Severine ; Carter, Alexandra ; Coles, Robert ; Rasheed, Michael ; Tol, Samantha ; Kay, Critchell ; Jonathan, Lambrechts
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25903/1vje-6c38&rft.title=Marine plant dispersal and connectivity measures differ in sensitivity to biophysical model parameters&rft.identifier=10.25903/1vje-6c38&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. Analyses were conducted in Python3 (version 3.6.5) and Gephi 0.9.2. Seagrass shapefile, model run files, raw outputs, model output analysis files, and analysis results are provided - see associated readme.txt                                                                                                   Carter, A.B., Taylor, H.A. & Rasheed, M.A. (2014) Torres Strait mapping: Seagrass consolidation 2002 – 2014. Centre for Tropical Water & Aquatic Ecosystem Research (TropWATER) report no. 14/55. James Cook University, Cairns. 47pp. Carter, A.B. & Rasheed, M.A. (2016) Assessment of key dugong and turtle seagrass resources in north-west Torres Strait. Report to the National Environmental Science Programme (NESP) and Torres Strait Regional Authority. Reef and Rainforest Research Centre Limited, Cairns. 41pp. Marsh, H., Grayson, J., Grech, A., Hagihara, R., Sobtzick, S. (2015) Re-evaluation of the sustainability of a marine mammal harvest by indigenous people using several lines of evidence. Biological Conservation. 192: 324 – 330. &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=Kay, Critchell &rft.creator=Jonathan, Lambrechts &rft.date=2021&rft.relation=https://research.jcu.edu.au/tropwater/publications/technical-reports/&rft.relation=http://bit.ly/2q7FrUZ&rft.relation=http://dx.doi.org/10.1016/j.biocon.2015.10.007&rft.coverage=141.940033,-9.202969 141.610512,-9.51733 141.621496,-10.831148 142.28603,-10.825753 142.467266,-10.572062 142.763835,-10.820357 144.592676,-10.793378 144.581692,-9.316822 143.461321,-9.14874 142.577107,-9.360185 142.34095,-9.219236 142.209142,-9.170433 142.099301,-9.186701 141.940033,-9.202969&rft.coverage=Torres Strait&rft_rights=&rft_rights=CC BY-NC 4.0: Attribution-Noncommercial 4.0 International http://creativecommons.org/licenses/by-nc/4.0&rft_subject=dispersal&rft_subject=connectivity&rft_subject=seagrasses&rft_subject=biophysical models&rft_subject=SLIM model&rft_subject=ARC Centre of Excellence for Coral Reef Studies&rft.type=dataset&rft.language=English Access the data

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Full 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. Analyses were conducted in Python3 (version 3.6.5) and Gephi 0.9.2. Seagrass shapefile, model run files, raw outputs, model output analysis files, and analysis results are provided - see associated readme.txt                                                                                                  

Carter, A.B., Taylor, H.A. & Rasheed, M.A. (2014) Torres Strait mapping: Seagrass consolidation 2002 – 2014. Centre for Tropical Water & Aquatic Ecosystem Research (TropWATER) report no. 14/55. James Cook University, Cairns. 47pp.

Carter, A.B. & Rasheed, M.A. (2016) Assessment of key dugong and turtle seagrass resources in north-west Torres Strait. Report to the National Environmental Science Programme (NESP) and Torres Strait Regional Authority. Reef and Rainforest Research Centre Limited, Cairns. 41pp.

Marsh, H., Grayson, J., Grech, A., Hagihara, R., Sobtzick, S. (2015) Re-evaluation of the sustainability of a marine mammal harvest by indigenous people using several lines of evidence. Biological Conservation. 192: 324 – 330. 

Created: 2021-07-22

This dataset is part of a larger collection

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141.94003,-9.20297 141.61051,-9.51733 141.6215,-10.83115 142.28603,-10.82575 142.46727,-10.57206 142.76384,-10.82036 144.59268,-10.79338 144.58169,-9.31682 143.46132,-9.14874 142.57711,-9.36019 142.34095,-9.21924 142.20914,-9.17043 142.0993,-9.1867 141.94003,-9.20297

143.101594,-9.989944

text: Torres Strait

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Identifiers
  • Local : https://research.jcu.edu.au/data/published/076f8761e5ef7a74bacf0f9868480526
  • DOI : 10.25903/1vje-6c38