2018-09-20T08:18:03 n8109

Data from: Managing seagrass resilience under cumulative dredging affecting light: predicting risk using dynamic Bayesian networks

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Coastal development is contributing to ongoing declines of ecosystems globally. Consequently, understanding the risks posed to these systems, and how they respond to successive disturbances, is paramount for their improved management. We present a risk-based modelling framework for time varying complex systems centred around a dynamic Bayesian network (DBN).  The impact on resilience of dredging disturbances is evaluated using a validated seagrass ecosystem DBN for meadows of the genera Amphibolis (Jurien Bay, WA, Australia), Halophila (Hay Point, Qld, Australia) and Zostera (Gladstone, Qld, Australia). 

Data supports the following publication:

Wu PP, McMahon K, Rasheed MA, Kendrick GA, York PH, Chartrand K, Caley MJ, Mengersen K. (2017) Managing seagrass resilience under cumulative dredging affecting light: predicting risk using dynamic Bayesian networks. Journal of Applied Ecology, online in advance of print. https://doi.org/10.1111/1365-2664.13037

Data includes: Validation data used to validate the DBN model for Amphibolis in Jurien Bay, Halophila at Hay Point, and Zostera at Gladstone (supporting information S4 through S6, respectively). 

Lateral Growth from Existing Individuals

Physiological Status of Plants

Rate of Recovery in Shoot Density

Recruitment Rate from Seeds

Seed Density

The datasets were submitted to Dryad Digital Repository 29 November 2017.

Access rights

When using the data, please cite the original publication and this dataset using citations provided here.

Geographical area of data collection

kmlPolyCoords
149.295753,-21.292243
kmlPolyCoords
151.256607,-23.833696
kmlPolyCoords
115.041687,-30.294567

Publications

Managing seagrass resilience under cumulative dredging affecting light: Predicting risk using Dynamic Bayesian Networks https://eprints.qut.edu.au/116652/

Research areas

MATHEMATICAL SCIENCES
ecosystem management
risk modelling
Environmental sciences
Dynamic Bayesian Networks
seagrass
resilience
cumulative impacts
complex systems

Cite this collection

Wu, Paul; McMahon, K.; Rasheed, M. A; Kendrick , G. A; Chartrand, K; Caley, M. J; Mengersen, K (2017): Data from: Managing seagrass resilience under cumulative dredging affecting light: predicting risk using dynamic Bayesian networks. Queensland University of Technology. https://doi.org/10.5061/dryad.f71vq

Related information

Seagrass Study QUT - YouTube https://youtu.be/YLZsnZecpu4

Licence


Creative Commons Attribution 4.0 (CC-BY)
http://creativecommons.org/licenses/by/4.0/

Copyright

© 2017, Wu et al

Connections

Has association with
Kerrie Mengersen  (Researcher)
Has principal investigator
Paul Wu  (Researcher)

Contacts

Name: Dr Paul Wu
Phone: +61 7 3138 9828

Other

Date record created:
2018-04-16T16:31:42
Date record modified:
2018-09-20T08:18:03
Record status:
Published - Open Access