Managing seagrass resilience under cumulative dredging affecting light: Predicting risk using dynamic Bayesian networks. Issue 3 (21st November 2017)
- Record Type:
- Journal Article
- Title:
- Managing seagrass resilience under cumulative dredging affecting light: Predicting risk using dynamic Bayesian networks. Issue 3 (21st November 2017)
- Main Title:
- Managing seagrass resilience under cumulative dredging affecting light: Predicting risk using dynamic Bayesian networks
- Authors:
- Wu, Paul Pao‐Yen
McMahon, Kathryn
Rasheed, Michael A.
Kendrick, Gary A.
York, Paul H.
Chartrand, Kathryn
Caley, M. Julian
Mengersen, Kerrie - Editors:
- Mac Nally, Ralph
- Abstract:
- Abstract: 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 study the cumulative impacts of maintenance dredging on seagrass ecosystems as a canonical example. Maintenance dredging causes disturbances lasting weeks to months, often repeated at yearly intervals. We present a risk‐based modelling framework for time varying complex systems centred around a dynamic Bayesian network (DBN). Our approach estimates the impact of a hazard on a system's response in terms of resistance, recovery and persistence, commonly used to characterise the resilience of a system. We consider whole‐of‐system interactions including light reduction due to dredging (the hazard), the duration, frequency and start time of dredging, and ecosystem characteristics such as the life‐history traits expressed by genera and local environmental conditions. 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). Although impacts varied by combinations of dredging parameters and the seagrass meadows being studied, in general, 3 months of duration or more, or repeat dredging every 3 or more years, were key thresholds beyond which resilienceAbstract: 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 study the cumulative impacts of maintenance dredging on seagrass ecosystems as a canonical example. Maintenance dredging causes disturbances lasting weeks to months, often repeated at yearly intervals. We present a risk‐based modelling framework for time varying complex systems centred around a dynamic Bayesian network (DBN). Our approach estimates the impact of a hazard on a system's response in terms of resistance, recovery and persistence, commonly used to characterise the resilience of a system. We consider whole‐of‐system interactions including light reduction due to dredging (the hazard), the duration, frequency and start time of dredging, and ecosystem characteristics such as the life‐history traits expressed by genera and local environmental conditions. 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). Although impacts varied by combinations of dredging parameters and the seagrass meadows being studied, in general, 3 months of duration or more, or repeat dredging every 3 or more years, were key thresholds beyond which resilience can be compromised. Additionally, managing light reduction to less than 50% can significantly decrease one or more of loss, recovery time and risk of local extinction, especially in the presence of cumulative stressors. Synthesis and applications . Our risk‐based approach enables managers to develop thresholds by predicting the impact of different configurations of anthropogenic disturbances being managed. Many real‐world maintenance dredging requirements fall within these parameters, and our results show that such dredging can be successfully managed to maintain healthy seagrass meadows in the absence of other disturbances. We evaluated opportunities for risk mitigation using time windows; periods during which the impact of dredging stress did not impair resilience. Abstract : Our risk‐based approach enables managers to develop thresholds by predicting the impact of different configurations of anthropogenic disturbances being managed. Many real‐world maintenance dredging requirements fall within these parameters, and our results show that such dredging can be successfully managed to maintain healthy seagrass meadows in the absence of other disturbances. We evaluated opportunities for risk mitigation using time windows; periods during which the impact of dredging stress did not impair resilience. … (more)
- Is Part Of:
- Journal of applied ecology. Volume 55:Issue 3(2018)
- Journal:
- Journal of applied ecology
- Issue:
- Volume 55:Issue 3(2018)
- Issue Display:
- Volume 55, Issue 3 (2018)
- Year:
- 2018
- Volume:
- 55
- Issue:
- 3
- Issue Sort Value:
- 2018-0055-0003-0000
- Page Start:
- 1339
- Page End:
- 1350
- Publication Date:
- 2017-11-21
- Subjects:
- complex systems -- cumulative impacts -- disturbance -- dredging -- ecosystem management -- resilience modelling -- risk modelling -- seagrass
Agriculture -- Periodicals
Biology, Economic -- Periodicals
Agricultural ecology -- Periodicals
Applied ecology -- Periodicals
577 - Journal URLs:
- http://besjournals.onlinelibrary.wiley.com/hub/journal/10.1111/(ISSN)1365-2664/ ↗
http://onlinelibrary.wiley.com/ ↗
http://www.blackwell-synergy.com/member/institutions/issuelist.asp?journal=jpe ↗ - DOI:
- 10.1111/1365-2664.13037 ↗
- Languages:
- English
- ISSNs:
- 0021-8901
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4942.500000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 6390.xml