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

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.