Adaptive monitoring of coral health at Scott Reef where data exhibit
nonlinear and disturbed trends over time
Abstract
Time series data are often observed in ecological monitoring. Frequently
such data exhibit nonlinear trends over time potentially due to complex
relationships between observed and auxiliary variables, and there may
also be sudden declines over time due to major disturbances. This poses
substantial challenges for modelling such data and also for model-based
adaptive monitoring. We propose novel methods for finding adaptive
designs for monitoring when historical data show such nonlinear patterns
and sudden declines over time. This work is motivated by a coral reef
monitoring program that has been established at Scott Reef; a coral reef
off the Western coast of Australia. Data collected for monitoring the
health of Scott Reef are considered, and semiparametric and interrupted
time series modelling approaches are adopted to describe how these data
vary over time. New methods are then proposed that enable adaptive
monitoring designs to be found based on such modelling approaches. These
methods are then applied to find future monitoring designs at Scott Reef
and form a set of recommendations for future monitoring. Through
applying the proposed methods, it was found that future information gain
is expected to be similar across a variety of different sites,
suggesting that no particular location needed to be prioritised at Scott
Reef for the next monitoring phase. In addition, it was found that
omitting some sampling sites/reef locations was possible without
substantial loss in expected information gain, depending upon the
disturbances that were observed. The resulting adaptive designs are used
to provide recommendations for future monitoring in this region, and for
reefs where changes to the current monitoring practices are being
sought. Furthermore, as the methods used and developed throughout this
study are generic in nature, this research has the potential to improve
ecological monitoring more broadly where complex data are being
collected over time.