Harris, Jim A. - Associate Supervisor
Simms, Daniel M. - Associate SupervisorClimate-induced perturbations are expected to increase in frequency and
intensity and affect wetlands by altering its hydrology. An essential first step in
comprehending the wetland hydrological and ecological resilience to future
amplified climatic disturbances in coastal regions and beyond is this work, which
enhances the approach for measuring wetland hydrologic resilience at a regional
scale.
Land use change, natural disturbance and climate change directly alter
ecosystem productivity and resilience levels. The estimation of ecological
resilience dynamics depends on the quality of land cover change data and the
effectiveness of the ecosystem models that represent the vegetation growth
processes and disturbance effects. We used different mathematical approaches
determining resilience, land cover change data to examine landscape resilience
of the ecological networks in terms of scale, and how resilience exhibits as an
emergent behaviour in different types of ecosystems, with its influencing factors,
suggesting application to other estuarine ecosystems. A set of quantitative
metrics was developed including the variations of landscapes, utilizing spectral
power to determine changes in autocorrelation and variance as measures of
critically slowing down, detecting the early warning signals with the development
of the Dynamic Linear Model (DLM).
The coastal landscape, which includes coastal-herbaceous wetlands, was then
subjected to this method detecting the influence of salinity intrusion on estuarine
systems along geographical and temporal salinity gradients. We discovered that
an excellent indication of resilience is the multiscale autocorrelation fluctuations
of wetlands, affected by the temporal trends in data, under various climatic
circumstances.
Climate interannual variability was the key driving force for the large interannual
changes of ecosystem state level while extreme weather events and drought
were the dominant driving forces for resilience balances in several specific
ecoregions. There is a need for techniques that may be utilised to recognise when
a major transition is about to happen because these events might happen without
warning and are challenging to handle. A number of "early warning signals" can
be used to determine a system's near to a critical transition, according to recent
theory, and successful empirical examples point to the possibility of practical use.
Our study provides a practical toolbox that can be applied in a variety of sectors
to help identify early warning signs of crucial transitions in time series data, in
addition to a methodological guide.Natural Environment Research Council (NERC)PhD in Environment and Agrifoo
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