Abstract
Changes in suspended sediment concentration (SSC)
are important for both the physical and ecological
environment. One of the main impacts is on the
attenuation of light intensity with depth, which
affects phytoplankton and macrophyte primary
production, and the environment for visual
predators. However, detailed data on SSC are
relatively scarce, so both dynamic and statistical
models which may predict SSC from more readily
available data are potentially valuable.
We analysed a dataset of >400 turbidity profiles
collected at weekly intervals during 2007-2011 at
the Marine Scotland Science sampling site off
Stonehaven on the east of Scotland. We sought to
establish a statistical General Additive Model
(GAM) of SSC at a given altitude above the seabed
with explanatory variables being seabed depth, tidal,
wind, wave, and river outflow data. Alternative
models were assessed with Akaike's Information
Criterion to choose between the fits offered by
different models.
Our final model provided a highly significant fit
to the observed data from the main sampling site.
We then tested the model by applying it to
independent data collected at secondary sampling
sites in both shallower and deeper water in the
vicinity and showed that the model provided as
significant account of the SSC dynamics at these site
also.
are important for both the physical and ecological
environment. One of the main impacts is on the
attenuation of light intensity with depth, which
affects phytoplankton and macrophyte primary
production, and the environment for visual
predators. However, detailed data on SSC are
relatively scarce, so both dynamic and statistical
models which may predict SSC from more readily
available data are potentially valuable.
We analysed a dataset of >400 turbidity profiles
collected at weekly intervals during 2007-2011 at
the Marine Scotland Science sampling site off
Stonehaven on the east of Scotland. We sought to
establish a statistical General Additive Model
(GAM) of SSC at a given altitude above the seabed
with explanatory variables being seabed depth, tidal,
wind, wave, and river outflow data. Alternative
models were assessed with Akaike's Information
Criterion to choose between the fits offered by
different models.
Our final model provided a highly significant fit
to the observed data from the main sampling site.
We then tested the model by applying it to
independent data collected at secondary sampling
sites in both shallower and deeper water in the
vicinity and showed that the model provided as
significant account of the SSC dynamics at these site
also.
| Original language | English |
|---|---|
| Pages | 1 |
| Publication status | Published - Aug 2013 |
| Event | Marine Alliance for Science and Technology for Scotland: Annual Science Meeting - Edinburgh, United Kingdom Duration: 27 Aug 2013 → 29 Aug 2013 |
Conference
| Conference | Marine Alliance for Science and Technology for Scotland: Annual Science Meeting |
|---|---|
| Country/Territory | United Kingdom |
| City | Edinburgh |
| Period | 27/08/13 → 29/08/13 |
Keywords
- statistical modelling
- suspended sediment
- stonehaven
