Environmental Engineering Reference
In-Depth Information
associated to species abundance than to species richness, suggesting that
biodiversity may act not only as a measure of biophysical integrity (Smith
1994), but also as a contributor to overall stability. TS has been estimated
using the coeffi cient of variation [CV = 100/(standard deviation/mean)], for
which smaller values represent greater stability (Tilman 1999). For example,
the TS of a system could be quantifi ed as mean macroinvertebrate biomass
(
b
, gC m
−2
) divided by the standard deviation of community biomass
production through time:
TS =
b
/ σ
xi
Æ
xj
The ecosystem concept cuts through the myriad of complex interactions
at a species level by focusing on a small subset of average or integrated
properties of all the populations within the area of study. Its big advantage
is that it can identify emergent properties such as energy fl ow and nutrient
cycling and study the stability of function of this abstract structure (Allen
2010, Allen and Fulton 2010). The weakness lies in its ability to explain
the relative stability of ecological systems in a changing environment; the
focus on a self regulating system leading to a focus on local and short term
stability (i.e., recovery from disturbance) rather than fl exibility in the sense
of maintaining variability in space and time as conditions change (O'Neill
2001). The result of the ecosystem approach has been the development of
the current generation of coupled bio-physical models, with a limited ability
to respond to environmental change. However, there is a requirement to
understand the impact of multiple climatic and anthropogenic drivers
on the whole ecosystem, which requires the development of a new
generation of end to end models (Parkes et al. 2003). Another driver in
model development has been the increase in knowledge of “previously
non considered processes”, e.g., the microbial loop (Azam et al. 1983), iron
limitation (Martin and Fitzwater 1988) and ocean acidifi cation (Raven et
al. 2005). This has led to increasing model complexity, but often at a rate
where the speed with which processes are included in models outstrips the
modelling community's ability to realistically parameterize them (Anderson
2005). This is despite the increased availability of integrated data sets, such
as the World Ocean Atlas (http://www.nodc.noaa.gov/OC5/WOA05/
pr_woa05.html).
One point that engages the effects of climate on the ecosystem and its
characteristics is the “regime shift”. The term
regime shift
has been used to
describe large, decadal-scale switches in the abundance and composition
of organisms within the ecosystem (e.g., plankton or fi sh) (Reid et al. 2001).
As an example, Venrick et al. (1987) reported an increase in phytoplankton
biomass before and after this period, which they attributed to a modifi cation
of atmospheric circulation. Spatial gradients in sea level pressure increased
the shift. Increased strength and frequency of storminess and westerly winds
