Geoscience Reference
In-Depth Information
II
shallow lakes
deep lakes
clear water
macrophyte
vegetation
stabilized
sediment
mixed, oxygen-rich
oxic sediment
I)
high turbidity
resuspended
sediment
not mixed,
oxygen-deficient
anoxic sediment
II)
I
nutrient
Figure 25.2
Example of a threshold effect and alternative states in eutrophied lacus-
trine ecosystems. Increasing nutrient content leads to expanding algal populations
and increased oxygen consumption, decreasing biotic variability and species popula-
tions and creating a positive feedback in algal growth. When a critical threshold of
nutrient supply and algal growth is exceeded, there is some discontinuity where the
system changes from one state to another. These changes in state are accompanied
by changes in both physical and biological characteristics, as indicated for both states
in shallow and deep lakes. Arrows show a generalised path of recovery for decreasing
nutrient loads, which is different to increasing loads. Taken from Pahl-Wostl (1995).
ience) compromising the system's ability to compensate for this stress, so that the
response is non-linear (fi gure 25.1c). This essentially means that a point is reached
when the system cannot compensate for stress and the stress effect is exacerbated
(i.e., a positive feedback occurs), so that the ecosystem 'crashes'. This is also termed
a 'threshold effect', and results in a system rapidly changing from one state to
another.
A classic example of a 'threshold effect' is eutrophication in lakes. With increas-
ing nutrient inputs into such systems, algal populations increase steadily until the
amount of algae reduces the level of oxygen in the water beyond a critical threshold,
whereupon a series or 'cascade' of interactions occurs, such as a rapid decline in
submerged plants, macrophytes, fi sh and invertebrates and further increases in algal
populations (Pahl-Wostl, 1995). This then rapidly increases the rate of change in
both biotic and abiotic structure and process in the ecosystem (fi gure 25.2), and is
a useful example of a non-linear adaptive response to a simple change in ecosystem
input, which may itself be a linear process. Petts and Gurnell (2005) discuss similar
non-linear responses in river system morphology and ecology to dams. Dams reduce
fl ows of energy, sediment and water into a river system, but the response to those
changes depends on sediment type, species characteristics and the variability of the
(regulated) hydrological regime.
Such non-linearity of system response inevitably causes problems for ecosystem
and resource prediction. Qi et al. (2002) demonstrate how soil respiration (carbon
emission) is sensitive to changes in temperature but has a non-linear response, being
much more sensitive (and therefore variable) at lower temperatures compared to
