Environmental Engineering Reference
In-Depth Information
Ecosystem Indicators
A selection of ecosystem indicators was included in EwE to describe the state of the
system. Following Odum (1969, 1971) it is assumed that an undisturbed ecosystem is
mature and that in a more mature system most niches are filled; that a larger part of
the energy flows should be through detritus-based food webs; that primary production
should be more efficiently utilized; that the total system biomass/energy throughput
ratio should be higher, etc. As shown by Christensen and Pauly (1998) (and many
others) the use of a composite of ecosystem indices may allow to describe the state of
a given system and how it may have changed over time. A selection of relevant
ecosystem “health” indices included in EwE are given in the following Table
5.1
.
5.2.2 Time-Dynamic Simulation: Ecosim
The basics of Ecosim are described in detail by Walters et al. (1997, 2000) and will
only be overviewed here. Ecosim consists of biomass dynamics expressed through
a series of coupled differential equations. The equations are derived from the
Ecopath master (5.1), and take the form
g
i
X
j
X
d
B
i
d
t
¼
Q
ij
Q
ij
þ
I
i
ð
M
0
i
þ
F
i
þ
e
i
Þ
B
i
;
(5.7)
j
where d
B
i
/
dt
represents the growth rate during the time interval d
t
of group
i
in terms
of its biomass,
B
i
;
g
i
is the net growth efficiency (production/consumption);
M
0
i
the
non-predation (“other”) natural mortality rate estimated from the ecotrophic effi-
ciency,
F
i
is fishing mortality rate,
e
i
is emigration rate,
I
i
is immigration rate
(assumed constant over time, and hence independent of events in the ecosystem
modelled), and
e
i
B
i
-
I
i
is the net migration rate of (5.1). The two summations
estimate consumption rates, the first expressing the total consumption by group
i
, and
the second the predation by all predators on the same group
i
. The consumption rates,
Q
ji
, are calculated based on the “foraging arena” concept, where
B
i
's are divided into
vulnerable and invulnerable components (Walters et al. 1997, Fig.
5.1
), and it is the
transfer rate (
v
ij
) between these two components that determines if control is top-
down (i.e. Lotka-Volterra), bottom-up (i.e. donor-driven), or of an intermediate type.
Ecosim bases the crucial assumption for prediction of consumption rates on a
simple Lotka-Volterra or “mass-action” assumption, modified to consider “forag-
ing arena” properties. Following this, prey can be in states that are either vulnerable
or un-vulnerable to predation, for instance by hiding (e.g. in crevices of coral reefs
or inside a school), when not feeding, and only being subject to predation when
having left their shelter to feed (Fig.
5.1
). In the Ecosim formulation (Walters et al.
1997, 2000) the consumption rate for a given predator feeding on a prey was thus
predicted from the effective search rate for predator-prey specific interactions, base
