4 Summary of the results
Here C0 denotes the mass concentration within each decade of particle diameter and a
the bre radius. The optimum lter spacing within the relevant range for choanoagellates
scales approximately linear as about one half the maximum prey size. The
observed lter designs in choanoagellates follow this trend with the assumption that
there is a xed ratio between maximum prey and predator size (gure 4.6 B).
Since biological systems are complex and formed by highly variable selective forces
in a changing environment, we acknowledge that even with a certain grade of optimisation
we can not say with certainty which parameter should be optimised with
respect to which function and to what degree. Thus we do not a priori assume that
choanoagellates with all their elements are designed to optimise a single function
Dudley and Gans, 1991. Instead we use our analytical and numerical models combined
with empirical data to explore possible limiting and optimal design components
of microbial lter feeders in a well-dened framework, where we explicitly take into
account physical constraints.
4.4 Paper IV: Dense dwarfs versus gelatinous giants
In this manuscript we investigate general trade-os of the lter-feeding strategy in
planktonic organisms. We are especially interested in the eect of the body composition
of lter feeders on their tness and the constraints that lead to body dilution,
since gelatinous, dilute organisms form an important group of lter feeders and other,
but more dense organisms with similar biomass often have the possibility of additional
sensing apparatus. Gelatinous species in general do not use remote senses like vision
or ow-sensing, unlike sh and copepods, and thus fully rely on prey physically intercepting
their body, mainly through feeding currents. This makes their strategy more
similar to much smaller species, such as choanoagellates.
We use the scope for growth as the energy gain minus the energy investment per
time as a proxy for the instantaneous tness of active planktonic lter feeders, which
actively create a ow through an internal, ne-meshed lter. In order to compare
organisms with dierent size and body composition we model the energy-specic scope
for growth. The basic equation that we use for the scope for growth is
H = Auc kAu2 Rb (4.2)
with the energy-specic lter area A, the lter ow speed u, the prey concentration c
in energy per volume, the lter resistance coecient k, and the energy-specic basal
respiration rate Rb. Filter feeders generally invest energy in the motor that is used to
create the feeding current, i.e. Rf = kAu2, as well as in basic maintenance, i.e. Rb.
Both investments can be measured in the form of the respiration rate of the organism.
The gained energy is given by the energy of the encountered prey with characteristic
abundance that is collected through the feeding ow, i.e. G = Auc, where Au is the
energy-specic clearance rate.
From our simple model we can predict optimal strategies that balance the trade-o
between gain and investment which are connected through the lter ow (gure 4.7 A).