A new theoretical performance landscape for suction feeding reveals adaptive kinematics in a natural population of reef damselfish

Understanding how organismal traits determine performance
and, ultimately, fitness is a fundamental goal of
evolutionary ecomorphology. However, multiple traits can interact in
non-linear and context-dependent ways to affect performance, hindering
efforts to place natural populations with respect to performance peaks or
valleys. Here, we used an established mechanistic model of suction-feeding
performance (SIFF) derived from hydrodynamic principles to estimate a
theoretical performance landscape for zooplankton prey capture. This
performance space can be used to predict prey capture performance for any
combination of six morphological and kinematic trait values. We then
mapped in situ high-speed video observations of suction feeding in a
natural population of a coral reef zooplanktivore, Chromis viridis, onto
the performance space to estimate the population’s location with respect
to the topography of the performance landscape. Although the kinematics of
the natural population closely matched regions of high performance in the
landscape, the population was not located on a performance peak.
Individuals were furthest from performance peaks on the peak gape, ram
speed and mouth opening speed trait axes. Moreover, we found that the
trait combinations in the observed population were associated
with higher performance than expected by chance, suggesting that these
combinations are under selection. Our results provide a framework for
assessing whether natural populations occupy performance optima.