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 eco-morphology. 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.