Tactile-feeding wading birds, such as wood storks and white ibises, require high densities of prey such as small fishes and crayfish to support themselves and their offspring during the breeding season. Prey availability in wetlands is often determined by seasonal hydrologic pulsing, such as in the subtropical Everglades, where spatial distributions of prey can vary through time, becoming heterogeneously clumped in patches, such as ponds or sloughs, as the wetland dries out. In this mathematical modeling study, we selected two possible foraging strategies to examine how they impact total energetic intake over a time scale of one day. In the first, wading birds sample prey patches without a priori knowledge of the patches' prey densities, moving from patch to patch, staying long enough to estimate the prey density, until they find one that meets a predetermined satisfactory threshold, and then staying there for a longer period. For this case, we solve for a wading bird's expected prey intake over the course of a day, given varying theoretical probability distributions of patch prey densities across the landscape. In the second strategy considered, it is assumed that the wading bird samples a given number of patches, and then uses memory to return to the highest quality patch. Our results show how total intake over a day is impacted by assumptions of the parameters governing the spatial distribution of prey among patches, which is a key source of parameter uncertainty in both natural and managed ecosystems. Perhaps surprisingly, the foraging strategy that uses a prey density threshold generally led to higher maximum potential prey intake than the strategy for using memory to return to the best patch sampled. These results will contribute to understanding the foraging of wading birds and to the management of wetlands.
|Publication Subtype||Journal Article|
|Title||Wading bird foraging on a wetland landscape: A comparison of two strategies|
|Series title||Mathematical Biosciences and Engineering|
|Contributing office(s)||Wetland and Aquatic Research Center|
|Google Analytic Metrics||Metrics page|