Sources of prey availability data alter interpretation of outputs from prey choice null networks

Author:

Cuff Jordan P.ORCID,Tercel Maximillian P.T.G.ORCID,Windsor Fredric M.ORCID,Hawthorne Ben S.J.ORCID,Hambäck Peter A.ORCID,Bell James R.ORCID,Symondson William O.C.ORCID,Vaughan Ian P.ORCID

Abstract

AbstractNull models provide an invaluable baseline against which to test fundamental ecological hypotheses and highlight patterns in foraging choices that cannot be explained by neutral processes or sampling artefacts. In this way, null models can advance our understanding beyond simplistic dietary descriptions to identify drivers of interactions. This method, however, requires estimates of resource availability, which are generally imperfect representations of highly dynamic systems. Optimising method selection is crucial for study design, but the precise effects of different resource availability data on the efficacy of null models are poorly understood.Using spider-prey networks as a model, we used prey abundance (suction sample) and activity density (sticky trap) data, and combinations of the two, to simulate null networks. We compared null diet composition, network properties (e.g., connectance and nestedness) and deviations of simulations from metabarcoding-based spider dietary data (to ascertain how different prey availability data alter ecological interpretation.Different sampling methods produced different null networks and inferred distinct prey selectivity. Null networks based on prey abundance and combined frequency-of-occurrence data more closely resembled the observed diet composition, and those based on prey abundance, activity density and proportionally combined data generated network properties most like dietary metabarcoding networks.We show that survey method choice impacts all aspects of null network analyses, the precise effects varying between methods but ultimately altering ecological interpretation by increasing disparity in network properties or trophic niches between null and directly constructed networks. Merging datasets can generate more complete prey availability data but is not a panacea because it introduces different biases. The choice of method should reflect the research hypotheses and study system being investigated. Ultimately, survey methods should emulate the foraging mode of the focal predator as closely as possible, informed by the known ecology, natural history and behaviour of the predator.

Publisher

Cold Spring Harbor Laboratory

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