Abstract
Successfully applying theoretical models to natural communities and predicting ecosystem behavior under changing conditions is the backbone of predictive ecology. However, the experiments required to test these models are dictated by practical constraints, and models are often opportunistically validated against data for which they were never intended. Alternatively, we can inform and improve experimental design by an in-depth pre-experimental analysis of the model, generating experiments better targeted at testing the validity of a theory. Here, we describe this process for a specific experiment. Starting from food web ecological theory, we formulate a model and design an experiment to optimally test the validity of the theory, supplementing traditional design considerations with model analysis. The experiment itself will be run and described in a separate paper. The theory we test is that trophic population dynamics are dictated by species traits, and we study this in a community of terrestrial arthropods. We depart from the Allometric Trophic Network (ATN) model and hypothesize that including habitat use, in addition to body mass, is necessary to better model trophic interactions. We therefore formulate new terms which account for micro-habitat use as well as intra- and interspecific interference in the ATN model. We design an experiment and an effective sampling regime to test this model and the underlying assumptions about the traits dominating trophic interactions. We arrive at a detailed sampling protocol to maximize information content in the empirical data obtained from the experiment and, relying on theoretical analysis of the proposed model, explore potential shortcomings of our design. Consequently, since this is a “pre-experimental” exercise aimed at improving the links between hypothesis formulation, model construction, experimental design and data collection, we hasten to publish our findings before analyzing data from the actual experiment, thus setting the stage for strong inference.
Highlights
Quantifying theory—A challenging processModels are abstractions of reality, distilling presumed relationships
We introduce a variation on the Allometric Trophic Network (ATN) model used in [8]
Lotka-Volterra dynamics, with a functional response of type two which accounts for both intraspecific competition and predator satiation, and interaction parameters are generalized as functions of body mass
Summary
Models are abstractions of reality, distilling presumed relationships. In empirical science, model credibility is established by predicting outcomes observable in real systems. Experimental design for trait-based predator-prey dynamics difficult, possibly requiring multiple observations of interactions between predator and prey to determine interaction frequencies as well as experiments to determine the impact of changes to species abundances or presence. Understanding and quantifying the nature of this relationship between traits and trophic interactions gives the two-fold advantage of understanding of the mechanisms behind the interactions as well as potentially reconstructing a food web with less empirical information This allows for the development of models that predict community population dynamics. We use model sensitivity to parameter estimation to determine optimal timing, frequency, and subsampling techniques which allow us to best sample the experiment to obtain information necessary for model validation; this analysis is the main theme of our paper, as it is rarely used in ecological research
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