Hidden layers of density dependence in consumer feeding rates

Stouffer, Daniel B.; Novák, Márk

doi:10.1111/ele.13670

Cited by 23 publications

(47 citation statements)

References 106 publications

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“…All but two of the considered models are previously published. The exceptions were a three-parameter model (AS) which represents an illustrative generalization of the adaptive behavior A1 model of Abrams (1990), and a four-parameter predator-dependent model (SN2) that extends the Beddington-DeAngelis and Crowley-Martin models and may be interpreted as reflecting predators that cannot interfere when feeding and can partially feed when interfering (see Stouffer and Novak, 2021).…”

Section: Functional-response Modelsmentioning

confidence: 99%

“…The upper bound is similarly arbitrary in a mathematical sense but seems logistically feasible since researchers are unlikely to choose a prey abundance beyond which they could not continually replace consumed individuals. For the SN1 and SN2 models, we imposed the respective additional requirement that bd ≤ 1/ max[F(N, P, θ )PT] and b ≤ 1/ max[F(N, P, θ )PT] for all treatments to maintain biologically-appropriate (non-negative) predator interference rates (Stouffer and Novak, 2021). We note that our placement of constraints on the expected number of eaten prey is similar to the use of Bayesian prior predictive checks with a joint prior distribution in that we restrict the domain of permissible parameter values based on how their conditional inter-dependencies lead to predicted model outcomes.…”

Section: Parameter Constraintsmentioning

confidence: 99%

“…For example, theoreticians often assume u ≥ 1 for the Hill exponent of the Holling-Real Type III (H3R) model, though Real (1977) did not do so. We consider non-negative values less than one to also be biologically and statistically possible (see discussion in Stouffer and Novak, 2021). Indeed, relaxing this constraint and redefining the statistically-redundant parameters of the original A3 model (Abrams, 1990) clarifies, for example, that it is mathematically equivalent to H3R with u = 0.5 (even if its assumed biological mechanism differs).…”

Section: Parameter Constraintsmentioning

confidence: 99%

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Geometric Complexity and the Information-Theoretic Comparison of Functional-Response Models

Novák

Stouffer

2021

Front. Ecol. Evol.

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The assessment of relative model performance using information criteria like AIC and BIC has become routine among functional-response studies, reflecting trends in the broader ecological literature. Such information criteria allow comparison across diverse models because they penalize each model's fit by its parametric complexity—in terms of their number of free parameters—which allows simpler models to outperform similarly fitting models of higher parametric complexity. However, criteria like AIC and BIC do not consider an additional form of model complexity, referred to as geometric complexity, which relates specifically to the mathematical form of the model. Models of equivalent parametric complexity can differ in their geometric complexity and thereby in their ability to flexibly fit data. Here we use the Fisher Information Approximation to compare, explain, and contextualize how geometric complexity varies across a large compilation of single-prey functional-response models—including prey-, ratio-, and predator-dependent formulations—reflecting varying apparent degrees and forms of non-linearity. Because a model's geometric complexity varies with the data's underlying experimental design, we also sought to determine which designs are best at leveling the playing field among functional-response models. Our analyses illustrate (1) the large differences in geometric complexity that exist among functional-response models, (2) there is no experimental design that can minimize these differences across all models, and (3) even the qualitative nature by which some models are more or less flexible than others is reversed by changes in experimental design. Failure to appreciate model flexibility in the empirical evaluation of functional-response models may therefore lead to biased inferences for predator–prey ecology, particularly at low experimental sample sizes where its impact is strongest. We conclude by discussing the statistical and epistemological challenges that model flexibility poses for the study of functional responses as it relates to the attainment of biological truth and predictive ability.

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Section: Functional-response Modelsmentioning

confidence: 99%

Section: Parameter Constraintsmentioning

confidence: 99%

Section: Parameter Constraintsmentioning

confidence: 99%

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Geometric Complexity and the Information-Theoretic Comparison of Functional-Response Models

Novák

Stouffer

2021

Front. Ecol. Evol.

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“…The challenge for ecologists is thus to evaluate and properly represent how the acquisition rate is influenced not only by the density of a given prey item as in typical Holling type II functional responses, but also by variation in abundance of the predator and all other potential prey items. Density-dependence has been considered in several functional response models (Hassell et al, 1977; Abrams, 1982) but rarely as explicit functions of prey densities (Stouffer and Novak, 2021). Such density-dependent changes in predator foraging behavior can generate positive effects between prey (Abrams and Matsuda, 1996, 1993) and warrant additional attention in natural predator-prey systems (Stouffer and Novak, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Density-dependence has been considered in several functional response models (Hassell et al, 1977; Abrams, 1982) but rarely as explicit functions of prey densities (Stouffer and Novak, 2021). Such density-dependent changes in predator foraging behavior can generate positive effects between prey (Abrams and Matsuda, 1996, 1993) and warrant additional attention in natural predator-prey systems (Stouffer and Novak, 2021).…”

Section: Introductionmentioning

confidence: 99%

Multi-species mechanistic model of functional response provides new insights into predator-mediated interactions in a vertebrate community

Beardsell

Gravel

Clermont

et al. 2021

Preprint

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Prey handling processes are considered a key driver of short-term positive indirect effects between prey sharing the same predator. However, a growing body of research indicates that predators are rarely limited by such processes in the wild. Density-dependent changes in predator foraging behavior can also generate positive indirect effects but they are rarely included as explicit functions of prey densities in functional response models. With the aim of untangling proximate drivers of species interactions in natural communities and improve our ability to quantify interaction strength, we extended the Holling multi-species model by including density-dependent changes in predator foraging behavior. Our model, based on species traits and behavior, was inspired by the vertebrate community of the arctic tundra, where the main predator (the arctic fox) is an active forager feeding primarily on cyclic small rodent (lemming) populations and eggs of various tundra-nesting bird species. Short-term positive indirect effects of lemmings on birds have been documented over the circumpolar Arctic but the underlying proximate mechanisms remain poorly known. We used a unique data set, containing high-frequency GPS tracking, accelerometer, behavioral, and experimental data to parameterize the multi-species model, and a 15-year time series of prey densities and bird nesting success to evaluate interaction strength between species. Our results showed that: (i) prey handling processes play a minor role in our system and (ii) density-dependent changes in predator foraging behavior can be the proximate drivers of a predominant predator-mediated interaction observed in the arctic tundra. Mechanisms outlined in our study have been little studied and may play a significant role in natural systems. We hope that our study will provide a useful starting point to build mechanistic models of predation, and we think that our approach could conceivably be applied to a broad range of food webs.

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A mechanistic model of functional response provides new insights into indirect interactions among arctic tundra prey

Beardsell

Gravel

Clermont

et al. 2022

Ecology

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Prey handling processes are considered a dominant mechanism leading to short‐term positive indirect effects between prey that share a predator. However, a growing body of research indicates that predators are not necessarily limited by such processes in the wild. Density‐dependent changes in predator foraging behavior can also generate positive indirect effects but they are rarely included as explicit functions of prey densities in functional response models. With the aim of untangling proximate mechanisms of species interactions in natural communities and improving our ability to quantify interaction strength, we extended the multi‐prey version of the Holling disk equation by including density‐dependent changes in predator foraging behavior. Our model, based on species traits and behavior, was inspired by the vertebrate community of the arctic tundra, where the main predator (the arctic fox) is an active forager feeding primarily on cyclic small rodent (lemming) and eggs of various tundra‐nesting bird species. Short‐term positive indirect effects of lemmings on birds have been documented over the circumpolar Arctic but the underlying mechanisms remain poorly understood. We used a unique data set, containing high‐frequency GPS tracking, accelerometer, behavioral, and experimental data to parameterize the multi‐prey model, and a 15‐year time series of prey densities and bird nesting success to evaluate interaction strength between species. We found that (1) prey handling processes play a minor role in our system and (2) changes in arctic fox daily activity budget and distance traveled can partly explain the predation release on birds observed during lemming peaks. These adjustments in predator foraging behavior with respect to the main prey density thus appear as the dominant mechanism leading to positive indirect effects commonly reported among arctic tundra prey. Density‐dependent changes in functional response components have been little studied in natural vertebrate communities and deserve more attention to improve our ability to quantify the strength of species interactions.

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Hidden layers of density dependence in consumer feeding rates

Cited by 23 publications

References 106 publications

Geometric Complexity and the Information-Theoretic Comparison of Functional-Response Models

Geometric Complexity and the Information-Theoretic Comparison of Functional-Response Models

Multi-species mechanistic model of functional response provides new insights into predator-mediated interactions in a vertebrate community

A mechanistic model of functional response provides new insights into indirect interactions among arctic tundra prey

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