Abstract
The stability of consumer-resource systems can depend on the form of feeding interactions (i.e. functional responses). Size-based models predict interactions - and thus stability - based on consumer-resource size ratios. However, little is known about how interaction contexts (e.g. simple or complex habitats) might alter scaling relationships. Addressing this, we experimentally measured interactions between a large size range of aquatic predators (4-6400mg over 1347 feeding trials) and an invasive prey that transitions among habitats: from the water column (3D interactions) to simple and complex benthic substrates (2D interactions). Simple and complex substrates mediated successive reductions in capture rates - particularly around the unimodal optimum - and promoted prey population stability in model simulations. Many real consumer-resource systems transition between 2D and 3D interactions, and along complexity gradients. Thus, Context-Dependent Scaling (CDS) of feeding interactions could represent an unrecognised aspect of food webs, and quantifying the extent of CDS might enhance predictive ecology.
Highlights
In ecology, complexity and contingency are pervasive, and so the notion that many patterns and processes can be unified by considering organisms as consumers and processors of energy – embodied within the metabolic theory of ecology (MTE; Brown et al 2004) – is appealingly parsimonious
Because MTE offers a mechanistic link between temperature, body size and metabolic rate, it follows that the feeding rates of consumers should reflect intrinsic metabolic demand
Generalising consumer feeding rates to metabolic first principles remains problematic, for two reasons: (1) because feeding rates emerge from the relative performance of at least two agents – the consumer and the resource (Ohlund et al 2014); and (2) because historical energy acquisition and storage can dictate the necessity for feeding interactions when consumers encounter resources (Maino et al 2014)
Summary
Complexity and contingency are pervasive, and so the notion that many patterns and processes can be unified by considering organisms as consumers and processors of energy – embodied within the metabolic theory of ecology (MTE; Brown et al 2004) – is appealingly parsimonious. Ð1bÞ where Ne is the per capita rate of resource consumption (individuals sÀ1), b is the capture rate or search coefficient of the consumer (m2 sÀ1 or m3 sÀ1) – for simplicity, we treat capture rates and search coefficients as synonymous (but see Kalinkat et al 2013) – N is the resource density (individuals m2 or m3, constant in time), h (s) is consumer handling time, strictly incorporating the processes of subjugation and ingestion (but often reflecting digestion: see supplementary materials) and q is the scaling exponent, defining the extent to which the functional response departs from a decelerating hyperbola (Type II) towards a sigmoidal (Type III) form. Where q > 0 capture rates depend explicitly on N, often reflecting consumer learning, whereby capture rates increase with N, resulting from: (1) increased encounters (e.g. switching from passive to active searching), or (2) an increased ratio of captures to encounters
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