Disentangling the nonlinear effects of habitat complexity on functional responses

Abstract

Structural complexity of habitats modifies trophic interactions by providing refuges and altering predator and prey behaviour. Nonlinear effects on trophic interaction strengths driven by these mechanisms may alter food web dynamics and community structure in response to habitat modifications. However, changes in functional response, the relationship between prey density and feeding rate, along habitat complexity (HC) gradients are little understood. We quantified functional responses along a HC gradient from an entirely unstructured to highly structured habitat in a freshwater system, using dragonfly larvae (Aeshna cyanea) preying on Chaoborus obscuripes larvae. To disentangle mechanisms by which changes in HC affect functional responses, we used two different approaches—a population‐level and a behavioural experiment—applied an information theoretic approach to identify plausible links between HC and functional response parameters, and compared our results to previous studies. Functional response shape did not change, but we found strong evidence for nonlinear dependence of attack rate and handling time on HC in our study. Combined results from both experiments imply that attack rate increased stepwise between the unstructured and structured habitats in line with the threshold hypothesis, because the predators gained better access to the prey. Handling time was lowest at an intermediate HC level in the population‐level experiment while the direct estimate of handling time did not vary with HC in the behavioural experiment. These differences point towards HC‐driven changes in foraging activity and other predator and prey behaviour. Most previous studies reported stepwise decrease in attack rate in line with the threshold hypothesis or no change with increasing HC. Moreover, changes in the handling time parameter with HC appear to be relatively common but not conforming to the threshold hypothesis. Overall, increased HC appears to, respectively, weaken and strengthen trophic links in 2D and 3D predator–prey interactions. We conclude that detailed understanding of HC effects on food webs requires complementary experimental approaches across HC gradients that consider predator foraging strategies and predator and prey behaviour. Such studies can also help guide conservation efforts as addition of structural elements is frequently used for restoration of degraded aquatic habitats.

From individuals to communities: Habitat complexity affects all levels of organization in aquatic environments

“…Barrios‐O'Neill et al (2016) thus predicted higher population stability for prey living on complex substrates than for prey on simple substrates based on extensive predation experiments with multiple species and size classes of freshwater predatory fish and crustaceans. However, most laboratory studies suggest that Holling Type II functional response, with the propensity to destabilize food web dynamics, is most common across taxa and different types and levels of HC (Mocq et al, 2021). Shifts from Type II to Type III are rare and come mainly from experiments on marine taxa (Alexander et al, 2012; Barrios‐O'Neill et al, 2016; Long & Whitefleet‐Smith, 2013).…”

“…At least three levels of HC are needed to distinguish between the main qualitative responses to HC (Figure 3), but more levels are advisable to allow for detection of threshold‐ or optimum effects of HC (Mocq et al, 2021). Ecological systems are complex, with many variables and agents at play even in simplified settings (Doak et al, 2008).…”

“…Shifts from Type II to Type III are rare and come mainly from experiments on marine taxa (Alexander et al, 2012; Barrios‐O'Neill et al, 2016; Long & Whitefleet‐Smith, 2013). On the other hand, HC effects on key functional response parameters, attack rate and handling time, appear to differ between 2D and 3D environments (for details see Mocq et al, 2021).…”

“…HC levels in some of these studies include only simple versus complex environments (e.g., De la Parra et al, 2016; Fulan & Anjos, 2015; Gregor & Anderson, 2016; Schmidt‐Drewello et al, 2016). The increasing use of HC gradients (Carroll et al, 2015; Lee et al, 2017) is commendable as it better reflects natural conditions and may reveal nonlinear dependence of trophic interactions on HC, with consequences on population and community stability (Mocq et al, 2021). Many possible response shapes can however occur for HC effects, ranging from no/constant response to linear and various types of nonlinear responses (Figure 3).…”

Quantifying predator functional responses under field conditions reveals interactive effects of temperature and interference with sex and stage

“…Functional responses were originally defined as the relationship between predator feeding rates and the densities of their prey (Holling, 1959; Solomon, 1949). In the intervening decades, however, we have discovered a multitude of factors other than resource densities that influence predator feeding rates such as: predator density/interference (DeLong & Vasseur, 2011; Hassell & Varley, 1969; Novak & Stouffer, 2021), temperature (Thompson, 1978; Uiterwaal & DeLong, 2020), predator and prey body sizes (Rall et al, 2012; Vucic-Pestic et al, 2010), habitat complexity (Mocq et al, 2021; Toscano & Griffen, 2013), alternative prey availability (Hossie et al, 2021; Murdoch, 1969), and others. We also have learned that the effects of these factors on predator feeding rates have important ramifications for population dynamics and their stability (Amarasekare, 2015; Beddington, 1975; Coblentz & DeLong, 2020; Murdoch & Oaten, 1975; O’Connor et al, 2011; Otto et al, 2007; Uszko et al, 2017) and are important for understanding how global changes in climate, habitat, and the movement of species are likely to influence predator-prey interactions and communities (Dick et al, 2014; Gilbert et al, 2014; Mocq et al, 2021).…”