Identifying important interaction modifications in ecological systems

Abstract

Trophic interaction modifications, where a consumer–resource link is affected by additional species, are widespread and significant causes of non‐trophic effects in ecological networks. The sheer number of potential interaction modifications in ecological systems poses a considerable challenge, making prioritisation for empirical study essential. Here, we introduce measures to quantify the topological relationship of individual interaction modifications relative to the underlying network. We use these, together with measures for the strength of trophic interaction modifications, to identify features of modifications that are most likely to exert significant effects on the dynamics of whole systems. Using a set of simulated food webs and randomly distributed interaction modifications, we test whether a subset of interaction modifications important for the local stability and direction of species responses to perturbation of complex networks can be identified. We show that trophic interaction modifications have particular importance for dynamics when they affect interactions with a high biomass flux, connect species otherwise distantly linked, and where high trophic‐level species modify interactions lower in the food web. In contrast, the centrality of modifications in the network provided little information. This work demonstrates that analyses of interaction modifications can be tractable at the network scale and highlights the importance of understanding the relationship between the distributions of trophic and non‐trophic effects.

Some neighbours are better than others: Variation in associational effects among plants in an old field community

“…Empirical work demonstrates that these 'trophic interaction modifications' (Golubski & Abrams, 2011;Terry et al, 2017;Wootton, 1993) can drive population dynamics (Tack et al, 2011) and affect how communities respond to perturbation (Barbosa et al, 2017). Furthermore, theory suggests that the strength, direction and distribution of trophic interaction modifications within food webs influence community stability (Arditi et al, 2005;Terry et al, 2020) and ecosystem function (Goudard & Loreau, 2008). However, we know little about how trophic interaction modifications vary in strength and direction among many diverse potential modifier species in natural communities (Terry et al, 2020;Wootton & Emmerson, 2005).…”

“…Furthermore, theory suggests that the strength, direction and distribution of trophic interaction modifications within food webs influence community stability (Arditi et al, 2005;Terry et al, 2020) and ecosystem function (Goudard & Loreau, 2008). However, we know little about how trophic interaction modifications vary in strength and direction among many diverse potential modifier species in natural communities (Terry et al, 2020;Wootton & Emmerson, 2005). This limits our understanding of when trophic interaction modifications should be included in predictive models of population dynamics, and of the role of trophic interaction modifications in structuring communities more generally.…”

“…We estimated effects of each neighbour species' presence (experimentally manipulated) and biomass (using unmanipulated variation in neighbour biomass among experimental replicates) as complementary measures. Manipulating the presence versus absence of a neighbour provides key information about the species' impact (Wootton, 1997), can be used to estimate its per-capita effect (which is typically used to represent interaction strength or trophic interaction modifications in models; Berlow et al, 2004;Golubski & Abrams, 2011;Terry et al, 2020), and is logistically feasible for many neighbour species at once. Together, the effects of neighbour presence and biomass also give us an idea about whether the strength of a neighbour's associational effect changes non-linearly with increasing biomass; non-linearity is a potentially important feature for determining how associational effects from multiple neighbours combine to influence population and community dynamics (Abrams, 2001;Underwood et al, 2014).…”

Beyond body size—new traits for new heights in trait-based modelling of predator-prey dynamics

“…Such work is both laborious and often imprecise, even for the links within a subset of a food web [ 4 ]. Additionally, some elements, such as non-consumptive interactions among multiple predators, cannot be understood solely from a pairwise predator-prey perspective because the presence of a third species modifies the interaction [ 5 ]. Although dynamic food-webs can accurately describe observed interactions, their complexity has made it unwieldy to map the abundance dynamics of diverse predator-prey assemblages in nature.…”

“…Mechanisms include avoidance of intraguild predation and interference among predator species as well as facilitation [ 22 , 26 – 29 ]. Such interactions are not described by the original ATN model, and so the model poorly captures their population-level effects [ 5 , 17 ]. Jonsson et al [ 17 ]’s results, that increasing trophic complexity weakened the ability of their model to explain the data, strongly suggested that it is a lack of behavior-based non-consumptive interspecific interference effects in the ATN model that is the main cause for its inability to accurately predict trophic interaction strength in more complex webs.…”