Interaction modifications lead to greater robustness than pairwise non-trophic effects in food webs

Experimental evidence for a hidden network of higher-order interactions in a diverse arthropod community

Transcending pairwise interactions in ecological networks remains a challenge.^1,2,3,4,5 Higher-order interactions (HOIs), the modulation of a pairwise interaction by a third species,⁶ are thought to play a particularly important role in stabilizing coexistence and maintaining species diversity.^{7,8,9,10,11,12} However, HOIs have so far only been demonstrated in models^{9,10,11,12,13,14} or isolated experimental systems including only a few interacting species.^7,8,15 Their ubiquity and importance at a community level in the real world remain unknown. We hypothesized that a complex network of HOIs could be constantly modifying pairwise interactions and shaping ecological communities and that consequently the outcome of pairwise interactions would be a product of many influences from distinct sources. Using field experiments, we tested how multiple interactions within a diverse arthropod community associated with the tropical shrub Baccharis dracunculifolia D.C. (Asteraceae) were modified by the removal of ant species or live or hatched insect galls (a non-trophic engineering effect) of the dominant galler species. We revealed an extensive hidden network of HOIs modifying each other and the "visible" pairwise interactions. Most pairwise interactions were affected indirectly by the manipulation of non-interacting taxonomic groups. The pervasiveness of these interaction modifications challenges pairwise approaches to understanding interaction outcomes and could shift our thinking about the structure and persistence of ecological communities. Investigating coexistence mechanisms involving interaction modulation by HOIs may be key to elucidating the underlying causes of the stability and persistence of ecological communities.

Surprising effects of cascading higher order interactions

Most species are embedded in multi-interaction networks. Consequently, theories focusing on simple pair-wise interactions cannot predict ecological and/or evolutionary outcomes. This study explores how cascading higher-order interactions (HOIs) would affect the population dynamics of a focal species. Employing a system that involves a myrmecophylic beetle, a parasitic wasp that attacks the beetle, an ant, and a parasitic fly that attacks the ant, the study explores how none, one, and two HOIs affect the parasitism and the sex ratio of the beetle. We conducted mesocosm experiments to examine these HOIs on beetle survival and sex ratio and found that the 1st degree HOI does not change the beetle's survival rate or sex ratio. However, the 2nd degree HOI significantly reduces the beetle's survival rate and changes its sex ratio from even to strongly female-biased. We applied Bayes' theorem to analyze the per capita survival probability of female vs. male beetles and suggested that the unexpected results might arise from complex eco-evolutionary dynamics involved with the 1st and 2nd degree HOIs. Field data suggested the HOIs significantly regulate the sex ratio of the beetle. As the same structure of HOIs appears in other systems, we believe the complexity associated with the 2nd degree HOI would be more common than known and deserve more scientific attention.

High-order correlations in species interactions lead to complex diversity-stability relationships for ecosystems

How ecosystems maintain stability is an active area of research. Inspired by applications of random matrix theory in nuclear physics, May showed decades ago that in an ecosystem model with many randomly interacting species, increasing species diversity decreases the stability of the ecosystem. There have since been many additions to May's efforts, one being an improved understanding the effect of mutualistic, competitive, or predator-prey-like correlations between pairs of species. Here we extend a random matrix technique developed in the context of spin-glass theory to study the effect of high-order correlations among species interactions. The resulting analytically solvable models include next-to-nearest-neighbor correlations in the species interaction network, such as the enemy of my enemy is my friend, as well as higher-order correlations. We find qualitative differences from May and others' models, including nonmonotonic diversity-stability relationships. Furthermore, inclusion of particular next-to-nearest-neighbor correlations in predator-prey as opposed to mutualist-competitive networks causes the former to transition to being more stable at higher species diversity. We discuss potential applicability of our results to microbiota engineering and to the ecology of interpredator interactions, such as cub predation between lions and hyenas as well as companionship between humans and dogs.

Interaction modifications lead to greater robustness than pairwise non-trophic effects in food webs

Considerable emphasis has been placed recently on the importance of incorporating non-trophic effects into our understanding of ecological networks. Interaction modifications are well-established as generating strong non-trophic impacts by modulating the strength of interspecific interactions. For simplicity and comparison with direct interactions within a network context, the consequences of interaction modifications have often been described as direct pairwise interactions. The consequences of this assumption have not been examined in non-equilibrium settings where unexpected consequences of interaction modifications are most likely. To test the distinct dynamic nature of these "higher-order" effects, we directly compare, using dynamic simulations, the robustness to extinctions under perturbation of systems where interaction modifications are either explicitly modelled or represented by corresponding equivalent pairwise non-trophic interactions. Full, multi-species representations of interaction modifications resulted in a greater robustness to extinctions compared to equivalent pairwise effects. Explanations for this increased stability despite apparent greater dynamic complexity can be found in additional routes for dynamic feedbacks. Furthermore, interaction modifications changed the relative vulnerability of species to extinction from those trophically connected close to the perturbed species towards those receiving a large number of modifications. Future empirical and theoretical research into non-trophic effects should distinguish interaction modifications from direct pairwise effects in order to maximize information about the system dynamics. Interaction modifications have the potential to shift expectations of species vulnerability based exclusively on trophic networks.