Finding missing links in interaction networks

Documenting which species interact within ecological communities is challenging and labor intensive. As a result, many interactions remain unrecorded, potentially distorting our understanding of network structure and dynamics. We test the utility of four structural models and a new coverage‐deficit model for predicting missing links in both simulated and empirical bipartite networks. We find they can perform well, although the predictive power of structural models varies with the underlying network structure. The accuracy of predictions can be improved by ensembling multiple models. Augmenting observed networks with most‐likely missing links improves estimates of qualitative network metrics. Tools to identify likely missing links can be simple to implement, allowing the prioritization of research effort and more robust assessment of network properties

Natural enemies have inconsistent impacts on the coexistence of competing species

The role of natural enemies in promoting coexistence of competing species has generated substantial debate. Modern coexistence theory provides a detailed framework to investigate this topic, but there have been remarkably few empirical applications to the impact of natural enemies. We tested experimentally the capacity for a generalist enemy to promote coexistence of competing insect species, and the extent to which any impact can be predicted by trade-offs between reproductive rate and susceptibility to natural enemies. We used experimental mesocosms to conduct a fully factorial pairwise competition experiment for six rainforest Drosophila species, with and without a generalist pupal parasitoid. We then parameterised models of competition and examined the coexistence of each pair of Drosophila species within the framework of modern coexistence theory. We found idiosyncratic impacts of parasitism on pairwise coexistence, mediated through changes in fitness differences, not niche differences. There was no evidence of an overall reproductive rate–susceptibility trade-off. Pairwise reproductive rate–susceptibility relationships were not useful shortcuts for predicting the impact of parasitism on coexistence. Our results exemplify the value of modern coexistence theory in multi-trophic contexts and the importance of contextualising the impact of generalist natural enemies to determine their impact. In the set of species investigated, competition was affected by the higher trophic level, but the overall impact on coexistence cannot be easily predicted just from knowledge of relative susceptibility. Methodologically, our Bayesian approach highlights issues with the separability of model parameters within modern coexistence theory and shows how using the full posterior parameter distribution improves inferences. This method should be widely applicable for understanding species coexistence in a range of systems

Identifying important interaction modifications in ecological systems

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

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

1.Considerable emphasis has been placed recently on the importance of incorporating non‐trophic effects in to our understanding of ecological networks. Interaction modifications are well established as generating strong non‐trophic impacts by modulating the strength of inter‐specific interactions. 2.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. 3.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. 4.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. 5.Future empirical and theoretical research into non‐trophic effects should distinguish interaction modifications from direct pairwise effects in order to maximise information about the system dynamics. Interaction modifications have the potential to shift expectations of species vulnerability based exclusively on trophic networks.</p

Trophic interaction modifications: An empirical and theoretical framework

Consumer-resource interactions are often influenced by other species in the community. At present these “trophic interaction modifications” are rarely included in ecological models despite demonstrations that they can drive system dynamics. Here we advocate and extend an approach that has the potential to unite and represent this key group of non-trophic interactions by emphasising the change to trophic interactions induced by modifying species. We highlight the opportunities this approach brings in comparison to frameworks that coerce trophic interaction modifications into pairwise relationships. To establish common frames of reference and explore the value of the approach, we set out a range of metrics for the ‘strength’ of an interaction modification which incorporate increasing levels of contextual information about the system. Through demonstrations in three-species model systems, we establish that these metrics capture complimentary aspects of interaction modifications. We show how the approach can be used in a range of empirical contexts; we identify as specific gaps in current understanding experiments with multiple levels of modifier species and the distributions of modifications in networks. The trophic interaction modification approach we propose can motivate and unite empirical and theoretical studies of system dynamics, providing a route to confront ecological complexity

Identifying important interaction modifications in ecological systems

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

Temporally robust occupancy frequency distributions in riverine metacommunities explained by local biodiversity regulation

Aim: The mechanisms determining the distribution of the number of sites species occupy, the occupancy frequency distribution (OFD), remain incompletely understood despite decades of research. To explore the dominant mechanisms responsible for the shape and temporal dynamics of empirical OFD, we develop a simple patch occupancy framework with intrinsically regulated local richness and fit the model to a highly replicated dataset describing macroinvertebrate, macrophyte and diatom occupancy. Location: England. Time period: Up to (Formula presented.) years between 1990 and 2020. Major taxa studied: Macroinvertebrates, macrophytes and diatoms. Methods: We study the OFD in a highly replicated dataset of freshwater metacommunities in England across time. We consider temporal change in species richness, composition, and in the shape of the OFD. Goodness-of-fit of the steady state of a simple patch occupancy model—which predicts a log-series OFD—to the empirical observations is assessed. Additionally, we test the capacity of the model to predict metacommunity-scale processes. Results: Our model provides a consistently good fit to empirical OFDs. It can additionally be used to predict metacommunity-scale species turnover. Main conclusions: Our results support the view that metacommunity structure reflects a dynamic steady state controlled by local limits to coexistence