Predicting tipping points in mutualistic networks through dimension reduction

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1714958115/-/DCSupplemental.Peer reviewedPublisher PD

Community structure determines the predictability of population collapse

1. Early warning signals (EWS) are phenomenological tools that have been proposed as predictors of the collapse of biological systems. Although a growing body of work has shown the utility of EWS based on either statistics derived from abundance data or shifts in phenotypic traits such as body size, so far this work has largely focused on single species populations. 2. However, to predict reliably the future state of ecological systems, which inherently could consist of multiple species, understanding how reliable such signals are in a community context is critical. 3. Here, reconciling quantitative trait evolution and Lotka–Volterra equations, which allow us to track both abundance and mean traits, we simulate the collapse of populations embedded in mutualistic and multi‐trophic predator–prey communities. Using these simulations and warning signals derived from both population‐ and community‐level data, we showed the utility of abundance‐based EWS, as well as metrics derived from stability‐landscape theory (e.g. width and depth of the basin of attraction), were fundamentally linked. Thus, the depth and width of such stability‐landscape curves could be used to identify which species should exhibit the strongest EWS of collapse. 4. The probability a species displays both trait and abundance‐based EWS was dependent on its position in a community, with some species able to act as indicator species. In addition, our results also demonstrated that in general trait‐based EWS were less reliable in comparison with abundance‐based EWS in forecasting species collapses in our simulated communities. Furthermore, community‐level abundance‐based EWS were fairly reliable in comparison with their species‐level counterparts in forecasting species‐level collapses. 5. Our study suggests a holistic framework that combines abundance‐based EWS and metrics derived from stability‐landscape theory that may help in forecasting species loss in a community context

Estimating the risk of species interaction loss in mutualistic communities

Funder: Royal Commission for the Exhibition of 1851 (GB)Funder: Cambridge TrustFunder: Cambridge Depatment of ZoologyFunder: Grantham Foundation for the Protection of the Environment; funder-id: http://dx.doi.org/10.13039/100008118Funder: Kenneth Miller TrustFunder: ArcadiaInteractions between species generate the functions on which ecosystems and humans depend. However, we lack an understanding of the risk that interaction loss poses to ecological communities. Here, we quantify the risk of interaction loss for 4,330 species interactions from 41 empirical pollination and seed dispersal networks across 6 continents. We estimate risk as a function of interaction vulnerability to extinction (likelihood of loss) and contribution to network feasibility, a measure of how much an interaction helps a community tolerate environmental perturbations. Remarkably, we find that more vulnerable interactions have higher contributions to network feasibility. Furthermore, interactions tend to have more similar vulnerability and contribution to feasibility across networks than expected by chance, suggesting that vulnerability and feasibility contribution may be intrinsic properties of interactions, rather than only a function of ecological context. These results may provide a starting point for prioritising interactions for conservation in species interaction networks in the future

Temporal Dynamics and Seed Dispersal in Plant-Frugivore Communities of the Dominican Republic

Plant-animal mutualisms are a foundational component of biodiversity in terrestrial ecosystems. Most tropical forest plants have adapted to produce fleshy fruits to attract frugivorous animals to disperse seeds. Interaction patterns among plant taxa and their seed dispersers are driven by a complex suite of factors involving their evolutionary history and environmental context, and the structure of these mutualistic networks are theoretically tied to their ecological function. I carried out a series of field studies to investigate the temporal dynamics of mutualistic interactions of plant and avian frugivore communities in the central Dominican Republic and how their characteristics affect seed dispersal in agricultural landscapes. I first investigated the effects of reproductive phenology of a tropical tree (Guarea guidonia) on the temporal variation of avian foraging behavior and seed dispersal patterns. I found that temporal variation in seed dispersal was driven most by landscape-level dynamics in the availability of alternative resources rather than tree– or neighborhood–level fruit production. I proceeded to expand my focus on the processes of frugivory and seed dispersal by monitoring the phenology of six local communities and characterizing the temporal dynamics of plant-frugivore networks across a full annual period. By applying multilayer network analyses, I identified a tendency of birds to shift between temporally defined modules in nonrandom patterns that suggest a prevailing influence of resource partitioning on consumer preferences across seasonal time periods. By systematically sampling seed dispersal at a subset of these monitoring sites, I demonstrated how frugivory measures from network data predict their dispersal potential and ability to colonize new patches in heterogenous landscapes. Finally, I applied network data from frugivorous bird species to design an experiment to test the effect sounds of frugivore taxa with varying degrees of fruit consumption on the movement behavior and use of artificial perches in abandoned pastures by potential seed dispersers, finding that frugivorous bird sounds stimulate an increase in the frequency of avian visitors to degraded habitat. Collectively, my investigations provide insight into the processes of frugivory and seed dispersal in a previously undocumented region and reveal how interaction patterns can translate to ecological outcomes