Tricky partners: native plants show stronger interaction preferences than their exotic counterparts

The coevolutionary consequences of biodiversity change

Coevolutionary selection is a powerful process shaping species interactions and biodiversity. Anthropogenic global environmental change is reshaping planetary biodiversity, including by altering the structure and intensity of interspecific interactions. However, remarkably little is understood of how coevolutionary selection is changing in the process. Here, we outline three interrelated pathways - change in evolutionary potential, change in community composition, and shifts in interaction trait distributions - that are expected to redirect coevolutionary selection under biodiversity change. Assessing how both ecological and evolutionary rules governing species interactions are disrupted under anthropogenic global change is of paramount importance to understand the past, present, and future of Earth's biodiversity.

Birds optimize fruit size consumed near their geographic range limits

Animals can adjust their diet to maximize energy or nutritional intake. For example, birds often target fruits that match their beak size because those fruits can be consumed more efficiently. We hypothesized that pressure to optimize diet-measured as matching between fruit and beak size-increases under stressful environments, such as those that determine species' range edges. Using fruit-consumption and trait information for 97 frugivorous bird and 831 plant species across six continents, we demonstrate that birds feed more frequently on closely size-matched fruits near their geographic range limits. This pattern was particularly strong for highly frugivorous birds, whereas opportunistic frugivores showed no such tendency. These findings highlight how frugivore interactions might respond to stressful conditions and reveal that trait matching may not predict resource use consistently.

Bumble bee diet breadth increases with local abundance and phenophase duration, not intraspecific variation in body size

Patterns of abundance across space and time, and intraspecific variation in body size, are two species attributes known to influence diet breadth and the structure of interaction networks. Yet, the relative influence of these attributes on diet breadth is often assumed to be equal among taxonomic groups, and the relationship between intraspecific variation in body size on interaction patterns is frequently neglected. We observed bee-flower interactions in multiple locations across Montana, USA, for two growing seasons and measured spatial and temporal patterns of abundance, along with interspecific and intraspecific variation in body size for prevalent species. We predicted that the association between spatial and temporal patterns of abundance and intraspecific variation in body size, and diet breadth, would be stronger for bumble bee compared to non-bumble bee species, because species with flexible diets and long activity periods can interact with more food items. Bumble bees had higher local abundance, occurred in many local communities, more intraspecific variation in body size, and longer phenophases compared to non-bumble bee species, but only local abundance and phenophase duration had a stronger positive association with the diet breadth of bumble bee compared to non-bumble bee species. Communities with a higher proportion of bumble bees also had higher intraspecific variation in body size at the network-level, and network-level intraspecific variation in body size was positively correlated with diet generalization. Our findings highlight that the association between species attributes and diet breadth changes depending on the taxonomic group, with implications for the structure of interaction networks.

Generalist and topologically central avian frugivores promote plant invasion unequally across land-bridge islands

Seed dispersal by frugivorous birds facilitates plant invasions, but it is poorly known how invasive plants integrate into native communities in fragmented landscapes. We surveyed plant-frugivore interactions, including an invasive plant (Phytolacca americana), on 22 artificial land-bridge islands (fragmented forests) in the Thousand Island Lake, China. Focusing on frugivory interactions that may lead to seed dispersal, we built ecological networks of studied islands both at the local island (community) and at landscape (metacommunity) levels. On islands with P. americana, we found that P. americana impacted local avian frugivory networks more on islands with species-poor plant communities and on isolated islands. Moreover, as P. americana interacted mainly with local core birds (generalists), this indicates reduced seed dispersal of native plants on invaded islands. At the landscape level, P. americana had established strong interactions with generalist birds that largely maintain seed-dispersal functions across islands, as revealed by their topologically central roles both in the regional plant-bird trophic network and in the spatial metanetwork. This indicates that generalist frugivorous birds may have facilitated the dispersal of P. americana across islands, making P. americana well integrated into the plant-frugivore mutualistic metacommunity. Taken together, our study demonstrates that the impact of plant invasion is context-dependent and that generalist native frugivores with high dispersal potential may accelerate plant invasion in fragmented landscapes. These findings highlight the importance of taking the functional roles of animal mutualists and habitat fragmentation into account when managing plant invasions and their impact on native communities.

Root diameter, host specificity and arbuscular mycorrhizal fungal community composition among native and exotic plant species

Plant root systems rely on a functionally diverse range of arbuscular mycorrhizal fungi to, among other benefits, extend their nutrient foraging. Extended nutrient foraging is likely of greatest importance to coarse-rooted plants, yet few studies have examined the link between root traits and arbuscular mycorrhizal fungal community composition. Here, we examine the relationship between root diameter and the composition of arbuscular mycorrhizal fungal communities in a range of native and exotic plant species. We characterized the arbuscular mycorrhizal fungal communities of 30 co-occurring native and exotic montane grassland/shrubland plant species in New Zealand. We found that plant root diameter and native/exotic status both strongly correlated with arbuscular mycorrhizal fungal community composition. Coarse-rooted plants had a lower diversity of mycorrhizal fungi compared with fine-rooted plants and associated less with generalist fungal partners. Exotic plants had a lower diversity of fungi and fewer associations with nondominant families of arbuscular mycorrhizal fungi compared with native plants. These observational patterns suggest that plants may differentially associate with fungal partners based on their root traits, with coarse-rooted plants being more specific in their associations. Furthermore, exotic plants may associate with dominant arbuscular mycorrhizal fungal taxa as a strategy in invasion.

A network perspective for sustainable agroecosystems

Nature-based management aims to improve sustainable agroecosystem production, but its efficacy has been variable. We argue that nature-based agroecosystem management could be significantly improved by explicitly considering and manipulating the underlying networks of species interactions. A network perspective can link species interactions to ecosystem functioning and stability, identify influential species and interactions, and suggest optimal management approaches. Recent advances in predicting the network roles of species from their functional traits could allow direct manipulation of network architecture through additions or removals of species with targeted traits. Combined with improved understanding of the structure and dynamics of networks across spatial and temporal scales and interaction types, including social-ecological, applying these tools to nature-based management can contribute to sustainable agroecosystems.

The contribution of mutualistic interactions to functional and phylogenetic diversity

Reduction of functional diversity (FD) and phylogenetic diversity (PD) likely affects ecosystem functions and reduces the potential of communities to respond to changes, such as climate change. Mutualistic interactions are essential for maintaining diversity, but their role has largely been ignored in conservation planning. We propose using a species' interaction niche - the diversity of its interaction partners - to measure a species' contribution to the maintenance of FD and PD via mutualistic interactions, and thus identify species and interspecific interactions that are particularly important for the conservation of ecosystem functions and evolutionary lineages in ecological communities. Our approach represents a switch in perspective that allows a direct assessment of the importance of mutualistic interactions for the maintenance of biodiversity and ecosystem functioning.

Spatial associations between plants and vegetation community characteristics provide insights into the processes influencing plant rarity

Determining the drivers of plant rarity is a major challenge in ecology. Analysing spatial associations between different plant species can provide an exploratory avenue for understanding the ecological drivers of plant rarity. Here, we examined the different types of spatial associations between rare and common plants to determine if they influence the occurrence patterns of rare species. We completed vegetation surveys at 86 sites in woodland, forest, and heath communities in south-east Australia. We also examined two different rarity measures to quantify how categorisation criteria affected our results. Rare species were more likely to have positive associations with both rare and common species across all three vegetation communities. However, common species had positive or negative associations with rare and other common species, depending on the vegetation community in which they occurred. Rare species were positively associated with species diversity in forest communities. In woodland communities, rare species were associated negatively with species diversity but positively associated with species evenness. Rare species with high habitat specificity were more clustered spatially than expected by chance. Efforts to understand the drivers of plant rarity should use rarity definitions that consider habitat specificity. Our findings suggest that examining spatial associations between plants can help understand the drivers of plant rarity.

Predicting direct and indirect non-target impacts of biocontrol agents using machine-learning approaches

Biological pest control (i.e. ‘biocontrol’) agents can have direct and indirect non-target impacts, and predicting these effects (especially indirect impacts) remains a central challenge in biocontrol risk assessment. The analysis of ecological networks offers a promising approach to understanding the community-wide impacts of biocontrol agents (via direct and indirect interactions). Independently, species traits and phylogenies have been shown to successfully predict species interactions and network structure (alleviating the need to collect quantitative interaction data), but whether these approaches can be combined to predict indirect impacts of natural enemies remains untested. Whether predictions of interactions (i.e. direct effects) can be made equally well for generalists vs. specialists, abundant vs. less abundant species, and across different habitat types is also untested for consumer-prey interactions. Here, we used two machine-learning techniques (random forest and k-nearest neighbour; KNN) to test whether we could accurately predict empirically-observed quantitative host-parasitoid networks using trait and phylogenetic information. Then, we tested whether the accuracy of machine-learning-predicted interactions depended on the generality or abundance of the interacting partners, or on the source (habitat type) of the training data. Finally, we used these predicted networks to generate predictions of indirect effects via shared natural enemies (i.e. apparent competition), and tested these predictions against empirically observed indirect effects between hosts. We found that random-forest models predicted host-parasitoid pairwise interactions (which could be used to predict attack of non-target host species) more successfully than KNN. This predictive ability depended on the generality of the interacting partners for KNN models, and depended on species’ abundances for both random-forest and KNN models, but did not depend on the source (habitat type) of data used to train the models. Further, although our machine-learning informed methods could significantly predict indirect effects, the explanatory power of our machine-learning models for indirect interactions was reasonably low. Combining machine-learning and network approaches provides a starting point for reducing risk in biocontrol introductions, and could be applied more generally to predicting species interactions such as impacts of invasive species.