Macroevolution of the plant-hummingbird pollination system.

Plant-hummingbird interactions are considered a classic example of coevolution, a process in which mutually dependent species influence each other's evolution. Plants depend on hummingbirds for pollination, whereas hummingbirds rely on nectar for food. As a step towards understanding coevolution, this review focuses on the macroevolutionary consequences of plant-hummingbird interactions, a relatively underexplored area in the current literature. We synthesize prior studies, illustrating the origins and dynamics of hummingbird pollination across different angiosperm clades previously pollinated by insects (mostly bees), bats, and passerine birds. In some cases, the crown age of hummingbirds pre-dates the plants they pollinate. In other cases, plant groups transitioned to hummingbird pollination early in the establishment of this bird group in the Americas, with the build-up of both diversities coinciding temporally, and hence suggesting co-diversification. Determining what triggers shifts to and away from hummingbird pollination remains a major open challenge. The impact of hummingbirds on plant diversification is complex, with many tropical plant lineages experiencing increased diversification after acquiring flowers that attract hummingbirds, and others experiencing no change or even a decrease in diversification rates. This mixed evidence suggests that other extrinsic or intrinsic factors, such as local climate and isolation, are important covariables driving the diversification of plants adapted to hummingbird pollination. To guide future studies, we discuss the mechanisms and contexts under which hummingbirds, as a clade and as individual species (e.g. traits, foraging behaviour, degree of specialization), could influence plant evolution. We conclude by commenting on how macroevolutionary signals of the mutualism could relate to coevolution, highlighting the unbalanced focus on the plant side of the interaction, and advocating for the use of species-level interaction data in macroevolutionary studies.

Transformation starts at the periphery of networks where pushback is less.

Complex systems ranging from societies to ecological communities and power grids may be viewed as networks of connected elements. Such systems can go through critical transitions driven by an avalanche of contagious change. Here we ask, where in a complex network such a systemic shift is most likely to start. Intuitively, a central node seems the most likely source of such change. Indeed, topological studies suggest that central nodes can be the Achilles heel for attacks. We argue that the opposite is true for the class of networks in which all nodes tend to follow the state of their neighbors, a category we call two-way pull networks. In this case, a well-connected central node is an unlikely starting point of a systemic shift due to the buffering effect of connected neighbors. As a result, change is most likely to cascade through the network if it spreads first among relatively poorly connected nodes in the periphery. The probability of such initial spread is highest when the perturbation starts from intermediately connected nodes at the periphery, or more specifically, nodes with intermediate degree and relatively low closeness centrality. Our finding is consistent with empirical observations on social innovation, and may be relevant to topics as different as the sources of originality of art, collapse of financial and ecological networks and the onset of psychiatric disorders.

Mechanistic interactions as the origin of modularity in biological networks.

Biological networks are often modular. Explanations for this peculiarity either assume an adaptive advantage of a modular design such as higher robustness, or attribute it to neutral factors such as constraints underlying network assembly. Interestingly, most insights on the origin of modularity stem from models in which interactions are either determined by highly simplistic mechanisms, or have no mechanistic basis at all. Yet, empirical knowledge suggests that biological interactions are often mediated by complex structural or behavioural traits. Here, we investigate the origins of modularity using a model in which interactions are determined by potentially complex traits. Specifically, we model system elements-such as the species in an ecosystem-as finite-state machines (FSMs), and determine their interactions by means of communication between the corresponding FSMs. Using this model, we show that modularity probably emerges for free. We further find that the more modular an interaction network is, the less complex are the traits that mediate the interactions. Altogether, our results suggest that the conditions for modularity to evolve may be much broader than previously thought.

Biotic homogenization, lower soil fungal diversity and fewer rare taxa in arable soils across Europe.

Soil fungi are a key constituent of global biodiversity and play a pivotal role in agroecosystems. How arable farming affects soil fungal biogeography and whether it has a disproportional impact on rare taxa is poorly understood. Here, we used the high-resolution PacBio Sequel targeting the entire ITS region to investigate the distribution of soil fungi in 217 sites across a 3000 km gradient in Europe. We found a consistently lower diversity of fungi in arable lands than grasslands, with geographic locations significantly impacting fungal community structures. Prevalent fungal groups became even more abundant, whereas rare groups became fewer or absent in arable lands, suggesting a biotic homogenization due to arable farming. The rare fungal groups were narrowly distributed and more common in grasslands. Our findings suggest that rare soil fungi are disproportionally affected by arable farming, and sustainable farming practices should protect rare taxa and the ecosystem services they support.

The Role of Indirect Effects in Coevolution along the Mutualism-Antagonism Continuum.

AbstractThe web of interactions in a community drives the coevolution of species. Yet it is unclear how the outcome of species interactions influences the coevolutionary dynamics of communities. This is a pressing matter, as changes to the outcome of interactions may become more common with human-induced global change. Here, we combine network and evolutionary theory to explore coevolutionary outcomes in communities harboring mutualistic and antagonistic interactions. We show that as the ratio of mutualistic to antagonistic interactions decreases, selection imposed by direct partners outweighs that imposed by indirect partners. This weakening of indirect effects results in communities composed of species with dissimilar traits and fast rates of adaptation. These changes are more pronounced when specialist consumers are the first species to engage in antagonistic interactions. Hence, a shift in the outcome of species interactions may reverberate across communities and alter the direction and speed of coevolution.

Plant choice between arbuscular mycorrhizal fungal species results in increased plant P acquisition.

Arbuscular mycorrhizal fungi (AMF) are plant root symbionts that provide phosphorus (P) to plants in exchange for photosynthetically fixed carbon (C). Previous research has shown that plants-given a choice among AMF species-may preferentially allocate C to AMF species that provide more P. However, these investigations rested on a limited set of plant and AMF species, and it therefore remains unclear how general this phenomenon is. Here, we combined 4 plant and 6 AMF species in 24 distinct plant-AMF species compositions in split-root microcosms, manipulating the species identity of AMF in either side of the root system. Using 14C and 32P/33P radioisotope tracers, we tracked the transfer of C and P between plants and AMF, respectively. We found that when plants had a choice of AMF species, AMF species which transferred more P acquired more C. Evidence for preferential C allocation to more beneficial AMF species within individual plant roots was equivocal. However, AMF species which transferred more P to plants did so at lower C-to-P ratios, highlighting the importance both of absolute and relative costs of P acquisition from AMF. When plants had a choice of AMF species, their shoots contained a larger total amount of P at higher concentrations. Our results thus highlight the benefits of plant C choice among AMF for plant P acquisition.

Genome-wide association study of aphid abundance highlights a locus affecting plant growth and flowering in Arabidopsis thaliana.

Plant life-history traits, such as size and flowering, contribute to shaping variation in herbivore abundance. Although plant genes involved in physical and chemical traits have been well studied, less is known about the loci linking plant life-history traits and herbivore abundance. Here, we conducted a genome-wide association study (GWAS) of aphid abundance in a field population of Arabidopsis thaliana. This GWAS of aphid abundance detected a relatively rare but significant variant on the third chromosome of A. thaliana, which was also suggestively but non-significantly associated with the presence or absence of inflorescence. Out of candidate genes near this significant variant, a mutant of a ribosomal gene (AT3G13882) exhibited slower growth and later flowering than a wild type under laboratory conditions. A no-choice assay with the turnip aphid, Lipaphis erysimi, found that aphids were unable to successfully establish on the mutant. Our GWAS of aphid abundance unexpectedly found a locus affecting plant growth and flowering.

Five fundamental ways in which complex food webs may spiral out of control.

Theory suggests that increasingly long, negative feedback loops of many interacting species may destabilize food webs as complexity increases. Less attention has, however, been paid to the specific ways in which these 'delayed negative feedbacks' may affect the response of complex ecosystems to global environmental change. Here, we describe five fundamental ways in which these feedbacks might pave the way for abrupt, large-scale transitions and species losses. By combining topological and bioenergetic models, we then proceed by showing that the likelihood of such transitions increases with the number of interacting species and/or when the combined effects of stabilizing network patterns approach the minimum required for stable coexistence. Our findings thus shift the question from the classical question of what makes complex, unaltered ecosystems stable to whether the effects of, known and unknown, stabilizing food-web patterns are sufficient to prevent abrupt, large-scale transitions under global environmental change.

Indirect effects shape species fitness in coevolved mutualistic networks.

Ecological interactions are one of the main forces that sustain Earth's biodiversity. A major challenge for studies of ecology and evolution is to determine how these interactions affect the fitness of species when we expand from studying isolated, pairwise interactions to include networks of interacting species1-4. In networks, chains of effects caused by a range of species have an indirect effect on other species they do not interact with directly, potentially affecting the fitness outcomes of a variety of ecological interactions (such as mutualism)5-7. Here we apply analytical techniques and numerical simulations to 186 empirical mutualistic networks and show how both direct and indirect effects alter the fitness of species coevolving in these networks. Although the fitness of species usually increased with the number of mutualistic partners, most of the fitness variation across species was driven by indirect effects. We found that these indirect effects prevent coevolving species from adapting to their mutualistic partners and to other sources of selection pressure in the environment, thereby decreasing their fitness. Such decreases are distributed in a predictable way within networks: peripheral species receive more indirect effects and experience higher reductions in fitness than central species. This topological effect was also evident when we analysed an empirical study of an invasion of pollination networks by honeybees. As honeybees became integrated as a central species within networks, they increased the contribution of indirect effects on several other species, reducing their fitness. Our study shows how and why indirect effects can govern the adaptive landscape of species-rich mutualistic assemblages.

Modularity in host-parasite mixed networks: interaction configuration shifts based on human perturbation and parasitism form.

Parasitism is an association based on host individual traits and environmental factors. The complexity of this type of interaction is often lost when studying species-by-species interaction networks. Here we analyze changes in modularity - a metric describing groups of nodes interacting much more frequently among themselves than they do with nodes of other modules, considering the host individual variation and the different forms of parasitism: ecto- and endo-parasitism. For this, we studied mixed networks: bipartite networks comprising host individuals and parasite species as two sets of nodes interacting with each other. We used a fish-parasite mixed network from a highly perturbed coastal river to understand how an anthropogenic perturbation gradient influences the modular structure of host-parasite networks. In addition, we tested how host individual traits drove module configuration within host-parasite mixed networks. Our results showed that different forms of parasitism respond differently to the environment: modularity in fish-ectoparasite networks increased with human perturbation, but modularity was not related to human perturbation in fish-endoparasite networks. In addition, mixed network modules were intrinsically related to individual variation, with host intensity of infection being the most important trait, regardless of the parasite's life form. The effect of total abundance over network structure indicates signs of changes in community equilibrium, with an increase in species with opportunistic behaviors. Module composition was also related to host fitness and body size, which were most predictive in more preserved and diverse river sections. Overall, our results indicate that host-parasite networks are sensitive to ecological gradients marked by human perturbation and that host individual fitness helps to determine network structure.

Rigorous Criteria for the Collapse of Nonlinear Cooperative Networks.

Many real-world complex systems, when hitting a tipping point, undergo irreversible sudden shifts that can eventually take a great toll on humanity and the natural world, such as ecosystem collapses, disease outbreaks, etc. Previous work has adopted approximations to predict the tipping points, but due to the nature of nonlinearity, this may lead to unexpected errors in predicting real-world systems. Here we obtain the rigorous bounds of the tipping points for general nonlinear cooperative networks. Our results offer two rigorous criteria that determine the collapse and survival of such a system. These two criteria are decided by the combined effect of dynamical parameters and interaction topology.

The Resilience of Plant-Pollinator Networks.

There is growing awareness of pollinator declines worldwide. Conservation efforts have mainly focused on finding the direct causes, while paying less attention to building a systemic understanding of the fragility of these communities of pollinators. To fill this gap, we need operational measures of network resilience that integrate two different approaches in theoretical ecology. First, we should consider the range of conditions compatible with the stable coexistence of all of the species in a community. Second, we should address the rate and shape of network collapse once this safe operational space is exited. In this review, we describe this integrative approach and consider several mechanisms that may enhance the resilience of pollinator communities, chiefly rewiring the network of interactions, increasing heterogeneity, allowing variance, and enhancing coevolution. The most pressing need is to develop ways to reduce the gap between these theoretical recommendations and practical applications. This perspective shifts the emphasis from traditional approaches focusing on the equilibrium states to strategies that allow pollination networks to cope with global environmental change.

Effects of habitat destruction on coevolving metacommunities.

Habitat destruction is a growing threat to biodiversity and ecosystem services. The ecological consequences of habitat loss and fragmentation involve reductions in species abundance and even the extinction of species and their interactions. However, we do not yet understand how habitat loss alters the coevolutionary trajectories of the remaining species or how coevolution, in turn, affects their response to habitat loss. To investigate this, we develop a spatially explicit model which couples metacommunity and coevolutionary dynamics. We show that, by changing the size, composition and structure of local networks, habitat destruction increases the diversity of coevolutionary trajectories of mutualists across the landscape. Conversely, in antagonistic communities, some species increase while others reduce their spatial trait heterogeneity. Furthermore, we show that while coevolution dampens the negative effects of habitat destruction in mutualistic networks, its effects on the persistence of antagonistic communities tend to be smaller and less predictable.

Hidden effects of habitat restoration on the persistence of pollination networks.

Past and recent studies have focused on the effects of global change drivers such as species invasions on species extinction. However, as we enter the United Nations Decade of Ecosystem Restoration the aim must switch to understanding how invasive-species management affects the persistence of the remaining species in a community. Focusing on plant-pollinator interactions, we test how species persistence is affected by restoration via the removal of invasive plant species. Restoration had a clear positive effect on plant persistence, whereas there was no difference between across treatments for pollinator persistence in the early season, but a clear effect in late season, with higher persistence in unrestored sites. Network structure affected only pollinator persistence, while centrality had a strong positive effect on both plants and pollinators. Our results suggest a hidden effect of invasive plants-although they may compete with native plant species, invasive plants may provide important resources for pollinators, at least in the short term.

Mycoheterotrophic plants preferentially target arbuscular mycorrhizal fungi that are highly connected to autotrophic plants.

How mycoheterotrophic plants that obtain carbon and soil nutrients from fungi are integrated in the usually mutualistic arbuscular mycorrhizal networks is unknown. Here, we compare autotrophic and mycoheterotrophic plant associations with arbuscular mycorrhizal fungi and use network analysis to investigate interaction preferences in the tripartite network. We sequenced root tips from autotrophic and mycoheterotrophic plants to assemble the combined tripartite network between autotrophic plants, mycorrhizal fungi and mycoheterotrophic plants. We compared plant-fungi interactions between mutualistic and antagonist networks, and searched for a diamond-like module defined by a mycoheterotrophic and an autotrophic plant interacting with the same pair of fungi to investigate whether pairs of fungi simultaneously linked to plant species from each interaction type were overrepresented throughout the network. Mycoheterotrophic plants as a group interacted with a subset of the fungi detected in autotrophs but are indirectly linked to all autotrophic plants, and fungi with a high overlap in autotrophic partners tended to interact with a similar set of mycoheterotrophs. Moreover, pairs of fungi sharing the same mycoheterotrophic and autotrophic plant species are overrepresented in the network. We hypothesise that the maintenance of antagonistic interactions is maximised by targeting well linked mutualistic fungi, thereby minimising the risk of carbon supply shortages.

A keystone gene underlies the persistence of an experimental food web.

Genes encode information that determines an organism's fitness. Yet we know little about whether genes of one species influence the persistence of interacting species in an ecological community. Here, we experimentally tested the effect of three plant defense genes on the persistence of an insect food web and found that a single allele at a single gene promoted coexistence by increasing plant growth rate, which in turn increased the intrinsic growth rates of species across multiple trophic levels. Our discovery of a "keystone gene" illustrates the need to bridge between biological scales, from genes to ecosystems, to understand community persistence.

Extinction, coextinction and colonization dynamics in plant-hummingbird networks under climate change.

Climate-driven range shifts may cause local extinctions, while the accompanying loss of biotic interactions may trigger secondary coextinctions. At the same time, climate change may facilitate colonizations from regional source pools, balancing out local species loss. At present, how these extinction-coextinction-colonization dynamics affect biological communities under climate change is poorly understood. Using 84 communities of interacting plants and hummingbirds, we simulated patterns in climate-driven extinctions, coextinctions and colonizations under future climate change scenarios. Our simulations showed clear geographic discrepancies in the communities' vulnerability to climate change. Andean communities were the least affected by future climate change, as they experienced few climate-driven extinctions and coextinctions while having the highest colonization potential. In North America and lowland South America, communities had many climate-driven extinctions and few colonization events. Meanwhile, the pattern of coextinction was highly dependent on the configuration of networks formed by interacting hummingbirds and plants. Notably, North American communities experienced proportionally fewer coextinctions than other regions because climate-driven extinctions here primarily affected species with peripheral network roles. Moreover, coextinctions generally decreased in communities where species have few overlapping interactions, that is, communities with more complementary specialized and modular networks. Together, these results highlight that we should not expect colonizations to adequately balance out local extinctions in the most vulnerable ecoregions.

Cheating in Mutualisms Promotes Diversity and Complexity.

AbstractMutualisms such as those between flowering plants and their pollinators are common in nature. Yet understanding their persistence in the face of cheaters and identifying the mechanisms behind their stunning diversity provide formidable challenges for evolutionary biologists. To shed light onto these questions, we introduce an individual-based model of two coevolving species in which individuals of one species use a Boolean circuit to discriminate between cooperators and cheaters in the other species. This conveys the idea that interactions are often mediated by complex biological processes rather than the matching of a single trait, as often assumed in models of coevolution. Our results show that cheating promotes diversification and complex discrimination mechanisms at the cost of a higher risk for mutualism to collapse. This result is mediated by an inverse relationship between mutational robustness and organismal complexity.

The joint role of coevolutionary selection and network structure in shaping trait matching in mutualisms.

Coevolution can sculpt remarkable trait similarity between mutualistic partners. Yet, it remains unclear which network topologies and selection regimes enhance trait matching. To address this, we simulate coevolution in topologically distinct networks under a gradient of mutualistic selection strength. We describe three main insights. First, trait matching is jointly influenced by the strength of mutualistic selection and the structural properties of the network where coevolution is unfolding. Second, the strength of mutualistic selection determines the network descriptors better correlated with higher trait matching. While network modularity enhances trait matching when coevolution is weak, network connectance does so when coevolution is strong. Third, the structural properties of networks outrank those of modules or species in determining the degree of trait matching. Our findings suggest networks can both enhance or constrain trait matching, depending on the strength of mutualistic selection.

Language extinction triggers the loss of unique medicinal knowledge.

Over 30% of the 7,400 languages in the world will no longer be spoken by the end of the century. So far, however, our understanding of whether language extinction may result in the loss of linguistically unique knowledge remains limited. Here, we ask to what degree indigenous knowledge of medicinal plants is associated with individual languages and quantify how much indigenous knowledge may vanish as languages and plants go extinct. Focusing on three regions that have a high biocultural diversity, we show that over 75% of all 12,495 medicinal plant services are linguistically unique-i.e., only known to one language. Whereas most plant species associated with linguistically unique knowledge are not threatened, most languages that report linguistically unique knowledge are. Our finding of high uniqueness in indigenous knowledge and strong coupling with threatened languages suggests that language loss will be even more critical to the extinction of medicinal knowledge than biodiversity loss.