Plant-pollinator community network response to species invasion depends on both invader and community characteristics

Prescribed fire increases plant-pollinator network robustness to losses of rare native forbs

Restoration efforts often focus on changing the composition and structure of invaded plant communities, with two implicit assumptions: (1) functional interactions with species of other trophic levels, such as pollinators, will reassemble automatically when native plant diversity is restored and (2) restored communities will be more resilient to future stressors. However, the impact of restoration activities on pollinator richness, plant-pollinator interaction network structure, and network robustness is incompletely understood. Leveraging a restoration chronosequence in Pacific Northwest prairies, we examined the effects of restoration-focused prescribed fire and native forb replanting on floral resources, pollinator visitation, and plant-pollinator network structure. We then simulated the effects of plant species loss/removal scenarios on secondary extinction cascades in the networks. Specifically, we explored three management-relevant plant loss scenarios (removal of an abundant exotic forb, removal of an abundant forb designated a noxious weed, and loss of the rarest native forb) and compared them to control scenarios. Pyrodiversity and proportion of area recently burned increased the abundance and diversity of floral resources, with concomitant increases in pollinator visitation and diversity. Pyrodiversity also decreased network connectance and nestedness, increased modularity, and buffered networks against secondary extinction cascades. Rare forbs contributed disproportionately to network robustness in less restored prairies, while removal of typical "problem" plants like exotic and noxious species had relatively small impacts on network robustness, particularly in prairies with a long history of restoration activities. Restoration actions aimed mainly at improving the diversity and abundance of pollinator-provisioning plants may also produce plant-pollinator networks with increased resilience to plant species losses.

Economic costs of the invasive Yellow-legged hornet on honey bees

Biological invasions have ecological impacts worldwide with potential massive economic costs. Among other ecosystem services such as nitrogen cycle, carbon sequestration and primary production, invasive alien species are particularly known to impact pollination. By predating honey bees (Apis mellifera), the invasive Yellow-legged hornet (Vespa velutina nigrithorax) increases the mortality risk of European bee colonies; however, little is known about its economic costs. We developed an analytic process combining large-scale field data, niche modelling techniques and agent-based models to spatially assess the ecological and economic impacts of the Yellow-legged hornet on honey bees and beekeeping in France. In particular, we estimated (i) the hornet-related risk of bee colony mortality, (ii) the economic cost of colony loss for beekeepers and (iii) the economic impact of livestock replacement compared to honey revenues at regional and national scales. We estimated an overall density of 1.08 hornet nest/km2 in France, based on the field record of 1260 nests over a searched area of 28,348 km2. However, this predator density was heterogeneously spread out across the country as well as the distribution of managed honey bee colonies. Overall, this hornet-related risk of bee colony mortality could reach up to 29.2 % of the beekeepers' livestock at national scale each year in high predation scenario. This national cost could reach as much as € 30.8 million per year due to colony loss, which represents for beekeepers an economic impact of livestock replacement of 26.6 % of honey revenues. Our results suggest non-negligible ecological and economic impacts of the invasive Yellow-legged hornet on honey bees and beekeeping activities. Moreover, this study meets the urgent need for more numerous and accurate economic estimations, necessary to calculate the impact of biological invasions on biodiversity and human goods, with a view to enhance policies of biodiversity conservation.

Predicting cascading extinctions and efficient restoration strategies in plant-pollinator networks via generalized positive feedback loops

The extinction of a species in a plant-pollinator mutualistic community can cause cascading effects and lead to major biodiversity loss. The ecologically important task of predicting the severity of the cascading effects is made challenging by the complex network of interactions among the species. In this work, we analyze an ensemble of models of communities of plant and pollinator species. These models describe the mutualistic inter-species interactions by Boolean threshold functions. We show that identifying generalized positive feedback loops can help pinpoint the species whose extinction leads to catastrophic and substantial damage to the whole community. We compare these results with the damage percentage caused by the loss of species identified as important by previously studied structural measures and show that positive feedback loops and the information gained from them can identify certain crucial species that the other measures fail to find. We also suggest mitigation measures for two specific purposes: (1) prevent the damage to the community by protecting a subset of the species, and (2) restore the community after the damage by restoring a subset of species. Our analyses indicate that the generalized positive feedback loops predict the most efficient strategies to achieve these purposes. The correct identification of species in each category has important implications for conservation efforts and developing community management strategies.

Relationships among generalized positive feedback loops determine possible community outcomes in plant-pollinator interaction networks

Attractors in Boolean network models representing complex systems such as ecological communities correspond to long-term outcomes (e.g., stable communities) in such systems. As a result, identifying efficient methods to find and characterize these attractors allows for a better understanding of the diversity of possible outcomes. Here we analyze networks that model mutualistic communities of plant and pollinator species governed by Boolean threshold functions. We propose a novel attractor identification method based on generalized positive feedback loops and their functional relationships in such networks. We show that these relationships determine the mechanisms by which groups of stable positive feedback loops collectively trap the system in specific regions of the state space and lead to attractors. Put into the ecological context, we show how survival units-small groups of species in which species can maintain a specific survival state-and their relationships determine the final community outcomes in plant-pollinator networks. We find a remarkable diversity of community outcomes: up to an average of 43 attractors possible for networks with 100 species. This diversity is due to the multiplicity of survival units (up to 34) and stable subcommunities (up to 14). The timing of species influx or outflux does not affect the number of attractors, but it may influence their basins of attraction.

Mutualistic networks emerging from adaptive niche-based interactions

Mutualistic networks are vital ecological and social systems shaped by adaptation and evolution. They involve bipartite cooperation via the exchange of goods or services between actors of different types. Empirical observations of mutualistic networks across genres and geographic conditions reveal correlated nested and modular patterns. Yet, the underlying mechanism for the network assembly remains unclear. We propose a niche-based adaptive mechanism where both nestedness and modularity emerge simultaneously as complementary facets of an optimal niche structure. Key dynamical properties are revealed at different timescales. Foremost, mutualism can either enhance or reduce the network stability, depending on competition intensity. Moreover, structural adaptations are asymmetric, exhibiting strong hysteresis in response to environmental change. Finally, at the evolutionary timescale we show that the adaptive mechanism plays a crucial role in preserving the distinctive patterns of mutualism under species invasions and extinctions.

Nested and modular patterns are vastly observed in mutualistic networks across genres and geographic conditions. Here, the authors show a unified mechanism that underlies the assembly and evolution of such networks, based on adaptive niche interactions of the participants.

Science communication is needed to inform risk perception and action of stakeholders

Stakeholders are critical environmental managers in human-dominated landscapes. In some contexts, stakeholders can be forced to personally act following their own observations and risk perception instead of science recommendation. In particular, biological invasions need rapid control actions to reduce potential socio-ecological impacts, while science-based risk assessments are rather complex and time-delayed. Although they can lead to important detrimental effects on biodiversity, potential time-delayed disconnections between stakeholders' action and science recommendations are rarely studied. Using the case study of western European beekeepers controlling the invasive Asian hornet Vespa velutina nigrithorax for its suspected impact on honey bee colonies, we analysed mechanisms underlying personal actions of stakeholders and how they evolved in science disconnection. Personal actions of stakeholders were causal-effect linked with their risk observation but disconnected to time-delayed science predictions and recommendations. Unfortunately, these science-disconnected actions also led to dramatic impacts on numerous species of the local entomofauna. These results highlight the need to improve mutual risk communication between science and action in the early-stages of management plans to improve the sustainably of stakeholders' practices.

Consequences of Multispecies Introductions on Island Ecosystems

The rate of non-native species introductions continues to increase, with directionality from continents to islands. It is no longer single species but entire networks of coevolved and newly interacting continental species that are establishing on islands. The consequences of multispecies introductions on the population dynamics and interactions of native and introduced species will depend on the form of trophic limitation on island ecosystems. Freed from biotic constraints in their native range, species introduced to islands no longer experience top-down limitation, instead becoming limited by and disrupting bottom-up processes that dominate on resource-limited islands. This framing of the ecological and evolutionary relationships among introduced species with one another and their ecosystem has important consequences for conservation. Whereas on continents the focus of conservation is on restoring native apex species and top-down limitation, on islands the focus must instead be on removing introduced animal and plant species to restore bottom-up limitation.

Fractal features of soil particle size distributions and their potential as an indicator of Robinia pseudoacacia invasion1

To study the fractal dimensions of the soil particle size distributions (PSDs) within different plantations (of Pinus densiflora, Quercus acutissima, Robinia pseudoacacia, and Larix kaempferi) and evaluate PSDs as an indicator of the likelihood of Robinia pseudoacacia invasion, the soil porosity of 0–20 cm soil layers was measured at different plantations in the Yaoxiang Forest Farm, Shandong Province, China. The results showed that the fractal dimension (D_m) values varied from 2.59 to 2.70 among the different plantations and were significantly negatively correlated to sand content and positively correlated to silt content and clay content. Significant negative correlations were observed between D_m and both soil organic matter (SOM) (P < 0.05) and available phosphorus (P < 0.01). The multifractal entropy dimension (D₁) and entropy dimension/capacity dimension (D₁/D₀) parameters were not significantly correlated with SOM, although significant correlations were found between SOM and each of D₀, Δα, and Δf(α). Compared with the other plantations, the Robinia pseudoacacia plantation had higher nutrient contents, higher D₀ and D₁ values and lower D_m values. Based on principal component analysis (PCA) ordination, we concluded that Robinia pseudoacacia and Pinus densiflora shared a similar habitat and that Robinia pseudoacacia is more likely to invade Pinus densiflora plantations for soil.

Correlations in the degeneracy of structurally controllable topologies for networks

Many dynamic systems display complex emergent phenomena. By directly controlling a subset of system components (nodes) via external intervention it is possible to indirectly control every other component in the system. When the system is linear or can be approximated sufficiently well by a linear model, methods exist to identify the number and connectivity of a minimum set of external inputs (constituting a so-called minimal control topology, or MCT). In general, many MCTs exist for a given network; here we characterize a broad ensemble of empirical networks in terms of the fraction of nodes and edges that are always, sometimes, or never a part of an MCT. We study the relationships between the measures, and apply the methodology to the T-LGL leukemia signaling network as a case study. We show that the properties introduced in this report can be used to predict key components of biological networks, with potentially broad applications to network medicine.

Invading a mutualistic network: to be or not to be similar

Biological invasion remains a major threat to biodiversity in general and a disruptor to mutualistic interactions in particular. While a number of empirical studies have directly explored the role of invasion in mutualistic pollination networks, a clear picture is yet to emerge and a theoretical model for comprehension still lacking. Here, using an eco‐evolutionary model of bipartite mutualistic networks with trait‐mediated interactions, we explore invader trait, propagule pressure, and network features of recipient community that contribute importantly to the success and impact of an invasion. High level of invasiveness is observed when invader trait differs from those of the community average, and level of interaction generalization equals to that of the community average. Moreover, multiple introductions of invaders with declining propagules enhance invasiveness. Surprisingly, the most successful invader is not always the one having the biggest impact on the recipient community. The network structure of recipient community, such as nestedness and modularity, is not a primary indicator of its invasibility; rather, the invasibility is best correlated with measurements of network stability such as robustness, resilience, and disruptiveness (a measure of evolutionary instability). Our model encompasses more general scenarios than previously studied in predicting invasion success and impact in mutualistic networks, and our results highlight the need for coupling eco‐evolutionary processes to resolve the invasion dilemma.

Exotic Plant Infestation Is Associated with Decreased Modularity and Increased Numbers of Connectors in Mixed-Grass Prairie Pollination Networks

The majority of pollinating insects are generalists whose lifetimes overlap flowering periods of many potentially suitable plant species. Such generality is instrumental in allowing exotic plant species to invade pollination networks. The particulars of how existing networks change in response to an invasive plant over the course of its phenology are not well characterized, but may shed light on the probability of long-term effects on plant-pollinator interactions and the stability of network structure. Here we describe changes in network topology and modular structure of infested and non-infested networks during the flowering season of the generalist non-native flowering plant, Cirsium arvense in mixed-grass prairie at Badlands National Park, South Dakota, USA. Objectives were to compare network-level effects of infestation as they propagate over the season in infested and non-infested (with respect to C. arvense) networks. We characterized plant-pollinator networks on 5 non-infested and 7 infested 1-ha plots during 4 sample periods that collectively covered the length of C. arvense flowering period. Two other abundantly-flowering invasive plants were present during this time: Melilotus officinalis had highly variable floral abundance in both C. arvense-infested and non-infested plots and Convolvulus arvensis, which occurred almost exclusively in infested plots and peaked early in the season. Modularity, including roles of individual species, and network topology were assessed for each sample period as well as in pooled infested and non-infested networks. Differences in modularity and network metrics between infested and non-infested networks were limited to the third and fourth sample periods, during flower senescence of C. arvense and the other invasive species; generality of pollinators rose concurrently, suggesting rewiring of the network and a lag effect of earlier floral abundance. Modularity was lower and number of connectors higher in infested networks, whether they were assessed in individual sample periods or pooled into infested and non-infested networks over the entire blooming period of C. arvense. Connectors typically did not reside within the same modules as C. arvense, suggesting that effects of the other invasive plants may also influence the modularity results, and that effects of infestation extend to co-flowering native plants. We conclude that the presence of abundantly flowering invasive species is associated with greater network stability due to decreased modularity, but whether this is advantageous for the associated native plant-pollinator communities depends on the nature of perturbations they experience.