The effect of multiple biotic interaction types on species persistence

Plant interaction networks reveal the limits of our understanding of diversity maintenance

Species interactions are key drivers of biodiversity and ecosystem stability. Current theoretical frameworks for understanding the role of interactions make many assumptions which unfortunately, do not always hold in natural, diverse communities. This mismatch extends to annual plants, a common model system for studying coexistence, where interactions are typically averaged across environmental conditions and transitive competitive hierarchies are assumed to dominate. We quantify interaction networks for a community of annual wildflowers in Western Australia across a natural shade gradient at local scales. Whilst competition dominated, intraspecific and interspecific facilitation were widespread in all shade categories. Interaction strengths and directions varied substantially despite close spatial proximity and similar levels of local species richness, with most species interacting in different ways under different environmental conditions. Contrary to expectations, all networks were predominantly intransitive. These findings encourage us to rethink how we conceive of and categorize the mechanisms driving biodiversity in plant systems.

Adaptive rewiring shapes structure and stability in a three-guild herbivore-plant-pollinator network

Animal species, encompassing both pollinators and herbivores, exhibit a preference for plants based on optimal foraging theory. Understanding the intricacies of these adaptive plant-animal interactions in the context of community assembly poses a main challenge in ecology. This study delves into the impact of adaptive interaction rewiring between species belonging to different guilds on the structure and stability of a 3-guild ecological network, incorporating both mutualistic and antagonistic interactions. Our findings reveal that adaptive rewiring results in sub-networks becoming more nested and compartmentalized. Furthermore, the rewiring of interactions uncovers a positive correlation between a plant's generalism concerning both pollinators and herbivores. Additionally, there is a positive correlation between a plant's degree centrality and its energy budget. Although network stability does not exhibit a clear relationship with non-random structures, it is primarily influenced by the balance of multiple interaction strengths. In summary, our results underscore the significance of adaptive interaction rewiring in shaping the structure of 3-guild networks. They emphasize the importance of considering the balance of multiple interactions for the stability of adaptive networks, providing valuable insights into the complex dynamics of ecological communities.

Quorum sensing-mediated microbial interactions: Mechanisms, applications, challenges and perspectives

Microbial community in natural or artificial environments playes critical roles in substance cycles, products synthesis and species evolution. Although microbial community structures have been revealed via culture-dependent and culture-independent approaches, the hidden forces driving the microbial community are rarely systematically discussed. As a mode of cell-to-cell communication that modifies microbial interactions, quorum sensing can regulate biofilm formation, public goods secretion, and antimicrobial substances synthesis, directly or indirectly influencing microbial community to adapt to the changing environment. Therefore, the current review focuses on microbial community in the different habitats from the quorum sensing perspective. Firstly, the definition and classification of quorum sensing were simply introduced. Subsequently, the relationships between quorum sensing and microbial interactions were deeply explored. The latest progressives regarding the applications of quorum sensing in wastewater treatment, human health, food fermentation, and synthetic biology were summarized in detail. Finally, the bottlenecks and outlooks of quorum sensing driving microbial community were adequately discussed. To our knowledge, this current review is the first to reveal the driving force of microbial community from the quorum sensing perspective. Hopefully, this review provides a theoretical basis for developing effective and convenient approaches to control the microbial community with quorum sensing approaches.

Whole-of-community invertebrate rewilding: Leaf litter transplants rapidly increase beetle diversity during restoration

Restoration of degraded areas is now a central tool in humanity's response to continued species-loss. However, restoration projects often report exceedingly slow or failed recolonization of fauna, especially dispersal-constrained groups such as invertebrates. Active interventions via reintroducing or "rewilding" invertebrates may assist recolonization and speed up restoration of communities toward a desired target. However, invertebrate rewilding is rarely implemented during ecological restoration. Here, we studied the efficacy of invertebrate rewilding as a means of reintroducing dispersal-constrained species and improving diversity and compositional similarities to remnant communities during restoration. Rewilding was conducted by transplanting leaf litter and soil, including associated communities of invertebrates from species rich remnant sites into species poor, and geographically isolated, revegetated farmland sites. We sampled pre- and post-rewilding invertebrate communities in remnant, rewilded revegetation, and control revegetation sites. We analyzed morphospecies richness, abundance, community composition, and modeled morphospecies traits (dispersal method/trophic guild) using a Hierarchical Modelling of Species Communities approach to determine which biological properties facilitated establishment. Beetle (Coleoptera) morphospecies richness increased rapidly in rewilded sites and was indistinguishable from remnant communities as early as 7 months post-rewilding. Beetle community similarity in the rewilding sites significantly deviated from the control sites 27 months post-rewilding, however remnant communities remained distinct over the study timeframe. Establishment success varied as other taxa did not respond as consistently as beetles within the study timeframe. Furthermore, there were no discernible shifts in dispersal traits in rewilded sites. However, predatory morphospecies were more likely to establish post-rewilding than other trophic groups. Our results demonstrate that the relatively simple act of transplanting leaf litter can result in comparatively large increases in morphospecies richness during restoration in a short timeframe. We advocate methodologies such as ours should be adopted more frequently to address failed community restoration as they are cost-effective and can be easily applied by practitioners in various restoration settings. However, further efficacy tests (e.g., varying the number of rewilding events) and longer study timeframes are needed to ensure effectiveness for a broader range of invertebrate taxa and ecosystems.

Pathways to global-change effects on biodiversity: new opportunities for dynamically forecasting demography and species interactions

In structured populations, persistence under environmental change may be particularly threatened when abiotic factors simultaneously negatively affect survival and reproduction of several life cycle stages, as opposed to a single stage. Such effects can then be exacerbated when species interactions generate reciprocal feedbacks between the demographic rates of the different species. Despite the importance of such demographic feedbacks, forecasts that account for them are limited as individual-based data on interacting species are perceived to be essential for such mechanistic forecasting-but are rarely available. Here, we first review the current shortcomings in assessing demographic feedbacks in population and community dynamics. We then present an overview of advances in statistical tools that provide an opportunity to leverage population-level data on abundances of multiple species to infer stage-specific demography. Lastly, we showcase a state-of-the-art Bayesian method to infer and project stage-specific survival and reproduction for several interacting species in a Mediterranean shrub community. This case study shows that climate change threatens populations most strongly by changing the interaction effects of conspecific and heterospecific neighbours on both juvenile and adult survival. Thus, the repurposing of multi-species abundance data for mechanistic forecasting can substantially improve our understanding of emerging threats on biodiversity.

How Multiple Interaction Types Affect Disease Spread and Dilution in Ecological Networks

Ecological communities are composed of different functional guilds that are engaging in multiple types of biotic interactions. We explore how ecological networks fare when confronting infectious diseases according to density-dependent (DD) and frequency-dependent (FD) transmission modes. Our model shows that network compositions can dictate both disease spreading and the relationship between disease and community diversity (including species richness and Shannon’s diversity) as depicted in the dilution effect. The disease becomes more prevalent within communities harboring more mutualistic interactions, generating a positive relationship between disease prevalence and community diversity (i.e., an amplification effect). By contrast, in communities with a fixed proportion of mutualistic interactions, higher diversity from the balance of competition and predation can impede disease prevalence (i.e., the dilution effect). Within-species disease prevalence increases linearly with a species’ degree centrality. These patterns of disease transmission and the diversity-disease relationship hold for both transmission modes. Our analyses highlight the complex effects of interaction compositions in ecological networks on infectious disease dynamics and further advance the debate on the dilution effect of host diversity on disease prevalence.

Dynamical robustness of complex networks subject to long-range connectivity

In spite of a few attempts in understanding the dynamical robustness of complex networks, this extremely important subject of research is still in its dawn as compared to the other dynamical processes on networks. We hereby consider the concept of long-range interactions among the dynamical units of complex networks and demonstrate for the first time that such a characteristic can have noteworthy impacts on the dynamical robustness of networked systems, regardless of the underlying network topology. We present a comprehensive analysis of this phenomenon on top of diverse network architectures. Such dynamical damages being able to substantially affect the network performance, determining mechanisms that boost the robustness of networks becomes a fundamental question. In this work, we put forward a prescription based upon self-feedback that can efficiently resurrect global rhythmicity of complex networks composed of active and inactive dynamical units, and thus can enhance the network robustness. We have been able to delineate the whole proposition analytically while dealing with all d -path adjacency matrices, having an excellent agreement with the numerical results. For the numerical computations, we examine scale-free networks, Watts–Strogatz small-world model and also Erdös–Rényi random network, along with Landau–Stuart oscillators for casting the local dynamics.

Fine scale prediction of ecological community composition using a two-step sequential Machine Learning ensemble

Prediction is one of the last frontiers in ecology. Indeed, predicting fine-scale species composition in natural systems is a complex challenge as multiple abiotic and biotic processes operate simultaneously to determine local species abundances. On the one hand, species intrinsic performance and their tolerance limits to different abiotic pressures modulate species abundances. On the other hand, there is growing recognition that species interactions play an equally important role in limiting or promoting such abundances within ecological communities. Here, we present a joint effort between ecologists and data scientists to use data-driven models to predict species abundances using reasonably easy to obtain data. We propose a sequential data-driven modeling approach that in a first step predicts the potential species abundances based on abiotic variables, and in a second step uses these predictions to model the realized abundances once accounting for species competition. Using a curated data set over five years we predict fine-scale species abundances in a highly diverse annual plant community. Our models show a remarkable spatial predictive accuracy using only easy-to-measure variables in the field, yet such predictive power is lost when temporal dynamics are taken into account. This result suggests that predicting future abundances requires longer time series analysis to capture enough variability. In addition, we show that these data-driven models can also suggest how to improve mechanistic models by adding missing variables that affect species performance such as particular soil conditions (e.g. carbonate availability in our case). Robust models for predicting fine-scale species composition informed by the mechanistic understanding of the underlying abiotic and biotic processes can be a pivotal tool for conservation, especially given the human-induced rapid environmental changes we are experiencing. This objective can be achieved by promoting the knowledge gained with classic modelling approaches in ecology and recently developed data-driven models.

Multilayer network structure enhances the coexistence of competitive species

The concept of a multiplex network can be used to characterize the dispersal paths and states of different species in a patch habitat system. The multiplex network is one of three types of multilayer networks. In this study, the effect of a multiplex network on the long-term stable coexistence of species is investigated using the concept of metapopulation. Based on the mean field approximation, the stability analysis of a two-species system shows that, compared to the single layer network, the multiplex network is more conducive to the stable coexistence of species when one species has a stronger colonization ability. That is, in such a patch habitat system, if the dispersal paths of the stronger species are different than those of the weaker species, then the larger the heterogeneity of the dispersal network of the stronger species is, the more likely the long-term stable coexistence of species. This result provides a different perspective for understanding the biodiversity in heterogeneous habitats.

Geographical variation of multiplex ecological networks in marine intertidal communities

Understanding the drivers of geographical variation in species distributions, and the resulting community structure, constitutes one of the grandest challenges in ecology. Geographical patterns of species richness and composition have been relatively well studied. Less is known about how the entire set of trophic and non-trophic ecological interactions, and the complex networks that they create by gluing species together in complex communities, change across geographical extents. Here, we compiled data of species composition and three types of ecological interactions occurring between species in rocky intertidal communities across a large spatial extent (~970 km of shoreline) of central Chile, and analyzed the geographical variability in these multiplex networks (i.e., comprising several interaction types) of ecological interactions. We calculated nine network summary statistics common across interaction types, and additional network attributes specific to each of the different types of interactions. We then investigated potential environmental drivers of this multivariate network organization. These included variation in sea surface temperature and coastal upwelling, the main drivers of productivity in nearshore waters. Our results suggest that structural properties of multiplex ecological networks are affected by local species richness and modulated by factors influencing productivity and environmental predictability. Our results show that non-trophic negative interactions are more sensitive to spatially structured temporal environmental variation than feeding relationships, with non-trophic positive interactions being the least labile to it. We also show that environmental effects are partly mediated through changes in species richness and partly through direct influences on species interactions, probably associated to changes in environmental predictability and to bottom-up nutrient availability. Our findings highlight the need for a comprehensive picture of ecological interactions and their geographical variability if we are to predict potential effects of environmental changes on ecological communities.

Mutualism increases diversity, stability, and function of multiplex networks that integrate pollinators into food webs

Ecosystems are composed of complex networks of many species interacting in different ways. While ecologists have long studied food webs of feeding interactions, recent studies increasingly focus on mutualistic networks including plants that exchange food for reproductive services provided by animals such as pollinators. Here, we synthesize both types of consumer-resource interactions to better understand the controversial effects of mutualism on ecosystems at the species, guild, and whole-community levels. We find that consumer-resource mechanisms underlying plant-pollinator mutualisms can increase persistence, productivity, abundance, and temporal stability of both mutualists and non-mutualists in food webs. These effects strongly increase with floral reward productivity and are qualitatively robust to variation in the prevalence of mutualism and pollinators feeding upon resources in addition to rewards. This work advances the ability of mechanistic network theory to synthesize different types of interactions and illustrates how mutualism can enhance the diversity, stability, and function of complex ecosystems.

Non-trophic interactions strengthen the diversity-functioning relationship in an ecological bioenergetic network model

Ecological communities are undeniably diverse, both in terms of the species that compose them as well as the type of interactions that link species to each other. Despite this long recognition of the coexistence of multiple interaction types in nature, little is known about the consequences of this diversity for community functioning. In the ongoing context of global change and increasing species extinction rates, it seems crucial to improve our understanding of the drivers of the relationship between species diversity and ecosystem functioning. Here, using a multispecies dynamical model of ecological communities including various interaction types (e.g. competition for space, predator interference, recruitment facilitation in addition to feeding), we studied the role of the presence and the intensity of these interactions for species diversity, community functioning (biomass and production) and the relationship between diversity and functioning.Taken jointly, the diverse interactions have significant effects on species diversity, whose amplitude and sign depend on the type of interactions involved and their relative abundance. They however consistently increase the slope of the relationship between diversity and functioning, suggesting that species losses might have stronger effects on community functioning than expected when ignoring the diversity of interaction types and focusing on feeding interactions only.

The question of how species diversity contributes to the functioning of ecological communities has intrigued ecologists for decades, and is especially relevant in the current context of species extinctions. Ecological communities are not only diverse in terms of the species that compose them but also in terms of the way they interact with each other: for example, species compete for space and for food, eat and facilitate each other. The diversity of ways species interact has rarely been taken into account in the study of ecological communities, although widely acknowledged. Here we show that the diversity of interaction types matters: it affects species diversity, community functioning and the relationship between them by strengthening this relationship. This means that when the diversity of interaction types is taken into account, species losses have stronger impacts on the functioning of ecological communities. Our results therefore suggest that species loss may have more important consequences than expected based on classical models that do not take the diversity of interaction types into account.