Experimental evidence rejects pairwise modelling approach to coexistence in plant communities

Fast-slow traits predict competition network structure and its response to resources and enemies

Plants interact in complex networks but how network structure depends on resources, natural enemies and species resource-use strategy remains poorly understood. Here, we quantified competition networks among 18 plants varying in fast-slow strategy, by testing how increased nutrient availability and reduced foliar pathogens affected intra- and inter-specific interactions. Our results show that nitrogen and pathogens altered several aspects of network structure, often in unexpected ways due to fast and slow growing species responding differently. Nitrogen addition increased competition asymmetry in slow growing networks, as expected, but decreased it in fast growing networks. Pathogen reduction made networks more even and less skewed because pathogens targeted weaker competitors. Surprisingly, pathogens and nitrogen dampened each other's effect. Our results show that plant growth strategy is key to understand how competition respond to resources and enemies, a prediction from classic theories which has rarely been tested by linking functional traits to competition networks.

Network structure of resource use and niche overlap within the endophytic microbiome

Endophytes often have dramatic effects on their host plants. Characterizing the relationships among members of these communities has focused on identifying the effects of single microbes on their host, but has generally overlooked interactions among the myriad microbes in natural communities as well as potential higher-order interactions. Network analyses offer a powerful means for characterizing patterns of interaction among microbial members of the phytobiome that may be crucial to mediating its assembly and function. We sampled twelve endophytic communities, comparing patterns of niche overlap between coexisting bacteria and fungi to evaluate the effect of nutrient supplementation on local and global competitive network structure. We found that, despite differences in the degree distribution, there were few significant differences in the global network structure of niche-overlap networks following persistent nutrient amendment. Likewise, we found idiosyncratic and weak evidence for higher-order interactions regardless of nutrient treatment. This work provides a first-time characterization of niche-overlap network structure in endophytic communities and serves as a framework for higher-resolution analyses of microbial interaction networks as a consequence and a cause of ecological variation in microbiome function.

The Open Challenge of in vitro Modeling Complex and Multi-Microbial Communities in Three-Dimensional Niches

The comprehension of the underlying mechanisms of the interactions within microbial communities represents a major challenge to be faced to control their outcome. Joint efforts of in vitro, in vivo and ecological models are crucial to controlling human health, including chronic infections. In a broader perspective, considering that polymicrobial communities are ubiquitous in nature, the understanding of these mechanisms is the groundwork to control and modulate bacterial response to any environmental condition. The reduction of the complex nature of communities of microorganisms to a single bacterial strain could not suffice to recapitulate the in vivo situation observed in mammals. Furthermore, some bacteria can adapt to various physiological or arduous environments embedding themselves in three-dimensional matrices, secluding from the external environment. Considering the increasing awareness that dynamic complex and dynamic population of microorganisms (microbiota), inhabiting different apparatuses, regulate different health states and protect against pathogen infections in a fragile and dynamic equilibrium, we underline the need to produce models to mimic the three-dimensional niches in which bacteria, and microorganisms in general, self-organize within a microbial consortium, strive and compete. This review mainly focuses, as a case study, to lung pathology-related dysbiosis and life-threatening diseases such as cystic fibrosis and bronchiectasis, where the co-presence of different bacteria and the altered 3D-environment, can be considered as worst-cases for chronic polymicrobial infections. We illustrate the state-of-art strategies used to study biofilms and bacterial niches in chronic infections, and multispecies ecological competition. Although far from the rendering of the 3D-environments and the polymicrobial nature of the infections, they represent the starting point to face their complexity. The increase of knowledge respect to the above aspects could positively affect the actual healthcare scenario. Indeed, infections are becoming a serious threat, due to the increasing bacterial resistance and the slow release of novel antibiotics on the market.

Microbial coexistence through chemical-mediated interactions

Many microbial functions happen within communities of interacting species. Explaining how species with disparate growth rates can coexist is important for applications such as manipulating host-associated microbiota or engineering industrial communities. Here, we ask how microbes interacting through their chemical environment can achieve coexistence in a continuous growth setup (similar to an industrial bioreactor or gut microbiota) where external resources are being supplied. We formulate and experimentally constrain a model in which mediators of interactions (e.g. metabolites or waste-products) are explicitly incorporated. Our model highlights facilitation and self-restraint as interactions that contribute to coexistence, consistent with our intuition. When interactions are strong, we observe that coexistence is determined primarily by the topology of facilitation and inhibition influences not their strengths. Importantly, we show that consumption or degradation of chemical mediators moderates interaction strengths and promotes coexistence. Our results offer insights into how to build or restructure microbial communities of interest.

Reconciling empirical interactions and species coexistence

Coexistence in ecological communities is governed largely by the nature and intensity of species interactions. Countless studies have proposed methods to infer these interactions from empirical data, yet models parameterised using such data often fail to recover observed coexistence patterns. Here, we propose a method to reconcile empirical parameterisations of community dynamics with species-abundance data, ensuring that the predicted equilibrium is consistent with the observed abundance distribution. To illustrate the approach, we explore two case studies: an experimental freshwater algal community and a long-term time series of displacement in an intertidal community. We demonstrate how our method helps recover observed coexistence patterns, capture the core dynamics of the system, and, in the latter case, predict the impacts of experimental extinctions. Collectively, these results demonstrate an intuitive approach for reconciling observed and empirical data, improving our ability to explore the links between species interactions and coexistence in natural systems.

Priority Effects and Nonhierarchical Competition Shape Species Composition in a Complex Grassland Community

Niche and fitness differences control the outcome of competition, but determining their relative importance in invaded communities—which may be far from equilibrium—remains a pressing concern. Moreover, it is unclear whether classic approaches for studying competition, which were developed predominantly for pairs of interacting species, will fully capture dynamics in complex species assemblages. We parameterized a population-dynamic model using competition experiments of two native and three exotic species from a grassland community. We found evidence for minimal fitness differences or niche differences between the native species, leading to slow replacement dynamics and priority effects, but large fitness advantages allowed exotics to unconditionally invade natives. Priority effects driven by strong interspecific competition between exotic species drove single-species dominance by one of two exotic species in 80% of model outcomes, while a complex mixture of nonhierarchical competition and coexistence between native and exotic species occurred in the remaining 20%. Fungal infection, a commonly hypothesized coexistence mechanism, had weak fitness effects and is unlikely to substantially affect coexistence. In contrast to previous work on pairwise outcomes in largely native-dominated communities, our work supports a role for nearly neutral dynamics and priority effects as drivers of species composition in invaded communities.

Bistability in a system of two species interacting through mutualism as well as competition: Chemostat vs. Lotka-Volterra equations

We theoretically study the dynamics of two interacting microbial species in the chemostat. These species are competitors for a common resource, as well as mutualists due to cross-feeding. In line with previous studies (Assaneo, et al., 2013; Holland, et al., 2010; Iwata, et al., 2011), we demonstrate that this system has a rich repertoire of dynamical behavior, including bistability. Standard Lotka-Volterra equations are not capable to describe this particular system, as these account for only one type of interaction (mutualistic or competitive). We show here that the different steady state solutions can be well captured by an extended Lotka-Volterra model, which better describe the density-dependent interaction (mutualism at low density and competition at high density). This two-variable model provides a more intuitive description of the dynamical behavior than the chemostat equations.

Harnessing uncertainty to approximate mechanistic models of interspecific interactions

Because the Lotka-Volterra competitive equations posit no specific competitive mechanisms, they are exceedingly general, and can theoretically approximate any underlying mechanism of competition near equilibrium. In practice, however, these models rarely generate accurate predictions in diverse communities. We propose that this difference between theory and practice may be caused by how uncertainty propagates through Lotka-Volterra systems. In approximating mechanistic relationships with Lotka-Volterra models, associations among parameters are lost, and small variation can correspond to large and unrealistic changes in predictions. We demonstrate that constraining Lotka-Volterra models using correlations among parameters expected from hypothesized underlying mechanisms can reintroduce some of the underlying structure imposed by those mechanisms, thereby improving model predictions by both reducing bias and increasing precision. Our results suggest that this hybrid approach may combine some of the generality of phenomenological models with the broader applicability and meaningful interpretability of mechanistic approaches. These methods could be useful in poorly understood systems for identifying important coexistence mechanisms, or for making more accurate predictions.

Native turncoats and indirect facilitation of species invasions

At local scales, native species can resist invasion by feeding on and competing with would-be invasive species. However, this relationship tends to break down or reverse at larger scales. Here, we consider the role of native species as indirect facilitators of invasion and their potential role in this diversity-driven 'invasion paradox'. We coin the term 'native turncoats' to describe native facilitators of non-native species and identify eight ways they may indirectly facilitate species invasion. Some are commonly documented, while others, such as indirect interactions within competitive communities, are largely undocumented in an invasion context. Therefore, we use models to evaluate the likelihood that these competitive interactions influence invasions. We find that native turncoat effects increase with the number of resources and native species. Furthermore, our findings suggest the existence, abundance and effectiveness of native turncoats in a community could greatly influence invasion success at large scales.

Beyond pairwise mechanisms of species coexistence in complex communities

The tremendous diversity of species in ecological communities has motivated a century of research into the mechanisms that maintain biodiversity. However, much of this work examines the coexistence of just pairs of competitors. This approach ignores those mechanisms of coexistence that emerge only in diverse competitive networks. Despite the potential for these mechanisms to create conditions under which the loss of one competitor triggers the loss of others, we lack the knowledge needed to judge their importance for coexistence in nature. Progress requires borrowing insight from the study of multitrophic interaction networks, and coupling empirical data to models of competition.

Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions

Pairwise models are commonly used to describe many-species communities. In these models, an individual receives additive fitness effects from pairwise interactions with each species in the community ('additivity assumption'). All pairwise interactions are typically represented by a single equation where parameters reflect signs and strengths of fitness effects ('universality assumption'). Here, we show that a single equation fails to qualitatively capture diverse pairwise microbial interactions. We build mechanistic reference models for two microbial species engaging in commonly-found chemical-mediated interactions, and attempt to derive pairwise models. Different equations are appropriate depending on whether a mediator is consumable or reusable, whether an interaction is mediated by one or more mediators, and sometimes even on quantitative details of the community (e.g. relative fitness of the two species, initial conditions). Our results, combined with potential violation of the additivity assumption in many-species communities, suggest that pairwise modeling will often fail to predict microbial dynamics.

Community structure follows simple assembly rules in microbial microcosms

Microorganisms typically form diverse communities of interacting species, whose activities have tremendous impact on the plants, animals and humans they associate with. The ability to predict the structure of these complex communities is crucial to understanding and managing them. Here, we propose a simple, qualitative assembly rule that predicts community structure from the outcomes of competitions between small sets of species, and experimentally assess its predictive power using synthetic microbial communities composed of up to eight soil bacterial species. Nearly all competitions resulted in a unique, stable community, whose composition was independent of the initial species fractions. Survival in three-species competitions was predicted by the pairwise outcomes with an accuracy of ~90%. Obtaining a similar level of accuracy in competitions between sets of seven or all eight species required incorporating additional information regarding the outcomes of the three-species competitions. Our results demonstrate experimentally the ability of a simple bottom-up approach to predict community structure. Such an approach is key for anticipating the response of communities to changing environments, designing interventions to steer existing communities to more desirable states and, ultimately, rationally designing communities de novo.

The Mechanisms and Consequences of Interspecific Competition Among Plants

During the past 100 years, studies spanning thousands of taxa across almost all biomes have demonstrated that competition has powerful negative effects on the performance of individuals and can affect the composition of plant communities, the evolution of traits, and the functioning of whole ecosystems. In this review, we highlight new and important developments that have the potential to greatly improve our understanding of how plants compete and the consequences of competition from individuals to communities in the following major areas of research: (a) mechanisms of competition, (b) competitive effect and response, (c) direct and indirect effects of competition, (d) population-level effects of competition, (e) biogeographical differences in competition, and (f) conditionality of competition. Ecologists have discovered much about competition, but the mechanisms of competition and how competition affects the organization of communities in nature still require both theoretical and empirical exploration.

Predictability of multispecies competitive interactions in three populations of Atlantic salmon Salmo salar

Juvenile Atlantic salmon Salmo salar from three allopatric populations (LaHave, Sebago and Saint-Jean) were placed into artificial streams with combinations of four non-native salmonids: brown trout Salmo trutta, rainbow trout Oncorhynchus mykiss, Chinook salmon Oncorhynchus tshawytscha and coho salmon Oncorhynchus kisutch. Non-additive effects, as evidenced by lower performance than predicted from weighted summed two-species competition trials, were detected for S. salar fork length (LF ) and mass, but not for survival, condition factor or riffle use. These data support emerging theory on niche overlap and species richness as factors that can lead to non-additive competition effects.

Contributions of temporal segregation, oviposition choice, and non-additive effects of competitors to invasion success of Aedes japonicus (Diptera: Culicidae) in North America

The mosquito Aedes japonicus (Diptera: Culicidae) has spread rapidly through North America since its introduction in the 1990s. The mechanisms underlying its establishment in container communities occupied by competitors Aedes triseriatus and Aedes albopictus are unclear. Possibilities include (A) temporal separation of A. japonicus from other Aedes, (B) oviposition avoidance by A. japonicus of sites containing heterospecific Aedes larvae, and (C) non-additive competitive effects in assemblages of multiple Aedes. Containers sampled throughout the summer in an oak-hickory forest near Eureka, MO showed peak abundance for A. japonicus occurring significantly earlier in the season than either of the other Aedes species. Despite this, A. japonicus co-occurred with one other Aedes species in 53 % of samples when present, and co-occurred with both other Aedes in 18 % of samples. In a field oviposition experiment, A. japonicus laid significantly more eggs in forest edge containers than in forest interior containers, but did not avoid containers with low or high densities of larvae of A. triseriatus, A. albopictus, or both, compared to containers without larvae. Interspecific competitive effects (measured as decrease in the index of performance, λ') of A. triseriatus or A. albopictus alone on A. japonicus larvae were not evident at the densities used, but the effect of both Aedes combined was significantly negative and super-additive of effects of individual interspecific competitors. Thus, neither oviposition avoidance of competitors nor non-additive competitive effects contribute to the invasion success of A. japonicus in North America. Distinct seasonal phenology may reduce competitive interactions with resident Aedes.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

Dynamic trajectories of growth and nitrogen capture by competing plants

Although dynamic, plant competition is usually estimated as biomass differences at a single, arbitrary time; resource capture is rarely measured. This restricted approach perpetuates uncertainty. To address this problem, we characterized the competitive dynamics of Dactylis glomerata and Plantago lanceolata as continuous trajectories of biomass production and nitrogen (N) capture. Plants were grown together or in isolation. Biomass and N content were measured at 17 harvests up to 76 d after sowing. Data were fitted to logistic models to derive instantaneous growth and N capture rates. Plantago lanceolata was initially more competitive in terms of cumulative growth and N capture, but D. glomerata was eventually superior. Neighbours reduced maximum biomass, but influenced both maximum N capture and its rate constant. Timings of maximal instantaneous growth and N capture rates were similar between species when they were isolated, but separated by 16 d when they were competing, corresponding to a temporal convergence in maximum growth and N capture rates in each species. Plants processed N and produced biomass differently when they competed. Biomass and N capture trajectories demonstrated that competitive outcomes depend crucially on when and how 'competition' is measured. This potentially compromises the interpretation of conventional competition experiments.

Plant competitive interactions and invasiveness: searching for the effects of phylogenetic relatedness and origin on competition intensity

The invasion success of introduced plants is frequently explained as a result of competitive interactions with native flora. Although previous theory and experiments have shown that plants are largely equivalent in their competitive effects on each other, competitive nonequivalence is hypothesized to occur in interactions between native and invasive species. Small overlap in resource use with unrelated native species, improved competitiveness, and production of novel allelochemicals are all believed to contribute to the invasiveness of introduced species. I tested all three assumptions in a common-garden experiment by examining the effect of plant origin and relatedness on competition intensity. Competitive interactions were explored within 12 triplets, each consisting of an invasive species, a native congeneric (or confamilial) species, and a native heterogeneric species that are likely to interact in the field. Plants were grown in pots alone or in pairs and in the absence or the presence of activated carbon to control for allelopathy. I found that competition intensity was not influenced by the relatedness or origin of competing neighbors. Although some exotic species may benefit from size advantages and species-specific effects in competitive interactions, none of the three mechanisms investigated is likely to be a principal driver of their invasiveness.