The joint influence of competition and mutualism on the biodiversity of mutualistic ecosystems

Coexistence mechanism of ecological specialists and generalists based on a network dimension reduction method

As an ecological strategy for species coexistence, some species adapt to a wide range of habitats, while others specialize in particular environments. Such 'generalists' and 'specialists' achieve normal ecological balance through a complex network of interactions between species. However, the role of these interactions in maintaining the coexistence of generalist and specialist species has not been elucidated within a general theoretical framework. Here, we analyze the ecological mechanism for the coexistence of specialist and generalist species in a class of mutualistic and competitive interaction ecosystems based on the network dimension reduction method. We find that ecological specialists and generalists can be identified based on the number of their respective interactions. We also find, using real-world empirical network simulations, that the removal of ecological generalists can lead to the collapse of local ecosystems, which is rarely observed with the loss of ecological specialists.

Non-random interactions within and across guilds shape the potential to coexist in multi-trophic ecological communities

Theory posits that the persistence of species in ecological communities is shaped by their interactions within and across trophic guilds. However, we lack empirical evaluations of how the structure, strength and sign of biotic interactions drive the potential to coexist in diverse multi-trophic communities. Here, we model community feasibility domains, a theoretically informed measure of multi-species coexistence probability, from grassland communities comprising more than 45 species on average from three trophic guilds (plants, pollinators and herbivores). Contrary to our hypothesis, increasing community complexity, measured either as the number of guilds or community richness, did not decrease community feasibility. Rather, we observed that high degrees of species self-regulation and niche partitioning allow for maintaining larger levels of community feasibility and higher species persistence in more diverse communities. Our results show that biotic interactions within and across guilds are not random in nature and both structures significantly contribute to maintaining multi-trophic diversity.

Niche differentiation and symbiotic association among ammonia/nitrite oxidizers in a full-scale rotating biological contactor

Although the distribution of ammonia/nitrite oxidizers had been profiled in different habitats, current understanding is still limited regarding their niche differentiation in the integrated biofilm reactors, the symbiotic associations of ammonia/nitrite oxidizers, as well as the parasitic interaction between viruses and those functional organisms involved in the nitrogen cycle. Here, the integrated metagenomics and metatranscriptomics are applied to profile the ammonia/nitrite oxidizers communities and transcriptional activities changes along the flowpath of a concatenated full-scale rotating biological contactor (RBC) (frontend Stage-A and backend Stage-B). 19 metagenome-assembled genomes (MAGs) of ammonia/nitrite oxidizers were recovered by using a hybrid assembly approach, including four ammonia-oxidizing bacteria (AOB), two ammonia-oxidizing archaea (AOA), two complete ammonia oxidation bacteria (comammox), eight nitrite-oxidizing bacteria (NOB), and three anaerobic ammonium oxidation bacteria (anammox). Diverse AOB and anammox dominated Stage-A and collectively contributed to nitrogen conversion. With the decline of ammonia concentration along the flowpath, comammox and AOA appeared and increased in relative abundance in Stage-B, accounting for 8.8% of the entire community at the end of this reactor, and their dominating role in nitrogen turnover was indicated by the high transcription activity of their corresponding function genes. Moreover, the variation in the abundance of viruses infecting ammonia and nitrite oxidizers suggests that viruses likely act as a biotic factor mediating ammonia/nitrite oxidizer populations. This study demonstrates that complex factors shaped niche differentiation and symbiotic associations of ammonia/nitrite oxidizers in the RBC and highlights the importance of RBCs as model systems for the investigation of biotic and abiotic factors affecting the composition of microbiomes.

Stability and selective extinction in complex mutualistic networks

We study species abundance in the empirical plant-pollinator mutualistic networks exhibiting broad degree distributions, with uniform intragroup competition assumed, by the Lotka-Volterra equation. The stability of a fixed point is found to be identified by the signs of its nonzero components and those of its neighboring fixed points. Taking the annealed approximation, we derive the nonzero components to be formulated in terms of degrees and the rescaled interaction strengths, which lead us to find different stable fixed points depending on parameters, and we obtain the phase diagram. The selective extinction phase finds small-degree species extinct and effective interaction reduced, maintaining stability and hindering the onset of instability. The nonzero minimum species abundances from different empirical networks show data collapse when rescaled as predicted theoretically.

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.

A review of sourdough starters: ecology, practices, and sensory quality with applications for baking and recommendations for future research

The practice of sourdough bread-making is an ancient science that involves the development, maintenance, and use of a diverse and complex starter culture. The sourdough starter culture comes in many different forms and is used in bread-making at both artisanal and commercial scales, in countries all over the world. While there is ample scientific research related to sourdough, there is no standardized approach to using sourdough starters in science or the bread industry; and there are few recommendations on future directions for sourdough research. Our review highlights what is currently known about the microbial ecosystem of sourdough (including microbial succession within the starter culture), methods of maintaining sourdough (analogous to land management) on the path to bread production, and factors that influence the sensory qualities of the final baked product. We present new hypotheses for the successful management of sourdough starters and propose future directions for sourdough research and application to better support and engage the sourdough baking community.

Explicit and implicit network connectivity: Analytical formulation and application to transport processes

Connectivity is a fundamental structural feature of a network that determines the outcome of any dynamics that happens on top of it. However, an analytical approach to obtain connection probabilities between nodes associated with to paths of different lengths is still missing. Here, we derive exact expressions for random-walk connectivity probabilities across any range of numbers of steps in a generic temporal, directed, and weighted network. This allows characterizing explicit connectivity realized by causal paths as well as implicit connectivity related to motifs of three nodes and two links called here pitchforks. We directly link such probabilities to the processes of tagging and sampling any quantity exchanged across the network, hence providing a natural framework to assess transport dynamics. Finally, we apply our theoretical framework to study ocean transport features in the Mediterranean Sea. We find that relevant transport structures, such as fluid barriers and corridors, can generate contrasting and counterintuitive connectivity patterns bringing novel insights into how ocean currents drive seascape connectivity.

The ambiguity of nestedness under soft and hard constraints

Many real networks feature the property of nestedness, i.e. the neighbours of nodes with a few connections are hierarchically nested within the neighbours of nodes with more connections. Despite the abstract simplicity of this notion, various mathematical definitions of nestedness have been proposed, sometimes giving contrasting results. Moreover, there is an ongoing debate on the statistical significance of nestedness, since random networks where the number of connections (degree) of each node is fixed to its empirical value are typically as nested as real ones. By using only ergodic and unbiased null models, we propose a clarification that exploits the recent finding that random networks where the degrees are enforced as hard constraints (microcanonical ensembles) are thermodynamically different from random networks where the degrees are enforced as soft constraints (canonical ensembles). Indeed, alternative definitions of nestedness can be negatively correlated in the microcanonical one, while being positively correlated in the canonical one. This result disentangles distinct notions of nestedness captured by different metrics and highlights the importance of making a principled choice between hard and soft constraints in null models of ecological networks.

Measuring nestedness: A comparative study of the performance of different metrics

Nestedness is a property of interaction networks widely observed in natural mutualistic communities, among other systems. A perfectly nested network is characterized by the peculiarity that the interactions of any node form a subset of the interactions of all nodes with higher degree. Despite a widespread interest on this pattern, no general consensus exists on how to measure it. Instead, several nestedness metrics, based on different but not necessarily independent properties of the networks, coexist in the literature, blurring the comparison between ecosystems. In this work, we present a detailed critical study of the behavior of six nestedness metrics and the variants of two of them. In order to evaluate their performance, we compare the obtained values of the nestedness of a large set of real networks among them and against a maximum-entropy and maximum-likelihood null model. We also analyze the dependencies of each metrics on different network parameters, as size, fill, and eccentricity. Our results point out, first, that the metrics do not rank networks universally in terms of their degree of nestedness. Furthermore, several metrics show significant dependencies on the network properties considered. The study of these dependencies allows us to understand some of the observed systematic shifts against the null model. Altogether, this paper intends to provide readers with a critical guide on how to measure nestedness patterns, by explaining the functioning of several metrics and disclosing their qualities and flaws. Besides, we also aim to extend the application of null models based on maximum entropy to the scarcely explored area of ecological networks. Finally, we provide a fully documented repository that allows constructing the null model and calculating the studied nestedness indexes. In addition, it provides the probability matrices to build the null model for a large dataset of more than 200 bipartite networks.

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.

Robustness to extinction and plasticity derived from mutualistic bipartite ecological networks

Understanding the response of ecological networks to perturbations and disruptive events is needed to anticipate the biodiversity loss and extinction cascades. Here, we study how network plasticity reshapes the topology of mutualistic networks in response to species loss. We analyze more than one hundred empirical mutualistic networks and considered random and targeted removal as mechanisms of species extinction. Network plasticity is modeled as either random rewiring, as the most parsimonious approach, or resource affinity-driven rewiring, as a proxy for encoding the phylogenetic similarity and functional redundancy among species. This redundancy should be positively correlated with the robustness of an ecosystem, as functions can be taken by other species once one of them is extinct. We show that effective modularity, i.e. the ability of an ecosystem to adapt or restructure, increases with increasing numbers of extinctions, and with decreasing the replacement probability. Importantly, modularity is mostly affected by the extinction rather than by rewiring mechanisms. These changes in community structure are reflected in the robustness and stability due to their positive correlation with modularity. Resource affinity-driven rewiring offers an increase of modularity, robustness, and stability which could be an evolutionary favored mechanism to prevent a cascade of co-extinctions.

Beyond Pairwise Interactions: Multispecies Character Displacement in Mexican Freshwater Fish Communities

Competition has long been recognized as a central force in shaping evolution, particularly through character displacement. Yet research on character displacement is biased, as it has focused almost exclusively on pairs of interacting species while ignoring multispecies interactions. Communities are seldom so simple that only pairs of species interact, and it is not clear whether inferences from pairwise interactions are sufficient to explain patterns of phenotypes in nature. Here, we test for character displacement in a natural system of freshwater fishes in western Mexico that contains up to four congeneric species of the genus Poeciliopsis. We analyzed body shape differences between populations with different numbers of competitors while accounting for confounding environmental variables. Surprisingly, we found evidence for convergent character displacement in populations of P. prolifica, P. viriosa, and P. latidens. We also found that the convergence in body shape was not consistently in the same direction, meaning that when three or more competitors co-occurred, we did not find more extreme body shapes compared with when there were only two competitors. Instead, when three or more competitors co-occurred, body shape was intermediate between the shape found with a pair of species and the shape found with no competitor present. This intermediate shape suggests that evolution in multispecies communities likely occurs in response to several competitors rather than to simple pairwise interactions. Overall, our results suggest that competition among multiple species is more complex than simple pairwise competitive interactions.

A Critical Mutualism - Competition Interplay Underlies the Loss of Microbial Diversity in Sedentary Lifestyle

Physical exercise improves the overall health status by preventing the development of several diseases. In recent years, it has been observed that physical exercise impacts gut microbiota by increasing the presence of beneficial bacteria and microbial diversity. In contrast, a sedentary lifestyle increases the incidence of chronic diseases that often have an associated loss of microbial diversity. The gut microbiota is a vast ecosystem in which microorganisms interact with each other in different ways; however, microbial ecosystem interactions are scarcely studied. The goal of this study was to determine whether individuals with a sedentary lifestyle have lower diversity in their gut microbiota and how microbial diversity is associated with changes in bacterial network interactions. For that purpose, diet, body composition, physical activity, and sedentarism behavior were characterized for individuals who did or did not comply with the World Health Organization recommendations for physical activity. The composition of the gut microbiome was determined by 16S rRNA gene sequencing. Reorganization of microbial structure with lifestyle was approached from network analysis, where network complexity and the topology of positive and negative interdependences between bacteria were compared and correlated with microbial diversity. Sedentary lifestyle was significantly associated with a diet low in fiber and rich in sugars and processed meat, as well as with high visceral and total corporal fat composition. The diversity (phylogenic diversity, Chao, observed species, and Shannon’s index) and network complexity of the gut microbiota were significantly lower in sedentary compared to active individuals. Whereas mutualism or co-occurrence interactions were similar between groups, competitiveness was significantly higher in the active lifestyle group. The mutualism-competition ratio was moderate and positively associated with diversity in sedentary individuals, but not in active individuals. This finding indicates that there is a critical point in this ratio beyond which the stability of the microbial community is lost, inducing a loss of diversity.

A Drive to Driven Model of Mapping Intraspecific Interaction Networks

Community ecology theory suggests that an individual's phenotype is determined by the phenotypes of its coexisting members to the extent at which this process can shape community evolution. Here, we develop a mapping theory to identify interaction quantitative trait loci (QTL) governing inter-individual dependence. We mathematically formulate the decision-making strategy of interacting individuals. We integrate these mathematical descriptors into a statistical procedure, enabling the joint characterization of how QTL drive the strengths of ecological interactions and how the genetic architecture of QTL is driven by ecological networks. In three fish full-sib mapping experiments, we identify a set of genome-wide QTL that control a range of societal behaviors, including mutualism, altruism, aggression, and antagonism, and find that these intraspecific interactions increase the genetic variation of body mass by about 50%. We showcase how the interaction QTL can be used as editors to reconstruct and engineer new social networks for ecological communities.

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We develop a new theory for complex-trait mapping by integrating behavioral ecology

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This theory can characterize how QTL drive cooperation or competition in populations

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It can also illustrate how the activation of QTL is driven by ecological interactions

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The new theory leverages interdisciplinary studies of genetics, ecology, and evolution