Predicting rates of interspecific interaction from phylogenetic trees

Phylogeny structures species' interactions in experimental ecological communities

Species' traits and interactions are products of evolutionary history. Despite the long-standing hypothesis that closely related species possess similar traits, and thus experience stronger competition, measuring the effect of evolutionary history on the ecology of natural communities remains challenging. We propose a novel framework to test whether phylogeny influences patterns of coexistence and abundance of species assemblages. In our approach, phylogenetic trees are used to parameterize species' interactions, which in turn determine the abundance of species in a given assemblage. We use likelihoods to score models parameterized with a given phylogeny, and contrast them with models built using random trees, allowing us to test whether phylogenetic information helps to predict species' abundances. Our statistical framework reveals that interactions are indeed structured by phylogeny in a large set of experimental plant communities. Our results confirm that evolutionary history can help predict, and potentially manage or conserve, the structure and function of complex ecological communities.

Ecological diversification preceded geographical expansion during the evolutionary radiation of Cataglyphis desert ants

Biological diversity often arises as organisms adapt to new ecological conditions (i.e., ecological opportunities) or colonize suitable areas (i.e., spatial opportunities). Cases of geographical expansion followed by local ecological divergence are well described; they result in clades comprising ecologically heterogeneous subclades. Here, we show that the desert ant genus Cataglyphis likely originated in open grassland habitats in the Middle East ∼18 million years ago and became a taxon of diverse species specializing in prey of different masses. The genus then colonized the Mediterranean Basin around 9 million years ago. The result was the rapid accumulation of species, and the appearance of local assemblages containing species from different lineages that still displayed ancestral foraging specialties. These findings highlight that, in Cataglyphis, ecological diversification preceded geographical expansion, resulting in a clade composed of ecologically homogeneous subclades.

Detecting the ecological footprint of selection

The structure of communities is influenced by many ecological and evolutionary processes, but the way these manifest in classic biodiversity patterns often remains unclear. Here we aim to distinguish the ecological footprint of selection-through competition or environmental filtering-from that of neutral processes that are invariant to species identity. We build on existing Massive Eco-evolutionary Synthesis Simulations (MESS), which uses information from three biodiversity axes-species abundances, genetic diversity, and trait variation-to distinguish between mechanistic processes. To correctly detect and characterise competition, we add a new and more realistic form of competition that explicitly compares the traits of each pair of individuals. Our results are qualitatively different to those of previous work in which competition is based on the distance of each individual's trait to the community mean. We find that our new form of competition is easier to identify in empirical data compared to the alternatives. This is especially true when trait data are available and used in the inference procedure. Our findings hint that signatures in empirical data previously attributed to neutrality may in fact be the result of pairwise-acting selective forces. We conclude that gathering more different types of data, together with more advanced mechanistic models and inference as done here, could be the key to unravelling the mechanisms of community assembly and question the relative roles of neutral and selective processes.

The ecological and evolutionary consequences of tropicalisation

Tropicalisation is a marine phenomenon arising from contemporary climate change, and is characterised by the range expansion of tropical/subtropical species and the retraction of temperate species. Tropicalisation occurs globally and can be detected in both tropical/temperate transition zones and temperate regions. The ecological consequences of tropicalisation range from single-species impacts (e.g., altered behaviour) to whole ecosystem changes (e.g., phase shifts in intertidal and subtidal habitats). Our understanding of the evolutionary consequences of tropicalisation is limited, but emerging evidence suggests that tropicalisation could induce phenotypic change as well as shifts in the genotypic composition of both expanding and retracting species. Given the rapid rate of contemporary climate change, research on tropicalisation focusing on shifts in ecosystem functioning, biodiversity change, and socioeconomic impacts is urgently needed.

Limited ecological opportunity influences the tempo of morphological evolution in birds

According to classic models of lineage diversification and adaptive radiation, phenotypic evolution should accelerate in the context of ecological opportunity and slow down when niches become saturated.1,2 However, only weak support for these ideas has been found in nature, perhaps because most analyses make the biologically unrealistic assumption that clade members contribute equally to reducing ecological opportunity, even when they occur in different continents or specialize on different habitats and diets. To view this problem through a different lens, we adapted a new phylogenetic modeling approach that accounts for the fact that competition for ecological opportunity only occurs between species that coexist and share similar habitats and diets. Applying this method to trait data for nearly all extant species of landbirds,3 we find a widespread signature of decelerating trait evolution in lineages adapted to similar habitats or diets. The strength of this pattern was consistent across latitudes when comparing tropical and temperate assemblages. Our results provide little support for the idea that increased diversity and tighter packing of niches accentuates evolutionary slowdowns in the tropics and instead suggest that limited ecological opportunity can be an important factor determining the rate of morphological diversification at a global scale.

How Important Is Budding Speciation for Comparative Studies?

The acknowledgment of evolutionary dependence among species has fundamentally changed how we ask biological questions. Phylogenetic models became the standard approach for studies with 3 or more lineages, in particular those using extant species. Most phylogenetic comparative methods (PCMs) translate relatedness into covariance, meaning that evolutionary changes before lineages split should be interpreted together whereas after the split lineages are expected to change independently. This clever realization has shaped decades of research. Here, we discuss one element of the comparative method often ignored or assumed as unimportant: if nodes of a phylogeny represent the dissolution of the ancestral lineage into two new ones or if the ancestral lineage can survive speciation events (i.e., budding). Budding speciation is often reported in paleontological studies, due to the nature of the evidence for budding in the fossil record, but it is surprisingly absent in comparative methods. Here, we show that many PCMs assume that divergence happens as a symmetric split, even if these methods do not explicitly mention this assumption. We discuss the properties of trait evolution models for continuous and discrete traits and their adequacy under a scenario of budding speciation. We discuss the effects of budding speciation under a series of plausible evolutionary scenarios and show when and how these can influence our estimates. We also propose that long-lived lineages that have survived through a series of budding speciation events and given birth to multiple new lineages can produce evolutionary patterns that challenge our intuition about the most parsimonious history of trait changes in a clade. We hope our discussion can help bridge comparative approaches in paleontology and neontology as well as foster awareness about the assumptions we make when we use phylogenetic trees.

Inferring the ecological and evolutionary determinants of community genetic diversity

Understanding the relative contributions of ecological and evolutionary processes to the structuring of ecological communities is needed to improve our ability to predict how communities may respond to future changes in an increasingly human-modified world. Metabarcoding methods make it possible to gather population genetic data for all species within a community, unlocking a new axis of data to potentially unveil the origins and maintenance of biodiversity at local scales. Here, we present a new eco-evolutionary simulation model for investigating community assembly dynamics using metabarcoding data. The model makes joint predictions of species abundance, genetic variation, trait distributions and phylogenetic relationships under a wide range of parameter settings (e.g. high speciation/low dispersal or vice versa) and across a range of community states, from pristine and unmodified to heavily disturbed. We first demonstrate that parameters governing metacommunity and local community processes leave detectable signatures in simulated biodiversity data axes. Next, using a simulation-based machine learning approach we show that neutral and non-neutral models are distinguishable and that reasonable estimates of several model parameters within the local community can be obtained using only community-scale genetic data, while phylogenetic information is required to estimate those describing metacommunity dynamics. Finally, we apply the model to soil microarthropod metabarcoding data from the Troodos mountains of Cyprus, where we find that communities in widespread forest habitats are structured by neutral processes, while high-elevation and isolated habitats act as an abiotic filter generating non-neutral community structure. We implement our model within the ibiogen R package, a package dedicated to the investigation of island, and more generally community-scale, biodiversity using community-scale genetic data.

Conceptual and empirical bridges between micro- and macroevolution

Explaining broad molecular, phenotypic and species biodiversity patterns necessitates a unifying framework spanning multiple evolutionary scales. Here we argue that although substantial effort has been made to reconcile microevolution and macroevolution, much work remains to identify the links between biological processes at play. We highlight four major questions of evolutionary biology whose solutions require conceptual bridges between micro and macroevolution. We review potential avenues for future research to establish how mechanisms at one scale (drift, mutation, migration, selection) translate to processes at the other scale (speciation, extinction, biogeographic dispersal) and vice versa. We propose ways in which current comparative methods to infer molecular evolution, phenotypic evolution and species diversification could be improved to specifically address these questions. We conclude that researchers are in a better position than ever before to build a synthesis to understand how microevolutionary dynamics unfold over millions of years.

Biotic Interactions and the Future of Fishes on Coral Reefs: The Importance of Trait-Based Approaches

Biotic interactions govern the structure and function of coral reef ecosystems. As environmental conditions change, reef-associated fish populations can persist by tracking their preferred niche or adapting to new conditions. Biotic interactions will affect how these responses proceed and whether they are successful. Yet, our understanding of these effects is currently limited. Ecological and evolutionary theories make explicit predictions about the effects of biotic interactions, but many remain untested. Here, we argue that large-scale functional trait datasets enable us to investigate how biotic interactions have shaped the assembly of contemporary reef fish communities and the evolution of species within them, thus improving our ability to predict future changes. Importantly, the effects of biotic interactions on these processes have occurred simultaneously within dynamic environments. Functional traits provide a means to integrate the effects of both ecological and evolutionary processes, as well as a way to overcome some of the challenges of studying biotic interactions. Moreover, functional trait data can enhance predictive modeling of future reef fish distributions and evolvability. We hope that our vision for an integrative approach, focused on quantifying functionally relevant traits and how they mediate biotic interactions in different environmental contexts, will catalyze new research on the future of reef fishes in a changing environment.

Estimating ancient biogeographic patterns with statistical model discrimination

The geographic ranges in which species live is a function of many factors underlying ecological and evolutionary contingencies. Observing the geographic range of an individual species provides valuable information about these historical contingencies for a lineage, determining the distribution of many distantly related species in tandem provides information about large-scale constraints on evolutionary and ecological processes generally. We present a linear regression method that allows for the discrimination of various hypothetical biogeographical models for determining which landscape distributional pattern best matches data from the fossil record. The linear regression models used in the discrimination rely on geodesic distances between sampling sites (typically geologic formations) as the independent variable and three possible dependent variables: Dice/Sorensen similarity; Euclidean distance; and phylogenetic community dissimilarity. Both the similarity and distance measures are useful for full-community analyses without evolutionary information, whereas the phylogenetic community dissimilarity requires phylogenetic data. Importantly, the discrimination method uses linear regression residual error to provide relative measures of support for each biogeographical model tested, not absolute answers or p-values. When applied to a recently published dataset of Campanian pollen, we find evidence that supports two plant communities separated by a transitional zone of unknown size. A similar case study of ceratopsid dinosaurs using phylogenetic community dissimilarity provided no evidence of a biogeographical pattern, but this case study suffers from a lack of data to accurately discriminate and/or too much temporal mixing. Future research aiming to reconstruct the distribution of organisms across a landscape has a statistical-based method for determining what biogeographic distributional model best matches the available data.

The Self-Organization of Marine Microbial Networks under Evolutionary and Ecological Processes: Observations and Modeling

Simple Summary

The properties and structure of ecological networks in marine microbial communities determine ecosystem functions and stability; however, the principles of microbial network assemblages are poorly understood. In this study, we revealed the influences of species phylogeny and niches on the self-organization of marine microbial co-occurrence networks and provided a mathematical framework to simulate microbial network assemblages. Our results provide deep insights into network stability from the perspective of network assembly principles and not just network properties, such as complexity and modularity.

Abstract

Evolutionary and ecological processes are primary drivers of ecological network constrictions. However, the ways that these processes underpin self-organization and modularity in networks are poorly understood. Here, we performed network analyses to explore the evolutionary and ecological effects on global marine microbial co-occurrence networks across multiple network levels, including those of nodes, motifs, modules and whole networks. We found that both direct and indirect species interactions were evolutionarily and ecologically constrained across at least four network levels. Compared to ecological processes, evolutionary processes generally showed stronger long-lasting effects on indirect interactions and dominated the network assembly of particle-associated communities in spatially homogeneous environments. Regarding the large network path distance, the contributions of either processes to species interactions generally decrease and almost disappear when network path distance is larger than six. Accordingly, we developed a novel mathematical model based on scale-free networks by considering the joint effects of evolutionary and ecological processes. We simulated the self-organization of microbial co-occurrence networks and found that long-lasting effects increased network stability via decreasing link gain or loss. Overall, these results revealed that evolutionary and ecological processes played key roles in the self-organization and modularization of microbial co-occurrence networks.

A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities

Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate simultaneously to shape patterns of biodiversity. Reconciling the relative importance of these is hindered by current models and inference methods, which tend to focus on a subset of processes and their resulting predictions. Here we introduce massive ecoevolutionary synthesis simulations (MESS), a unified mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: (i) species richness and abundances, (ii) population genetic diversities, and (iii) trait variation in a phylogenetic context. Using simulations we demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. MESS is unique in generating predictions of community-scale genetic diversity, and in characterizing joint patterns of genetic diversity, abundance, and trait values. MESS unlocks the full potential for investigation of biodiversity processes using multidimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine MESS with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of data availability scenarios, and spatial and taxonomic scales.

Plant-bacteria associations are phylogenetically structured in the phyllosphere

Determining whether and how global change will lead to novel interactions between hosts and microbes is an important issue in ecology and evolution. Understanding the contribution of host and microbial ecologies and evolutionary histories in driving their contemporary associations is an important step towards addressing this challenge and predicting the fitness consequences of novel associations. Using shotgun metagenomic and amplicon sequencing of bacterial communities from the leaf surfaces (phyllosphere) of trees, we investigated how phylogenetic relatedness among hosts and among their associated bacteria influences the distribution of bacteria among hosts. We also evaluated whether the functional traits of trees and bacteria explained these associations across multiple host species. We show that phylogenetically similar hosts tended to associate with the same bacteria and that phylogenetically similar bacteria tended to associate with the same host species. Phylogenetic interactions between tree and bacterial taxa also explained variation in their associations. The effect of host and symbiont evolutionary histories on bacterial distribution across hosts were observed across phylogenetic scales, but prominently explained variation among higher taxonomic categories of hosts and symbionts. These results suggest that ecological variation arising early in the plant and bacterial phylogenies have been particularly important for driving their contemporary associations. Variation in bacterial functional genes associated with the biosynthesis of aromatic amino acids and compounds and with cell motility were notably important in explaining bacterial community turnover among gymnosperm and angiosperm hosts. Overall, our results suggest an influence of host and bacterial traits and evolutionary histories in driving their contemporary associations.

Role of Algal Community Stability in Harmful Algal Blooms in River-Connected Lakes

Harmful algal blooms (HABs) in freshwater produce toxins that pose a threat to public health and aquatic ecosystems. Although algal communities have been studied globally to understand the characteristics of HABs, the occurrence of toxic cyanobacteria in freshwater ecosystems is rarely understood. Unlike abiotic factors, the effects of biotic factors (e.g., interaction, dominance, and variability) on the occurrence of toxic cyanobacteria were overlooked due to the intricate interaction of microorganisms under different environmental conditions. To address this problem, a comprehensive ecological concept stability, which encompasses variations in species or communities due to changing biological interactions or environmental fluctuations, was applied in this study. The algal communities in six river-connected lakes in the North Han River, South Korea, were classified into high and low stability groups. The algal species belonging to diatoms and green algae groups played a major role in the interaction within the algal community in highly stable lakes, but the frequency of Microcystis led the interaction within the algal community at the center of the network in low-stability lakes. These results indicate that the interaction within the cluster is easily changed by Microcystis, where the abundance explosively increases in lakes with low algal community stability. Water quality is more strongly associated with the occurrence of toxic cyanobacteria (Microcystis and Dolichospermum). In low-stability lakes, more diverse water quality indicators are correlated with the development of toxic algae than in high-stability lakes. This paper is the first report on the importance of algal community stability in freshwater in the occurrence of toxic cyanobacteria and offers a new perspective on Microcystis monitoring and management.

Tempo and mode of morphological evolution are decoupled from latitude in birds

The latitudinal diversity gradient is one of the most striking patterns in nature, yet its implications for morphological evolution are poorly understood. In particular, it has been proposed that an increased intensity of species interactions in tropical biota may either promote or constrain trait evolution, but which of these outcomes predominates remains uncertain. Here, we develop tools for fitting phylogenetic models of phenotypic evolution in which the impact of species interactions-namely, competition-can vary across lineages. Deploying these models on a global avian trait dataset to explore differences in trait divergence between tropical and temperate lineages, we find that the effect of latitude on the mode and tempo of morphological evolution is weak and clade- or trait dependent. Our results indicate that species interactions do not disproportionately impact morphological evolution in tropical bird families and question the validity of previously reported patterns of slower trait evolution in the tropics.

Studying Microbial Communities through Co-Occurrence Network Analyses during Processes of Waste Treatment and in Organically Amended Soils: A Review

Organic wastes have the potential to be used as soil organic amendments after undergoing a process of stabilization such as composting or as a resource of renewable energy by anaerobic digestion (AD). Both composting and AD are well-known, eco-friendly approaches to eliminate and recycle massive amounts of wastes. Likewise, the application of compost amendments and digestate (the by-product resulting from AD) has been proposed as an effective way of improving soil fertility. The study of microbial communities involved in these waste treatment processes, as well as in organically amended soils, is key in promoting waste resource efficiency and deciphering the features that characterize microbial communities under improved soil fertility conditions. To move beyond the classical analyses of metataxonomic data, the application of co-occurrence network approaches has shown to be useful to gain insights into the interactions among the members of a microbial community, to identify its keystone members and modelling the environmental factors that drive microbial network patterns. Here, we provide an overview of essential concepts for the interpretation and construction of co-occurrence networks and review the features of microbial co-occurrence networks during the processes of composting and AD and following the application of the respective end products (compost and digestate) into soil.

Macroevolutionary stability predicts interaction patterns of species in seed dispersal networks

Assessing deep-time mechanisms affecting the assembly of ecological networks is key to understanding biodiversity changes on broader time scales. We combined analyses of diversification rates with interaction network descriptors from 468 bird species belonging to 29 seed dispersal networks to show that bird species that contribute most to the network structure of plant–frugivore interactions belong to lineages that show higher macroevolutionary stability. This association is stronger in warmer, wetter, less seasonal environments. We infer that the macroevolutionary sorting mechanism acts through the regional pool of species by sorting species on the basis of the available relative differences in diversification rates, rather than absolute rates. Our results illustrate how the interplay between interaction patterns and diversification dynamics may shape the organization and long-term dynamics of ecological networks.

Priority effects and the macroevolutionary dynamics of biodiversity

Priority effects can play a fundamental role in the assembly of ecological communities, but how they shape the dynamics of biodiversity over macroevolutionary timescales remains unclear. Here we develop and analyse a metacommunity model combining local priority effects with niche evolution, speciation and extinction. We show that by promoting the persistence of rare species, local priority effects cause the evolution of higher metacommunity diversity as well as major disparities in richness among evolutionary lineages. However, we also show how classic macroevolutionary patterns of niche incumbency-whereby rates of regional diversification and invasion slow down as ecological niches are filled-do not depend on local priority effects, arising even when invading species continuously displace residents. Together, these results clarify the connection between local priority effects and the filling of ecological niche space, and reveal how the impact of species arrival order on competition fundamentally shapes the generation and maintenance of biodiversity.

On the Effect of Asymmetrical Trait Inheritance on Models of Trait Evolution

Current phylogenetic comparative methods modeling quantitative trait evolution generally assume that, during speciation, phenotypes are inherited identically between the two daughter species. This, however, neglects the fact that species consist of a set of individuals, each bearing its own trait value. Indeed, because descendent populations after speciation are samples of a parent population, we can expect their mean phenotypes to randomly differ from one another potentially generating a "jump" of mean phenotypes due to asymmetrical trait inheritance at cladogenesis. Here, we aim to clarify the effect of asymmetrical trait inheritance at speciation on macroevolutionary analyses, focusing on model testing and parameter estimation using some of the most common models of quantitative trait evolution. We developed an individual-based simulation framework in which the evolution of phenotypes is determined by trait changes at the individual level accumulating across generations, and cladogenesis occurs then by separation of subsets of the individuals into new lineages. Through simulations, we assess the magnitude of phenotypic jumps at cladogenesis under different modes of trait inheritance at speciation. We show that even small jumps can strongly alter both the results of model selection and parameter estimations, potentially affecting the biological interpretation of the estimated mode of evolution of a trait. Our results call for caution when interpreting analyses of trait evolution, while highlighting the importance of testing a wide range of alternative models. In the light of our findings, we propose that future methodological advances in comparative methods should more explicitly model the intraspecific variability around species mean phenotypes and how it is inherited at speciation.

Phylogenetic signatures of ecological divergence and leapfrog adaptive radiation in Espeletia

PREMISE

Events of accelerated species diversification represent one of Earth's most celebrated evolutionary outcomes. Northern Andean high-elevation ecosystems, or páramos, host some plant lineages that have experienced the fastest diversification rates, likely triggered by ecological opportunities created by mountain uplifts, local climate shifts, and key trait innovations. However, the mechanisms behind rapid speciation into the new adaptive zone provided by these opportunities have long remained unclear.

METHODS

We address this issue by studying the Venezuelan clade of Espeletia, a species-rich group of páramo-endemics showing a dazzling ecological and morphological diversity. We performed several comparative analyses to study both lineage and trait diversification, using an updated molecular phylogeny of this plant group.

RESULTS

We showed that sets of either vegetative or reproductive traits have conjointly diversified in Espeletia along different vegetation belts, leading to adaptive syndromes. Diversification in vegetative traits occurred earlier than in reproductive ones. The rate of species and morphological diversification showed a tendency to slow down over time, probably due to diversity dependence. We also found that closely related species exhibit significantly more overlap in their geographic distributions than distantly related taxa, suggesting that most events of ecological divergence occurred at close geographic proximity within páramos.

CONCLUSIONS

These results provide compelling support for a scenario of small-scale ecological divergence along multiple ecological niche dimensions, possibly driven by competitive interactions between species, and acting sequentially over time in a leapfrog pattern.

The Structure of Ecological Networks Across Levels of Organization

Interactions connect the units of ecological systems, forming networks. Individual-based networks characterize variation in niches among individuals within populations. These individual-based networks merge with each other, forming species-based networks and food webs that describe the architecture of ecological communities. Networks at broader spatiotemporal scales portray the structure of ecological interactions across landscapes and over macroevolutionary time. Here, I review the patterns observed in ecological networks across multiple levels of biological organization. A fundamental challenge is to understand the amount of interdependence as we move from individual-based networks to species-based networks and beyond. Despite the uneven distribution of studies, regularities in network structure emerge across scales due to the fundamental architectural patterns shared by complex networks and the interplay between traits and numerical effects. I illustrate the integration of these organizational scales by exploring the consequences of the emergence of highly connected species for network structures across scales.

Ecological Interactions and Macroevolution: A New Field with Old Roots

Linking interspecific interactions (e.g., mutualism, competition, predation, parasitism) to macroevolution (evolutionary change on deep timescales) is a key goal in biology. The role of species interactions in shaping macroevolutionary trajectories has been studied for centuries and remains a cutting-edge topic of current research. However, despite its deep historical roots, classic and current approaches to this topic are highly diverse. Here, we combine historical and contemporary perspectives on the study of ecological interactions in macroevolution, synthesizing ideas across eras to build a zoomed-out picture of the big questions at the nexus of ecology and macroevolution. We discuss the trajectory of this important and challenging field, dividing research into work done before the 1970s, research between 1970 and 2005, and work done since 2005. We argue that in response to long-standing questions in paleobiology, evidence accumulated to date has demonstrated that biotic interactions (including mutualism) can influence lineage diversification and trait evolution over macroevolutionary timescales, and we outline major open questions for future research in the field.

Inferring the Effect of Species Interactions on Trait Evolution

Models of trait evolution form an important part of macroevolutionary biology. The Brownian motion model and Ornstein–Uhlenbeck models have become classic (null) models of character evolution, in which species evolve independently. Recently, models incorporating species interactions have been developed, particularly involving competition where abiotic factors pull species toward an optimal trait value and competitive interactions drive the trait values apart. However, these models assume a fitness function rather than derive it from population dynamics and they do not consider dynamics of the trait variance. Here, we develop a general coherent trait evolution framework where the fitness function is based on a model of population dynamics, and therefore it can, in principle, accommodate any type of species interaction. We illustrate our framework with a model of abundance-dependent competitive interactions against a macroevolutionary background encoded in a phylogenetic tree. We develop an inference tool based on Approximate Bayesian Computation and test it on simulated data (of traits at the tips). We find that inference performs well when the diversity predicted by the parameters equals the number of species in the phylogeny. We then fit the model to empirical data of baleen whale body lengths, using three different summary statistics, and compare it to a model without population dynamics and a model where competition depends on the total metabolic rate of the competitors. We show that the unweighted model performs best for the least informative summary statistic, while the model with competition weighted by the total metabolic rate fits the data slightly better than the other two models for the two more informative summary statistics. Regardless of the summary statistic used, the three models substantially differ in their predictions of the abundance distribution. Therefore, data on abundance distributions will allow us to better distinguish the models from one another, and infer the nature of species interactions. Thus, our framework provides a conceptual approach to reveal species interactions underlying trait evolution and identifies the data needed to do so in practice. [Approximate Bayesian computation; competition; phylogeny; population dynamics; simulations; species interaction; trait evolution.]

Phylogenomics of Monitor Lizards and the Role of Competition in Dictating Body Size Disparity

Organismal interactions drive the accumulation of diversity by influencing species ranges, morphology, and behavior. Interactions vary from agonistic to cooperative and should result in predictable patterns in trait and range evolution. However, despite a conceptual understanding of these processes, they have been difficult to model, particularly on macroevolutionary timescales and across broad geographic spaces. Here, we investigate the influence of biotic interactions on trait evolution and community assembly in monitor lizards (Varanus). Monitors are an iconic radiation with a cosmopolitan distribution and the greatest size disparity of any living terrestrial vertebrate genus. Between the colossal Komodo dragon Varanus komodoensis and the smallest Australian dwarf goannas, Varanus length and mass vary by multiple orders of magnitude. To test the hypothesis that size variation in this genus was driven by character displacement, we extended existing phylogenetic comparative methods which consider lineage interactions to account for dynamic biogeographic history and apply these methods to Australian monitors and marsupial predators. Incorporating both exon-capture molecular and morphological data sets we use a combined evidence approach to estimate the relationships among living and extinct varaniform lizards. Our results suggest that communities of Australian Varanus show high functional diversity as a result of continent-wide interspecific competition among monitors but not with faunivorous marsupials. We demonstrate that patterns of trait evolution resulting from character displacement on continental scales are recoverable from comparative data and highlight that these macroevolutionary patterns may develop in parallel across widely distributed sympatric groups.[Character displacement; comparative methods; phylogenetics; trait evolution; Varanus.].

Contrasting Patterns of the Bacterial Communities in Melting Ponds and Periglacial Rivers of the Zhuxi glacier in the Tibet Plateau

Since the early 21^st century, global climate change has been inducing rapid glacier retreat at an unprecedented rate. In this context, the melt ponds impart increasing unique footprints on the periglacial rivers due to their hydrodynamic connection. Given that bacterial communities control numerous ecosystem processes in the glacial ecosystem, exploring the fate of bacterial communities from melt ponds to periglacial rivers yields key knowledge of the biodiversity and biogeochemistry of glacial ecosystems. Here, we analyzed the bacterial community structure, diversity, and co-occurrence network to reveal the community organization in the Zhuxi glacier in the Tibet Plateau. The results showed that the bacterial communities in melt ponds were significantly lower in alpha-diversity but were significantly higher in beta-diversity than those in periglacial rivers. The rare sub-communities significantly contributed to the stability of the bacterial communities in both habitats. The co-occurrence network inferred that the mutually beneficial relationships predominated in the two networks. Nevertheless, the lower ratio of positive to negative edges in melt ponds than periglacial rivers implicated fiercer competition in the former habitat. Based on the significantly higher value of degree, betweenness, and modules, as well as shorter average path length in melt ponds, we speculated that their bacterial communities are less resilient than those of periglacial rivers.

Large-sized planktonic bioaggregates possess high biofilm formation potentials: Bacterial succession and assembly in the biofilm metacommunity

Wanted and unwanted surface-attached growth of bacteria is ubiquitous in natural and engineered settings. Normally, attachment of planktonic cells to media surfaces initiates biofilm formation and fundamentally regulates biofilm assembly processes. Here, culturing biofilm with planktonic sludge as source community, we found distinct succession profiles of biofilm communities sourced from the size-fractionated sludge flocs (<25; 25-120; >120 μm). Null model analyses revealed that deterministic process dominated in biofilm community assemblies but decreased with decreasing floc size. Additionally, the relative importance of environmental selection increased with increasing floc size of the source sludge, whereas homogenizing dispersal and ecological drift followed opposite trends. Phylogenetic molecular ecological networks (pMENs) indicated that species interactions were intensive in biofilm microbiota developed from large-sized flocs (>120 μm), as evidenced by the low modularity and harmonic geodesic distance and the high average degree. Intriguingly, the keystone taxa in these biofilm ecological networks were controlled by distinct interaction patterns but all showed strong habitat characteristics (e.g., facultative anaerobic, motile, hydrophobic and involved in extracellular polymeric substance metabolism), corroborating the crucial roles of environmental filtering in structuring biofilm community. Taken together, our findings highlight the role of planktonic floc properties in biofilm community assembly and advance our understanding of microbial ecology in biofilm-based systems.

Distinct mechanisms shape soil bacterial and fungal co-occurrence networks in a mountain ecosystem

Understanding microbial network assembly is a promising way to predict potential impacts of environmental changes on ecosystem functions. Yet, soil microbial network assembly in mountain ecosystems and its underlying mechanisms remain elusive. Here, we characterized soil microbial co-occurrence networks across 12 altitudinal sites in Mountain Gongga. Despite differences in habitats, soil bacterial networks separated into two different clusters by altitude, namely the lower and higher altitudes, while fungi did not show such a pattern. Bacterial networks encompassed more complex and closer relationships at the lower altitudes, while fungi had closer relationships at the higher altitudes, which could be attributed to niche differentiation caused by high variations in soil environments and plant communities. Both abiotic and biotic factors (e.g. soil pH and bacterial community composition) shaped bacterial networks. However, biotic factors played more important roles than the measured abiotic factors for fungal network assembly. Further analyses suggest that multiple mechanisms including niche overlap/differentiation, cross-feeding and competition between microorganisms could play important roles in shaping soil microbial networks. This study reveals microbial co-occurrence networks in response to different ecological factors, which provides important insights into our comprehensive understanding of microbial network assembly and their functional potentials in mountain ecosystems.

Interdependent Phenotypic and Biogeographic Evolution Driven by Biotic Interactions

Biotic interactions are hypothesized to be one of the main processes shaping trait and biogeographic evolution during lineage diversification. Theoretical and empirical evidence suggests that species with similar ecological requirements either spatially exclude each other, by preventing the colonization of competitors or by driving coexisting populations to extinction, or show niche divergence when in sympatry. However, the extent and generality of the effect of interspecific competition in trait and biogeographic evolution has been limited by a dearth of appropriate process-generating models to directly test the effect of biotic interactions. Here, we formulate a phylogenetic parametric model that allows interdependence between trait and biogeographic evolution, thus enabling a direct test of central hypotheses on how biotic interactions shape these evolutionary processes. We adopt a Bayesian data augmentation approach to estimate the joint posterior distribution of trait histories, range histories, and coevolutionary process parameters under this analytically intractable model. Through simulations, we show that our model is capable of distinguishing alternative scenarios of biotic interactions. We apply our model to the radiation of Darwin’s finches—a classic example of adaptive divergence—and find limited support for in situ trait divergence in beak size, but stronger evidence for convergence in traits such as beak shape and tarsus length and for competitive exclusion throughout their evolutionary history. These findings are more consistent with presympatric, rather than postsympatric, niche divergence. Our modeling framework opens new possibilities for testing more complex hypotheses about the processes underlying lineage diversification. More generally, it provides a robust probabilistic methodology to model correlated evolution of continuous and discrete characters. [Bayesian; biotic interactions; competition; data augmentation; historical biogeography; trait evolution.]

Identifying models of trait-mediated community assembly using random forests and approximate Bayesian computation

Ecologists often use dispersion metrics and statistical hypothesis testing to infer processes of community formation such as environmental filtering, competitive exclusion, and neutral species assembly. These metrics have limited power in inferring assembly models because they rely on often-violated assumptions. Here, we adapt a model of phenotypic similarity and repulsion to simulate the process of community assembly via environmental filtering and competitive exclusion, all while parameterizing the strength of the respective ecological processes. We then use random forests and approximate Bayesian computation to distinguish between these models given the simulated data. We find that our approach is more accurate than using dispersion metrics and accounts for uncertainty in model selection. We also demonstrate that the parameter determining the strength of the assembly processes can be accurately estimated. This approach is available in the R package CAMI; Community Assembly Model Inference. We demonstrate the effectiveness of CAMI using an example of plant communities living on lava flow islands.

The nature of interspecific interactions and co-diversification patterns, as illustrated by the fig microcosm

Interactions between mutualists, competitors, and antagonists have contrasting ecological effects that, sustained over generations, can influence micro- and macroevolution. Dissimilar benefits and costs for these interactions should cause contrasting co-diversification patterns between interacting clades, with prevalent co-speciation by mutualists, association loss by competitors, and host switching by antagonists. We assessed these expectations for a local assemblage of 26 fig species (Moraceae: Ficus), 26 species of mutualistic (pollinating), and 33 species of parasitic (galling) wasps (Chalcidoidea). Using newly acquired gene sequences, we inferred the phylogenies for all three clades. We then compared the three possible pairs of phylogenies to assess phylogenetic congruence and the relative frequencies of co-speciation, association duplication, switching, and loss. The paired phylogenies of pollinators with their mutualists and competitors were significantly congruent, unlike that of figs and their parasites. The distributions of macroevolutionary events largely agreed with expectations for mutualists and antagonists. By contrast, that for competitors involved relatively frequent association switching, as expected, but also unexpectedly frequent co-speciation. The latter result likely reflects the heterogeneous nature of competition among fig wasps. These results illustrate the influence of different interspecific interactions on co-diversification, while also revealing its dependence on specific characteristics of those interactions.

Understanding the effect of competition during evolutionary radiations: an integrated model of phenotypic and species diversification

Competition can drive macroevolutionary change, for example during adaptive radiations. However, we still lack a clear understanding of how it shapes diversification processes and patterns. To better understand the macroevolutionary consequences of competition, as well as the signal left on phylogenetic data, we developed a model linking trait evolution and species diversification in an ecological context. We find four main results: first, competition spurs trait diversity but not necessarily species richness; second, competition produces slowdowns in species diversification even in the absence of explicit ecological limits, but not in phenotypic diversification even in the presence of such limits; third, early burst patterns do not provide a reliable way of testing for adaptive radiations; and fourth, looking for phylogenetic signal in trait data and support for phenotypic models incorporating competition is a better alternative. Our results clarify the macroevolutionary consequences of competition and could help design more powerful tests of adaptive radiations in nature.

An ancestral process with selection in an ecological community

An ecological community is a geographical area composed of two or more species. The ancestral histories of individuals from the same and different species in an ecological community may be interconnected due to direct and indirect interactions. Here, we present a model of the ancestral history of an ecological community that is built upon the framework of coalescent and ancestral graph theory. The model includes selection, whereby the fitness of an ancestral lineage is a function of both its abiotic environment and interactions with individuals from its biotic environment. The model also allows for metacommunity structure. We first define a forward-time percolation process characterizing the evolution of an ecological community and then present its corresponding backward-time graphical model in the limit of large population sizes. Next, we present expectations of properties of phenotypes in the graph. These expectations give insight into the structure of phenotypic variation and trait-environment covariances across local communities, including the effects of drift, intra and inter-species genealogical structure and the sampling effects of selection. In addition, we derive expectations for multivariate phenotypic diversity in a community assuming neutrality and compare this to expectations with stabilizing selection.

Tests of alternative evolutionary models are needed to enhance our understanding of biological invasions

Contents Summary 701 I. Introduction 701 II. Why we need an explicitly evolutionary perspective 702 III. A case study invasion experiment 702 IV. The way forward 703 V. Conclusions 705 Acknowledgements 706 References 706 SUMMARY: Comparing models of trait evolution might generate new insights into the role of evolutionary history in biological invasions. Assumptions underlying Darwin's naturalization conundrum suggest that close relatives are functionally similar. However, newer work is suggesting more complex relationships between phylogenetic and functional distance. We present an example in which communities of close relatives are functionally divergent in leaf traits and have greater invader biomass. Such an approach leads to new questions, such as: When might selection lead to divergence between close relatives? For example, a history of sympatry might correspond with divergence. We suggest that moving beyond a simplistic version of Darwin's naturalization conundrum as alternative hypotheses will lead to a more nuanced view on how evolution has shaped biological invasions.

Detecting Environment-Dependent Diversification From Phylogenies: A Simulation Study and Some Empirical Illustrations

Understanding the relative influence of various abiotic and biotic variables on diversification dynamics is a major goal of macroevolutionary studies. Recently, phylogenetic approaches have been developed that make it possible to estimate the role of various environmental variables on diversification using time-calibrated species trees, paleoenvironmental data, and maximum-likelihood techniques. These approaches have been effectively employed to estimate how speciation and extinction rates vary with key abiotic variables, such as temperature and sea level, and we can anticipate that they will be increasingly used in the future. Here we compile a series of biotic and abiotic paleodatasets that can be used as explanatory variables in these models and use simulations to assess the statistical properties of the approach when applied to these paleodatasets. We demonstrate that environment-dependent models perform well in recovering environment-dependent speciation and extinction parameters, as well as in correctly identifying the simulated environmental model when speciation is environment-dependent. We explore how the strength of the environment-dependency, tree size, missing taxa, and characteristics of the paleoenvironmental curves influence the performance of the models. Finally, using these models, we infer environment-dependent diversification in two empirical phylogenies: temperature-dependence in Cetacea and $\delta^{13}C$-dependence in Ruminantia. We illustrate how to evaluate the relative importance of abiotic and biotic variables in these two clades and interpret these results in light of macroevolutionary hypotheses. Given the important role paleoenvironments are presumed to have played in species evolution, our statistical assessment of how environment-dependent models behave is crucial for their utility in macroevolutionary analysis.

Contemporary Ecological Interactions Improve Models of Past Trait Evolution

Despite the fact that natural selection underlies both traits and interactions, evolutionary models often neglect that ecological interactions may, and in many cases do, influence the evolution of traits. Herein, we explore the interdependence of ecological interactions and functional traits in the pollination associations of hawkmoths and flowering plants. Specifically, we develop an adaptation of the Ornstein-Uhlenbeck model of trait evolution that allows us to study the influence of plant corolla depth and observed hawkmoth-plant interactions on the evolution of hawkmoth proboscis length. Across diverse modelling scenarios, we find that the inclusion of contemporary interactions can provide a better description of trait evolution than the null expectation. Moreover, we show that the pollination interactions provide more-likely models of hawkmoth trait evolution when interactions are considered at increasingly fine-scale groups of hawkmoths. Finally, we demonstrate how the results of best-fit modeling approaches can implicitly support the association between interactions and trait evolution that our method explicitly examines. In showing that contemporary interactions can provide insight into the historical evolution of hawkmoth proboscis length, we demonstrate the clear utility of incorporating additional ecological information to models designed to study past trait evolution.

Two-year microbial adaptation during hydrogen-mediated biogas upgrading process in a serial reactor configuration

Microbial dynamics in an upgrading biogas reactor system undergoing a more than two years-period at stable operating conditions were explored. The carbon dioxide generated during biomass degradation in the first reactor of the system was converted to methane into the secondary reactor by addition of external hydrogen. Considering the overall efficiency, the long-term operation period resulted in an improved biogas upgrading performance (99% methane content). However, a remarkable accumulation of acetate was revealed, indicating the enhancement of homoacetogenic activity. For this reason, a shift in the anaerobic digestion microbiome was expected and evaluated by 16S rRNA amplicon analysis. Results demonstrated that the most abundant archaeal species identified in the first time point, Candidatus Methanoculleus thermohydrogenotrophicum, was replaced by Methanothermobacter thermautotrophicus, becoming dominant after the community adaptation. The most interesting taxonomic units were clustered by relative abundance and six main long-term adaptation trends were found, characterizing functionally related microbes (e.g. homoacetogens).

Inferring Evolutionary Process From Neuroanatomical Data

Brain evolution has interested neuroanatomists for over a century. These interests often fall on how free the brain is to evolve independently of the body, how free brain regions are to evolve independently of each other, and how different environmental and ecological factors affect the brain over evolutionary time. But despite major advances in phylogenetic methods, comparative neuroanatomists have tended to limit their macroevolutionary toolbox to regression-based analyses and ignored the scope of evolutionary process-based models at their disposal. This Review summarizes the history of comparative neuroanatomy and highlights the pitfalls of the methodologies traditionally used. It provides an overview of evolutionary process-based modeling approaches for investigating univariate and multivariate data, as well as more sophisticated methods that incorporate hypotheses about biotic and abiotic pressures that may drive brain evolution. The benefits of evolutionary process-based models, and shortcomings of regression-based ones, are illustrated with widely used neuroanatomical data. Ultimately, the intent of this Review is to be a guide for subsuming macroevolutionary methods not typically used in comparative neuroanatomy, in order to improve our understanding of how the brain evolves.

Co-occurrence Network Reveals the Higher Fragmentation of the Bacterial Community in Kaidu River Than Its Tributaries in Northwestern China

Rivers and their tributaries sculpt the earth's surface, and play an important role in substance circulation and energy flow. Bacteria are involved in most biogeochemical processes in the fluvial ecosystem; however, their pattern distribution in a river and its tributaries has not yet been investigated in detail. In the present study, high-throughput sequencing was employed to examine bacterial communities and their co-occurrence networks between Kaidu River and its nine tributaries in northwestern China. The results obtained demonstrated that both bacterial communities shared a similar dominant sub-community, mainly consisting of Actinobacteria, Bacteroidetes, and Proteobacteria, with Limnohabitans and Variovorax as the dominant genera. In spite of these commonalities, bacterial community structures still significantly differed between these two habitats, which may be related to the distance-related dispersal limitation. Their co-occurrence networks were generally both positively structured. The structural analysis showed that OTUs from the same phyla were more likely to co-occur. Although the keystone genera were taxonomically different between Kaidu River and its tributaries, they both shared common trophic properties in exploiting niches under oligotrophic conditions. We noted that their relative abundances were less than 1%, indicating the over-proportional roles of rare genera in the bacterial community. In addition, the inferred networks showed less nodes and edges, but higher modularity in Kaidu River than its tributaries, suggesting the higher fragmentation of the bacterial community in the mainstream.

Preadaptation and Naturalization of Nonnative Species: Darwin's Two Fundamental Insights into Species Invasion

Predicting which nonnative species become invasive is critical for their successful management, and Charles Darwin provided predictions based on species' relatedness. However, Darwin provided two opposing predictions about the relatedness of introduced nonnatives to indigenous species. First, environmental fit is the dominant factor determining invader success; thus, we should expect that invasive species are closely related to local native residents. Alternatively, if competition is important, we should expect successful invaders are distantly related to the native residents. These opposing expectations are referred to as Darwin's naturalization conundrum. The results of studies that examine nonnative species relatedness to natives are largely inconsistent. This inconsistency arises from the fact that studies occur at different spatial and temporal scales, and at different stages of invasion, and so implicitly examine different mechanisms. Further, while species have evolved ecological differences, the mode and tempo of evolution can affect species' differences, complicating the predictions from simple hypotheses. We outline unanswered questions and provide guidelines for collecting the data required to test competing hypotheses.