A simulation-based approach to understand how metacommunity characteristics influence emergent biodiversity patterns

In a niche-neutral continuum, a set of theoretical models in a metacommunity operates simultaneously in patchy habitats

This study investigated the origins and maintenance of biodiversity by integrating ecological and evolutionary mechanisms into a spatially-explicit synthesis between niche-based processes and neutral dynamics (ND). An individual-based model on a two-dimensional grid with periodic boundary conditions was used to compare a niche-neutral continuum induced in contrasting spatial and environmental settings while characterizing the operational scaling of deterministic-stochastic processes. The spatially-explicit simulations revealed three major findings. First, the number of guilds in a system approaches a stationary state and the species composition in a system converges to a dynamic equilibrium of ecologically-equivalent species generated by the speciation-extinction balance. This convergence of species composition can be argued under a point mutation mode of speciation and niche conservatism due to the duality of ND. Second, the dispersal modes of biota may affect how the influence of environmental filtering changes across ecological-evolutionary scales. This influence is greatest in compactly-packed areas within biogeographic units for large-bodied active dispersers, such as fish. Third, the species are filtered along the environmental gradient and the coexistence of ecologically-different species in each local community in a homogeneous environment is allowed by dispersals in a set of local communities. Therefore, the ND among the single-guild species, extinction-colonization trade-off among species of similar environmental optima and different levels of specialization, and mass effect, such as weak species-environment associations, operate simultaneously in patchy habitats. In spatially-explicit synthesis, characterizing where a metacommunity falls along a niche-neutral continuum is too superficial and involves an abstraction that any biological process is probabilistic; therefore, they are dynamic-stochastic processes. The general patterns observed in the simulations allowed a theoretical synthesis of a metacommunity and explained the complex patterns observed in the real world.

Blowin' in the wind: Dispersal, structure, and metacommunity dynamics of aeolian diatoms in the McMurdo Sound region, Antarctica

Diatom metacommunities are structured by environmental, historical, and spatial factors that are often attributed to organism dispersal. In the McMurdo Sound region (MSR) of Antarctica, wind connects aquatic habitats through delivery of inorganic and organic matter. We evaluated the dispersal of diatoms in aeolian material and its relation to the regional diatom metacommunity using light microscopy and 18S rRNA high-throughput sequencing. The concentration of diatoms ranged from 0 to 8.76 * 10⁶  valves · g^-1 dry aeolian material. Up to 15% of whole cells contained visible protoplasm, indicating that up to 3.43 * 10⁴ potentially viable individuals could be dispersed in a year to a single 2 -cm² site. Diatom DNA and RNA was detected at each site, reinforcing the likelihood that we observed dispersal of viable diatoms. Of the 50 known morphospecies in the MSR, 72% were identified from aeolian material using microscopy. Aeolian community composition varied primarily by site. Meanwhile, each aeolian community was comprised of morphospecies found in aquatic communities from the same lake basin. These results suggest that aeolian diatom dispersal in the MSR is spatially structured, is predominantly local, and connects local aquatic habitats via a shared species pool. Nonetheless, aeolian community structure was distinct from that of aquatic communities, indicating that intrahabitat dispersal and environmental filtering also underlie diatom metacommunity dynamics. The present study confirms that a large number of diatoms are passively dispersed by wind across a landscape characterized by aeolian processes, integrating the regional flora and contributing to metacommunity structure and landscape connectivity.

Coherence in (meta)community networks

In a general sense, a metacommunity can be considered as a network of communities, the coherence of which is based on characteristics that are shared by members of different communities, whatever forces were responsible (dispersal, migration, local adaptation, etc.). The purpose is to show that by basing the assessment of coherence on the degree of nestedness of one community within another with respect to the shared characteristics, coherence components can be identified within the network. To assess coherence, a measure of nestedness is developed, and its application to complex (variable) object differences (including multiple traits or characters) is investigated. A community network is then viewed as a graph in which the nodes represent the communities and the edges connecting nodes are weighted by the reverse of the degrees of nestedness between the corresponding communities. Given this framework, it is argued that a minimum requirement for a set of communities to be coherent is the existence of a spanning tree known from graph theory, i.e. a subgraph that connects all nodes through a cycle-free sequence of edges with positive weights. Of all spanning trees, minimum spanning trees (MST, or spanning trees with the minimum sum of edge weights) are most indicative of coherence. By expressing the degree of coherence as one minus the average weight of the edges of an MST, it is uniquely determined which communities form a coherent set at any given level of community distinctness. By this method, community networks can be broken down into coherence components that are separated at a specified distinctness level. This is illustrated in a worked example showing how to apply graph theoretical methods to distinguish coherence components at various threshold levels of object difference (resolution) and community distinctness. These results provide a basis for discussion of coherence gradients and coherence at various levels of distinctness in terms of MST-characteristics. As intuitively expected and analytically confirmed, coherence is a non-decreasing function of the object difference threshold, and the number of coherence components is a non-increasing function of both the object difference and the community distinctness thresholds.

Novel Insights to Be Gained From Applying Metacommunity Theory to Long-Term, Spatially Replicated Biodiversity Data

Global loss of biodiversity and its associated ecosystem services is occurring at an alarming rate and is predicted to accelerate in the future. Metacommunity theory provides a framework to investigate multi-scale processes that drive change in biodiversity across space and time. Short-term ecological studies across space have progressed our understanding of biodiversity through a metacommunity lens, however, such snapshots in time have been limited in their ability to explain which processes, at which scales, generate observed spatial patterns. Temporal dynamics of metacommunities have been understudied, and large gaps in theory and empirical data have hindered progress in our understanding of underlying metacommunity processes that give rise to biodiversity patterns. Fortunately, we are at an important point in the history of ecology, where long-term studies with cross-scale spatial replication provide a means to gain a deeper understanding of the multiscale processes driving biodiversity patterns in time and space to inform metacommunity theory. The maturation of coordinated research and observation networks, such as the United States Long Term Ecological Research (LTER) program, provides an opportunity to advance explanation and prediction of biodiversity change with observational and experimental data at spatial and temporal scales greater than any single research group could accomplish. Synthesis of LTER network community datasets illustrates that long-term studies with spatial replication present an under-utilized resource for advancing spatio-temporal metacommunity research. We identify challenges towards synthesizing these data and present recommendations for addressing these challenges. We conclude with insights about how future monitoring efforts by coordinated research and observation networks could further the development of metacommunity theory and its applications aimed at improving conservation efforts.

Rethinking Biological Invasions as a Metacommunity Problem

Perhaps more than any other ecological discipline, invasion biology has married the practices of basic science and the application of that science. The conceptual frameworks of population regulation, metapopulations, supply-side ecology, and community assembly have all to some degree informed the regulation, management, and prevention of biological invasions. Invasion biology needs to continue to adopt emerging frameworks and paradigms to progress as both a basic and applied science. This need is urgent as the biological invasion problem continues to worsen. The development of metacommunity theory in the last two decades represents a paradigm-shifting approach to community ecology that emphasizes the multi-scale nature of community assembly and biodiversity regulation. Work on metacommunities has demonstrated that even relatively simple processes at local scales are often heavily influenced by regional-scale processes driven primarily by the dispersal of organisms. Often the influence of dispersal interacts with, or even swamps, the influence of local-scale drivers like environmental conditions and species interactions. An emphasis on dispersal and a focus on multi-scale processes enable metacommunity theory to contribute strongly to the advancement of invasion biology. Propagule pressure of invaders has been identified as one of the most important drivers facilitating invasion, so the metacommunity concept, designed to address how dispersal-driven dynamics affect community structure, can directly address many of the central questions of invasion biology. Here we revisit many of the important concepts and paradigms of biological invasions—propagule pressure, biotic resistance, enemy release, functional traits, neonative species, human-assisted transport,—and view those concepts through the lens of metacommunity theory. In doing so, we accomplish several goals. First, we show that work on metacommunities has generated multiple predictions, models, and the tools that can be directly applied to invasion scenarios. Among these predictions is that invasibility of a community should decrease with both local controls on community assembly, and the dispersal rates of native species. Second, we demonstrate that framing biological invasions in metacommunity terms actually unifies several seemingly disparate concepts central to invasion biology. Finally, we recommend several courses of action for the control and management of invasive species that emerge from applying the concepts of metacommunity theory.

Assessing metacommunity processes through signatures in spatiotemporal turnover of community composition

Although metacommunity ecology has been a major field of research in the last decades, with both conceptual and empirical outputs, the analysis of the temporal dynamics of metacommunities has only emerged recently and consists mostly of repeated static analyses. Here we propose a novel analytical framework to assess metacommunity processes using path analyses of spatial and temporal diversity turnovers. We detail the principles and practical aspects of this framework and apply it to simulated datasets to illustrate its ability to decipher the respective contributions of entangled drivers of metacommunity dynamics. We then apply it to four empirical datasets. Empirical results support the view that metacommunity dynamics may be generally shaped by multiple ecological processes acting in concert, with environmental filtering being variable across both space and time. These results reinforce our call to go beyond static analyses of metacommunities that are blind to the temporal part of environmental variability.

Influence of Environmental Drivers and Potential Interactions on the Distribution of Microbial Communities From Three Permanently Stratified Antarctic Lakes

The McMurdo Dry Valley (MDV) lakes represent unique habitats in the microbial world. Perennial ice covers protect liquid water columns from either significant allochthonous inputs or seasonal mixing, resulting in centuries of stable biogeochemistry. Extreme environmental conditions including low seasonal photosynthetically active radiation (PAR), near freezing temperatures, and oligotrophy have precluded higher trophic levels from the food webs. Despite these limitations, diverse microbial life flourishes in the stratified water columns, including Archaea, bacteria, fungi, protists, and viruses. While a few recent studies have applied next generation sequencing, a thorough understanding of the MDV lake microbial diversity and community structure is currently lacking. Here we used Illumina MiSeq sequencing of the 16S and 18S rRNA genes combined with a microscopic survey of key eukaryotes to compare the community structure and potential interactions among the bacterial and eukaryal communities within the water columns of Lakes Bonney (east and west lobes, ELB, and WLB, respectively) and Fryxell (FRX). Communities were distinct between the upper, oxic layers and the dark, anoxic waters, particularly among the bacterial communities residing in WLB and FRX. Both eukaryal and bacterial community structure was influenced by different biogeochemical parameters in the oxic and anoxic zones. Bacteria formed complex interaction networks which were lake-specific. Several eukaryotes exhibit potential interactions with bacteria in ELB and WLB, while interactions between these groups in the more productive FRX were relatively rare.

Univariate Community Assembly Analysis (UniCAA): Combining hierarchical models with null models to test the influence of spatially restricted dispersal, environmental filtering, and stochasticity on community assembly

Identifying the influence of stochastic processes and of deterministic processes, such as dispersal of individuals of different species and trait-based environmental filtering, has long been a challenge in studies of community assembly. Here, we present the Univariate Community Assembly Analysis (UniCAA) and test its ability to address three hypotheses: species occurrences within communities are (a) limited by spatially restricted dispersal; (b) environmentally filtered; or (c) the outcome of stochasticity-so that as community size decreases-species that are common outside a local community have a disproportionately higher probability of occurrence than rare species. The comparison with a null model allows assessing if the influence of each of the three processes differs from what one would expect under a purely stochastic distribution of species. We tested the framework by simulating "empirical" metacommunities under 15 scenarios that differed with respect to the strengths of spatially restricted dispersal (restricted vs. not restricted); habitat isolation (low, intermediate, and high immigration rates); and environmental filtering (strong, intermediate, and no filtering). Through these tests, we found that UniCAA rarely produced false positives for the influence of the three processes, yielding a type-I error rate ≤5%. The type-II error rate, that is, production of false negatives, was also acceptable and within the typical cutoff (20%). We demonstrate that the UniCAA provides a flexible framework for retrieving the processes behind community assembly and propose avenues for future developments of the framework.

Making sense of metacommunities: dispelling the mythology of a metacommunity typology

Metacommunity ecology has rapidly become a dominant framework through which ecologists understand the natural world. Unfortunately, persistent misunderstandings regarding metacommunity theory and the methods for evaluating hypotheses based on the theory are common in the ecological literature. Since its beginnings, four major paradigms-species sorting, mass effects, neutrality, and patch dynamics-have been associated with metacommunity ecology. The Big 4 have been misconstrued to represent the complete set of metacommunity dynamics. As a result, many investigators attempt to evaluate community assembly processes as strictly belonging to one of the Big 4 types, rather than embracing the full scope of metacommunity theory. The Big 4 were never intended to represent the entire spectrum of metacommunity dynamics and were rather examples of historical paradigms that fit within the new framework. We argue that perpetuation of the Big 4 typology hurts community ecology and we encourage researchers to embrace the full inference space of metacommunity theory. A related, but distinct issue is that the technique of variation partitioning is often used to evaluate the dynamics of metacommunities. This methodology has produced its own set of misunderstandings, some of which are directly a product of the Big 4 typology and others which are simply the product of poor study design or statistical artefacts. However, variation partitioning is a potentially powerful technique when used appropriately and we identify several strategies for successful utilization of variation partitioning.