Linking metacommunity paradigms to spatial coexistence mechanisms

The Geography of Metacommunities: Landscape Characteristics Drive Geographic Variation in the Assembly Process through Selecting Species Pool Attributes

AbstractThe nonrandom association between landscape characteristics and the dominant life history strategies observed in species pools is a typical pattern in nature. Here, we argue that these associations determine predictable changes in the relative importance of assembly mechanisms along broadscale geographic gradients (i.e., the geographic context of metacommunity dynamics). To demonstrate that, we employed simulation models in which groups of species with the same initial distribution of niche breadths and dispersal abilities interacted across a wide range of landscapes with contrasting characteristics. By assessing the traits of dominant species in the species pool in each landscape type, we determined how different landscape characteristics select for different life history strategies at the metacommunity level. We analyzed the simulated data using the same analytical approaches used in the study of empirical metacommunities to derive predictions about the causal relationships between landscape characteristics and dominant life histories in species pools, as well as their reciprocal influence on empirical inferences regarding the assembly process. We provide empirical support for these predictions by contrasting the assembly of moth metacommunities in a tropical versus a temperate mountainous landscape. Together, our model framework and empirical analyses demonstrate how the geographic context of metacommunities influences our understanding of community assembly across broadscale ecological gradients.

Effects of dispersal and temperature variability on phytoplankton realized temperature niches

Phytoplankton species exhibit fundamental temperature niches that drive observed species distributions linked to realized temperature niches. A recent analysis of field observations of Prochlorococcus showed that for all ecotypes, the realized niche was, on average, colder and wider than the fundamental niche. Using a simple trait-based metacommunity model that resolves fundamental temperature niches for a range of competing phytoplankton, we ask how dispersal and local temperature variability influence species distributions and diversity, and whether these processes help explain the observed discrepancies between fundamental and realized niches for Prochlorococcus. We find that, independently, both dispersal and temperature variability increase realized temperature niche widths and local diversity. The combined effects result in high diversity and realized temperature niches that are consistently wider than fundamental temperature niches. These results have broad implications for understanding the drivers of phytoplankton biogeography as well as for refining species distribution models used to project how climate change impacts phytoplankton distributions.

Habitat Heterogeneity, Environmental Feedbacks, and Species Coexistence across Timescales

AbstractClassic ecological theory explains species coexistence in variable environments. While spatial variation is often treated as an intrinsic feature of a landscape, it may be shaped and even generated by the resident community. All species modify their local environment to some extent, driving changes that can feed back to affect the composition and coexistence of the community, potentially over timescales very different from population dynamics. We introduce a simple nested modeling framework for community dynamics in heterogeneous environments, including the possible evolution of heterogeneity over time due to community-environment feedbacks. We use this model to derive analytical conditions for species coexistence in environments where heterogeneity is either fixed or shaped by feedbacks. Among other results, our approach reveals how dispersal and environmental specialization interact to shape realized patterns of habitat association and demonstrates that environmental feedbacks can tune landscape conditions to allow the stable coexistence of any number of species. Our flexible modeling framework helps explain feedback dynamics that arise in a wide range of ecosystems and offers a generic platform for exploring the interplay between species and landscape diversity.

Integrating the flow regime and water quality effects into a niche-based metacommunity dynamics model for river ecosystems

Aquatic community dynamics are closely dominated by flow regime and water quality conditions, which are increasingly threatened by dam regulation, water diversion, and nutrition pollution. However, further understanding of the ecological impacts of flow regime and water quality conditions on aquatic multi-population dynamics has rarely been integrated into existing ecological models. To address this issue, a new niche-based metacommunity dynamics model (MDM) is proposed. The MDM aims to simulate the coevolution processes of multiple populations under changing abiotic environments, pioneeringly applied to the mid-lower Han River, China. The quantile regression method was used for the first time to derive ecological niches and competition coefficients of the MDM, which are demonstrated to be reasonable by comparing them with the empirical evidence. Simulation results show that the Nash efficiency coefficients for fish, zooplankton, zoobenthos, and macrophytes are more than 0.64, while the Pearson correlation coefficients for them are no less than 0.71. Overall, the MDM performs effectively in simulating metacommunity dynamics. For all river stations, the average contributions of biological interaction, flow regime effects, and water quality effects to multi-population dynamics are 64%, 21%, and 15%, respectively, suggesting that the population dynamics are dominated by biological interaction. For upstream stations, the fish population is 8%-22% more responsive to flow regime alteration than other populations, while other populations are 9%-26% more responsive to changes in water quality conditions than fish. For downstream stations, flow regime effects on each population account for less than 1% due to more stable hydrological conditions. The innovative contribution of this study lies in proposing a multi-population model to quantify the effects of flow regime and water quality on aquatic community dynamics by incorporating multiple indicators of water quantity, water quality, and biomass. This work has potential for the ecological restoration of rivers at the ecosystem level. This study also highlights the importance of considering threshold and tipping point issues when analyzing the "water quantity-water quality-aquatic ecology" nexus in future works.

The fitness value of ecological information in a variable world

Information processing is increasingly recognized as a fundamental component of life in variable environments, including the evolved use of environmental cues, biomolecular networks, and social learning. Despite this, ecology lacks a quantitative framework for understanding how population, community, and ecosystem dynamics depend on information processing. Here, we review the rationale and evidence for 'fitness value of information' (FVOI), and synthesize theoretical work in ecology, information theory, and probability behind this general mathematical framework. The FVOI quantifies how species' per capita population growth rates can depend on the use of information in their environment. FVOI is a breakthrough approach to linking information processing and ecological and evolutionary outcomes in a changing environment, addressing longstanding questions about how information mediates the effects of environmental change and species interactions.

Deterministic Assembly Processes Strengthen the Effects of β-Diversity on Community Biomass of Marine Bacterioplankton

The presence of more species in the community of a sampling site (α diversity) typically increases ecosystem functions via nonrandom processes like resource partitioning. When considering multiple communities, we hypothesize that higher compositional difference (β diversity) increases overall functions of these communities. Further, we hypothesize that the β diversity effect is more positive when β diversity is increased by nonrandom assembly processes. To test these hypotheses, we collected bacterioplankton along a transect of 6 sampling sites in the southern East China Sea in 14 cruises. For any pairs of the 6 sites within a cruise, we calculated the Bray-Curtis index to represent β diversity and summed bacterial biomass as a proxy to indicate the overall function of the two communities. We then calculated deviation of observed mean pairwise phylogenetic similarities among species in two communities from random to represent the influences of nonrandom processes. The bacterial β diversity was found to positively affect the summed bacterial biomass; however, the effect varied among cruises. Cross-cruise comparison indicated that the β diversity effect increased with the nonrandom processes selecting for phylogenetically dissimilar species. This study extends biodiversity-ecosystem functioning research to the scale of multiple sites and enriches the framework by considering community assembly processes. IMPORTANCE The implications of our analyses are twofold. First, we emphasize the importance of studying β diversity. We expanded the current biodiversity-ecosystem functioning framework from single to multiple sampling sites and investigated the influences of species compositional differences among sites on the overall functioning of these sites. Since natural ecological communities never exist alone, our analyses allow us to more holistically perceive the role of biodiversity in natural ecosystems. Second, we took community assembly processes into account to attain a more mechanistic understanding of the impacts of biodiversity on ecosystem functioning.

Multispecies coexistence in fragmented landscapes

Spatial dynamics have long been recognized as an important driver of biodiversity. However, our understanding of species' coexistence under realistic landscape configurations has been limited by lack of adequate analytical tools. To fill this gap, we develop a spatially explicit metacommunity model of multiple competing species and derive analytical criteria for their coexistence in fragmented heterogeneous landscapes. Specifically, we propose measures of niche and fitness differences for metacommunities, which clarify how spatial dynamics and habitat configuration interact with local competition to determine coexistence of species. We parameterize our model with a Bayesian approach using a 36-y time-series dataset of three Daphnia species in a rockpool metacommunity covering >500 patches. Our results illustrate the emergence of interspecific variation in extinction and recolonization processes, including their dependencies on habitat size and environmental temperature. We find that such interspecific variation contributes to the coexistence of Daphnia species by reducing fitness differences and increasing niche differences. Additionally, our parameterized model allows separating the effects of habitat destruction and temperature change on species extinction. By integrating coexistence theory and metacommunity theory, our study provides platforms to increase our understanding of species' coexistence in fragmented heterogeneous landscapes and the response of biodiversity to environmental changes.

Quantifying mechanisms of coexistence in disease ecology

Pathogen coexistence depends on ecological processes operating at both within and between-host scales, making it difficult to quantify which processes may promote or prevent coexistence. Here, we propose that adapting modern coexistence theory-traditionally applied in plant communities-to pathogen systems provides an exciting approach for examining mechanisms of coexistence operating across different spatial scales. We first overview modern coexistence theory and its mechanistic decomposition; we subsequently adapt the framework to quantify how spatial variation in pathogen density, host resources and immunity, and their interaction may promote pathogen coexistence. We apply this derivation to an example two pathogen, multi-scale model comparing two scenarios with generalist and strain-specific immunity: one with demographic equivalency among pathogens and one with demographic trade-offs among pathogens. We then show how host-pathogen feedbacks generate spatial heterogeneity that promote pathogen coexistence and decompose those mechanisms to quantify how each spatial heterogeneity contributes to that coexistence. Specifically, coexistence of demographically equivalent pathogens occurs due to spatial variation in host resources, immune responses, and pathogen aggregation. With a competition-colonization trade-off, the superior colonizer requires spatial heterogeneity to coexist, whereas the superior competitor does not. Finally, we suggest ways forward for linking theory and empirical tests of coexistence in disease systems.

Disentangling key species interactions in diverse and heterogeneous communities: A Bayesian sparse modelling approach

Modelling species interactions in diverse communities traditionally requires a prohibitively large number of species‐interaction coefficients, especially when considering environmental dependence of parameters. We implemented Bayesian variable selection via sparsity‐inducing priors on non‐linear species abundance models to determine which species interactions should be retained and which can be represented as an average heterospecific interaction term, reducing the number of model parameters. We evaluated model performance using simulated communities, computing out‐of‐sample predictive accuracy and parameter recovery across different input sample sizes. We applied our method to a diverse empirical community, allowing us to disentangle the direct role of environmental gradients on species’ intrinsic growth rates from indirect effects via competitive interactions. We also identified a few neighbouring species from the diverse community that had non‐generic interactions with our focal species. This sparse modelling approach facilitates exploration of species interactions in diverse communities while maintaining a manageable number of parameters.

Seed banks can help to maintain the diversity of interacting phytoplankton species

Seed formation is part of the reproductive cycle, leading to the accumulation of resistance stages that can withstand harsh environmental conditions for long periods of time. At the community level, multiple species with such long-lasting life stages can be more likely to coexist. While the implications of this process for biodiversity have been studied in terrestrial plants, seed banks are usually neglected in phytoplankton multispecies dynamic models, in spite of widespread empirical evidence for such seed banks. In this study, we build a metacommunity model of interacting phytoplankton species, including a resting stage supplying the seed bank. The model is parameterized with empirically-driven growth rate functions and field-based interaction estimates, which include both facilitative and competitive interactions. Exchanges between compartments (coastal pelagic cells, coastal resting cells on the seabed, and open ocean pelagic cells) are controlled by hydrodynamical parameters to which the sensitivity of the model is assessed. We consider two models, i.e., with and without a saturating effect of the interactions on the growth rates. Our results are consistent between models, and show that a seed bank allows to maintain all species in the community over 30 years. Indeed, a fraction of the species are vulnerable to extinction at specific times within the year, but this process is buffered by their survival in their resting stage. We thus highlight the potential role of the seed bank in the recurrent re-invasion of the coastal community, and of coastal environments in re-seeding oceanic regions. Moreover, the seed bank enables populations to tolerate stronger interactions within the community as well as more severe changes in the environment, such as those predicted within a climate change context. Our study therefore shows how a resting stage may help phytoplanktonic diversity maintenance.

Seed banks alter metacommunity diversity: The interactive effects of competition, dispersal and dormancy

Dispersal and dormancy are two common strategies allowing for species persistence and the maintenance of biodiversity in variable environments. However, theory and empirical tests of spatial diversity patterns tend to examine either mechanism in isolation. Here, we developed a stochastic, spatially explicit metacommunity model incorporating seed banks with varying germination and survival rates. We found that dormancy and dispersal had interactive, nonlinear effects on the maintenance and distribution of metacommunity diversity. Seed banks promoted local diversity when seed survival was high and maintained regional diversity through interactions with dispersal. The benefits of seed banks for regional diversity were largest when dispersal was high or intermediate, depending on whether local competition was equal or stabilising. Our study shows that classic predictions for how dispersal affects metacommunity diversity can be strongly influenced by dormancy. Together, these results emphasise the need to consider both temporal and spatial processes when predicting multi-scale patterns of diversity.

The spatial synchrony of species richness and its relationship to ecosystem stability

Synchrony is broadly important to population and community dynamics due to its ubiquity and implications for extinction dynamics, system stability, and species diversity. Investigations of synchrony in community ecology have tended to focus on covariance in the abundances of multiple species in a single location. Yet, the importance of regional environmental variation and spatial processes in community dynamics suggests that community properties, such as species richness, could fluctuate synchronously across patches in a metacommunity, in an analog of population spatial synchrony. Here, we test the prevalence of this phenomenon and the conditions under which it may occur using theoretical simulations and empirical data from 20 marine and terrestrial metacommunities. Additionally, given the importance of biodiversity for stability of ecosystem function, we posit that spatial synchrony in species richness is strongly related to stability. Our findings show that metacommunities often exhibit spatial synchrony in species richness. We also found that richness synchrony can be driven by environmental stochasticity and dispersal, two mechanisms of population spatial synchrony. Richness synchrony also depended on community structure, including species evenness and beta diversity. Strikingly, ecosystem stability was more strongly related to richness synchrony than to species richness itself, likely because richness synchrony integrates information about community processes and environmental forcing. Our study highlights a new approach for studying spatiotemporal community dynamics and emphasizes the spatial dimensions of community dynamics and stability.

The effect of colonization dynamics in competition for space in metacommunities

One of the main factors that determines habitat suitability for sessile and territorial organisms is the presence or absence of another competing individual in that habitat. This type of competition arises in populations occupying patches in a metacommunity. Previous studies have looked at this process using a continuous-time modeling framework, where colonizations and extinctions occur simultaneously. However, different colonization processes may be performed by different species, which may affect the metacommunity dynamics. We address this issue by developing a discrete-time framework that describes these kinds of metacommunity interactions, and we consider different colonization dynamics. To understand potential dynamics, we consider specific functional forms that characterize the colonization and extinction processes of metapopulations competing for space as their limiting factor. We then provide a mathematical analysis of the models generated by this framework, and we compare these results to what is seen in nature and in previous models.

Climate-driven range shifts reduce persistence of competitors in a perennial plant community

Forecasting the impacts of climate change on species persistence in diverse natural communities requires a way to account for indirect effects mediated through species interactions. In particular, we expect species to experience major changes in competition as they track favorable climates. Here, we combine experimental data with a recently developed theoretical framework based on coexistence theory to measure the impact of climate-driven range shifts on alpine plant persistence under climate change. We transplanted three co-dominant alpine perennial species to five elevations, creating a maximum of 5°C increase in average growing-season temperature. We statistically modeled species' demographic rates in response to the environment and interpolated species' intrinsic ranges-the environmental mapping of reproduction in the absence of competition. We used low-density population growth rates-species' initial rate of invasion into an established community-as a metric of persistence. Further analysis of low-density growth rates (LGRs) allowed us to parse the direct impacts of climate change from indirect impacts mediated by shifting competition. Our models predict qualitatively different range shifts for each species based on the climate conditions under which growth rates are maximized and where they are zero. Overall, climate change is predicted to increase the intrinsic (competition free) growth rates of all species, as warmer and wetter conditions increase the favorability of alpine habitat. However, these benefits are entirely negated by increased competition arising from greater overlap between competitors in their intrinsic ranges. Species were highly dispersal limited, which can prevent species from tracking shifting intrinsic ranges by reducing population spread rates. Yet dispersal limitation also promoted species' persistence because it promotes persistence mechanisms. Our study demonstrates the complex pathways by which climate change impacts species' persistence by altering their competitive environment, and highlights how a persistence framework based on LGRs can help disentangle impacts.

A process-based metacommunity framework linking local and regional scale community ecology

The metacommunity concept has the potential to integrate local and regional dynamics within a general community ecology framework. To this end, the concept must move beyond the discrete archetypes that have largely defined it (e.g. neutral vs. species sorting) and better incorporate local scale species interactions and coexistence mechanisms. Here, we present a fundamental reconception of the framework that explicitly links local coexistence theory to the spatial processes inherent to metacommunity theory, allowing for a continuous range of competitive community dynamics. These dynamics emerge from the three underlying processes that shape ecological communities: (1) density-independent responses to abiotic conditions, (2) density-dependent biotic interactions and (3) dispersal. Stochasticity is incorporated in the demographic realisation of each of these processes. We formalise this framework using a simulation model that explores a wide range of competitive metacommunity dynamics by varying the strength of the underlying processes. Using this model and framework, we show how existing theories, including the traditional metacommunity archetypes, are linked by this common set of processes. We then use the model to generate new hypotheses about how the three processes combine to interactively shape diversity, functioning and stability within metacommunities.

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.

Movement-mediated community assembly and coexistence

Organismal movement is ubiquitous and facilitates important ecological mechanisms that drive community and metacommunity composition and hence biodiversity. In most existing ecological theories and models in biodiversity research, movement is represented simplistically, ignoring the behavioural basis of movement and consequently the variation in behaviour at species and individual levels. However, as human endeavours modify climate and land use, the behavioural processes of organisms in response to these changes, including movement, become critical to understanding the resulting biodiversity loss. Here, we draw together research from different subdisciplines in ecology to understand the impact of individual-level movement processes on community-level patterns in species composition and coexistence. We join the movement ecology framework with the key concepts from metacommunity theory, community assembly and modern coexistence theory using the idea of micro-macro links, where various aspects of emergent movement behaviour scale up to local and regional patterns in species mobility and mobile-link-generated patterns in abiotic and biotic environmental conditions. These in turn influence both individual movement and, at ecological timescales, mechanisms such as dispersal limitation, environmental filtering, and niche partitioning. We conclude by highlighting challenges to and promising future avenues for data generation, data analysis and complementary modelling approaches and provide a brief outlook on how a new behaviour-based view on movement becomes important in understanding the responses of communities under ongoing environmental change.

Quantifying the relative importance of variation in predation and the environment for species coexistence

Coexistence and food web theory are two cornerstones of the long-standing effort to understand how species coexist. Although competition and predation are known to act simultaneously in communities, theory and empirical study of these processes continue to be developed largely independently. Here, we integrate modern coexistence theory and food web theory to simultaneously quantify the relative importance of predation and environmental fluctuations for species coexistence. We first examine coexistence in a theoretical, multitrophic model, adding complexity to the food web using machine learning approaches. We then apply our framework to a stochastic model of the rocky intertidal food web, partitioning empirical coexistence dynamics. We find the main effects of both environmental fluctuations and variation in predator abundances contribute substantially to species coexistence. Unexpectedly, their interaction tends to destabilise coexistence, leading to new insights about the role of bottom-up vs. top-down forces in both theory and the rocky intertidal ecosystem.

Integrating the underlying structure of stochasticity into community ecology

Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics.

Habitat heterogeneity mediates effects of individual variation on spatial species coexistence

Numerous studies have documented the importance of individual variation (IV) in determining the outcome of competition between species. However, little is known about how the interplay between IV and habitat heterogeneity (i.e. variation and spatial autocorrelation in habitat quality) affects species coexistence at the landscape scale. Here, we incorporate habitat heterogeneity into a competition model with IV, in order to explore the mechanism of spatial species coexistence. We find that individual-level variation and habitat heterogeneity interact to promote species coexistence, more obviously at lower dispersal rates. This is in stark contrast to early non-spatial models, which predicted that IV reinforces competitive hierarchies and therefore speeds up species exclusion. In essence, increasing variation in patch quality and/or spatial habitat autocorrelation moderates differences in the competitive ability of species, thereby allowing species to coexist both locally and globally. Overall, our theoretical study offers a mechanistic explanation for emerging empirical evidence that both habitat heterogeneity and IV promote species coexistence and therefore biodiversity maintenance.

Spatial ecology of territorial populations

Many ecosystems, from vegetation to biofilms, are composed of territorial populations that compete for both nutrients and physical space. What are the implications of such spatial organization for biodiversity? To address this question, we developed and analyzed a model of territorial resource competition. In the model, all species obey trade-offs inspired by biophysical constraints on metabolism; the species occupy nonoverlapping territories, while nutrients diffuse in space. We find that the nutrient diffusion time is an important control parameter for both biodiversity and the timescale of population dynamics. Interestingly, fast nutrient diffusion allows the populations of some species to fluctuate to zero, leading to extinctions. Moreover, territorial competition spontaneously gives rise to both multistability and the Allee effect (in which a minimum population is required for survival), so that small perturbations can have major ecological effects. While the assumption of trade-offs allows for the coexistence of more species than the number of nutrients-thus violating the principle of competitive exclusion-overall biodiversity is curbed by the domination of "oligotroph" species. Importantly, in contrast to well-mixed models, spatial structure renders diversity robust to inequalities in metabolic trade-offs. Our results suggest that territorial ecosystems can display high biodiversity and rich dynamics simply due to competition for resources in a spatial community.

Rainfall variability maintains grass-forb species coexistence

Environmental variability can structure species coexistence by enhancing niche partitioning. Modern coexistence theory highlights two fluctuation-dependent temporal coexistence mechanisms -the storage effect and relative nonlinearity - but empirical tests are rare. Here, we experimentally test if environmental fluctuations enhance coexistence in a California annual grassland. We manipulate rainfall timing and relative densities of the grass Avena barbata and forb Erodium botrys, parameterise a demographic model, and partition coexistence mechanisms. Rainfall variability was integral to grass-forb coexistence. Variability enhanced growth rates of both species, and early-season drought was essential for Erodium persistence. While theoretical developments have focused on the storage effect, it was not critical for coexistence. In comparison, relative nonlinearity strongly stabilised coexistence, where Erodium experienced disproportionately high growth under early-season drought due to competitive release from Avena. Our results underscore the importance of environmental variability and suggest that relative nonlinearity is a critical if underappreciated coexistence mechanism.

The spatial scales of species coexistence

Understanding how species diversity is maintained is a foundational problem in ecology and an essential requirement for the discipline to be effective as an applied science. Ecologists' understanding of this problem has rapidly matured, but this has exposed profound uncertainty about the spatial scales required to maintain species diversity. Here we define and develop this frontier by proposing the coexistence-area relationship-a real relationship in nature that can be used to understand the determinants of the scale-dependence of diversity maintenance. The coexistence-area relationship motivates new empirical techniques for addressing important, unresolved problems about the influence of demographic stochasticity, environmental heterogeneity and dispersal on scale-dependent patterns of diversity. In so doing, this framework substantially reframes current approaches to spatial community ecology. Quantifying the spatial scales of species coexistence will permit the next important advance in our understanding of the maintenance of diversity in nature, and should improve the contribution of community ecology to biodiversity conservation.

Recent advances in metacommunities and meta-ecosystem theories

Metacommunity theory has provided many insights into the general problem of local versus regional control of species diversity and relative abundance. The metacommunity framework has been extended from competitive interactions to whole food webs that can be described as spatial networks of interaction networks. Trophic metacommunity theory greatly contributed to resolving the community complexity-stability debate by predicting its dependence on the regional spatial context. The meta-ecosystem framework has since been suggested as a useful simplification of complex ecosystems to apply this spatial context to spatial flows of both individuals and matter. Reviewing the recent literature on metacommunity and meta-ecosystem theories suggests the importance of unifying theories of interaction strength into a meta-ecosystem framework that captures how the strength of spatial, species, and ecosystem fluxes are distributed across location and trophic levels. Such integration predicts important feedback between local and regional processes that drive the assembly of species, the stability of community, and the emergence of ecosystem functions, from limited spatial fluxes of individuals and (in)organic matter. These predictions are often mediated by the maintenance of environmental or endogenous fluctuations from local to regional scales that create important challenges and opportunities for the validation of metacommunity and meta-ecosystem theories and their application to conservation.

Estimating partial regulation in spatiotemporal models of community dynamics

Niche-based approaches to community analysis often involve estimating a matrix of pairwise interactions among species (the "community matrix"), but this task becomes infeasible using observational data as the number of modeled species increases. As an alternative, neutral theories achieve parsimony by assuming that species within a trophic level are exchangeable, but generally cannot incorporate stabilizing interactions even when they are evident in field data. Finally, both regulated (niche) and unregulated (neutral) approaches have rarely been fitted directly to survey data using spatiotemporal statistical methods. We therefore propose a spatiotemporal and model-based approach to estimate community dynamics that are partially regulated. Specifically, we start with a neutral spatiotemporal model where all species follow ecological drift, which precludes estimating pairwise interactions. We then add regulatory relations until model selection favors stopping, where the "rank" of the interaction matrix may range from zero to the number of species. A simulation experiment shows that model selection can accurately identify the rank of the interaction matrix, and that the identified spatiotemporal model can estimate the magnitude of species interactions. A 40-yr case study for the Gulf of St. Lawrence marine community shows that recovering grey seals have an unregulated and negative relationship with demersal fishes. We therefore conclude that partial regulation is a plausible approximation to community dynamics using field data and hypothesize that estimating partial regulation will be expedient in future analyses of spatiotemporal community dynamics given limited field data. We conclude by recommending ongoing research to add explicit models for movement, so that meta-community theory can be confronted with data in a spatiotemporal statistical framework.