Long-term climate and hydrologic regimes shape stream invertebrate community responses to a hurricane disturbance

Disturbances can produce a spectrum of short- and long-term ecological consequences that depend on complex interactions of the characteristics of the event, antecedent environmental conditions, and the intrinsic properties of resistance and resilience of the affected biological system. We used Hurricane Harvey's impact on coastal rivers of Texas to examine the roles of storm-related changes in hydrology and long-term precipitation regime on the response of stream invertebrate communities to hurricane disturbance. We detected declines in richness, diversity and total abundance following the storm, but responses were strongly tied to direct and indirect effects of long-term aridity and short-term changes in stream hydrology. The amount of rainfall a site received drove both flood duration and flood magnitude across sites, but lower annual rainfall amounts (i.e. aridity) increased flood magnitude and decreased flood duration. Across all sites, flood duration was positively related to the time it took for invertebrate communities to return to a long-term baseline and flood magnitude drove larger invertebrate community responses (i.e. changes in diversity and total abundance). However, invertebrate response per unit flood magnitude was lower in sub-humid sites, potentially because of differences in refuge availability or ecological-evolutionary interactions. Interestingly, sub-humid streams had temporary large peaks in invertebrate total abundance and diversity following recovery period that may be indicative of the larger organic matter pulses expected in these systems because of their comparatively well-developed riparian vegetation. Our findings show that hydrology and long-term precipitation regime predictably affected invertebrate community responses and, thus, our work underscores the important influence of local climate to ecosystem sensitivity to disturbances.

Gut-associated functions are favored during microbiome assembly across a major part of C. elegans life

The microbiome expresses a variety of functions that influence host biology. The range of functions depends on the microbiome's composition, which can change during the host's lifetime due to neutral assembly processes, host-mediated selection, and environmental conditions. To date, the exact dynamics of microbiome assembly, the underlying determinants, and the effects on host-associated functions remain poorly understood. Here, we used the nematode Caenorhabditis elegans and a defined community of fully sequenced, naturally associated bacteria to study microbiome dynamics and functions across a major part of the worm's lifetime of hosts under controlled experimental conditions. Bacterial community composition initially shows strongly declining levels of stochasticity, which increases during later time points, suggesting selective effects in younger animals as opposed to more random processes in older animals. The adult microbiome is enriched in genera Ochrobactrum and Enterobacter compared to the direct substrate and a host-free control environment. Using pathway analysis, metabolic, and ecological modeling, we further find that the lifetime assembly dynamics increase competitive strategies and gut-associated functions in the host-associated microbiome, indicating that the colonizing bacteria benefit the worm. Overall, our study introduces a framework for studying microbiome assembly dynamics based on stochastic, ecological, and metabolic models, yielding new insights into the processes that determine host-associated microbiome composition and function.

IMPORTANCE

The microbiome plays a crucial role in host biology. Its functions depend on the microbiome composition that can change during a host's lifetime. To date, the dynamics of microbiome assembly and the resulting functions still need to be better understood. This study introduces a new approach to characterize the functional consequences of microbiome assembly by modeling both the relevance of stochastic processes and metabolic characteristics of microbial community changes. The approach was applied to experimental time-series data obtained for the microbiome of the nematode Caenorhabditis elegans across the major part of its lifetime. Stochastic processes played a minor role, whereas beneficial bacteria as well as gut-associated functions enriched in hosts. This indicates that the host might actively shape the composition of its microbiome. Overall, this study provides a framework for studying microbiome assembly dynamics and yields new insights into C. elegans microbiome functions.

High response diversity and conspecific density-dependence, not species interactions, drive dynamics of coral reef fish communities

Species-to-species and species-to-environment interactions are key drivers of community dynamics. Disentangling these drivers in species-rich assemblages is challenging due to the high number of potentially interacting species (the 'curse of dimensionality'). We develop a process-based model that quantifies how intraspecific and interspecific interactions, and species' covarying responses to environmental fluctuations, jointly drive community dynamics. We fit the model to reef fish abundance time series from 41 reefs of Australia's Great Barrier Reef. We found that fluctuating relative abundances are driven by species' heterogenous responses to environmental fluctuations, whereas interspecific interactions are negligible. Species differences in long-term average abundances are driven by interspecific variation in the magnitudes of both conspecific density-dependence and density-independent growth rates. This study introduces a novel approach to overcoming the curse of dimensionality, which reveals highly individualistic dynamics in coral reef fish communities that imply a high level of niche structure.

More than the sum of its parts: uncovering emerging effects of microbial interactions in complex communities

Microbial communities are not only shaped by the diversity of microorganisms and their individual metabolic potential, but also by the vast amount of intra- and interspecies interactions that can occur pairwise interactions among microorganisms, we suggest that more attention should be drawn towards the effects on the entire microbiome that emerge from individual interactions between community members. The production of certain metabolites that can be tied to a specific microbe-microbe interaction might subsequently influence the physicochemical parameters of the habitat, stimulate a change in the trophic network of the community or create new micro-habitats through the formation of biofilms, similar to the production of antimicrobial substances which might negatively affect only one microorganism but cause a ripple effect on the abundance of other community members. Here, we argue that combining established as well as innovative laboratory and computational methods is needed to predict novel interactions and assess their secondary effects. Such efforts will enable future microbiome studies to expand our knowledge on the dynamics of complex microbial communities.

A test of the loose-equilibrium concept with long-lived organisms: Evaluating temporal change in freshwater mussel assemblages

The loose-equilibrium concept (LEC) predicts that ecological assemblages change transiently but return towards an earlier or average structure. The LEC framework can help determine whether assemblages vary within expected ranges or are permanently altered following environmental change. Long-lived, slow-growing animals typically respond slowly to environmental change, and their assemblage dynamics may respond over decades, which transcends most ecological studies. Unionid mussels are valuable for studying dynamics of long-lived animals because they can live >50 years and occur in dense, species-rich assemblages (mussel beds). Mussel beds can persist for decades, but disturbance can affect species differently, resulting in variable trajectories according to differences in species composition within and among rivers. We used long-term data sets (10-40 years) from seven rivers in the eastern United States to evaluate the magnitude, pace and directionality of mussel assemblage change within the context of the LEC. Site trajectories varied within and among streams and showed patterns consistent with either the LEC or directional change. In streams that conformed to the LEC, rank abundance of dominant species remained stable over time, but directional change in other streams was driven by changes in the rank abundance and composition of dominant species. Characteristics of mussel assemblage change varied widely, ranging from those conforming to the LEC to those showing strong directional change. Conservation approaches that attempt to maintain or create a desired assemblage condition should acknowledge this wide range of possible assemblage trajectories and that the environmental factors that influence those changes remain poorly understood.

Structured community transitions explain the switching capacity of microbial systems

Microbial systems appear to exhibit a relatively high switching capacity of moving back and forth among few dominant communities (taxon memberships). While this switching behavior has been mainly attributed to random environmental factors, it remains unclear the extent to which internal community dynamics affect the switching capacity of microbial systems. Here, we integrate ecological theory and empirical data to demonstrate that structured community transitions increase the dependency of future communities on the current taxon membership, enhancing the switching capacity of microbial systems. Following a structuralist approach, we propose that each community is feasible within a unique domain in environmental parameter space. Then, structured transitions between any two communities can happen with probability proportional to the size of their feasibility domains and inversely proportional to their distance in environmental parameter space-which can be treated as a special case of the gravity model. We detect two broad classes of systems with structured transitions: one class where switching capacity is high across a wide range of community sizes and another class where switching capacity is high only inside a narrow size range. We corroborate our theory using temporal data of gut and oral microbiota (belonging to class 1) as well as vaginal and ocean microbiota (belonging to class 2). These results reveal that the topology of feasibility domains in environmental parameter space is a relevant property to understand the changing behavior of microbial systems. This knowledge can be potentially used to understand the relevant community size at which internal dynamics can be operating in microbial systems.

Time for a paradigm shift? Small carnivores' sensitivity highlights the importance of monitoring mid-rank predators in future global change studies

Research Highlight: Jachowski, D. S., Marneweck, C. J., Olfenbuttel, C., & Harris, S. N. (2024). Support for the size-mediated sensitivity hypothesis within a diverse carnivore community. Journal of Animal Ecology, https://doi.org/10.1111/1365-2656.13916. A current paradigm in ecological research suggests that top predators are suitable sentinel species to identify ecosystem dysfunctions and monitor the effects of climate change. However, the adequacy of top predators to systematically take this function may be mistakenly inferred or unintentionally conflated from the fact that these species are regarded as biodiversity indicators or keystone, umbrella and flagship species in most ecosystems. Regarding terrestrial mammalian carnivores (order Carnivora), some researchers recently suggested that the smaller species likely possess a higher sensitivity to environmental changes than large carnivores because of their biological attributes and their intermediate position in food webs. To test this hypothesis, Jachowski et al. (2024) used camera trapping followed by occupancy and structural equation modelling to explore the dynamics of a diverse carnivore community and the factors that influence them. Their results confirmed that small carnivores are more sensitive to habitat changes and are interconnected by a greater number of significant pathways compared with larger carnivores. This support for the size-mediated sensitivity hypothesis strengthens the proposition that small carnivores (and other mid-rank predators) are ideal sentinel species for monitoring the effects of the wide range of contemporary and future environmental changes. Time will tell whether this new 'middle-out ecology' paradigm will be considered in future global change studies.

Behavioral interactions are modulated by facilitation along a heterotrophic succession

Competition and facilitation drive ecological succession but are often hard to quantify. In this sense, behavioral data may be a key tool to analyze interaction networks, providing insights into temporal trends in facilitation and competition processes within animal heterotrophic succession. Here, we perform the first in-depth analysis of the factors driving temporal dynamics of carcass consumption by analyzing behavioral patterns (i.e., interactions) and community dynamics metrics (i.e., species richness, abundance, turnover, and diversity) in a Neotropical scavenger guild. For this purpose, we monitored goat carcasses using automatic cameras. From 573 reviewed videos, we registered 1784 intraspecific and 624 interspecific interactions, using intraspecific and interspecific aggressions (n = 2048) as a behavioral proxy of competition intensity. Our results show that resource availability shapes behavioral interactions between vultures, with a specific effect of the different species on behavioral and competition dynamics, showing the existence of a hierarchy between species. Furthermore, behavioral processes linked to carcass opening tended to be facilitative, related to moments of higher tolerance (i.e., lower aggressiveness), thus reducing competition intensity and also affecting community structure and dynamics. This novel framework demonstrates complex ephemeral successional processes characterized by a fluctuation in facilitation and competition intensity during the consumption of an unpredictable resource linked to key ecosystem processes.

Functional traits shape plant-plant interactions and recruitment in a hotspot of woody plant diversity

Understanding and predicting recruitment in species-rich plant communities requires identifying functional determinants of both density-independent performance and interactions. In a common-garden field experiment with 25 species of the woody plant genus Protea, we varied the initial spatial and taxonomic arrangement of seedlings and followed their survival and growth during recruitment. Neighbourhood models quantified how six key functional traits affect density-independent performance, interaction effects and responses. Trait-based neighbourhood models accurately predicted individual survival and growth from the initial spatial and functional composition of species-rich experimental communities. Functional variation among species caused substantial variation in density-independent survival and growth that was not correlated with interaction effects and responses. Interactions were spatially restricted but had important, predominantly competitive, effects on recruitment. Traits increasing the acquisition of limiting resources (water for survival and soil P for growth) mediated trade-offs between interaction effects and responses. Moreover, resprouting species had higher survival but reduced growth, likely reinforcing the survival-growth trade-off in adult plants. Resource acquisition of juvenile plants shapes Protea community dynamics with acquisitive species with strong competitive effects suffering more from competition. Together with functional determinants of density-independent performance, this makes recruitment remarkably predictable, which is critical for efficient restoration and near-term ecological forecasts of species-rich communities.

Assessing the sensitivity and resistance of communities in a changing environment

We propose that the ecological resilience of communities to permanent changes of the environment can be based on how variation in the overall abundance of individuals affects the number of species. Community sensitivity is defined as the ratio between the rate of change in the log expected number of species and the rate of change in the log expected number of individuals in the community. High community sensitivity means that small changes in the total abundance strongly impact the number of species. Community resistance is the proportional reduction in expected number of individuals that the community can sustain before expecting to lose one species. A small value of community resistance means that the community can only endure a small reduction in abundance before it is expected to lose one species. Based on long-term studies of four bird communities in European deciduous forests at different latitudes large differences were found in the resilience to environmental perturbations. Estimating the variance components of the species abundance distribution revealed how different processes contributed to the community sensitivity and resistance. Species heterogeneity in the population dynamics was the largest component, but its proportion varied among communities. Species-specific response to environmental fluctuations was the second major component of the variation in abundance. Estimates of community sensitivity and resistance based on data only from a single year were in general larger than those based on estimates from longer time series. Thus, our approach can provide rapid and conservative assessment of the resilience of communities to environmental changes also including only short-term data. This study shows that a general ecological mechanism, caused by increased strength of density dependence due to reduction in resource availability, can provide an intuitive measure of community resilience to environmental variation. Our analyses also illustrate the importance of including specific assumptions about how different processes affect community dynamics. For example, if stochastic fluctuations in the environment affect all species in a similar way, the sensitivity and resistance of the community to environmental changes will be different from communities in which all species show independent responses.

The active free-living bathypelagic microbiome is largely dominated by rare surface taxa

A persistent microbial seed bank is postulated to sustain the marine biosphere, and recent findings show that prokaryotic taxa present in the ocean's surface dominate prokaryotic communities throughout the water column. Yet, environmental conditions exert a tight control on the activity of prokaryotes, and drastic changes in these conditions are known to occur from the surface to deep waters. The simultaneous characterization of the total (DNA) and active (i.e. with potential for protein synthesis, RNA) free-living communities in 13 stations distributed across the tropical and subtropical global ocean allowed us to assess their change in structure and diversity along the water column. We observed that active communities were surprisingly more similar along the vertical gradient than total communities. Looking at the vertical connectivity of the active vs. the total communities, we found that taxa detected in the surface sometimes accounted for more than 75% of the active microbiome of bathypelagic waters (50% on average). These active taxa were generally rare in the surface, representing a small fraction of all the surface taxa. Our findings show that the drastic vertical change in environmental conditions leads to the inactivation and disappearance of a large proportion of surface taxa, but some surface-rare taxa remain active (or with potential for protein synthesis) and dominate the bathypelagic active microbiome.

Increased dispersal explains increasing local diversity with global biodiversity declines

The narrative of biodiversity decline in response to human impacts is overly simplistic because different aspects of biodiversity show different trajectories at different spatial scales. It is also debated whether human-caused biodiversity changes lead to subsequent, accelerating change (cascades) in ecological communities, or alternatively build increasingly robust community networks with decreasing extinction rates and reduced invasibility. Mechanistic approaches are needed that simultaneously reconcile different aspects of biodiversity change, and explore the robustness of communities to further change. We develop a trophically structured, mainland-archipelago metacommunity model of community assembly. Varying the parameters across model simulations shows that local alpha diversity (the number of species per island) and regional gamma diversity (the total number of species in the archipelago) depend on both the rate of extirpation per island and on the rate of dispersal between islands within the archipelago. In particular, local diversity increases with increased dispersal and heterogeneity between islands, but regional diversity declines because the islands become biotically similar and local one-island and few-island species are excluded (homogenisation, or reduced beta diversity). This mirrors changes observed empirically: real islands have gained species (increased local and island-scale community diversity) with increased human-assisted transfers of species, but global diversity has declined with the loss of endemic species. However, biological invasions may be self-limiting. High-dispersal, high local-diversity model communities become resistant to subsequent invasions, generating robust species-community networks unless dispersal is extremely high. A mixed-up world is likely to lose many species, but the resulting ecological communities may nonetheless be relatively robust.

Phosphorus Addition Reduces Seedling Growth and Survival for the Arbuscular Mycorrhizal Tree Cinnamomum camphora (Lauraceae) and Ectomycorrhizal Tree Castanopsis sclerophylla (Fagaceae) in Fragmented Forests in Eastern China

Global changes in nutrient deposition rates and habitat fragmentation are likely to have profound effects on plant communities, particularly in the nutrient-limited systems of the tropics and subtropics. However, it remains unclear how increased phosphorus (P) supply affects seedling growth in P-deficient subtropical fragmented forests. To explore this, we applied P to 11 islands in a subtropical Chinese archipelago and examined the results in combination with a contemporary greenhouse experiment to test the influence of P addition on seedling growth and survival. We measured the growth (i.e., base area) and mortality rate of seedlings for one arbuscular mycorrhizal (AM) and one ectomycorrhizal (EcM) tree species separately and calculated their relative growth rate and mortality when compared with P addition and control treatment on each island. We also measured three functional traits and the biomass of seedlings in the greenhouse experiment. Results showed that P addition significantly increased the mortality of AM and EcM seedlings and reduced the growth rate of EcM seedlings. The relative growth rate of AM seedlings, but not EcM seedlings, significantly decreased as the island area decreased, suggesting that P addition could promote the relative growth rate of AM seedlings on larger islands. The greenhouse experiment showed that P addition could reduce the specific root length of AM and EcM seedlings and reduce the aboveground and total biomass of seedlings, indicating that P addition may affect the resource acquisition of seedlings, thereby affecting their survival and growth. Our study reveals the synergistic influence of habitat fragmentation and P deposition, which may affect the regeneration of forest communities and biodiversity maintenance in fragmented habitats.

Solving the stochastic dynamics of population growth

Population growth is a fundamental process in ecology and evolution. The population size dynamics during growth are often described by deterministic equations derived from kinetic models. Here, we simulate several population growth models and compare the size averaged over many stochastic realizations with the deterministic predictions. We show that these deterministic equations are generically bad predictors of the average stochastic population dynamics. Specifically, deterministic predictions overestimate the simulated population sizes, especially those of populations starting with a small number of individuals. Describing population growth as a stochastic birth process, we prove that the discrepancy between deterministic predictions and simulated data is due to unclosed-moment dynamics. In other words, the deterministic approach does not consider the variability of birth times, which is particularly important with small population sizes. We show that some moment-closure approximations describe the growth dynamics better than the deterministic prediction. However, they do not reduce the error satisfactorily and only apply to some population growth models. We explicitly solve the stochastic growth dynamics, and our solution applies to any population growth model. We show that our solution exactly quantifies the dynamics of a community composed of different strains and correctly predicts the fixation probability of a strain in a serial dilution experiment. Our work sets the foundations for a more faithful modeling of community and population dynamics. It will allow the development of new tools for a more accurate analysis of experimental and empirical results, including the inference of important growth parameters.

Microbial composition and diversity of the tobacco leaf phyllosphere during plant development

Phyllosphere-associated microorganisms affect host plant's nutrients availability, its growth and ecological functions. Tobacco leaves provide a wide-area habitat for microbial life. Previous studies have mainly focused on phyllosphere microbiota at one time point of tobacco growth process, but more is unknown about dynamic changes in phyllospheric microbial composition from earlier to the late stage of plant development. In the current study, we had determined the bacterial and fungal communities succession of tobacco growth stages (i.e., seedling, squaring, and maturing) by using both 16S rRNA sequencing for bacterial and ITS sequencing for fungi. Our results demonstrated that among tobacco growth stages, the phyllospheric bacterial communities went through more distinct succession than the fungal communities did. Proteobacteria and Actinobacteria exerted the most influence in tobacco development from seedling to squaring stages. At maturing stage, Proteobacteria and Actinobacteria dominance was gradually replaced by Firmicutes and Bacteroidetes. Network analysis revealed that Proteobacteria, as the core phyllospheric microbia, played essential role in stabilizing the whole bacterial network during tobacco development, and consequently rendered it to more profound ecological functions. During tobacco development, the contents of leaf sugar, nicotine, nitrogen and potassium were significantly correlated with either bacterial or fungal communities, and these abiotic factors accounted for 39.3 and 51.5% of the total variation, respectively. We overall evinced that the development of tobacco phyllosphere is accompanied by variant dynamics of phyllospheric microbial community.

Temperature sensitivity of the interspecific interaction strength of coastal marine fish communities

The effects of temperature on interaction strengths are important for understanding and forecasting how global climate change impacts marine ecosystems; however, tracking and quantifying interactions of marine fish species are practically difficult especially under field conditions, and thus, how temperature influences their interaction strengths under field conditions remains poorly understood. We herein performed quantitative fish environmental DNA (eDNA) metabarcoding on 550 seawater samples that were collected twice a month from 11 coastal sites for 2 years in the Boso Peninsula, Japan, and analyzed eDNA monitoring data using nonlinear time series analytical tools. We detected fish-fish interactions as information flow between eDNA time series, reconstructed interaction networks for the top 50 frequently detected species, and quantified pairwise, fluctuating interaction strengths. Although there was a large variation, water temperature influenced fish-fish interaction strengths. The impact of water temperature on interspecific interaction strengths varied among fish species, suggesting that fish species identity influences the temperature effects on interactions. For example, interaction strengths that Halichoeres tenuispinis and Microcanthus strigatus received strongly increased with water temperature, while those of Engraulis japonicus and Girella punctata decreased with water temperature. An increase in water temperature induced by global climate change may change fish interactions in a complex way, which consequently influences marine community dynamics and stability. Our research demonstrates a practical research framework to study the effects of environmental variables on interaction strengths of marine communities in nature, which would contribute to understanding and predicting natural marine ecosystem dynamics.

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.

Navigation between initial and desired community states using shortcuts

Ecological management problems often involve navigating from an initial to a desired community state. We ask whether navigation without brute-force additions and deletions of species is possible via: adding/deleting a small number of individuals of a species, changing the environment, and waiting. Navigation can yield direct paths (single sequence of actions) or shortcut paths (multiple sequences of actions with lower cost than a direct path). We ask (1) when is non-brute-force navigation possible?; (2) do shortcuts exist and what are their properties?; and (3) what heuristics predict shortcut existence? Using a state diagram framework applied to several empirical datasets, we show that (1) non-brute-force navigation is only possible between some state pairs, (2) shortcuts exist between many state pairs; and (3) changes in abundance and richness are the strongest predictors of shortcut existence, independent of dataset and algorithm choices. State diagrams thus unveil hidden strategies for manipulating species coexistence and efficiently navigating between states.

Conceptualizing microbe-plasmid communities as complex adaptive systems

Plasmids shape microbial communities' diversity, structure, and function. Nevertheless, we lack a mechanistic understanding of how community structure and dynamics emerge from local microbe-plasmid interactions and coevolution. Addressing this gap is challenging because multiple processes operate simultaneously at multiple levels of organization. For example, immunity operates between a plasmid and a cell, but incompatibility mechanisms regulate coexistence between plasmids. Conceptualizing microbe-plasmid communities as complex adaptive systems is a promising approach to overcoming these challenges. I illustrate how agent-based evolutionary modeling, extended by network analysis, can be used to quantify the relative importance of local processes governing community dynamics. These theoretical developments can advance our understanding of plasmid ecology and evolution, especially when combined with empirical data.

Geographical shifts in the successional dynamics of inland dune shrub communities

Species' environmental requirements and large-scale spatial and evolutionary processes determine the structure and composition of local communities. However, ecological interactions also have major effects on community assembly at landscape and local scales. We evaluate whether two xerophytic shrub communities occurring in SW Portugal follow constrained ecological assembly dynamics throughout large geographical extents, or their composition is rather driven by species' individualistic responses to environmental and macroecological constraints. Inland dune xerophytic shrub communities were characterized in 95 plots. Then, we described the main gradients of vegetation composition and assessed the relevance of biotic interactions. We also characterized the habitat suitability of the dominant species, Stauracanthus genistoides, and Ulex australis, to map the potential distribution of the xerophytic shrub communities. Finally, we examined the relationships between the vegetation gradients and a broad set of explanatory variables to identify the relative importance of each factor driving changes in community composition. We found that xerophytic shrubs follow uniform successional patterns throughout the whole geographical area studied, but each community responds differently to the main environmental gradients in each region. Soil organic matter is the main determinant of community variations in the northern region, Setúbal Peninsula, whereas aridity is so in the South/South-Western region. In contrast, in the central region, Comporta, the variation between S. genistoides and U. australis communities is explained mainly by aridity and temperature seasonality, followed by the individualistic responses of the dominant species and soil organic matter. Overall, these results indicate that, the relative importance of the main factors causing community-level responses varies according to regional processes and the suitability of the environmental conditions for the dominant species in these communities. These responses are also determined by intrinsic community mechanisms that result in a high degree of similarity in the gradient-driven community stages in different regions.

Inference of dynamic interaction networks: A comparison between Lotka-Volterra and multivariate autoregressive models

Networks are ubiquitous throughout biology, spanning the entire range from molecules to food webs and global environmental systems. Yet, despite substantial efforts by the scientific community, the inference of these networks from data still presents a problem that is unsolved in general. One frequent strategy of addressing the structure of networks is the assumption that the interactions among molecular or organismal populations are static and correlative. While often successful, these static methods are no panacea. They usually ignore the asymmetry of relationships between two species and inferences become more challenging if the network nodes represent dynamically changing quantities. Overcoming these challenges, two very different network inference approaches have been proposed in the literature: Lotka-Volterra (LV) models and Multivariate Autoregressive (MAR) models. These models are computational frameworks with different mathematical structures which, nevertheless, have both been proposed for the same purpose of inferring the interactions within coexisting population networks from observed time-series data. Here, we assess these dynamic network inference methods for the first time in a side-by-side comparison, using both synthetically generated and ecological datasets. Multivariate Autoregressive and Lotka-Volterra models are mathematically equivalent at the steady state, but the results of our comparison suggest that Lotka-Volterra models are generally superior in capturing the dynamics of networks with non-linear dynamics, whereas Multivariate Autoregressive models are better suited for analyses of networks of populations with process noise and close-to linear behavior. To the best of our knowledge, this is the first study comparing LV and MAR approaches. Both frameworks are valuable tools that address slightly different aspects of dynamic networks.

Disentangling direct and indirect effects of extreme events on coastal wetland communities

One of the primary ways in which climate change will impact coastal freshwater wetlands is through changes in the frequency, intensity, timing and distribution of extreme weather events. Disentangling the direct and indirect mechanisms of population- and community-level responses to extreme events is vital to predicting how species composition of coastal wetlands will change under future conditions. We extended static structural equation modelling approaches to incorporate system dynamics in a multi-year multispecies occupancy model to quantify the effects of extreme weather events on a coastal freshwater wetland system. We used data from an 8-year study (2009-2016) on St. Marks National Wildlife Refuge in Florida, USA, to quantify species-specific and community-level changes in amphibian and fish occupancy associated with two flooding events in 2012 and 2013. We examine how physical changes to the landscape, including potential changes in salinity and increased wetland connectivity, may have contributed to or exacerbated the effects of these extreme weather events on the biota of isolated coastal wetlands. We provide evidence that the primary effects of flooding on the amphibian community were through indirect mechanisms via changes in the composition of the sympatric fish community that may have had lethal (i.e. through direct predation) or non-lethal (i.e. through direct or indirect competitive interactions) effects. In addition, we have shown that amphibian species differed in their sensitivity to direct flooding effects and indirect changes in the fish community and wetland-specific conductance, which led to variable responses across the community. These effects led to the overall decline in amphibian species richness from 2009 to 2016, suggesting that wetland-breeding amphibian communities on St. Marks National Wildlife Refuge may not be resilient to predicted changes in coastal disturbance regimes because of climate change. Understanding both direct and indirect effects, as well as species interactions, is important for predicting the effects of a changing climate on individual species, communities and ecosystems.

A basic community dynamics experiment: Disentangling deterministic and stochastic processes in structuring ecological communities

Community dynamics are governed by two opposed processes: species sorting, which produces deterministic dynamics leading to an equilibrium state, and ecological drift, which produces stochastic dynamics. Despite a great deal of theoretical and empirical work aiming to demonstrate the predominance of one or the other of these processes, the importance of drift in structuring communities and maintaining species diversity remains contested. Here, we present the results of a basic community dynamics experiment using floating aquatic plants, designed to measure the relative contributions of species sorting and ecological drift to community change over about a dozen generations. We found that species sorting became overwhelmingly dominant as the experiment progressed, and directed communities toward a stable equilibrium state maintained by negative frequency-dependent selection. The dynamics of any particular species depended on how far its initial frequency was from its equilibrium frequency, however, and consequently the balance of sorting and drift varied among species.

Climate disequilibrium dominates uncertainty in long-term projections of primary productivity

Rapid climate change may exceed ecosystems' capacities to respond through processes including phenotypic plasticity, compositional turnover and evolutionary adaption. However, consequences of the resulting climate disequilibria for ecosystem functioning are rarely considered in projections of climate change impacts. Combining statistical models fit to historical climate data and remotely-sensed estimates of herbaceous net primary productivity with an ensemble of climate models, we demonstrate that assumptions concerning the magnitude of climate disequilibrium are a dominant source of uncertainty: models assuming maximum disequilibrium project widespread decreases in productivity in the western US by 2100, while models assuming minimal disequilibrium project productivity increases. Uncertainty related to climate disequilibrium is larger than uncertainties from variation among climate models or emissions pathways. A better understanding of processes that regulate climate disequilibria is essential for improving long-term projections of ecological responses and informing management to maintain ecosystem functioning at historical baselines.

Community structure determines the predictability of population collapse

Early warning signals (EWS) are phenomenological tools that have been proposed as predictors of the collapse of biological systems. Although a growing body of work has shown the utility of EWS based on either statistics derived from abundance data or shifts in phenotypic traits such as body size, so far this work has largely focused on single species populations.

However, to predict reliably the future state of ecological systems, which inherently could consist of multiple species, understanding how reliable such signals are in a community context is critical.

Here, reconciling quantitative trait evolution and Lotka–Volterra equations, which allow us to track both abundance and mean traits, we simulate the collapse of populations embedded in mutualistic and multi‐trophic predator–prey communities. Using these simulations and warning signals derived from both population‐ and community‐level data, we showed the utility of abundance‐based EWS, as well as metrics derived from stability‐landscape theory (e.g. width and depth of the basin of attraction), were fundamentally linked. Thus, the depth and width of such stability‐landscape curves could be used to identify which species should exhibit the strongest EWS of collapse.

The probability a species displays both trait and abundance‐based EWS was dependent on its position in a community, with some species able to act as indicator species. In addition, our results also demonstrated that in general trait‐based EWS were less reliable in comparison with abundance‐based EWS in forecasting species collapses in our simulated communities. Furthermore, community‐level abundance‐based EWS were fairly reliable in comparison with their species‐level counterparts in forecasting species‐level collapses.

Our study suggests a holistic framework that combines abundance‐based EWS and metrics derived from stability‐landscape theory that may help in forecasting species loss in a community context.

Quantifying invasibility

Invasibility, the chance of a population to grow from rarity and become established, plays a fundamental role in population genetics, ecology, epidemiology and evolution. For many decades, the mean growth rate of a species when it is rare has been employed as an invasion criterion. Recent studies show that the mean growth rate fails as a quantitative metric for invasibility, with its magnitude sometimes even increasing while the invasibility decreases. Here we provide two novel formulae, based on the diffusion approximation and a large‐deviations (Wentzel–Kramers–Brillouin) approach, for the chance of invasion given the mean growth and its variance. The first formula has the virtue of simplicity, while the second one holds over a wider parameter range. The efficacy of the formulae, including their accompanying data analysis technique, is demonstrated using synthetic time series generated from canonical models and parameterised with empirical data.

The Leaf Microbiome of Arabidopsis Displays Reproducible Dynamics and Patterns throughout the Growing Season

Leaves are primarily responsible for the plant’s photosynthetic activity. Thus, changes in the leaf microbiota, which includes deleterious and beneficial microbes, can have far-reaching effects on plant fitness and productivity. Identifying the processes and microorganisms that drive these changes over a plant’s lifetime is, therefore, crucial. In this study, we analyzed the temporal dynamics in the leaf microbiome of Arabidopsis thaliana, integrating changes in both composition and microbe-microbe interactions via the study of microbial networks. Field-grown Arabidopsis were used to monitor leaf bacterial, fungal and oomycete communities throughout the plant’s natural growing season (extending from November to March) over three consecutive years. Our results revealed the existence of conserved temporal patterns, with microbial communities and networks going through a stabilization phase of decreased diversity and variability at the beginning of the plant’s growing season. Despite a high turnover in these communities, we identified 19 “core” taxa persisting on Arabidopsis leaves across time and plant generations. With the hypothesis these microbes could be playing key roles in the structuring of leaf microbial communities, we conducted a time-informed microbial network analysis which showed core taxa are not necessarily highly connected network “hubs,” and “hubs” alternate with time. Our study shows that leaf microbial communities exhibit reproducible dynamics and patterns, suggesting the potential of using our understanding of temporal trajectories in microbial community composition to design experiments aimed at driving these communities toward desired states.

Effects of density, species interactions, and environmental stochasticity on the dynamics of British bird communities

Our knowledge of the factors affecting species abundances is mainly based on time‐series analyses of a few well‐studied species at single or few localities, but we know little about whether results from such analyses can be extrapolated to the community level. We apply a joint species distribution model to long‐term time‐series data on British bird communities to examine the relative contribution of intra‐ and interspecific density dependence at different spatial scales, as well as the influence of environmental stochasticity, to spatiotemporal interspecific variation in abundance. Intraspecific density dependence has the major structuring effect on these bird communities. In addition, environmental fluctuations affect spatiotemporal differences in abundance. In contrast, species interactions had a minor impact on variation in abundance. Thus, important drivers of single‐species dynamics are also strongly affecting dynamics of communities in time and space.

Fast growth can counteract antibiotic susceptibility in shaping microbial community resilience to antibiotics

SignificanceAntibiotic exposure stands among the most used interventions to drive microbial communities away from undesired states. How the ecology of microbial communities shapes their recovery-e.g., posttreatment shifts toward Clostridioides difficile infections in the gut-after antibiotic exposure is poorly understood. We study community response to antibiotics using a model community that can reach two alternative states. Guided by theory, our experiments show that microbial growth following antibiotic exposure can counteract antibiotic susceptibility in driving transitions between alternative community states. This makes it possible to reverse the outcome of antibiotic exposure through modifying growth dynamics, including cooperative growth, of community members. Our research highlights the relevance of simple ecological models to better understand the long-term effects of antibiotic treatment.

A tale of two reef systems: Local conditions, disturbances, coral life histories, and the climate catastrophe

Coral reefs have evolved over millennia to survive disturbances. Yet, in just a few decades chronic local pressures and the climate catastrophe have accelerated so quickly that most coral reefs are now threatened. Rising ocean temperatures and recurrent bleaching pose the biggest threat, affecting even remote and well-managed reefs on global scales. We illustrate how coral bleaching is altering reefs by contrasting the dynamics of adjacent reef systems over more than two decades. Both reef systems sit near the edge of northwest Australia's continental shelf, have escaped chronic local pressures and are regularly affected by tropical storms and cyclones. The Scott reef system has experienced multiple bleaching events, including mass bleaching in 1998 and 2016, from which it is unlikely to fully recover. The Rowley Shoals has maintained a high cover and diversity of corals and has not yet been impacted by mass bleaching. We show how the dynamics of both reef systems were driven by a combination of local environment, exposure to disturbances and coral life history traits, and consider future shifts in community structure with ongoing climate change. We then demonstrate how applying knowledge of community dynamics at local scales can aid management strategies to slow the degradation of coral reefs until carbon emissions and other human impacts are properly managed.

The long and the short of it: Mechanisms of synchronous and compensatory dynamics across temporal scales

Synchronous dynamics (fluctuations that occur in unison) are universal phenomena with widespread implications for ecological stability. Synchronous dynamics can amplify the destabilizing effect of environmental variability on ecosystem functions such as productivity, whereas the inverse, compensatory dynamics, can stabilize function. Here we combine simulation and empirical analyses to elucidate mechanisms that underlie patterns of synchronous versus compensatory dynamics. In both simulated and empirical communities, we show that synchronous and compensatory dynamics are not mutually exclusive but instead can vary by timescale. Our simulations identify multiple mechanisms that can generate timescale‐specific patterns, including different environmental drivers, diverse life histories, dispersal, and non‐stationary dynamics. We find that traditional metrics for quantifying synchronous dynamics are often biased toward long‐term drivers and may miss the importance of short‐term drivers. Our findings indicate key mechanisms to consider when assessing synchronous versus compensatory dynamics and our approach provides a pathway for disentangling these dynamics in natural systems.

Emergent Diversity and Persistent Turnover in Evolving Microbial Cross-Feeding Networks

A distinguishing feature of many ecological networks in the microbial realm is the diversity of substrates that could potentially serve as energy sources for microbial consumers. The microorganisms are themselves the agents of compound diversification via metabolite excretion or overflow metabolism. It has been suggested that the emerging richness of different substrates is an important condition for the immense biological diversity in microbial ecosystems. In this work, we study how complex cross-feeding networks (CFN) of microbial species may develop from a simple initial community given some elemental evolutionary mechanisms of resource-dependent speciation and extinctions using a network flow model. We report results of several numerical experiments and report an in-depth analysis of the evolutionary dynamics. We find that even in stable environments, the system is subject to persisting turnover, indicating an ongoing co-evolution. Further, we compare the impact of different parameters, such as the ratio of mineralization, as well as the metabolic versatility and variability on the evolving community structure. The results imply that high microbial and molecular diversity is an emergent property of evolution in cross-feeding networks, which affects transformation and accumulation of substrates in natural systems, such as soils and oceans, with potential relevance to biotechnological applications.

Year-round dynamics of amplicon sequence variant communities differ among eukaryotes, Imitervirales, and prokaryotes in a coastal ecosystem

Coastal microbial communities are affected by seasonal environmental change, biotic interactions, and fluctuating nutrient availability. We investigated the seasonal dynamics of communities of eukaryotes, a major group of double-stranded DNA viruses that infect eukaryotes (order Imitervirales; phylum Nucleocytoviricota), and prokaryotes in the Uranouchi Inlet, Kochi, Japan. We performed metabarcoding using ribosomal RNA genes and viral polB genes as markers in 43 seawater samples collected over 20 months. Eukaryotes, prokaryotes, and Imitervirales communities characterized by the compositions of amplicon sequence variants (ASVs) showed synchronic seasonal cycles. However, the community dynamics showed intriguing differences in several aspects, such as the recovery rate after a year. We also showed that the differences in community dynamics were at least partially explained by differences in recurrence/persistence levels of individual ASVs among eukaryotes, prokaryotes, and Imitervirales. Prokaryotic ASVs were the most persistent, followed by eukaryotic ASVs and Imitervirales ASVs, which were the least persistent. We argue that the differences in the specificity of interactions (virus-eukaryote vs. prokaryote-eukaryote) as well as the niche breadth of community members were at the origin of the distinct community dynamics among eukaryotes, their viruses, and prokaryotes.

Seed dispersal by wind decreases when plants are water-stressed, potentially counteracting species coexistence and niche evolution

Hydrology is a major environmental factor determining plant fitness, and hydrological niche segregation (HNS) has been widely used to explain species coexistence. Nevertheless, the distribution of plant species along hydrological gradients does not only depend on their hydrological niches but also depend on their seed dispersal, with dispersal either weakening or reinforcing the effects of HNS on coexistence. However, it is poorly understood how seed dispersal responds to hydrological conditions. To close this gap, we conducted a common-garden experiment exposing five wind-dispersed plant species (Bellis perennis, Chenopodium album, Crepis sancta, Hypochaeris glabra, and Hypochaeris radicata) to different hydrological conditions. We quantified the effects of hydrological conditions on seed production and dispersal traits, and simulated seed dispersal distances with a mechanistic dispersal model. We found species-specific responses of seed production, seed dispersal traits, and predicted dispersal distances to hydrological conditions. Despite these species-specific responses, there was a general positive relationship between seed production and dispersal distance: Plants growing in favorable hydrological conditions not only produce more seeds but also disperse them over longer distances. This arises mostly because plants growing in favorable environments grow taller and thus disperse their seeds over longer distances. We postulate that the positive relationship between seed production and dispersal may reduce the concentration of each species to the environments favorable for it, thus counteracting species coexistence. Moreover, the resulting asymmetrical gene flow from favorable to stressful habitats may slow down the microevolution of hydrological niches, causing evolutionary niche conservatism. Accounting for context-dependent seed dispersal should thus improve ecological and evolutionary models for the spatial dynamics of plant populations and communities.

A High Rate Algal Pond Hosting a Dynamic Community of RNA Viruses

Despite a surge of RNA virome sequencing in recent years, there are still many RNA viruses to uncover-as indicated by the relevance of viral dark matter to RNA virome studies (i.e., putative viruses that do not match to taxonomically identified viruses). This study explores a unique site, a high-rate algal pond (HRAP), for culturing industrially microalgae, to elucidate new RNA viruses. The importance of viral-host interactions in aquatic systems are well documented, and the ever-expanding microalgae industry is no exception. As the industry becomes a more important source of sustainable plastic manufacturing, a producer of cosmetic pigments and alternative protein sources, and a means of CO2 remediation in the face of climate change, studying microalgal viruses becomes a vital practice for proactive management of microalgae cultures at the industrial level. This study provides evidence of RNA microalgal viruses persisting in a CO2 remediation pilot project HRAP and uncovers the diversity of the RNA virosphere contained within it. Evidence shows that family Marnaviridae is cultured in the basin, alongside other potential microalgal infecting viruses (e.g., family Narnaviridae, family Totitiviridae, and family Yueviridae). Finally, we demonstrate that the RNA viral diversity of the HRAP is temporally dynamic across two successive culturing seasons.

Cropping systems impact changes in soil fungal, but not prokaryote, alpha-diversity and community composition stability over a growing season in a long-term field trial

Crop harvest followed by a fallow period can act as a disturbance on soil microbial communities. Cropping systems intended to improve alpha-diversity of communities may also confer increased compositional stability during succeeding growing seasons. Over a single growing season in a long-term (18 year) agricultural field experiment incorporating conventional (CON), conservation (CA), organic (ORG) and integrated (INT) cropping systems, temporal changes in prokaryote, fungal and arbuscular mycorrhizal fungi (AMF) communities were investigated overwinter, during crop growth and at harvest. While certain prokaryote phyla were influenced by cropping system (e.g. Acidobacteria), the community as a whole was primarily driven by temporal changes over the growing season as distinct overwinter and crop-associated communities, with the same trend observed regardless of cropping system. Species-rich prokaryote communities were most stable over the growing season. Cropping system exerted a greater effect on fungal communities, with alpha-diversity highest and temporal changes most stable under CA. CON was particularly detrimental for alpha-diversity in AMF communities, with AMF alpha-diversity and stability improved under all other cropping systems. Practices that promoted alpha-diversity tended to also increase the similarity and temporal stability of soil fungal (and AMF) communities during a growing season, while prokaryote communities were largely insensitive to management.

Divergent climate change effects on widespread dryland plant communities driven by climatic and ecohydrological gradients

Plant community response to climate change will be influenced by individual plant responses that emerge from competition for limiting resources that fluctuate through time and vary across space. Projecting these responses requires an approach that integrates environmental conditions and species interactions that result from future climatic variability. Dryland plant communities are being substantially affected by climate change because their structure and function are closely tied to precipitation and temperature, yet impacts vary substantially due to environmental heterogeneity, especially in topographically complex regions. Here, we quantified the effects of climate change on big sagebrush (Artemisia tridentata Nutt.) plant communities that span 76 million ha in the western United States. We used an individual-based plant simulation model that represents intra- and inter-specific competition for water availability, which is represented by a process-based soil water balance model. For dominant plant functional types, we quantified changes in biomass and characterized agreement among 52 future climate scenarios. We then used a multivariate matching algorithm to generate fine-scale interpolated surfaces of functional type biomass for our study area. Results suggest geographically divergent responses of big sagebrush to climate change (changes in biomass of -20% to +27%), declines in perennial C₃ grass and perennial forb biomass in most sites, and widespread, consistent, and sometimes large increases in perennial C₄ grasses. The largest declines in big sagebrush, perennial C₃ grass and perennial forb biomass were simulated in warm, dry sites. In contrast, we simulated no change or increases in functional type biomass in cold, moist sites. There was high agreement among climate scenarios on climate change impacts to functional type biomass, except for big sagebrush. Collectively, these results suggest divergent responses to warming in moisture-limited versus temperature-limited sites and potential shifts in the relative importance of some of the dominant functional types that result from competition for limiting resources.

Trends in bird abundance differ among protected forests but not bird guilds

Improved monitoring and associated inferential tools to efficiently identify declining bird populations, particularly of rare or sparsely distributed species, is key to informed conservation and management across large spatiotemporal regions. We assess abundance trends for 106 bird species in a network of eight forested national parks located within the northeast United States from 2006 to 2019 using a novel hierarchical model. We develop a multispecies, multiregion, removal-sampling model that shares information across species and parks to enable inference on rare species and sparsely sampled parks and to evaluate the effects of local forest structure. Trends in bird abundance over time varied widely across parks, but species showed similar trends within parks. Three parks (Acadia National Park and Marsh-Billings-Rockefeller and Morristown National Historical Parks [NHP]) decreased in bird abundance across all species, while three parks (Saratoga NHP and Roosevelt-Vanderbilt and Weir-Farm National Historic Sites) increased in abundance. Bird abundance peaked at medium levels of basal area and high levels of percent forest and forest regeneration, with percent forest having the largest effect. Variation in these effects across parks could be a result of differences in forest structural stage and diversity. By sharing information across both communities and parks, our novel hierarchical model enables uncertainty-quantified estimates of abundance across multiple geographical (i.e., network, park) and taxonomic (i.e., community, guild, species) levels over a large spatiotemporal region. We found large variation in abundance trends across parks but not across bird guilds, suggesting that local forest condition might have a broad and consistent effect on the entire bird community within a given park. Research should target the three parks with overall decreasing trends in bird abundance to further identify what specific factors are driving observed declines across the bird community. Understanding how bird communities respond to local forest structure and other stressors (e.g., pest outbreaks, climate change) is crucial for informed and lasting management.

Stabilising role of seed banks and the maintenance of bacterial diversity

Coexisting species often exhibit negative frequency dependence due to mechanisms that promote population growth and persistence when rare. These stabilising mechanisms can maintain diversity through interspecific niche differences, but also through life-history strategies like dormancy that buffer populations in fluctuating environments. However, there are few tests demonstrating how seed banks contribute to long-term community dynamics and the maintenance of diversity. Using a multi-year, high-frequency time series of bacterial community data from a north temperate lake, we documented patterns consistent with stabilising coexistence. Bacterial taxa exhibited differential responses to seasonal environmental conditions, while seed bank dynamics helped maintain diversity over less-favourable winter periods. Strong negative frequency dependence in rare, but metabolically active, taxa suggested a role for biotic interactions in promoting coexistence. Together, our results provide field-based evidence that niche differences and seed banks contribute to recurring community dynamics and the long-term maintenance of diversity in nature.

Dynamic population stage structure due to juvenile-adult asymmetry stabilizes complex ecological communities

Natural ecological communities are diverse, complex, and often surprisingly stable, but the mechanisms underlying their stability remain a theoretical enigma. Interactions such as competition and predation presumably structure communities, yet theory predicts that complex communities are stable only when species growth rates are mostly limited by intraspecific self-regulation rather than by interactions with resources, competitors, and predators. Current theory, however, considers only the network topology of population-level interactions between species and ignores within-population differences, such as between juvenile and adult individuals. Here, using model simulations and analysis, I show that including commonly observed differences in vulnerability to predation and foraging efficiency between juvenile and adult individuals results in up to 10 times larger, more complex communities than observed in simulations without population stage structure. These diverse communities are stable or fluctuate with limited amplitude, although in the model only a single basal species is self-regulated, and the population-level interaction network is highly connected. Analysis of the species interaction matrix predicts the simulated communities to be unstable but for the interaction with the population-structure subsystem, which completely cancels out these instabilities through dynamic changes in population stage structure. Common differences between juveniles and adults and fluctuations in their relative abundance may hence have a decisive influence on the stability of complex natural communities and their vulnerability when environmental conditions change. To explain community persistence, it may not be sufficient to consider only the network of interactions between the constituting species.

Unraveling a Lignocellulose-Decomposing Bacterial Consortium from Soil Associated with Dry Sugarcane Straw by Genomic-Centered Metagenomics

Second-generation biofuel production is in high demand, but lignocellulosic biomass’ complexity impairs its use due to the vast diversity of enzymes necessary to execute the complete saccharification. In nature, lignocellulose can be rapidly deconstructed due to the division of biochemical labor effectuated in bacterial communities. Here, we analyzed the lignocellulolytic potential of a bacterial consortium obtained from soil and dry straw leftover from a sugarcane milling plant. This consortium was cultivated for 20 weeks in aerobic conditions using sugarcane bagasse as a sole carbon source. Scanning electron microscopy and chemical analyses registered modification of the sugarcane fiber’s appearance and biochemical composition, indicating that this consortium can deconstruct cellulose and hemicellulose but no lignin. A total of 52 metagenome-assembled genomes from eight bacterial classes (Actinobacteria, Alphaproteobacteria, Bacilli, Bacteroidia, Cytophagia, Gammaproteobacteria, Oligoflexia, and Thermoleophilia) were recovered from the consortium, in which ~46% of species showed no relevant modification in their abundance during the 20 weeks of cultivation, suggesting a mostly stable consortium. Their CAZymes repertoire indicated that many of the most abundant species are known to deconstruct lignin (e.g., Chryseobacterium) and carry sequences related to hemicellulose and cellulose deconstruction (e.g., Chitinophaga, Niastella, Niabella, and Siphonobacter). Taken together, our results unraveled the bacterial diversity, enzymatic potential, and effectiveness of this lignocellulose-decomposing bacterial consortium.

Ocean acidification locks algal communities in a species-poor early successional stage

Long-term exposure to CO₂ -enriched waters can considerably alter marine biological community development, often resulting in simplified systems dominated by turf algae that possess reduced biodiversity and low ecological complexity. Current understanding of the underlying processes by which ocean acidification alters biological community development and stability remains limited, making the management of such shifts problematic. Here, we deployed recruitment tiles in reference (pH_T 8.137 ± 0.056 SD) and CO₂ -enriched conditions (pH_T 7.788 ± 0.105 SD) at a volcanic CO₂ seep in Japan to assess the underlying processes and patterns of algal community development. We assessed (i) algal community succession in two different seasons (Cooler months: January-July, and warmer months: July-January), (ii) the effects of initial community composition on subsequent community succession (by reciprocally transplanting preestablished communities for a further 6 months), and (iii) the community production of resulting communities, to assess how their functioning was altered (following 12 months recruitment). Settlement tiles became dominated by turf algae under CO₂ -enrichment and had lower biomass, diversity and complexity, a pattern consistent across seasons. This locked the community in a species-poor early successional stage. In terms of community functioning, the elevated pCO₂ community had greater net community production, but this did not result in increased algal community cover, biomass, biodiversity or structural complexity. Taken together, this shows that both new and established communities become simplified by rising CO₂ levels. Our transplant of preestablished communities from enriched CO₂ to reference conditions demonstrated their high resilience, since they became indistinguishable from communities maintained entirely in reference conditions. This shows that meaningful reductions in pCO₂ can enable the recovery of algal communities. By understanding the ecological processes responsible for driving shifts in community composition, we can better assess how communities are likely to be altered by ocean acidification.

A modified niche model for generating food webs with stage-structured consumers: The stabilizing effects of life-history stages on complex food webs

Almost all organisms grow in size during their lifetime and switch diets, trophic positions, and interacting partners as they grow. Such ontogenetic development introduces life-history stages and flows of biomass between the stages through growth and reproduction. However, current research on complex food webs rarely considers life-history stages. The few previously proposed methods do not take full advantage of the existing food web structural models that can produce realistic food web topologies.We extended the niche model developed by Williams and Martinez (Nature, 2000, 404, 180-183) to generate food webs that included trophic species with a life-history stage structure. Our method aggregated trophic species based on niche overlap to form a life-history structured population; therefore, it largely preserved the topological structure of food webs generated by the niche model. We applied the theory of allometric predator-prey body mass ratio and parameterized an allometric bioenergetic model augmented with biomass flow between stages via growth and reproduction to study the effects of a stage structure on the stability of food webs.When life-history stages were linked via growth and reproduction, more food webs persisted, and persisting food webs tended to retain more trophic species. Topological differences between persisting linked and unlinked food webs were small to modest. The slopes of biomass spectra were lower, and weak interaction links were more prevalent in the linked food webs than the unlinked ones, suggesting that a life-history stage structure promotes characteristics that can enhance stability of complex food webs.Our results suggest a positive relationship between the complexity and stability of complex food webs. A life-history stage structure in food webs may play important roles in dynamics of and diversity in food webs.

Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300-400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of -0.1 to -0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.

Habitat amount and distribution modify community dynamics under climate change

Habitat fragmentation may present a major impediment to species range shifts caused by climate change, but how it affects local community dynamics in a changing climate has so far not been adequately investigated empirically. Using long-term monitoring data of butterfly assemblages, we tested the effects of the amount and distribution of semi-natural habitat (SNH), moderated by species traits, on climate-driven species turnover. We found that spatially dispersed SNH favoured the colonisation of warm-adapted and mobile species. In contrast, extinction risk of cold-adapted species increased in dispersed (as opposed to aggregated) habitats and when the amount of SNH was low. Strengthening habitat networks by maintaining or creating stepping-stone patches could thus allow warm-adapted species to expand their range, while increasing the area of natural habitat and its spatial cohesion may be important to aid the local persistence of species threatened by a warming climate.

Reproductive interference hampers species coexistence despite conspecific sperm precedence

Negative interspecific mating interactions, known as reproductive interference, can hamper species coexistence in a local patch and promote niche partitioning or geographical segregation of closely related species. Conspecific sperm precedence (CSP), which occurs when females that have mated with both conspecific and heterospecific males preferentially use conspecific sperm for fertilization, might contribute to species coexistence by mitigating the costs of interspecific mating and hybridization. We discussed whether two species exhibiting CSP can coexist in a local environment in the presence of reproductive interference. First, using a behaviorally explicit mathematical model, we demonstrated that two species characterized by negative mating interactions are unlikely to coexist because the costs of reproductive interference, such as loss of mating opportunity with conspecific partners, are inevitably incurred when individuals of both species are present. Second, we experimentally examined differences in mating activity and preference in two Harmonia ladybird species known to exhibit CSP. These behavioral differences may lead to local extinction of H. yedoensis because of reproductive interference by H. axyridis. This prediction is consistent with field observations that H. axyridis uses various food sources and habitats whereas H. yedoensis is confined to a less preferred prey item and a pine tree habitat. Finally, by a comparative approach, we observed that niche partitioning or parapatric distribution, but not sympatric coexistence in the same habitat, is maintained between species with CSP belonging to a wide range of taxa, including vertebrates and invertebrates living in aquatic or terrestrial environments. Taken together, it is possible that reproductive interference may destabilize local coexistence even in closely related species that exhibit CSP.

The effects of resource subsidy duration in a detritus-based stream ecosystem: A mesocosm experiment

Most resource subsidies are temporally variable, dynamically affecting the consumer populations, community structures and ecosystem functions of recipient ecosystems. Temporally variable resource subsidies are characterized by the duration, magnitude, timing and frequency of resource subsidy inputs. These different characteristics may have different mechanisms by which to affect recipient ecosystems. Few studies have examined the duration of resource subsidy inputs on recipient ecosystems, although there exist previous studies focusing on magnitude, timing and frequency. We provide the first experimental test of the effects of subsidy duration on a stream ecosystem by using an outdoor mesocosm experiment, in which we directly manipulated the subsidy duration (pulsed vs. prolonged) of terrestrial invertebrate input into the mesocosm. Given the same overall amount of terrestrial invertebrate subsidy was added, a prolonged subsidy allowed large-stage fish to effectively monopolize the subsidy over small-stage fish, which led small-stage fish to maintain their predation pressure on in-situ prey, that is, benthic invertebrates. On the other hand, a pulsed subsidy allowed small-stage fish to increase their feeding rate of the subsidy and to become away from foraging in-situ prey. Consequently, weaker indirect positive effects on in-situ benthic prey and leaf break-down rate were found with the prolonged versus pulsed subsidy. However, these indirect effects varied by the dominant benthic prey species, which differed in edibility for fish. Such predator-specific vulnerability of benthic prey can be important in mediating trophic cascades in detritus-based stream food webs. Phenological events that generate temporal subsidies (e.g. salmon spawning run and arthropod emergence) can be synchronized (pulsed) or desynchronized (prolonged) within and among species, depending on the degree of spatial and temporal environmental heterogeneity. The effects of subsidy duration would thus be important to better understand ecological processes in spatially and temporally coupled ecosystems.

Drivers of assemblage-wide calling activity in tropical anurans and the role of temporal resolution

Temporal scale in animal communities is often associated with seasonality, despite the large variation in species activity during a diel cycle. A gap thus remains in understanding the dynamics of short-term activity in animal communities. Here we assessed calling activity of tropical anurans and addressed how species composition varied during night activity in assemblages along gradients of local and landscape environmental heterogeneity. We investigated 39 anuran assemblages in the Pantanal wetlands (Brazil) with passive acoustic monitoring during the peak of one breeding season, and first determined changes in species composition between night periods (early, mid and late) using two temporal resolutions (1- and 3-hr intervals). Then, we addressed the role of habitat structure (local and landscape heterogeneity variables from field-based and remote sensing metrics) and ecological context (species richness and phylogenetic relatedness) in determining changes in species composition (a) between night periods and (b) across days. Nocturnal calling activity of anuran assemblages varied more within the 1-hr resolution than the 3-hr resolution. Differences in species composition between early- and late-night periods were related to local habitat structure and phylogenetic relatedness, while a low variation in compositional changes across days was associated with low-heterogeneous landscapes. None of these relationships were observed using the coarser temporal resolution (3 hr). Our findings on the variation of calling activity in tropical anuran assemblages suggest potential trade-offs mediated by fine-temporal partitioning. Local and landscape heterogeneity may provide conditions for spatial partitioning, while the relatedness among co-signalling species provides cues on the ecological overlap of species with similar requirements. These relationships suggest a role of niche dimensional complementarity on the structuring of these anuran assemblages over fine-temporal scales. We argue that fine-temporal differences between species in breeding activity can influence the outcome of species interaction and thus, addressing temporal scaling issues can improve our understanding of the dynamics of animal communities.

Eco-evolutionary dynamics driven by fishing: From single species models to dynamic evolution within complex food webs

Evidence of contemporary evolution across ecological time scales stimulated research on the eco-evolutionary dynamics of natural populations. Aquatic systems provide a good setting to study eco-evolutionary dynamics owing to a wealth of long-term monitoring data and the detected trends in fish life-history traits across intensively harvested marine and freshwater systems. In the present study, we focus on modelling approaches to simulate eco-evolutionary dynamics of fishes and their ecosystems. Firstly, we review the development of modelling from single species to multispecies approaches. Secondly, we advance the current state-of-the-art methodology by implementing evolution of life-history traits of a top predator into the context of complex food web dynamics as described by the allometric trophic network (ATN) framework. The functioning of our newly developed eco-evolutionary ATNE framework is illustrated using a well-studied lake food web. Our simulations show how both natural selection arising from feeding interactions and size-selective fishing cause evolutionary changes in the top predator and how those feed back to its prey species and further cascade down to lower trophic levels. Finally, we discuss future directions, particularly the need to integrate genomic discoveries into eco-evolutionary projections.