Community assembly: alternative stable states or alternative transient states?

The concept of alternative stable states has long been a dominant framework for studying the influence of historical contingency in community assembly. This concept focuses on stable states, yet many real communities are kept in a transient state by disturbance, and the utility of predictions for stable states in explaining transient states remains unclear. Using a simple model of plant community assembly, we show that the conditions under which historical contingency affects community assembly can differ greatly for stable versus transient states. Differences arise because the contribution of such factors as mortality rate, environmental heterogeneity and plant-soil feedback to historical contingency changes as community assembly proceeds. We also show that transient states can last for a long time relative to immigration rate and generation time. These results argue for a conceptual shift of focus from alternative stable states to alternative transient states for understanding historical contingency in community assembly.     

Alternative stable states in inherently unstable systems

Alternative stable states are nontransitory states within which communities can exist. However, even highly dynamic communities can be viewed within the framework of stable‐state theory if an appropriate “ecologically relevant” time scale is identified. The ecologically relevant time scale for dynamic systems needs to conform to the amount of time needed for a system's community to complete an entire cycle through its normal range of variation. For some systems, the ecologically relevant period can be relatively short (eg, tidal systems), for others it can be decadal (eg, prairie wetlands). We explore the concept of alternative stable states in unstable systems using the highly dynamic wetland ecosystems of North America's Prairie Pothole Region. The communities in these wetland ecosystems transition through multiple states in response to decadal‐long climate oscillations that cyclically influence ponded‐water depth, permanence, and chemistry. The perspective gained by considering dynamic systems in the context of stable‐state theory allows for an increased understanding of how these systems respond to changing drivers that can push them past tipping points into alternative states. Incorporation of concepts inherent to stable‐state theory has been suggested as a key scientific element upon which to base sustainable environmental management.     

Directionality and community-level selection

Many ecological community dynamics display some degree of directionality, known as succession patterns. But complex interaction networks frequently tend to non-directional dynamics such as chaos, unless additional structures or mechanisms impose some form of, often fragile or shot-lived, directionality. We exhibit here a novel property of emergent long-lasting directionality in competitive communities, which relies on very minimal assumptions. We model communities where each species has a few strong competitive interactions, and many weak ones. We find that, at high enough diversity, the dynamics become directional, meaning that the community state can be characterized by a function that increases in time, which we call ‘maturity'. In the presence of noise, the community composition changes toward increasingly stable and productive states. This scenario occupies a middle ground between deterministic succession and purely random species associations: there are many overlapping stable states, with stochastic transitions, that are nevertheless biased in a particular direction. When a spatial dimension is added in the form of a meta-community, higher-maturity community states are able to expand in space, replacing others by (exact or approximate) copies of themselves. This leads to community-level selection, with the same maturity function acting as fitness. Classic concepts from evolutionary dynamics provide a powerful analogy to understand this strictly ecological, community-level phenomenon of emergent directionality.     

Evolution to alternative levels of stable diversity leaves areas of niche space unexplored

One of the oldest and most persistent questions in ecology and evolution is whether natural communities tend to evolve toward saturation and maximal diversity. Robert MacArthur’s classical theory of niche packing and the theory of adaptive radiations both imply that populations will diversify and fully partition any available niche space. However, the saturation of natural populations is still very much an open area of debate and investigation. Additionally, recent evolutionary theory suggests the existence of alternative evolutionary stable states (ESSs), which implies that some stable communities may not be fully saturated. Using models with classical Lotka-Volterra ecological dynamics and three formulations of evolutionary dynamics (a model using adaptive dynamics, an individual-based model, and a partial differential equation model), we show that following an adaptive radiation, communities can often get stuck in low diversity states when limited by mutations of small phenotypic effect. These low diversity metastable states can also be maintained by limited resources and finite population sizes. When small mutations and finite populations are considered together, it is clear that despite the presence of higher-diversity stable states, natural populations are likely not fully saturating their environment and leaving potential niche space unfilled. Additionally, within-species variation can further reduce community diversity from levels predicted by models that assume species-level homogeneity.     

Species assembly in model ecosystems, I: Analysis of the population model and the invasion dynamics

Recently we have introduced a simplified model of ecosystem assembly (Capitán et al., 2009) for which we are able to map out all assembly pathways generated by external invasions in an exact manner. In this paper we provide a deeper analysis of the model, obtaining analytical results and introducing some approximations which allow us to reconstruct the results of our previous work. In particular, we show that the population dynamics equations of a very general class of trophic-level structured food-web have an unique interior equilibrium point which is globally stable. We show analytically that communities found as end states of the assembly process are pyramidal and we find that the equilibrium abundance of any species at any trophic level is approximately inversely proportional to the number of species in that level. We also find that the per capita growth rate of a top predator invading a resident community is key to understand the appearance of complex end states reported in our previous work. The sign of these rates allows us to separate regions in the space of parameters where the end state is either a single community or a complex set containing more than one community. We have also built up analytical approximations to the time evolution of species abundances that allow us to determine, with high accuracy, the sequence of extinctions that an invasion may cause. Finally we apply this analysis to obtain the communities in the end states. To test the accuracy of the transition probability matrix generated by this analytical procedure for the end states, we have compared averages over those sets with those obtained from the graph derived by numerical integration of the Lotka-Volterra equations. The agreement is excellent.     

Complex shifts between food web states in response to whole‐ecosystem manipulations

Food webs can respond in surprising and complex ways to temporary alterations in their species composition. When such a perturbation is reversed, food webs have been shown to either return to the pre‐perturbation community state or remain in the food web configuration that established during the perturbation. Here we report findings from a replicated whole‐lake experiment investigating food web responses to a perturbation and its consecutive reversal. We could identify three distinct community states in the food web that corresponded to the periods before, during and after the perturbation. Most importantly, we demonstrate the establishment of a distinct post‐perturbation food web configuration that differed from both the pre‐ and during‐perturbation communities in phytoplankton biomass and micro‐ and mesozooplankton species composition. We suggest that the pre‐ and post‐perturbation food web configurations may represent two alternative stable community states. We provide explanations for how each of the contrasting communities may be maintained through altered species interactions. These findings add to the discussion of how natural food webs react to environmental change and imply that the range of potential ecosystem dynamics in response to perturbations can be wider and more complex than is often recognized.     

Ecological and evolutionary responses in complex communities: implications for invasions and eco‐evolutionary feedbacks

It is easier to predict the ecological and evolutionary outcomes of interactions in less diverse communities. As species are added to communities, their direct and indirect interactions multiply, their niches may shift, and there may be increased ecological redundancy. Accompanying this complexity in ecological interactions, is also complexity in selection and subsequent evolution, which may feed back to affect the ecology of the system, as species with different traits may play different ecological roles. Drawing from my own work and that of many others, I first discuss what we currently understand about ecology and evolution in light of simple and diverse communities, and suggest the importance of escape from community complexity per se in the success of invaders. Then, I examine how community complexity may influence the nature and magnitude of eco‐evolutionary feedbacks, classifying eco‐evolutionary dynamics into three general types: those generating alternative stable states, cyclic dynamics, and those maintaining ecological stasis and stability. The latter may be important and yet very hard to detect. I suggest future directions, as well as discuss methodological approaches and their potential pitfalls, in assessing the importance and longevity of eco‐evolutionary feedbacks in complex communities. Synthesis The ecology, evolution and eco‐evolutionary dynamics of simple and diverse communities are reviewed. In more diverse communities, direct and indirect interactions multiply, species’ niches often shift, ecological redundancy can increase, and selection may be less directional. Community complexity may influence the magnitude and nature of eco‐evolutionary dynamics, which are classified into three types: those generating alternative stable states, cyclic dynamics, and those maintaining ecological stasis and stability. Strengths and pitfalls of approaches to investigating eco‐evolutionary feedbacks in complex field communities are discussed.     

Size hierarchy and stability in competitive plant populations

A neighbourhood-based competition model for plant individuals is studied to evaluate how a hierarchical structure related to size may emerge in plant communities. It is shown by numerical simulations and linear stability analysis that many stable states exist in the hierarchical structure when both the total number of individuals and the degree of asymmetry of competition are high. When the hierarchical structures are self-organized by the dynamic instability of the homogeneous state due to non-linearity of competition, it is proved that these states are always locally stable. The relevance of the results to size structures in real plant communities (boreal forests vs tropical and temperate forests) is discussed. This is suggested to be the mechanism responsible for the coexistence of species in plant communities.     

Planktonic ciliate community structure in shallow lakes of lowland Western Europe

Temperate shallow meso- to eutrophic lakes can exist in one of two alternative states with contrasting foodwebs, referred to as the clear-water and the turbid state. We describe the planktonic ciliate communities of such lakes based on a survey of 66 northwestern European lakes. Ciliates were enumerated and identified to species level according to the quantitative protargol staining technique. Ciliate biomass was on average twice as high in the turbid than in the clear-water lakes. The ciliate communities were dominated by oligotrichs and protostomatids, and no differences in functional composition or α-diversity could be detected between turbid and clear-water lakes, although β-diversity tended to be higher in the latter. At the species level, however, community structure strongly differed between turbid and clear-water lakes, and several indicator species could be identified for the different lake categories. Variation partitioning showed that nutrient status did not explain ciliate community structure independent of the alternative states, while lake area was identified as an additional structuring factor for the ciliate communities. These results stress the importance of the ecosystem structure in shaping ciliate communities in temperate shallow lakes and suggest that nutrient status has little direct effect on ciliate community structure in such lakes.     

The Scaling of Host Density with Richness Affects the Direction,Shape, and Detectability of Diversity-Disease Relationships

Pathogen transmission responds differently to host richness and abundance, two unique components of host diversity. However, the heated debate around whether biodiversity generally increases or decreases disease has not considered the relationships between host richness and abundance that may exist in natural systems. Here we use a multi-species model to study how the scaling of total host community abundance with species richness mediates diversity-disease relationships. For pathogens with density-dependent transmission, non-monotonic trends emerge between pathogen transmission and host richness when host community abundance saturates with richness. Further, host species identity drives high variability in pathogen transmission in depauperate communities, but this effect diminishes as host richness accumulates. Using simulation we show that high variability in low richness communities and the non-monotonic relationship observed with host community saturation may reduce the detectability of trends in empirical data. Our study emphasizes that understanding the patterns and predictability of host community composition and pathogen transmission mode will be crucial for predicting where and when specific diversity-disease relationships should occur in natural systems.     

Catastrophic regime shifts in coral communities exposed to physical disturbances: Simulation results from object-oriented 3-dimensional coral reef model

A 3-dimensional individual-based model, the ReefModel, was developed to simulate the dynamical structure of coral reef community using object-oriented techniques. Interactions among functional groups of reef organisms were simulated in the model. The behaviours of these organisms were described with simple mechanistic rules that were derived from their general behaviours (e.g. growing habits, competitive mechanisms, response to physical disturbance) observed in natural coral reef communities. The model was implemented to explore the effects of physical disturbance on the dynamical structure of a 3-coral community that was characterized with three functional coral groups: tabular coral, foliaceous coral and massive coral. Simulation results suggest that (i) the integration of physical disturbance and differential responses (disturbance sensitivity and growing habit) of corals plays an important role in structuring coral communities; (ii) diversity of coral communities can be maximal under intermediate level of acute physical disturbance; (iii) multimodality exists in the final states and dynamic regimes of individual coral group as well as coral community structure, which results from the influence of small random spatial events occurring during the interactions among the corals in the community, under acute and repeated physical disturbances. These results suggest that alternative stable states and catastrophic regime shifts may exist in a coral community under unstable physical environment.     

Identifying and evaluating causes of alternative community states in wetland plant communities

Ecological communities can vary greatly in species composition. Often this variation is discontinuous, in that abrupt changes in composition occur over small distances in space or short periods of time. A wide range of hypotheses from different subfields of ecology have been proposed to explain these patterns. I suggest a framework to quantitatively evaluate these hypotheses with observational data by characterizing 1) how community composition varies across sites in space, 2) how community composition varies through time, and 3) the possible drivers of this variation. I applied this approach to understand the community composition of producers in temporary and semipermanent wetlands in Michigan, USA. I identified several distinct community states which were variously dominated by particular plant functional groups (submerged, floating or emergent plants) or had no plants throughout a season. Evaluating possible hypotheses to explain this variation, I found that similar communities were not necessarily clustered near each other, suggesting that dispersal was not limited for these plants. Some sites exhibited a great deal of change in plant composition among years, shifting between two community states, but there was relatively little change at sites within a year. Moreover, these shifts did not occur in a particular order to suggest directional change or repeating cycles. Community composition was associated with several environmental variables such as pH, light and depth, and multivariate analyses suggested that species had complex, nonlinear responses to these possible drivers. Alternative stable states and interactions among multiple nonlinear drivers best explained the patterns observed in these wetlands. By formalizing initial data collection in other systems with the framework suggested here, we may gain insight into the causes of alternative community states beyond wetlands and the role of climate change and other anthropogenic forces in precipitating transitions between states.     

A conceptual model of plant community changes following cessation of cultivation in semi‐arid grassland

Question: Can vegetation changes that occur following cessation of cultivation for cereal crop production in semi‐arid native grasslands be described using a conceptual model that explains plant community dynamics following disturbance? Location: Eighteen native grasslands with varying time‐since‐last cultivation across northern Victoria, Australia. Methods: We examined recovery of native grasslands after cessation of cultivation along a space for‐ time chronosequence. By documenting floristic composition and soil properties of grasslands with known cultivation histories, we established a conceptual model of the vegetation states that occur following cessation of cultivation and inferred transition pathways for community recovery. Results: Succession from an exotic‐dominated grassland to native grassland followed a linear trajectory. These changes represent an increase in richness and cover of native forbs, a decrease in cover of exotic annual species and little change in native perennial graminoids and exotic perennial forbs. Using a state‐and‐transition model, two distinct vegetation states were evident: (1) an unstable, recently cultivated state, dominated by exotic annuals, and (2) a more diverse, stable state. The last‐mentioned state can be divided into two further states based on species composition: (1) a never‐cultivated state dominated by native perennial shrubs and grasses, and (2) a long‐uncultivated state dominated by a small number of native perennial and native and exotic annual species that is best described as a subset of the never‐cultivated state. Transitions between these states are hypothesized to be dependent upon landscape context, seed availability and soil recovery. Conclusions: Legacies of past land use on soils and vegetation of semi‐arid grasslands are not as persistent as in other Australian communities. Recovery appears to follow a linear, directional model of post‐disturbance regeneration which may be advanced by overcoming dispersal barriers hypothesised to restrict recovery.     

Nested species interactions promote feasibility over stability during the assembly of a pollinator community

The foundational concepts behind the persistence of ecological communities have been based on two ecological properties: dynamical stability and feasibility. The former is typically regarded as the capacity of a community to return to an original equilibrium state after a perturbation in species abundances and is usually linked to the strength of interspecific interactions. The latter is the capacity to sustain positive abundances on all its constituent species and is linked to both interspecific interactions and species demographic characteristics. Over the last 40 years, theoretical research in ecology has emphasized the search for conditions leading to the dynamical stability of ecological communities, while the conditions leading to feasibility have been overlooked. However, thus far, we have no evidence of whether species interactions are more conditioned by the community''s need to be stable or feasible. Here, we introduce novel quantitative methods and use empirical data to investigate the consequences of species interactions on the dynamical stability and feasibility of mutualistic communities. First, we demonstrate that the more nested the species interactions in a community are, the lower the mutualistic strength that the community can tolerate without losing dynamical stability. Second, we show that high feasibility in a community can be reached either with high mutualistic strength or with highly nested species interactions. Third, we find that during the assembly process of a seasonal pollinator community located at The Zackenberg Research Station (northeastern Greenland), a high feasibility is reached through the nested species interactions established between newcomer and resident species. Our findings imply that nested mutualistic communities promote feasibility over stability, which may suggest that the former can be key for community persistence.     

Generalized Linear Dynamics of a Plant-Parasitic Nematode Population and the Economic Evaluation of Crop Rotations

In 1-year experiments, the final population density of nematodes is usually modeled as a function of initial density. Often, estimation of the parameters is precarious because nematode measurements, although laborious and expensive, are imprecise and the range in initial densities may be small. The estimation procedure can be improved by using orthogonal regression with a parameter for initial density on each experimental unit. In multi-year experiments parameters of a dynamic model can be estimated with optimization techniques like simulated annealing or Bayesian methods such as Markov chain Monte Carlo (MCMC). With these algorithms information from different experiments can be combined. In multi-year dynamic models, the stability of the steady states is an important issue. With chaotic dynamics, prediction of densities and associated economic loss will be possible only on a short timescale. In this study, a generic model was developed that describes population dynamics in crop rotations. Mathematical analysis showed stable steady states do exist for this dynamic model. Using the Metropolis algorithm, the model was fitted to data from a multi-year experiment on Pratylenchus penetrans dynamics with treatments that varied between years. For three crops, parameters for a yield loss assessment model were available and gross margin of the six possible rotations comprising these three crops and a fallow year were compared at the steady state of nematode density. Sensitivity of mean gross margin to changes in the parameter estimates was investigated. We discuss the general applicability of the dynamic rotation model and the opportunities arising from combination of the model with Bayesian calibration techniques for more efficient utilization and collection of data relevant for economic evaluation of crop rotations.     

Alternative community compositional and dynamical states: the dual consequences of assembly history

1. Much work on ecological consequences of community assembly history has focused on the formation of history-induced alternative stable equilibria. We hypothesize that assembly history may affect not only community composition but also population dynamics, with assembled communities differing in species composition potentially residing in different dynamical states. 2. We provided an empirical test of the aforementioned hypothesis using a laboratory microcosm experiment that manipulated both the colonization order of three bacterivorous protist species in the presence of a protist predator and environmental productivity. 3. Both priority effects and random divergence emerged, resulting in two different community compositional states: one characterized by the dominance of one prey species and the other by the extinction of the same prey. While communities in the former state exhibited noncyclic dynamics, the majority of communities in the latter state exhibited cyclic dynamics driven by the interaction between another prey and the predator. 4. Temporal variability of total prey community biovolume consequently differed among communities with different histories. 5. Changing productivity altered priority effects on the structure and dynamics of communities experiencing only certain histories. 6. Our results support the dual (compositional and dynamical) consequences of assembly history and emphasize the importance of incorporating the dynamical view into the field of community assembly.     

Self-recovery of plant communities: examples, mechanisms, and approaches for description

Autogenic (self-recovering) plant communities that need no transitional stages of succession for their recovery after damage are widespread in different areas of the Globe. They are typical for tundras, but also common in boreal forests, alpine belts, deserts and Mediterranean biomes. Such communities usually dominate the landscape. The authors examine in details the communities of cottongrass (Eriophorum vaginatum) wet tussock tundras of North-Eastern Asia and Alaska, the dryad (Dryas punctata) lichen dry patchy tundras of the same region and Scots pine (Pinus sylvestris) lichen-feathermoss forests on fluvial-glacial deposits of Fennoscandia and Russian Plain. Although authogenic plant communities are serial, they exist side by side with proper edaphic variants of climaxes but don't appear to be replaced by the latter, being even more stable. Moreover, they even seem to "compete" for the space with the climax communities. Stabilization of autogenic communities is primarily induced by the impact of abiotic disturbance factors, like periodic fires, permafrost action or scree sliding, and afterwards maintained by several mechanisms of community structure organization. Such mechanisms of self-recovery act at the levels of both plant population and community as a whole. Specific adaptions of dominant species to typical kinds of disturbance (at a scale of either the community, or its local parts) illustrate the first level, whereas close co-adaptations between dominants and accompanying species refer to the second one. Such co-adaptations are present as complementarity of plant life strategies and growth forms within a community and/or as a shifting-mosaic steady state which leads to quick recovery of local disturbances. Among different possible approaches to simulation of community autogenesis those of combinatorial simulation seem to be especially perspective.     

Optimizing the Detection of Wakeful and Sleep-Like States for Future Electrocorticographic Brain Computer Interface Applications

Previous studies suggest stable and robust control of a brain-computer interface (BCI) can be achieved using electrocorticography (ECoG). Translation of this technology from the laboratory to the real world requires additional methods that allow users operate their ECoG-based BCI autonomously. In such an environment, users must be able to perform all tasks currently performed by the experimenter, including manually switching the BCI system on/off. Although a simple task, it can be challenging for target users (e.g., individuals with tetraplegia) due to severe motor disability. In this study, we present an automated and practical strategy to switch a BCI system on or off based on the cognitive state of the user. Using a logistic regression, we built probabilistic models that utilized sub-dural ECoG signals from humans to estimate in pseudo real-time whether a person is awake or in a sleep-like state, and subsequently, whether to turn a BCI system on or off. Furthermore, we constrained these models to identify the optimal anatomical and spectral parameters for delineating states. Other methods exist to differentiate wake and sleep states using ECoG, but none account for practical requirements of BCI application, such as minimizing the size of an ECoG implant and predicting states in real time. Our results demonstrate that, across 4 individuals, wakeful and sleep-like states can be classified with over 80% accuracy (up to 92%) in pseudo real-time using high gamma (70–110 Hz) band limited power from only 5 electrodes (platinum discs with a diameter of 2.3 mm) located above the precentral and posterior superior temporal gyrus.     

Environmental predictability of taxonomic and functional community composition in high‐latitude streams

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