Bacterial diversity stabilizes community productivity

Background

Stability is a crucial ecosystem feature gaining particular importance in face of increasing anthropogenic stressors. Biodiversity is considered to be a driving biotic force maintaining stability, and in this study we investigate how different indices of biodiversity affect the stability of communities in varied abiotic (composition of available resources) and biotic (invasion) contexts.

Methodology/Principal Findings

We set up microbial microcosms to study the effects of genotypic diversity on the reliability of community productivity, defined as the inverse of the coefficient of variation of across-treatment productivity, in different environmental contexts. We established a bacterial diversity gradient ranging from 1 to 8 Pseudomonas fluorescens genotypes and grew the communities in different resource environments or in the presence of model invasive species. Biodiversity significantly stabilized community productivity across treatments in both experiments. Path analyses revealed that different aspects of diversity determined stability: genotypic richness stabilized community productivity across resource environments, whereas functional diversity determined stability when subjected to invasion.

Conclusions/Significance

Biodiversity increases the stability of microbial communities against both biotic and abiotic environmental perturbations. Depending on stressor type, varying aspects of biodiversity contribute to the stability of ecosystem functions. The results suggest that both genetic and functional diversity need to be preserved to ensure buffering of communities against abiotic and biotic stresses.     

Random ecological systems with structure: Stability-complexity relationship

We have numerically examined more than one million Large Complex Systems (LCS) of interacting variables (interpretable as interacting populations) governed by Generalized Lotka-Volterra Equations (GLV), with self-regulation term. The scope was to have some insight on the stability-complexity relationship. We considered systems of prey-predator type, and we gave appropriate rules for constructing the model systems, rules that specify the behaviour of model systems in order to put them near the biological reality. The results show, among other things, a strict correlation between the stability and the prey-predator ratio (which, in our model, uniquely determines the connectedness of the system).     

On the generality of stability-complexity relationships in Lotka-Volterra ecosystems

Understanding how complexity persists in nature is a long-standing goal of ecologists. In theoretical ecology, local stability is a widely used measure of ecosystem persistence and has made a major contribution to the ecosystem stability-complexity debate over the last few decades. However, permanence is coming to be regarded as a more satisfactory definition of ecosystem persistence and has relatively recently become available as a tool for assessing the global stability of Lotka-Volterra communities. Here we document positive relationships between permanence and Lotka-Volterra food web complexity and report a positive correlation between the probability of local stability and permanence. We investigate further the frequency of discrepancy (attributed to fragile systems that are locally stable but not permanent or locally unstable systems that are permanent and have cyclic or chaotic dynamics), associate non-permanence with the local stability or instability of equilibria on the boundary of the state-space, and investigate how these vary with aspects of ecosystem complexity. We find that locally stable interior equilibria tend to have all locally unstable boundary equilibria. Since a locally stable boundary is inconsistent with permanent dynamics, this can explain the observed positive correlation between local interior stability and permanence. Our key finding is that, at least in Lotka-Volterra model ecosystems, local stability may be a better measure of persistence than previously thought.     

Quantifying Ecological Stability: From Community to the Lake Ecosystem

We performed a methodological study aimed at extending our previously developed approach to quantify the ecological stability of biotic communities and an entire ecosystem, using Lake Kinneret as a case study. The ecological stability of the biotic communities (phytoplankton and zooplankton) of Lake Kinneret was estimated using two different aggregating schemes. The first scheme used the combined stability index, based on the combined indices of the individual phytoplankton (SI[Comb]_P) and zooplankton (SI[Comb]_Z) taxonomic groups. The total community stability index was calculated based on the total abundances of these communities. The stability of the entire ecosystem was estimated for two sets of ecosystem state variables, a lake “trophic state” set and a “water quality” set, which provided considerably different estimates of the lake ecosystem stability. Good agreement between the results of this study and qualitative estimates of Lake Kinneret stability validates the suitability of this approach to estimate the stability of different ecological units.     

Stability patterns and trophic structure in a Delaware Bay plankton community.

Using qualitative loop analysis we have extended our examination of a Delaware Bay plankton community to include an investigation of the roles played by the various entities (population, guild or nutrient) in the community. In an entity removal exercise, we used stability relationships as a probe into community structure. Six types of stability change are possible as a result of entity removal from the system: stable to stable (s-->s); stable to unstable (s-->u); stable to disconnected (s-->d); unstable to stable (u-->s); unstable to unstable (u-->u); unstable to disconnected (u-->d). Using these changes as an investigative tool, we found that in order to account for the stability-instability patterns, it was necessary to construct a refined trophic structure model. The observed connections between the entities in the larger model could be grouped into two different types of stability substructures: a simple pattern and a more complex branching pattern. These patterns map easily onto the refined trophic structure model. Using stability analysis it is also possible to model community structure in ways other than the traditional trophic approach. Patterns of system necessity and relative contribution to stability are observed. These patterns match the refined trophic structure model derived previously. The roles that the various entities play in the overall community were followed over an annual cycle. Entities were seen to change their roles as a function of time and status within a subgroup. These results show that stability determinations have the potential to be used as a valuable tool in community analysis.     

Complexity does not affect stability in feasible model communities

The complexity-stability relation is a central issue in ecology. In this paper, we show how the sampling method most often used to parameterize an ecological community, can affect the conclusions about whether or not complexity promotes stability and we suggest a sampling algorithm that overcomes the problem. We also illustrate the importance of treating feasibility separately from stability when constructing model communities. Using model Lotka-Volterra competition communities we found that probability of feasibility decreases with increasing interaction strength and number of species in the community. However, for feasible systems we found that local stability probability and resilience do not significantly differ between communities with few or many species, in contrast with earlier studies that, did not account for feasibility and concluded that species-poor communities had higher probability of being locally stable than species-rich communities.     

Disturbance Frequency and Community Stability in Native Tallgrass Prairie

Ecological communities are spatially and temporally variable in response to a variety of biotic and abiotic forces. It is not always clear, however, if spatial and temporal variability leads to instability in communities. Instability may result from strong biotic interactions or from stochastic processes acting on small populations. I used 10-15 yr of annual data from the Konza Prairie Long-Term Ecological Research site to examine whether plant, breeding bird, grasshopper, and small mammal communities in tallgrass prairie exhibit stability or directional change in response to different experimentally induced fire frequencies. Based on ordination and ANOVA, plant and grasshopper communities on annually burned sites differed significantly from plant and grasshopper communities on less frequently burned sites. Breeding birds and small mammals differed among sites as well, but these differences were not clearly related to disturbance frequency. A modified time series analysis indicated that plant communities were undergoing directional change (unstable) on all watersheds, regardless of fire frequency. Contrary to expectations, directional change was greatest on the annually burned sites and lowest on the infrequently burned sites. Unlike the plant communities, breeding bird, grasshopper, and small mammal communities were temporally stable, despite high-compositional variability from 1 yr to the next. Stability among the consumer communities within these dynamic plant communities occurs because three-dimensional vegetation structure does not change over time, despite changes in plant species composition. Evidence suggests that instability in the plant community results from strong biotic interactions among temporally persistent core species and stochastic dynamics among infrequent satellite species. Overall, community stability cannot be assessed if the pattern of temporal dynamics is unknown. Long-term empirical studies of different taxa under different disturbance regimes are needed to determine over what time frames and spatial scales communities may be stable. Such studies are essential for the development of generalities regarding the relationship between disturbance frequency and community stability in terrestrial and aquatic systems.     

Unraveling negative biotic interactions determining soil microbial community assembly and functioning

Microbial communities play important roles in all ecosystems and yet a comprehensive understanding of the ecological processes governing the assembly of these communities is missing. To address the role of biotic interactions between microorganisms in assembly and for functioning of the soil microbiota, we used a top-down manipulation approach based on the removal of various populations in a natural soil microbial community. We hypothesized that removal of certain microbial groups will strongly affect the relative fitness of many others, therefore unraveling the contribution of biotic interactions in shaping the soil microbiome. Here we show that 39% of the dominant bacterial taxa across treatments were subjected to competitive interactions during soil recolonization, highlighting the importance of biotic interactions in the assembly of microbial communities in soil. Moreover, our approach allowed the identification of microbial community assembly rule as exemplified by the competitive exclusion between members of Bacillales and Proteobacteriales. Modified biotic interactions resulted in greater changes in activities related to N- than to C-cycling. Our approach can provide a new and promising avenue to study microbial interactions in complex ecosystems as well as the links between microbial community composition and ecosystem function.Subject terms: Soil microbiology, Ecology     

H. A. GLEASON'S 'INDIVIDUALISTIC CONCEPT' AND THEORY OF ANIMAL COMMUNITIES: A CONTINUING CONTROVERSY

A tradition of natural history and of the lore of early twentieth-century ecology was that organisms lived together and interacted to form natural entities or communities. Before there was a recognizable science of ecology, Mobius (1877) had provided a name ‘biocoenosis’ for such entities. This concept persisted in the early decades of ecological science; at an extreme it was maintained that the community had integrating capabilities and organization like those of an individual organism, hence the term organismic community. In the 1950s- 1970s an alternative individualist concept, derived from the ideas of H. A. Gleason (1939), gained credence which held that communities were largely a coincidence of individualistic species characteristics, continuously varying environments and different probabilities of a species arriving on a given site. During the same period, however, a body of population based theory of animal communities became dominant which perpetuated the idea of patterns in nature based on biotic interactions among species resulting in integrated communities. This theory introduced an extended terminology and mathematical models to explain the organization of species into groups of compatible species governed by rules. In the late 1970s the premises and methods of the theory came under attack and a vigorous debate ensued. The alternatives proposed were, at an extreme, null models of random aggregations of species or stochastic, individualistic aggregations of species, sensu Gleason. Extended research and debate ensued during the 1980s resulting in an explosion of studies of animal communities and a plethora of symposia and volumes of collected works concerning the nature of animal communities. The inherent complexity of communities and the traditional differences among animal ecologists about how they should be defined and delimited, at what scale of taxa, space and time to study them, and appropriate methods of study and analysis have resulted in extended and as yet inconclusive discussions. Recent differences and discussions are considered under five general categories, evolution and community theory, individualistic concept, community definition, questions from community ecology and empirical studies. Communities are seen by some ecologists as entities of coevolving species and, in any case, it is necessary to integrate evolutionary ideas with the varied concepts of community. The individualistic concept of community, as a relative latecomer to discussions of animal community, is sometimes misconstrued as holding that communities are random assemblages of organisms without biotic interactions among species. Nevertheless, it has increasingly been accepted as supported by studies of diverse taxa and habitats. However, many other ecologists continue to argue for integrated, biotically controlled and evolved communities. Among the major difficulties of addressing the problems of community are problems of definition and terminology. One commentator noted that community ecology may be unique in the sciences because there is no consensus definition of community. One consequence of the lack of consensus definition is evident in the varied and diffuse questions posed in studies of community. Some critics of community ecology fault it for posing unanswerable questions. Recent empirical studies include various assessments about community ranging from deterministic, integrated and organismic to individualistic with various suggestions for compromise. The early emphasis on birds in studies of animal communities has expanded to obviate the argument that any position is constrained by the taxon studied. Insects, in general, are more prone to give rise to interpretation of a nonintegrated community. Parasite community studies have given rise to some distinctive categories and terminology. However, consensus is not achieved either within or among taxonomic groups or habitat groups. The extreme heterogeneity and complexity of communities (and of ecologists) has produced extended discussions of how to approach such multidimensional complexity. These discussions often turn on polarized positions of reductionism and experiment versus holism. Proponents of reductionism asserted that natural communities cannot be understood or their structure and organization predicted until experimental communities, or models thereof, are understood. Holists insisted that the inherent complexity and variability of communities cannot be elucidated in simplified experimental communities or in models. A more recent trend has urged pluralism, or, at least, mutual respect and dialogue, which are sometimes lacking, between proponents of these divergent approaches to communities. Recent work perpetuates the original dichotomy between integrated organismic community concept and individualistic non-integrated concept. The hope for a rule-governed community has extended to metarules and a new theory of community as divided into core species and satellite species is called into question. The problems of distinguishing between determinism and chance effects in community organization continue and the lost or fading hope of a general theory of community is revived in a search for rules that govern their assembly.     

Predicting species establishment using absent species and functional neighborhoods

Species establishment within a community depends on their interactions with the local environment and resident community. Such environmental and biotic filtering is frequently inferred from functional trait and phylogenetic patterns within communities; these patterns may also predict which additional species can establish. However, differentiating between environmental and biotic filtering can be challenging, which may complicate establishment predictions. Creating a habitat‐specific species pool by identifying which absent species within the region can establish in the focal habitat allows us to isolate biotic filtering by modeling dissimilarity between the observed and biotically excluded species able to pass environmental filters. Similarly, modeling the dissimilarity between the habitat‐specific species pool and the environmentally excluded species within the region can isolate local environmental filters. Combined, these models identify potentially successful phenotypes and why certain phenotypes were unsuccessful. Here, we present a framework that uses the functional dissimilarity among these groups in logistic models to predict establishment of additional species. This approach can use multivariate trait distances and phylogenetic information, but is most powerful when using individual traits and their interactions. It also requires an appropriate distance‐based dissimilarity measure, yet the two most commonly used indices, nearest neighbor (one species) and mean pairwise (all species) distances, may inaccurately predict establishment. By iteratively increasing the number of species used to measure dissimilarity, a functional neighborhood can be chosen that maximizes the detection of underlying trait patterns. We tested this framework using two seed addition experiments in calcareous grasslands. Although the functional neighborhood size that best fits the community's trait structure depended on the type of filtering considered, selecting these functional neighborhood sizes allowed our framework to predict up to 50% of the variation in actual establishment from seed. These results indicate that the proposed framework may be a powerful tool for studying and predicting species establishment.     

Large-scale biomedical ontology matching with ServOMap

The proliferation of biomedical applications, which rely on different knowledge organization systems, such as ontologies and thesauri raises the issue of the automated identification of the correspondences between these models, in particular for the data integration need. A significant effort has been conducted for tackling this issue of ontology alignment. However, few systems are able to deal with ontologies containing tens of thousands of entities, as it may be the case in the biomedical domain where resources such as SNOMED-CT, the FMA or the NCI thesaurus are commonly used. We present in this paper ServOMap, an efficient system for large-scale ontology alignment. It relies on an Ontology Server (ServO) and uses Information Retrieval techniques for computing similarity between entities. The system participated with two configurations in the 2012 Ontology Alignment Evaluation Initiative campaign. We report the very promising results obtained by the system for large biomedical ontologies alignment. ServOMap is freely available for download at http://code.google.com/p/servo/.     

Diatom Cooccurrence Shows Less Segregation than Predicted from Niche Modeling

Species cooccurrence patterns give significant insights into the processes shaping communities. While biotic interactions have been widely studied using cooccurrence analyses in animals and larger plants, studies about cooccurrences among micro-organisms are still relatively rare. We examined stream diatom cooccurrences in France through a national database of samples. In order to test the relative influence of environmental, biotic and spatial constraints on species’ incidence distribution, cooccurrence and nestedness patterns of real communities were compared with the patterns generated from a set of standard and environmentally constrained null models. Real communities showed a higher level of segregation than the most conservative standard null models, but a general aggregation of cooccurrences when compared to environmentally constrained null models. We did not find any evidence of limiting similarity between cooccurring species. Aggregations of species cooccurrences were associated with the high levels of nestedness. Altogether, these results suggested that biotic interactions were not structuring cooccurrences of diatom species at our study scale. Instead, the patterns were more likely to be related with colonization patterns, mass effect, and local temporal dynamics of diatom biofilms. We further highlight that the association of standard and environmentally constrained null models may give realistic insight into the cooccurrence patterns of microbial communities.     

Integrating Human Health and Environmental Health into the DPSIR Framework: A Tool to Identify Research Opportunities for Sustainable and Healthy Communities

The U.S. Environmental Protection Agency has recently realigned its research enterprise around the concept of sustainability. Scientists from across multiple disciplines have a role to play in contributing the information, methods, and tools needed to more fully understand the long-term impacts of decisions on the social and economic sustainability of communities. Success will depend on a shift in thinking to integrate, organize, and prioritize research within a systems context. We used the Driving forces–Pressures–State–Impact–Response (DPSIR) framework as a basis for integrating social, cultural, and economic aspects of environmental and human health into a single framework. To make the framework broadly applicable to sustainability research planning, we provide a hierarchical system of DPSIR keywords and guidelines for use as a communication tool. The applicability of the integrated framework was first tested on a public health issue (asthma disparities) for purposes of discussion. We then applied the framework at a science planning meeting to identify opportunities for sustainable and healthy communities research. We conclude that an integrated systems framework has many potential roles in science planning, including identifying key issues, visualizing interactions within the system, identifying research gaps, organizing information, developing computational models, and identifying indicators.     

The effects of space and diversity of interaction types on the stability of complex ecological networks

The relationship between structure and stability in ecological networks and the effect of spatial dynamics on natural communities have both been major foci of ecological research for decades. Network research has traditionally focused on a single interaction type at a time (e.g. food webs, mutualistic networks). Networks comprising different types of interactions have recently started to be empirically characterized. Patterns observed in these networks and their implications for stability demand for further theoretical investigations. Here, we employed a spatially explicit model to disentangle the effects of mutualism/antagonism ratios in food web dynamics and stability. We found that increasing levels of plant-animal mutualistic interactions generally resulted in more stable communities. More importantly, increasing the proportion of mutualistic vs. antagonistic interactions at the base of the food web affects different aspects of ecological stability in different directions, although never negatively. Stability is either not influenced by increasing mutualism—for the cases of population stability and species’ spatial distributions—or is positively influenced by it—for spatial aggregation of species. Additionally, we observe that the relative increase of mutualistic relationships decreases the strength of biotic interactions in general within the ecological network. Our work highlights the importance of considering several dimensions of stability simultaneously to understand the dynamics of communities comprising multiple interaction types.     

Environmental drivers of plankton protist communities along latitudinal and vertical gradients in the oldest and deepest freshwater lake

Identifying which abiotic and biotic factors determine microbial community assembly is crucial to understand ecological processes and predict how communities will respond to environmental change. While global surveys aim at addressing this question in the world's oceans, equivalent studies in large freshwater systems are virtually lacking. Being the oldest, deepest and most voluminous freshwater lake on Earth, Lake Baikal offers a unique opportunity to test the effect of horizontal versus vertical gradients in community structure. Here, we characterized the structure of planktonic microbial eukaryotic communities (0.2–30 μm cell size) along a North–South latitudinal gradient (~600 km) from samples collected in coastal and pelagic waters and from surface to the deepest zones (5–1400 m) using an 18S rRNA gene metabarcoding approach. Our results show complex and diverse protist communities dominated by alveolates (ciliates and dinoflagellates), ochrophytes and holomycotan lineages, with cryptophytes, haptophytes, katablepharids and telonemids in moderate abundance and many low-frequency lineages, including several typical marine members, such as diplonemids, syndinians and radiolarians. Depth had a strong significant effect on protist community stratification. By contrast, the effect of the latitudinal gradient was marginal and no significant difference was observed between coastal and surface open water communities. Co-occurrence network analyses showed that epipelagic communities were significantly more interconnected than communities from the dark water column and suggest specific biotic interactions between autotrophic, heterotrophic and parasitic lineages that influence protist community structure. Since climate change is rapidly affecting Siberia and Lake Baikal, our comprehensive protist survey constitutes a useful reference to monitor ongoing community shifts.     

Effects of diversity on diversity: consequences of competition and facilitation

Diversity in one group of species or genotypes is often correlated with diversity in a second group – prominent examples including native vs exotic species, and genetic diversity in a focal species vs species diversity in the rest of the community. I used simulation models to investigate the roles of competition and facilitation among species or genotypes in creating diversity–diversity relationships, with a focus on facilitation, which has received little theoretical attention. When competitive interactions dominate, increasing diversity in one group reduces diversity in the second group via filling of available niche space. Facilitation can create positive diversity–diversity relationships via a sampling effect, whereby a strong facilitator of the second group is more likely to be present as diversity increases in the first group, and also via one group acting as a source of biotic heterogeneity (i.e. diversifying selection) on the second group. However, the biotic heterogeneity effect is expected only under restricted conditions – with asymmetric facilitation, only during a transient period, or only over a small range of species diversity levels – and therefore seems unlikely to operate within trophic levels in natural communities. More generally, the simultaneous operation of competition and facilitation results in several different diversity–diversity relationships and underlying mechanisms. The results clarify the potential roles of positive and negative interactions in creating diversity–diversity relationships, and in determining the outcome of community dynamics in general. This study also highlights some important difficulties in incorporating facilitation into ecological theory for communities with many species.     

Key Edaphic Properties Largely Explain Temporal and Geographic Variation in Soil Microbial Communities across Four Biomes

Soil microbial communities play a critical role in nutrient transformation and storage in all ecosystems. Quantifying the seasonal and long-term temporal extent of genetic and functional variation of soil microorganisms in response to biotic and abiotic changes within and across ecosystems will inform our understanding of the effect of climate change on these processes. We examined spatial and seasonal variation in microbial communities based on 16S rRNA gene sequencing and phospholipid fatty acid (PLFA) composition across four biomes: a tropical broadleaf forest (Hawaii), taiga (Alaska), semiarid grassland-shrubland (Utah), and a subtropical coniferous forest (Florida). In this study, we used a team-based instructional approach leveraging the iPlant Collaborative to examine publicly available National Ecological Observatory Network (NEON) 16S gene and PLFA measurements that quantify microbial diversity, composition, and growth. Both profiling techniques revealed that microbial communities grouped strongly by ecosystem and were predominately influenced by three edaphic factors: pH, soil water content, and cation exchange capacity. Temporal variability of microbial communities differed by profiling technique; 16S-based community measurements showed significant temporal variability only in the subtropical coniferous forest communities, specifically through changes within subgroups of Acidobacteria. Conversely, PLFA-based community measurements showed seasonal shifts in taiga and tropical broadleaf forest systems. These differences may be due to the premise that 16S-based measurements are predominantly influenced by large shifts in the abiotic soil environment, while PLFA-based analyses reflect the metabolically active fraction of the microbial community, which is more sensitive to local disturbances and biotic interactions. To address the technical issue of the response of soil microbial communities to sample storage temperature, we compared 16S-based community structure in soils stored at -80°C and -20°C and found no significant differences in community composition based on storage temperature. Free, open access datasets and data sharing platforms are powerful tools for integrating research and teaching in undergraduate and graduate student classrooms. They are a valuable resource for fostering interdisciplinary collaborations, testing ecological theory, model development and validation, and generating novel hypotheses. Training in data analysis and interpretation of large datasets in university classrooms through project-based learning improves the learning experience for students and enables their use of these significant resources throughout their careers.     

The effect of seasonal variation in abiotic factors on fish community structure in temporary and permanent pools in a tropical wetland

1. Fish community structure depends on biotic interactions and abiotic variables. Abiotic variables appear to gain importance in highly variable freshwater systems, such as tropical wetlands where a marked seasonal hydroperiod (dry and wet seasons) modifies water quality and quantity, differentially affecting fish survival and, consequently, modifying species richness and abundance. 2. We evaluated the relationship between abiotic variables and fish community structure in variable (temporary) and stable (permanent) pools that were interconnected in a tropical wetland with marked annual dry and wet seasons. 3. All fish species were able to occupy any of the studied pools, but our results showed distinctive fish community structures in permanent and temporary pools. Community structure was related to temperature, depth, pH and macrophyte coverage. Total fish abundance in the wetland was negatively related to water depth and positively related to macrophyte coverage. 4. Null models of co‐occurrence indicated a non‐random pattern at the wetland scale and a random pattern within groups of pools with similar characteristics, suggesting that fish communities are structured according to habitat features. We conclude that seasonal abiotic variation and habitat characteristics in this highly variable pristine wetland play major roles in structuring fish communities.