Regional species pools control community saturation in lake phytoplankton

Recent research has highlighted that positive biodiversity–ecosystem functioning relationships hold for all groups of organisms, including microbes. Yet, we still lack understanding regarding the drivers of microbial diversity, in particular, whether diversity of microbial communities is a matter of local factors, or whether metacommunities are of similar importance to what is known from higher organisms. Here, we explore the driving forces behind spatial variability in lake phytoplankton diversity in Fennoscandia. While phytoplankton biovolume is best predicted by local phosphorus concentrations, phytoplankton diversity (measured as genus richness, G) only showed weak correlations with local concentrations of total phosphorus. By estimating spatial averages of total phosphorus concentrations on various scales from an independent, spatially representative lake survey, we found that close to 70 per cent of the variability in local phytoplankton diversity can be explained by regionally averaged phosphorus concentrations on a scale between 100 and 400 km. Thus, the data strongly indicate the existence of metacommunities on this scale. Furthermore, we show a strong dependency between lake productivity and spatial community turnover. Thus, regional productivity affects beta-diversity by controlling spatial community turnover, resulting in scale-dependent productivity-diversity relationships. As an illustration of the interaction between local and regional processes in shaping microbial diversity, our results offer both empirical support and a plausible mechanism for the existence of common scaling rules in both the macrobial and the microbial worlds. We argue that awareness of regional species pools in phytoplankton and other unicellular organisms may critically improve our understanding of ecosystems and their susceptibility to anthropogenic stressors.     

Abiotic drivers and plant traits explain landscape‐scale patterns in soil microbial communities

The controls on aboveground community composition and diversity have been extensively studied, but our understanding of the drivers of belowground microbial communities is relatively lacking, despite their importance for ecosystem functioning. In this study, we fitted statistical models to explain landscape‐scale variation in soil microbial community composition using data from 180 sites covering a broad range of grassland types, soil and climatic conditions in England. We found that variation in soil microbial communities was explained by abiotic factors like climate, pH and soil properties. Biotic factors, namely community‐weighted means (CWM) of plant functional traits, also explained variation in soil microbial communities. In particular, more bacterial‐dominated microbial communities were associated with exploitative plant traits versus fungal‐dominated communities with resource‐conservative traits, showing that plant functional traits and soil microbial communities are closely related at the landscape scale.     

Relating belowground microbial composition to the taxonomic,phylogenetic, and functional trait distributions of trees in a tropical forest

The complexities of the relationships between plant and soil microbial communities remain unresolved. We determined the associations between plant aboveground and belowground (root) distributions and the communities of soil fungi and bacteria found across a diverse tropical forest plot. Soil microbial community composition was correlated with the taxonomic and phylogenetic structure of the aboveground plant assemblages even after controlling for differences in soil characteristics, but these relationships were stronger for fungi than for bacteria. In contrast to expectations, the species composition of roots in our soil core samples was a poor predictor of microbial community composition perhaps due to the patchy, ephemeral, and highly overlapping nature of fine root distributions. Our ability to predict soil microbial composition was not improved by incorporating information on plant functional traits suggesting that the most commonly measured plant traits are not particularly useful for predicting the plot‐level variability in belowground microbial communities.     

Partitioning the effects of species loss on community variability using multi‐level selection theory

The temporal variability of ecological communities may depend on species richness and composition due to a variety of statistical and ecological mechanisms. However, ecologists currently lack a general, unified theoretical framework within which to compare the effects of these mechanisms. Developing such a framework is difficult because community variability depends not just on how species vary, but also how they covary, making it unclear how to isolate the contributions of individual species to community variability. Here I develop such a theoretical framework using the multi‐level Price equation, originally developed in evolutionary biology to partition the effects of group selection and individual selection. I show how the variability of a community can be related to the properties of the individual species comprising it, just as the properties of an evolving group can be related to the properties of the individual organisms comprising it. I show that effects of species loss on community variability can be partitioned into effects of species richness (random loss of species), effects of species composition (non‐random loss of species with respect to their variances and covariances), and effects of context dependence (post‐loss changes in species’ variances and covariances). I illustrate the application of this framework using data from the Biodiversity II experiment, and show that it leads to new conceptual and empirical insights. For instance, effects of species richness on community variability necessarily occur, but often are swamped by other effects, particularly context dependence.     

Matrix type alters structure of aquatic vertebrate assemblages in cypress domes

Management of communities in fragmented systems requires application of models for predicting and understanding patterns of diversity at relevant scales. Metacommunity models may help explain patterns of beta-diversity, but more empirical investigations are needed to determine the generality of these models and the importance of matrix identity as a mediator of metacommunity processes. We studied patterns of beta diversity among cypress domes in a landscape composed of two different matrix types within Big Cypress National Preserve to determine whether community composition differed by matrix type and to evaluate predictions of metacommunity models. We sampled fully-aquatic vertebrates in 16 cypress domes. A causal modeling framework was used to assess the relative importance of space and environmental variables measured in the domes and in the nearby matrix in explaining variation in community similarities. Our results show that community composition was influenced by matrix type, which violates the common metacommunity assumption that matrix identity has negligible effect on patch patterns. We found different drivers of beta-diversity patterns between matrix types; similarities among dome communities within cypress-prairie matrix were influenced by local environmental conditions and matrix characteristics, while communities in pine-rockland domes were most influenced by conditions in the matrix. Our results have implications for use of metacommunity models in conservation planning and we suggest that future research should focus on the importance of matrix identity and complexity in mediating community patterns in patchy landscapes.     

Measuring community responses to large-scale disturbance in conservation biogeography

Aim   Which community metrics should be used to reflect community response to large-scale habitat alterations is unclear. Here, we assess what and how community changes should be measured to accurately track community responses to large-scale disturbance in space and/or time.
Location   France.
Method   We first developed a simulation model to examine temporal changes in the species composition of large-scale metacommunities. Using this model, we assessed how species richness, Shannon index, trends of particular subset of species or community indices of habitat specialization were influenced by different disturbance scenarios, and whether these indices were biased by imperfect detectability. We further used more than 1000 empirical bird communities from the French Breeding Bird Survey recently exposed to disturbances of various intensities as a case study.
Results   Our simulation and empirical results both demonstrate that species richness and diversity measures can show confusing trends and even provide misleading messages of communities' fate. In contrast, reflecting the composition of the community in terms of habitat specialist and generalist species was more robust and powerful to reflect disturbance effects.
Main conclusions   We highlight the weakness of using community metrics that fail to incorporate ecological difference among species when summarizing community-level trends in disturbed landscapes.     

Understanding diversity–stability relationships: towards a unified model of portfolio effects

A major ecosystem effect of biodiversity is to stabilise assemblages that perform particular functions. However, diversity–stability relationships (DSRs) are analysed using a variety of different population and community properties, most of which are adopted from theory that makes several restrictive assumptions that are unlikely to be reflected in nature. Here, we construct a simple synthesis and generalisation of previous theory for the DSR. We show that community stability is a product of two quantities: the synchrony of population fluctuations, and an average species‐level population stability that is weighted by relative abundance. Weighted average population stability can be decomposed to consider effects of the mean‐variance scaling of abundance, changes in mean abundance with diversity and differences in species' mean abundance in monoculture. Our framework makes explicit how unevenness in the abundances of species in real communities influences the DSR, which occurs both through effects on community synchrony, and effects on weighted average population variability. This theory provides a more robust framework for analysing the results of empirical studies of the DSR, and facilitates the integration of findings from real and model communities.     

Global dynamics of microbial communities emerge from local interaction rules

Most microbes live in spatially structured communities (e.g., biofilms) in which they interact with their neighbors through the local exchange of diffusible molecules. To understand the functioning of these communities, it is essential to uncover how these local interactions shape community-level properties, such as the community composition, spatial arrangement, and growth rate. Here, we present a mathematical framework to derive community-level properties from the molecular mechanisms underlying the cell-cell interactions for systems consisting of two cell types. Our framework consists of two parts: a biophysical model to derive the local interaction rules (i.e. interaction range and strength) from the molecular parameters underlying the cell-cell interactions and a graph based model to derive the equilibrium properties of the community (i.e. composition, spatial arrangement, and growth rate) from these local interaction rules. Our framework shows that key molecular parameters underlying the cell-cell interactions (e.g., the uptake and leakage rates of molecules) determine community-level properties. We apply our model to mutualistic cross-feeding communities and show that spatial structure can be detrimental for these communities. Moreover, our model can qualitatively recapitulate the properties of an experimental microbial community. Our framework can be extended to a variety of systems of two interacting cell types, within and beyond the microbial world, and contributes to our understanding of how community-level properties emerge from microscopic interactions between cells.     

Species dynamics alter community diversity–biomass stability relationships

The relationship between community diversity and biomass variability remains a crucial ecological topic, with positive, negative and neutral diversity–stability relationships reported from empirical studies. Theory highlights the relative importance of Species–Species or Species–Environment interactions in driving diversity–stability patterns. Much previous work is based on an assumption of identical (stable) species‐level dynamics. We studied ecosystem models incorporating stable, cyclic and more complex species‐level dynamics, with either linear or non‐linear density dependence, within a locally stable community framework. Species composition varies with increasing diversity, interacting with the correlation of species' environmental responses to drive either positive or negative diversity–stability patterns, which theory based on communities with only stable species‐level dynamics fails to predict. Including different dynamics points to new mechanisms that drive the full range of diversity–biomass stability relationships in empirical systems where a wider range of dynamical behaviours are important.     

Sparse and Compositionally Robust Inference of Microbial Ecological Networks

16S ribosomal RNA (rRNA) gene and other environmental sequencing techniques provide snapshots of microbial communities, revealing phylogeny and the abundances of microbial populations across diverse ecosystems. While changes in microbial community structure are demonstrably associated with certain environmental conditions (from metabolic and immunological health in mammals to ecological stability in soils and oceans), identification of underlying mechanisms requires new statistical tools, as these datasets present several technical challenges. First, the abundances of microbial operational taxonomic units (OTUs) from amplicon-based datasets are compositional. Counts are normalized to the total number of counts in the sample. Thus, microbial abundances are not independent, and traditional statistical metrics (e.g., correlation) for the detection of OTU-OTU relationships can lead to spurious results. Secondly, microbial sequencing-based studies typically measure hundreds of OTUs on only tens to hundreds of samples; thus, inference of OTU-OTU association networks is severely under-powered, and additional information (or assumptions) are required for accurate inference. Here, we present SPIEC-EASI (SParse InversE Covariance Estimation for Ecological Association Inference), a statistical method for the inference of microbial ecological networks from amplicon sequencing datasets that addresses both of these issues. SPIEC-EASI combines data transformations developed for compositional data analysis with a graphical model inference framework that assumes the underlying ecological association network is sparse. To reconstruct the network, SPIEC-EASI relies on algorithms for sparse neighborhood and inverse covariance selection. To provide a synthetic benchmark in the absence of an experimentally validated gold-standard network, SPIEC-EASI is accompanied by a set of computational tools to generate OTU count data from a set of diverse underlying network topologies. SPIEC-EASI outperforms state-of-the-art methods to recover edges and network properties on synthetic data under a variety of scenarios. SPIEC-EASI also reproducibly predicts previously unknown microbial associations using data from the American Gut project.     

Relationship of Farm Level Pesticide Use and Physical Habitat on Benthic Community Status in a California Agricultural Stream

The objectives of this study were to: (1) evaluate temporal and spatial trends in water quality parameters, physical habitat metrics, and benthic community metrics in the Orestimba Creek from years 2000 to 2005, and (2) assess the relationship of benthic community condition from ten Orestimba Creek stations and both pesticide use at the farm level and physical habitat conditions. Significant year effects were reported for temperature, pH, dissolved oxygen, and turbidity. In general, most of the 17 physical habitat metrics did not show statistical variability over the 6-year period. Most of the benthic metrics were variable over the 6-year period. A total of 41 herbicides, 14 organophosphorus (OP) insecticides, and 5 pyrethroids were applied to 23 sections of land bordering the Orestimba Creek from 2000 to 2004. The OP insecticides showed the strongest relationship to benthic metrics using univariate regression models when all three classes of pesticides were compared; however, these statistical relationships had low R² values. Stepwise regression analysis showed statistically significant relationships between most benthic metrics and habitat metrics. In general, both pesticide applications and physical habitat have a similar but modest statistical association with benthic communities. However, the relationship of both pesticide applications and physical habitat on benthic communities in the Orestimba Creek appear to be insignificant compared to the magnitude of spatiotemporal patterns reported.     

An allometric model of home range formation explains the structuring of animal communities exploiting heterogeneous resources

Understanding and predicting the composition and spatial structure of communities is a central challenge in ecology. An important structural property of animal communities is the distribution of individual home ranges. Home range formation is controlled by resource heterogeneity, the physiology and behaviour of individual animals, and their intra‐ and interspecific interactions. However, a quantitative mechanistic understanding of how home range formation influences community composition is still lacking. To explore the link between home range formation and community composition in heterogeneous landscapes we combine allometric relationships for physiological properties with an algorithm that selects optimal home ranges given locomotion costs, resource depletion and competition in a spatially‐explicit individual‐based modelling framework. From a spatial distribution of resources and an input distribution of animal body mass, our model predicts the size and location of individual home ranges as well as the individual size distribution (ISD) in an animal community. For a broad range of body mass input distributions, including empirical body mass distributions of North American and Australian mammals, our model predictions agree with independent data on the body mass scaling of home range size and individual abundance in terrestrial mammals. Model predictions are also robust against variation in habitat productivity and landscape heterogeneity. The combination of allometric relationships for locomotion costs and resource needs with resource competition in an optimal foraging framework enables us to scale from individual properties to the structure of animal communities in heterogeneous landscapes. The proposed spatially‐explicit modelling concept not only allows for detailed investigation of landscape effects on animal communities, but also provides novel insights into the mechanisms by which resource competition in space shapes animal communities.     

Temporal patterns in the stability, persistence and condition of stream macroinvertebrate communities: relationships with catchment land-use and regional climate

1. A spatially‐extensive data set of stream macroinvertebrate communities from 49 northern New Zealand sites sampled over a 10‐year period was analysed to assess relationships between the environment (catchment land‐cover, landscape position and regional‐scale weather patterns), and (i) community persistence and stability based on the constancy of species occurrence (presence–absence) and abundance (per cent composition), respectively and (ii) the temporal variability of various community condition metrics. 2. No significant relationship was evident between community stability or persistence within sites and a gradient of increasing land‐use stress (LUS) based on types of upstream land‐cover, with interannual mean similarities at all sites falling within the standard deviations recorded at long‐term reference sites. In contrast, condition metrics were inversely related to LUS. Land‐use appeared to be a key factor influencing community composition among sites whereas climate influenced stability and persistence within sites. 3. Three response trajectories of community variability to increasing LUS were distinguished based on the coefficient of variation of mean interannual similarities, such that (i) persistence and stability appeared to be more variable at developed sites with low LUS and at sites with high stress relative to the variability experienced naturally, but similar to the natural range at intermediate levels of stress (‘sinusoidal response’); (ii) variability in Ephemeroptera, Plecoptera and Trichoptera metrics increased at low‐to‐moderate stress and then accelerated rapidly at highly developed sites (‘stepped‐exponential response’) and (iii) variability in a pollution tolerance metric increased rapidly and then maintained a similar level of variability along the remaining stress gradient (‘plateau response’). 4. The results of this study have implications for biomonitoring approaches that assume high temporal persistence and stability of communities to define site impairment. Misclassifications caused by interannual variability could lead to misinterpretation of site condition, if conclusions are based on single annual surveys. Temporal variability in stability and persistence may help distinguish low levels of impairment where a predominantly healthy fauna experiences increased environmental fluctuations.     

Phylogenetic metrics of community similarity

We derive a new metric of community similarity that takes into account the phylogenetic relatedness among species. This metric, phylogenetic community dissimilarity (PCD), can be partitioned into two components, a nonphylogenetic component that reflects shared species between communities (analogous to S?rensen' s similarity metric) and a phylogenetic component that reflects the evolutionary relationships among nonshared species. Therefore, even if a species is not shared between two communities, it will increase the similarity of the two communities if it is phylogenetically related to species in the other community. We illustrate PCD with data on fish and aquatic macrophyte communities from 59 temperate lakes. Dissimilarity between fish communities associated with environmental differences between lakes often has a phylogenetic component, whereas this is not the case for macrophyte communities. With simulations, we then compare PCD with two other metrics of phylogenetic community similarity, II(ST) and UniFrac. Of the three metrics, PCD was best at identifying environmental drivers of community dissimilarity, showing lower variability and greater statistical power. Thus, PCD is a statistically powerful metric that separates the effects of environmental drivers on compositional versus phylogenetic components of community structure.     

高寒草甸植物群落中物种多样性与群落变异性的关系及其机制初探

通过对高寒草甸植物群落中采集的群落数据进行分析,探讨了物种构成的相似性、统计平均、种群变异性和净协方差等机制对形成高寒草甸植物群落中多样性与群落地上生物量变异性之间关系的影响。结果表明,地上生物量的年际变异性随着多样性的增加而减小。物种构成相似性是多样性一变异性负关系产生的原因之一,而相似性与多样性之间并无显著相关关系;统计平均效应是另一个多样性一变异性负关系的主要决定者;净协方差效应、种群变异性对多样性一变异性关系产生的影响不显著或非常有限。     

Microbial leaf degraders in boreal streams: bringing together stochastic and deterministic regulators of community composition

1. Leaves that fall into the water represent a new habitat for microorganisms to colonise in streams, providing an opportunity to study colonisation and the subsequent regulation of community structure. We explored community composition of bacteria and fungi on decomposing alder leaves in nine streams in central Sweden, and describe their relationship with environmental variables. Succession of the microbial community was studied in one of the streams for 118 days. Microbial community composition was examined by denaturing gradient gel electrophoresis on replicate samples of leaves from each stream. 2. During succession in one stream, maximum taxon richness was reached after 34 days for bacteria and 20 days for fungi respectively. Replicate samples within this stream differed between each other earlier in colonisation, while subsequently such variation among replicate communities was low and remained stable for several weeks. Replicate samples taken from all the nine streams after 34 days of succession showed striking similarities in microbial communities within‐streams, although communities differed more strongly between streams. 3. Canonical analysis of microbial communities and environmental variables revealed that water chemistry had a significant influence on community composition. This influence was superimposed on a statistical relationship between the properties of stream catchments and microbial community composition. 4. The catchment regulates microbial communities in two different ways. It harbours the species pool from which the in‐stream microbial community is drawn and it governs stream chemistry and the composition of organic substrates that further shape the communities. We suggest that there is a random element to colonisation early in succession, whereas other factors such as species interactions, stream chemistry and organic substrate properties, result in a more deterministic regulation of communities during later stages.     

Seasonal Dynamics of Microbial Community Composition and Function in Oak Canopy and Open Grassland Soils

Soil microbial communities are closely associated with aboveground plant communities, with multiple potential drivers of this relationship. Plants can affect available soil carbon, temperature, and water content, which each have the potential to affect microbial community composition and function. These same variables change seasonally, and thus plant control on microbial community composition may be modulated or overshadowed by annual climatic patterns. We examined microbial community composition, C cycling processes, and environmental data in California annual grassland soils from beneath oak canopies and in open grassland areas to distinguish factors controlling microbial community composition and function seasonally and in association with the two plant overstory communities. Every 3 months for up to 2 years, we monitored microbial community composition using phospholipid fatty acid (PLFA) analysis, microbial biomass, respiration rates, microbial enzyme activities, and the activity of microbial groups using isotope labeling of PLFA biomarkers (¹³C-PLFA). Distinct microbial communities were associated with oak canopy soils and open grassland soils and microbial communities displayed seasonal patterns from year to year. The effects of plant species and seasonal climate on microbial community composition were similar in magnitude. In this Mediterranean ecosystem, plant control of microbial community composition was primarily due to effects on soil water content, whereas the changes in microbial community composition seasonally appeared to be due, in large part, to soil temperature. Available soil carbon was not a significant control on microbial community composition. Microbial community composition (PLFA) and ¹³C-PLFA ordination values were strongly related to intra-annual variability in soil enzyme activities and soil respiration, but microbial biomass was not. In this Mediterranean climate, soil microclimate appeared to be the master variable controlling microbial community composition and function.     

Successional and seasonal variations in soil and litter microbial community structure and function during tropical postagricultural forest regeneration: a multiyear study

Soil microorganisms regulate fundamental biochemical processes in plant litter decomposition and soil organic matter (SOM) transformations. Understanding how microbial communities respond to changes in vegetation is critical for improving predictions of how land‐cover change affects belowground carbon storage and nutrient availability. We measured intra‐ and interannual variability in soil and forest litter microbial community composition and activity via phospholipid fatty acid analysis (PLFA) and extracellular enzyme activity across a well‐replicated, long‐term chronosequence of secondary forests growing on abandoned pastures in the wet subtropical forest life zone of Puerto Rico. Microbial community PLFA structure differed between young secondary forests and older secondary and primary forests, following successional shifts in tree species composition. These successional patterns held across seasons, but the microbial groups driving these patterns differed over time. Microbial community composition from the forest litter differed greatly from those in the soil, but did not show the same successional trends. Extracellular enzyme activity did not differ with forest succession, but varied by season with greater rates of potential activity in the dry seasons. We found few robust significant relationships among microbial community parameters and soil pH, moisture, carbon, and nitrogen concentrations. Observed inter‐ and intrannual variability in microbial community structure and activity reveal the importance of a multiple, temporal sampling strategy when investigating microbial community dynamics with land‐use change. Successional control over microbial composition with forest recovery suggests strong links between above and belowground communities.     

Species richness, environmental fluctuations, and temporal change in total community biomass

Theory and empirical results suggest that high biodiversity should often cause lower temporal variability in aggregate community properties such as total community biomass. We assembled microbial communities containing 2 to 8 species of competitors in aquatic microcosms and found that the temporal change in total community biomass was positively but insignificantly associated with diversity in a constant temperature environment. There was no evidence of any trend in variable temperature environments. Three non-exclusive mechanisms might explain the lack of a net stabilising effect of species richness on temporal change. (1) A direct destabilising effect of diversity on population level variances caused some populations to vary more when embedded in more diverse communities. (2) Similar responses of the different species to environmental variability might have limited any insurance effect of increased species richness. (3) Large differences in the population level variability of different species (i.e., unevenness) could weaken the relation between species richness and community level stability. These three mechanisms may outweigh the stabilising effects of increases in total community biomass with diversity, statistical averaging, and slightly more negative covariance in more diverse communities. Our experiment and analyses advocate for further experimental investigations of diversity-variability relations.