Diana R. Nemergut

Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes?

Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

Relationships between protein-encoding gene abundance and corresponding process are commonly assumed yet rarely observed

For any enzyme-catalyzed reaction to occur, the corresponding protein-encoding genes and transcripts are necessary prerequisites. Thus, a positive relationship between the abundance of gene or transcripts and corresponding process rates is often assumed. To test this assumption, we conducted a meta-analysis of the relationships between gene and/or transcript abundances and corresponding process rates. We identified 415 studies that quantified the abundance of genes or transcripts for enzymes involved in carbon or nitrogen cycling. However, in only 59 of these manuscripts did the authors report both gene or transcript abundance and rates of the appropriate process. We found that within studies there was a significant but weak positive relationship between gene abundance and the corresponding process. Correlations were not strengthened by accounting for habitat type, differences among genes or reaction products versus reactants, suggesting that other ecological and methodological factors may affect the strength of this relationship. Our findings highlight the need for fundamental research on the factors that control transcription, translation and enzyme function in natural systems to better link genomic and transcriptomic data to ecosystem processes.

Linking microbial community structure and microbial processes: an empirical and conceptual overview

A major goal of microbial ecology is to identify links between microbial community structure and microbial processes. Although this objective seems straightforward, there are conceptual and methodological challenges to designing studies that explicitly evaluate this link. Here, we analyzed literature documenting structure and process responses to manipulations to determine the frequency of structure-process links and whether experimental approaches and techniques influence link detection. We examined nine journals (published 2009-13) and retained 148 experimental studies measuring microbial community structure and processes. Many qualifying papers (112 of 148) documented structure and process responses, but few (38 of 112 papers) reported statistically testing for a link. Of these tested links, 75% were significant and typically used Spearman or Pearsons correlation analysis (68%). No particular approach for characterizing structure or processes was more likely to produce significant links. Process responses were detected earlier on average than responses in structure or both structure and process. Together, our findings suggest that few publications report statistically testing structure-process links. However, when links are tested for they often occur but share few commonalities in the processes or structures that were linked and the techniques used for measuring them.

Changes in community assembly may shift the relationship between biodiversity and ecosystem function

Can differences in community assemblyalter the relationship between biodiver-sity and ecosystem function? Pholchanet al. (2013) used a variety of manipu-lations to change microbial communityassembly in sludge reactors and exam-ined the subsequent links between diver-sity and a rare function, the removal ofendocrinedisruptingcompounds(EDCs).Interestingly, the authors saw no consis-tent differences between shifts in alphadiversity (e.g., species richness and even-ness) and ecosystem function, observingan increase, decrease and no difference inthe amount of removal of specific EDCswith increases in diversity. They suggestedthat differences in community assemblymay be driving variation in the rela-tionship between biodiversity and func-tion, a fascinating hypothesis that unitesprocesses in community and ecosystemecology.Combinations of four processes affectcommunity assembly: dispersal and diver-sification add new taxa to communitieswhile selection and drift affect their rela-tive abundances (Vellend, 2010; Nemergutet al., 2013). Particular research emphasishas been placed on assembly processesthataredriven bydifferences betweentaxa(“niche”) compared to those in whichany such differences are irrelevant to fit-ness(“neutral”)(Hubbell,2001).Likewise,researchers have focused on the roleof stochasticity, where assembly is moreprobabilistic vs. determinism, in whichrandomness does not affect communitydynamics.Nicheandneutralprocessescanoperateinunison(Adler et al., 2007)andboth can be affected by stochastic anddeterministic forces (Fox, 2012). Indeed,extensive data demonstrate that a varietyof factors, including nutrients, produc-tivity, resource availability, successionalstage, and disturbances may affect the rel-ative importance of different communityassembly mechanisms (Chase, 2007, 2010;Ferrenbergetal.,2013;Kardoletal.,2013).However, to our knowledge, no studieshave directly tested how shifts in com-munity assembly may affect the relation-ship between biodiversity and ecosystemfunction.Of course, a great deal of researchhas focused on pairwise combinationsof the interactions between communityassembly, biodiversity and/or function inisolation. First, a large body of workdemonstrates links between biodiversityand ecosystem function (Cardinale et al.,2011; Hooper et al., 2012), even formicrobial systems (Bell et al., 2005; Hsuand Buckley, 2009; Langenheder et al.,2010; Levine et al., 2011; Jousset et al.,2014). However, the nature and strengthof biodiversity ecosystem function (BEF)relationships have been widely debatedand strongly depend on the type of func-tion and ecosystem examined (Grime,1997; Hooper et al., 2005)andthedegree of redundancy within the com-munity (Reich et al., 2012; Jousset et al.,2014). These complexities may be height-ened for microorganisms due to theextraordinary phylogenetic diversity har-bored within microbial communities, andthe fact that a typical microbial commu-nity contains organisms from within avariety of functional guilds.Second, it is known that differentassemblymechanismsdrivebiodiversityindistinct ways. For example, spatial or tem-poral variation in environmental condi-tions increases biodiversity through nicheprocesses while increases in the diver-sity of the metacommunity or in theratio of immigration/emigration rates canincrease biodiversity through neutral pro-cesses (Vellend, 2010).Finally, a relatively new topic in the lit-erature relates community assembly andecosystem function (Fukami et al., 2010;Nemergut et al., 2013). Vital to such aconsideration is the relationship betweenresponse traits, or traits that can interactwithenvironmentalvariationtodeterminespecies distribution and abundance pat-terns, and effect traits, or traits that deter-mine the functional roles of different taxa(Naeem and Wright, 2003). When com-munities are largely structured by nicheprocesses, variation in the environmentcan directly correlate to effect traits thatare linked to selected response traits(Allison, 2012). However, when commu-nities are structured by neutral processes,ecosystem function will primarily dependon effect trait abundances within themetacommunity, dispersal and ecologicaldrift; thus, relationships between varia-tion in the environment and effect traits

When, where and how does microbial community composition matter?

Our planet is experiencing rates of environmental change unprecedented in modern times, and an understanding of how microbes both mediate and respond to these shifts is an important research challenge (De Vries and Shade, 2013). Because of the temporal and spatial scales over which microbes function as well as their extreme diversity, dynamics in microbial structure and processes are typically examined at the community level. However, the factors that drive patterns in microbial structure and function, and the links between them, remain widely debated (Prosser et al., 2007). In this issue, such patterns in microbial communities are further documented for soils, lakes, streams and ocean provinces (Arnosti et al., 2012; Jones et al., 2012; King et al., 2012; Larouche et al., 2012). Additionally, the importance of spatial and temporal dynamics (Armitage et al., 2012; Arnosti et al., 2012; Jones et al., 2012; Larouche et al., 2012) and interactions with macrobiota (King et al., 2012) in driving these patterns is demonstrated. Yet, a central but unanswered question is: “does knowing who is there help us to better understand what they are doing?” Indeed, as shown here by Salles et al. (2012), links between structure and function can often be weak, both at the level of the individual and at the level of the community. Several papers in this special issue, “The Causes and Consequences of Microbial Community Structure,” use empirical or modeling approaches as well as literature reviews to enrich our mechanistic understanding of the controls over the relationship between community structure and ecosystem processes. Specifically, authors address the role of trait distributions and trade-offs, species-species interactions, evolutionary dynamics, community assembly processes and physical controls in affecting “whos there” and “what they are doing.” n nTrait-based approaches can provide mechanistic links between community structure and function, and are gaining popularity in microbial ecology (Krause et al., 2014). Importantly, the distribution of traits within a community may affect the relationship between structure and function (Webb et al., 2010). Thus, as highlighted in this issue by Comte et al. (2013), traits can be considered at both the individual and the community level, where trait distributions may have important implications for emergent properties (e.g., redundancy). Indeed, Shade et al. (2012) highlight a variety of traits that may govern the stability of individual organisms, populations and communities including plasticity, tolerance and dormancy. Folse and Allison (2012) used a multi-nutrient, multi-genotype model of enzyme activity, and showed that trait distributions could yield insight into the relationships between biodiversity and ecosystem function. They found that generalists dominated at low levels of community diversity when rates of enzyme production and enzyme diffusion were lowest. Matias et al. (2013) used a simple microcosm experiment and examined the response of assembled communities to fluctuations in salinity. Their results were somewhat different from Folse and Allison (2012), as they found that community diversity was positively related to productivity and that generalists were more productive and less variable over time. Their work also showed that there did not appear to be a fitness trade-off associated with generalization. Comte et al. (2013) took a novel approach to examine plasticity and redundancy in freshwater bacterioplankton communities, and described explicit metrics to track these traits within community transplant experiments. They showed that plasticity appeared to be an intrinsic community property while redundancy was affected by external environmental factors. Their work also revealed strong relationships between community plasticity and redundancy, with no evidence for trade-offs and a possible co-selection of these attributes. n nAs well, species-species interactions can affect the relationship between communities and processes. In the model presented by Folse and Allison (2012), the importance of both “coalitions” of complementary organisms and the abundance of “cheaters,” or organisms that use a public good without contributing to its production, increased under high levels of enzyme production. They also found that the presence of cheaters could affect the relationship between biodiversity and function. Fox (2012) offered a cautionary tale in terms of our ability to interpret relationships between abundance and “adaptedness” because of organismal interactions. He used a consumer-resource model to demonstrate that, at medium levels of niche overlap, outcomes of competition can be unpredictable, decoupling relationships between abundance and adaptation. n nEvolutionary dynamics can also alter relationships between structure and function. In a Perspectives Article, Choudoir et al. (2012) advocate for population-level approaches to examining microbial community diversity, emphasizing that organisms with exactly the same 16S rRNA gene sequence can exhibit very different ecological dynamics. Indeed, Salles et al. (2012) examined the links between rates of denitrification and phylogenies and highlighted the potential importance of horizontal gene transfer (HGT) by showing that similarity in nirK genes, which are thought to be subject to HGT, is not related to N2O accumulation rates. Furthermore, for nirS and 16S rRNA genes, Salles et al. (2012) showed that there was more explanatory power between structure and function at finer scales of phylogenetic resolution for denitrification and metabolic profiles respectively. Pearce et al. (2012) used metagenomics to examine a soil microbial community from Mars Oasis, Antarctica, and showed that while genera-level diversity was limited, species-level diversity was high. They proposed that this suggests strong selection on the types of taxa that can inhabit this extreme environment combined with high rates of diversification within those lineages. Related, Knope et al. (2012) used a microcosm approach to examine the importance of evolutionary history for diversification in bacteria. They showed that prior exposure to an environmental challenge led to higher rates of diversification. These studies suggest that understanding the coupling of ecological and evolutionary processes is key for interpreting microbial community patterns of structure and function. n nCommunity assembly processes may also alter the relationship between “whos there” and “what they do” (Nemergut et al., 2013). Knope et al. (2012) found that arriving in a community first led to a greater degree of diversification within bacteria, likely because of niche-preemption. Pholchan et al. (2013) used a variety of manipulations to alter microbial community assembly in sludge reactors and showed that relationships between biodiversity and ecosystem function in these systems were unpredictable. They hypothesized that the relative importance of stochastic vs. deterministic assembly processes could change the relationship between biodiversity and ecosystem function. In their comment on the Pholchan manuscript, Knelman and Nemergut (2014) provide a conceptual framework illustrating how assembly, biodiversity and function may be related. Together, these studies provide growing evidence for the importance of assembly processes in determining microbial community properties. n nPhysical dynamics may also be key in regulating the relationship between structure and function. Schimel and Schaeffer (2012) propose a conceptual framework that highlights a requirement that biological processes need to be rate limiting or fate determining in order for community structure to matter for ecosystem function. For example, they propose that structure is not likely to be relevant for organic matter breakdown in mineral soils, where diffusion is limited and organic particles may be occluded or sorbed to soil surfaces. Likewise, Folse and Allison (2012) demonstrate that rates of diffusion of enzymes can affect community diversity and the relative proportion of generalists to specialists. Their work also showed high rates of diffusion coupled to high rates of production can lead to community bottlenecks and increases in stochasticity. As well, King et al. (2012) found that physical dynamics may also affect biotic relationships. They found that associations between plants and microbial community composition were less pronounced at higher elevations, likely due to an increase in the influence of physical harshness on community composition. n nTogether, the studies in this special issue highlight the role of a variety of ecological, evolutionary and physical dynamics in microbial community structure and function (Figure u200b(Figure1).1). This body of work emphasizes the importance of emergent, aggregate community properties and the role of community dynamics in variations in the strength of the structure-function relationships. As Schimel wrote in 1995 “At a small enough scale, microbial community structure must be a dominant control on ecological processes, but as we move up in scale toward the ecosystem and integrate across many individual communities, the influence of microbial community structures decreases.” Predicting when, where, how, and at what scale microbial communities may respond to environmental changes remains a research priority and these papers present new insights into this challenge. n n n nFigure 1 n nDoes “whos there” matter for “what they do”? The papers in this special issue use modeling, empirical approaches, and literature reviews to address a suite of controls over the relationship between community structure ...

Soil bacterial community structure remains stable over a 5-year chronosequence of insect-induced tree mortality

Extensive tree mortality from insect epidemics has raised concern over possible effects on soil biogeochemical processes. Yet despite the importance of microbes in nutrient cycling, how soil bacterial communities respond to insect-induced tree mortality is largely unknown. We examined soil bacterial community structure (via 16S rRNA gene pyrosequencing) and community assembly processes (via null deviation analysis) along a 5-year chronosequence (substituting space for time) of bark beetle-induced tree mortality in the southern Rocky Mountains, USA. We also measured microbial biomass and soil chemistry, and used in situ experiments to assess inorganic nitrogen mineralization rates. We found that bacterial community structure and assembly—which was strongly influenced by stochastic processes—were largely unaffected by tree mortality despite increased soil ammonium (NH4+) pools and reductions in soil nitrate (NO3−) pools and net nitrogen mineralization rates after tree mortality. Linear models suggested that microbial biomass and bacterial phylogenetic diversity are significantly correlated with nitrogen mineralization rates of this forested ecosystem. However, given the overall resistance of the bacterial community to disturbance from tree mortality, soil nitrogen processes likely remained relatively stable following tree mortality when considered at larger spatial and longer temporal scales—a supposition supported by the majority of available studies regarding biogeochemical effects of bark beetle infestations in this region. Our results suggest that soil bacterial community resistance to disturbance helps to explain the relatively weak effects of insect-induced tree mortality on soil N and C pools reported across the Rocky Mountains, USA.

Plant community and soil chemistry responses to long-term nitrogen inputs drive changes in alpine bacterial communities.

Bacterial community composition and diversity was studied in alpine tundra soils across a plant species and moisture gradient in 20 y-old experimental plots with four nutrient addition regimes (control, nitrogen (N), phosphorus (P) or both nutrients). Different bacterial communities inhabited different alpine meadows, reflecting differences in moisture, nutrients and plant species. Bacterial community alpha-diversity metrics were strongly correlated with plant richness and the production of forbs. After meadow type, N addition proved the strongest determinant of bacterial community structure. Structural Equation Modeling demonstrated that tundra bacterial community responses to N addition occur via changes in plant community composition and soil pH resulting from N inputs, thus disentangling the influence of direct (resource availability) vs. indirect (changes in plant community structure and soil pH) N effects that have remained unexplored in past work examining bacterial responses to long-term N inputs in these vulnerable environments. Across meadow types, the relative influence of these indirect N effects on bacterial community structure varied. In explicitly evaluating the relative importance of direct and indirect effects of long-term N addition on bacterial communities, this study provides new mechanistic understandings of the interaction between plant and microbial community responses to N inputs amidst environmental change.

Metagenomic evidence for metabolism of trace atmospheric gases by high-elevation desert Actinobacteria

Previous surveys of very dry Atacama Desert mineral soils have consistently revealed sparse communities of non-photosynthetic microbes. The functional nature of these microorganisms remains debatable given the harshness of the environment and low levels of biomass and diversity. The aim of this study was to gain an understanding of the phylogenetic community structure and metabolic potential of a low-diversity mineral soil metagenome that was collected from a high-elevation Atacama Desert volcano debris field. We pooled DNA extractions from over 15 g of volcanic material, and using whole genome shotgun sequencing, observed only 75–78 total 16S rRNA gene OTUs3%. The phylogenetic structure of this community is significantly under dispersed, with actinobacterial lineages making up 97.9–98.6% of the 16S rRNA genes, suggesting a high degree of environmental selection. Due to this low diversity and uneven community composition, we assembled and analyzed the metabolic pathways of the most abundant genome, a Pseudonocardia sp. (56–72% of total 16S genes). Our assembly and binning efforts yielded almost 4.9 Mb of Pseudonocardia sp. contigs, which accounts for an estimated 99.3% of its non-repetitive genomic content. This genome contains a limited array of carbohydrate catabolic pathways, but encodes for CO2 fixation via the Calvin cycle. The genome also encodes complete pathways for the catabolism of various trace gases (H2, CO and several organic C1 compounds) and the assimilation of ammonia and nitrate. We compared genomic content among related Pseudonocardia spp. and estimated rates of non-synonymous and synonymous nucleic acid substitutions between protein coding homologs. Collectively, these comparative analyses suggest that the community structure and various functional genes have undergone strong selection in the nutrient poor desert mineral soils and high-elevation atmospheric conditions.

Microbes ride the current

Biogeographical diversity in bacterial populations can arise without need for natural selection [Also see Report by Hellweger et al.] How do differences in marine bacterial populations arise in the ocean? On page 1346 of this issue, Hellweger et al. (1) investigate this question with a model based on ocean currents, parameterized with data from the most ubiquitous and abundant ocean bacterium, Pelagibacter. The model assumes that mutations are neutral—that is, they cause no change in the fitness of organisms, so that selection cannot act on them. The results show that neutral processes are enough to generate biogeographical patterns in marine bacteria without any adaptive evolution taking place.

Phosphorus, not nitrogen, limits plants and microbial primary producers following glacial retreat

Unlike temperate soils, where N limits primary productivity, cold and dry soils exposed by retreating glaciers are P-limited. Current models of ecosystem development hold that low nitrogen availability limits the earliest stages of primary succession, but these models were developed from studies conducted in areas with temperate or wet climates. Global warming is now causing rapid glacial retreat even in inland areas with cold, dry climates, areas where ecological succession has not been adequately studied. We combine field and microcosm studies of both plant and microbial primary producers and show that phosphorus, not nitrogen, is the nutrient most limiting to the earliest stages of primary succession along glacial chronosequences in the Central Andes and central Alaska. We also show that phosphorus addition greatly accelerates the rate of succession for plants and for microbial phototrophs, even at the most extreme deglaciating site at over 5000 meters above sea level in the Andes of arid southern Peru. These results challenge the idea that nitrogen availability and a severe climate limit the rate of plant and microbial succession in cold-arid regions and will inform conservation efforts to mitigate the effects of global change on these fragile and threatened ecosystems.