Edward K. Hall

A trait-based framework for predicting when and where microbial adaptation to climate change will affect ecosystem functioning

As the earth system changes in response to human activities, a critical objective is to predict how biogeochemical process rates (e.g. nitrification, decomposition) and ecosystem function (e.g. net ecosystem productivity) will change under future conditions. A particular challenge is that the microbial communities that drive many of these processes are capable of adapting to environmental change in ways that alter ecosystem functioning. Despite evidence that microbes can adapt to temperature, precipitation regimes, and redox fluctuations, microbial communities are typically not optimally adapted to their local environment. For example, temperature optima for growth and enzyme activity are often greater than in situ temperatures in their environment. Here we discuss fundamental constraints on microbial adaptation and suggest specific environments where microbial adaptation to climate change (or lack thereof) is most likely to alter ecosystem functioning. Our framework is based on two principal assumptions. First, there are fundamental ecological trade-offs in microbial community traits that occur across environmental gradients (in time and space). These trade-offs result in shifting of microbial function (e.g. ability to take up resources at low temperature) in response to adaptation of another trait (e.g. limiting maintenance respiration at high temperature). Second, the mechanism and level of microbial community adaptation to changing environmental parameters is a function of the potential rate of change in community composition relative to the rate of environmental change. Together, this framework provides a basis for developing testable predictions about how the rate and degree of microbial adaptation to climate change will alter biogeochemical processes in aquatic and terrestrial ecosystems across the planet.

The effect of resource quantity and resource stoichiometry on microbial carbon‐use‐efficiency

The carbon-use-efficiency (CUE) of microorganisms is an important parameter in determining ecosystem-level carbon (C) cycling; however, little is known about how variance in resources affects microbial CUE. To elucidate how resource quantity and resource stoichiometry affect microbial CUE, we cultured four microorganisms - two fungi (Aspergillus nidulans and Trichoderma harzianum) and two bacteria (Pectobacterium carotovorum and Verrucomicrobium spinosum) - under 12 unique C, nitrogen (N) and phosphorus (P) ratios. Whereas the CUE of A. nidulans was strongly affected by C, bacterial CUE was more strongly affected by mineral nutrients (N and P). Specifically, CUE in P. carotovorum was positively correlated with P, while CUE of V. spinosum primarily depended on N. This resulted in a positive relationship between fungal CUE and resource C : nutrient stoichiometry and a negative relationship between bacterial CUE and resource C : nutrient stoichiometry. The difference in the direction of the relationship between CUE and C : nutrient for fungi vs. bacteria was consistent with differences in biomass stoichiometry and suggested that fungi have a higher C demand than bacteria. These results suggest that the links between biomass stoichiometry, resource demand and CUE may provide a mechanism for commonly observed temporal and spatial patterns in microbial community structure and function in natural habitats.

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.

The interactive effects of excess reactive nitrogen and climate change on aquatic ecosystems and water resources of the United States

Nearly all freshwaters and coastal zones of the US are degraded from inputs of excess reactive nitrogen (Nr), sources of which are runoff, atmospheric N deposition, and imported food and feed. Some major adverse effects include harmful algal blooms, hypoxia of fresh and coastal waters, ocean acidification, long-term harm to human health, and increased emissions of greenhouse gases. Nitrogen fluxes to coastal areas and emissions of nitrous oxide from waters have increased in response to N inputs. Denitrification and sedimentation of organic N to sediments are important processes that divert N from downstream transport. Aquatic ecosystems are particularly important denitrification hotspots. Carbon storage in sediments is enhanced by Nr, but whether carbon is permanently buried is unknown. The effect of climate change on N transport and processing in fresh and coastal waters will be felt most strongly through changes to the hydrologic cycle, whereas N loading is mostly climate-independent. Alterations in precipitation amount and dynamics will alter runoff, thereby influencing both rates of Nr inputs to aquatic ecosystems and groundwater and the water residence times that affect Nr removal within aquatic systems. Both infrastructure and climate change alter the landscape connectivity and hydrologic residence time that are essential to denitrification. While Nr inputs to and removal rates from aquatic systems are influenced by climate and management, reduction of N inputs from their source will be the most effective means to prevent or to minimize environmental and economic impacts of excess Nr to the nation’s water resources.

Toward a mechanistic understanding of how natural bacterial communities respond to changes in temperature in aquatic ecosystems

We examine how heterotrophic bacterioplankton communities respond to temperature by mathematically defining two thermally adapted species and showing how changes in environmental temperature affect competitive outcome in a two-resource environment. We did this by adding temperature dependence to both the respiration and uptake terms of a two species, two-resource model rooted in Droop kinetics. We used published literature values and results of our own work with experimental microcosms to parameterize the model and to quantitatively and qualitatively define relationships between temperature and bacterioplankton physiology. Using a graphical resource competition framework, we show how physiological adaptation to temperature can allow organisms to be more, or less, competitive for limiting resources across a thermal gradient (2–34 °C). Our results suggest that the effect of temperature on bacterial community composition, and therefore bacterially mediated biogeochemical processes, depends on the available resource pool in a given system. In addition, our results suggest that the often unclear relationship between temperature and bacterial metabolism, as reported in the literature, can be understood by allowing for changes in the relative contribution of thermally adapted populations to community metabolism.

Linking microbial and ecosystem ecology using ecological stoichiometry: a synthesis of conceptual and empirical approaches

Currently, one of the biggest challenges in microbial and ecosystem ecology is to develop conceptual models that organize the growing body of information on environmental microbiology into a clear mechanistic framework with a direct link to ecosystem processes. Doing so will enable development of testable hypotheses to better direct future research and increase understanding of key constraints on biogeochemical networks. Although the understanding of phenotypic and genotypic diversity of microorganisms in the environment is rapidly accumulating, how controls on microbial physiology ultimately affect biogeochemical fluxes remains poorly understood. We propose that insight into constraints on biogeochemical cycles can be achieved by a more rigorous evaluation of microbial community biomass composition within the context of ecological stoichiometry. Multiple recent studies have pointed to microbial biomass stoichiometry as an important determinant of when microorganisms retain or recycle mineral nutrients. We identify the relevant cellular components that most likely drive changes in microbial biomass stoichiometry by defining a conceptual model rooted in ecological stoichiometry. More importantly, we show how X-ray microanalysis (XRMA), nanoscale secondary ion mass spectroscopy (NanoSIMS), Raman microspectroscopy, and in situ hybridization techniques (for example, FISH) can be applied in concert to allow for direct empirical evaluation of the proposed conceptual framework. This approach links an important piece of the ecological literature, ecological stoichiometry, with the molecular front of the microbial revolution, in an attempt to provide new insight into how microbial physiology could constrain ecosystem processes.

Freshwater Bacteria are Stoichiometrically Flexible with a Nutrient Composition Similar to Seston

Although aquatic bacteria are assumed to be nutrient-rich, they out-compete other foodweb osmotrophs for nitrogen (N) and phosphorus (P) an apparent contradiction to resource ratio theory. This paradox could be resolved if aquatic bacteria were demonstrated to be nutrient-poor relative other portions of the planktonic food web. In a survey of >120 lakes in the upper Midwest of the USA, the nutrient content of bacteria was lower than previously reported and very similar to the Redfield ratio, with a mean biomass composition of 102:12:1 (C:N:P). Individual freshwater bacterial isolates grown under P-limiting and P-replete conditions had even higher C:P and N:P ratios with a mean community biomass composition ratio of 875C:179N:1P suggesting that individual strains can be extremely nutrient-poor, especially with respect to P. Cell-specific measurements of individual cells from one lake confirmed that low P content could be observed at the community level in natural systems with a mean biomass composition of 259C:69N:1P. Variability in bacterial stoichiometry is typically not recognized in the literature as most studies assume constant and nutrient-rich bacterial biomass composition. We present evidence that bacteria can be extremely P-poor in individual systems and in culture, suggesting that bacteria in freshwater ecosystems can either play a role as regenerators or consumers of inorganic nutrients and that this role could switch depending on the relationship between bacterial biomass stoichiometry and resource stoichiometry. This ability to switch roles between nutrient retention and regeneration likely facilitates processing of terrestrial organic matter in lakes and rivers and has important implications for a wide range of bacterially mediated biogeochemical 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.

Patterns of genome size evolution in tetraodontiform fishes

Abstract We used flow cytometry to measure genome size in 15 species from seven families and subfamilies of tetraodontiform fishes. Previous studies have found that smooth pufferfishes (Tetraodontidae) have the smallest genome of any vertebrate measured to date (0.7–1.0 picograms diploid). We found that spiny pufferfishes (Diodontidae, sister group to the smooth puffers) possess a genome that is about two times larger (1.6–1.8 pg). Mola mola, a member of the sister group to Diodontidae and Tetraodontidae, also has a relatively large genome (1.7 pg). Parsimony analysis of this pattern indicates that the plesiomorphic condition for Molidae (Diodontidae, Tetraodontidae) is a genome size of 1.6–1.8 pg, and that tiny genome size is a derived character unique to smooth puffers. However, an alternative explanation is that the ancestor of Tetraodontidae acquired a heritable tendency toward decreasing genome size, such as a new or modified deletion mechanism, and genome size in all of the tetraodontid lineages has been decreasing in parallel since the split from Diodontidae. Small genome size (1.1–1.3 pg) also appears to have evolved independently in some members of Balistoidea (triggerfishes and filefishes) within Tetraodontiformes.

Optimization of Biomass Composition Explains Microbial Growth-Stoichiometry Relationships

Integrating microbial physiology and biomass stoichiometry opens far-reaching possibilities for linking microbial dynamics to ecosystem processes. For example, the growth-rate hypothesis (GRH) predicts positive correlations among growth rate, RNA content, and biomass phosphorus (P) content. Such relationships have been used to infer patterns of microbial activity, resource availability, and nutrient recycling in ecosystems. However, for microorganisms it is unclear under which resource conditions the GRH applies. We developed a model to test whether the response of microbial biomass stoichiometry to variable resource stoichiometry can be explained by a trade-off among cellular components that maximizes growth. The results show mechanistically why the GRH is valid under P limitation but not under N limitation. We also show why variability of growth rate–biomass stoichiometry relationships is lower under P limitation than under N or C limitation. These theoretical results are supported by experimental data on macromolecular composition (RNA, DNA, and protein) and biomass stoichiometry from two different bacteria. In addition, compared to a model with strictly homeostatic biomass, the optimization mechanism we suggest results in increased microbial N and P mineralization during organic-matter decomposition. Therefore, this mechanism may also have important implications for our understanding of nutrient cycling in ecosystems.