Explore the vast range of titles available.

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.

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.

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 Pearson's 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. Few publications reported statistically testing microbial community structure-process links; 75% of tested links were significant, though had few commonalities in which processes or structures were measured and the techniques used.

Global change may contribute to ecological changes in high-elevation lakes and reservoirs, but a lack of data makes it difficult to evaluate spatiotemporal patterns. Remote sensing imagery can provide more complete records to evaluate whether consistent changes across a broad geographic region are occurring. We used Landsat surface reflectance data to evaluate spatial patterns of contemporary lake color (2010–2020) in 940 lakes in the U.S. Rocky Mountains, a historically understudied area for lake water quality. Intuitively, we found that most of the lakes in the region are blue (66%) and were found in steep-sided watersheds (>22.5°) or alternatively were relatively deep (>4.5 m) with mean annual air temperature (MAAT) <4.5°C. Most green/brown lakes were found in relatively shallow sloped watersheds with MAAT ⩾4.5°C. We extended the analysis of contemporary lake color to evaluate changes in color from 1984 to 2020 for a subset of lakes with the most complete time series ( n = 527). We found limited evidence of lakes shifting from blue to green states, but rather, 55% of the lakes had no trend in lake color. Surprisingly, where lake color was changing, 32% of lakes were trending toward bluer wavelengths, and only 13% shifted toward greener wavelengths. Lakes and reservoirs with the most substantial shifts toward blue wavelengths tended to be in urbanized, human population centers at relatively lower elevations. In contrast, lakes that shifted to greener wavelengths did not relate clearly to any lake or landscape features that we evaluated, though declining winter precipitation and warming summer and fall temperatures may play a role in some systems. Collectively, these results suggest that the interactions between local landscape factors and broader climatic changes can result in heterogeneous, context-dependent changes in lake color.

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.

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.

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.

1. Shifts in bacterial community composition along temporal and spatial temperature gradients occur in a wide range of habitats and have potentially important implications for ecosystem functioning. However, it is often challenging to empirically link an adaptation or acclimation that defines environmental niche or biogeography with a quantifiable phenotype, especially in micro-organisms. 2. Here we evaluate a possible mechanistic explanation for shifts in bacterioplankton community composition in response to temperature by testing a previously hypothesized membrane mediated trade-off between resource acquisition and respiratory costs. 3. We isolated two strains of Flavobacterium sp. at two temperatures (cold isolate and warm isolate) from the epilimnion of a small temperate lake in North Central Minnesota. 4. Compared with the cold isolate the warm isolate had higher growth rate, higher carrying capacity, lower lag time and lower respiration at the high temperature and lower phosphorus uptake at the low temperature. We also observed significant differences in membrane lipid composition between isolates and between environments that were consistent with adjustments necessary to maintain membrane fluidity at different temperatures. 5. Our results suggest that temperature acclimation in planktonic bacteria is, in part, a resource-dependent membrane-facilitated phenomenon. This study provides an explicit example of how a quantifiable phenotype can be linked through physiology to competitive ability and environmental niche.

Wolfe-Simon et al . (Research Articles, 3 June 2011, p. 1163; published online 2 December 2010) reported that the bacterial strain GFAJ-1 can grow by using arsenic (As) instead of phosphorus (P), noting that the P content in bacteria grown in +As/–P culture medium was far below the quantity needed to support growth. However, low P content is a common phenotype across a broad range of environmental bacteria that experience P limitation.

Phosphorus (P) routinely limits microbial growth in freshwater ecosystems. The growth rate hypothesis (GRH) relates growth to biomass P content mechanistically through changes in ribosomal ribonucleic acid (rRNA). Although the GRH has been shown in cultured bacteria, less well understood is how GRH relationships are affected by interactions with environmental parameters such as temperature. To address this, we evaluated the relationship between bacterial biomass P, RNA: deoxy ribonucleic acid (DNA) ratio, and growth rate in 47 northern temperate lakes. Although RNA: DNA ratio was positively correlated with bacterial biomass P:carbon (C), we found no correlation between growth rate and RNA: DNA or between growth rate and biomass P:C. There was, however, a significant effect of temperature on biomass P:C. We investigated the effect of temperature more directly using filter-separated bacterial communities from two lakes during two seasons while experimentally manipulating temperature and resources. For the summer communities, bacterial production (BP) and biomass P were positively correlated, and the slope of that relationship increased with increasing temperature. In winter communities, BP and biomass P were again positively correlated; however, the slope of that relationship decreased with increasing temperature. The slope of the relationship between BP and biomass P is a metric of nutrient use efficiency and was strongly influenced by temperature. More importantly, bacterioplankton demonstrated seasonal acclimation or adaptation to in situ temperature, suggesting that studies evaluating multiple communities in time and space fail to find a clear relationship between temperature and bacterial metabolism because bacterial communities are locally adapted to in situ temperature.