Historical Contingency in Microbial Resilience to Hydrologic Perturbations

Development of reliable biogeochemical models requires a mechanistic consideration of microbial interactions with hydrology. Microbial response to and its recovery after hydrologic perturbations (i.e., resilience) is a critical component to understand in this regard, but generally difficult to predict because the impacts of future events can be dependent on the history of perturbations (i.e., historical contingency). Fundamental issues underlying this phenomenon include how microbial resilience to hydrologic perturbations is influenced by historical contingency and how their relationships vary depending on the characteristics of microbial functions. To answer these questions, we considered a simple microbial community composed of two species that redundantly consume a common substrate but specialize in producing distinct products and developed a continuous flow reactor model where the two species grow with trade-offs along the flow rate. Simulations of this model revealed that (1) the history of hydrologic perturbations can lead to the shifts in microbial populations, which consequently affect the community’s functional dynamics, and (2) while historical contingency in resilience was consistently predicted for all microbial functions, it was more pronounced for specialized functions, compared to the redundant function. As a signature of historical contingency, our model also predicted the emergence of hysteresis in the transitions across conditions, a critical aspect that can affect transient formation of intermediate compounds in biogeochemistry. This work presents microbial growth traits and their functional redundancy or specialization as fundamental factors that control historical contingencies in resilience

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community’s traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community’s traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators

On the processes generating latitudinal richness gradients: identifying diagnostic patterns and predictions

We use a simulation model to examine four of the most common hypotheses for the latitudinal richness gradient and identify patterns that might be diagnostic of those four hypotheses. The hypotheses examined include (1) tropical niche conservatism, or the idea that the tropics are more diverse because a tropical clade origin has allowed more time for diversification in the tropics and has resulted in few species adapted to extra-tropical climates. (2) The ecological limits hypothesis suggests that species richness is limited by the amount of biologically available energy in a region. (3) The speciation rates hypothesis suggests that the latitudinal gradient arises from a gradient in speciation rates. (4) Finally, the tropical stability hypothesis argues that climatic fluctuations and glacial cycles in extratropical regions have led to greater extinction rates and less opportunity for specialization relative to the tropics. We found that tropical niche conservatism can be distinguished from the other three scenarios by phylogenies which are more balanced than expected, no relationship between mean root distance (MRD) and richness across regions, and a homogeneous rate of speciation across clades and through time. The energy gradient, speciation gradient, and disturbance gradient scenarios all produced phylogenies which were more imbalanced than expected, showed a negative relationship between MRD and richness, and diversity-dependence of speciation rate estimates through time. We found that the relationship between speciation rates and latitude could distinguish among these three scenarios, with no relation expected under the ecological limits hypothesis, a negative relationship expected under the speciation rates hypothesis, and a positive relationship expected under the tropical stability hypothesis. We emphasize the importance of considering multiple hypotheses and focusing on diagnostic predictions instead of predictions that are consistent with multiple hypotheses

Exploring the determinants of organic matter bioavailability through substrate-explicit thermodynamic modeling

Microbial decomposition of organic matter (OM) in river corridors is a major driver of nutrient and energy cycles in natural ecosystems. Recent advances in omics technologies enabled high-throughput generation of molecular data that could be used to inform biogeochemical models. With ultrahigh-resolution OM data becoming more readily available, in particular, the substrate-explicit thermodynamic modeling (SXTM) has emerged as a promising approach due to its ability to predict OM degradation and respiration rates from chemical formulae of compounds. This model implicitly assumes that all detected organic compounds are bioavailable, and that aerobic respiration is driven solely by thermodynamics. Despite promising demonstrations in previous studies, these assumptions may not be universally valid because OM degradation is a complex process governed by multiple factors. To identify key drivers of OM respiration, we performed a comprehensive analysis of diverse river systems using Fourier- transform ion cyclotron resonance mass spectrometry OM data and associated respiration measurements collected by the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. In support of our argument, we found that the incorporation of all compounds detected in the samples into the SXTM resulted in a poor correlation between the predicted and measured respiration rates. The data-model consistency was significantly improved by the selective use of a small subset (i.e., only about 5%) of organic compounds identified using an optimization method. Through a subsequent comparative analysis of the subset of compounds (which we presume as bioavailable) against the full set of compounds, we identified three major traits that potentially determine OM bioavailability, including: (1) thermodynamic favorability of aerobic respiration, (2) the number of C atoms contained in compounds, and (2) carbon/nitrogen (C/N) ratio. We found that all three factors serve as “filters” in that the compounds with undesirable properties in any of these traits are strictly excluded from the bioavailable fraction. This work highlights the importance of accounting for the complex interplay among multiple key traits to increase the predictive power of biogeochemical and ecosystem models

Carbohydrate supplementation during prolonged cycling exercise spares muscle glycogen but does not affect intramyocellular lipid use

Using contemporary stable-isotope methodology and fluorescence microscopy, we assessed the impact of carbohydrate supplementation on whole-body and fiber-type-specific intramyocellular triacylglycerol (IMTG) and glycogen use during prolonged endurance exercise. Ten endurance-trained male subjects were studied twice during 3 h of cycling at 63 ± 4% of maximal O2 uptake with either glucose ingestion (CHO trial; 0.7 g CHO kg−1 h−1) or without (CON placebo trial; water only). Continuous infusions with [U-13C] palmitate and [6,6-2H2] glucose were applied to quantify plasma free fatty acids (FFA) and glucose oxidation rates and to estimate intramyocellular lipid and glycogen use. Before and after exercise, muscle biopsy samples were taken to quantify fiber-type-specific IMTG and glycogen content. Plasma glucose rate of appearance (Ra) and carbohydrate oxidation rates were substantially greater in the CHO vs CON trial. Carbohydrate supplementation resulted in a lower muscle glycogen use during the first hour of exercise in the CHO vs CON trial, resulting in a 38 ± 19 and 57 ± 22% decreased utilization in type I and II muscle-fiber glycogen content, respectively. In the CHO trial, both plasma FFA Ra and subsequent plasma FFA concentrations were lower, resulting in a 34 ± 12% reduction in plasma FFA oxidation rates during exercise (P < 0.05). Carbohydrate intake did not augment IMTG utilization, as fluorescence microscopy revealed a 76 ± 21 and 78 ± 22% reduction in type I muscle-fiber lipid content in the CHO and CON trial, respectively. We conclude that carbohydrate supplementation during prolonged cycling exercise does not modulate IMTG use but spares muscle glycogen use during the initial stages of exercise in endurance-trained men

Dispersal, environmental niches and oceanic-scale turnover in deep-sea bivalves

Patterns of beta-diversity or distance decay at oceanic scales are completely unknown for deep-sea communities. Even when appropriate data exist, methodological problems have made it difficult to discern the relative roles of environmental filtering and dispersal limitation for generating faunal turnover patterns. Here, we combine a spatially extensive dataset on deep-sea bivalves with a model incorporating ecological dynamics and shared evolutionary history to quantify the effects of environmental filtering and dispersal limitation. Both the model and empirical data are used to relate functional, taxonomic and phylogenetic similarity between communities to environmental and spatial distances separating them for 270 sites across the Atlantic Ocean. This study represents the first ocean-wide analysis examining distance decay as a function of a broad suite of explanatory variables. We find that both strong environmental filtering and dispersal limitation drive turnover in taxonomic, functional and phylogenetic composition in deep-sea bivalves, explaining 26 per cent, 34 per cent and 9 per cent of the variation, respectively. This contrasts with previous suggestions that dispersal is not limiting in broad-scale biogeographic and biodiversity patterning in marine systems. However, rates of decay in similarity with environmental distance were eightfold to 44-fold steeper than with spatial distance. Energy availability is the most influential environmental variable evaluated, accounting for 3.9 per cent, 9.4 per cent and 22.3 per cent of the variation in functional, phylogenetic and taxonomic similarity, respectively. Comparing empirical patterns with process-based theoretical predictions provided quantitative estimates of dispersal limitation and niche breadth, indicating that 95 per cent of deep-sea bivalve propagules will be able to persist in environments that deviate from their optimum by up to 2.1 g m−2 yr−1 and typically disperse 749 km from their natal site

Evolving ecological networks and the emergence of biodiversity patterns across temperature gradients

In ectothermic organisms, it is hypothesized that metabolic rates mediate influences of temperature on the ecological and evolutionary processes governing biodiversity. However, it is unclear how and to what extent the influence of temperature on metabolism scales up to shape large-scale diversity patterns. In order to clarify the roles of temperature and metabolism, new theory is needed. Here, we establish such theory and model eco-evolutionary dynamics of trophic networks along a broad temperature gradient. In the model temperature can influence, via metabolism, resource supply, consumers' vital rates and mutation rate. Mutation causes heritable variation in consumer body size, which diversifies and governs consumer function in the ecological network. The model predicts diversity to increase with temperature if resource supply is temperature-dependent, whereas temperature-dependent consumer vital rates cause diversity to decrease with increasing temperature. When combining both thermal dependencies, a unimodal temperature–diversity pattern evolves, which is reinforced by temperature-dependent mutation rate. Studying coexistence criteria for two consumers showed that these outcomes are owing to temperature effects on mutual invasibility and facilitation. Our theory shows how and why metabolism can influence diversity, generates predictions useful for understanding biodiversity gradients and represents an extendable framework that could include factors such as colonization history and niche conservatism