10 Cities Without Sunlight
Somewhere in the Earth’s crust, a cell divides once per century. Its energy source is hydrogen gas, produced by the radioactive decay of uranium in the surrounding rock. Its electron acceptor is sulfate, trapped in mineral inclusions since the Archean. No photon has reached it in at least twenty million years. It has no genes for oxygen use, no genes for oxygen defense. By every measure that laboratory microbiologists use to define “alive,” it barely qualifies – and yet it persists, and it reproduces, on a timescale measured in centuries.
The organism is Candidatus Desulforudis audaxviator. It was discovered in 2006, when a drilling crew at the Mponeng gold mine in South Africa punched through rock at 2.8 kilometers below the surface and hit water.
The water was hot – slightly above 60 degrees Celsius – alkaline, and saturated with a cocktail of dissolved chemicals: sulfate, molecular hydrogen, methane, carbon dioxide, and a scattering of simple organic molecules like formate and acetate. The rock enclosing it was basalt, part of a formation 2.7 billion years old. The water had been sealed down there for millions of years, in the dark, under crushing pressure, with no connection to the surface.
And it was alive.
Not teeming – not a jungle. But when Li-Hung Lin and colleagues analyzed the microbial community in that fracture water, they found something startling: a functioning ecosystem, dominated by a single bacterial species, running on chemistry that the rock itself provided.1 Most of the organic matter in the water had an abiogenic origin – produced not by photosynthesis or any biological process, but by geological reactions between water and minerals deep in the crust. The hydrogen came from radiolysis of water by uranium decay in the surrounding rock. The sulfate came from ancient seawater trapped in mineral inclusions.
Life, in this place, was not borrowing from the sun. It was borrowing from the Earth’s interior.
10.1 The brave wanderer
The organism that dominated that fracture water – comprising over 99.9 percent of the community – received one of the more literary names in microbiology: Candidatus Desulforudis audaxviator. The name comes from a Latin phrase in Jules Verne’s Journey to the Center of the Earth: “Descende, audax viator, et terrestre centrum attinges” – “Descend, brave traveler, and you will reach the center of the Earth”.2
The name was earned. When Dylan Chivian and colleagues reconstructed the organism’s genome from metagenomic data, they found a cell prepared for total independence. D. audaxviator carries a complete genetic toolkit for life in extreme isolation: it fixes its own carbon from CO\(_2\), fixes atmospheric nitrogen (there is no “atmosphere” down there, but trace dissolved N\(_2\) suffices), and harvests energy by reducing sulfate with molecular hydrogen. Thermodynamic calculations confirm that under the conditions of the Mponeng fracture water – the specific concentrations of H\(_2\), sulfate, and products present – this metabolism is the most energetically favorable option available.3 The calculated Gibbs energy yield is just barely sufficient to support ATP synthesis, placing this organism at the thermodynamic edge of life.4
What the genome does not contain is equally telling. There are zero genes for oxygen use. Minimal genes for oxygen defense – a lone superoxide dismutase but no catalase, no peroxidase, little of the protective machinery that aerobic or even facultatively anaerobic organisms carry as insurance. This organism has not dealt with oxygen for a very long time.5
Alongside D. audaxviator, the community includes roughly 25 other species, among them four methanogenic archaea. But the brave wanderer is the keystone – the organism that, more than any other, demonstrates that a living system can persist for geological time without any connection to the surface biosphere. Lin and colleagues called it “the first proven case of autonomous long existence of living organisms in the bowels of the earth, without any connection with the big biosphere”.6
The fracture water community made its journey underground millions of years ago – noble gas dating suggests residence times of 3 to 25 million years, depending on the fracture system. Since then, it has survived on the thin trickle of chemical energy that radioactive decay and water-rock reactions provide. No sunlight. No organic rain from above. No seasonal pulse of nutrients. Just rock, water, heat, and the patient rearrangement of electrons.
10.2 What counts as “deep”
The Mponeng discovery is dramatic, but it is not an isolated curiosity. By the mid-1990s, evidence was accumulating that microbial life extends far deeper into the Earth’s crust than anyone had assumed. The question was how to think about it systematically.
Derek Lovley and Francis Chapelle proposed a framework that remains useful today.7 The key insight is that “deep” should not be defined by depth alone. A sample from 500 meters in one geological setting might be more connected to the surface than a sample from 50 meters in another. What matters is the hydrology – how water moves through the subsurface.
Lovley and Chapelle described three scales of groundwater flow:
- Local flow systems: high recharge from the surface (1–30 cm/yr), relatively rapid groundwater movement (1–100 m/yr). These are the shallow aquifers, the wells, the springs. Surface influence is strong.
- Intermediate flow systems: less connected to the surface. Recharge rates drop to 0.01–1 cm/yr. Water ages increase from years to centuries.
- Regional flow systems: recharge occurs only at the topographic divide. Flow is sluggish. Water may be thousands or millions of years old. These are the domains where life, if it exists, must be self-sustaining.
The “deep subsurface,” in Lovley and Chapelle’s definition, should be restricted to intermediate and regional flow systems – environments where surface-derived inputs are minimal and microorganisms must work with whatever chemistry the geology provides. This is a functional definition, not a geometric one. It is about isolation, not depth.
One constraint is universal across all these settings: “Microorganisms are the only life forms that can inhabit most deep subsurface environments because typical pore spaces are too small for other types of life”.8 A bacterium fits through a pore throat that would stop a nematode, let alone anything with a circulatory system. In the deep subsurface, smallness is not a limitation. It is the entry ticket.
And one absence is absolute: “Light is not available in the deep subsurface”.9 No photosynthesis. Every calorie of energy must come from chemical reactions – from the oxidation of organic matter buried with the sediment, from reduced compounds like Fe(II), Mn(II), ammonia, or sulfide carried in by recharge water, or from geological processes like serpentinization and radiolysis that generate fresh electron donors in situ.10
10.3 The terminal electron acceptor hierarchy
Without sunlight, the deep subsurface runs on the same fundamental principle as the redox ladder we met in earlier chapters – but stripped to its essentials. Organisms oxidize electron donors (organic carbon, hydrogen, reduced metals) and pass the electrons to whatever acceptor is available. The most common terminal electron acceptors, in order of the energy they typically yield, are:
\[ \text{O}_2 > \text{NO}_3^- > \text{Mn(IV)} > \text{Fe(III)} > \text{SO}_4^{2-} > \text{CO}_2 \]
[FIGURE: The terminal electron acceptor hierarchy shown as a vertical column. Depth increases downward. At the top, O2 is consumed first (narrow zone). Below it, NO3- disappears. Then Mn(IV) and Fe(III) reduction zones. Then a broad SO4-2 reduction zone. At the bottom, CO2 reduction (methanogenesis). Each zone is labeled with the dominant metabolism and the Gibbs energy yield per mole of electron donor. The energy yield decreases with depth. Caption: “The redox ladder, expressed in sediment. Each zone represents the cheapest electron acceptor still available.”]
Each acceptor supports a distinct metabolic community: aerobic respirers, denitrifiers, manganese reducers, iron reducers, sulfate reducers, methanogens. These are the Terminal Electron Accepting Processes, or TEAPs, and in an idealized system they appear in sequence as the more energetically favorable acceptors are exhausted.11 Iron and sulfate reducers typically conserve four to five times more energy per mole of electron donor than methanogens – a difference that has profound implications for community structure and biomass yields.12
In practice, the deep subsurface is messier. Lovley and Chapelle noted a tendency in geochemistry to treat microorganisms as “black boxes that may facilitate thermodynamically favorable reactions” – as if the bugs are just catalysts that speed up whatever chemistry the Gibbs energy landscape demands.13 This shorthand works surprisingly often, but it fails in important cases.
The reason is that thermodynamic favorability is necessary but not sufficient. A reaction can be favorable on paper and still not happen because no organism present carries the right enzymes. A reaction can be favorable and fast in a beaker but starved in a pore because transport cannot supply reactants. As Lovley and Chapelle put it: “It is becoming increasingly apparent that even in ancient, relatively nondynamic subsurface environments, simplified nonbiological models do not accurately describe important geochemical processes”.14
The practical consequence is stark: “Most redox reactions do not take place spontaneously but require microorganisms to catalyze them”.15 In the deep subsurface, the biology is not a detail layered on top of the chemistry. The biology is the chemistry, or at least the part of it that actually happens on observable timescales.
10.4 Respiration in equations
To model these communities, we need a mathematical expression for respiration rate. The standard approach uses a dual-Monod kinetic form:
\[ R_{\text{resp}} = k_{\text{resp}} \cdot [B] \cdot \frac{[\text{TED}]}{[\text{TED}] + K_{m,\text{TED}}} \cdot \frac{[\text{TEA}]}{[\text{TEA}] + K_{m,\text{TEA}}} \]
where \([B]\) is biomass concentration, \([\text{TED}]\) and \([\text{TEA}]\) are the concentrations of the terminal electron donor and acceptor, \(K_m\) values are half-saturation constants, and \(k_{\text{resp}}\) is the maximum specific rate.1617
The dual-Monod form captures something important: respiration slows when either the donor or the acceptor becomes scarce. A sulfate reducer with plenty of hydrogen but vanishing sulfate will slow down just as surely as one with plenty of sulfate but no hydrogen. The two Monod terms act as independent throttles.
In shallow, oxygenated environments, aerobic respiration dominates so thoroughly that it accounts for 90–95 percent of all degraded organic carbon.18 But the deep subsurface is almost never oxygenated. In anoxic, nitrate-depleted settings, a division of labor emerges: fermentative microorganisms first break complex organic molecules into simpler ones – acetate, formate, hydrogen – and then respiring bacteria use those simpler compounds as electron donors, passing the electrons to whatever terminal acceptor remains.19 The fermenters and the respirers are partners, not competitors, linked by the small molecules that one produces and the other consumes.
No single organism can do everything. That constraint – the inability of any one species to completely oxidize complex organic matter using a given terminal electron acceptor – is what forces the community to be a community. Even in the Mponeng fracture, where D. audaxviator dominates, those 25 other species are not bystanders. They fill niches that the brave wanderer cannot.
10.5 Life at the thermodynamic edge
The deep subsurface pushes microbial life to its energetic limits. How slow can metabolism get before it ceases to be metabolism?
The answer, it turns out, is extraordinarily slow. Douglas LaRowe and Jan Amend compiled data on microbial turnover times across a range of natural settings and found that in aquifers, sedimentary rocks, marine sediments, and ice cores, biomass turnover times can exceed 1,000 years.20 In Antarctic photosynthetic communities – admittedly a surface environment, but one where conditions are extreme – biomass turnover times reach up to 19,000 years.
Consider what that means. A cell that turns over its biomass once every thousand years is not dormant. It is metabolically active, but so slowly that its existence plays out on a geological timescale.
The range of metabolic rates across Earth’s biosphere is staggering. LaRowe and Amend found that catabolic rates vary over twelve orders of magnitude, from approximately \(6 \times 10^{-9}\) to \(6.66 \times 10^{3}\) nmol cm\(^{-3}\) day\(^{-1}\).21 Twelve orders of magnitude. The fastest microbial communities metabolize a trillion times faster than the slowest. And yet the slowest are still alive.
This raises a fundamental question about maintenance energy – the minimum energy flux a cell needs just to stay alive without growing. In laboratory cultures, maintenance energy can be measured: you starve a culture, track its decline, and calculate the energy cost of keeping the lights on. But in deep subsurface settings, per-cell energy fluxes are “several orders of magnitude lower than maintenance energies predicted from laboratory cultures”.22
Either the cells are dying (but they aren’t – they persist for millions of years), or our laboratory-derived maintenance estimates are wrong for these conditions. LaRowe and Amend argue for the latter: maintenance energy is not a constant. It depends on growth conditions, temperature, community structure, and the specific stresses a cell faces. It should be treated as a variable, not a parameter.23
The implication reshapes how we model deep life. A cell in a laboratory flask, bathed in rich media at 37 degrees, has a “maintenance bill” that includes the cost of dealing with rapid environmental fluctuations, repairing damage from reactive oxygen species, and competing with neighbors. A cell in a fracture at 2.8 kilometers depth, in stable, anoxic water that changes on geological timescales, has shed most of those costs. It has not optimized for speed or yield. It has satisficed – found the minimal metabolic strategy that covers the minimal maintenance cost under its specific constraints, and held that position for geological time.
This is the satisficing principle at its purest. D. audaxviator does not maximize anything. It persists. It runs sulfate reduction with hydrogen not because that reaction yields the most energy per electron (it doesn’t – aerobic respiration would yield far more, if oxygen were available), but because it is the reaction its enzymes can catalyze with the substrates its environment provides. The “choice” is not a choice at all. It is the intersection of thermodynamic possibility and enzymatic capability, filtered through billions of years of genome erosion in which every unnecessary gene was lost. What remains is the minimal toolkit for the minimal strategy that covers the minimal cost. Optimization would imply that the organism surveyed its options and selected the best one. Satisficing means it kept the one that worked and discarded the rest.
The mathematical framework for describing how chemical species change in sediments and subsurface environments rests on a conservation law first formalized by Robert Berner and later refined by Bernard Boudreau (Berner 1980; Boudreau 1997).
The starting point is a bulk concentration: an average taken over a volume element that is larger than individual grain diameters but smaller than the scale of macroscopic gradients. This averaging smooths out the pore-scale chaos while preserving the gradients we care about.
The reference frame is Cartesian and moves with the accumulating sediment – a choice that simplifies the math for systems where material is continuously buried.
At steady state, the time derivative vanishes (\(\partial C / \partial t = 0\)), and the substantial derivative reduces to:
\[ \frac{DC}{Dt} = w \frac{\partial C}{\partial x} \]
where \(w\) is the burial velocity.
The general conservation equation is:
\[ \frac{\partial \hat{C}}{\partial t} = -\frac{\partial F}{\partial x} + \sum R_i \]
The left side is the rate of change of bulk concentration \(\hat{C}\). The right side balances two terms: the divergence of the flux \(F\) (how much stuff moves in and out of a volume element) and the sum of all reactions \(R_i\) (how much stuff is created or destroyed).
For solutes (dissolved species), the bulk concentration is \(\hat{C} = \phi \cdot C\), where \(\phi\) is porosity and \(C\) is the porewater concentration.
For solids (minerals, organic particles, biomass), the bulk concentration is \(\hat{C} = (1 - \phi) \cdot B\), where \(B\) is the concentration per unit volume of solid.
This equation is the bookkeeping device that makes reaction-transport models possible. Everything else – the specific rate laws, the transport terms, the boundary conditions – plugs into this frame.
10.6 The dark photosynthesizer
In 2016, a group of American chemists reported something that sounded like science fiction. They took Moorella thermoacetica, a non-photosynthetic, anaerobic bacterium – a species that has never, in its evolutionary history, used light for energy – and turned it into a kind of solar cell.
The trick was cadmium sulfide nanoparticles. The researchers dissolved cadmium and sulfide precursors in the growth medium. The bacterium, doing what Moorella does naturally, precipitated cadmium sulfide crystals on its own cell surface. These nanoparticles acted as light-harvesting antennae: when illuminated, they generated excited electrons that the bacterium captured and used to reduce CO\(_2\) into acetic acid and other organic molecules.
The bacterium built its own solar panels.
This is remarkable not because it is natural – it is thoroughly artificial – but because it reveals the metabolic flexibility hiding inside organisms we thought we understood. Moorella thermoacetica can grow as a heterotroph (eating organic carbon), as a chemoautotroph (fixing CO\(_2\) using hydrogen), and even as an “electrotroph” – fed electrons directly from an electrode. Adding nanoparticle-mediated photosynthesis to its repertoire did not require genetic engineering. It required only the right chemistry in the right place.
For our story, the lesson is about potential. The deep subsurface harbors organisms whose metabolic capabilities are far broader than their current environment demands. D. audaxviator fixes carbon, fixes nitrogen, and reduces sulfate – but its genome also contains genes for flagellar motility, chemotaxis, and sporulation. These are capabilities it may not have used for millions of years. They are evolutionary memories, carried forward because the cost of keeping them is lower than the cost of losing them and needing them later.
In the deep subsurface and in sediments generally, chemistry means nothing without transport. A reaction can be thermodynamically favorable and enzymatically possible, but if the reactants cannot reach the organisms, nothing happens.
Advective flux for solutes (dissolved species carried by flowing porewater):
\[ F_A = \phi \cdot u \cdot C \]
where \(\phi\) is porosity, \(u\) is the porewater velocity, and \(C\) is concentration.
Advective flux for solids (particles, minerals, biomass carried by sediment burial):
\[ F_A = (1 - \phi) \cdot w \cdot B \]
where \(w\) is the burial velocity and \(B\) is the solid-phase concentration.
Compaction creates a subtlety that trips up newcomers. As sediment is buried and compressed, porosity decreases. Porewater is squeezed upward relative to the grains – but it still moves downward relative to the sediment-water interface. The porewater velocity \(u\) and the solid velocity \(w\) are generally not equal, and their difference is what drives compaction-related porewater flow.
Darcy flow through porous media:
\[ u_x = -\frac{k}{\phi \cdot \mu} \cdot \frac{\partial p'}{\partial x} \]
where \(k\) is permeability, \(\mu\) is dynamic viscosity, and \(\partial p'/\partial x\) is the pressure gradient driving flow.
There is also a biological conveyor belt: head-down deposit feeders (worms, in shallow marine settings) that ingest sediment at depth and excrete it at the surface, effectively pumping particles upward. This “bioturbation” can dominate transport in the upper few centimeters of marine sediment. In the deep subsurface, where such organisms cannot live, this term disappears – and transport becomes purely physical: advection, diffusion, and pressure-driven flow.
10.7 Competing or cooperating?
One of the persistent questions in deep subsurface microbiology is whether organisms in these communities are competing for scarce resources or somehow cooperating to optimize the overall energy harvest. The answer matters for modeling, because competition and cooperation lead to different predictions about which organisms persist and at what rates.
Craig Bethke and colleagues examined this question through the lens of the thermodynamic ladder.24 They noted an apparent paradox: iron reducers and sulfate reducers conserve four to five times more energy in their ATP pools per mole of electron donor consumed than methanogens do. If competition were purely about energy yield, methanogens should be consistently outcompeted wherever iron or sulfate is available. Yet in many natural environments, all three groups coexist, sometimes operating at similar overall rates.
One possible resolution is that the organisms are not simply maximizing their own energy harvest. Perhaps the community as a whole tends toward a state that maximizes the total usable energy extracted from all available reactions – a kind of collective optimization.25 Under this view, the community composition is not determined solely by pairwise competition but by a global optimization problem: given the available electron donors and acceptors, what combination of metabolisms extracts the most energy?
But there is a third possibility, and it is the one most consistent with the data we have seen throughout this book: neither individual optimization nor collective optimization, but satisficing. Each organism runs the metabolism its enzymes permit, at the rate the local concentrations support, without reference to any global objective. The community structure that results is not optimal in any formal sense – it is merely viable. Every guild covers its maintenance costs. No guild is excluded unless its reaction is thermodynamically impossible under local conditions. The coexistence of iron reducers, sulfate reducers, and methanogens in the same aquifer is not paradoxical under this view. It is expected: all three can cover costs, so all three persist. The boundaries are fuzzy because the constraints are fuzzy.
This is an active area of research, and the models are not yet settled. But the satisficing view has a practical advantage over both the competitive-exclusion and collective-optimization views: it predicts the messy coexistence that field data actually show, without requiring mechanisms (altruism, group selection, global coordination) for which there is no evidence in prokaryotic communities. Over geological time, communities may converge toward configurations where relatively little energy is wasted – not because any organism optimizes, and not because the community optimizes, but because evolution in a closed system eliminates strategies that cannot cover maintenance. What survives is what works, not what is best.
10.8 Growth, decay, and the meaning of yield
To connect all of this to quantitative models, we need an equation for biomass. The standard form is deceptively simple:
\[ \frac{d[B]}{dt} = Y \cdot R_{\text{resp}} - \mu_{\text{dec}} \cdot [B] \]
Biomass grows in proportion to the respiration rate (scaled by the yield coefficient \(Y\)) and decays at a rate proportional to the current biomass (scaled by the decay constant \(\mu_{\text{dec}}\)).2627
The yield coefficient \(Y\) is the fraction of energy from respiration that gets converted into new biomass. It is the efficiency of the organism as a machine: how much of the fuel becomes structure rather than heat?
Several approaches exist for estimating \(Y\). Theoretical frameworks, such as those developed by Rittmann and McCarty or by Heijnen and Van Dijken, derive yield from thermodynamic first principles – partitioning the Gibbs energy of the catabolic reaction between the energy needed for biosynthesis and the energy dissipated.2829 Empirical approaches fit yield to experimental data and find relationships that scale with the available Gibbs energy.30 The more energy available per mole of reaction, the higher the yield – but the relationship is shallow. Even large changes in available energy produce only modest changes in yield, because biosynthesis has irreducible costs.
For the standard Monod growth model, the rate of biomass production is:
\[ r_X = \mu_{\max} \cdot \frac{S}{K + S} \cdot X \]
where \(\mu_{\max}\) is the maximum specific growth rate, \(S\) is the limiting substrate, \(K\) is the half-saturation constant, and \(X\) is biomass. This is the workhorse of microbial ecology modeling. It captures the essential behavior: growth accelerates with substrate availability, saturates when substrate is abundant, and scales with the amount of biomass present.
But in the deep subsurface, growth is only half the story. Much of the biomass at any given time may be dormant – alive but metabolically inactive, waiting for conditions to improve. Stolpovsky and colleagues developed models that explicitly track dormant and active cell fractions, showing that the transition between states can dramatically affect community dynamics and the apparent rates of geochemical processes.31
Three approaches to estimating yield deserve comparison. Rittmann and McCarty partition catabolic energy into a growth fraction and a dissipated fraction, based on the energetics of biosynthesis from available carbon and nitrogen sources.32 Heijnen and Van Dijken use a correlation between the Gibbs energy dissipated per C-mol of biomass produced and the degree of reduction of the substrate.33 Empirical approaches fit yield directly to experimental data across a range of metabolic types and environmental conditions.34
A deeper issue: cells do not respond instantaneously to environmental changes. There is a lag phase – a delay between a change in conditions and the metabolic response.35 Simple unstructured models assume quasi-steady state. For stable deep subsurface settings, this may be acceptable. For perturbed systems – aquifers receiving a pulse of contaminant, sediments exposed to sudden changes – “simple unstructured models are not adequate descriptors”.36 Additional complications arise from substrate and product inhibition, and from activity coefficient corrections in high-ionic-strength porewaters.37
The honest summary: yield and growth rate are not constants. They are functions of thermodynamics, environment, and history. Models that treat them as fixed parameters work in narrow conditions; models that let them vary work more broadly, at the cost of more parameters to constrain.
10.10 What the brave wanderer teaches
Return, for a moment, to the Mponeng fracture. A single species, in water sealed from the surface for millions of years, in rock billions of years old, at 60 degrees Celsius and 2.8 kilometers down. No sunlight, no organic rain, no seasonal cycle. Just hydrogen from radiolysis, sulfate from ancient inclusions, and the patient machinery of a genome honed for exactly these conditions.
Desulforudis audaxviator is, in a sense, the purest test of the non-equilibrium trick we introduced at the beginning of this book. It maintains its internal order not by drawing on the sun’s energy, not by consuming the products of photosynthesis, but by harvesting the thin chemical gradients that geology provides. Its existence proves that the minimum requirements for life are astonishingly modest: a thermodynamic gradient, however small; a catalytic machinery, however slow; and time.
The mathematics of this chapter – the Monod kinetics, the yield coefficients, the diagenetic equations – are not decorations. They are the tools that let us ask quantitative questions about this alien world. How fast can D. audaxviator grow on the hydrogen flux available? What yield does its sulfate reduction support? How does the community partition the available energy? What happens when the hydrogen flux changes on geological timescales?
These are answerable questions. The models exist. The parameters are being measured. And the answers, when they come, will tell us something profound not just about life in the deep Earth, but about life anywhere that chemistry and thermodynamics permit it – including, perhaps, the subsurface oceans of Europa or the ancient aquifers of Mars.
The brave wanderer descended into the dark and found a way to live there. The equations are our way of following it down.
10.11 Takeaway
- The deep biosphere hosts microbial communities that survive without any connection to photosynthesis, powered instead by geological energy sources like radiolysis and water-rock reactions.
- “Deep” is defined by hydrological isolation, not depth: intermediate and regional flow systems where surface inputs are negligible.
- The terminal electron acceptor hierarchy governs energy metabolism in the subsurface, but biology is not a passive catalyst – organisms determine which thermodynamically favorable reactions actually occur.
- Life at the thermodynamic edge operates over twelve orders of magnitude in metabolic rate, with turnover times exceeding thousands of years and maintenance energies far below laboratory predictions.
- Quantitative models (dual-Monod kinetics, biomass growth-decay equations, yield coefficients) connect the biology to measurable geochemical processes – but parameters like yield and maintenance energy must be treated as variables, not constants.
Li-Hung Lin et al., “Long-Term Sustainability of a High-Energy, Low-Diversity Crustal Biome,” Science 314 (2006): 479–482. (Lin et al. 2006)↩︎
Dylan Chivian et al., “Environmental Genomics Reveals a Single-Species Ecosystem Deep Within Earth,” Science 322 (2008): 275–278. (Chivian et al. 2008)↩︎
Li-Hung Lin et al., “Long-Term Sustainability of a High-Energy, Low-Diversity Crustal Biome,” Science 314 (2006): 479–482. (Lin et al. 2006)↩︎
Dylan Chivian et al., “Environmental Genomics Reveals a Single-Species Ecosystem Deep Within Earth,” Science 322 (2008): 275–278. (Chivian et al. 2008)↩︎
Dylan Chivian et al., “Environmental Genomics Reveals a Single-Species Ecosystem Deep Within Earth,” Science 322 (2008): 275–278. (Chivian et al. 2008)↩︎
Li-Hung Lin et al., “Long-Term Sustainability of a High-Energy, Low-Diversity Crustal Biome,” Science 314 (2006): 479–482. (Lin et al. 2006)↩︎
Derek R. Lovley and Francis H. Chapelle, “Deep Subsurface Microbial Processes,” Reviews of Geophysics 33 (1995): 365–381. (Lovley and Chapelle 1995)↩︎
Derek R. Lovley and Francis H. Chapelle, “Deep Subsurface Microbial Processes,” Reviews of Geophysics 33 (1995): 365–381. (Lovley and Chapelle 1995)↩︎
Derek R. Lovley and Francis H. Chapelle, “Deep Subsurface Microbial Processes,” Reviews of Geophysics 33 (1995): 365–381. (Lovley and Chapelle 1995)↩︎
Serpentinization – the hydration of ultramafic rocks – produces molecular hydrogen abiotically and has been recognized as a key energy source for deep subsurface chemosynthetic ecosystems. (Lovley and Chapelle 1995)↩︎
Derek R. Lovley and Francis H. Chapelle, “Deep Subsurface Microbial Processes,” Reviews of Geophysics 33 (1995): 365–381. (Lovley and Chapelle 1995)↩︎
Craig M. Bethke et al., “The thermodynamic ladder in geomicrobiology,” American Journal of Science 311 (2011): 183–210. (Bethke et al. 2011)↩︎
Derek R. Lovley and Francis H. Chapelle, “Deep Subsurface Microbial Processes,” Reviews of Geophysics 33 (1995): 365–381. (Lovley and Chapelle 1995)↩︎
Derek R. Lovley and Francis H. Chapelle, “Deep Subsurface Microbial Processes,” Reviews of Geophysics 33 (1995): 365–381. (Lovley and Chapelle 1995)↩︎
Derek R. Lovley and Francis H. Chapelle, “Deep Subsurface Microbial Processes,” Reviews of Geophysics 33 (1995): 365–381. (Lovley and Chapelle 1995)↩︎
Qusheng Jin and Craig M. Bethke, “Predicting the Rate of Microbial Respiration in Geochemical Environments,” Geochimica et Cosmochimica Acta 69 (2005): 1133–1143. (Jin and Bethke 2005)↩︎
Martin Thullner, Pierre Regnier, and Philippe Van Cappellen, “Modeling Microbially Induced Carbon Degradation in Redox-Stratified Subsurface Environments: Concepts and Open Questions,” Geomicrobiology Journal 24 (2007): 139–155. (Thullner, Regnier, and Van Cappellen 2007)↩︎
C. Rabouille and J.-F. Gaillard, “A coupled model representing the deep-sea organic carbon mineralization and oxygen consumption in surficial sediments,” Journal of Geophysical Research 96 (1991): 2761–2776. (Rabouille and Gaillard 1991)↩︎
Derek R. Lovley and Francis H. Chapelle, “Deep Subsurface Microbial Processes,” Reviews of Geophysics 33 (1995): 365–381. (Lovley and Chapelle 1995)↩︎
Douglas E. LaRowe and Jan P. Amend, “Catabolic rates, population sizes and doubling/replacement times of microorganisms in natural settings,” American Journal of Science 315 (2015): 167–203. Comprehensive compilation of metabolic rates spanning twelve orders of magnitude across Earth’s biosphere. (D. E. LaRowe and Amend 2015)↩︎
Douglas E. LaRowe and Jan P. Amend, “Catabolic rates, population sizes and doubling/replacement times of microorganisms in natural settings,” American Journal of Science 315 (2015): 167–203. Comprehensive compilation of metabolic rates spanning twelve orders of magnitude across Earth’s biosphere. (D. E. LaRowe and Amend 2015)↩︎
Douglas E. LaRowe and Jan P. Amend, “Catabolic rates, population sizes and doubling/replacement times of microorganisms in natural settings,” American Journal of Science 315 (2015): 167–203. Comprehensive compilation of metabolic rates spanning twelve orders of magnitude across Earth’s biosphere. (D. E. LaRowe and Amend 2015)↩︎
Douglas E. LaRowe and Jan P. Amend, “Catabolic rates, population sizes and doubling/replacement times of microorganisms in natural settings,” American Journal of Science 315 (2015): 167–203. Comprehensive compilation of metabolic rates spanning twelve orders of magnitude across Earth’s biosphere. (D. E. LaRowe and Amend 2015)↩︎
Craig M. Bethke et al., “The thermodynamic ladder in geomicrobiology,” American Journal of Science 311 (2011): 183–210. (Bethke et al. 2011)↩︎
Craig M. Bethke et al., “The thermodynamic ladder in geomicrobiology,” American Journal of Science 311 (2011): 183–210. (Bethke et al. 2011)↩︎
Martin Thullner, Pierre Regnier, and Philippe Van Cappellen, “Modeling Microbially Induced Carbon Degradation in Redox-Stratified Subsurface Environments: Concepts and Open Questions,” Geomicrobiology Journal 24 (2007): 139–155. (Thullner, Regnier, and Van Cappellen 2007)↩︎
A. W. Dale et al., “Pathways and regulation of carbon, sulfur and energy transfer in marine sediments overlying methane gas hydrates on the Opouawe Bank (New Zealand),” Geochimica et Cosmochimica Acta 74 (2010): 5763–5784. (Dale et al. 2010)↩︎
Bruce E. Rittmann and Perry L. McCarty, Environmental Biotechnology: Principles and Applications (McGraw-Hill, 2001). (Rittmann and McCarty 2001)↩︎
J. J. Heijnen and J. P. Van Dijken, “In search of a thermodynamic description of biomass yields for the chemotrophic growth of microorganisms,” Biotechnology and Bioengineering 39 (1992): 833–858. (Heijnen and Van Dijken 1992)↩︎
Douglas E. LaRowe and Philippe Van Cappellen, “Degradation of natural organic matter: A thermodynamic analysis,” Geochimica et Cosmochimica Acta 75 (2011): 2030–2042. Thermodynamic framework for predicting organic matter reactivity and microbial yield. (Douglas E. LaRowe and Van Cappellen 2011)↩︎
Konstantin Stolpovsky et al., “Incorporating dormancy in dynamic microbial community models,” Ecological Modelling 222 (2011): 3092–3102. (Stolpovsky et al. 2011)↩︎
Bruce E. Rittmann and Perry L. McCarty, Environmental Biotechnology: Principles and Applications (McGraw-Hill, 2001). (Rittmann and McCarty 2001)↩︎
J. J. Heijnen and J. P. Van Dijken, “In search of a thermodynamic description of biomass yields for the chemotrophic growth of microorganisms,” Biotechnology and Bioengineering 39 (1992): 833–858. (Heijnen and Van Dijken 1992)↩︎
Douglas E. LaRowe and Philippe Van Cappellen, “Degradation of natural organic matter: A thermodynamic analysis,” Geochimica et Cosmochimica Acta 75 (2011): 2030–2042. Thermodynamic framework for predicting organic matter reactivity and microbial yield. (Douglas E. LaRowe and Van Cappellen 2011)↩︎
Harvey W. Blanch, “Invited Review: Microbial Growth Kinetics,” Biotechnology and Bioengineering 23 (1981): 1691–1722. (Blanch 1981)↩︎
Harvey W. Blanch, “Invited Review: Microbial Growth Kinetics,” Biotechnology and Bioengineering 23 (1981): 1691–1722. (Blanch 1981)↩︎
Harvey W. Blanch, “Invited Review: Microbial Growth Kinetics,” Biotechnology and Bioengineering 23 (1981): 1691–1722. (Blanch 1981)↩︎