Abstract
Prebiotic chemistry for the origin of life requires a high degree of chemical and mineralogical complexity with the potential for multiple reactions under differing physico-chemical conditions. This includes processes that can promote the condensation reactions required to form polymers and the mechanisms to concentrate trace elements that can catalyze polymerization reactions. Competing hypotheses for favorable settings for life to emerge include submerged ocean hydrothermal vents and subaerial, terrestrial hot spring fields. A key challenge for permanently submerged hydrothermal vents is the inevitable dilution that occurs when fluids are ejected from deep-sea hydrothermal vents into a relatively uniform oceanic reservoir, meaning that whatever geochemical complexity that may have developed in the subsurface conduits of such systems is rapidly lost. Open water systems also lack the ability to form polymers and concentrate the trace elements required to catalyze polymerization reactions. Terrestrial hot spring environments experience wet–dry cycling, concentrate elements through multiple processes, and can have a range of pH values, yet they are regarded by some as unfavorable sites because they are too hot (the tar problem) and typically portrayed as individual, relatively static pools (e.g., Darwin’s “Warm Little Pond”). Here, we illustrate how the terrestrial hot spring field of the Taupō Volcanic Zone (TVZ) of New Zealand is much more dynamic and geochemically diverse than generally considered due to the many closely located pools with widely variable physico-chemical attributes that mix components at a variety of scales, creating a level of geochemical complexity unmatched elsewhere on Earth. The tens to thousands of diverse surface pools of the TVZ are characterized by wet–dry cycling and multiple mechanisms that can concentrate trace elements and mix fluids of very different composition that result in geochemical variability as well as mineral precipitation that can enhance the preservation of biosignatures.
Introduction
A current debate relevant to origin of life (OoL) hypotheses centers on whether alkaline deep- or shallow-sea hydrothermal vents (e.g., Russell and Hall, 2006; Russell et al., 2010; Lane et al., 2010; Shibuya and Takai, 2022; Kitadai et al., 2024; Tagawa et al., 2024), terrestrial hot springs (Mulkidjanian et al., 2012; Forsythe et al., 2015; Pearce et al., 2017; Van Kranendonk et al., 2017, 2021; Damer and Deamer, 2020; Barge and Price, 2022), or tidal (e.g., Lathe, 2004) or other land-based environments (Jerome et al., 2022) are the most likely sites that could have provided the chemical ingredients and processes that led to the OoL. Key to this debate is the ability of these settings to provide the physico-chemical complexity necessary to support the multitude of reactions required to generate the complex organic molecules and interactive processes used by even the simplest (prokaryotic) life to effect metabolism (e.g., Kitadai and Maruyama, 2018). In addition, any site must have the capacity to promote organic molecule polymerization (e.g., Deamer, 2012); encapsulate organic matter within a lipid membrane (e.g., Monnard and Deamer, 2002; Rajamani et al., 2008; Milshteyn et al., 2018); and concentrate the elements required for life, including not only CHNOPS but also trace elements such as B, Zn, and Mn (e.g., Grew et al., 2011; Kim et al., 2011; Mulkidjanian et al., 2012; Van Kranendonk et al., 2017, 2021).
Both deep-sea vents and terrestrial hot spring fields are characterized by elevated temperature water/rock interactions that can promote complex chemical reactions (e.g., Russell and Hall, 2006; Russell et al., 2010; Deamer and Georgiou, 2015). Various studies have suggested mechanisms for organic molecule polymerization at these sites, including at deep-sea hydrothermal vents where liquid/supercritical-CO2 fluids in modern, and possibly Hadean, hydrothermal systems could act as an organic solvent to potentially initiate the dehydration synthesis of organic molecules (e.g., Shibuya and Takai, 2022; Kitadai et al., 2024; Tagawa et al., 2024). However, many researchers now regard land-based settings as more conducive to the formation of organic polymers on account of their lower concentration of ionic solutes, ability to undergo wet–dry cycling, and capacity to concentrate key elements (Monnard and Deamer, 2002; Mulkidjanian et al., 2012; Ross and Deamer, 2016; Forsythe et al., 2015; Van Kranendonk et al., 2017, 2021; Milshteyn et al., 2018; Becker et al., 2019; Damer and Deamer, 2020).
What remains poorly documented is the level of physico-chemical complexity and reactivity that these sites are able to generate. For example, although modeling suggests that a degree of chemical complexity may be achieved within deep-sea vents (Martin et al., 2008; Lane et al., 2010; Branscomb et al., 2017), these sites are limited by having permanently wet conditions and high salt contents that preclude lipid protocell formation (Deamer and Barchfeld, 1982). Deep-sea vents are also limited because they are dilute with respect to key OoL elements/molecules and have limited potential for chemical diversification (e.g., Monnard and Deamer, 2002; Mulkidjanian et al., 2012).
Hot springs, on the other hand, are viewed by some as unsatisfactory because they are generally portrayed only as a single pool (e.g., Darwin’s “Warm Little Pond”) that consequently lacks diversity and the potential for complexity, and because the most well-known pools—such as Grand Prismatic Spring in Yellowstone or Champagne Pool in New Zealand—are hot, which can be detrimental to the formation and stability of complex organic molecules for prebiotic chemistry (e.g., Benner et al., 2012). Additional potential problems with hot springs as the site for the OoL include more exposure to damaging UV light, generally short-term duration compared with deep-sea vents, lack of a mechanism to provide a continuous exogenous source of organic building blocks, and lack of a persistent, reliable source of chemical energy (see, e.g., Brazil and Chemistry World, 2017). Counters to these issues have been summarized elsewhere (e.g., see Mulkidjanian et al., 2003; Ranjan and Sasselov, 2016; Van Kranendonk et al., 2017; Damer and Deamer, 2020, and references therein).
However, it is important to recognize that hot springs occur in geothermal fields of several tens to thousands of closely spaced pools that have remarkably diverse physical and chemical characteristics and that not all springs are boiling hot (e.g., Renaut and Jones, 2011; Jones and Renaut, 2012; Power et al., 2018; Steller et al., 2019). For example, Yellowstone has >10,000 pools that range from boiling to ambient temperature, have acidic to alkaline pH values, and precipitate different mineralogical deposits (e.g., silica, carbonate, iron, and manganese oxides; Fournier, 1989). Hot springs in Yellowstone are also highly diverse with respect to their inventory of organic molecules and dissolved major, minor, and trace elements, which can vary in concentration by multiple orders of magnitude and, in some cases, be distributed across decimeters to tens of meter scale distances (e.g., Fournier, 1989; Ball et al., 2002; Chafetz and Guidry, 2003; Hurwitz and Lowenstern, 2014; Gonsior et al., 2018). Similarly, the Taupō Volcanic Zone of New Zealand contains multiple, geochemically diverse pools scattered in fields over a wide area (Fig. 1A).
Schematic map of the northern part of the Tikitere/Hell’s Gate geothermal area, showing the pH (outer rings) and temperature (interior color fill) of the major springs in this area. Insets:
Variability in the pH and chemistry of hot springs has, in general, been shown to be controlled by subsurface processes, especially when near-surface boiling occurs (Supplementary Fig. S1: Ellis and Wilson, 1961; White et al., 1971; Truesdell and Fournier, 1976; Fournier, 1989; Hedenquist and Lowenstern, 1994; Barnes, 1997; Nordstrom et al., 2009; Power et al., 2018; Havig et al., 2021). This is because near-surface boiling causes hydrothermal fluids (and the elements they contain) to partition into either a vapor phase (consisting of steam and any elements that favor the vapor phase) or a residual liquid phase. Hot springs fed by either of these end members can be categorized as either vapor phase dominant (VPD) or residual liquid phase dominant (RLPD). VPD hot springs on modern Earth have very low chloride but elevated sulfate concentrations (from oxidation of hydrogen sulfide concentrated with the vapor phase and subsequently oxidized to sulfuric acid), and low pH values that promote leaching of elements from local rock/soil sources (e.g., Ellis and Wilson, 1961; Fournier, 1989; Nordstrom et al., 2009). RLPD hot springs, in contrast, have slightly elevated chloride concentrations and moderately elevated sulfate concentrations relative to the original source water, but at lower concentrations than for VDP fluids (Supplementary Fig. S1). These springs also have elevated values of other elements that favor the liquid phase due to concentration from boiling, and they have mildly acidic to circum-neutral pH values buffered by bicarbonate. Due to complicated pathways to the surface, VPD and RLPD fluids can remix, creating variable fluid compositions and a wide range of pH values from strongly acidic to circum-neutral, which can vary on temporal as well as lateral scales (Supplementary Fig. S1: e.g., Fournier et al., 2002; Arnórsson et al., 2007; Power et al., 2018; Colman et al., 2021).
In contrast, in fields where there is minimal near-subsurface boiling and, consequently, minimum phase separation, chloride and sulfate concentrations derive from deep-sourced fluids and in-mixed groundwater, resulting in fluids with circum-neutral to alkaline pH and limited ranges of element concentrations (e.g., Havig et al., 2021).
The different types of fluids formed in the shallow subsurface also have the potential to mix with surface fluids (e.g., meteoric water, surface water, groundwater) to varying degrees, causing dilution, mineral precipitation, and changes in pH and T (e.g., White et al., 1988; Stefánsson et al., 2016). Furthermore, local topography and seasonal water level fluctuations cause individual springs to overflow and mix with adjacent springs, dried-up pools, and/or flowing streams (see Section 4.2.2). Additionally, pH values often increase down outflow channels due to volatilization/loss of CO2(aq), further altering mineral and elemental solubilities.
What has been less well documented is the way in which pools within hot spring fields interact and mix components, generating greater geochemical complexity. In this contribution, we provide data that demonstrates these phenomena through analysis of the physico-chemical characteristics (geometry, water, and sediment geochemistry) and fluid mixing styles of a set of hot springs from the Taupō Volcanic Zone, New Zealand (TVZ). Examples consist of a closely spaced range of highly diverse, linked to isolated pools, lakes, and streams that have a wide range of physico-chemical characteristics across a scale of tens of meters and that mix components through a variety of mechanisms, providing significantly increased complexity of surface environments.
These observations demonstrate that hot spring fields represent the most complex geological environments on Earth and thus the most likely top contender in which the components for life may have been assembled to construct the first living cells.
Water sample collection
Temperature, pH, and conductivity
Water temperature, pH, and conductivity were measured at each location. Temperature and pH were measured using a WTW 330i meter and probe (Xylem Analytics, Weiheim, Germany). Conductivity was measured using a YSI 30 conductivity meter and probe (YSI Inc., Yellow Springs, OH). Both instruments were calibrated and checked daily against standard solutions.
Water sample collection
Water samples were collected using a 140-mL acid-washed syringe (3-day soak in 10% TraceMetal Grade HNO3 followed by a triple rinse using 18.2 MΩ/cm deionized water). The syringe was acid-washed to leach out any trace element contaminants from within the plastic. At the field site, prior to sample collection, the syringe was then rinsed three times using the hot spring water. During sampling, the syringe was slowly filled to exclude air bubbles. Water samples were dispensed into two glass cuvettes, prerinsed with sample water, for spectrophotometric analysis of silica (SiO2), sulfide (S2−), and ferrous iron (Fe2+) (see Section 2.1.3). The remaining water was filtered through 25 mm 0.2 μm polyethersulfone syringe filters (VWR International, Radnor, PA) to sterilize and remove particulates, and then dispensed into new polypropylene centrifuge tubes (VWR) for different analyses: 10 mL was dispensed into a 15 mL centrifuge tube for spectrophotometric analyses of nitrate and ammonia (see Section 2.1.3); anion samples were filtered into a 15-mL centrifuge tube for ion chromatography. Samples for analysis with an induced coupled plasma mass spectrometer (ICP-MS) and an induced coupled plasma emission spectrometer (ICP-OES) were filtered into a 15-mL acid-washed centrifuge tube (3 days in 10% TraceMetal Grade HNO3 (Fisher Scientific, Hampton, NH) followed by triple rinsing with 18.2 MΩ/cm deionized water). These samples were acidified using 400 μL OmniTrace Ultra™ concentrated HNO3 (EMD Millipore, Billerica, MA) after each field day. Then, 2 mL of the sample was filtered into a 2-mL microcentrifuge tube for D/H and δ18O analysis. Samples for dissolved inorganic carbon (DIC) were filtered into a three-way stopcock/needle/5-mL gas-tight syringe and then injected into a He-purge Labco Exetainers® (Labco Limited, Lampeter, UK) with excess He removed following the addition of 4 mL of sample. Then, 40 mL of the sample for dissolved organic carbon (DOC) was filtered into a sterilized 50-mL centrifuge tube, which was then flash frozen on dry ice in the field and kept frozen until analysis. All samples (except those flash frozen) were kept cool with water ice during fieldwork and then kept at 4°C in the dark until analysis. Prior to analyses, 1 mL of H3PO4 was added to each DIC sample.
Spectrophotometric measurements
Total dissolved silica, sulfide, and ferrous iron (Fe2+) were measured on site using a DR1900 portable spectrophotometer (Hach Company, Loveland, CO). Dissolved silica values should be treated as qualitative estimates, as higher temperatures and interferences from other aqueous species are known to affect the colorimetric chemical reaction involved with the Hach methods (unpublished data). After each field day, nitrate and ammonia were also measured using the portable spectrophotometer via powder pillows upon return to the laboratory to minimize interferences from temperature and interfering chemical species (e.g., sulfide).
Water chemistry analysis
Elemental analysis
Anion samples were measured using a Thermo Scientific Dionex ICS 5000 + ion chromatography system. Cations were measured using a Thermo Scientific iCAP 6000 series ICP-OES. Trace element analysis was carried out using a Thermo Scientific X Series 2 ICP-MS. All anion, cation, and trace element analyses were carried out by the Quantitative Bio-element Imaging Center (QBIC) at Northwestern University.
Carbon concentration and isotopes
Samples for DIC and DOC were analyzed by the Stable Isotope Facility (SIF) at the University of California, Davis using a GasBench II system interfaced to a Delta V Plus isotope ratio mass spectrometer (IR-MS) (Thermo Scientific, Bremen, Germany) for concentration and δ13C signal, with raw delta values converted to final values with the use of standards provided at the SIF (lithium carbonate, δ13C = −46.6‰ and a deep seawater, δ13C = +0.8‰) calibrated against standards NBS-19 and L-SVEC. DOC analyses for concentration and 13C isotopic signal were carried out using an OI Analytical AURORA Model 1030 TOC Analyzer (College Station, TX). The ratio of 13C/12C of the sample or standard is reported in comparison to that of the Vienna Pee Dee Belemnite (VPDB) standard and calculated using the equation:
Water isotopes (oxygen and hydrogen)
Water δ18O and D/H ratios were analyzed using method 2017 A on a Picarro L2130-i Cavity Ringdown Spectrometer with a Vaporization Module Autosampler. Analyses were calibrated using Picarro standards (ZERO, δ18O = 0.3‰ and D/H = 1.8‰; MID, δ18O = −20.6 ‰ and D/H = −159.0 ‰; and DEPL, δ18O = −29.6‰ and D/H = −235.0‰, all vs. Vienna standard mean ocean water (VSMOW)) and checked against an internal lab standard (MLPS rainwater). δ18O D/H isotopic values are reported as are carbon stable isotopes, analyzed at the Gibson Hydrogeochemistry Laboratory, University of Minnesota.
Sediment sample collection and preparation
The 50-mL centrifuge tubes were acid-washed initially by first soaking the tubes for 24-hours in active cleaning agent DECON 90, followed by a 24-hour soak in 10% nitric acid, and triple rinsed with deionized (DI) water. Then, 50 mL of each sediment sample was collected using an ethanol-cleaned stainless-steel spatula, placed into a centrifuge tube or zip-lock bag, and stored in refrigerated conditions.
Sediment sample analysis
X-ray diffraction analysis
A set of 68 sediment samples was analyzed by powder X-ray diffraction (XRD) to identify the major mineralogical phases and determine the proportion of minerals. Approximately 1–2 g of each sediment sample was air-dried and pulverized into powder using an agate mortar and pestle, cleaned with ethanol between each sample. A PANalytical Empryrean diffractometer was operated for sample analysis at 45 kV and 40 mA with CuKα radiation (λα1 = 1.54060 Å; λα2 = 1.54443 Å). Diffraction patterns were collected from 5 to 70° 2ϴ with a 0.02° step size, a 1° fixed divergence slit, and an integrated dwell time of 70–100 s/step. Highscore Plus software was utilized for data processing, with mineral identification based on comparison of analyzed sample diffraction patterns to reference materials in the Crystallography Open Database (COD) (Gražulis et al., 2020), and to perform Rietveld analyses to quantify mineral proportions. X-ray amorphous mineraloid proportions were calculated using the procedure described by Rowe et al. (2012). The relative proportions of amorphous and crystalline components were quantified using a series of XRD standards created from mixtures of glass and mineral (quartz, plagioclase feldspar, alkali feldspar) powders (0%–100% crystallinity in 10% increments).
Sediment geochemistry analysis
Geochemical analyses of sediment samples were performed at the Pheasant Memorial Laboratory, Institute for Planetary Materials (PML), Okayama University (Misasa, Japan) following the procedures utilized in Yokoyama et al. (1999), Makishima and Nakamura (2001, 2006), Makishima et al. (2002), Lu et al. (2007), and Nakamura et al. (2022).
Sediment samples were transferred into new 15 mL Falcon tubes and centrifuged at 3000 rpm for 5 min. The resulting fluid supernatant was removed using a single-use plastic syringe and placed into a polypropylene container. One-half of the sediment separate was scooped into an alcohol-cleaned Teflon container and then immersed in deionized milli-Q water (USQ; Nakamura et al., 2022) and centrifuged at 3500 rpm for 3 min, with the supernatant removed by pipetting. This procedure for separating the sample supernatant was repeated three times. Each sample was then dried in the Teflon container that was placed on a hot plate in a clean-evaporator at ∼90°C for 24 h and then homogenized using a heat-sterilized silicon nitride mortar and pestle.
Trace, major, and minor elements were determined by induced coupled plasma mass spectrometry with a quadrupole analyzer using a Thermo Fisher Scientific iCAP TQ and by induced coupled plasma sector field mass spectrometry using a Thermo Fisher Scientific ELEMENT XR, respectively, in duplicate, with relative differences generally less than 5%, although Ni, Cu, Zn, In, and Ba showed relative differences >10%. These variations were not systematic across samples (i.e., which would indicate variation dependence on concentration or measured signal intensity), which indicates sample heterogeneity. For Sb, samples were redecomposed with only an Sb spike and analyzed independently. Sulfur and Cr concentrations were determined simultaneously by isotope dilution with S and Cr spikes.
Results
Detailed maps and analytical data of the individual study areas, which include records of in situ measurements, are presented in Figures 1–6. Geochemical data are presented in Table 1 (hot spring fluids) and Table 2 (sediments) from the three studied hot spring areas: Tikitere, Champagne Pool, and Alum Cliffs.
Digitate nodular silica deposits in the outflow stream of Pool EP2 at Tikitere (see Fig. 1B for location).
Schematic map of the tourist area of the Wai-O-Tapu Thermal Wonderland. Blue ellipsoids = major hot springs; blue lines = streams; dashed black line = outline of “rotten ground”. Inset:
A carpet of filamentous sulfur-cycling bacteria (Beggiatoa) covering the floor of the outlet channel of Alum Cliffs Lake, and a surface concentration of sulfur bacteria-coated collapsed bubbles.
Geochemical Data for the Sampled Fluids from the Study Areas
DIC, dissolved inorganic carbon; DOC, dissolved organic carbon; St Dev, Standard Deviation; Cond, Conductivity.
Geochemical Data for the Sampled Sediments from the Study Areas
Samples with prefix TIK‐C are from the Tikitere Study Area (Fig. 1), whereas those with prefix WT are from the Wai‐O‐Tapu Thermal Wonderland; DL, Detection Limit; RPD, Reproducibility, as 1 standard deviation.
The hot spring fields of the TVZ are situated over a relatively shallow magmatic source (∼4 km depth; Wilson and Rowland, 2016), which drives relatively intense subsurface boiling that leads to geochemical extremes in elemental concentrations between VPD and RLPD fluids (Kissling and Weir, 2005; Hurwitz and Lowenstern, 2014). TVZ pools are generally closely spaced (a few meters or less), with large differences in temperature, pH, and geochemistry between adjacent pools (Power et al., 2018). This situation contrasts with that of the hot spring fields of Yellowstone National Park, USA, which are positioned above a deeper magma chamber, 5–10 km below the surface (Hurwitz and Lowenstern, 2014). The Yellowstone architecture results in the fluids that interact with the hot magma chamber having a longer distance to travel to the surface, leading to larger hot springs that are more spread out (hundreds to thousands of meters) along gradients that are flushed by fresh water (Hurwitz and Lowenstern, 2014).
Hot spring physico-chemical complexity arising from surface mixing between locally complex distributions of closely adjacent pools is documented here for three areas within the TVZ: Tikitere, Champagne Pool, and Alum Cliffs (Fig. 1A). Surface mixing processes highlighted in this work include simple binary mixing of pool fluids; complex mixing of multiple pool fluids; evaporation, cooling, and mineral precipitation; redox gradients; turbulent flow; and overspill and mixing back into the subsurface and/or with other surface fluids. Collectively, the study areas demonstrate complex mixing through a range of processes that lead to increased geochemical complexity that is relevant to our understanding of the OoL.
Tikitere
The Cooking Pool area of Tikitere (Fig. 1B; Española, 1974) provides an example of a system fed by fluids produced by binary mixing between two distinct pool fluids and demonstrates how evaporation along outflow channels leads to an increase in the concentration of biologically relevant elements. Here, water spills out from two closely adjacent, geochemically distinct source pools (EP1 = Cooking Pool and EP2 = Northern Green Pool) and down shallow outflow channels that merge at a mixing zone before entering and mixing with the fluids of Hot Sulfur Lake (main panel in Fig. 1).
Geochemical variability from subsurface processes
EP1 is clear, has a pH = 6.09, is 73.8°C, has a Cl− concentration of 141 µmol/L, 0.622 mmol/L SO42−, 208.63 µmol/L sulfide, DIC = 177.19 µg C/mL, δ18OVSMOW = 8.83 ‰, and a D/HVSMOW = 4.61‰ (Table 1). In contrast, EP2 is dark, has pH = 5.92, and Cl− (146 µmol/L) and sulfide (197.72 µmol/L) concentrations like EP1 though it is cooler (69.3°C) and has distinct values of DIC (60.25 µg C/mL), SO42− (6.633 mM), δ18OVSMOW (3.85‰), and D/HVSMOW (−8.68‰) (Table 1). These data indicate that while both pools have a similar input of RLPD (i.e., similar chloride concentrations), EP2 is more strongly impacted by VPD, as highlighted by the order of magnitude higher sulfate and lower DIC concentrations.
Physical surface mixing
The fluids of springs EP1 and EP2 physically mix in the outflow channel that drains into Hot Sulfur Lake (Fig. 1B), producing intermediate values of DOC, δ13C, δ18O, and D/H at the mixing zone compared with the values in each pool (sample TICK-C-MX in Table 1). This sample has very low sulfide concentration and low temperature, resulting in low ionic conductivity, despite high concentrations of other elements (i.e., Ca, Al, Cr, Mn, Fe).
Evaporation and cooling
Changes to fluid composition in the outflow channel are also controlled by additional surface processes, such as evaporation, cooling, and mineral precipitation that arise from low flow rates spread out over relatively large surface areas (e.g., Reed and Palandri, 2006). These processes cause fluid temperature to drop, a loss in DIC (via dissolution and loss to the atmosphere as CO2(g)) and DOC (taken up into biomass or metabolized into CO2(g) via microbial activity), and precipitation of various minerals and elements, resulting in decreased conductivity in the fluids (Table 1; Nordstrom et al., 2009; Reed and Palandri, 2006; Havig et al., 2021). These changes are evidenced by comparing the DIC concentration and δ13C value for EP1 (177.19 μg C/mL, −6.47‰) and EP2 (60.25 μg C/mL, −5.91 ‰), with the dramatically decreased DIC concentration (10.08 μg C/mL) and enriched δ13C value (+4.18‰) in the mixing zone arising from the preferential loss of 12CO2(g) to the atmosphere (Table 1). The loss of DIC down the mixed outflow channel is reflected in the increase in pH of the fluids to 6.51.
Evaporation accompanied by cooling is demonstrated by the fact that elements dissolved within each of the pool fluids increase in concentration down the outflow channel compared with either of pools EP1 and EP2 (including higher concentrations of Cl−, SO42−, Al, P, Ca, V, Cr, Mn, Co, Cu, Zn, As, Rb, Sr, Mo, and Sb; Table 1).
Mineral precipitation
Another critical process in changing the composition of outflow fluids at Tikitere is mineral precipitation. Precipitation of silica in the outflow channel is reflected not only by the observed precipitation of digitate nodules of silica sinter (Fig. 2; Sriaporn et al., 2020), but also in the dissolved silica concentration, which is lower in the outflow channel (7.44 mmol/L) than in the source pools (EP1 = 8.95 mmol/L, EP2 = 10.19 mmol/L). This is despite the evidence for evaporative concentration of other elements in the water discussed above. The amount of Sb dissolved in fluid is controlled by dissolved sulfide concentration, pH, and temperature (Wilson et al., 2012): at increased sulfide concentrations and lower pH, the concentration of Sb decreases due to the precipitation of Sb-sulfides. Indeed, Sb concentration is highest in fluids from the mixing zone, where the concentration of dissolved sulfide (24.32 μmol/L) is the lowest, and the pH (6.51) is the highest (Table 1).
A sediment sample in the mixing zone channel (TIK-C-MX-S2 from point X in Fig. 1B) has Be, Na, and Ca at values somewhat intermediate between the two source pool sediment samples, derived from mixing between the two pool fluids as noted above, though values of Al, Mg, Fe, Cr, Co, Ni, Cu, and Zn are all at significantly lower concentrations than in either source pool, which suggests precipitation/sequestration of elements upstream at the initial mixing point between EP1 and EP2 fluids (Table 2). The concentration of S in the mixing zone sediment, however, is dramatically higher (297,614 μg/g) relative to either of the source pool samples (4967 μg/g at EP1 and 24,226 μg/g at EP2). Elemental sulfur, which can be precipitated as original sulfide, is oxidized by O2 from the atmosphere or through sulfide-oxidizing bacteria, both processes taking place with increasing evaporation, cooling, and exposure to the atmosphere (e.g., Pokrovski et al., 2008).
Some elements dissolved in the pool fluids are incorporated into minerals, such as amorphous silica, pyrite, sulfur, and alunite, as measured in the outflow channel of EP2 (samples TIK-C-EP2 and TIK-C-MX-S3; Table 2). For example, metal and nonmetal elements are at higher concentrations in the sediments close to the source pool and lower concentrations within the sediments of the outflow channel margin (i.e., the unmixed part), as their distribution is controlled by the pH, temperature, and redox state of the fluid.
Microbial cells, biofilms, and exopolymeric substances (EPS), the latter secreted by microorganisms for their survival (e.g., for nutrient and enzyme facilitation, toxin exclusion, and substrate attachment; Briggs, 2003; Hall-Stoodley et al., 2004), may become incorporated into hot spring minerals and mineraloids (e.g., Weed, 1889; Westall et al., 2000; Handley and Campbell, 2011 and references therein). These microbial features have been reported to influence the morphological development of siliceous sinter deposits, for example, as shown in field growth experiments by Handley et al. (2005, 2008), where filamentous microbial colony clusters became coated with amorphous silica around the rim of Champagne Pool. Repeated surface colonization, followed by silicification of biofilms and EPS, produces sinter laminations that accrete as spicular sinter microstromatolites. Silicification of biofilms appears to be passively induced (Urrutia and Beveridge, 1993; Westall et al., 1995), although experimental studies of cyanobacteria undergoing silicification revealed a physiological response to mineral encrustation (i.e., thickening of the polysaccharide sheath; Benning et al., 2004a, 2004b). Furthermore, the active or passive sequestration of metals by microbes and precipitation of silica and iron minerals in association with microorganisms have been reported in several studies (e.g., Cady and Farmer, 1996; Konhauser and Ferris, 1996; Phoenix et al., 2000, 2005; Phoenix and Konhauser, 2008; Churchill et al., 2021; Gangidine et al., 2020, 2021; Murphy et al., 2021; Nersesova et al., 2024).
When considered collectively, these results demonstrate that changes in the geochemical environment down the outflow channel drive changes in mineral precipitation that could potentially lead to variations in mineral/mineraloid/element encrustation and/or templating on microbial colonies and biofilms growing on benthic and marginal hot spring outflow channel surfaces. These changes would then also be subject to shifting discharge volumes and/or subsurface geochemical inputs, as well as variations in precipitation input across seasons, illustrating the potential for multiple types of changes that can occur within a single outflow channel over time.
Turbulent mixing
The final method of increasing the physico-chemical complexity of fluids at this locality is evident at the drainage channel south of the pool called “The Big One” (Fig. 1C). Here, the channel is characterized by rapid flow and displays turbulent eddies that mix hot (50–60°C) fluids draining from the center of The Big One with muddier fluids that have cooled along the pool margins (20–30°C). This mixing results in a fluid with intermediate temperature (41.3°C) that cools further downstream and fills a cool (30–40°C), yet still acidic (pH = 3), unnamed pool to the south (blue-filled pool in main panel of Fig. 1).
Champagne Pool
The main tourist area of the Wai-O-Tapu (Fig. 3) Thermal Wonderland at Rotorua, New Zealand, comprises a large silica sinter terrace (Artist’s palette: Fig. 3A) located on the flanks of Champagne Pool, which is a CO2-effervescing, As-Au-Sb precipitating hot spring pool with pH = 5.4 and T = 74°C, Cl− = 53.0 mmol/L, and SO42− = 1.27 mmol/L (Fig. 3B; Giggenbach et al., 1994: Childs et al., 2008; Power et al., 2018). The Sb and As precipitates of the pool are governed by diurnal sulfur redox chemistry (Ullrich et al., 2013).
Physical surface mixing
Fluids from Champagne Pool overspill in three directions. To the northeast, Champagne Pool fluids mix across a broad sinter terrace with those of a small, light green spring that is hot (c. 90°C), low pH, and S-rich (Fig. 3A).
Evaporation and cooling
To the north-northwest, fluids from Champagne Pool overspill, flow downhill through rotten ground (Fig. 3C), and undergo strong evaporation, finally collecting in Roto Kārikitea, a neon green colored, S-rich pool with a strong acidity (pH = 2) and remarkably cool temperature (14°C) (Fig. 3D).
Mineral precipitation
The overspilled fluids of Champagne Pool have precipitated a broad sinter terrace that fills a valley (Fig. 3E) that extends for ∼300 m south, downslope to the Alum Cliffs study area (Fig. 3F; see Section 4.3). Silica precipitation, input from small acidic springs and seeps, evaporation, and cooling across the terrace lead to a dramatic change in the fluid that flows out the bottom end, which is strongly acidic (pH = 2.51) and significantly cooler (32.4°C) than Champagne Pool itself.
Alum cliffs
Alum Cliffs is a complex area of multiple pools and mixing zones located in the southern part of the Wai-O-Tapu Thermal Wonderland (Figs. 3, 4). This area contains several small, clear to turbid source hot springs (samples WT-A-8, −10: pH = 3.1–5.5, T = 86–92.9°C) that are high in dissolved silica (5.06 to 8.71 mmol/L) and are assumed to be at, or above, saturation with respect to amorphous silica. These pools feed downslope, southwards, into a series of interconnected, slightly larger, turbid green pools (samples WT-A-6, −3; pH = 2.9–3.8, T = 53.2–71.7°C), which then drain north-northeastward into, and mix with (sample WT-A-5), the acidic stream (samples WT-A-1, −2; pH = 2.5, T = 32.5°C) that emanates from the Champagne Pool sinter terrace and flows south into the spring-fed Alum Cliffs Lake (pH = 2.5, T = 42°C). Two small, bright yellow springs that lie across either side of this stream have rim sediments highly enriched in As, Zn, and Cu (sample WT-A-13; Table 2) and fluids with pH = 3.1 at 90.7°C (Table 1). The warm (=36.9°C) acidic river (sample WT-A-14) that empties out of Alum Cliffs Lake has low pH (2.58) and lower Si concentration (3.81 mmol/L) than any of the source pools or the inflowing river.
Geochemical variability from subsurface processes
The hot spring pools sampled at Alum Cliffs (WT-A-3, −6, −8, −10, and −13 on Fig. 4) have relatively elevated Cl− (18.6–23.3 mmol/L) and SO42− concentrations (10.7–15.4 mmol/L) that are higher than the predicted pre-near-surface-boiling source fluid (Cl− ≈ 10 mmol/L, SO42− ≈ 1 mmol/L, Supplementary Fig. S1; Havig et al., 2021) but consistent with mixed residual liquid phase and vapor phase source inputs. The bright yellow arsenic-precipitating acidic pool WT-B-13 is unique relative to the other fluids analyzed here in having high dissolved SiO2 (523 mg/L), DOC (3.5 ppm), and As, P, Ca, and Zn, but low Al (56.7 mmol/L) (Table 1).
The acidic stream that flows into the Alum Cliffs Lake is fed by discharge from Champagne Pool, from adjacent springs to the north, as well as from the acidic Lake Whangioterangi (Echo Lake) to the east (pH = 2.4, Cl− = 6.80 mmol/L, SO42− = 3.96 mmol/L: Timperley and Vigor‐Brown, 1986). This stream (samples WT-A-1 and -2) has a Cl− concentration of 8.56 mmol/L and a high concentration of SO42− (10.26 mmol/L), which suggests that the primary source of Champagne Pool, adjacent springs, and Lake Whangioterangi derives from a high SO42− concentration vapor phase.
Physical surface mixing
At the Alum Cliffs site, the fluid composition of two hot, clear, and slightly elevated source pools (WT-A-8 and -10, both at ∼90°C) was analyzed and compared with the composition of two warm, turbid, and somewhat lower elevation pools (WT-A-6 and -3, at ∼72°C and 53°C, respectively). The hot pools were found to have higher total dissolved ionic concentrations and DIC than the warm pools; total SO42−, Cl−, Al; and the values of many of the other elements analyzed were all at higher or variable concentration levels in the warm pools relative to the hot pools (Table 1). These findings indicate that temperature variations between the connected pools do not simply reflect dilution by cool surface waters, but that there are variable fluid components and variable degrees of mixing between all of the different pools in this area. Temperature plays a clear role in the level of ionic concentration across all of the fluids in this area, with pH having a lesser role (Fig. 5).
These hot springs have Li, B, Na, K, Ca, As, S2−, and DIC concentrations that are higher than in the inflowing acidic stream, whereas Mg, Fe, Co, and Ni concentrations are lower than in the stream, and Al, Ti, Mn, Cu, Zn, Mo, Sb, and W, as well as NH4(T) and Fe2+ concentrations, overlap with the stream values (Table 1). These data illustrate how input from the Alum Cliffs hot to warm springs and pools, and from the springs that bubble up into Alum Cliffs Lake itself, has changed the composition of fluids of the inflowing acidic creek, as also reflected by the composition of the outflow creek fluids (sample WT-C-14) that show increases in Li, B, Na, Al, K, Ca, Fe, Cu, Zn, As, and W, as well as S2−, Fe2+, and DIC concentrations, and decreases in the concentrations of Mg, Mo, Sb, as well as NH4(T) and NO3− (Table 1). The impact of this mixing is also reflected by the increased concentration of Cl− (11.63 mmol/L) and SO42− (11.74 mmol/L) in the outflow stream that—uniquely in this area—hosts a thriving sulfur-based microbial community (Fig. 6), reflective of the high S contents (e.g., Sriaporn et al., 2023).
Mineral precipitation
The shifts in aqueous geochemistry documented for this site are mirrored by changes in sediment element contents (Table 2). For example, light tan turbid pool WT-A-6 (pH = 3.80, T = 71.7°C) flows into light yellow-green pool WT-A-7 (pH = 2.94, T = 52.9°C). The sediments in the mixing zone between these pools (Wt-A-7S) have higher Al, Na, Mg, and Ca concentrations than sediments from the rim of the source pool (WT-A-6S), suggesting precipitation of aluminosilicate minerals. An increase in relative Fe content and a decrease in total sulfur (likely reflecting a decrease in the amount of elemental sulfur present) from the source pool to the mixing zone suggest pyrite precipitation, although trace element concentrations (e.g., Cr, Mn, Co, Ni, Cu, and Zn) show no change between the two sites.
Discharge from dark brown turbid source pool WT-A-8 (pH = 3.07, T = 86.0°C) flows into a light yellow-green pool (WT-A-9, with pH = 3.09, T = 44.3°C). Sediments in the source pool (WT-A-8s) and in the outflow mixing zone (WT-A-9S) showed no discernible changes in either the concentration of the major elements (Al, Na, Mg, K, Ca) or the trace elements, which is interpreted to reflect the similarity in pH, which minimizes any mineral saturation changes. However, Fe and S concentrations were higher in the mixing zone sediments, which attests to precipitation of pyrite and oxidation of sulfide to elemental sulfur.
The clear and dark brown source pool WT-A-10 (pH 5.50, T = 92.9°C) discharges into an unlabeled yellowish-green pool (pH 3.11, T = 45.8°C), which then flows into another unlabeled light yellowish-green pool (pH ∼ 3, T = 44.0°C) (Fig. 4). Sediments were collected from the source pool rim (WT-A-10S), from the entry point into the first unlabeled pool (WT-A-11S), and at the entry point to the second unlabeled pool (WT-A-12S). Whereas Na and Mg increased in concentration in the sediments from the first pool through to the second mixing zone, K and Ca values decreased at site 11S compared with site 10S but then increased again at site 12S. The trace elements Cr, Ni, Cu, and Zn increased across the three sites, whereas Al decreased across the 10S and 11S transition, suggesting mineral precipitation in the outflow from pool 10 due to the decrease in pH or a shift in porewater element concentration. Across this transition, Fe concentration decreased by half, whereas total sulfur increased, suggesting that there was greater precipitation of Fe as pyrite in the source pool, while more oxidation of sulfide to elemental sulfur occurred in the mixing zones.
Bright yellow, As-rich pool WT-A-13 (pH = 3.10, T = 90.7°C) discharges directly into the Alum Cliffs Lake (pH = 2.50, T = 42.1°C) (Fig. 4). Sediments collected from the rim of the As-rich pool (WT-A-13-1S) were compared with those from the small delta deposit at the mixing zone between the discharge fluid from this spring and the water of Alum Lake (WT-A-13-2S) and ∼30 cm further away from the outflow channel water on the shore of the lake (WT-A-13-3S) (Table 2). Sample 13-2S contained higher concentrations of the major elements (Al, Na, Mg, K, Ca) compared with the source pool sediments (WT-A-13-1S), suggesting precipitation of aluminosilicates. Total Fe also increased in relative concentration across this first transition, whereas total S decreased, suggesting precipitation of Fe as pyrite at both localities, but accompanied by the additional precipitation of S as elemental sulfur at the source pool. The relative concentration of trace elements showed no distinct trend across all three sites, though P increased at all three sites, perhaps reflecting an increase in biological activity away from the hot source pool. The Alum Cliffs lakeshore sediment (13-3S) was lower in major element concentrations and three times higher in total sulfur concentration.
Reflecting the input of the Alum Cliffs hydrothermal area, sediments from the acidic stream flowing out from Alum Cliffs Lake (sample WT-A-14S) show a relative decrease in Al, Na, Mg, Ca, Cr, Mn, Fe, No, Ni, Li, and Zn concentration, but an increase in Cu, Mo, Sn, Sb, Pb, and U compared with sediments from the inflowing acidic stream (samples WT-A-1S and -2S) (Table 2).
Implications for the OoL
The OoL would have required multiple complex chemical reactions (e.g., Kitadai and Maruyama, 2018) under a variety of temperature and pH conditions and in the presence of diverse rock and mineral surfaces (including fresh basaltic glass and clay minerals), exposure to UV radiation and the energy from meteorite impacts, fresh—not salty—water, wet–dry cycling, and the ability to concentrate the elements required to promote polymerization (e.g., Monnard and Deamer, 2002; Ferris, 2005; Kim et al., 2011; Mulkidjanian et al., 2003, 2012; Ferus et al., 2015; Forsythe et al., 2015; Ranjan and Sasselov, 2016; Milshteyn et al., 2018; Osinski et al., 2020; Van Kranendonk et al., 2021; Zhao and Wang, 2021; Jerome et al., 2022; Steller et al., 2022). While some of these conditions can be met in deep or shallow marine hydrothermal vents or in marine tidal pools, marine sites generally have significant limitations in terms of their ability to concentrate prebiotically important elements, promote polymerization, enhance lipid protocell formation, and develop geochemical environments that drive increasingly complex prebiotic chemistry, while tide pools are too ephemeral and salty to develop significant geochemical complexity.
As a result, attention has turned to terrestrial sites where surface and subsurface processes generate a complex range of physico-chemical environments, subaerial exposure allows for additional rock-air and water–air reactive interfaces in addition to the hot water–rock interactions that also occur in deep-sea hydrothermal vents, concentration of prebiotically important elements can occur in distinct geochemical environments within individual hot springs, and evaporation and/or pulsing and/or geyser splashing can drive critical wet–dry cycling across a range of timescales (e.g., Mulkidjanian et al., 2012; Forsythe et al., 2015; Van Kranendonk et al., 2017, 2021; King et al., 2018; Rimmer and Shorttle, 2019; Damer and Deamer, 2020; Peters et al., 2023; Nan et al., 2024). Furthermore, the diversity of surface geochemical environments within hot spring fields, including the ability of individual pools to mix components (e.g., cold to hot pools, neutral to acidic pH, turbulent or laminar mixing, seasonal variability in rainfall and evaporation), as documented here and in previous studies, demonstrates that terrestrial hot spring fields have the capacity to drive complexity in geochemical and mineralogical environments on scales of centimeters to several hundreds of meters (see also Fournier et al., 2002; Shock et al., 2010; Gardner et al., 2011; Ward et al., 2017; Gonsior et al., 2018; Colman et al., 2021; Power et al., 2023).
This conclusion is important, as terrestrial hot springs have been questioned as a plausible site for the OoL on the basis (in part) that the generally high temperatures of most hot springs could render any organic components to transform to prebiotically useless “tar” and that the chemical reactivity of any single pool is limited (e.g., Benner et al., 2012; although it should be noted that the temperatures and pressures of hot spring pools are too low for tar production).
Critical in terms of the findings presented here is that hot springs do not occur only as isolated, hot pools but that they exist within diverse fields of many tens to thousands of closely spaced, and often geochemically distinct, pools that span a wide range of temperature and pH conditions, experience wet–dry cycling across a range of timescales, and contain distinct concentrations of prebiotically important elements within individual pools (e.g., B, Mn, K, Zn, in addition to CHNOPS: Power et al., 2018, 2023; Steller et al., 2019; Van Kranendonk et al., 2021).
The geochemical complexity of geothermal fields commences in the subsurface, where boiling and phase separation of magmatic fluids and mixing of those phases with circulating groundwaters result in highly variable fluid compositions, pH, and temperatures in pools at the surface (see Figs. 1 and 5 in Havig et al., 2021; see also Fournier, 1989; Fournier et al., 2002; Nordstrom et al., 2009; Stefánsson et al., 2016; Colman et al., 2021; Power et al., 2023).
Furthermore, the geochemical environments both within pools and in zones where pool outflows mix drive complex precipitation and evaporative forcing that can drive mineral precipitation, redox reactions, changes to microbial consortia, and so on, that lead to changes in the concentration of elements (e.g., Shock et al., 2010; Gardner et al., 2011; Stefánsson et al., 2016). Such spatially complex geothermal surface manifestations have also been noted by Jones and Renaut (2012) along the shoreline of Lake Roto-a-Tamaheke, Rotorua, where complexity is largely controlled by fluctuations in lake levels and variations in the cycles of adjacent acid and alkaline springs. Temporal variations in chemistry due to seasonal fluctuations in rainfall, evaporation, and so on have been documented previously by Fournier et al. (2002) and Colman et al. (2021), among others. Importantly, the ability of hot springs to concentrate elements and undergo wet–dry cycling is now known to occur not only in active geothermal springs but also in the fossil record back to some of the earliest records of life on Earth, 3.5 billion years ago (Djokic et al., 2017, 2021; Van Kranendonk et al., 2017, 2021).
Mineral precipitation may play a potentially vital role in OoL scenarios, as it may provide shelter from incoming UV, catalyze reactions of organic molecules, and so on. In current hot spring systems, mineral precipitation is commonly induced by inorganic hydrothermal alteration, and/or evaporative processes, and/or through the activity of microbial communities (e.g., Cady and Farmer, 1996; Markuson and Stefansson, 2011; Campbell et al., 2015; Gong et al., 2020; Caruso et al., 2021). On prebiotic Earth, hydrothermal and evaporative mineral precipitation may have dominated, yet (nonbiological) organo-mineral complexes may also have formed, providing complex pathways for prebiotic synthesis, protection, and preservation (e.g., Fornaro et al., 2018; Kostetsky and Uversky, 2022; Damer and Deamer, 2020).
At the surface, additional geochemical complexity is generated through a variety of processes, including the interaction between the different pools from splashing, geyser eruption, overspill, merging of outflows, evaporation, cooling, and turbulent flow (Fig. 7 and Supplementary Video). In addition, the components of the pools are available for interaction with both the rocky substrate—altering fresh volcanic glasses to clays and other important mineral components (e.g., Ferris, 2005)—and with the atmosphere, which promotes additional rock alteration and new mineral growth (King et al., 2018). Importantly, this interactivity includes not only hot, but warm and even cool pools that have a variety of pH and element concentrations (Figs. 3, 4, 7).
Schematic diagram summarizing the various physico-chemical complexity processes derived from subsurface and surface processes in geothermal areas.
Of additional importance is the capacity for geothermal fields to develop discrete components of the OoL pathway in geochemically distinct pools that are optimal for that specific component. For example, lipid bilayer vesicles (protocells) preferentially form in pools with neutral-alkaline or mildly acidic pH, fresh water, and dehydration/rehydration events (e.g., Deamer and Barchfeld, 1982; Apel et al., 2002; Milshteyn et al., 2018; Steller et al., 2022; Siddique et al., 2026 in this issue), whereas many important prebiotic reactions, including RNA polymerization (Bernhardt and Tate, 2012) and nucleotide activation chemistry (Pearce et al., 2017; Bonfio et al., 2020), are optimized in pools with acidic conditions. Mixing of these individual prebiotic components through any of the physical mechanisms documented here could provide a pathway for organic polymers to become encapsulated within lipid vesicles, providing a key step along the way to life (e.g., Rajamani et al., 2008) (see Supplementary Video). Furthermore, delivery of a redox gradient in sulfur chemical species (e.g., sulfide, thiosulfate, sulfite, and sulfate; Kaasalainen and Stefánsson, 2011) may provide a ready energy source for early energetic chemotrophic metabolisms (e.g., Lane et al., 2010; Shock et al., 2010; Deamer and Georgiou, 2015; Ranjan and Sasselov, 2016; Ross and Deamer, 2016; Havig et al., 2017; Milshteyn et al., 2019; Deamer et al., 2019; Havig and Hamilton, 2019; Damer and Deamer, 2020).
A question arises whether investigations of modern hot spring systems relate to the conditions on early Earth, when life was starting. There are (at least) three important factors to consider here.
First, studies from the 3.5 billion-year-old Dresser Formation of the Pilbara Craton demonstrate that ancient, microbially inhabited hot springs had the capacity to concentrate prebiotically important elements such as CHNOPS and B, Fe, S, and Mn and that the chemistry of the system was comparable to hot springs in modern-day basaltic environments such as Iceland (Van Kranendonk et al., 2019, 2021; Caruso et al., 2021, 2023; Djokic et al., 2024).
The second factor is the permanency of hot spring fields on early Earth. On modern Earth, the largest hot spring fields occur either over magmas generated in tectonically active subduction zones and rifts or over relatively tectonically inactive mantle hot spots. In the former, active tectonics causes lateral migration of volcanism, faulting, and associated large-scale changes on timescales of ∼1–10 million years (e.g., Adams et al., 1994), although individual hot spring fields may come and go within the timescale of human history (e.g., de Ronde et al., 2016). Volcanic eruptions associated with the Yellowstone mantle hotspot occur every ∼700,000 years, resetting all hydrothermal activity (Christiansen, 2001). Such geologically relatively rapid changes for modern hot spring fields reflect a tectonically active modern Earth, dominated by plate tectonics. On early Earth, however, many studies suggest that plate tectonics did not operate but that heat loss occurred via stagnant-lid convection, with intermittent recycling events that were effected via vertical processes on timescales that have not been absolutely constrained but likely occurred at 10–100 million year-long cycles (e.g., Smithies et al., 2005; Moore and Webb, 2013; O’Neill and Debaille, 2014; Van Kranendonk et al., 2015; O’Neill and Zhang, 2019). Under such conditions, hot spring fields on newly emergent continents may have been longer-lived than modern counterparts and commenced no earlier than c. 4.3–4.2 Ga after the oceans had rained out from the atmosphere (Cavosie et al., 2019), and perhaps significantly later, as it would have taken some time for nascent tectonics to form differentiated continents that rose up out of the oceans.
The third factor to consider is the state of the atmosphere and whether springs would have had the same chemistry on early Earth. This is largely because of the effect of free oxygen, which oxidizes hydrogen sulfide to form sulfuric acid, creating a common type of spring on modern Earth. On early Earth, however, such oxidation is unlikely to have occurred, so sulfidic pools may have been lacking. However, studies from the Pilbara show that sulfidic conditions did exist, likely caused by disproportionation of hydrogen sulfide in epithermal systems and the formation of abundant atmospheric sulfate through photolytic processes (e.g., Farquhar et al., 2000; Van Kranendonk, 2006; Caruso et al., 2021).
Perhaps there is another way of thinking about the development of hot spring fields on early Earth that allows for an even earlier beginning for an OoL scenario in terrestrial hot springs. A potential interval of interest to consider may be the period just before the oceans had rained out of the early steam atmosphere, when the entire planetary surface would represent a reactive interface between the rocky (dominantly basaltic) surface and collecting pools of water. In this scenario, heat from early Earth magmatism would have provided the driving force for hydrothermal circulation and the formation of hot spring fields, with the potential for water–rock interaction, formation of clays, wet–dry cycling, element concentration, lipid membrane formation, and geochemical complexity through all of the processes documented here for modern springs. As the precursor components for life developed under the freshwater conditions of hot spring pools, they would have had to adapt to the saltier and permanently wet conditions of the oceans as they rained out across the globe (e.g., Van Kranendonk et al., 2017).
5. Conclusions
Collectively, terrestrial hydrothermal systems provide a vast suite of physical and geochemical conditions and drivers of processes and mechanisms that maximize complexity (Fig. 7), making them ideal incubators where prebiotic chemical reactions can occur over geologically extremely short periods of time. Critical is their ability to provide kinetic traps that allow simple compounds created in early reactions to develop continuously into more complex products via return cycles, a process lacking in the flow reactors of deep-sea hydrothermal vents (e.g., Bartel and Szostak, 1993; Damer and Deamer, 2015; Horning and Joyce, 2016; Ross and Deamer, 2016). Chemical units undergoing a selection and evolution on and through such complex surface geochemical landscapes would thus be subject to functions on an actual fitness landscape (see also Van Kranendonk et al., 2017; Damer and Deamer, 2020). The combination of subsurface, surface, and atmospheric interactions in terrestrial hot spring fields leads to the most highly reactive and complex geochemical environments on Earth, suitable for developing the conditions for the OoL.
Footnotes
Acknowledgments
The authors thank Michelle Phillips and the Ngati Tahu-Ngati Whaoa Runanga Trust for permission to access and study pools near Alum Cliffs in the geothermal system at the Wai-O-Tapu Thermal Wonderland tourist area. Chanenath (Kitty) Sriaporn and Kim Handley advised on the microbiological context of this study, and Luke Stellar and Brian Drake assisted in the field campaign. Dr. Chie Sakaguchi assisted with analyses undertaken at the Pheasant Memorial Laboratory, Okayama University. The authors are grateful for geochemical analyses conducted by Scott Alexander in the Gibson Hydrogeochemistry Laboratory at the University of Minnesota. Reviews by Dr. Bruce Damer and an anonymous reviewer are acknowledged for significantly contributing clarity and breadth to the article.
Authors’ Contributions
M.J.V.K., K.A.C., and M.R.R. devised the study. M.J.V.K., L.K.P., J.H., M.R.R., K.A.C., and T.H. collected samples. L.K.P. undertook the analyses as part of her MSc thesis at University of Auckland, under the guidance and supervision of M.R.R. and E.N. All authors contributed to writing of the manuscript.
Author Disclosure Statement
No competing financial interests exist.
Funding Information
This study was supported through
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Associate Editor: Radu Popa
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References
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