Microorganisms have long been thought to impact CaCO 3 precipitation, but determining the extent of their infl uence on sediment formation has been hampered by our inability to obtain direct experimental evidence about mineral formation processes in natural environments. We address this problem by conducting kinetic experiments within a modern terrestrial carbonate spring to determine aragonite precipitation rates and to quantify the relative infl uences of aragonite saturation state (Ω a ), microbial biomass concentration and microbial viability on CaCO 3 mineralization in advection-dominated transport regimes. At an Ω a value consistent with modern seawater (3.63 ± 0.09), our controlled in situ kinetic experiments show that: (1) the natural steady-state aragonite precipitation rate is more than twice that determined when microbial biomass on the aragonite mineral surface is depleted by 0.2 µm fi ltration; and (2) inhibiting microbial viability with ultraviolet (UV) irradiation has no signifi cant effect on the mean precipitation rate. Furthermore, our modeling of the CaCO 3 precipitation process, which uses the empirical crystal growth rate expression and additional in situ kinetic measurements, reveals that reducing biomass concentrations by 45% can decrease the empirical rate constant by more than an order of magnitude. These fi ndings strongly suggest that microorganisms catalyze CaCO 3 precipitation in advection-dominated systems and imply that changes in carbonate mineralization rates may have resulted from changes in local microbial biomass concentration throughout geologic history.

The seemingly simple problem of determining the drag on a body moving through a very viscous fluid has, for over 150 years, been a source of theoretical confusion, mathematical paradoxes, and experimental artifacts, primarily arising from the complex boundary layer structure of the flow near the body and at infinity.We review the extensive experimental and theoretical literature on this problem, with special emphasis on the logical relationship between different approaches. The survey begins with the developments of matched asymptotic expansions, and concludes with a discussion of perturbative renormalization group techniques, adapted from quantum field theory to differential equations. The renormalization group calculations lead to a new prediction for the drag coefficient, one which can both reproduce and surpass the results of matched asymptotics.

An extensive data set of the physical and chemical attributes of two modern hot springs in the Mammoth Hot Springs complex of Yellowstone National Park, Wyoming, U.S.A., yields a strong correlation between travertine depositional facies and the temperature, pH, and flux of the hot-spring water from which the travertine precipitated. Because advection dominates in these hot-spring drainage systems, we quantify variability between and within springs in order to construct a hydrologic model that defines the primary flow path in the context of key macroscopic travertine accumulation patterns. This model, based on 343 in situ triplicate measurements, provides the basis for the use of travertine facies models to quantitatively reconstruct hot-spring aqueous temperature, pH, and flux solely from precipitated travertine. As an example reconstruction, we deduce that previously described Pleistocene apron and channel facies travertine quarry deposits from central Italy precipitated from hot-spring waters with a pH of 6.86 6 0.19 and a temperature of 65.4 6 3.6uC.

We formulate and model the dynamics of spatial patterns arising during the precipitation of calcium carbonate from a supersaturated shallow water flow. The model describes the formation of travertine deposits at geothermal hot springs and rimstone dams of calcite in caves. We find explicit solutions for travertine domes at low flow rates, identify the linear instabilities which generate dam and pond formation on sloped substrates, and present simulations of statistical landscape evolution.

Nature abounds with beautiful and striking landscapes, but a comprehensive understanding of their forms requires examples where detailed comparisons can be made between theory and experiment. Geothermal hot springs 1 produce some of the most rapidly changing terrestrial landscapes, with reported travertine (calcium carbonate) growth rates as high as 5 mm per day 2-4 . Unlike most landscapes, the patterns of which are the result of erosion processes on timescales of millions of years, the hot-spring depositional landscapes exhibit a spectacular cascade of nested ponds and terraces 5 , for which the origins and quantitative characterization have remained elusive. Here, we take advantage of this millionfold difference in geological timescale to present a novel combination of data from time-lapse photography, computer simulation and mathematical modelling that explains the emergence of the large-scale pond and terrace patterns, predicts and verifies the dynamics of their growth and shows that these patterns are scale invariant.The dynamics of turbulent fluid flow coupled to the precipitation-driven growth of the travertine substrate was modelled on a discrete lattice of cells. Our cell dynamical system (CDS) is a set of rules, described in detail in the Methods section, that updates the lattice variables representing the heights of the landscape and fluid above each cell. The rules mimic fluid depositional dynamics and the influence of landscape features on the flow pattern 6,7 , enabling efficient computations of complex landscapes. Such a formalism complements analytic descriptions of carbonate precipitation patterns, such as our work on travertine domes 7 and recent studies of needle-like speleothem growth 8,9 . We were able to verify that our CDS model is quantitatively equivalent to the more conventional approach using differential equations, by using it to analyse the growth of single travertine domes 7 . The CDS enables long-time (28,000 steps), large-scale 600 × 500 cells) simulations of landscapes with arbitrary, complex structure. Statistical properties were computed by averaging over 130 independent simulations. The model was not 'tuned': as long as the parameters are not varied so much that the model ceases to make physical sense, it produces the same morphological and statistical results, showing that our findings are generic for this class of precipitation patterns. Figure 1 shows frames captured from a typical time-dependent simulation, initiated on a sloping plane with small initial roughness. Initial depositional instabilities grow to form dams, pond water pools behind the dams and complicated interactions arise as terraces grow and interact. The frames show a process of pond inundation, or 'drowning' . In this mechanism, which seems to be the dominant one through which larger ponds form, the lip of a downstream pond grows more rapidly than that of its upstream neighbour. Eventually the downstream lip becomes taller, inundating the upstream pond, and leaving a single large pond. Although we also obs...