Browsing by Subject "SCALE"
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Item Open Access An improved approach to age-modeling in deep time: Implications for the Santa Cruz Formation, Argentina(Bulletin of the Geological Society of America, 2020-01-01) Trayler, RB; Schmitz, MD; Cuitiño, JI; Kohn, MJ; Bargo, MS; Kay, RF; Strömberg, CAE; Vizcaíno, SF© 2019 Geological Society of America. Accurate age-depth models for proxy records are crucial for inferring changes to the environment through space and time, yet traditional methods of constructing these models assume unrealistically small age uncertainties and do not account for many geologic complexities. Here we modify an existing Bayesian age-depth model to foster its application for deep time U-Pb and 40Ar/39Ar geochronology. More flexible input likelihood functions and use of an adaptive proposal algorithm in the Markov Chain Monte Carlo engine better account for the age variability often observed in magmatic crystal populations, whose dispersion can reflect inheritance, crystal residence times and daughter isotope loss. We illustrate this approach by calculating an age-depth model with a contiguous and realistic uncertainty envelope for the Miocene Santa Cruz Formation (early Miocene; Burdigalian), Argentina. The model is calibrated using new, high-precision isotope dilution U-Pb zircon ages for stratigraphically located interbedded tuffs, whose weighted mean ages range from ca. 16.78 ± 0.03 Ma to 17.62 ± 0.03 Ma. We document how the Bayesian age-depth model objectively reallocates probability across the posterior ages of dated horizons, and thus produces better estimates of relative ages among strata and variations in sedimentation rate. We also present a simple method to propagate age-depth model uncertainties onto stratigraphic proxy data using a Monte Carlo technique. This approach allows us to estimate robust uncertainties on isotope composition through time, important for comparisons of terrestrial systems to other proxy records.Item Open Access Complexity by Subtraction(Evolutionary Biology, 2013) McShea, DW; Hordijk, WThe eye and brain: standard thinking is that these devices are both complex and functional. They are complex in the sense of having many different types of parts, and functional in the sense of having capacities that promote survival and reproduction. Standard thinking says that the evolution of complex functionality proceeds by the addition of new parts, and that this build-up of complexity is driven by selection, by the functional advantages of complex design. The standard thinking could be right, even in general. But alternatives have not been much discussed or investigated, and the possibility remains open that other routes may not only exist but may be the norm. Our purpose here is to introduce a new route to functional complexity, a route in which complexity starts high, rising perhaps on account of the spontaneous tendency for parts to differentiate. Then, driven by selection for effective and efficient function, complexity decreases over time. Eventually, the result is a system that is highly functional and retains considerable residual complexity, enough to impress us. We try to raise this alternative route to the level of plausibility as a general mechanism in evolution by describing two cases, one from a computational model and one from the history of life. © 2013 Springer Science+Business Media New York.Item Open Access Hydro-geomorphic perturbations on the soil-atmosphere CO2exchange: How (un)certain are our balances?(Water Resources Research, 2017-02) Dialynas, Yannis G; Bras, Rafael L; deB. Richter, DanielItem Open Access Three Trends in the History of Life: An Evolutionary Syndrome(Evolutionary Biology, 2016-12-01) McShea, DWThe history of life seems to be characterized by three large-scale trends in complexity: (1) the rise in complexity in the sense of hierarchy, in other words, an increase in the number of levels of organization within organisms; (2) the increase in complexity in the sense of differentiation, that is, a rise in the number of different part types at the level just below the whole; and (3) a downward trend, the loss of differentiation at the lowest levels in organisms, a kind of complexity drain within the parts. Here, I describe the three trends, outlining the evidence for each and arguing that they are connected with each other, that together they constitute an evolutionary syndrome, one that has recurred a number times over the history of life. Finally, in the last section, I offer an argument connecting the third trend to the reduction at lower levels of organization in “autonomy”, or from a different perspective, to an increase in what might be called the “machinification” of the lower levels.