The calculation of a maximum depositional age(MDA)from a detrital zircon sample can provide insight into a variety of geological problems.However,the impact of sample size and calculation method on the accuracy of a r...The calculation of a maximum depositional age(MDA)from a detrital zircon sample can provide insight into a variety of geological problems.However,the impact of sample size and calculation method on the accuracy of a resulting MDA has not been evaluated.We use large populations of synthetic zircon dates(N≈25,000)to analyze the impact of varying sample size(n),measurement uncertainty,and the abundance of neardepositional-age zircons on the accuracy and uncertainty of 9 commonly used MDA calculation methods.Furthermore,a new method,the youngest statistical population is tested.For each method,500 samples of n synthetic dates were drawn from the parent population and MDAs were calculated.The mean and standard deviation of each method ove r the 500 trials at each n-value(50-1000,in increments of 50)were compa red to the known depositional age of the synthetic population and used to compare the methods quantitatively in two simulation scenarios.The first simulation scenario varied the proportion of near-depositional-age grains in the synthetic population.The second scenario varied the uncertainty of the dates used to calculate the MDAs.Increasing sample size initially decreased the mean residual error and standard deviation calculated by each method.At higher n-values(>~300 grains),calculated MDAs changed more slowly and the mean resid ual error increased or decreased depending on the method used.Increasing the p roportion of near-depositional-age grains and lowering measurement uncertainty decreased the number of measurements required for the calculated MDAs to stabilize and decreased the standard deviation in calculated MDAs of the 500 samples.Results of the two simulation scenarios show that the most successful way to increase the accuracy of a calculated M DA is by acquiring a large number of low-uncertainty measurements(300300)approach is used if the calculation of accurate MDAs are key to research goals.Other acquisition method s,such as high-to moderate-precision measurement methods(e.g.,1%-5%,2σ)acquiring lo展开更多
基金Funding for this research was provided by a NSERC Discovery Grant(No.RGPIN/341715-2013)to S.Hubbard and a Queen Eliz-abethⅡscholarship from the University of Calgary to D.Coutts
文摘The calculation of a maximum depositional age(MDA)from a detrital zircon sample can provide insight into a variety of geological problems.However,the impact of sample size and calculation method on the accuracy of a resulting MDA has not been evaluated.We use large populations of synthetic zircon dates(N≈25,000)to analyze the impact of varying sample size(n),measurement uncertainty,and the abundance of neardepositional-age zircons on the accuracy and uncertainty of 9 commonly used MDA calculation methods.Furthermore,a new method,the youngest statistical population is tested.For each method,500 samples of n synthetic dates were drawn from the parent population and MDAs were calculated.The mean and standard deviation of each method ove r the 500 trials at each n-value(50-1000,in increments of 50)were compa red to the known depositional age of the synthetic population and used to compare the methods quantitatively in two simulation scenarios.The first simulation scenario varied the proportion of near-depositional-age grains in the synthetic population.The second scenario varied the uncertainty of the dates used to calculate the MDAs.Increasing sample size initially decreased the mean residual error and standard deviation calculated by each method.At higher n-values(>~300 grains),calculated MDAs changed more slowly and the mean resid ual error increased or decreased depending on the method used.Increasing the p roportion of near-depositional-age grains and lowering measurement uncertainty decreased the number of measurements required for the calculated MDAs to stabilize and decreased the standard deviation in calculated MDAs of the 500 samples.Results of the two simulation scenarios show that the most successful way to increase the accuracy of a calculated M DA is by acquiring a large number of low-uncertainty measurements(300300)approach is used if the calculation of accurate MDAs are key to research goals.Other acquisition method s,such as high-to moderate-precision measurement methods(e.g.,1%-5%,2σ)acquiring lo
