Simulated data from Kelly et al. 2011, A signal-to-noise index to quantify the potential for peak detection in sediment-charcoal records, Quaternary Reserach, 75: 11-17.
Simulated charcoal time series used in:
Kelly, R. F., Higuera, P. E., Barrett, C. M. & Hu, F. S. (2011) A signal-to-noise index to quantify the potential for peak detection in sediment-charcoal records. Quaternary Research, 75, 11-17.
Each .csv file contains "summary data" that describes the parameters used in the CharAnalysis program for threshold determination. Row 16 includes column headings for CharAnalysis input, as follows:
age -- [yr BP] age of simulated record
cm -- [cm] depth of simulated record
count -- [#] charcoal count (not discrete)
vol -- [cm3] volume of sample
acc -- [# cm^-2 yr^-1] Charcoal accumulation rate
bkg -- [# cm^-2 yr^-1] Background charcoal
rsd -- [# cm^-2 yr^-1] Residual charcoal
thr -- [# cm^-2 yr^-1] Threshold separating peaks from non-peak values
pkBool -- [binary] Peaks (1) or non-peak values (0)
pkMCP -- [binary] Equals 1 if a "peak" value was screened out by the minimum count test. That is, the sample surpassed the threshold, but the count was low enough to not pass the minimum count test. (These values should almost always be 0)
sni -- [index] Signal-to-noise index
sniSm -- [index] Smoothd SNI
Detials from Kelly et al. (2011):
"Simulated records were generated using the CharSim model (Higuera et al., 2007), which simulates a spatially and temporally explicit fire regime, charcoal production and dispersal processes, primary (airborne) and secondary (slope wash and withinlake redeposition) deposition, sediment mixing, and sediment sampling. The CS1 scenario is based on model parameters representing boreal-forest charcoal records, with high temporal resolution (15-yr contiguous samples) and little vertical mixing in sediments. The CS2 scenario differs from CS1 only in that additional sediment mixing is simulated (vertical mixing depth doubled from 1.0 to 2.0 cm), as might be observed in shallower lakes. In both CS1 and CS2 scenarios, fire sizes mimic those observed in Alaska from 1988 to 2003 (Alaska Fire Service, 2004). By contrast, the CS3 scenario is based on fires of constant size, equal to the mean fire size of the same dataset. This scenario creates a charcoal series with a relatively uniform distribution of CHAR values, and illustrates a record in which peaks from local fires are difficult to detect due to processes independent of charcoal taphonomy."
