Abstract
Boreal forest fire history is typically reconstructed using tree-ring based time since last fire (TSLF) frequency distributions from across the landscape. We employed stochastic landscape fire simulations to assess how large a study area and how many TSLF sample-points are required to estimate the fire cycle (FC) within a given accuracy, and if those requirements change with length of the simulated fire rotation (FRS). FRS is calculated from simulated fire-year maps used to create the TSLF map, and is the “true” measure of fire history that FC estimates should equal. Fire-year maps were created by (i) using a spatially homogenous landscape, (ii) imposing large variations in annual area burned, and (iii) having no age-related change in the hazard of burning. We found that study areas should be ≥3× the size of largest total annual area burned, with smaller-scale areas having a bias that cannot be fixed by employing more samples. For a study area scale of 3×, a FC estimate with an error <10% was obtained with 187 TSLF samples at 0.81 samples per 100 km2. FC estimates were not biased in study area scales that were ≥3×, but smaller-scale areas with a short FRS had an overestimated FC and smaller-scale areas with a long FRS had an underestimated FC. Site specific variations in environmental- and age-related variations in the hazard of burning may require more sample-points; site specific simulations should thus be conducted to determine sample numbers before conducting a TSLF field study.
Highlights
There is concern that fire frequency is increasing globally [1] and that the resulting carbon emissions will enhance climate change [2]
Our key findings suggest that: times since last fire (TSLF) fire histories should employ study areas ≥3× the largest total annual area burned [7]; the minimum number of TSLF sample numbers and sample density that should be employed differs with study area scale; and an influence of FRS length on the fire cycle (FC) estimate only occurs if the study area scale is
The method of constructing and sampling TSLF maps that we developed allows guidelines to be tested in regard to how large of a study area and how many TSLF sample-points should be employed to estimate the FC using the TSLF method
Summary
There is concern that fire frequency is increasing globally [1] and that the resulting carbon emissions will enhance climate change [2]. In areas of high fire frequency, the use of decades-long historical and remotely sensed data can indicate temporal changes in wildfire frequency [5], while areas of lower fire frequency require longer-term biophysical records such as provided by fossil charcoal and tree-rings [6]. Fire frequency is equal to the inverse of each of the fire cycle (FC), fire rotation (FR), and mean fire interval (MFI), if the hazard of burning is constant over historical time and forest age [4,7]. FC and FR are both equal to the number of years required to burn an area equal in size to the study area, but they differ in the data employed for their estimation. FR is estimated from a series of annual fire-year maps created using either historical records or tree-ring reconstructions [8]. FC is estimated from a map that displays the times since last fire (TSLF) across the landscape; a frequency distribution of TSLF ages typically displays a negative exponential form and its FC can be obtained using a maximum likelihood
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