Spatial and temporal corroboration of a fire‐scar‐based fire history in a frequently burned ponderosa pine forest

Abstract

Fire scars are used widely to reconstruct historical fire regime parameters in forests around the world. Because fire scars provide incomplete records of past fire occurrence at discrete points in space, inferences must be made to reconstruct fire frequency and extent across landscapes using spatial networks of fire-scar samples. Assessing the relative accuracy of fire-scar fire history reconstructions has been hampered due to a lack of empirical comparisons with independent fire history data sources. We carried out such a comparison in a 2780-ha ponderosa pine forest on Mica Mountain in southern Arizona (USA) for the time period 1937-2000. Using documentary records of fire perimeter maps and ignition locations, we compared reconstructions of key spatial and temporal fire regime parameters developed from documentary fire maps and independently collected fire-scar data (n = 60 plots). We found that fire-scar data provided spatially representative and complete inventories of all major fire years (> 100 ha) in the study area but failed to detect most small fires. There was a strong linear relationship between the percentage of samples recording fire scars in a given year (i.e., fire-scar synchrony) and total area burned for that year (y = 0.0003x + 0.0087, r2 = 0.96). There was also strong spatial coherence between cumulative fire frequency maps interpolated from fire-scar data and ground-mapped fire perimeters. Widely reported fire frequency summary statistics varied little between fire history data sets: fire-scar natural fire rotations (NFR) differed by < 3 yr from documentary records (29.6 yr); mean fire return intervals (MFI) for large-fire years (i.e., > or = 25% of study area burned) were identical between data sets (25.5 yr); fire-scar MFIs for all fire years differed by 1.2 yr from documentary records. The known seasonal timing of past fires based on documentary records was furthermore reconstructed accurately by observing intra-annual ring position of fire scars and using knowledge of tree-ring growth phenology in the Southwest. Our results demonstrate clearly that representative landscape-scale fire histories can be reconstructed accurately from spatially distributed fire-scar samples.

Decadal predictability of soil water, vegetation, and wildfire frequency over North America

“…Our study has been motivated by the finding of decadal-scale persistence of drought conditions over North America (Woodhouse and Overpeck 1998;Stahle et al 2007;Dai 2011) and low-frequency characteristics of fire cycles (e.g., Swetnam and Betancourt 1998;Westerling et al 2003;Brown et al 2005;Farris et al 2010), as reconstructed from lake sediments and fire-scar. Based on the perfect model framework, our results provide estimates of the maximum potential predictability of soil hydrological variability.…”

Modern calibration and historical testing of small-area, fire-interval reconstruction methods

“…These overcome the small-fire problem (Kou and Baker 2006a), and also biased, targeted sampling if plots are statistically unbiased samples across a landscape and scars are sampled without bias within plots. Consequently, the most reliable and unbiased way to use CFIs would be in plots #,1.0 ha, as originally intended (Dieterich 1980;Farris et al 2010). However, of 101 past studies reporting CFIs 100% were from areas .1 ha, 95% from .10 ha and 52% from .100 ha (Kou and Baker 2006a).…”

“…However, it is unclear whether there is an advantage to generally using these small-area methods, as landscape-scale methods that reconstruct fire-year maps to estimate fire rotation (e.g. Farris et al 2010) are reliable and spatially explicit (Hessl et al 2007). Managers tasked with restoring fire across large, variable landscapes, such as the South Rim of GCNP (e.g.…”

“…Fulé et al (2003) validated detection of fires in a composite list, rather than estimation of population MFI. Farris et al (2010) found a filtered CFI accurately predicted population MFI, but for filtered plots not filtered trees that are the fire-history tradition (e.g. Swetnam and Baisan 1996).…”

Approximation of Fire-Return Intervals with Point Samples in the Southern Range of the Coast Redwood Forest, California, USA

“…Less than 10 % of the cross-sectional area of the boles of snags and live trees were removed, thus minimizing the potential for mechanical failure (Heyerdahl and McKay 2008). Both young and old specimens were selected in order to maximize the length and completeness of the temporal record (Farris et al 2010). Wood exhibiting minimal decay and multiple externally visible fire scars were initially prioritized for sampling (Speer 2010).…”