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Lake sediment charcoal records are used in paleoecological analyses toreconstruct fire history including the identification of past wildland fires.One challenge of applying sediment charcoal records to infer fire history isthe separation of charcoal associated with local fire occurrence and charcoaloriginating from regional fire activity. Despite a variety of methods toidentify local fires from sediment charcoal records, an integrated statisticalframework for fire reconstruction is lacking. We develop a Bayesian pointprocess model to estimate probability of fire associated with charcoal countsfrom individual-lake sediments and estimate mean fire return intervals. Amultivariate extension of the model combines records from multiple lakes toreduce uncertainty in local fire identification and estimate a regional meanfire return interval. The univariate and multivariate models are applied to 13lakes in the Yukon Flats region of Alaska. Both models resulted in similar meanfire return intervals (100-350 years) with reduced uncertainty under themultivariate model due to improved estimation of regional charcoal deposition.The point process model offers an integrated statistical framework forpaleo-fire reconstruction and extends existing methods to infer regional firehistory from multiple lake records with uncertainty following directly fromposterior distributions.

A Model-Based Approach to Wildland Fire Reconstruction Using Sediment Charcoal Records