Abstract. We characterized historical fire regimes in Pinus palustris (longleaf pine) forests of southern Mississippi with regard to global and regional coupled climate systems (e.g., El Niño-Southern Oscillation) and past human activity. The composite fire chronology spanned 1756-2013 with 132 individual scars representing 89 separate fire events. The mean fire interval was 2.9 yr, and mean intervals were significantly different between identified time periods (e.g., settlement period vs. management period). Evidence of biannual fire activity (up to three fires occurring within a 12-to 15-month period) was found coeval with a peak in livestock grazing and logging from the 1850s through the 1880s. Connections were also found between historical fire and Pacific climate variability (e.g., El Niño-Southern Oscillation and Pacific Decadal Oscillation; P < 0.05), yet the fire-climate linkage was likely at least partially masked by substantial human land use activities over the past several centuries. Coupled climate and human land use activity controlled the historical fire regime over the past ca. 240 yr. Although the many fire adaptions of P. palustris yield limitations in tree-ring-based fire history studies (e.g., thick bark), we highlight the efficacy of considering the height at which fire scars are analyzed along the bole as a way to glean a more accurate depiction of historical fire occurrence, especially in ecosystems characterized by a frequent, lowseverity fire regime. This study suggests growing-season fire prescribed at a 2-to 3-yr interval would be the first step toward simulating historical landscape conditions and fire activity, should that be the goal by land managers.
Efficient allocation of resources is essential in any activity, but experimenting to determine appropriate levels risks a reduction in services that could be dangerous in a healthcare operation. Computer simulations offer a risk-free environment for testing alternate resource levels and balancing costs and services. This article describes the use of a simulation to determine appropriate staffing levels for an emergency medical service.
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