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TECHNICAL REPORTS

Estimation of Postfire Nutrient Loss in the Florida Everglades

^a Tropical Research & Education Center, Soil and Water Science Dep., IFAS, Univ. of Florida, 18905 SW 280th St., Homestead, FL 33031
^b South Florida Water Management District, 3301 Gun Club Rd., West Palm Beach, FL 33406

^* Corresponding author (yunli{at}ufl.edu).

Received for publication August 28, 2008. Postfire nutrient release into ecosystem via plant ash is critical to the understanding of fire impacts on the environment. Factors determining a postfire nutrient budget are prefire nutrient content in the combustible biomass, burn temperature, and the amount of combustible biomass. Our objective was to quantitatively describe the relationships between nutrient losses (or concentrations in ash) and burning temperature in laboratory controlled combustion and to further predict nutrient losses in field fire by applying predictive models established based on laboratory data. The percentage losses of total nitrogen (TN), total carbon (TC), and material mass showed a significant linear correlation with a slope close to 1, indicating that TN or TC loss occurred predominantly through volatilization during combustion. Data obtained in laboratory experiments suggest that the losses of TN, TC, as well as the ratio of ash total phosphorus (TP) concentration to leaf TP concentration have strong relationships with burning temperature and these relationships can be quantitatively described by nonlinear equations. The potential use of these nonlinear models relating nutrient loss (or concentration) to temperature in predicting nutrient concentrations in field ash appear to be promising. During a prescribed fire in the northern Everglades, 73.1% of TP was estimated to be retained in ash while 26.9% was lost to the atmosphere, agreeing well with the distribution of TP during previously reported wild fires. The use of predictive models would greatly reduce the cost associated with measuring field ash nutrient concentrations.

Abbreviations: DA, discriminant analysis • DDI water, double deionized water • H zone, highly-impacted zone • MLR, multiple linear regression • M zone, moderately-impacted zone • R zone, reference zone • WCA 2A, Water Conservation Area 2A