Wildfires are often governed by rapid changes in seasonal rainfall. Therefore, measuring seasonal rainfall on a temporally finescale should facilitate the prediction of wildfire regimes. To explore this hypothesis, daily rainfall data over a 58-yr period in south-central Florida were transformed into cumulative rainfall anomalies (CRAs). This transformation allowed precise estimation of onset dates and durations of the dry and wet seasons, as well as a number of other variables characterizing seasonal rainfall. These variables were compared with parameters that describe ENSO and a wildfire regime in the region (at the Avon Park Air Force Range). Onset dates and durations were found to be highly variable among years, with standard deviations ranging from 27 to 41 days. Rainfall during the two seasons was distinctive, with the dry season having half as much as the wet season despite being nearly 2 times as long. The precise quantification of seasonal rainfall led to strong statistical models describing linkages between climate and wildfires: a multiple-regression technique relating the area burned with the seasonal rainfall characteristics had an R 2 adj of 0.61, and a similar analysis examining the number of wildfires had an R 2 adj of 0.56. Moreover, the CRA approach was effective in outlining how seasonal rainfall was associated with ENSO, particularly during the strongest and most unusual events (e.g., El Niñ o of 1997/98). Overall, the results presented here show that using CRAs helped to define the linkages among seasonality, ENSO, and wildfires in south-central Florida, and they suggest that this approach can be used in other fire-prone ecosystems.

Fire seasonality, an important characteristic of fire regimes, commonly is delineated using seasons based on single weather variables (rainfall or temperature). We used nonparametric cluster analyses of a 17-year (1993–2009) data set of weather variables that influence likelihoods and spread of fires (relative humidity, air temperature, solar radiation, wind speed, soil moisture) to explore seasonality of fire in pine savanna-grassland landscapes at the Avon Park Air Force Range in southern Florida. A four-variable, three-season model explained more variation within fire weather variables than models with more seasons. The three-season model also delineated intra-annual timing of fire more accurately than a conventional rainfall-based two-season model. Two seasons coincided roughly with dry and wet seasons based on rainfall. The third season, which we labeled the fire season, occurred between dry and wet seasons and was characterized by fire-promoting conditions present annually: drought, intense solar radiation, low humidity, and warm air temperatures. Fine fuels consisting of variable combinations of pyrogenic pine needles, abundant C4 grasses, and flammable shrubs, coupled with low soil moisture, and lightning ignitions early in the fire season facilitate natural landscape-scale wildfires that burn uplands and across wetlands. We related our three season model to fires with different ignition sources (lightning, military missions, and prescribed fires) over a 13-year period with fire records (1997–2009). Largest wildfires originate from lightning and military ignitions that occur within the early fire season substantially prior to the peak of lightning strikes in the wet season. Prescribed ignitions, in contrast, largely occur outside the fire season. Our delineation of a pronounced fire season provides insight into the extent to which different human-derived fire regimes mimic lightning fire regimes. Delineation of a fire season associated with timing of natural lightning ignitions should be useful as a basis for ecological fire management of humid savanna-grassland landscapes worldwide.

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Feral swine are estimated to annually cost hundreds of millions of dollars in economic loss to property and agriculture in the USA, while their ecological consequences remain largely unmeasured. Using submeter-accurate Global Positioning System technology over a multiyear project, we are quantifying in a novel way the spatial and temporal attributes of swine rooting damage within 587 ha of ecologically sensitive wetland plant communities at Avon Park Air Force Range in south-central Florida. We delineated damage polygons from 0.0023 to 4,335 m(2) and were able to document recurrent damage through time at most sites during each assessment. For each polygon, we also estimated the age of damage and assigned to it a severity index, qualities of the rooting in which we detected changes in proportions over time. Spatially explicit damage assessments at fine scales conducted over several years can assist land managers in determining effects of rooting on rare plant populations, and will allow investigators to hypothesize what factors are driving patterns of this disturbance across ecologically sensitive plant communities.

Understanding of historical fire seasonality should facilitate development of concepts regarding fire as an ecological and evolutionary process. In