Abstract
Analysis of complex spatio-temporal fire data is an important tool to assist the management and study of fire regimes. For fire ecologists, a useful visual aid to identify contrasting fire regimes is to map temporal sequences of data such as fire return intervals, seasons, and types (planned versus unplanned fire) across the landscape. However, most of the programs that map this information are costly and complex, requiring specialist training. We present a simple yet novel method for creating sequences of temporal data for mapping fire regimes using basic geographic information system (GIS) techniques and logical test functions in Microsoft® Excel 2003 (Microsoft, Bellevue, Washington, USA). Using fire history data (1972 to 2005) for southwestern Australia, we assigned integer classifications to fire return intervals (short, moderate, and long) and fire types and seasons (wildfires and prescribed burns in different seasons) and joined the integer classifications together to form a sequence of numbers representing the order of either fire return intervals or fire seasons in reverse time sequence. This sequence can be mapped in a GIS environment so that spatial dimensions formed by overlapping polygons are readily observed, and the temporal sequence of fire data within each polygon can be interpreted across the landscape. We applied the technique to examine experimental design options for investigating the effects of contrasting fire regimes on biota at the landscape scale. This investigation identified several important factors: 1) patterns were evident in fire types and seasons, 2) patterns were evident for fire return interval sequences, and 3) combining fire types and seasons with fire return intervals significantly constrained options for the study design. A visual analysis of this type highlights fire regime patterns in the landscape and permits a feasibility study for the development of study design options and the spatial arrangement of potential study sites.
Highlights
Questions of patterning in space and time are fundamental to ecology and the management of natural resources (Levin 1992, Cadenasso et al 2006) and find particular application in fire management (Fulé et al 1997, Brockett et al 2001, Bradstock et al 2005, Burrows 2008)
Creating fire season sequences followed a similar process as used for deriving fire return interval sequences, though we supplemented the information by producing a combined classification for fire type and fire season (Figure 2)
The results suggest that it will be difficult to develop a study with suitable replicates based on past fire season sequences, but a study investigating the contrasting fire return interval sequences would provide an adequate number of replicate sites (Table 2)
Summary
Questions of patterning in space and time are fundamental to ecology and the management of natural resources (Levin 1992, Cadenasso et al 2006) and find particular application in fire management (Fulé et al 1997, Brockett et al 2001, Bradstock et al 2005, Burrows 2008). Advances in geographic information systems (GIS) have formalised the accurate capture of spatial data such as perimeter and area of fires, temporal data such as year and season-of-burn, and attribute data such as fire type (wildfire or prescribed burn) and measures of intensity and severity. Such data are important for understanding interactions between fire regimes and a range of values including biodiversity, water, and carbon fluxes (Burrows and Abbott 2003, Wittkuhn et al 2009). We demonstrate the effectiveness of this technique by presenting results from a case study that used these temporal sequences to investigate contrasting fire regimes as a basis for an ecological study at a landscape scale (Wittkuhn et al 2008, Wittkuhn et al 2009)
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