Relationships between fire severity and post-fire landscape pattern following a large mixed-severity fire in the Valle Vidal, New Mexico, USA

The predominant fire regime associated with ponderosa pine (Pinus ponderosa) forests in the southwestern US has shifted from the historic norm of frequent, low-severity fires to less frequent mixed-severity and crown fires. This change in the severity of fire has altered ponderosa pine forests from the open stands typical of pre-settlement times to even-aged, high-density stands at increased risk of crown fire. As a result, restoration plans and post-fire management practices must consider the spatial and temporal variability of fire severity in both mixed-severity and crown fire events because fire-severity patterns strongly influence post-fire ecological conditions. This study examines the landscape pattern of fire severity in the Ponil Complex Fire and applies a moving-window approach to post-fire landscape pattern measurement. The moving-window approach allows examination of the quantitative and spatial variability of landscape pattern, producing a more nuanced description of forest pattern when compared to whole-landscape or patch-based metrics. The fire resulted in a complex mosaic of fire patches and forest-structure changes. In high-severity fire patches, mean and median values of many post-fire landscape metrics were markedly different from those in low and moderate-severity patches. Landscape pattern in high-severity patches also had the greatest variability of metric values, suggesting that high-severity fire patches require a spatially mediated management response to fire. Categorical fire-severity maps and traditional landscape-pattern assessment would not be able to identify these spatially variable post-fire conditions.

Research highlights
► We map landscape metrics in New Mexico, USA, using a moving-window approach.
► Moving-window generated metrics reveal spatial heterogeneity in landscape pattern.
► Moving-window maps produce spatial and quantitative distributions of metric values.
► Different levels of fire-severity fire result in distinctive landscape patterns.
► High-severity fire led to the greatest variability of post-fire landscape pattern.