Spatial and Temporal Variations of Predicting Fuel Load in Temperate Forests of Northeastern Mexico

Abstract

The prediction of fuel load areas and species associated with these events reduces the response time to fight forest fires. The objective of this study was to estimate the annual fuel load from 2009–2013, predict the annual fuel load in the rest of the ecosystem, identify species that contribute most to this load and compare the percentage of area by risk category in the temperate forests of Tamaulipas. Fuel load was estimated with inventory data using three models. Fuel load was predicted with elevation, total annual precipitation, mean annual temperature, and enhanced vegetation index from satellite scenes using partial least squares regression. The highest concentration of fuel load was associated with the oak, oak-pine, pine forest and mountain mesophyll forest ecosystems. The contribution of genera to fuel load was different. Quercus contributed the most variation among clusters, and the contribution among Quercus species was similar. The results highlight the importance of focusing fuel management programs on this type of ecosystem, emphasizing actions in particular Quercus, and the results can also serve as a basis for future research, such as carbon sequestration and forest management programs.

Keywords

• forest fire
• clusters
• vegetation index
• partial least squares
• PERMANOVA