Modelling aboveground biomass and fuel load components at stand level in shrub communities in NW Spain.

• Novel stand-level biomass models developed for 9 shrubland types, by groups and all together. • Nonlinear iterative seemingly unrelated regression used to fit systems of integrated additive equations. • Models were also developed for standing fuel loads by size and condition, and litter. • Predictor variables were stand height alone or with stand cover and litter depth. • Generally, models performed reasonably well even those based on height alone. Shrub-dominated ecosystems cover large areas globally and play essential roles in ecological processes. Aboveground biomass expressed on an area basis (AGB) is central to many of the ecological processes and services provided by shrublands and is important as the main fuel source for wildfires. Hence, its accurate estimation in shrublands is crucial for ecologists and land managers. This is especially relevant in fire-prone regions such as NW Spain, where shrublands are an important part of the landscape, providing multiple services, but are severely impacted by wildfires. Although biomass models are available for numerous shrub species at the individual plant level, operational models based directly on easily measured shrub stand attributes are scarce. In this study, equations for estimating AGB and loads of different fuel components by size and condition (live and dead) from stand biometric variables were developed for the nine most prevalent shrub communities in NW Spain. Non-linear iterative seemingly unrelated regression was used to fit compatible systems of equations for estimating fuel loads, with shrub stand height and cover and litter depth as predictors for individual shrub communities and all data combined. In general, the goodness-of-fit statistics indicated that the estimates were reasonably accurate for all communities (grouped and ungrouped). The best results were obtained for AGB and total fuel load, including litter, whereas the poorest results were obtained for standing live and dead fine fuel load. Model performance was reduced when height was the only independent variable, although the reduction was small for most fuel categories, except litter load for which the variability was adequately explained by the litter depth. These results illustrate the feasibility of the stand level approach for constructing operational models of shrub fuel load that are accurate for most of fuel components, while also highlighting the ongoing challenges in live and dead fine fuel modelling. The equations developed represent an appreciable advance in shrubland biomass assessment in the region and areas with similar characteristics and may be instrumental in generating fuel maps, fire management improvement and better C storage assessment by vegetation, among other many uses. [ABSTRACT FROM AUTHOR]