Conclusion

We present a new lidar-based method that furthers our understanding of effects of forest disturbance on snow accumulation and ablation and translates that into a decision support tool. Our novel and open-source methods for processing high-resolution, spatially-distributed lidar data identify forested zones which are most likely to experience increased snowpack water storage following canopy removal from forest treatments. Our “open reference site” analyses motivated by the Varhola et al. (2010) meta-analysis, confirms a linear predictive relationship between coarse-scale forest structure metrics (i.e. fVEG) and snow accumulation. However, our method utilizing thousands of “reference sites” provides new insight about thresholds in fine-scale forest structure metrics (i.e. openness) that were not possible with previous observational techniques. Our analysis allows us to isolate the fine-scale forest structure metrics using widely available airborne lidar datasets, thereby creating opportunity to understand climate-driven differences in snow retention across multiple sites. Moreover, cross site analysis that spans climate and snowpack gradients could yield truly novel insights into the underlying processes controlling snow accumulation. Ablation dynamics and pre-post disturbance analyses presented methodological challenges, primarily from temporal limitations in lidar collections across the large elevation gradients. Despite a detectable shift towards less ablation with lower fVEG, an improved method for calculating ablation using multi-temporal lidar across large elevation gradients would be valuable. Lidar data collections in the snow accumulation season have the potential to inform decision support tools , but have more limitations in detecting post-disturbance change, while inter-annual variability limits pre versus post disturbance analyses. Consequently, lidar data collections need to be tailored to local conditions (e.g. low and high elevation collections) and done in close coordination with local management agencies to maximize utility for forest restoration planning.