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.