Figures
Figure 1. Sagehen Creek Basin, located in the northeastern Sierra
Nevada. The area of interest (black outline) shows the study domain
given available lidar and modeled snow density. a. The elevation profile
spans ~1800 to 2800 meters, increasing to the southwest.
b. Northness shows steep slopes to the southwest. c. The thinning
project summary shows proposed thinning boundaries overlaying a canopy
height model (CHM) in meters, which align well with the fraction of
vegetation (fVEG) difference between the pre- and post-thinning flights
(d).
Figure
2. SNOTEL SWE values compared with flight dates (vertical dashed lines)
used in this study for water year (a) 2008, (b) 2016, and (c) 2022.
Orange = Independence Lake SNOTEL Site (541), Black = Independence Camp
SNOTEL Site (539), Blue = Independence Creek SNOTEL Site (540).
Figure
3. (a) Example image displaying the lidar snow-on classification with an
example subsection of a lidar grid cell (tan = ground, green =
vegetation, blue = snow surface). The bottom color bar aligns with the
correct canopy cover class as classified from the height strata (dark
blue = open, light blue = short canopy, dark green = tall canopy, light
green = understory). The black zones indicate that the area above would
be removed from the analysis, either because there are points between
1.5-3 m or because the snow is not >0.3 m above the
vegetation surface (note: not to scale and point cloud colors do not
correspond with classification
colors). b. Vegetation
classification output. The refined classification includes short and
understory classes, allowing us to include shorter vegetation types if
the snow depth is ≥ 0.3 m above the
vegetation. c. Snow-depth
classification example for the 04/17/2016 flight.
Figure
4. Spatial distribution of pre-disturbance forest structure metrics
across the area of interest, colored by northness, where negative values
indicate south-facing slopes. Box plots show quartiles with the
horizontal bar representing the median value. Higher elevations tend
have denser canopy on northern-facing slopes.
Figure
5. Spatial distribution of SWE across the domain. We see greater SWE at
higher elevations and more northern-facing slopes.
Figure
6. Median DSnowAc (shown by horizontal lines within each box plot) is
always below zero, indicating greater accumulation in open areas. The
spatial distribution of DSnowAc across the domain is varied with a more
pronounced difference at lower elevations on more northern-facing slopes
in 2016 and more muted effects in 2008 and 2022.
Figure
7. DSnowAc against fVEG for the a. NCALM flight from 02/10/2008. b. ASO
flight from 03/26/2016 c. NCALM flight from 03/21/2022. Lidar points are
colored by density with darker blue = greater point density. Black
points show the Varhola et al. (2010) data.
Figure
8. Normalized DSnowAb against fVEG for both early (a) and late (b)
season ablation show a weak positive relationship, with the differences
between forested and open sites increasing (becoming more positive) with
increasing vegetation.
Figure
9. Annotated partial plots showing the response area determination.
Higher pre-disturbance fVEG areas are identified as high response areas
because thinning would lead to a pronounced increase (positive response)
in DSnowAc whereas lower pre-disturbance Openness (ln[gap
diameter/mean tree height]) areas are identified as high response
because thinning would lead to a pronounced decrease (negative response)
in DSnowAc.
Figure 10. Predicted response
classes based on the Random Forest results. Shading shows areas that are
predicted to experience a low (light purple), moderate, or high (dark
purple) response to treatment. a. The spatial distribution of these maps
on top of actual treatments, shown both as planned treatment outline
(dotted black line) and the delta fVEG raster. b. Snow accumulation
dynamics across all three flights and predicted response classes.
Figure 11. An expanded response analysis using the 2014 lidar flight.
The LANDFIRE EVT map (a. and c.) shows that the domain is dominated by
Ponderosa Pine Forests, which are also primarily where areas are
impacted by fire. Moderate response zones account for the majority of
the domain, and high response areas are concentrated between
Douglas/Grand/White Fir and Ponderosa Pine Forests (c.). Treatment and
burned areas overlain on an expanded response map show that low response
areas overlap with burned areas (b.) and taking the area of pixels per
each date range, the proportion of low response areas increases as the
treatment dates become more recent (e.g. 2007-2014). Planned treatment
areas (2014-2024) show an increase in high response areas.