Interactions between thresholds and spatial discretizations of snow: insights from estimates of wolverine denning habitat in the Colorado Rocky Mountains
Thresholds can be used to interpret environmental data in a way
that is easily communicated and useful for decision-making purposes.
However, thresholds are often developed for specific data products and time
periods, changing findings when the same threshold is applied to datasets or
periods with different characteristics. Here, we test the impact of
different spatial discretizations of snow on annual estimates of wolverine
denning opportunities in the Colorado Rocky Mountains, defined using a snow
water equivalent (SWE) threshold (0.20 m) and threshold date (15 May) from
previous habitat assessments. Annual potential wolverine denning area (PWDA)
was thresholded from a 36-year (1985–2020) snow reanalysis model with
three different spatial discretizations: (1) 480 m grid cells (D480), (2) 90 m
grid cells (D90), and (3) 480 m grid cells with implicit representations of
subgrid snow spatial heterogeneity (S480). Relative to the D480 and S480
discretizations, D90 resolved shallower snow deposits on slopes between 3050
and 3350 m elevation, decreasing PWDA by 10 %, on average. In years with
warmer and/or drier winters, S480 discretizations with subgrid
representations of snow heterogeneity increased PWDA, even within grid cells
where mean 15 May SWE was less than the SWE threshold. These simulations
increased PWDA by upwards of 30 % in low-snow years, as compared to the
D480 and D90 simulations without subgrid snow heterogeneity. Despite PWDA
sensitivity to different snow spatial discretizations, PWDA was controlled
more by annual variations in winter precipitation and temperature. However,
small changes to the SWE threshold (±0.07 m) and threshold date
(±2 weeks) also affected PWDA by as much as 82 %. Across these
threshold ranges, PWDA was approximately 18 % more sensitive to the SWE
threshold than the threshold date. However, the sensitivity to the threshold
date was larger in years with late spring snowfall, when PWDA depended on
whether modeled SWE was thresholded before, during, or after spring snow
accumulation. Our results demonstrate that snow thresholds are useful but
may not always provide a complete picture of the annual variability in
snow-adapted wildlife denning opportunities. Studies thresholding
spatiotemporal datasets could be improved by including (1) information about
the fidelity of thresholds across multiple spatial discretizations and (2) uncertainties related to ranges of realistic thresholds.</p