Forest composition and structural controls on canopy snow interception in a Colorado watershed
Abstract
Globally and across the Western United States shifting climate regimes have the ability to propagate change throughout ecosystems and affect their associated hydrologic functions. In mountain regions, which serve as “water towers” for much of humanity, the complex interactions between vegetation and water are especially vulnerable to climate change as they are subject to both ecological and hydrological disturbances. Forests exhibit major controls on the hydrology of mountain systems, of which a primary mechanism is the interception of falling snow in forest canopies which can result in up to 50% of intercepted snow being lost back to the atmosphere through sublimation. Despite being an important driver of forest-snow interactions, scientific inquiry on canopy snow interception has been limited to small spatial scales and limited observations due to the difficult nature of measuring snow in forest canopies. We used Terrestrial Laser Scanning (TLS) to quantify interception rates and interrogate how tree species, forest structure, and weather conditions influence canopy snow interception potential in a high elevation Colorado watershed. Our results represent a step forward in expanding the spatial scale of canopy snow observations and elucidating the differences in interception rates across different tree species, forest compositions, and structures. We compared deciduous tree stands comprised of Quaking Aspen against 3 prevalent coniferous tree species at this altitude (Lodgepole Pine, Engelmann Spruce, and Subalpine Fir) and found that on average conifer forests intercepted an order of magnitude greater snow volume. Analysis of a supplementary dataset on snowpack depth revealed that aspen stands had a 22% greater snow depth on average, despite wide ranges
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