Moisture stress indicators in giant sequoia groves in the southern Sierra Nevada of California, USA

Document Type

Article

Publication Title

Vadose Zone Journal

Abstract

Giant sequoia [Sequoiadendron giganteum (Lindl.) J. Buchholz] trees and their ecosystems are unique natural treasures in the Sierra Nevada, California, where most groves are federally managed for biodiversity, perpetuation of the species, and aesthetic, recreational, ecological, and scientific values. Increasing temperatures during the next several decades may create conditions unfavorable for these giant sequoias. Therefore, it is necessary to develop effective management systems to preserve the health of these giant sequoia groves. This study used a topographic wetness index (TWI) as the indicator of soil moisture conditions to evaluate the vulnerability of giant sequoia groves to soil moisture stress and focused on evaluating TWI distributions among all 70 sequoia groves to assess their vulnerability to soil moisture stress. The TWI values were derived using a 10-m digital elevation model and compared with soil, geology, slope, aspect, and elevation at the sequoia groves to understand the vulnerability of the groves to soil moisture stress. The TWI values were also compared with snow cover persistence derived from 12 yr of MODIS snow cover products. In addition, satellite soil moisture products were used to compare the dry and wet periods predicted by snow cover persistence. Results showed that the groves located at higher elevation are less vulnerable unless the TWI across the groves is low. For the large number of groves with elevations mainly in the 1800- to 2100-m range, the TWI distributions can serve as a first-order indicator of relative vulnerability. Further, this analysis showed that areas with milder slopes and more converging area (higher TWI), plus longer snow cover persistence, should be less susceptible to low summer soil moisture than areas having steeper slopes, more diverging topography (lower TWI), and earlier snowmelt. This analysis can be used to highlight groves that are potentially more vulnerable, particularly when considering TWI, snow cover persistence, and satellite soil moisture together.

DOI

10.2136/vzj2016.03.0018

Publication Date

10-1-2016

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