Document Type

Article

Journal/Book Title/Conference

Journal of Arid Environments

Volume

76

Publisher

Academic Press

Publication Date

7-20-2011

First Page

97

Last Page

104

Creative Commons License

Creative Commons Public Domain Mark 1.0 License
This work has been identified with a Creative Commons Public Domain Mark 1.0.

Abstract

Sagebrush-steppe ecosystems are one of the most threatened ecosystems in North America due to woodland expansion, wildfire, and exotic annual grass invasion. Some scientists and policy makers have suggested that woodland expansion will lead to increased carbon (C) storage on the landscape. To assess this potential we used data collected from a Joint Fire Sciences Program demonstration area to develop a Microsoft Excel™ based biomass, carbon, and nitrogen (N) spreadsheet model. The model uses input for tree cover, soil chemistry, soil physical properties, and vegetation chemistry to estimate biomass, carbon, and nitrogen accumulation on the landscape with woodland expansion. The model also estimates C and N losses associated with prescribed burning. On our study plots we estimate in treeless sagebrush-steppe ecosystems, biomass accounts for 4.5 Mg ha−1 C and 0.3 Mg ha−1 N this is <10% of total estimated ecosystem C and N to a soil depth of 53 cm, but as tree cover increases to near closed canopy conditions aboveground biomass may account for 62 Mg ha−1 C and 0.6 Mg ha−1 N which is nearly 53% of total estimated ecosystem C and 13% of total estimated ecosystem N to a soil depth of 53 cm. Prescribed burning removes aboveground biomass, C and N, but may increase soil C at areal tree cover below 26%. The model serves as a tool by which we are able to assess our understanding of the system and identify knowledge gaps which exist for this ecosystem. We believe that further work is necessary to quantify herbaceous biomass, root biomass, woody debris decomposition, and soil C and N with woodland expansion and prescribed fire. It will also be necessary to appropriately scale these estimates from the plot to the landscape.

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