Model-based analysis of environmental controls over ecosystem primary production in an alpine tundra dry meadow

• Published in: Biogeochemistry
• Other Authors: Fan, Zhaosheng (author), Neff, Jason (author), Wieder, William (author)
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer 2016
• Subjects: Tundra
• Online Access: http://nldr.library.ucar.edu/repository/collections/OSGC-000-000-022-897; https://doi.org/10.1007/s10533-016-0193-9

We investigated several key limiting factors that control alpine tundra productivity by developing an ecosystem biogeochemistry model. The model simulates the coupled cycling of carbon (C), nitrogen (N), and phosphorus (P) and their interactions with gross primary production (GPP). It was parameterized with field observations from an alpine dry meadow ecosystem using a global optimization strategy to estimate the unknown parameters. The model, along with the estimated parameters, was first validated against independent data and then used to examine the environmental controls over plant productivity. Our results show that air temperature is the strongest limiting factor to GPP in the early growing season, N availability becomes important during the middle portion of the growing season, and soil moisture is the strongest limiting factors by late in the growing season. Overall, the controls over GPP during the growing season, from strongest to weakest, are soil moisture content, air temperature, N availability, and P availability. This simulation provides testable predictions of the shifting nature of physical and nutrient limitations on plant growth. The model also indicates that changing environmental conditions in the alpine will likely lead to changes in productivity. For example, warming eliminates the control of P availability on GPP and makes N availability surpass air temperature to become the second strongest limiting factor. In contrast, an increase in atmospheric nutrient deposition eliminates the control of N availability and enhances the importance of P availability. These analyses provide a quantitative and conceptual framework that can be used to test predictions and refine ecological analyses at this long-term ecological research site.