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  5. Developing Historical Productivity Maps for the Blue Oak Woodlands in California using Remote Sensing and Dendrochronology
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Developing Historical Productivity Maps for the Blue Oak Woodlands in California using Remote Sensing and Dendrochronology

Date Issued
August 1, 2016
Author(s)
Landolt, Kyle Lawrence  
Advisor(s)
Robert A. Washington-Allen
Additional Advisor(s)
Nicholas Nagle
Henri Grissino-Mayer
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/40110
Abstract

Global terrestrial carbon dynamics play a critical role in the Earth system. Increased net primary productivity (NPP) associated with terrestrial ecosystems can influence the amount of atmospheric carbon dioxide by sequestering carbon through photosynthesis. Drylands, in particular, are an important terrestrial component that can act as a source or sink for carbon storage depending on various environmental factors that influence vegetation and soil patterns. Blue oak woodlands represent a large component of the terrestrial vegetation in California and provide an opportunity to study the historical variation in NPP by combining dendrochronological measurements and a satellite-based proxy for NPP: the remotely sensed time-integrated NDVI (iNDVI). The purpose of this research was to investigate the possible correlation of iNDVI to blue oak chronology measurements to reconstruct iNDVI of the blue oak woodlands from 1700 to 2003. We developed linear regressions to explain iNDVI using two types of blue oak chronologies, elevation, slope, aspect, cation exchange capacity, and ecological sections and compared our results to reconstructed Palmer Drought Severity Index (PDSI). A spatial scale study was done to test for the optimal scale at which iNDVI can be predicted. Our reconstructions were able to predict iNDVI (Adjusted R-squared = 0.715; p < 0.001) and were also correlated to PDSI values (r = 0.8; p < 0.001), finding notably high and low values of iNDVI at 1789 and 1934, respectively. We also found that the residual chronology and a spatial scale of 3136 square kilometers predicted iNDVI most accurately. These findings produce a novel time-series of iNDVI that can be used to determine how historical vegetation productivity has fluctuated and sequestered carbon in the blue oak woodlands and provides a framework for global reconstructions of vegetation productivity.

Degree
Master of Science
Major
Geography
Embargo Date
August 15, 2017
File(s)
Thumbnail Image
Name

0-mean_rerror.pdf

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15.31 KB

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Adobe PDF

Checksum (MD5)

b0238c546a2ff771060614ea51011e03

Thumbnail Image
Name

1-mean_rerror.pdf

Size

15.31 KB

Format

Adobe PDF

Checksum (MD5)

b0238c546a2ff771060614ea51011e03


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