Spatial Modeling of Forest Foliar Nitrogen Concentration across the Southern US Region

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dc.contributor.advisor Hugh Devine, Committee Member en_US
dc.contributor.advisor Montserrat Fuentes, Committee Member en_US
dc.contributor.advisor Steven McNulty, Committee Member en_US
dc.contributor.advisor Ge Sun, Committee Co-Chair en_US
dc.contributor.advisor Siamak Khorram, Committee Co-Chair en_US Mao, Zhiyan en_US 2010-04-02T18:12:50Z 2010-04-02T18:12:50Z 2003-12-03 en_US
dc.identifier.other etd-09032003-092528 en_US
dc.description.abstract Foliar N concentration represents a primary link between C and N dynamics in forest ecosystems, and it is widely used as a critical parameter for ecosystem modeling. This study was designed to investigate the relationships between foliar N concentrations and a set of environmental factors, and to detect the spatial pattern of forest foliar N concentrations in the southern US region. A field observation foliar N concentration database was generated by combining literature search data with field study data. A spatial GIS database was developed from diverse data sources, which contained: climatic variables such as mean January temperature, mean July temperature and precipitation; soil variables such as soil organic matter and soil available water capacity; and total N deposition. Totally 104 data points were obtained including 61 for deciduous forests and 43 for coniferous forests after processing both foliar N concentration and GIS data. Various model fit approaches were employed for exploring the regression relations between foliar N concentrations and the selected environmental variables, including simple linear regression, variable-transformed linear regression and stepwise-based multiple regression. It was found that in this region, foliar N concentrations of deciduous forests were correlated primarily with mean July temperature, secondarily with mean January temperature, while foliar N concentrations of coniferous forests were correlated primarily latitude, secondarily with mean January temperature. A set of predictive equations were developed based on the regression analysis results and validated against previously reserved data points using split-sample approach. These equations could be applied across the region for spatially explicit estimation of forest foliar N concentrations. en_US
dc.rights I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. en_US
dc.subject spatial modeling en_US
dc.subject GIS en_US
dc.subject linear regression en_US
dc.subject stepwise regression en_US
dc.subject foliar N concentration en_US
dc.title Spatial Modeling of Forest Foliar Nitrogen Concentration across the Southern US Region en_US MS en_US thesis en_US Forestry en_US

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