Item Details

Ecohydrology of Delmarva Peninsula Barrier Island Forests and the Application of Lidar to Measure and Monitor Forest Structure

O'Connell, Michael John
Format
Thesis/Dissertation; Online
Author
O'Connell, Michael John
Advisor
Okin, Gregory
D’Odorico, Paolo
Macko, Stephen
Shugart, Hank
Abstract
Introduction 139 4.2. Background 142 4.2.1. Lidar remote sensing 142 4.2.2. The EAARL lidar 144 4.3. Methods 146 4.3.1. General considerations 146 4.3.2. Data collections 147 viii Section Page 4.3.3. EAARL data descriptions 148 4.3.4. Analyses 149 4.4. Results 152 4.4.1. Direct comparisons 152 4.4.2. Multiple regressions for stand-level metrics 157 4.4.3. PAI, and relationships of structural variables to site moisture 157 4.4.4. The EAARL correlates for moisture status monitoring 159 4.4.5. Alternative method of canopy information comparisons: principal components analysis 161 4.5. Discussion 164 4.5.1. Direct comparisons 164 4.5.2. Canopy profiles 167 4.5.3. Multiple regression models 169 4.5.4. Canopy principal components analysis 170 4.5.5. Occlusion 174 4.5.6. Ecohydrological relationships and monitoring 176 4.6. Conclusions 181 4.7. References 185 V. Summary 190 5.1. References 193 Appendix A. Canopy profiles 194 ix Section Page Appendix B. Crown lengths 199 Appendix C. PAI fluctuation 201 C.1. References 204 x List of Figures Figure Page 1.1. Map of Assateague and Parramore Islands of the Delmarva Peninsula 5 1.2. Conceptual model of the Mid-Atlantic barrier island sea-level and above-ground forest structure relationship, with basic monitoring cues 8 2.1. Overview map of the study area with plot locations 18 2.2. 2005 PAI readings by the sub-bio-types 29 2.3. Predicted PAI by multiple regression against field average PAI 30 2.4. The average litterfall (leaves only) through 2005 31 2.5a. Canopy presence frequency spectrums and tree stem profile charts from water-monitoring field plots of bio-type 1 33 2.5b. Canopy presence frequency spectrums and tree stem profile charts from water-monitoring field plots of bio-type 2 34 2.5c. Canopy presence frequency spectrums and tree stem profile charts from water-monitoring field plots of the outlier bio-type 34 2.5d. Canopy presence frequency spectrums and tree stem profile charts from water-monitoring field plots of PIVCR 35 2.6. PC space in the biophysical principal components analysis (PCA) 38 2.7. The dendrogram of cluster analysis results of the PC space functions developed with the plot biophysical features 39 2.8. PC space in the environmental principal components analysis (PCA) 41 xi Figure Page 2.9. The dendrogram of cluster analysis results of the PC space functions developed with the plot environmental features 42 2.10. Map of the AINS biophysical (bio)-type groups 44 2.11. Map of the AINS environmental (site) type groups 45 2.12. Graphical comparisons of the sub-bio-types in magnitudes and variation of sample population statistics for biophysical metrics 46 2.13. Graphical comparisons of the site-types in magnitudes and variation of sample population statistics for environmental metrics 47 2.14a. Bio-type 1 subdivision post-dbh 20-year radial growth trends 51 2.14a. Bio-type 2 subdivision post-dbh 20-year radial growth trends 51 2.15. Site type master tree ring chronology mean sensitivity and maximum canopy height 53 2.16. Pearson correlations between yearly tree ring radial increment and the months of a 17-month climate activity cycle 55 3.1. An example of water table fluctuation data used in the White ET equation from AINS plot 29803 86 3.2. Map of Assateague and Parramore Islands of the Delmarva Peninsula 89 3.3. Pearson correlations between PAI from 2005 and coarse structural metrics collected in all plots 95 3.4. PAI values across 2005 study period for plots in the biophysical bio-types 1 and 2 95 xii Figure Page 3.5. The average litterfall (leaves only) through 2005 monitoring for individual sites 97 3.6. Shrub canopy area and average height of the shrub layer in plots at AINS 100 3.7a. The STI profiles of plots in bio-type 1 with a linear best-fit trendline 102 3.7b. The STI profiles of plots in bio-type 2 with a linear best-fit trendline 103 3.7c. The STI profiles of plots in bio-type outliers with a linear best-fit trendline 103 3.8. Results of a dendrochronological analysis of radial growth rates performed on two bio-type subgroups at AINS of similar age and comparable canopy crown class positions 107 3.9a. 12-hour average tide and fresh water table levels at AINS plots in the winter dry period 109 3.9b. 24-hour average tide and fresh water table levels at PIVCR plots in the dry winter period 110 3.10. The Spearman correlation ranks of the tide and water tables for AINS and PIVCR in the winter dry period 110 3.11a. The SPECTRA procedure results for AINS plots in the dry winter period 111 3.11b. The SPECTRA procedure results for PIVCR plots in the dry winter period 112 3.12. Hourly OC Inlet tide for the winter dry period 112 xiii Figure Page 3.13. The best cross-correlation values between "prewhitened" tide and fresh water table levels at various lags for 7 AINS plots 113 3.14a-f. Individual AINS plot map excerpts with ARIMA results interpretations 114-115 3.15 Diagram of current water availability scale in an idealized Assateague Island soil column 120 4.1. An example of a lidar waveform returned from a 0.08ha land surface plot on AINS, August 2004 143 4.2. General EAARL survey configuration 145 4.3. Map of Assateague and Parramore Islands of the Delmarva Peninsula 147 4.4. A raw EAARL composite waveform and graphical metric descriptions 149 4.5. A comparison of an EAARL backscatter count spectrum and a field plot canopy foliage presence histogram 150 4.6. The EAARL waveform, field crown presence frequency histogram, maximum field height, and stem profile for the 10 instrumented water plots at AINS and 3 measured PIVCR plots 155-156 4.7. Regressions of the field-collected maximum canopy height, height of peak canopy density, and bare earth elevation against the respective EAARL-predicted values 157 4.8. Predictions of stand variables from multiple stepwise regressions with standard EAARL metrics MCH, CRR and HOME 158 xiv Figure Page 4.9. PAI values across 2005 study period for plots in the biophysical bio-types 1 and 2 159 4.10. Regressions of EAARL CRR-predicted PAI against the field-collected values 160 4.11. The PC loading locations in the canopy across all plots in the field measures of maximum foliage presence frequency and the EAARL returns of backscatter energy 162 4.12. Site type groups plotted in canopy density PCA space for field and EAARL according to their respective scores 162 4.13. New PC loading locations with HPCD as upper bounds in the field measures of maximum foliage presence frequency and the EAARL returns of backscatter energy 163 4.14 Site type groups plotted in the new HPCD-based canopy density principal component space for field and EAARL according to their respective scores 164 4.15. Correlations of HPCD and MCH with the other major structural parameters 166 4.16. Major biophysical parameters in the six environmental site types used to stratify PCA and other analyses 171 4.17. Diagram of water availability scale in an idealized Assateague Island soil column 179xv Figure Page 4.18. Conceptual model of the Mid-Atlantic barrier island sea-level and above-ground forest structure relationship, with basic monitoring cues 181 A.1. The EAARL waveform diagrams, the canopy presence frequency by height increment histograms, and the stem profiles for all plots 195-198 B.1. A comparison of the two results from separate crown length data sets for AINS plot 21901 200 C. Note: Abstract extracted from PDF text
Language
English
Date Received
20140123
Published
University of Virginia, Department of Environmental Sciences, PHD (Doctor of Philosophy), 2009
Published Date
2009-05-01
Degree
PHD (Doctor of Philosophy)
Collection
Libra ETD Repository
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