Van Gunst, K.J. 2012. Forest Mortality in Lake Tahoe Basin from ...

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16where NIR=Near-Infrared wavelength, Landsat TM band 4 and SWIR=ShortwaveInfrared wavelength, Landsat TM band 5. NDWI is less sensitive to atmosphericscattering and more sensitive to water absorption, rendering the index better suited todetection of coniferous forest mortality than other vegetation indices, such as NDVI orthe Tasseled Cap Indices (Gao 1996; Hunt and Rock 1989; Jin and Sader 2005;Vogelmann 1990; Vogelmann et al. 2009; Wilson and Sader 2002). Index strength incapturing gradations of foliage health was measured against 254 pixels in 80 polygons ofvarying mortality levels, delineated within USFS aerial survey damage polygons for 2008that were reconstructed using 2009 high-resolution imagery (Figure1-4; USDA ForestService-Forest Health Monitoring, 2008 Damage Polygons). Trees in high mortality plotswere defined by USFS as having over 75% of crown as red/brown/gray needles with treeswith fading crown foliage covering over 75% of the digitized polygon. Areas with lowmortality had less than 25% of fading trees covering the polygon, and medium mortalitypolygons had from 25-50% of the polygon covered by trees with 25-50% of fadingfoliage. Two way-ANOVA with a follow-up Bonferroni multiple comparison test wasused to compare NDWI values with the USFS forest mortality polygons. NDWI valueswere significantly different among high, medium and low, and no mortality pixels (p
17field data. In early fall of 2010, we measured canopy cover using the moosehorn canopymeasurement tool and recorded percent green canopy cover for trees over 5cm DBHacross 24, 60m x 60m plots with varying species composition, density, and amount ofmortality. Average percent green canopy per plot was regressed against the single-year2010 NDWI (Figure1-5). We used linear regression to estimate percent green canopycover per pixel, differenced NDWI among consecutive years to obtain dNDWI, and thenconsidered three possible thresholds of canopy mortality to convert continuous annualmortality maps, based on dNDWI, into binary maps of “healthy” and “unhealthy” pixels.The three dNDWI thresholds considered corresponded to an absolute loss of 5, 10, or20% of green canopy per year. Initial sensitivity analyses revealed that the 20% thresholdwas too strict, but that the 5% loss (corresponding dNDWI= -0.0503) and 10% loss(corresponding dNDWI= -0.106) thresholds exhibited reasonable behavior. Simard et al.(2012) used a similar approach to transform remote-sensing derived mortality maps tobeetle-killed and undisturbed pixels using a threshold of 10% beetle-killed basal area. Insummary, annual mortality maps were derived in the following sequence (Figure 1-6): 1)Image acquisition and processing (a), 2) Transformation of image pairs into single-yearNDWI (b1 and b2), 3) Calculation of differenced NDWI between image pairs in forestedareas of LTB (c), and 4) Transformation of continuous dNDWI into binary classificationof healthy v canopy dieback pixels (d).Mortality processes in tree crowns are defined by progressive changes in spectralindices as canopy foliage dies, with needles turning from green to red to gray andeventually dropping from the tree (Ahern 1988; Dennison et al. 2010; Wulder et al.2006). Pixel NDWI may decline further following the initial onset of mortality due to
Page 1 and 2: University of Nevada, RenoForest Mo
Page 4 and 5: iTHESIS ABSTRACTWidespread and sync
Page 6 and 7: iiimiddle and upper-elevation fores
Page 8 and 9: vpine (Pinus albicaulis) forests of
Page 10 and 11: viiACKNOWLEDGMENTS: Primary financi
Page 12 and 13: ixPlate 2. Photograph of mountain p
Page 14 and 15: xiForest Types and Ecoregions......
Page 16 and 17: xiiiAPPENDIX A. 25 years of annual
Page 18 and 19: xvefficiency measures agreement bet
Page 20 and 21: xviimortality; Negative DDM: decrea
Page 22 and 23: xixratios greater than one indicate
Page 24 and 25: 2ABSTRACTIncreased stand density is
Page 26 and 27: 4rise to outbreaks of widespread mo
Page 28 and 29: 6of compounds and structures necess
Page 30 and 31: 8landscapes (Logan et al. 1998; Nel
Page 33 and 34: 11(Sierra Nevada) of the LTB with m
Page 35 and 36: 13treatment areas were also exclude
Page 37: 15We evaluated the accuracy of mode
Page 41 and 42: 19gray canopies, a result of the co
Page 43 and 44: 21established five climatic periods
Page 45 and 46: 23far greater during the first drou
Page 47 and 48: 25slightly more frequent during the
Page 49 and 50: 27but persistent factor for forest
Page 51 and 52: 29For sugar pine, mortality risk in
Page 53 and 54: 31treatments to be variable, incons
Page 55 and 56: 33Baret, F. and G. Guyot. 1991. Pot
Page 57 and 58: 35Das, Adrian, John Battles, Nathan
Page 59 and 60: 37Fettig, Christopher J., Robert R.
Page 61 and 62: 39Huete, A.R., H.Q. Liu, K. Batchil
Page 63 and 64: 41Loomis W E. 1932. Growth-differen
Page 65 and 66: 43Moritz, Max A., Paul F. Hessburg,
Page 67 and 68: 45Scholl, Andrew E. and Alan H. Tay
Page 69 and 70: 47van Mantgem, P.J., Stephenson, N.
Page 71 and 72: 49Table 1-1. Description of LTB for
Page 73 and 74: 51TABLE 1-3a,b. Validation of remot
Page 75 and 76: 53TABLE 1-5. Summary of odds-ratios
Page 77 and 78: FIGURE 1-1. Location of Lake Tahoe
Page 79 and 80: 57a.b.FIGURE 1-3a, b. LAI Validatio
Page 82 and 83: 60b1.b2.d. c.FIGURE 1-6. Pictorial
Page 84 and 85: 62FIGURE 1-8. Mortality levels and
Page 86 and 87: 64FIGURE 1-10. Direction and magnit
Page 88 and 89:
66FIGURE 1-12. Number of models whe
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Ratio: Positive DDM:Negative DDM681
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70FIGURE 1-16. Average odds ratio f
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72APPENDIX A. 95 th Percentile of L
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19801982198419861988199019921994199
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76APPENDIX C. Final models in five
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78ForestType Year Model LRT ModelTy
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80Chapter 2 - Spatial and Temporal
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83mountainous regions of snow-domin
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85McDowell et al. 2008; Rice et al.
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87periods in the same forest may re
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89Forest Types and EcoregionsWe exa
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91Environmental VariablesIn additio
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93(Figure 2-6). Forest mortality ma
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95In JP forests, decreases in eleva
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97that abrupt declines in growth ar
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99and d2) and increased temperature
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101concentrated at lower elevations
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103responses may be due to the grea
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105Berg, Edward E, J. David Henry,
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107from 1991-1996 near Spooner Lake
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109Hansen, E., Bentz, B. and Turner
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111reference to historical disturba
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113Ogle, Kiona, Thomas G. Whitham,
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115SNEP [Sierra Nevada Ecosystem Pr
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117Vygodskaya, N.N., E.D. Schulze,
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119ForestType Coefficients Standar
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121a.b.c.d.FIGURE 2-1. Ecoregions (
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123FIGURE 2-3. Solar radiation (WH/
Page 147 and 148:
125FIGURE 2-5. Boxplots of annual m
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127FIGURE 2-7. Effect plots for Ann
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129a: JPb: MFc: RFFIGURE 2-9a-c. Le
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131FIGURE 2-11. Location of increas
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133FIGURE 2-13. Location of increas
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1351993-94 1994-95 1995-96 1996-971
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137THESIS SUMMARYForest mortality i
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Van Gunst, K.J. 2012. Forest Mortality in Lake Tahoe Basin from ...

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