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Applying Dendrochronology in Environmental Studies of Effects of Nitrogen Deposition on Forest Productivity. Paul R. Sheppard. Perturbations in N Cycle. Natural fixation: 140 Human fixation: 140 Mostly fertilizers Then legumes Plus cars, factories
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Applying DendrochronologyinEnvironmental Studies of Effects of Nitrogen Deposition on Forest Productivity Paul R. Sheppard
Perturbations inN Cycle • Natural fixation: 140 • Human fixation: 140 • Mostly fertilizers • Then legumes • Plus cars, factories • Essential fact: N fixation is doubled now
Nitrogen Saturation Too much of a good thing is not a good thing • Nutrient imbalances • Plant growth decline • Nitrate leaching into drinking water • Trace gas emissions Not certain of the impact of the grand N perturbation on forest productivity
Dendro-Soils Field Methods • Collect tree cores as usual • Collect soils data for each tree • Whole soil samples • Nutrient availability from IER • Careful mapping of trees within site • Normal physiographic information • Associate tree growth trends with soil/geomorphic properties, N
Field Useof Resins • Bury in root zone • How many per tree? • Distance from trunk? • Depth? • Rocks! • Working on this now Key point: like root absorption of nutrients
Dendro Environmental N Studies • Sites with sluggish natural N cycling • Along a steep gradient of N deposition • SoCal/Baja: • Old trees • Subalpine sites • Poor soils • Huge Ngradient
One-way ANOVA: 1950-70s versus hllslp5 Analysis of Variance for 1950-70s Source DF SS MS F P hllslp5 4 0.000881 0.000220 1.97 0.109 Error 66 0.007368 0.000112 Total 70 0.008249 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ----------+---------+---------+------ 1flats 8 0.00661 0.01564 (--------*---------) 2toeslp 6 0.00114 0.00978 (---------*----------) 3midslp 41 0.00100 0.00969 (---*---) 4shldr 10 0.00661 0.00540 (-------*--------) 5sumsad 6 0.01185 0.01523 (----------*----------) ----------+---------+---------+------ Pooled StDev = 0.01057 0.0000 0.0080 0.0160
One-way ANOVA: 1950-70s versus midslopes Analysis of Variance for 1950-70s Source DF SS MS F P midslope 1 0.000767 0.000767 7.07 0.010 Error 69 0.007482 0.000108 Total 70 0.008249 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+---------+---------+---------+ 1midslop 47 0.00100 0.00921 (-------*------) 2others 24 0.00795 0.01248 (----------*---------) ------+---------+---------+---------+ Pooled StDev = 0.01041 0.0000 0.0040 0.0080 0.0120
One-way ANOVA: 1950-70s versus mislopetoe Analysis of Variance for 1950-70s Source DF SS MS F P mislopet 1 0.000809 0.000809 7.50 0.008 Error 69 0.007440 0.000108 Total 70 0.008249 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ----+---------+---------+---------+-- 1midslop 51 0.00124 0.00929 (----*-----) 2others 20 0.00874 0.01283 (--------*---------) ----+---------+---------+---------+-- Pooled StDev = 0.01038 0.0000 0.0050 0.0100 0.0150
One-way ANOVA: NO3-N versus midslopes Analysis of Variance for NO3-N Source DF SS MS F P midslope 1 0.1 0.1 0.00 0.964 Error 69 2381.0 34.5 Total 70 2381.0 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+---------+---------+---------+ 1midslop 47 4.517 5.783 (----------*-----------) 2others 24 4.583 6.052 (---------------*---------------) ------+---------+---------+---------+ Pooled StDev = 5.874 3.0 4.5 6.0 7.5
One-way ANOVA: NH4-N versus midslopes Analysis of Variance for NH4-N Source DF SS MS F P midslope 1 69 69 0.63 0.430 Error 69 7589 110 Total 70 7658 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev -------+---------+---------+--------- 1midslop 47 16.44 11.26 (---------*---------) 2others 24 14.35 8.73 (-------------*-------------) -------+---------+---------+--------- Pooled StDev = 10.49 12.0 15.0 18.0
One-way ANOVA: K versus midslopes Analysis of Variance for K Source DF SS MS F P midslope 1 19390 19390 4.02 0.049 Error 69 332577 4820 Total 70 351967 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev -----+---------+---------+---------+- 1midslop 47 127.89 78.07 (-------*-------) 2others 24 92.96 47.64 (----------*----------) -----+---------+---------+---------+- Pooled StDev = 69.43 75 100 125 150
One-way ANOVA: Ca versus midslopes Analysis of Variance for Ca Source DF SS MS F P midslope 1 7.371 7.371 8.66 0.004 Error 69 58.709 0.851 Total 70 66.080 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev -------+---------+---------+--------- 1midslop 47 1.6157 0.9235 (-----*------) 2others 24 0.9346 0.9202 (--------*---------) -------+---------+---------+--------- Pooled StDev = 0.9224 0.80 1.20 1.60
One-way ANOVA: Mg versus midslopes Analysis of Variance for Mg Source DF SS MS F P midslope 1 0.1719 0.1719 7.79 0.007 Error 69 1.5220 0.0221 Total 70 1.6938 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ----+---------+---------+---------+-- 1midslop 47 0.3223 0.1509 (------*------) 2others 24 0.2183 0.1436 (---------*---------) ----+---------+---------+---------+-- Pooled StDev = 0.1485 0.180 0.240 0.300 0.360
One-way ANOVA: Na versus midslopes Analysis of Variance for Na Source DF SS MS F P midslope 1 0.0002700 0.0002700 5.56 0.021 Error 69 0.0033497 0.0000485 Total 70 0.0036197 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev -------+---------+---------+--------- 1midslop 47 0.017872 0.006896 (-------*--------) 2others 24 0.013750 0.007109 (----------*----------) -------+---------+---------+--------- Pooled StDev = 0.006968 0.0125 0.0150 0.0175
One-way ANOVA: IER NO3-N versus midslopes Analysis of Variance for IER NO3- Source DF SS MS F P midslope 1 475.8 475.8 4.76 0.034 Error 53 5297.0 99.9 Total 54 5772.7 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev -+---------+---------+---------+----- 1midslop 36 10.688 11.065 (--------*-------) 2others 19 4.503 7.498 (----------*-----------) -+---------+---------+---------+----- Pooled StDev = 9.997 0.0 4.0 8.0 12.0
Conclusions • Site selection • Tree selection • Ring-width processing • Soil measurements • Site chronologies have internal variability