analysis of taper responses to sulfur treatments in coastal oregon doug-fir

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Analysis of Taper Responses to Sulfur Treatments in Coastal Oregon Doug-fir. Western Mensurationists’ 2006 Annual Meeting June 19, 2006. Nicole Younger MS student, Department of Forest Resources, Oregon State University. And Hud. What is Swiss Needle Cast Disease?. - PowerPoint PPT Presentation

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Analysis of Taper Responses to Sulfur Treatments in Coastal Oregon Doug-fir

Western Mensurationists’ 2006 Annual Meeting June 19, 2006

Nicole YoungerMS student,

Department of Forest Resources,Oregon State University

And Hud

What is Swiss Needle Cast Disease?• Blame the Swiss!

• Tree rust caused by a fungus

• Clogs stomata with pseudothecia

• Pseudothecia count increases with age of needle

• Needle eventually dies

• Needle retention 3-4 years in healthy trees, two or less in infected trees

3rd year 2nd yearCurrent year

Volume loss estimated at 23% with a high of 50% in the severely infected stands.

Spread over the target population of 187,000 acres, this means that

approximately 40MMBF were lost to this disease in 1996 alone!

(Maguire et al. 1998)

What is Swiss Needle Cast Disease?

What do we do now?!?

• Essential ingredient for plant nutrition --component of amino acids, proteins, fats, and other plant compounds

• In the soil, sulfur (SO4) also plays a pivotal role in the movement of acidic cations such as H+, and Al3+, as well as nutrient cations such as Ca2+ and Mg2+ (Johnson and Mitchell 1998) Critical C/N ratio in the OR coast range

• Factory emmisions are being tightened resulting in less atmosheric Sulfur

• Recent discoveries of plants actually producing sulfur as a natural fungal defense (Williams and Cooper 2003)

• “Considered essentially non-toxic by ingestion” (MSDS)

Three treatments:

1. Sulfur

2. Sulfur and nutrients

3. Control

10 plots/treatment

4 Trees/plot

(40 trees per treatment, 120 total)

Experimental Site

Nilsen Creek, Lincoln County, Oregon

Aerial applications took place 2000-2004

Ca prils

• Planted in 1983 with all the same stock, 430 TPA

• Total height (H) ranged from 16.92 – 26.20 meters, with the mean at 21.53 m (std dev 1.61 m)

• DBH outside bark (D) ranged from 104.50 – 336.00 mm with a mean of 208.87 mm (std dev 42.25 mm)

• Early vegetation control, hack and squirt of hardwoods pre-canopy closure

• Slope/elevation/aspect all similar between treatment sites

Felled in April 2005

Trees measured and disks collected July – August 2005

Stump disk

DBH disk

Disk 1

Crown base disk

Disk 2

Approximately 9 disks per tree were taken (1063 disks total) Diameter (inside and outside bark), height of disk

as well as sapwood area of CB

disk recorded

6” DBH 1 2 CB 3 4 5

Each tree measured for:

Total height, crown ratio, lowest live branch location, crown width

Needle characteristics (LA, width, length)

control – sulfur comparison p-value = 0.51

control – sulfur and nutrient comparison p-value = 0.85

Cont r ol Sul f _ nu Sul f ur

0

1

2

3

4

5

Crown

Width

Control Sulfur and Nutrient Sulfur

control – sulfur comparison p-value = 0.94

control – sulfur and nutrient comparison p-value = 0.67

Cont r ol Sul f _nu Sul f ur

0

10000

20000

30000

40000

Sapwood

area

Control Sulfur and Nutrient Sulfur

control – sulfur comparison p-value = 0.14

control – sulfur and nutrient comparison p-value = 0.16

Cont r ol Sul f _nu Sul f ur

0. 2

0. 3

0. 4

0. 5

0. 6

0. 7

0. 8

Crown

ratio

Control Sulfur and Nutrient Sulfur

control – sulfur comparison p-value = 0.998

control – sulfur and nutrient comparison p-value = 0.073

Cont r ol Sul phur Sul phur _ Li me

0

200

400

600

800

1000

Total

Foliar

Weight

Control Sulfur Sulfur and Nutrient

control – sulfur comparison p-value = 0.276

control – sulfur and nutrient comparison p-value = 0.028

Cont r ol Sul phur Sul phur _ Li me

2. 50

2. 75

3. 00

3. 25

3. 50

3. 75

4. 00

Foliar

Retention

Control Sulfur Sulfur and Nutrient

control – sulfur comparison p-value = 0.0039

control – sulfur and nutrient comparison p-value = <0.0001

TreatmentLS mean (mm) 95% Conf. Int.

Control 3.26 3.12 – 3.39

Sulfur/Nutrient 3.70 3.57 – 3.84

Sulfur 3.54 3.40 – 3.67

“pre-treat” increment = (1996+1997+1998+1999)/4“post-treat” increment = (2001+2002+2003+2004)/4

Ignoring autocorrelations in taper data sets causes (Kozak 1997):

1. Estimators which no longer have a minimum variance property

2. Underestimation of standard errors on parameter estimates

3. Unreliable tests of significance

Question:

Does ignoring these autocorrelations in my taper dataset cause tests of treatment effects to be falsely significant?

X a HDb b Zb 0.001)ln(Zb ZbD

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Where: di = diameter inside bark of ith diskhi = height from ground of ith diskH = total height of treeZ = hi/Hp =(HI/H)*100D = diameter outside bark at breast heighta0 – a2 and b1 – b5 = parameters to be estimated

X = pH

hi

1

1

Properties of Model:

1. di = 0 when hi/H = 1.0

2. di = DI (estimated dib at inflection point) when HI/H = P

3. function changes direction when hi/H = p

X a HDb b Zb 0.001)ln(Zb ZbD

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0 5 10 15 20 25

hi

0

100

200

300

400

di

ControlSulf_nutrSulfur

a0 a1 a2 b1 b2 b3 b4

a1 -0.999            

a2 0.984 -0.989    

b1 0.007 -0.001 -0.003  

b2 -0.024 0.017 -0.018 -0.91  

b3 0.023 -0.015 0.014 0.883 -0.987  

b4 -0.016 0.008 -0.006 -0.937 0.982 -0.988  

b5 -0.049 0.053 -0.07 0.392 -0.11 0.151 -0.275

Parameter Correlation Matrix

X a HDb b Zb 0.001)ln(Zb ZbD

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Value Std.Error t-value p-value a0 3.1370 1.2648 2.480 0.0133a1 0.7066 0.0923 7.653 <.0001a2 1.0009 0.0004 2332.256 <.0001

After Removal of a2 parameter:

a0 1.3607 0.0993 13.6992 <.0001a1 0.8989 0.0135 66.6847 <.0001

X HDb b Zb 0.001)ln(Zb Zb

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X IbIbHDb b Zb 0.001)ln(Zb Zb

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Treatment Indicators added to exponent:

IS = 1 if treatment = Sulfur, 0 otherwiseISN = 1 if treatment = Sulfur and Nutrient, 0 otherwise

Sulfur treatment insignificant (p = 0.3588)Sulfur and nutrients treatment does effect taper! (p = 0.0017)

Z

dC

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.5

1.0

1.5

2.0

0.0

0.2

0.4

0.6

0.8

1.0

0 2 4 6

Lag

Au

toco

rre

latio

n

-50

0

50

100

0 100 200 300 400

di

Re

sid

ua

ls

-50

0

50

100

0.0 0.2 0.4 0.6 0.8 1.0

Z

Re

sid

ua

ls

-50

0

50

100

0.0 0.5 1.0 1.5

X

Re

sid

ua

ls

-50

0

50

100

100 150 200 250 300

D

Re

sid

ua

ls

Sulfur treatment still insignificant (p = 0.6689 vs. p = 0.3588 without car(1))

Sulfur and nutrient treatment still significant (p = 0.0010 vs. p = 0.0017 without car(1))

X IbIbHDb b Zb 0.001)ln(Zb Zb

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Sulfur treatment still insignificant (p = 0.1230)

Sulfur and nutrient treatment still significant (p = 0.0135)

X IbIbHDb b Zb 0.001)ln(Zb Zb

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Sulfur treatment still insignificant (p = 0.0930)

Sulfur and nutrient treatment more significant (p = <0.0001)

Model df AIC BIC log LikelihoodGNLS 10 8447.159 8496.847 -4213.579 GNLScar 12 8370.610 8430.236 -4173.305 NLME 11 8460.590 8515.248 -4219.295 NLMEcar 13 8452.210 8516.805 -4213.105

X IbIbHDb b Zb 0.001)ln(Zb Zb

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Test log likelihood ratio p-valueGNLS vs GLNScar 80.54881 <.0001GNLScar vs NLME 91.98045 <.0001NLME vs NLMEcar 12.38081 0.002GNLS vs NLME 11.43164 0.0007GNLScar vs NLMEcar 79.59964 <.0001

X IbIbHDb b Zb 0.001)ln(Zb Zb

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Sulfur/

Sulfur Nutrient

GNLS -0.01 -0.04

GNLS car(1) -0.01 -0.04

NLME -0.02 -0.04

NLMEcar(1) -0.02 -0.05

Parameter estimates experienced little change:

X IbIbHDb b Zb 0.001)ln(Zb Zb

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P-values of treatment parameters show no clear patterns:

X IbIbHDb b Zb 0.001)ln(Zb Zb

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Sulfur/

Sulfur Nutrient

GNLS 0.3588 0.0017

GNLS car(1) 0.6689 0.0010

NLME 0.1230 0.0135

NLMEcar(1) 0.0930 <0.0001

• Parameters relatively unchanged as hypothesized

• Standard errors of treatment parameters fluxuated, did not necessarily become less significant as expected

• Adding car(1) to GNLS or NLME significantly fit data better

• Adding random tree effect also helped to fit data significantly better

Special Thanks

Starker Forests Inc. for project funding supplying treated field sites

Sean Garber for sharing his S-Plus knowledge and taper enthusiasm

Temesgen Hailemariam for his guidance and the opportunity to attend this meeting

Works Cited

• Johnson DW, Mitchell MJ (1998) Responces of forest ecosystems to changing sulfur inputs. In 'Sulfur in the Environment'. (Ed. D Maynard) pp. 219-262. (Marcel Dekker, Inc.: New York)

• Maguire DA, Kanaskie A, Johnson R, Johnson G, Voelker W (1998) 'Swiss needle cast growth impact study: report on results from phases I and II.' College of Forestry, Oregon State University, Corvallis, OR.

• Material Safety Data Sheets (2005)

• Williams JS, Cooper RM (2003) Elemental sulfur is produced by diverse plant families as a component of defense against fungal and bacterial pathogens. Physiological and Molecular Plant Pathology 63, 3-16.

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