TRADER-package: Tree Ring Analysis of Disturbance Events in R
In TRADER: Tree Ring Analysis of Disturbance Events in R
Description
Details
Author(s)
References
See Also
Examples
Description
The TRADER package provides only one way for disturbance reconstruction from tree-ring data. TRADER is a unique package bringing the first instrument for analysis of forest disturbance history in complementary ways. Final advantage of TRADER is the possibility of results comparison between individual studies. This is enabled by easy parameter changes in data processing, as well as by clearly arranged graphical and tabular outputs. We developed TRADER in open source R environment, to further support the on-going open-source software development for dendrochronological methods and data availability.
Details
Package: TRADER
Type: Package
Version: 1.2-3
Date: 2017-01-13
License: GPL-2 | GPL-3
library(TRADER)
Author(s)
Pavel Fibich <pavel.fibich@prf.jcu.cz>, Jan Altman <altman.jan@gmail.com>, Tuomas Aakala <tuomas.aakala@helsinki.fi>, Jiri Dolezal <jiriddolezal@gmail.com>
Maintainer: Pavel Fibich <pavel.fibich@prf.jcu.cz>
References
Nowacki, G.J. & Abrams, M.D. 1997. Radial-growth averaging criteria for reconstructing disturbance histories from presettlement-origin oaks. Ecological Monographs, 67, 225-249.
Black, B.A. & Abrams, M.D. 2003. Use of boundary-line growth patterns as a basis for dendroecological release criteria. Ecological Applications, 13, 1733-1749.
Fraver, S. & White, A.S. 2005. Identifying growth releases in dendrochronological studies of forest disturbance. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere, 35, 1648-1656.
Splechtna, B.E., Gratzer, G. & Black, B.A. 2005. Disturbance history of a European old-growth mixed-species forest - A spatial dendro-ecological analysis. Journal of Vegetation Science, 16, 511-522.
See Also
Examples
1
2
3
4
5
6
7
8
9
10
11
12
13
14
data(relData)
plotFirstYears(relData1)
plotGrowth(relData1)
absoluteIncreaseALL(relData1,length=3,buffer=4,storedev=jpeg)
growthAveragingALL(relData1,length=3,buffer=4,storedev=pdf)
boundaryLineALL(relData1,length=2,buffer=2,storedev=pdf,
boundary=function(x) {5.0067*exp(-0.664*x)} )
splechtnaALL(relData1,length=3,buffer=4,storedev=pdf,
boundary=function(x) {5.0067*exp(-0.664*x)} )
doAll(relData1,length=3,buffer=4,storedev=pdf)
knownBL
Example output
png
2
[1] "## Fraver & White analysis!"
[1] "Absolute threshold 1.2 m1 10 m2 10 Buffer 4 Length 3"
[1] "Total number of releases is 16"
inyears
1895 1896 1904 1935 1936 1938 1939 1944 1978
1 3 1 4 1 2 1 1 2
[1] "## Nowacki & Abrams analysis!"
[1] "Criteria 0.25 Criteria2 0.5 m1 10 m2 10 Buffer 4 Length 3"
[1] "Total number of releases >= 0.25 & < 0.5 is 6"
inyears
1888 1920 1935 1936 1978 1980
1 1 1 1 1 1
[1] "Total number of releases >= 0.5 is 22"
inyears
1895 1896 1903 1927 1935 1936 1938 1942 1947 1978 1986 1993
1 3 1 1 4 4 2 1 1 2 1 1
[1] "## Black & Abrams analysis!"
[1] "Criteria 0.2 Criteria2 0.5 m1 10 m2 10 Buffer 2 Length 2 Segment 0.5 Segment2 0.5"
[1] "Total number of releases >= 0.2 & < 0.5 is 14"
inyears
1888 1899 1935 1936 1938 1940 1947 1978 1980 1984 1986
1 1 1 2 3 1 1 1 1 1 1
[1] "Total number of releases >= 0.5 is 25"
inyears
1893 1894 1895 1896 1899 1903 1907 1935 1936 1938 1939 1940 1941 1942 1978
1 1 1 3 1 1 1 6 2 2 1 1 1 1 2
[1] "## Splechtna analysis!"
[1] "Criteria 0.2 Criteria2 0.5 m1 10 m2 10 Buffer 4 Length 3 Segment 0.5 Segment2 0.5"
[1] "Total number of releases >= 0.2 & < 0.5 is 16"
inyears
1896 1927 1935 1936 1938 1942 1947 1978 1986 1993
1 1 4 3 1 1 1 2 1 1
[1] "Total number of releases >= 0.5 is 9"
inyears
1896 1935 1936 1942 1978
1 3 2 1 2
[1] "## Fraver & White analysis!"
[1] "Absolute threshold 1.2 m1 10 m2 10 Buffer 4 Length 3"
[1] "Total number of releases is 16"
inyears
1895 1896 1904 1935 1936 1938 1939 1944 1978
1 3 1 4 1 2 1 1 2
[1] "## Nowacki & Abrams analysis!"
[1] "Criteria 0.25 Criteria2 0.5 m1 10 m2 10 Buffer 4 Length 3"
[1] "Total number of releases >= 0.25 & < 0.5 is 6"
inyears
1888 1920 1935 1936 1978 1980
1 1 1 1 1 1
[1] "Total number of releases >= 0.5 is 22"
inyears
1895 1896 1903 1927 1935 1936 1938 1942 1947 1978 1986 1993
1 3 1 1 4 4 2 1 1 2 1 1
[1] "## Black & Abrams analysis!"
[1] "Criteria 0.2 Criteria2 0.5 m1 10 m2 10 Buffer 4 Length 3 Segment 0.5 Segment2 0.5"
[1] "--Summary of y=a+bx fit."
Call:
lm(formula = tops ~ segments, data = boundaries)
Residuals:
1 2 3 4 5 6 7
-2.1637 1.7473 1.3473 -0.1650 -0.1749 -0.2988 -0.2922
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.6631 1.0656 2.499 0.0545 .
segments -0.7266 0.5287 -1.374 0.2277
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.399 on 5 degrees of freedom
Multiple R-squared: 0.2742, Adjusted R-squared: 0.129
F-statistic: 1.889 on 1 and 5 DF, p-value: 0.2277
[1] "--Summary of y=a+bx+cx^2 fit."
Call:
lm(formula = tops ~ segments + I(segments^2), data = boundaries)
Residuals:
1 2 3 4 5 6 7
-1.2627 1.7473 0.8067 -0.8858 -0.7155 -0.2988 0.6088
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.1766 1.5661 0.751 0.494
segments 1.7961 2.0898 0.859 0.439
I(segments^2) -0.7208 0.5796 -1.244 0.282
Residual standard error: 1.328 on 4 degrees of freedom
Multiple R-squared: 0.4765, Adjusted R-squared: 0.2148
F-statistic: 1.821 on 2 and 4 DF, p-value: 0.274
[1] "--Summary of y=ae^bx fit."
Formula: tops ~ a * exp(b * segments)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 2.4721 1.4860 1.664 0.157
b -0.3441 0.4231 -0.813 0.453
Residual standard error: 1.48 on 5 degrees of freedom
Number of iterations to convergence: 19
Achieved convergence tolerance: 7.85e-06
[1] "y=c+ae^bx nls error: step factor 0.000488281 reduced below 'minFactor' of 0.000976562"
[1] "y=c+dx+ae^bx nls error: singular gradient"
[1] "y=ae^bx+ce^dx nls error: Missing value or an infinity produced when evaluating the model"
[1] "--Summary of y=a+blog(x) fit."
Formula: tops ~ a + b * log(segments)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 1.5195 0.6389 2.378 0.0633 .
b -0.4241 0.7248 -0.585 0.5839
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.588 on 5 degrees of freedom
Number of iterations to convergence: 1
Achieved convergence tolerance: 8.688e-09
[1] "--Summary of y=a+bx+clog(x)+dxlog(x) fit."
Call:
lm(formula = tops ~ segments + log(segments) + segments:log(segments),
data = boundaries)
Residuals:
1 2 3 4 5 6 7
-0.007628 0.001627 0.189574 -0.418157 0.170181 0.193449 -0.129045
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 30.061 4.285 7.016 0.00595 **
segments -26.547 4.156 -6.388 0.00777 **
log(segments) 14.067 1.957 7.189 0.00555 **
segments:log(segments) 10.384 1.852 5.606 0.01121 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.313 on 3 degrees of freedom
Multiple R-squared: 0.9782, Adjusted R-squared: 0.9564
F-statistic: 44.86 on 3 and 3 DF, p-value: 0.005431
[1] "The fitted boundary line summary!"
[1] "Logarithmic model y=a+bx+clog(x)+dxlog(x) was the best!"
Call:
lm(formula = tops ~ segments + log(segments) + segments:log(segments),
data = boundaries)
Residuals:
1 2 3 4 5 6 7
-0.007628 0.001627 0.189574 -0.418157 0.170181 0.193449 -0.129045
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 30.061 4.285 7.016 0.00595 **
segments -26.547 4.156 -6.388 0.00777 **
log(segments) 14.067 1.957 7.189 0.00555 **
segments:log(segments) 10.384 1.852 5.606 0.01121 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.313 on 3 degrees of freedom
Multiple R-squared: 0.9782, Adjusted R-squared: 0.9564
F-statistic: 44.86 on 3 and 3 DF, p-value: 0.005431
[1] "Total number of releases >= 0.2 & < 0.5 is 13"
inyears
1888 1897 1899 1934 1935 1938 1944 1947 1967
1 1 2 1 3 2 1 1 1
[1] "Total number of releases >= 0.5 is 23"
inyears
1893 1896 1899 1903 1910 1935 1938 1939 1940 1941 1942 1943 1944 1978 1982
2 2 1 2 1 4 1 2 1 1 1 1 1 2 1
[1] "## Splechtna analysis!"
[1] "Criteria 0.2 Criteria2 0.5 m1 10 m2 10 Buffer 4 Length 3 Segment 0.5 Segment2 0.5"
[1] "--Summary of y=a+bx fit."
Call:
lm(formula = tops ~ segments, data = boundaries)
Residuals:
1 2 3 4 5 6 7
-2.1637 1.7473 1.3473 -0.1650 -0.1749 -0.2988 -0.2922
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.6631 1.0656 2.499 0.0545 .
segments -0.7266 0.5287 -1.374 0.2277
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.399 on 5 degrees of freedom
Multiple R-squared: 0.2742, Adjusted R-squared: 0.129
F-statistic: 1.889 on 1 and 5 DF, p-value: 0.2277
[1] "--Summary of y=a+bx+cx^2 fit."
Call:
lm(formula = tops ~ segments + I(segments^2), data = boundaries)
Residuals:
1 2 3 4 5 6 7
-1.2627 1.7473 0.8067 -0.8858 -0.7155 -0.2988 0.6088
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.1766 1.5661 0.751 0.494
segments 1.7961 2.0898 0.859 0.439
I(segments^2) -0.7208 0.5796 -1.244 0.282
Residual standard error: 1.328 on 4 degrees of freedom
Multiple R-squared: 0.4765, Adjusted R-squared: 0.2148
F-statistic: 1.821 on 2 and 4 DF, p-value: 0.274
[1] "--Summary of y=ae^bx fit."
Formula: tops ~ a * exp(b * segments)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 2.4721 1.4860 1.664 0.157
b -0.3441 0.4231 -0.813 0.453
Residual standard error: 1.48 on 5 degrees of freedom
Number of iterations to convergence: 19
Achieved convergence tolerance: 7.85e-06
[1] "y=c+ae^bx nls error: step factor 0.000488281 reduced below 'minFactor' of 0.000976562"
[1] "y=c+dx+ae^bx nls error: singular gradient"
[1] "y=ae^bx+ce^dx nls error: Missing value or an infinity produced when evaluating the model"
[1] "--Summary of y=a+blog(x) fit."
Formula: tops ~ a + b * log(segments)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 1.5195 0.6389 2.378 0.0633 .
b -0.4241 0.7248 -0.585 0.5839
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.588 on 5 degrees of freedom
Number of iterations to convergence: 1
Achieved convergence tolerance: 8.688e-09
[1] "--Summary of y=a+bx+clog(x)+dxlog(x) fit."
Call:
lm(formula = tops ~ segments + log(segments) + segments:log(segments),
data = boundaries)
Residuals:
1 2 3 4 5 6 7
-0.007628 0.001627 0.189574 -0.418157 0.170181 0.193449 -0.129045
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 30.061 4.285 7.016 0.00595 **
segments -26.547 4.156 -6.388 0.00777 **
log(segments) 14.067 1.957 7.189 0.00555 **
segments:log(segments) 10.384 1.852 5.606 0.01121 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.313 on 3 degrees of freedom
Multiple R-squared: 0.9782, Adjusted R-squared: 0.9564
F-statistic: 44.86 on 3 and 3 DF, p-value: 0.005431
[1] "The fitted boundary line summary!"
[1] "Logarithmic model y=a+bx+clog(x)+dxlog(x) was the best!"
Call:
lm(formula = tops ~ segments + log(segments) + segments:log(segments),
data = boundaries)
Residuals:
1 2 3 4 5 6 7
-0.007628 0.001627 0.189574 -0.418157 0.170181 0.193449 -0.129045
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 30.061 4.285 7.016 0.00595 **
segments -26.547 4.156 -6.388 0.00777 **
log(segments) 14.067 1.957 7.189 0.00555 **
segments:log(segments) 10.384 1.852 5.606 0.01121 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.313 on 3 degrees of freedom
Multiple R-squared: 0.9782, Adjusted R-squared: 0.9564
F-statistic: 44.86 on 3 and 3 DF, p-value: 0.005431
[1] "Total number of releases >= 0.2 & < 0.5 is 16"
inyears
1896 1927 1935 1936 1938 1941 1942 1978 1991 1993
1 1 4 3 1 1 1 2 1 1
[1] "Total number of releases >= 0.5 is 9"
inyears
1896 1935 1936 1942 1947 1978
1 3 1 1 1 2
Species Number.of.tree.rings
1 Abies alba 132 544
2 Abies alba 33 549
3 Betula alleghaniensis 4 491
4 Fagus sylvatica 94 649
5 Fagus sylvatica 53 324
6 Fagus sylvatica 80 539
7 Fagus sylvatica 19 833
8 Fagus sylvatica 20 670
9 Larix decidua 3 830
10 Picea abies 147 949
11 Picea abies 8 194
12 Picea abies unknown
13 Picea abies unknown
14 Picea glauca 102 306
15 Picea mariana 49 007
16 Pinus echinata 74 925
17 Pinus palustris 32 970
18 Pinus ponderosa 157 243
19 Pinus strobus 72 714
20 Pseudotsuga menziesii 172 372
21 Quercus alba 164 867
22 Quercus macrocarpa 92 092
23 Quercus mongolica 30 377
24 Quercus petraea 45 755
25 Quercus prinus 35 337
26 Quercus stellata 169 333
27 Tsuga canadensis 180 708
Boundary.line.equation
1 y = 131.8 + 1012.6exp(-1.603x) - 16.8078x
2 y = 266.138 + 2827.365exp(-3.259x) - 44.963x
3 y = 1257.7exp(-1.16x)
4 y = 2801.0799exp(-5.4058x) + 488.6093exp(-0.7466x)
5 y = 10.089exp(-1.289x) + 1.959exp(-0.336x)
6 y = 18.040exp(-4.112x) + 4.797exp(-0.454x)
7 y = 45.9429 + exp(7.58466-2.4772x)
8 y = 2242.78exp(-5.06x) + 418.24exp(-0.88x)
9 Y = 204.78 - 153.16ln(x)
10 y = 130.8732 + 1399.4031exp(-2.4804x) - 17.2694x
11 Y = 338.83 - 257.15ln(x)
12 x = 530.69exp(-1.4626y)
13 x = 308.49exp(-0.7713y)
14 y = 649.97exp(-1.0798x)
15 y = 407.92exp(-1.4679x)
16 y = 998.65exp(-1.0237x)
17 y = 1728.5exp(-0.9735x)
18 y = 655.97exp(-0.9354x)
19 y = 501.96exp(-0.664x0
20 y = 569.80exp(-0.928x)
21 y = 527.22exp(-0.787x)
22 y = 511.27exp(-0.7018x)
23 y = 195.73-153.9ln(x)
24 y = 5.0067exp(-0.664x)
25 y = 742.83exp(-0.9445x)
26 y = 948.45exp(-1.6188x)
27 y = 974.54exp(-1.1202x)
Source
1 (Splechtna, Gratzer & Black 2005)
2 (Nagel, Levanic & Diaci 2007)
3 (Webster & Jensen 2007)
4 (Splechtna, Gratzer & Black 2005)
5 (Ziaco et al. 2012)
6 (Ziaco et al. 2012)
7 (Samonil et al. 2009)
8 (Trotsiuk, Hobi & Commarmot 2012)
9 (Zielonka et al. 2010)
10 (Splechtna, Gratzer & Black 2005)
11 (Zielonka et al. 2010)
12 (Szewczyk, Szwagrzyk & Muter 2011)
13 (Szewczyk, Szwagrzyk & Muter 2011)
14 (Black et al. 2009)
15 (Black et al. 2009)
16 (Black et al. 2004)
17 (Bhuta et al. 2008)
18 (Black et al. 2004)
19 (Black & Abrams 2003)
20 (Black et al. 2009)
21 (Black et al. 2004)
22 (Black et al. 2004)
23 (Altman et al. 2013a)
24 (Altman et al. 2013b)
25 (Black & Abrams 2003)
26 (Black et al. 2009)
27 (Black & Abrams 2003)
TRADER documentation built on May 2, 2019, 9:02 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Details Author(s) References See Also Examples
Description
The TRADER package provides only one way for disturbance reconstruction from tree-ring data. TRADER is a unique package bringing the first instrument for analysis of forest disturbance history in complementary ways. Final advantage of TRADER is the possibility of results comparison between individual studies. This is enabled by easy parameter changes in data processing, as well as by clearly arranged graphical and tabular outputs. We developed TRADER in open source R environment, to further support the on-going open-source software development for dendrochronological methods and data availability.
Details
| Package: | TRADER |
| Type: | Package |
| Version: | 1.2-3 |
| Date: | 2017-01-13 |
| License: | GPL-2 | GPL-3 |
library(TRADER)
Author(s)
Pavel Fibich <pavel.fibich@prf.jcu.cz>, Jan Altman <altman.jan@gmail.com>, Tuomas Aakala <tuomas.aakala@helsinki.fi>, Jiri Dolezal <jiriddolezal@gmail.com>
Maintainer: Pavel Fibich <pavel.fibich@prf.jcu.cz>
References
Nowacki, G.J. & Abrams, M.D. 1997. Radial-growth averaging criteria for reconstructing disturbance histories from presettlement-origin oaks. Ecological Monographs, 67, 225-249.
Black, B.A. & Abrams, M.D. 2003. Use of boundary-line growth patterns as a basis for dendroecological release criteria. Ecological Applications, 13, 1733-1749.
Fraver, S. & White, A.S. 2005. Identifying growth releases in dendrochronological studies of forest disturbance. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere, 35, 1648-1656.
Splechtna, B.E., Gratzer, G. & Black, B.A. 2005. Disturbance history of a European old-growth mixed-species forest - A spatial dendro-ecological analysis. Journal of Vegetation Science, 16, 511-522.
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | data(relData)
plotFirstYears(relData1)
plotGrowth(relData1)
absoluteIncreaseALL(relData1,length=3,buffer=4,storedev=jpeg)
growthAveragingALL(relData1,length=3,buffer=4,storedev=pdf)
boundaryLineALL(relData1,length=2,buffer=2,storedev=pdf,
boundary=function(x) {5.0067*exp(-0.664*x)} )
splechtnaALL(relData1,length=3,buffer=4,storedev=pdf,
boundary=function(x) {5.0067*exp(-0.664*x)} )
doAll(relData1,length=3,buffer=4,storedev=pdf)
knownBL
|
Example output
png
2
[1] "## Fraver & White analysis!"
[1] "Absolute threshold 1.2 m1 10 m2 10 Buffer 4 Length 3"
[1] "Total number of releases is 16"
inyears
1895 1896 1904 1935 1936 1938 1939 1944 1978
1 3 1 4 1 2 1 1 2
[1] "## Nowacki & Abrams analysis!"
[1] "Criteria 0.25 Criteria2 0.5 m1 10 m2 10 Buffer 4 Length 3"
[1] "Total number of releases >= 0.25 & < 0.5 is 6"
inyears
1888 1920 1935 1936 1978 1980
1 1 1 1 1 1
[1] "Total number of releases >= 0.5 is 22"
inyears
1895 1896 1903 1927 1935 1936 1938 1942 1947 1978 1986 1993
1 3 1 1 4 4 2 1 1 2 1 1
[1] "## Black & Abrams analysis!"
[1] "Criteria 0.2 Criteria2 0.5 m1 10 m2 10 Buffer 2 Length 2 Segment 0.5 Segment2 0.5"
[1] "Total number of releases >= 0.2 & < 0.5 is 14"
inyears
1888 1899 1935 1936 1938 1940 1947 1978 1980 1984 1986
1 1 1 2 3 1 1 1 1 1 1
[1] "Total number of releases >= 0.5 is 25"
inyears
1893 1894 1895 1896 1899 1903 1907 1935 1936 1938 1939 1940 1941 1942 1978
1 1 1 3 1 1 1 6 2 2 1 1 1 1 2
[1] "## Splechtna analysis!"
[1] "Criteria 0.2 Criteria2 0.5 m1 10 m2 10 Buffer 4 Length 3 Segment 0.5 Segment2 0.5"
[1] "Total number of releases >= 0.2 & < 0.5 is 16"
inyears
1896 1927 1935 1936 1938 1942 1947 1978 1986 1993
1 1 4 3 1 1 1 2 1 1
[1] "Total number of releases >= 0.5 is 9"
inyears
1896 1935 1936 1942 1978
1 3 2 1 2
[1] "## Fraver & White analysis!"
[1] "Absolute threshold 1.2 m1 10 m2 10 Buffer 4 Length 3"
[1] "Total number of releases is 16"
inyears
1895 1896 1904 1935 1936 1938 1939 1944 1978
1 3 1 4 1 2 1 1 2
[1] "## Nowacki & Abrams analysis!"
[1] "Criteria 0.25 Criteria2 0.5 m1 10 m2 10 Buffer 4 Length 3"
[1] "Total number of releases >= 0.25 & < 0.5 is 6"
inyears
1888 1920 1935 1936 1978 1980
1 1 1 1 1 1
[1] "Total number of releases >= 0.5 is 22"
inyears
1895 1896 1903 1927 1935 1936 1938 1942 1947 1978 1986 1993
1 3 1 1 4 4 2 1 1 2 1 1
[1] "## Black & Abrams analysis!"
[1] "Criteria 0.2 Criteria2 0.5 m1 10 m2 10 Buffer 4 Length 3 Segment 0.5 Segment2 0.5"
[1] "--Summary of y=a+bx fit."
Call:
lm(formula = tops ~ segments, data = boundaries)
Residuals:
1 2 3 4 5 6 7
-2.1637 1.7473 1.3473 -0.1650 -0.1749 -0.2988 -0.2922
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.6631 1.0656 2.499 0.0545 .
segments -0.7266 0.5287 -1.374 0.2277
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.399 on 5 degrees of freedom
Multiple R-squared: 0.2742, Adjusted R-squared: 0.129
F-statistic: 1.889 on 1 and 5 DF, p-value: 0.2277
[1] "--Summary of y=a+bx+cx^2 fit."
Call:
lm(formula = tops ~ segments + I(segments^2), data = boundaries)
Residuals:
1 2 3 4 5 6 7
-1.2627 1.7473 0.8067 -0.8858 -0.7155 -0.2988 0.6088
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.1766 1.5661 0.751 0.494
segments 1.7961 2.0898 0.859 0.439
I(segments^2) -0.7208 0.5796 -1.244 0.282
Residual standard error: 1.328 on 4 degrees of freedom
Multiple R-squared: 0.4765, Adjusted R-squared: 0.2148
F-statistic: 1.821 on 2 and 4 DF, p-value: 0.274
[1] "--Summary of y=ae^bx fit."
Formula: tops ~ a * exp(b * segments)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 2.4721 1.4860 1.664 0.157
b -0.3441 0.4231 -0.813 0.453
Residual standard error: 1.48 on 5 degrees of freedom
Number of iterations to convergence: 19
Achieved convergence tolerance: 7.85e-06
[1] "y=c+ae^bx nls error: step factor 0.000488281 reduced below 'minFactor' of 0.000976562"
[1] "y=c+dx+ae^bx nls error: singular gradient"
[1] "y=ae^bx+ce^dx nls error: Missing value or an infinity produced when evaluating the model"
[1] "--Summary of y=a+blog(x) fit."
Formula: tops ~ a + b * log(segments)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 1.5195 0.6389 2.378 0.0633 .
b -0.4241 0.7248 -0.585 0.5839
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.588 on 5 degrees of freedom
Number of iterations to convergence: 1
Achieved convergence tolerance: 8.688e-09
[1] "--Summary of y=a+bx+clog(x)+dxlog(x) fit."
Call:
lm(formula = tops ~ segments + log(segments) + segments:log(segments),
data = boundaries)
Residuals:
1 2 3 4 5 6 7
-0.007628 0.001627 0.189574 -0.418157 0.170181 0.193449 -0.129045
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 30.061 4.285 7.016 0.00595 **
segments -26.547 4.156 -6.388 0.00777 **
log(segments) 14.067 1.957 7.189 0.00555 **
segments:log(segments) 10.384 1.852 5.606 0.01121 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.313 on 3 degrees of freedom
Multiple R-squared: 0.9782, Adjusted R-squared: 0.9564
F-statistic: 44.86 on 3 and 3 DF, p-value: 0.005431
[1] "The fitted boundary line summary!"
[1] "Logarithmic model y=a+bx+clog(x)+dxlog(x) was the best!"
Call:
lm(formula = tops ~ segments + log(segments) + segments:log(segments),
data = boundaries)
Residuals:
1 2 3 4 5 6 7
-0.007628 0.001627 0.189574 -0.418157 0.170181 0.193449 -0.129045
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 30.061 4.285 7.016 0.00595 **
segments -26.547 4.156 -6.388 0.00777 **
log(segments) 14.067 1.957 7.189 0.00555 **
segments:log(segments) 10.384 1.852 5.606 0.01121 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.313 on 3 degrees of freedom
Multiple R-squared: 0.9782, Adjusted R-squared: 0.9564
F-statistic: 44.86 on 3 and 3 DF, p-value: 0.005431
[1] "Total number of releases >= 0.2 & < 0.5 is 13"
inyears
1888 1897 1899 1934 1935 1938 1944 1947 1967
1 1 2 1 3 2 1 1 1
[1] "Total number of releases >= 0.5 is 23"
inyears
1893 1896 1899 1903 1910 1935 1938 1939 1940 1941 1942 1943 1944 1978 1982
2 2 1 2 1 4 1 2 1 1 1 1 1 2 1
[1] "## Splechtna analysis!"
[1] "Criteria 0.2 Criteria2 0.5 m1 10 m2 10 Buffer 4 Length 3 Segment 0.5 Segment2 0.5"
[1] "--Summary of y=a+bx fit."
Call:
lm(formula = tops ~ segments, data = boundaries)
Residuals:
1 2 3 4 5 6 7
-2.1637 1.7473 1.3473 -0.1650 -0.1749 -0.2988 -0.2922
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.6631 1.0656 2.499 0.0545 .
segments -0.7266 0.5287 -1.374 0.2277
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.399 on 5 degrees of freedom
Multiple R-squared: 0.2742, Adjusted R-squared: 0.129
F-statistic: 1.889 on 1 and 5 DF, p-value: 0.2277
[1] "--Summary of y=a+bx+cx^2 fit."
Call:
lm(formula = tops ~ segments + I(segments^2), data = boundaries)
Residuals:
1 2 3 4 5 6 7
-1.2627 1.7473 0.8067 -0.8858 -0.7155 -0.2988 0.6088
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.1766 1.5661 0.751 0.494
segments 1.7961 2.0898 0.859 0.439
I(segments^2) -0.7208 0.5796 -1.244 0.282
Residual standard error: 1.328 on 4 degrees of freedom
Multiple R-squared: 0.4765, Adjusted R-squared: 0.2148
F-statistic: 1.821 on 2 and 4 DF, p-value: 0.274
[1] "--Summary of y=ae^bx fit."
Formula: tops ~ a * exp(b * segments)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 2.4721 1.4860 1.664 0.157
b -0.3441 0.4231 -0.813 0.453
Residual standard error: 1.48 on 5 degrees of freedom
Number of iterations to convergence: 19
Achieved convergence tolerance: 7.85e-06
[1] "y=c+ae^bx nls error: step factor 0.000488281 reduced below 'minFactor' of 0.000976562"
[1] "y=c+dx+ae^bx nls error: singular gradient"
[1] "y=ae^bx+ce^dx nls error: Missing value or an infinity produced when evaluating the model"
[1] "--Summary of y=a+blog(x) fit."
Formula: tops ~ a + b * log(segments)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 1.5195 0.6389 2.378 0.0633 .
b -0.4241 0.7248 -0.585 0.5839
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.588 on 5 degrees of freedom
Number of iterations to convergence: 1
Achieved convergence tolerance: 8.688e-09
[1] "--Summary of y=a+bx+clog(x)+dxlog(x) fit."
Call:
lm(formula = tops ~ segments + log(segments) + segments:log(segments),
data = boundaries)
Residuals:
1 2 3 4 5 6 7
-0.007628 0.001627 0.189574 -0.418157 0.170181 0.193449 -0.129045
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 30.061 4.285 7.016 0.00595 **
segments -26.547 4.156 -6.388 0.00777 **
log(segments) 14.067 1.957 7.189 0.00555 **
segments:log(segments) 10.384 1.852 5.606 0.01121 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.313 on 3 degrees of freedom
Multiple R-squared: 0.9782, Adjusted R-squared: 0.9564
F-statistic: 44.86 on 3 and 3 DF, p-value: 0.005431
[1] "The fitted boundary line summary!"
[1] "Logarithmic model y=a+bx+clog(x)+dxlog(x) was the best!"
Call:
lm(formula = tops ~ segments + log(segments) + segments:log(segments),
data = boundaries)
Residuals:
1 2 3 4 5 6 7
-0.007628 0.001627 0.189574 -0.418157 0.170181 0.193449 -0.129045
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 30.061 4.285 7.016 0.00595 **
segments -26.547 4.156 -6.388 0.00777 **
log(segments) 14.067 1.957 7.189 0.00555 **
segments:log(segments) 10.384 1.852 5.606 0.01121 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.313 on 3 degrees of freedom
Multiple R-squared: 0.9782, Adjusted R-squared: 0.9564
F-statistic: 44.86 on 3 and 3 DF, p-value: 0.005431
[1] "Total number of releases >= 0.2 & < 0.5 is 16"
inyears
1896 1927 1935 1936 1938 1941 1942 1978 1991 1993
1 1 4 3 1 1 1 2 1 1
[1] "Total number of releases >= 0.5 is 9"
inyears
1896 1935 1936 1942 1947 1978
1 3 1 1 1 2
Species Number.of.tree.rings
1 Abies alba 132 544
2 Abies alba 33 549
3 Betula alleghaniensis 4 491
4 Fagus sylvatica 94 649
5 Fagus sylvatica 53 324
6 Fagus sylvatica 80 539
7 Fagus sylvatica 19 833
8 Fagus sylvatica 20 670
9 Larix decidua 3 830
10 Picea abies 147 949
11 Picea abies 8 194
12 Picea abies unknown
13 Picea abies unknown
14 Picea glauca 102 306
15 Picea mariana 49 007
16 Pinus echinata 74 925
17 Pinus palustris 32 970
18 Pinus ponderosa 157 243
19 Pinus strobus 72 714
20 Pseudotsuga menziesii 172 372
21 Quercus alba 164 867
22 Quercus macrocarpa 92 092
23 Quercus mongolica 30 377
24 Quercus petraea 45 755
25 Quercus prinus 35 337
26 Quercus stellata 169 333
27 Tsuga canadensis 180 708
Boundary.line.equation
1 y = 131.8 + 1012.6exp(-1.603x) - 16.8078x
2 y = 266.138 + 2827.365exp(-3.259x) - 44.963x
3 y = 1257.7exp(-1.16x)
4 y = 2801.0799exp(-5.4058x) + 488.6093exp(-0.7466x)
5 y = 10.089exp(-1.289x) + 1.959exp(-0.336x)
6 y = 18.040exp(-4.112x) + 4.797exp(-0.454x)
7 y = 45.9429 + exp(7.58466-2.4772x)
8 y = 2242.78exp(-5.06x) + 418.24exp(-0.88x)
9 Y = 204.78 - 153.16ln(x)
10 y = 130.8732 + 1399.4031exp(-2.4804x) - 17.2694x
11 Y = 338.83 - 257.15ln(x)
12 x = 530.69exp(-1.4626y)
13 x = 308.49exp(-0.7713y)
14 y = 649.97exp(-1.0798x)
15 y = 407.92exp(-1.4679x)
16 y = 998.65exp(-1.0237x)
17 y = 1728.5exp(-0.9735x)
18 y = 655.97exp(-0.9354x)
19 y = 501.96exp(-0.664x0
20 y = 569.80exp(-0.928x)
21 y = 527.22exp(-0.787x)
22 y = 511.27exp(-0.7018x)
23 y = 195.73-153.9ln(x)
24 y = 5.0067exp(-0.664x)
25 y = 742.83exp(-0.9445x)
26 y = 948.45exp(-1.6188x)
27 y = 974.54exp(-1.1202x)
Source
1 (Splechtna, Gratzer & Black 2005)
2 (Nagel, Levanic & Diaci 2007)
3 (Webster & Jensen 2007)
4 (Splechtna, Gratzer & Black 2005)
5 (Ziaco et al. 2012)
6 (Ziaco et al. 2012)
7 (Samonil et al. 2009)
8 (Trotsiuk, Hobi & Commarmot 2012)
9 (Zielonka et al. 2010)
10 (Splechtna, Gratzer & Black 2005)
11 (Zielonka et al. 2010)
12 (Szewczyk, Szwagrzyk & Muter 2011)
13 (Szewczyk, Szwagrzyk & Muter 2011)
14 (Black et al. 2009)
15 (Black et al. 2009)
16 (Black et al. 2004)
17 (Bhuta et al. 2008)
18 (Black et al. 2004)
19 (Black & Abrams 2003)
20 (Black et al. 2009)
21 (Black et al. 2004)
22 (Black et al. 2004)
23 (Altman et al. 2013a)
24 (Altman et al. 2013b)
25 (Black & Abrams 2003)
26 (Black et al. 2009)
27 (Black & Abrams 2003)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.