Increased deadwood carbon stocks through planted forestry practices: insights from a Forest Inventory Survey in Japan

Figures & data

Figure 1. Distribution of survey sites (solid circles) in Japan. Green indicates forested areas determined by JAXA (Japan Aerospace Exploration Agency)'s ALOS (Advanced Land Observing Satellite).

Figure 2. Design of a sampling plot.

Table 1. Survey methods by deadwood composition.

	Method	Definition	Size measurement
Fallen logs	Line-intersect	Diameter > 5 cm length	Diameter on line
		Excluding roots > 1.5 m
Stumps	Belt transect	Diameter > 5 cm length	Diameter
		Excluding roots ≤ 1.5 m	Diameter above ground level
			Height above ground level (top)
			Height below ground level (bottom)
Snags	Belt transect	Diameter > 5 cm	Diameter at breast height
		Height above ground level > 1.5 m	Height

Table 2. Wood density in each decay class of deadwood.

Decay class	Wood density (g cm^−3)
	Conifer^b	Broadleaved^b	Unidentified^b^,c	Bamboo^d
0	0.347	0.495	0.421	0.22
1	0.347	0.495	0.421	0.21
2	0.278	0.399	0.339	0.16
3	0.206	0.303	0.255
4	0.148	0.207	0.178
5	0.112	0.112	0.112

^a These values were determined from data from [45] and [6].

^b Appearance of dead wood: 0, No decay, branches, twigs, and leaves remain; 1, Slightly decayed, only cambium decayed, branches and twigs remain; 2, Most bark and branches present, some parts of wood are softened by decay; 3, Moderately decayed, all parts of dead wood are softened by decay, Some bark is gone in conifer species, moss has sometimes adhered; 4, Some parts of wood are gone, initial form is recognizable, brown rot is observed in conifer species; 5, Wood collapsed, ≥50% of wood is gone, some parts of wood are buried in soil, some bark remains in broadleaved species.

^c If the species of the dead wood could not be determined as conifer or broadleaved, it was classified as “Unidentified.”

^d Decay classes of bamboo – Three levels from 0 to 2, based on the appearance of dead culm: 0, Culm separated from ground surface; 1, Culm in contact with ground surface, culm is still hard; 2, Culm is soft, culm is destroyed easily by stepping on it.

Table 3. List of explanatory variables, databases and data.

Variable	Details	Database	Data
MAT	Mean annual temperature (°C)	Mesh^a	Continuous^c
DEM	Digital elevation model (m)	Mesh	Continuous^c
Precipitation	Mean annual precipitation (mm)	Mesh	Continuous^c
Volume	Plot total forest volume (m^3/ha)	Diversity^b	Continuous^c
Preferred tree species	Principal tree species in terms of percentage of volume (conifers (0)/broad (1)/bamboo and others (1))	Diversity	Qualitative^d
Forest age	Forest age on forest register	Diversity	Continuous^c
Ownership classification	National forest (0)/private forest (1)	Diversity	Qualitative^d
Forest type	Natural forest (0)/planted forest (1)/other (1)	Diversity	Qualitative^d
Forestry operation	Existence (1)/non-existence (0)	Diversity	Qualitative^d

^a Mesh Climate Data of Japan 2010 (Statistical period 1981–2010).

^b Forest Ecosystem Diversity Basic Survey – 2nd (2004–2008).

 Forest Ecosystem Diversity Basic Survey – 3rd (2009–2013).

^c Continuous variables were standardized.

^d Qualitative variables were converted to dummy variables by assigning reference categories. The reference category was set to 0 and the dummy variable to 1.

Table 4. All (planted, natural, and other), planted, and natural forest deadwood carbon stocks in Japan, and their respective carbon stocks by composition (t-C/ha).

	Mean ± SD	Median	Range	Number of plots
All (Planted, natural and other) forest
Dead wood	7.50 ± 9.74	4.17	0– 97.30	2255
Fallen logs	3.26 ± 4.43	1.75	0– 47.88	2254
Stumps	2.45 ± 5.69	0.15	0– 86.66	2252
Snags	1.80 ± 5.27	0.00	0– 67.39	2252
Planted forest
Dead wood	9.00 ± 10.43	5.36	0– 97.30	1075
Fallen logs	3.73 ± 4.80	2.09	0– 47.88	1075
Stumps	3.89 ± 7.28	1.12	0– 86.66	1075
Snags	1.37 ± 3.89	0.00	0– 53.22	1075
Natural forest
Dead wood	6.21 ± 8.93	3.17	0– 94.62	1087
Fallen logs	2.90 ± 4.09	1.50	0– 43.86	1087
Stumps	1.12 ± 3.13	0.00	0– 27.35	1085
Snags	2.20 ± 6.30	0.00	0– 67.39	1085

SD: standard deviation.

Figure 3. Deadwood carbon stocks in six global regions. Deadwood carbon stocks in Japan and worldwide [1].

Figure 4. Distribution of fallen logs, stumps, and snags by forest management in various countries.

Tree species: Japan: this study. Finland: European red pine or Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.). USA: western hemlock (Tsuga heterophylla (Raf.) Sarg.) or grand fir (Abies grandis (Dougl. ex D. Don) Lindl.). Spain: French bay gooseberry (Pinus pinaster Ait.). Sweden: European oak (Quercus robur), Norway spruce (Picea abies (L.) Karst.), birch (Betula pendula Roth, Betula pubescens Ehrhs), poplar (Populus tremula L.).

Figure A1. Correlation coefficients for each pair of the nine explanatory and objective variables.

Variable names are displayed on the diagonal line from the upper left to the lower right of the matrix. The upper right of the matrix graph shows the correlation coefficients, the lower left a scatter plot, and the center a histogram and probability density.

Table A1. Selection of explanatory variables using the VIF function.

Variable	GVIF^a	Df^b	GVIF ^ (1/(2*Df ))
Ownership classification	1.47	1	1.21
Forest age	1.63	1	1.28
MAT	2.53	1	1.59
DEM	1.50	1	1.23
Precipitation	1.73	1	1.32
Forest type	1.86	2	1.17
Dominant tree species	1.69	2	1.14
Volume	1.40	1	1.18
Forestry operation	1.03	1	1.01

^a GVIF: Generalized VIF 

^b Df : Degree of freedom

Table A2. Environmental factors affecting carbon stocks in deadwood.

Variables	Estimate	Std.Error	t value	Pr(>ltI)
(Intercept)	−0.143	0.028	−5.174	<0.001	***
Ownership classification, Private	−0.061	0.022	−2.766	0.006	**
MAT_s	0.016	0.021	0.751	0.452
Forest type, Other	0.013	0.055	0.242	0.809
Forest type, Planted	0.009	0.023	0.376	0.707
Dominant tree species, Broad	−0.189	0.021	−8.869	<0.001	***
Dominant tree species, Others	0.103	0.075	1.368	0.171
Forestry operation, Yes	0.141	0.035	4.019	<0.001	***
Age_slog	−0.026	0.019	−1.370	0.171
DEM_slog	0.075	0.021	3.634	<0.001	***
Precipitation_slog	−0.011	0.012	−0.979	0.328
Volume_slog	0.066	0.010	6.624	<0.001	***
Ownership classificationPrivate:Age	0.029	0.019	1.547	0.122
Ownership classificationPrivate:DEM	−0.038	0.023	−1.674	0.094	.
MAT: Forest typeOther	−0.007	0.048	−0.135	0.892
MAT_s:Forest typePlanted	0.049	0.021	2.269	0.023	*
MAT_s:Dominant tree speciesBroad	0.043	0.020	2.125	0.034	*
MAT_s:Dominant tree speciesOther	−0.007	0.061	−0.115	0.908
MAT_s:Forestry operationYes	−0.079	0.056	−1.407	0.159
MAT_s:DEM_slog	0.030	0.009	3.354	<0.001	***
MAT_s:Precipitation_slog	−0.026	0.009	−2.751	0.006	**
MAT_s:Volume_slog	−0.051	0.012	−4.200	<0.001	***
Dominant tree speciesBroad:Age_slog	0.041	0.019	2.157	0.031	*
Dominant tree speciesOther:Age_slog	−0.073	0.055	−1.347	0.178
Forestry operationYes:DEM_slog	−0.063	0.041	−1.524	0.128
Forestry operationYes:Precipitation_slog	0.070	0.047	1.502	0.133
Age_slog:DEM_slog	0.017	0.010	1.771	0.077	.
Age_slog:Precipitation_slog	−0.028	0.010	−2.744	0.006	**
DEM_slog:Volume_slog	−0.032	0.010	−3.203	0.001	**
Precipitation_slog:Volume_slog	0.017	0.011	1.491	0.136

Significance codes: ***p < .001; **p < .01; *p < .05.

・s: Standardization.

・slog: After logarithmic transformations, the data were standardized.

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Data availability statement

Data are not available – access to data is restricted because the data is under government jurisdiction and control.