Selection from the list of topics

What do the numbers stand for?
What is the purpose of the standard error?
When are two results statistically different?
When is it not sufficient to consider only the standard error?
Two types of changes?
Change analyses: When are the results (not) additive?
Why is a dot (“.”) sometimes given in the cells for standard error or estimated value?
Why are no standard error values shown in some tables?
Negative values for growing stock, increment or fellings?

1. What do the numbers stand for?

The tables mainly show results that were calculated using statistical methods from the data of the sample inventory of the National Forest Inventory (NFI). Such results always consist of two figures: (1) the estimated value and (2) the sampling error, the so-called standard error.

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

state 2018/26
	production region
	Jura		Plateau		Pre-Alps		Alps		Southern Alps		Switzerland
ownership (2 categories)	m³/ha	±%	m³/ha	±%	m³/ha	±%	m³/ha	±%	m³/ha	±%	m³/ha	±%
public	30	10	17	13	37	9	36	6	26	10	30	4
private	27	17	20	12	50	10	32	8	39	13	34	5
total	29estimated value	9standard error	19	9	44	7	35	5	29	8	32	3

The tables usually show the relative (percentage) standard error (“±%”), but occasionally – in the case of estimated percentages – the absolute standard error (“±”).

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2. What is the purpose of the standard error?

The standard error can be used to define confidence intervals around the estimated value, which contain the true value of the population with a certain statistical certainty.

The statistical certainty is:

68% if the confidence interval is calculated using the standard error
(68% confidence interval = estimated value ± standard error), and
95% if the confidence interval is calculated using twice the standard error
(95% confidence interval = estimated value ± 2 × standard error*)

Example 2: Calculating confidence intervals

LFI5
volume of deadwood (stemwood)
ownership (2 categories)
regional demarcation: production region
unit: m³/ha
evaluation area: accessible forest without shrub forest
grid: 1.4 km grid, subgrids 1-5
state 2018/26
	production region
	Jura
ownership (2 classes)	m³/ha	±%
public	30	10
private	27	17
total	29	9

Question
What are the 68% and 95% confidence intervals of the above estimates?

Procedure

Calculate the absolute standard error (= relative standard error × estimated value / 100)
Calculate the confidence intervals
- 68% confidence interval = estimated value ± absolute standard error
- 95% confidence interval = estimated value ± 2 × absolute standard error

Answer

			Step 1	Step 2

ownership (2 categories)	volume of deadwood Jura NFI5
	estimated value	standard error		confidence interval
		relative	absolute	68%	95%
	m³/ha	±%	±m³/ha	m³/ha	m³/ha
public	30	10	3	27-33	24-36
private	27	17	5	22-32	17-37
total	29	9	3	26-32calculated with the standard error, i.e. 29 ± 3	23-25calculated with twice the standard error, i.e. 29 ± 2 × 3

The volume of deadwood in the Jura is between 26 and 32 m³/ha with a statistical certainty of 68% and between 23 and 35 m³/ha with a statistical certainty of 95%.

The 95% confidence interval is larger than the 68% confidence interval. This results in higher statistical certainty with the 95% confidence interval.

Example 3: Visualisation of the 68% and 95% confidence intervals

Data: see example 2

When interpreting the results, one must define the level of statistical certainty that one would like to apply to the statement.

The 68% confidence interval is generally used in the National Forest Inventory (NFI).

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3. When are two results statistically different?*

This can be checked by comparing the confidence intervals of two estimated values:

If the 68% confidence intervals of two estimates do not overlap, it can be assumed with some certainty that the two populations differ.
If the 95% confidence intervals of two estimates do not overlap, it can be assumed with high certainty that the two populations differ.

Example 4: Interpretation of two results from the same inventory

NFI5
growing stock (stemwood)
ownership (2 categories)
regional demarcation: production region
unit: m³/ha
evaluation area: accessible forest without shrub forest
grid: 1.4 km grid, subgrids 1-5
state 2018/26
	production region
	Jura		Plateau		Pre-Alps		Alps		Southern Alps		Switzerland
ownership (2 categories)	m³/ha	±%	m³/ha	±%	m³/ha	±%	m³/ha	±%	m³/ha	±%	m³/ha	±%
public	331	3	311	3	405	4	300	3	256	5	314	2
private	387	5	432	4	454	4	348	4	285	6	398	2
total	345	2	363	2	431	2	314	2	262	4	343	1

	case 2						case 1

case 1

Question
Is the growing stock per hectare greater in the Alps than in the Southern Alps?

Procedure

Calculate the absolute standard errors
Calculate the confidence intervals depending on the desired level of statistical certainty:
- 68% confidence intervals (some certainty; absolute standard error)
- 95% confidence intervals (high certainty; twice the absolute standard error)
Assess whether the confidence intervals corresponding to the desired level of statistical certainty do not overlap

Answer

ownership (2 categories)	growing stock NFI5
	Alps					Southern Alps
	estimated value	standard error		confidence interval		estimated value	standard error		confidence interval
		relative	absolute	68%	95%		relative	absolute	68%	95%
	m³/ha	±%	±m³/ha	m³/ha	m³/ha	m³/ha	±%	±m³/ha	m³/ha	m³/ha
total	314	2	6	308-320	302-326	262	4	10	252-272	242-282

Neither the 68%-confidence intervals nor the 95%-confidence intervals overlap (pairs of values in ).

In this case, the level of statistical certainty selected has no influence on the result.

Overall, this means that there is high statistical certainty that the growing stock per hectare is greater in the Alps than in the Southern Alps.

Case 2

Question
Is the growing stock per hectare greater in the Plateau than in the Jura?

Procedure

See case 1.

Answer

ownership (2 categories)	growing stock NFI5
	Jura					Plateau
	estimated value	standard error		confidence interval		estimated value	standard error		confidence interval
		relative	absolute	68%	95%		relative	absolute	68%	95%
	m³/ha	±%	±m³/ha	m³/ha	m³/ha	m³/ha	±%	±m³/ha	m³/ha	m³/ha
total	345	2	7	338-352	331-359	363	2	7	356-370	349-377

The 68%-confidence intervals do not overlap (pairs of values in ).
In contrast, the 95%-confidence intervals overlap (pairs of values in ).

In this case, the level of statistical certainty selected has an influence on the interpretation of the results. At the 68% confidence interval level, the conclusion is that the growing stock per hectare is higher in the Plateau than in the Jura. At the 95% confidence interval level, however, this conclusion cannot be drawn.

Considering both confidence interval levels, it can be said that there is some, but not high, statistical certainty that the growing stock per hectare is greater in the Plateau than in the Jura.

The confidence intervals can also be used to determine whether a value estimated with a sample from the National Forest Inventory (NFI) deviates from a target value (e.g. from Swiss forest policy) or whether a change between two inventories is statistically certain.

Example 5: Interpretation of two results from different inventories

ownership (2 categories)	growing stock Plateau*
	NFI4		NFI5
	m³/ha	±%	m³/ha	±%
public	340	3	309	3
private	447	4	432	4
total	386	2	363	2
* accessible forest without shrub forest NFI4/NFI5

Question
Has the growing stock per hectare in the Plateau decreased from NFI4 to NFI5?

Procedure

Calculate the absolute standard errors
Calculate the confidence intervals depending on the desired level of statistical certainty:
- 68% confidence intervals (some certainty; absolute standard error)
- 95% confidence intervals (high certainty; twice the absolute standard error)
Assess whether the confidence intervals corresponding to the desired level of statistical certainty do not overlap.

Answer

ownership (2 categories)	growing stock Plateau*
	NFI4					NFI5
	estimated value	standard error		confidence interval		estimated value	standard error		confidence interval
		relative	absolute	68%	95%		relative	absolute	68%	95%
	m³/ha	±%	±	m³/ha	m³/ha	m³/ha	±%	±	m³/ha	m³/ha
public	340	3	11	329-351	318-362	309	3	11	298-320	287-331
private	447	4	16	431-463	415-479	432	4	17	415-449	398-466
total	386	2	8	378-394	370-402	363	2	9	354-372	345-381
* accessible forest without shrub forest NFI4/NFI5

The 68%-confidence intervals do not overlap in the public forest (pairs of values in ), but they do in the private forest and the total forest (pairs of values in ). At the certainty level of the 68% confidence intervals, it can be concluded that the growing stock per hectare in the public forest of the Plateau has decreased. For the private forest, as well as for the total forest, the decrease is not statistically certain at this level.

The 95%-confidence intervals overlap in all three categories. At the certainty level of the 95% confidence intervals, it is therefore not certain that the growing stock has decreased, even for the public forest.

See also examples 6 and 7, in which changes between two inventories are interpreted using the more sensitive metric of net change.

For many target variables in the NFI, it is possible to determine whether a change between two inventories is statistically certain, not only by comparing the states in the two inventories (see example 5), but also by analysing the net change** between the two inventories.

To do this, one must first define the level of statistical certainty that one would like to apply to the statement (as done above):

A net change has occurred with some certainty if the relative standard error is less than 100% or if the confidence interval calculated with the absolute standard error (68% confidence interval) does not include the value 0.
A net change has occurred with high certainty if twice the relative standard error is less than 100% or if the confidence interval calculated with twice the absolute standard error (95% confidence interval) does not include the value 0.

Example 6: Interpretation of net changes with the relative standard error

ownership (2 categories)	change in growing stock from NFI4 to NFI5, Plateau*
	estimated value	standard error
	m³/ha	±%
public	-34	30
private	-9	147
total	-23	34
* accessible forest without shrub forest NFI4/NFI5

Question
Has the growing stock per hectare in the Plateau decreased from NFI4 to NFI5?

Procedure

Define the level of statistical certainty (68% or 95% confidence interval)
Determine whether:
- the relative standard error is less than 100% (certainty level of the 68% confidence interval)
- twice the relative standard error is less than 100% (certainty level of the 95% confidence interval)

Answer

ownership (2 categories)	change in growing stock from NFI4 to NFI5, Plateau*
	estimated value	standard error
		single	double
	m³/ha	±%	±%
public	-34	30	60
private	-9	147	294
total	-23	34	68
* accessible forest without shrub forest NFI4/NFI5

The single relative standard error is less than 100% for both the public forest and the total forest (highlighted values). For the private forest, however, it is greater than 100% (highlighted values). At the certainty level of the 68% confidence interval, it can be concluded that the growing stock in the Plateau has decreased in the public forest and in total. For the private forest, on the other hand, the decrease in stock is not statistically certain at this level.

The same conclusion is reached in this example with the certainty level of the 95% confidence interval, as twice the relative standard error is again less than 100% for both the public forest and the total forest.

Overall, this means that there is high statistical certainty that the growing stock per hectare has decreased in the public forest in the Plateau, as well as overall. For private forests, on the other hand, the decrease in stock is not statistically certain (as twice the relative standard error and the relative standard error are both less than 100%).

Example 7: Interpretation of net changes with the absolute standard error

ownership (2 categories)	change in growing stock from NFI4 to NFI5, Plateau*
	estimated value	standard error
	%	±
public	-10	3
private	-2	3
total	-6	2
* accessible forest without shrub forest NFI4/NFI5

Question
Has the growing stock per hectare in the Plateau decreased from NFI4 to NFI5?

Procedure

Define the level of statistical certainty (68% or 95% confidence interval)
Calculate the confidence interval based on the defined certainty level
- 68% confidence interval with the absolute standard error
- 95% confidence interval with twice the absolute standard error
Determine whether the corresponding confidence interval does not include the value 0

Answer

ownership (2 categories)	change in growing stock from NFI4 to NFI5, Plateau*
	estimated value	standard error		confidence interval
		single	double	68%	95%
	%	±	±	%	%
public	-10	3	6	-13 to -7	-16 to -4
private	-2	3	6	-5 to +1	-8 to +4
total	-6	2	4	-8 to -4	-10 to -2
* accessible forest without shrub forest NFI4/NFI5

Neither the 68% nor the 95% confidence interval includes the value 0 for the public forest or for the total forest. At both certainty levels, this leads to the conclusion that the growing stock in the Plateau has decreased in the public forest and in total. For the private forest, on the other hand, the decrease in stock is not statistically certain (as the confidence intervals include the value 0).

Net changes can be interpreted using the absolute or relative standard error (see examples 6 and 7). It is advisable to use the absolute standard error if the estimated value in the table is shown as a percentage (%; as in example 7), and the relative standard error if the estimated value in the table is shown in absolute terms (m³, m³/ha, pc, m²; as in example 6). This means that the standard error can be taken directly from the table and does not need to be converted.

To assess whether a change is statistically certain, it is advisable to analyse the net change between the two inventories wherever possible. Net changes are more sensitive than status comparisons, which makes it easier to detect differences statistically. See examples 6 and 7 (net change) and 7 (comparison of two results from different inventories).

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4. When is it not sufficient to consider only the standard error?

The National Forest Inventory (NFI) is a sample-based large-scale inventory whose sample areas are arranged on a grid with a mesh size of 1.4 km × 1.4 km. The NFI was designed in such a way that the growing stock for Switzerland as a whole can be predicted with a maximum standard error of 1%.

If results are requested for individual regions or for individual classes, the standard error quickly becomes much larger. This is because the number of sample areas and subjects (e.g. sample trees, young forest plants, pieces of deadwood) analysed for the queried combination of variable expressions* is considerably lower than for the total.

Example 8: Standard error and combination of variable expressions

region	growing stock
	total		maple		sycamore		Norway maple
	estimated value	standard error	estimated value	standard error	estimated value	standard error	estimated value	standard error
	m³/ha	±%	m³/ha	±%	m³/ha	±%	m³/ha	±%
Switzerland	343	1	12	5	11	5	1	20
production region "Plateau"	363	2	15	10	14	11	0	50
Canton of Aargau	289	7	15	20	13	20	1	63

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

forest districts are selected as the regional demarcation or results for small cantons (e.g. Appenzell Innerrhoden, Nidwalden) are queried,
a classification variable with many classes is selected (e.g. tree species in 56 classes),
several classification variables are combined with each other (e.g. main tree species and development stage).

Large standard errors are an indication that the estimate may have been based on too small a number of sample areas or subjects and that the result of the estimate therefore may not be reliable.

For the target variable “number of stems of young forest plants with browsing damage” (browsing intensity), an uncertain estimate is not necessarily recognisable by a large standard error. This is because this target variable is a quotient estimator**, which is – due to the survey method – only based on a small number of assessed young forest plants for rarer tree species (e.g. pine, larch, Arolla pine, oak, chestnut). Accordingly, for this target variable one should always check how many young forest plants were assessed for the individual estimates. As a rule of thumb, at least 30 young forest plants per estimate should have been assessed for browsing in order to obtain a reliable estimate.

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5. Two types of changes?

There are two types of changes in the National Forest Inventory (NFI):

The first type of change involves specific target variables for change components such as increment, fellings or mortality. These target variables are only available for two consecutive measurement cycles, e.g. NFI4 to NFI5. When change components are analysed, the classification variable expression of the second measurement cycle is generally assigned to the first measurement cycle. These analyses therefore do not take into account any change in the expression (e.g. from private to public ownership) from the earlier to the later measurement cycle.
In the second type of change, the difference in target variables, such as stem number, growing stock or forest area, is used to calculate the net change between two measurement cycles. These target variables are usually used to represent states, e.g. that in NFI5, but can also show the net change between any two measurement cycles, e.g. between NFI1 and NFI5. In these net change analyses, the change in expression is taken into account for some of the classification variables, including “tree condition” and “forest, non-forest”. In this way, it can be seen, for example, that the forest area has increased. For the remaining classification variables, the expressions are regarded as static. This means that the most recent state – whether it was assessed in a measurement cycle (e.g. “primary forest function NFI5”) or taken from an external data source (e.g. “protection forest [2022]”) – is assigned to all measurement cycles.

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6. Change analyses: When are the results (not) additive?

The results are:

additive if they are reported as the total change between two measurement dates. For example, the fellings for the various production regions reported in cubic metres (m³) can be added together to obtain the total fellings for Switzerland.
not additive if they are reported as a change per year (e.g. m³/year). For example, the fellings for the various production regions reported in cubic metres per year (m³/year) cannot be added together to obtain the total fellings for Switzerland.

Example 9: : Additivity/non-additivity of changes

	growing stock: total change between NFI4 and NFI5 (in 1000 m³)*
	Jura		Plateau		Pre-Alps		Alps		Southern Alps		Switzerland
higher/lower altitude zone	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%
lower altitude zone	-3759.0	28	-4909.1	36	-1025.2	133	-317.1	195	3464.1	31	-6546.3	42
higher altitude zone	574.3	117	-328.0	62	1093.0	123	7128.4	21	666.7	93	9134.3	24
total	-3184.7	40	-5237.1	34	67.9	2805	6811.3	23	4130.8	30	2588.1	136
	* accessible forest without shrub forest NFI4/NFI5
	additive

	growing stock: annual change between NFI4 and NFI5 (in 1000 m³/year)*
	Jura		Plateau		Pre-Alps		Alps		Southern Alps		Switzerland
higher/lower altitude zone	1000 m³/year	±%	1000 m³/year	±%	1000 m³/year	±%	1000 m³/year	±%	1000 m³/year	±%	1000 m³/year	±%
lower altitude zone	-421.1	28	-560.6	36	-115.7	133	-35.9	195	389.5	31	-740.7	42
higher altitude zone	64.7	117	-38.3	62	122.4	123	810.4	21	74.9	93	1032.7	24
total	-357.3	40	-598.4	34	7.6	2805	773.8	23	464.4	30	292.7	136
	* accessible forest without shrub forest NFI4/NFI5
	not additive

The non-additivity of changes expressed per year arises because the total change is divided by the average number of years between the two measurement dates in the domain* under consideration, and this average number of years varies slightly depending on the domain.

Example 10: Average number of years per domain

domain		mean number of years*
production region	higher/lower altitude zone
Mittelland	-	8.75
Plateau	higher altitude zone	8.56
Plateau	lower altitude zone	8.76
Southern Alps	-	8.90
Southern Alps	higher altitude zone	8.90
Southern Alps	lower altitude zone	8.89
* between the NFI4 and NFI5 measurements in the accessible forest without shrub forest

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7. Why is a dot (“.”) sometimes given in the cells for standard error or estimated value?

In the calculation of a results table, data is not always available for all combinations of variable expressions*. In most cases, this indicates that the variable estimated with the relevant target variable does not occur or only occurs very rarely. The value 0 is then usually used. However, as this value is not based on any direct measurements, a dot (“.”) is given for the associated standard error. If reference is made to the assumed value of 0 in the calculation, e.g. in the case of percentages or certain change estimates, no value can be used. In this case, a dot (“.”) is given for the estimated value and the standard error.

For example, no Arolla pines have yet been found and measured in the Plateau in the National Forest Inventory (NFI) (growing stock of Arolla pine by production region). It can therefore be assumed that the values are missing because the Arolla pine actually does not occur in the Plateau, and therefore the growing stock in that region must be 0.

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8. Why are no standard error values shown in some tables?

The data in these tables originates from a complete survey and not from a sample inventory. Accordingly, it is not necessary to specify a standard error because there is no uncertainty due to sampling.

The forest road network survey that the National Forest Inventory (NFI) periodically carries out with the local forestry services is an example of such a complete survey.

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9. Negative values for growing stock, increment or fellings?

A negative value is possible if the result could only be calculated on the basis of a few trees. The estimate is therefore not reliable. This is also reflected in the standard error, which is usually extremely large for negative stock, increment or felling values.

Negative values can occur because, when the stemwood volume of the tally trees is determined, the volume estimated solely on the basis of the diameter at breast height (DBH) (tariff volume) is adjusted using the volume of the tally trees estimated on the basis of DBH, diameter at 7 m height and tree height. This procedure enables an unbiased and more accurate calculation of the stemwood volume. However, it can lead to negative values for all target variables that are based on the stemwood volume of the tally trees (e.g. growing stock, increment, fellings) if the number of tally trees in the selected combination of variable expressions* is small.

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NFI1—NFI5
change: growing stock (stemwood)
protection forest against channel processes (2022) · main tree species
regional demarcation: forest district (2024)
unit: 1000 m³
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
change 1983/85–2018/26
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
protection forest against channel processes (2022)	main tree species	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%
n/a	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	fir	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	pine	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	larch	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	other conifers	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	beech	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	maple	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	ash	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	oak	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	other broadleaves	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	indeterminable	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
inside	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	.	.	.	.	.	.	.	.	-74	231	-150	117	-383	228	-1034	49	-223	112	-182	70	.	.	4	.	29	100	.	.	222	89	336	122	-55	776	734	49	.	.	-593	70	1373	45	360	115	-743	79	-135	430	208	217	-90	107	42	167	.	.	-75	401	.	.	112	77	-17	.	.	.	11	83	26	232	157	99	421	61	-75	105	-762	73	-227	201	-164	101	61	552	.	.	.	.	-23	.	-133	100	-42	100	220	108	-459	76	-3	5633	90	100	-106	100	-30	100	268	127	1688	62	141	219	1	100	47	78	-19	222	170	50	7	100	177	53	116	143	342	72	20	1726	67	268	224	122	214	55	6	778	7	.	1	.	.	.	.	.	.	.	.	.	-25	.	25	.	.	.	-31	168	.	.	21	.	870	45	279	128	1389	32	-148	107	31	245	-42	239	125	122	319	79	.	.	-140	.	.	.	.	.	4781	53
	fir	.	.	.	.	.	.	.	.	5	924	303	73	766	32	-488	93	108	59	77	161	.	.	.	.	-10	100	.	.	85	100	91	80	266	93	14	1507	.	.	47	156	67	95	67	80	26	100	34	362	0	0	-76	230	86	151	.	.	71	213	.	.	5	580	18	.	.	.	.	.	51	131	-52	113	328	54	31	494	-66	74	109	87	396	70	3	6880	.	.	.	.	9	.	.	.	43	100	357	80	98	200	-111	130	64	90	-61	100	.	.	18	100	143	55	.	.	.	.	.	.	2	699	41	362	-8	642	183	70	58	309	.	.	136	62	76	129	171	98	436	46	3	100	.	.	7	.	.	.	.	.	.	.	.	.	.	.	-140	.	.	.	11	100	.	.	92	.	31	505	170	59	290	59	-93	107	.	.	-13	146	-27	142	-15	363	.	.	.	.	.	.	.	.	4331	25
	pine	.	.	.	.	.	.	.	.	.	.	.	.	-137	65	46	128	-8	100	64	72	.	.	.	.	-10	100	.	.	.	.	.	.	.	.	-28	100	.	.	.	.	0	30234	55	70	.	.	-20	101	15	142	-53	81	18	100	.	.	.	.	.	.	29	100	.	.	.	.	16	100	.	.	.	.	29	100	.	.	.	.	.	.	.	.	-25	100	.	.	.	.	-5	.	-39	100	.	.	.	.	.	.	.	.	-2	928	.	.	.	.	-14	100	-105	73	.	.	.	.	.	.	.	.	.	.	.	.	10	100	.	.	.	.	-27	229	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-17	698	115	52	49	148	.	.	-4	100	7	96	-4	100	.	.	.	.	-33	.	.	.	.	.	-79	307
	larch	.	.	.	.	.	.	.	.	.	.	.	.	-25	153	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-53	103	-32	222	-55	85	417	32	733	26	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	37	100	-48	175	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	18	100	14	100	.	.	.	.	75	49	178	54	196	58	69	78	.	.	-75	118	629	33	115	65	148	79	.	.	.	.	-63	100	-27	231	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	390	44	573	30	194	65	-12	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	3396	15
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	11	100	.	.	.	.	45	81	62	71	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	208	48	28	180	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	358	35
	other conifers	.	.	.	.	.	.	.	.	.	.	6	100	1	100	.	.	38	100	1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	100	3	80	10	73	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	7	100	1	723	-18	104	4	72	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	3	100	.	.	.	.	2	100	.	.	.	.	.	.	.	.	.	.	.	.	81	100	.	.	.	.	.	.	.	.	-2	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-10	100	4	100	1	100	.	.	.	.	4	72	20	74	7	78	.	.	.	.	.	.	.	.	175	54
	beech	.	.	.	.	.	.	.	.	19	119	-39	113	464	50	476	56	193	101	264	52	.	.	46	.	61	115	.	.	6	100	112	93	192	41	5	100	.	.	-11	2026	3	2741	36	117	.	.	216	70	.	.	62	233	56	100	.	.	138	69	.	.	22	66	-3	.	.	.	11	100	-4	863	4	100	-294	105	113	50	170	56	376	47	166	74	197	76	.	.	.	.	.	.	18	71	6	213	109	58	60	115	211	65	52	57	54	78	87	100	.	.	103	56	.	.	426	43	589	36	376	37	599	35	572	33	229	64	119	74	.	.	72	71	2	2140	24	130	183	58	42	74	26	.	53	.	.	.	3	.	.	.	.	.	.	.	-23	.	.	.	28	254	.	.	4	.	.	.	25	86	378	36	108	99	-58	116	-146	78	68	79	-92	79	.	.	-6	.	.	.	.	.	7359	12
	maple	.	.	.	.	.	.	.	.	-6	276	-22	150	226	44	93	49	.	.	110	47	.	.	9	.	31	105	.	.	.	.	40	62	109	47	37	109	.	.	128	71	12	55	17	100	35	100	74	53	.	.	-51	125	18	151	.	.	77	51	.	.	25	73	12	.	.	.	6	100	13	176	-41	105	97	108	4	853	98	121	57	96	124	55	204	50	.	.	.	.	.	.	17	71	61	91	37	69	19	118	47	102	49	93	2	100	-18	100	34	100	57	100	11	100	3	70	15	100	32	72	7	58	44	100	5	74	19	123	5	384	.	.	63	61	18	109	87	66	-9	85	7	.	0	.	.	.	2	.	.	.	.	.	-32	.	-20	.	.	.	10	100	.	.	12	.	.	.	46	72	133	41	33	88	56	76	-20	121	10	470	-58	62	.	.	.	.	.	.	.	.	2321	15
	ash	.	.	.	.	.	.	.	.	.	.	36	140	61	74	-48	190	0	6448	27	71	.	.	-12	.	10	100	.	.	.	.	120	133	48	73	12	325	.	.	110	82	.	.	3	100	23	100	82	70	.	.	-12	159	19	124	.	.	7	551	.	.	-40	100	.	.	.	.	.	.	6	135	-14	100	83	73	-109	76	34	161	28	93	-13	149	119	68	.	.	.	.	.	.	36	89	-16	73	103	65	11	72	106	86	41	95	.	.	-15	100	.	.	202	100	2	100	25	63	22	93	51	81	110	73	-2	588	52	51	22	69	45	70	.	.	64	97	8	62	38	97	114	100	40	.	.	.	.	.	.	.	.	.	.	.	-34	.	.	.	.	.	-28	121	.	.	14	.	30	65	31	100	56	74	18	151	42	74	-8	237	-50	71	-19	76	.	.	-58	.	.	.	.	.	1637	26
	oak	.	.	.	.	.	.	.	.	.	.	.	.	5	100	0	0	36	118	.	.	.	.	.	.	-29	100	.	.	.	.	25	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-1	100	51	100	-19	82	-3	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-4	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	8	100	.	.	.	.	6	75	-25	100	3	100	.	.	.	.	.	.	21	115	43	52	54	95	12	71	32	92	57	47	0	100	.	.	13	100	.	.	.	.	.	.	19	171	.	.	.	.	.	.	33	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	3	.	38	74	9	75	-2	513	.	.	.	.	30	71	-10	100	.	.	.	.	.	.	.	.	.	.	407	31
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	114	65	-19	126	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	2	100	74	146	27	78	161	70	-14	582	139	117	223	55	66	121	311	72	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	100	.	.	12	72	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1101	33
	other broadleaves	.	.	.	.	.	.	.	.	-2	100	41	100	42	109	38	136	-7	189	16	52	.	.	-15	.	10	247	.	.	-16	99	-18	86	11	100	-48	117	.	.	40	80	15	185	8	71	60	172	189	63	281	75	15	138	14	93	.	.	44	88	.	.	1	100	.	.	.	.	5	100	15	77	-14	113	-13	128	.	.	32	58	-17	330	-17	89	31	132	.	.	.	.	2	.	73	85	-6	100	-7	277	3	133	-76	52	.	.	-2	100	4	100	50	105	225	69	49	96	46	132	166	75	308	34	-8	814	36	220	137	52	-16	337	-29	100	13	92	-13	75	12	71	13	123	9	89	.	.	.	.	.	.	.	.	.	.	.	.	0	.	-2	.	.	.	-3	100	.	.	.	.	90	75	96	50	72	59	-3	371	16	71	.	.	-2	856	-3	100	.	.	.	.	.	.	.	.	1992	21
	indeterminable	.	.	.	.	.	.	.	.	.	.	0	0	0	0	.	.	0	0	0	0	.	.	.	.	0	0	.	.	.	.	.	.	.	.	0	0	.	.	.	.	0	0	.	.	0	0	0	0	.	.	0	0	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	0	0	.	.	0	0	.	.	.	.	0	0	0	0	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	0	0	0	.	.	.	.	0	0	.	.	.	.	.	.	0	0	0	0	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	0	0	0	0	0	.	.	.	.	.	.	.	.	0	0	.	.	.	.	.	.	.	.	0	0
	total	.	.	.	.	.	.	.	.	-58	345	175	216	1026	94	-917	81	138	242	378	65	.	.	32	.	94	87	.	.	297	72	707	71	572	99	725	61	.	.	-279	193	1427	45	514	85	-654	86	1020	68	1334	43	-213	143	250	72	.	.	262	164	.	.	154	67	10	.	.	.	50	83	107	129	41	479	651	77	-29	589	-461	135	261	211	496	54	590	85	.	.	.	.	-17	.	-29	684	46	210	827	52	-268	163	194	193	313	58	-137	91	32	250	435	84	2563	49	427	81	752	31	868	28	869	34	1863	22	864	28	1308	28	319	94	363	67	162	265	233	103	458	79	971	35	184	80	80	.	61	.	.	.	44	.	.	.	.	.	-91	.	-160	.	.	.	-12	776	.	.	145	.	1635	31	1376	35	2572	24	-97	251	84	149	-188	106	131	154	139	194	.	.	-237	.	.	.	.	.	27780	12
outside	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	-662	60	-965	59	424	61	-1810	33	641	55	-794	79	-897	103	-1181	57	-3382	31	-352	118	-237	83	67	115	-237	99	.	.	-323	113	-595	85	-848	66	-1022	59	3	121	223	134	599	85	828	43	854	71	1076	42	597	65	-340	133	-832	55	-986	58	-796	80	108	168	368	56	-227	66	-24	837	-434	60	636	61	-157	175	-510	77	-61	526	521	64	217	93	84	387	-317	121	-283	136	-319	111	-354	74	-523	77	86	106	132	150	-43	614	-248	78	-479	101	-261	98	-122	273	49	162	103	62	33	189	.	.	.	.	.	.	.	.	30	111	.	.	148	70	83	116	214	67	220	52	346	39	89	118	-405	105	-209	148	-111	306	-211	92	-277	57	132	170	265	90	98	221	-215	71	28	413	-229	91	-163	60	-582	97	193	138	538	69	-239	113	220	66	-171	173	-525	68	-36	1128	-17	2054	-904	41	-393	87	-255	142	.	.	-15310	22
	fir	28	684	-22	238	-58	283	-361	73	95	50	216	102	239	64	301	178	213	316	161	184	18	63	106	58	170	54	.	.	122	74	193	68	-450	71	4	3744	4	100	57	103	77	90	74	76	-22	101	279	65	.	.	1332	29	308	90	553	70	250	100	-116	118	580	51	73	207	96	120	933	42	30	89	-269	91	162	89	211	77	-27	100	-4	161	126	58	112	88	129	67	45	591	-110	123	-160	60	-46	249	84	78	-71	149	129	93	315	79	105	113	234	73	.	.	.	.	74	100	.	.	.	.	.	.	.	.	.	.	.	.	17	68	.	.	-9	100	56	87	-2	527	174	72	66	75	75	100	487	41	-76	323	-123	180	226	60	124	88	241	46	217	68	56	333	246	75	-11	1369	48	94	.	.	48	70	146	54	107	60	10	860	-124	131	-126	186	-118	169	53	79	-109	119	-39	239	.	.	8182	20
	pine	-168	49	-492	53	-61	56	-27	110	.	.	-8	100	-23	108	9	100	-283	57	14	777	-14	164	18	139	-9	392	.	.	10	100	-115	102	.	.	-192	71	22	201	.	.	-53	154	-310	52	7	100	133	82	90	118	3	2572	.	.	57	63	.	.	-20	100	.	.	.	.	-14	85	.	.	4	100	110	100	.	.	11	100	.	.	.	.	.	.	.	.	-73	138	-112	63	-24	150	-153	59	-61	56	25	100	-3	100	.	.	-6	558	-47	120	-57	96	.	.	.	.	17	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	65	94	-5	100	.	.	.	.	.	.	19	79	-7	100	-68	100	3	100	.	.	5	71	.	.	-230	89	-2	100	.	.	10	100	.	.	36	324	-23	207	-38	197	.	.	.	.	-130	101	-21	143	-134	67	-221	58	-65	74	-109	71	.	.	-2713	23
	larch	19	110	-22	203	73	84	-99	53	.	.	.	.	-56	155	-66	71	-73	84	.	.	.	.	.	.	-2	71	-63	.	.	.	-6	1455	.	.	-60	145	.	.	13	100	-41	171	14	138	211	60	151	79	333	67	5	100	0	1840	20	71	1	100	.	.	.	.	.	.	8	100	.	.	.	.	.	.	18	100	13	100	.	.	-13	76	5	100	.	.	-8	288	.	.	.	.	20	100	.	.	.	.	.	.	.	.	.	.	7	100	27	100	.	.	35	76	83	70	59	100	.	.	8	100	179	59	40	72	.	.	.	.	.	.	.	.	139	57	.	.	20	100	.	.	66	100	.	.	22	100	-21	100	.	.	-2	100	.	.	27	138	.	.	21	100	.	.	68	100	1168	47	430	42	110	61	.	.	15	100	9	100	20	89	.	.	-36	139	-12	100	-43	139	.	.	2836	25
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	40	61	129	141	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	8	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	18	177	18	74	39	111	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	253	76
	other conifers	35	82	.	.	61	100	70	89	.	.	5	100	.	.	.	.	272	79	2	100	.	.	.	.	.	.	222	.	.	.	.	.	.	.	-35	100	.	.	2	100	7	100	.	.	.	.	.	.	17	50	.	.	52	98	178	80	2	100	.	.	.	.	5	100	.	.	.	.	.	.	.	.	8	100	200	100	5	100	.	.	.	.	.	.	63	100	9	100	5	100	33	75	.	.	.	.	.	.	.	.	.	.	.	.	1	257	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	100	.	.	.	.	.	.	4	100	.	.	9	100	.	.	.	.	56	100	23	63	.	.	.	.	.	.	.	.	.	.	-149	100	.	.	6	100	.	.	.	.	2	100	.	.	2	77	.	.	.	.	3	481	1	278	.	.	.	.	.	.	.	.	.	.	1176	38
	beech	-644	62	-98	190	229	69	525	55	71	60	-52	299	-246	82	-172	161	-1086	51	700	38	-327	87	-60	345	-15	1597	.	.	15	665	15	1000	242	49	235	124	.	.	19	407	-110	149	69	202	-21	104	29	77	.	.	-333	119	6	3127	134	189	240	33	44	195	-15	374	69	120	78	105	-31	343	83	151	28	72	162	67	236	48	-145	131	21	294	154	87	159	83	707	35	91	216	-309	79	158	109	196	69	60	71	.	.	202	75	313	44	83	71	-109	163	.	.	.	.	.	.	92	82	62	59	-21	100	.	.	26	89	.	.	294	58	.	.	24	100	301	51	-14	182	21	100	120	72	45	100	244	53	-8	739	-235	39	166	40	-83	137	87	214	236	41	109	82	11	670	121	100	88	112	.	.	.	.	-35	199	52	78	54	139	315	41	15	1224	-233	119	310	42	-79	205	89	120	.	.	3771	39
	maple	-119	87	108	51	34	134	-69	81	12	100	90	73	10	472	222	48	205	41	141	58	81	62	-16	223	65	65	-36	.	56	73	13	86	113	42	50	63	.	.	45	91	56	61	31	75	31	74	10	71	3	100	146	43	102	46	41	56	83	62	75	73	91	40	45	82	84	67	23	60	19	216	.	.	6	112	-60	121	18	103	.	.	24	96	85	58	70	67	122	42	72	90	16	227	26	114	34	76	-9	85	26	64	94	57	-2	1581	61	81	.	.	.	.	.	.	.	.	-13	100	5	99	2	100	2	100	5	100	72	64	.	.	1	100	13	91	31	50	9	100	6	689	2	100	104	50	10	100	20	69	14	71	63	39	0	2958	57	62	34	79	.	.	.	.	61	74	6	100	1	100	95	70	.	.	76	53	32	77	104	43	52	73	228	57	-27	154	130	61	.	.	3625	11
	ash	0	22151	-80	144	-68	102	-9	732	.	.	6	928	-70	71	41	185	251	68	12	207	-31	238	34	56	48	60	.	.	74	65	166	92	261	50	45	152	3	100	-49	134	18	95	7	75	-21	129	19	74	.	.	168	76	229	88	15	329	-17	100	-47	209	2	71	4	100	3	100	6	100	271	75	.	.	1	848	213	84	87	63	26	100	101	108	-3	100	53	86	112	47	20	59	83	54	2	2369	63	61	.	.	-19	100	100	52	2	4848	150	57	10	100	.	.	.	.	.	.	7	100	107	76	.	.	7	281	19	100	96	81	.	.	.	.	-21	397	51	71	.	.	68	101	16	59	-20	136	-9	100	9	77	10	100	-52	76	-1	1199	107	64	64	68	-56	100	-2	100	-66	137	20	196	23	72	47	97	-54	100	184	65	-26	177	4	1530	103	61	74	93	-35	109	-29	208	.	.	2934	22
	oak	242	63	-33	154	-147	62	77	139	.	.	.	.	9	100	30	120	48	201	.	.	-38	69	-4	258	38	84	.	.	-20	93	-29	94	42	83	32	92	3	5322	.	.	.	.	30	100	.	.	.	.	.	.	33	215	14	567	35	142	36	100	-36	117	.	.	8	100	.	.	.	.	3	100	.	.	.	.	-6	100	-29	100	.	.	9	126	-9	100	-93	87	13	100	-9	101	13	74	57	59	.	.	.	.	.	.	6	489	291	93	2	4596	.	.	.	.	.	.	-1	100	-4	76	95	70	2	100	-16	155	.	.	32	100	.	.	.	.	10	79	14	100	.	.	.	.	2	100	14	73	-80	166	17	61	.	.	148	78	9	100	-51	68	96	83	.	.	41	100	18	100	7	100	74	66	36	92	.	.	-21	100	20	100	.	.	-125	94	26	136	-19	264	-25	222	.	.	933	56
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	130	71	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	70	85	57	117	43	122	-75	60	156	121	.	.	-29	80	108	87	.	.	.	.	.	.	.	.	6	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-3	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	467	55
	other broadleaves	24	320	-13	468	-2	5789	9	250	-1	100	16	86	39	158	12	221	188	55	25	88	-44	84	6	126	3	311	.	.	-37	100	149	63	37	62	102	64	5	150	12	189	30	101	-19	161	137	95	36	231	101	104	66	130	48	107	7	703	21	100	-91	72	16	64	-20	93	-18	77	-11	83	34	67	.	.	11	62	2	240	-134	60	-20	106	40	108	5	110	2	1190	78	84	-34	69	45	87	-88	62	82	59	-2	557	.	.	28	178	16	499	-43	112	16	71	134	83	8	119	10	100	-4	1572	320	56	4	948	46	74	19	186	10	64	.	.	3	103	-12	218	149	183	-2	199	-15	211	157	106	23	98	-46	98	-2	226	16	70	50	96	14	55	-32	71	0	3347	37	109	3	100	-3	121	45	62	81	45	-6	1387	-9	100	82	67	136	65	10	377	-31	139	-20	144	29	63	-9	731	.	.	2066	28
	indeterminable	.	.	.	.	.	.	.	.	.	.	0	0	0	0	0	0	.	.	.	.	0	0	.	.	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	.	.	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	.	.	.	.	.	.	0	0	0	0	0	0	0	0	.	.	0	0	0	0	.	.	.	.	0	0	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	.	.	0	0	0	0	.	.	.	.	.	.	0	0	.	.	.	.	0	0	0	0	.	.	.	.	.	.	.	.	.	.	.	.	0	0	.	.	0	0	.	.	.	.	.	.	.	.	.	.	0	0	.	.	0	0	.	.	0	0
	total	-1245	57	-1618	42	486	69	-1696	42	818	48	-521	145	-994	101	-804	132	-3646	38	702	94	-593	64	150	178	62	579	124	.	-104	390	-209	308	-602	126	-842	80	40	427	320	104	587	93	724	59	1177	54	1900	30	1270	45	1078	71	-73	738	54	1434	-180	400	-83	421	1042	37	-41	505	213	102	485	99	1079	45	-288	170	-144	280	759	73	296	149	227	96	543	78	32	1519	569	93	38	1259	-743	60	-468	98	171	138	479	51	-128	224	90	316	372	152	193	172	143	320	75	105	341	45	280	44	202	54	-28	305	671	37	187	66	107	53	151	65	669	52	83	116	301	46	702	41	590	52	311	66	-160	306	230	183	756	56	-464	78	-609	60	566	49	518	64	447	76	-34	1017	384	77	36	859	-2	13025	-368	148	1495	45	1190	39	156	198	316	62	228	149	-291	173	-28	2066	-503	124	-490	91	-710	53	-289	148	.	.	8220	52
total	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	-662	60	-965	59	424	61	-1810	33	567	69	-943	69	-1279	99	-2215	38	-3605	30	-533	82	-237	83	71	108	-208	114	.	.	-101	412	-259	251	-903	78	-288	244	3	121	-371	138	1972	40	1188	46	111	759	941	78	805	74	-430	108	-790	59	-986	58	-871	81	108	168	479	46	-244	61	-24	837	-423	62	662	59	0	88230	-89	530	-136	243	-241	270	-10	5155	-80	454	-255	200	-283	136	-319	111	-377	69	-656	64	44	227	351	88	-502	87	-252	104	-389	126	-367	75	-152	220	317	110	1791	58	174	181	1	100	47	78	-19	222	170	50	36	92	177	53	265	74	426	62	234	157	288	74	571	53	303	52	-400	107	-202	154	-110	308	-211	92	-277	57	132	170	265	90	74	297	-190	82	28	413	-259	82	-163	60	-561	101	1063	45	817	63	1151	46	71	301	-140	218	-567	66	89	482	302	141	-904	41	-534	69	-255	142	.	.	-10529	39
	fir	28	684	-22	238	-58	283	-361	73	100	67	519	60	1005	29	-187	376	321	210	237	135	18	63	106	58	161	58	.	.	207	60	284	53	-183	222	18	1446	4	100	104	90	143	65	142	55	5	741	312	70	0	0	1256	34	394	78	553	70	321	91	-116	118	585	51	91	167	96	120	933	42	81	88	-320	79	489	46	242	92	-93	60	105	91	522	55	114	181	129	67	45	591	-101	134	-160	60	-4	3412	441	66	27	821	18	1038	379	67	44	303	234	73	18	100	143	55	74	100	.	.	.	.	2	699	41	362	-8	642	183	70	75	239	.	.	126	67	132	83	169	99	610	39	69	72	75	100	494	41	-76	323	-123	180	226	60	124	88	241	46	77	267	56	333	257	72	-11	1369	140	73	31	505	218	48	436	43	14	842	10	860	-137	119	-153	156	-133	155	53	79	-109	119	-39	239	.	.	12513	16
	pine	-168	49	-492	53	-61	56	-27	110	.	.	-8	100	-160	58	54	109	-291	55	78	148	-14	164	18	139	-19	194	.	.	10	100	-115	102	.	.	-219	64	22	201	.	.	-53	156	-255	65	7	100	113	99	104	103	-51	156	18	100	57	63	.	.	-20	100	29	100	.	.	-14	85	16	100	4	100	110	100	29	100	11	100	.	.	.	.	.	.	-25	100	-73	138	-112	63	-29	124	-191	51	-61	56	25	100	-3	100	.	.	-8	479	-47	120	-57	96	-14	100	-105	73	17	100	.	.	.	.	.	.	.	.	.	.	10	100	.	.	.	.	37	233	-5	100	.	.	.	.	.	.	19	79	-7	100	-68	100	3	100	.	.	5	71	.	.	-230	89	-2	100	.	.	10	100	.	.	19	900	92	84	11	938	.	.	-4	100	-124	107	-25	121	-134	67	-221	58	-97	60	-109	71	.	.	-2792	23
	larch	19	110	-22	203	73	84	-99	53	.	.	.	.	-81	117	-66	71	-73	84	.	.	.	.	.	.	-2	71	-63	.	.	.	-6	1455	.	.	-60	145	.	.	13	100	-95	95	-18	406	156	87	567	31	1067	27	5	100	0	1840	20	71	1	100	.	.	.	.	.	.	8	100	.	.	.	.	.	.	18	100	13	100	37	100	-60	139	5	100	.	.	-8	288	.	.	.	.	20	100	.	.	.	.	.	.	18	100	14	100	7	100	27	100	75	49	212	46	279	46	128	62	.	.	-67	133	808	29	155	52	148	79	.	.	.	.	-63	100	112	90	.	.	20	100	.	.	66	100	.	.	22	100	-21	100	.	.	-2	100	.	.	27	138	.	.	21	100	.	.	68	100	1558	37	1003	25	304	47	-12	100	15	100	9	100	20	89	.	.	-36	139	-12	100	-43	139	.	.	6232	14
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	11	100	.	.	.	.	84	51	191	98	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	8	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	226	46	46	112	39	111	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	611	38
	other conifers	35	82	.	.	61	100	70	89	.	.	11	71	1	100	.	.	311	71	3	71	.	.	.	.	.	.	222	.	.	.	.	.	.	.	-35	100	.	.	2	100	7	100	.	.	.	.	6	100	20	44	10	73	52	98	178	80	2	100	.	.	.	.	5	100	.	.	.	.	.	.	.	.	8	100	207	97	6	153	-18	104	4	72	.	.	63	100	9	100	5	100	33	75	.	.	.	.	.	.	3	100	.	.	.	.	3	120	.	.	.	.	.	.	.	.	.	.	.	.	81	100	1	100	.	.	.	.	.	.	3	175	.	.	9	100	.	.	.	.	56	100	23	63	.	.	6	100	.	.	.	.	.	.	-149	100	.	.	6	100	.	.	.	.	-9	125	4	100	3	64	.	.	.	.	7	228	20	73	7	78	.	.	.	.	.	.	.	.	1351	34
	beech	-644	62	-98	190	229	69	525	55	90	54	-91	176	218	141	304	127	-893	65	964	31	-327	87	-14	1500	46	535	.	.	21	469	127	144	434	33	240	121	.	.	8	3062	-107	169	105	139	-21	104	245	62	.	.	-271	156	63	327	134	189	378	33	44	195	7	804	66	125	78	105	-21	524	80	162	32	64	-133	247	349	37	25	855	398	47	320	57	356	56	707	35	91	216	-309	79	176	98	202	68	169	45	60	115	413	49	365	39	137	53	-22	917	.	.	103	56	.	.	517	38	651	33	356	39	599	35	598	31	229	64	413	46	.	.	95	59	303	52	10	407	204	53	162	56	71	73	297	47	-8	739	-232	40	166	40	-83	137	87	214	212	47	109	82	40	263	121	100	92	106	.	.	25	86	343	45	161	71	-4	2547	168	103	83	231	-325	88	310	42	-85	192	89	120	.	.	11130	15
	maple	-119	87	108	51	34	134	-69	81	6	345	68	108	236	46	316	37	205	41	252	39	81	62	-7	516	96	55	-36	.	56	73	53	51	223	31	87	59	.	.	173	58	68	51	48	59	66	63	84	47	3	100	95	94	120	46	41	56	160	40	75	73	116	35	58	68	84	67	30	51	31	146	-41	105	103	102	-56	142	116	103	57	96	148	49	289	39	70	67	122	42	72	90	33	117	87	72	70	51	11	223	73	69	143	49	0	12103	42	123	34	100	57	100	11	100	3	70	2	1295	37	63	9	50	47	95	9	62	91	57	5	384	1	100	76	53	49	51	97	60	-4	1055	9	78	105	50	10	100	22	65	14	71	63	39	-33	108	38	108	34	79	10	100	.	.	73	64	6	100	48	70	228	37	33	88	132	45	12	302	114	56	-6	865	228	57	-27	154	130	61	.	.	5947	9
	ash	0	22151	-80	144	-68	102	-9	732	.	.	42	178	-9	743	-7	1736	252	69	39	81	-31	238	22	104	58	53	.	.	74	65	286	77	310	44	56	138	3	100	61	184	18	95	10	61	3	1289	101	58	.	.	156	83	248	82	15	329	-11	373	-47	209	-37	106	4	100	3	100	6	100	277	73	-14	100	84	73	105	189	121	64	54	68	88	126	117	70	53	86	112	47	20	59	118	47	-13	395	167	47	11	72	87	108	141	46	2	4848	135	64	10	100	202	100	2	100	25	63	29	75	158	58	110	73	5	415	70	46	118	67	45	70	.	.	43	237	59	62	38	97	182	73	56	74	-20	136	-9	100	9	77	10	100	-52	76	-36	107	107	64	64	68	-84	78	-2	100	-52	176	50	87	53	65	103	60	-36	167	226	55	-34	147	-45	159	84	76	74	93	-93	75	-29	208	.	.	4571	17
	oak	242	63	-33	154	-147	62	77	139	.	.	.	.	14	73	30	120	83	126	.	.	-38	69	-4	258	9	460	.	.	-20	93	-4	942	42	83	32	92	3	5322	.	.	.	.	30	100	.	.	-1	100	51	100	14	516	11	722	35	142	36	100	-36	117	.	.	8	100	.	.	.	.	3	100	.	.	.	.	-6	100	-34	88	.	.	9	126	-9	100	-93	87	13	100	-9	101	13	74	57	59	8	100	.	.	.	.	12	257	266	102	5	2127	.	.	.	.	.	.	20	121	39	58	149	56	13	63	16	239	57	47	32	99	.	.	13	100	10	79	14	100	.	.	19	171	2	100	14	73	-80	166	50	69	.	.	148	78	9	100	-51	68	96	83	.	.	41	100	21	88	45	65	83	59	34	100	.	.	-21	100	50	58	-10	100	-125	94	26	136	-19	264	-25	222	.	.	1341	40
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	243	48	-19	126	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	2	100	143	86	84	83	204	61	-89	107	296	84	223	55	38	224	419	57	.	.	.	.	.	.	.	.	6	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	100	.	.	8	110	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1568	28
	other broadleaves	24	320	-13	468	-2	5789	9	250	-3	72	57	76	81	95	50	116	181	57	41	57	-44	84	-10	180	13	202	.	.	-53	76	131	72	49	53	53	162	5	150	52	75	45	91	-12	275	196	84	225	65	382	62	81	108	63	85	7	703	65	68	-91	72	17	61	-20	93	-18	77	-6	183	49	52	-14	113	-2	867	2	240	-102	81	-37	163	23	199	36	114	2	1190	78	84	-32	73	118	62	-94	58	75	70	1	1111	-76	52	28	178	14	575	-39	124	67	81	359	53	57	84	56	110	162	88	628	33	-4	1864	83	105	156	51	-6	957	-29	100	16	77	-25	110	161	170	11	144	-5	607	157	106	23	98	-46	98	-2	226	16	70	50	96	14	55	-35	66	0	3347	34	120	3	100	-3	121	135	54	176	34	66	137	-11	113	98	57	136	65	8	496	-34	127	-20	144	29	63	-9	731	.	.	4058	18
	indeterminable	.	.	.	.	.	.	.	.	.	.	0	0	0	0	0	0	0	0	0	0	0	0	.	.	0	0	.	.	0	0	.	.	.	.	0	0	.	.	.	.	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	.	.	.	.	.	.	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	.	.	0	0	0	0	.	.	.	.	0	0	.	.	.	.	0	0	0	0	0	0	.	.	.	.	0	0	.	.	.	.	0	0	0	0	.	.	.	.	.	.	.	.	.	.	.	.	0	0	0	0	0	0	.	.	.	.	.	.	.	.	0	0	0	0	.	.	0	0	.	.	0	0
	total	-1245	57	-1618	42	486	69	-1696	42	760	58	-346	244	31	4442	-1721	75	-3508	41	1079	65	-593	64	182	148	155	235	124	.	194	237	498	164	-30	3149	-117	688	40	427	41	1539	2014	42	1238	49	523	162	2920	30	2604	31	866	96	177	322	54	1434	82	1017	-83	421	1196	33	-31	663	213	102	535	91	1187	43	-247	213	508	127	730	79	-165	464	488	121	1039	48	622	113	569	93	38	1259	-760	59	-497	100	217	118	1306	38	-396	132	284	165	685	87	56	638	176	265	510	73	2905	43	707	52	954	27	840	31	1540	24	2051	21	971	25	1459	26	988	46	446	59	462	97	935	40	1048	45	1282	31	24	2131	310	138	817	52	-464	78	-566	65	566	49	518	64	356	99	-194	194	384	77	24	1324	-2	13025	-222	253	3130	27	2566	26	2728	25	220	141	312	116	-480	113	102	603	-365	187	-490	91	-947	47	-289	148	.	.	36000	15

Table citation

Abegg, M.; Ahles, P.; Allgaier Leuch, B.; Cioldi, F.; Didion, M.; Düggelin, C.; Fischer, C.; Herold, A.; Meile, R.; Rohner, B.; Rösler, E.; Speich, S.; Temperli, C.; Traub, B.,
2023: Swiss national forest inventory - Result table No. 2285336. Birmensdorf, Swiss Federal Research Institute WSL

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