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	23-35calculated 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 and the total forest (pairs of values in ), but they do in the private 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 and the total forest of the Plateau has decreased. For the private 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 and total 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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NFI2—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 1993/95–2018/26
		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	.	.	.	.	.	.	.	.	137	142	-207	78	-282	277	-1557	36	-216	93	-87	122	.	.	4	.	23	100	.	.	108	113	-152	287	-387	124	451	55	.	.	-639	88	1138	47	227	141	-376	119	-711	83	436	71	-57	154	19	269	.	.	-307	92	.	.	70	95	-50	.	.	.	18	96	33	166	70	250	401	55	-77	121	-440	87	139	262	88	53	-232	201	.	.	.	.	-52	.	-164	100	-37	100	162	91	-609	63	72	236	145	48	-47	100	-22	100	57	507	1603	61	-80	363	.	.	39	83	17	100	147	53	3	100	159	76	144	61	218	87	-188	196	-5	3487	371	47	197	64	-82	72	1	.	-3	.	.	.	.	.	.	.	.	.	.	.	25	.	.	.	-141	82	.	.	18	.	801	36	248	108	1180	34	-149	124	89	65	-93	97	106	103	257	75	.	.	-165	.	.	.	.	.	1811	130
	fir	.	.	.	.	.	.	.	.	78	94	185	117	647	33	-900	51	-14	418	37	285	.	.	.	.	-13	100	.	.	75	100	68	93	-48	444	-65	364	.	.	48	122	49	122	102	61	22	100	104	66	0	0	-211	93	24	524	.	.	55	259	.	.	-3	1314	19	.	.	.	.	.	24	302	-2	100	272	49	53	352	-22	267	4	2440	347	69	-42	424	.	.	.	.	8	.	.	.	27	100	332	66	-51	342	-51	279	18	210	13	100	.	.	18	100	130	56	.	.	.	.	.	.	12	100	38	344	29	161	160	69	73	205	.	.	109	76	18	552	134	108	310	57	-35	100	.	.	-9	.	.	.	.	.	.	.	.	.	.	.	-85	.	.	.	-13	100	.	.	78	.	78	161	112	62	321	44	28	283	.	.	-24	100	35	246	-3	1701	.	.	.	.	.	.	.	.	2705	37
	pine	.	.	.	.	.	.	.	.	.	.	.	.	-88	85	26	228	.	.	38	72	.	.	.	.	-14	100	.	.	.	.	.	.	.	.	-26	100	.	.	.	.	20	102	40	74	.	.	3	1214	6	409	-53	88	18	100	.	.	.	.	.	.	14	100	.	.	.	.	32	100	.	.	.	.	27	100	.	.	.	.	.	.	.	.	5	100	.	.	.	.	0	.	-43	100	.	.	.	.	-9	100	.	.	-5	345	.	.	.	.	-16	100	-46	70	.	.	.	.	.	.	.	.	.	.	.	.	10	100	.	.	.	.	0	8372	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-77	167	122	49	14	402	.	.	-20	100	2	108	2	100	.	.	.	.	-32	.	.	.	.	.	-51	420
	larch	.	.	.	.	.	.	.	.	.	.	.	.	-41	95	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-15	386	-35	195	-31	74	255	35	820	25	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	25	100	-44	166	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	12	100	10	100	.	.	.	.	76	55	168	46	146	58	35	94	.	.	8	222	467	33	58	75	72	100	.	.	.	.	-18	100	-43	182	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	263	64	350	41	168	76	-19	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	2685	16
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	-1	546	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	9	100	.	.	.	.	31	84	75	53	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	152	54	10	468	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	276	38
	other conifers	.	.	.	.	.	.	.	.	.	.	6	100	1	100	.	.	22	100	1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	100	1	218	10	72	-1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	7	100	6	100	0	666	2	89	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	2	100	.	.	.	.	2	100	.	.	.	.	.	.	.	.	.	.	.	.	69	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	4	126	0	100	.	.	.	.	4	72	22	86	6	76	.	.	.	.	.	.	.	.	173	44
	beech	.	.	.	.	.	.	.	.	64	87	22	213	358	55	191	130	204	57	144	94	.	.	47	.	22	282	.	.	6	100	38	276	209	49	5	100	.	.	21	1153	-1	7722	25	132	.	.	223	54	.	.	43	336	111	65	.	.	220	55	.	.	29	71	-2	.	.	.	11	100	0	99674	17	100	-213	132	78	54	143	57	334	51	152	60	-114	185	.	.	.	.	.	.	18	71	19	279	45	108	48	88	163	63	31	84	17	121	69	100	.	.	77	65	.	.	299	45	565	31	285	38	418	31	442	33	84	186	80	76	.	.	117	57	-20	69	35	87	119	59	-6	655	26	.	48	.	.	.	2	.	.	.	.	.	.	.	-36	.	.	.	-37	227	.	.	8	.	.	.	24	89	282	38	77	131	-7	346	-168	67	2	1669	-112	85	.	.	3	.	.	.	.	.	5399	15
	maple	.	.	.	.	.	.	.	.	-8	123	-4	263	135	72	74	56	.	.	90	46	.	.	12	.	23	106	.	.	.	.	31	70	95	48	30	105	.	.	58	111	13	63	15	100	35	100	59	58	.	.	-72	81	19	101	.	.	55	65	.	.	23	75	8	.	.	.	6	100	11	145	-74	98	70	110	10	279	95	120	-17	247	97	50	41	170	.	.	.	.	.	.	13	74	41	93	30	63	6	276	44	105	51	111	-2	100	-19	100	33	100	46	100	10	100	-1	294	9	100	31	73	7	58	33	105	5	74	16	101	10	77	.	.	38	57	8	317	70	80	.	.	7	.	-1	.	.	.	2	.	.	.	.	.	-1	.	-9	.	.	.	31	100	.	.	4	.	.	.	40	72	90	53	14	172	28	95	-7	421	-12	387	-37	106	.	.	.	.	.	.	.	.	1555	19
	ash	.	.	.	.	.	.	.	.	.	.	52	100	35	85	-31	229	5	443	12	71	.	.	-14	.	10	100	.	.	.	.	76	192	31	95	6	685	.	.	51	111	-1	100	0	100	-5	100	47	60	.	.	-213	76	6	371	.	.	17	75	.	.	-34	100	.	.	.	.	.	.	10	91	.	.	85	75	-73	78	40	108	4	855	3	100	47	105	.	.	.	.	.	.	26	86	-81	93	18	332	9	76	79	76	27	113	.	.	-7	100	.	.	190	100	2	100	16	71	-2	1449	44	80	100	73	25	112	42	58	17	92	39	74	.	.	60	97	17	78	35	107	104	100	11	.	.	.	.	.	.	.	.	.	.	.	-8	.	.	.	.	.	-55	90	.	.	0	.	22	69	18	112	51	77	35	76	49	91	-45	98	-95	82	-24	100	.	.	-34	.	.	.	.	.	850	49
	oak	.	.	.	.	.	.	.	.	.	.	.	.	1	100	0	0	35	100	.	.	.	.	.	.	-29	100	.	.	.	.	19	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-1	100	23	100	-19	71	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-2	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	100	.	.	.	.	12	86	-33	100	4	100	.	.	.	.	.	.	27	92	62	63	14	360	-48	98	33	93	37	56	-4	100	.	.	14	100	.	.	.	.	.	.	4	1190	.	.	.	.	.	.	28	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	3	.	27	73	7	76	-2	373	.	.	.	.	21	76	0	100	.	.	.	.	.	.	.	.	.	.	239	53
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	96	62	4	74	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-2	100	42	246	96	85	16	281	-32	212	57	236	98	72	32	241	72	256	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-3	100	.	.	7	325	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	484	62
	other broadleaves	.	.	.	.	.	.	.	.	-3	100	19	100	5	1132	34	160	-9	181	12	53	.	.	-10	.	0	18155	.	.	-23	77	21	125	3	399	-16	74	.	.	23	69	-10	202	3	98	120	66	121	79	230	84	9	184	15	99	.	.	38	93	.	.	1	100	.	.	.	.	3	100	15	77	-17	99	-2	415	.	.	18	78	-20	184	1	100	-19	221	.	.	.	.	1	.	51	82	8	100	-1	2114	0	3120	-48	63	.	.	-2	100	-5	100	31	128	204	71	68	97	64	79	87	97	229	44	-33	183	57	148	68	84	2	1846	-33	100	8	87	-12	79	12	71	10	92	6	84	.	.	.	.	.	.	.	.	.	.	.	.	-16	.	.	.	.	.	-5	100	.	.	.	.	75	70	54	67	14	316	-9	151	10	71	.	.	3	291	.	.	.	.	.	.	.	.	.	.	1462	26
	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	.	.	.	.	.	.	.	.	268	95	72	473	770	116	-2163	38	27	879	247	96	.	.	39	.	22	211	.	.	167	73	100	536	-96	585	385	98	.	.	-438	148	1202	47	377	88	-235	188	233	274	1596	27	-563	62	211	84	.	.	77	494	.	.	100	98	-25	.	.	.	70	79	92	133	-6	3990	639	68	-1	22329	-139	339	398	115	690	49	-314	190	.	.	.	.	-44	.	-100	218	-23	147	592	49	-605	82	271	123	289	62	-53	77	22	264	198	161	2416	49	242	136	456	33	728	26	697	34	1264	25	711	30	709	46	327	68	235	83	40	993	36	652	577	43	741	38	-9	1820	45	.	34	.	.	.	36	.	.	.	.	.	-25	.	-105	.	.	.	-220	92	.	.	111	.	1338	32	988	39	2126	24	-22	1115	148	56	-312	63	64	292	89	274	.	.	-228	.	.	.	.	.	17588	17
outside	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	-717	61	-1041	61	131	176	-1750	34	431	63	-474	103	-596	147	-1395	44	-3399	29	-899	46	-312	83	-3	1635	-245	100	-5	.	-379	88	-755	70	-1177	47	-1064	65	1	478	258	92	697	57	644	50	781	49	726	58	365	98	-1048	48	-1110	46	-1342	46	-1523	50	95	107	328	52	-221	54	46	349	-533	52	553	57	69	271	-569	75	-138	235	469	48	269	75	20	1236	-120	204	-417	85	-222	139	-355	73	-713	60	68	135	40	517	-157	161	-117	101	-728	68	-271	66	-625	72	58	81	74	84	-135	91	.	.	.	.	.	.	.	.	31	83	.	.	89	72	122	76	118	107	123	54	332	40	275	52	-110	374	-290	125	3	8870	-265	84	-260	70	288	59	159	129	21	882	-338	52	13	651	-199	112	-131	66	-955	69	284	58	521	58	74	208	45	227	-70	328	-686	62	-181	164	-170	175	-1068	39	-477	84	-238	150	.	.	-21370	15
	fir	3	5131	-27	204	81	75	-322	77	129	67	234	67	128	77	3	11832	-141	441	-15	1643	28	63	63	63	120	54	.	.	65	78	140	73	-439	72	62	207	4	100	67	76	76	70	38	113	-10	280	205	66	.	.	971	33	270	93	224	163	22	1116	-128	131	370	49	104	77	81	161	711	37	10	290	-164	120	193	62	156	95	.	.	-18	109	113	54	31	310	108	75	119	173	-101	174	-141	61	-104	131	68	75	-42	244	61	157	210	83	63	235	145	75	.	.	.	.	59	100	.	.	.	.	.	.	.	.	.	.	.	.	16	140	.	.	-2	100	100	60	11	71	240	56	128	68	56	100	441	32	-56	285	-19	1024	143	67	196	47	190	49	163	73	-9	1968	121	117	-112	188	41	131	.	.	46	69	197	67	99	62	1	10526	-165	97	-303	85	56	126	45	80	19	100	-61	197	.	.	5466	26
	pine	-55	54	-342	58	-61	65	-27	122	.	.	-13	100	-19	196	6	100	-191	61	-13	602	-14	166	-17	91	19	102	.	.	8	100	-140	100	.	.	-144	85	-51	70	.	.	-14	287	-227	69	3	100	94	117	-25	315	-72	98	.	.	50	68	.	.	-19	100	.	.	.	.	.	.	.	.	4	100	70	100	.	.	10	100	.	.	.	.	.	.	.	.	-114	88	-30	85	-6	485	-30	93	-59	60	25	100	-4	100	.	.	-2	1097	-43	129	-45	86	.	.	.	.	14	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	26	85	5	100	.	.	.	.	.	.	12	85	2	100	.	.	-14	100	.	.	3	74	.	.	-91	84	.	.	.	.	6	100	.	.	30	221	-22	177	-42	108	.	.	.	.	-81	100	-26	143	-165	50	-54	132	-110	71	-56	85	.	.	-2052	23
	larch	9	338	-15	151	65	77	-125	62	.	.	.	.	-83	120	-77	71	-76	105	.	.	.	.	.	.	-4	145	.	.	.	.	-27	301	.	.	-42	153	.	.	8	100	-87	146	-39	79	154	58	83	108	364	42	3	100	-17	130	12	79	1	100	.	.	.	.	.	.	3	100	.	.	.	.	.	.	18	100	4	100	.	.	-40	66	-13	100	.	.	-26	131	.	.	.	.	20	100	.	.	.	.	.	.	.	.	.	.	-14	100	27	100	.	.	24	88	67	67	49	100	.	.	5	100	156	58	25	75	.	.	.	.	.	.	.	.	113	67	.	.	20	100	.	.	66	100	.	.	22	100	.	.	.	.	-13	100	.	.	2	1015	.	.	21	100	.	.	68	100	754	37	300	48	-16	318	.	.	11	100	6	100	20	89	.	.	-39	100	8	100	-49	166	.	.	1704	29
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	40	94	27	643	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	7	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-20	205	16	79	-2	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	68	271
	other conifers	34	84	.	.	38	100	84	72	.	.	5	100	.	.	.	.	212	79	2	100	.	.	.	.	.	.	165	.	-1	100	.	.	.	.	.	.	.	.	1	100	4	100	.	.	.	.	.	.	15	47	.	.	17	94	149	77	2	100	.	.	.	.	2	100	.	.	.	.	.	.	.	.	7	100	180	100	5	100	.	.	.	.	.	.	53	100	6	100	4	100	29	76	.	.	.	.	.	.	.	.	.	.	.	.	0	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	100	.	.	-1	100	.	.	4	100	.	.	6	100	.	.	.	.	43	100	19	68	.	.	.	.	.	.	.	.	.	.	-97	100	.	.	6	100	.	.	.	.	-11	100	.	.	1	71	.	.	.	.	-6	356	0	9474	.	.	.	.	.	.	.	.	.	.	976	36
	beech	-999	43	-157	120	187	77	-129	180	51	82	-24	532	-332	87	-15	1744	-1404	40	229	121	-462	70	-77	199	-57	250	.	.	46	261	-25	398	21	755	134	214	.	.	14	500	-31	210	96	125	-31	80	27	81	.	.	-406	97	95	280	216	70	80	61	29	234	-52	141	-35	195	-6	1949	17	584	139	58	25	71	75	102	207	53	-348	72	-8	907	82	239	-54	133	411	42	157	84	-389	71	-25	770	-106	124	93	71	.	.	148	70	160	62	72	56	-97	119	.	.	.	.	.	.	63	83	67	60	14	100	.	.	16	82	.	.	288	57	.	.	13	100	220	58	-18	234	12	100	91	59	36	100	40	199	-16	61	-204	45	134	45	-107	121	-1	15382	166	57	-13	907	-27	267	62	143	18	524	.	.	.	.	-53	81	20	77	51	130	251	49	-318	73	-48	370	124	58	-56	267	138	72	.	.	-1496	95
	maple	-77	118	77	65	17	141	-53	76	8	100	48	106	-18	256	174	55	224	41	68	94	69	72	-43	95	20	130	.	.	25	77	5	288	76	50	48	62	.	.	69	75	84	56	23	69	17	72	5	111	3	100	139	37	96	50	13	169	39	144	83	67	46	77	38	95	60	64	17	84	26	110	.	.	3	275	-51	146	19	86	.	.	19	59	29	96	82	52	98	45	47	121	-13	223	10	224	3	1833	-11	86	18	71	97	52	33	150	39	93	.	.	.	.	.	.	.	.	-18	100	3	109	2	100	2	100	5	100	47	65	.	.	1	100	-31	94	5	1011	6	100	15	203	2	100	71	49	10	100	20	69	9	92	58	40	24	86	66	57	34	80	.	.	.	.	60	75	9	100	0	100	96	77	.	.	55	50	14	134	86	61	51	68	179	66	-34	119	172	59	.	.	2865	13
	ash	-27	343	-75	156	-82	87	-28	200	.	.	-40	195	-68	67	-25	307	233	48	1	2403	-113	62	27	52	17	140	.	.	67	65	162	89	165	47	60	114	1	100	-142	88	9	210	-2	502	-17	144	11	147	.	.	43	295	-151	113	-37	139	-22	92	2	1140	4	186	2	100	3	100	6	100	191	93	.	.	-1	1173	186	96	-8	545	22	100	65	160	-1	100	81	70	114	47	11	76	10	243	-3	1092	39	77	.	.	-20	100	39	142	-120	93	59	140	4	100	.	.	.	.	.	.	2	100	86	85	.	.	12	100	9	100	78	78	.	.	.	.	-17	512	11	263	.	.	59	99	15	60	-33	128	-45	100	9	77	8	100	-86	74	-72	86	105	70	52	62	-87	99	.	.	-124	103	18	174	21	70	18	217	-52	100	99	68	-30	104	-43	158	100	80	2	3850	-37	93	-66	87	.	.	662	92
	oak	174	72	1	2187	-59	100	31	223	.	.	.	.	3	100	19	71	-27	435	.	.	-66	71	2	100	27	145	.	.	-24	86	.	.	31	98	63	50	-194	95	.	.	.	.	21	100	.	.	.	.	.	.	24	319	-77	71	15	300	-43	100	-10	128	.	.	7	100	.	.	.	.	2	100	.	.	.	.	13	100	-34	100	.	.	-3	732	-10	100	-78	96	13	100	-8	103	19	88	27	75	.	.	.	.	.	.	-17	124	163	122	-57	127	.	.	.	.	.	.	-5	100	-5	114	74	92	4	100	18	72	-2	100	25	100	.	.	.	.	8	90	6	100	.	.	.	.	2	100	0	625	-138	79	5	89	.	.	15	578	15	100	-87	75	53	99	-10	100	41	100	38	100	3	139	56	77	37	64	.	.	-57	80	20	100	-12	100	-75	120	1	4509	-39	124	15	185	.	.	-48	926
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	80	83	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	82	60	-37	76	30	183	-182	51	207	60	.	.	22	78	68	97	.	.	.	.	.	.	.	.	6	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-1	100	.	.	.	.	.	.	.	.	.	.	.	.	-7	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	274	73
	other broadleaves	56	107	-67	131	17	427	17	111	-2	100	14	90	3	2341	23	138	44	266	0	81387	-63	79	2	346	-2	413	.	.	-28	100	117	61	21	112	120	67	5	104	-21	96	22	140	-28	123	79	163	-60	158	40	182	90	65	32	117	32	76	12	80	-28	100	5	141	-16	100	-21	72	-5	129	32	60	.	.	9	71	3	100	-57	58	-31	79	-7	932	1	262	10	198	72	90	-35	77	16	186	-65	63	84	56	-1	559	.	.	-69	85	95	50	-55	80	9	75	112	94	6	123	11	100	2	2598	284	54	4	680	79	72	5	890	7	64	.	.	4	203	-31	63	15	1414	1	100	-6	439	155	104	23	88	-4	133	2	130	13	78	26	95	3	300	-28	65	-33	123	17	189	0	100	0	1566	18	134	59	58	98	81	-14	138	62	68	138	72	1	2711	3	766	-14	242	1	984	24	217	.	.	1468	35
	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	-1600	45	-1646	45	334	97	-2302	32	617	53	-250	244	-983	105	-1287	71	-4525	29	-628	103	-933	49	-46	428	-106	259	160	.	-222	160	-524	122	-1301	63	-764	99	-233	77	254	112	766	57	527	76	975	44	1210	42	788	63	-258	293	-846	61	-668	113	-1432	57	24	914	702	38	-118	110	166	147	212	193	957	43	0	81593	-264	164	568	93	46	829	194	116	277	156	-125	235	110	425	327	148	-831	61	-827	62	-232	105	351	76	-214	115	91	226	-311	165	-21	1585	-610	84	72	69	292	55	-19	735	148	59	-133	83	673	31	165	62	207	51	85	82	549	52	122	76	163	70	490	53	373	72	554	49	177	264	98	444	566	56	-492	66	-461	79	595	36	252	109	180	169	-139	210	97	315	-158	225	-134	224	-853	74	1086	36	997	40	400	66	98	120	152	183	-540	100	-775	72	-249	174	-824	58	-724	59	-123	363	.	.	-11483	36
total	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	-717	61	-1041	61	131	176	-1750	34	568	59	-681	76	-878	134	-2952	28	-3615	28	-986	43	-312	83	1	5388	-222	111	-5	.	-271	132	-907	76	-1563	47	-613	120	1	478	-381	160	1835	36	871	52	405	145	15	4911	801	59	-1106	46	-1091	47	-1342	46	-1830	44	95	107	397	46	-270	48	46	349	-515	53	586	55	139	184	-168	285	-214	157	28	1576	408	102	108	229	-352	150	-417	85	-222	139	-407	65	-877	52	31	316	202	125	-765	60	-45	459	-583	86	-318	58	-646	70	116	254	1678	58	-215	147	.	.	39	83	17	100	147	53	34	77	159	76	233	47	340	62	-70	555	119	148	702	31	472	40	-191	216	-289	126	0	811360	-265	84	-260	70	288	59	159	129	21	882	-312	57	13	651	-340	74	-131	66	-936	70	1086	31	769	53	1254	34	-105	202	19	1271	-779	56	-75	423	88	404	-1068	39	-641	67	-238	150	.	.	-19559	20
	fir	3	5131	-27	204	81	75	-322	77	207	55	419	64	775	31	-897	68	-156	403	22	1207	28	63	63	63	107	62	.	.	140	65	208	58	-486	78	-3	10417	4	100	115	67	125	64	140	54	12	310	309	49	0	0	760	49	294	96	224	163	76	366	-128	131	367	51	123	67	81	161	711	37	34	228	-166	118	464	38	209	114	-22	267	-14	725	461	54	-11	1806	108	75	119	173	-93	189	-141	61	-76	181	400	56	-93	218	10	1794	227	79	76	195	145	75	18	100	130	56	59	100	.	.	.	.	12	100	38	344	29	161	160	69	89	171	.	.	106	78	118	99	145	100	551	41	92	102	56	100	432	32	-56	285	-19	1024	143	67	196	47	190	49	78	187	-9	1968	109	131	-112	188	119	80	78	161	158	48	518	37	127	79	1	10526	-189	85	-267	101	53	156	45	80	19	100	-61	197	.	.	8170	21
	pine	-55	54	-342	58	-61	65	-27	122	.	.	-13	100	-107	78	32	184	-191	61	25	342	-14	166	-17	91	4	536	.	.	8	100	-140	100	.	.	-170	74	-51	70	.	.	6	699	-186	86	3	100	96	119	-20	429	-126	68	18	100	50	68	.	.	-19	100	14	100	.	.	.	.	32	100	4	100	70	100	27	100	10	100	.	.	.	.	.	.	5	100	-114	88	-30	85	-6	485	-72	70	-59	60	25	100	-13	75	.	.	-7	377	-43	129	-45	86	-16	100	-46	70	14	100	.	.	.	.	.	.	.	.	.	.	10	100	.	.	.	.	25	104	5	100	.	.	.	.	.	.	12	85	2	100	.	.	-14	100	.	.	3	74	.	.	-91	84	.	.	.	.	6	100	.	.	-47	309	99	73	-28	265	.	.	-20	100	-79	102	-25	151	-165	50	-54	132	-142	59	-56	85	.	.	-2104	24
	larch	9	338	-15	151	65	77	-125	62	.	.	.	.	-124	86	-77	71	-76	105	.	.	.	.	.	.	-4	145	.	.	.	.	-27	301	.	.	-42	153	.	.	8	100	-102	137	-73	101	123	74	338	37	1184	22	3	100	-17	130	12	79	1	100	.	.	.	.	.	.	3	100	.	.	.	.	.	.	18	100	4	100	25	100	-84	92	-13	100	.	.	-26	131	.	.	.	.	20	100	.	.	.	.	.	.	12	100	10	100	-14	100	27	100	76	55	192	42	213	45	84	70	.	.	13	139	623	29	83	57	72	100	.	.	.	.	-18	100	70	156	.	.	20	100	.	.	66	100	.	.	22	100	.	.	.	.	-13	100	.	.	2	1015	.	.	21	100	.	.	68	100	1017	32	650	31	152	91	-19	100	11	100	6	100	20	89	.	.	-39	100	8	100	-49	166	.	.	4389	15
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	-1	546	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	9	100	.	.	.	.	71	64	102	176	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	7	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	132	69	25	185	-2	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	344	62
	other conifers	34	84	.	.	38	100	84	72	.	.	10	71	1	100	.	.	235	72	3	71	.	.	.	.	.	.	165	.	-1	100	.	.	.	.	.	.	.	.	1	100	4	100	.	.	.	.	6	100	16	46	10	72	16	101	149	77	2	100	.	.	.	.	2	100	.	.	.	.	.	.	.	.	7	100	187	96	10	71	0	666	2	89	.	.	53	100	6	100	4	100	29	76	.	.	.	.	.	.	2	100	.	.	.	.	1	133	.	.	.	.	.	.	.	.	.	.	.	.	69	100	1	100	.	.	-1	100	.	.	4	100	.	.	6	100	.	.	.	.	43	100	19	68	.	.	5	100	.	.	.	.	.	.	-97	100	.	.	6	100	.	.	.	.	-11	100	4	126	1	114	.	.	.	.	-2	933	22	86	6	76	.	.	.	.	.	.	.	.	1150	31
	beech	-999	43	-157	120	187	77	-129	180	115	60	-3	4812	26	1349	176	204	-1200	48	373	83	-462	70	-30	531	-35	442	.	.	52	232	12	1161	230	82	138	207	.	.	35	728	-32	284	120	103	-31	80	250	49	.	.	-363	115	205	134	216	70	300	43	29	234	-22	340	-37	183	-6	1949	27	356	139	59	42	59	-138	212	284	41	-206	128	326	57	234	92	-168	133	411	42	157	84	-389	71	-7	2796	-87	162	138	59	48	88	312	47	191	54	89	51	-29	473	.	.	77	65	.	.	362	40	632	28	299	37	418	31	458	32	84	186	368	47	.	.	130	52	199	64	17	315	131	54	85	76	62	71	88	106	-16	61	-202	45	134	45	-107	121	-1	15382	130	79	-13	907	-65	173	62	143	26	368	.	.	24	89	229	51	97	105	44	158	83	203	-316	74	-160	126	124	58	-53	282	138	72	.	.	3903	42
	maple	-77	118	77	65	17	141	-53	76	0	60556	43	120	117	93	248	42	224	41	158	48	69	72	-32	135	43	83	.	.	25	77	35	73	171	35	78	55	.	.	127	65	97	49	38	57	51	71	64	54	3	100	67	115	114	45	13	169	93	71	83	67	69	57	46	81	60	64	23	66	37	89	-74	98	73	106	-41	195	115	101	-17	247	116	43	70	108	82	52	98	45	47	121	-1	3950	51	87	33	154	-4	451	62	77	148	51	31	160	20	207	33	100	46	100	10	100	-1	294	-9	217	34	68	9	50	35	98	9	62	62	55	10	77	1	100	6	593	13	436	75	75	15	203	9	78	70	50	10	100	22	65	9	92	58	40	24	88	57	69	34	80	31	100	.	.	64	70	9	100	41	71	186	47	14	172	83	46	6	586	74	94	15	357	179	66	-34	119	172	59	.	.	4419	11
	ash	-27	343	-75	156	-82	87	-28	200	.	.	12	788	-33	164	-56	187	238	48	13	171	-113	62	13	147	27	95	.	.	67	65	237	86	196	42	66	121	1	100	-91	152	8	239	-2	461	-22	115	58	56	.	.	-171	120	-145	119	-37	139	-5	494	2	1140	-29	119	2	100	3	100	6	100	201	88	.	.	84	76	113	166	32	187	26	148	68	154	46	108	81	70	114	47	11	76	37	93	-85	100	56	116	9	76	59	107	66	95	-120	93	52	158	4	100	190	100	2	100	16	71	0	5569	130	62	100	73	38	82	51	50	95	66	39	74	.	.	43	243	28	114	35	107	163	73	26	55	-33	128	-45	100	9	77	8	100	-86	74	-80	78	105	70	52	62	-142	70	.	.	-124	103	40	87	40	64	68	80	-17	345	147	55	-75	72	-139	75	75	111	2	3850	-72	68	-66	87	.	.	1512	49
	oak	174	72	1	2187	-59	100	31	223	.	.	.	.	4	88	19	71	8	1599	.	.	-66	71	2	100	-2	2151	.	.	-24	86	19	100	31	98	63	50	-194	95	.	.	.	.	21	100	.	.	-1	100	23	100	5	1482	-77	71	15	300	-43	100	-10	128	.	.	7	100	.	.	.	.	2	100	.	.	.	.	13	100	-36	94	.	.	-3	732	-10	100	-78	96	13	100	-8	103	19	88	27	75	6	100	.	.	.	.	-4	531	131	154	-53	138	.	.	.	.	.	.	21	117	57	70	88	97	-44	106	51	65	36	59	21	121	.	.	14	100	8	90	6	100	.	.	4	1190	2	100	0	625	-138	79	33	87	.	.	15	578	15	100	-87	75	53	99	-10	100	41	100	41	93	30	66	63	69	36	69	.	.	-57	80	40	62	-11	101	-75	120	1	4509	-39	124	15	185	.	.	192	240
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	177	51	4	74	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-2	100	124	92	58	148	46	155	-213	54	264	69	98	72	54	145	141	139	.	.	.	.	.	.	.	.	6	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-1	100	.	.	.	.	.	.	.	.	-3	100	.	.	0	12075	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	758	47
	other broadleaves	56	107	-67	131	17	427	17	111	-5	73	34	69	8	1096	57	111	36	333	12	182	-63	79	-8	165	-2	785	.	.	-51	65	138	55	25	110	104	78	5	104	2	1430	12	307	-25	140	198	76	61	221	271	77	99	61	48	86	32	76	50	73	-28	100	6	117	-16	100	-21	72	-2	372	47	47	-17	99	7	162	3	100	-39	91	-52	87	-6	1132	-18	232	10	198	72	90	-34	78	67	76	-57	74	83	65	0	1329	-48	63	-69	85	94	51	-60	74	40	101	316	57	75	90	75	69	90	115	513	36	-30	221	136	74	72	97	9	322	-33	100	11	89	-43	50	27	794	11	82	0	8043	155	104	23	88	-4	133	2	130	13	78	26	95	-13	138	-28	65	-33	123	12	266	0	100	0	1566	94	62	113	44	112	81	-23	103	72	60	138	72	5	844	3	766	-14	242	1	984	24	217	.	.	2930	22
	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	-1600	45	-1646	45	334	97	-2302	32	885	47	-178	391	-212	641	-3450	36	-4498	29	-381	181	-933	49	-8	2660	-84	333	160	.	-55	681	-424	196	-1398	71	-379	222	-233	77	-184	383	1967	36	904	57	739	83	1443	56	2384	28	-820	101	-635	86	-668	113	-1355	66	24	914	802	35	-143	92	166	147	283	146	1049	41	-5	7191	375	164	567	103	-94	647	593	86	967	57	-439	151	110	425	327	148	-875	58	-927	60	-255	96	942	42	-819	67	362	108	-22	2511	-74	461	-587	87	270	120	2708	44	223	160	604	29	595	37	1369	23	1430	23	918	26	794	42	876	41	357	60	203	204	525	66	950	38	1295	30	168	294	143	307	601	53	-492	66	-425	86	595	36	252	109	155	197	-244	127	97	315	-378	108	-134	224	-742	86	2424	24	1985	28	2527	23	75	362	301	97	-852	67	-711	83	-160	310	-824	58	-952	51	-123	363	.	.	6104	82

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. 2285950. Birmensdorf, Swiss Federal Research Institute WSL

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