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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NFI5
volume of deadwood (stemwood)
main tree species · diameter at breast height (10 classes)
regional demarcation: canton
unit: 1000 m³
evaluation area: accessible forest without shrub forest NFI4/NFI5
grid: 1.4 km grid, subgrids 1-5
state 2018/26
		canton
		AG		AI		AR		BE		BL/BS		FR		GE		GL		GR		JU		LU		NE		NW		OW		SG		SH		SO		SZ		TG		TI		UR		VD		VS		ZG		ZH		Switzerland
main tree species	diameter at breast height (10 classes)	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	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	>100 cm	0	.	0	.	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	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
spruce	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	18	50	23	41	10	52	282	15	13	59	76	27	0	0	23	44	266	14	37	54	110	30	26	35	16	70	28	41	104	27	5	62	13	73	56	38	21	56	32	33	28	46	126	21	251	19	7	55	50	63	1624	6
	21-30 cm	38	52	5	100	83	38	521	19	15	73	155	31	0	.	70	49	607	16	14	100	247	41	12	100	37	51	42	48	97	32	24	61	46	46	134	56	48	56	81	44	113	32	238	34	272	22	6	100	83	59	2991	8
	31-40 cm	13	100	14	100	37	61	1021	16	18	100	131	43	0	.	85	50	759	19	148	66	178	27	43	61	23	59	130	51	181	35	20	71	32	74	90	48	54	82	94	35	94	47	265	30	665	18	44	77	56	45	4195	8
	41-50 cm	56	51	28	71	19	100	789	18	13	100	245	28	0	.	39	73	765	19	27	71	162	35	34	71	38	100	158	41	214	31	139	81	27	71	138	51	39	71	124	32	39	58	359	25	476	17	0	0	39	71	3966	8
	51-60 cm	46	100	20	100	103	82	790	20	0	0	158	61	0	.	70	76	850	19	40	71	121	52	47	71	0	0	43	74	154	39	45	100	0	0	208	41	23	100	208	56	101	45	226	40	478	26	18	100	190	47	3940	9
	61-70 cm	0	0	0	0	31	100	102	51	0	0	68	73	0	.	32	100	229	34	29	100	273	43	0	0	0	0	76	58	76	58	39	100	0	0	0	0	34	100	136	70	101	50	45	71	163	38	0	0	68	100	1503	16
	71-80 cm	0	0	0	0	0	0	132	61	0	0	170	58	0	.	0	0	65	71	45	100	96	71	0	0	0	0	0	0	28	100	0	0	0	0	47	100	0	0	106	62	0	0	34	100	90	58	0	0	41	100	852	23
	81-90 cm	0	0	0	0	0	.	92	71	0	.	0	0	0	.	0	0	28	100	0	0	0	0	0	0	0	.	0	.	44	100	0	.	0	0	0	0	0	0	26	100	0	0	0	0	0	0	0	.	0	0	189	46
	91-100 cm	0	0	0	.	0	.	0	0	0	.	0	0	0	.	49	100	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	0	0	.	0	0	0	0	0	.	0	.	49	100
	>100 cm	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	0	0	0	0	0	0	0	106	100	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	0	0	.	0	0	0	0	0	.	0	.	106	100
	total	172	35	91	40	283	48	3728	12	59	45	1004	29	0	0	368	33	3568	12	340	39	1187	22	267	50	113	47	477	33	898	20	272	66	119	43	673	28	219	46	808	28	477	28	1294	19	2397	13	75	55	527	35	19416	5
fir	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	11	48	2	100	7	74	52	28	8	52	21	41	0	0	3	100	5	87	20	39	17	54	24	49	0	0	14	68	11	46	0	0	12	43	15	65	8	100	3	78	12	48	27	32	8	65	12	78	3	100	296	12
	21-30 cm	13	71	0	0	17	74	219	26	11	100	0	0	0	.	0	.	46	50	49	63	35	51	0	0	7	100	12	71	7	100	0	0	14	72	45	58	0	0	0	0	34	51	25	54	24	71	22	100	26	71	606	15
	31-40 cm	32	75	0	0	34	100	177	29	20	100	62	79	0	.	10	100	42	53	71	42	114	38	53	52	21	71	11	100	37	58	0	0	11	100	23	74	0	0	30	58	30	100	107	44	25	73	0	0	10	100	917	14
	41-50 cm	53	78	0	0	37	71	216	47	28	71	15	100	0	.	0	0	40	58	58	71	141	36	13	100	15	100	0	0	111	50	0	0	15	100	67	51	0	0	49	58	31	73	48	58	17	100	0	0	28	71	980	16
	51-60 cm	25	100	0	0	0	0	181	39	0	0	88	58	0	.	0	0	75	58	44	71	29	100	0	0	0	0	23	100	0	0	0	.	0	0	0	0	0	0	0	0	17	100	68	58	43	71	25	100	20	100	638	20
	61-70 cm	68	71	0	0	0	0	126	50	0	0	62	100	0	.	0	.	70	71	41	100	248	48	0	0	0	0	32	100	0	0	0	0	96	58	0	0	0	0	0	0	37	100	109	58	38	100	0	.	0	0	928	21
	71-80 cm	0	0	0	0	0	0	183	59	0	0	0	0	0	.	0	0	0	0	42	100	41	100	0	0	0	.	0	0	135	58	0	.	0	0	0	0	0	0	0	0	0	.	39	100	0	0	0	.	34	100	474	33
	81-90 cm	0	0	0	.	0	.	0	0	0	.	0	0	0	.	0	0	0	0	0	.	0	0	0	0	0	.	0	0	0	0	0	.	0	0	0	.	0	0	0	0	0	.	55	100	0	.	0	0	0	0	55	100
	91-100 cm	0	.	0	.	0	.	53	100	0	.	0	.	0	.	0	0	0	0	0	0	0	.	0	0	0	.	0	.	0	0	0	.	0	0	0	0	0	0	0	0	0	.	0	0	0	.	0	.	0	.	53	100
	>100 cm	0	.	0	.	0	.	0	0	0	.	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	202	37	2	100	95	59	1208	18	67	54	249	49	0	0	13	80	277	36	325	29	624	29	90	37	43	79	93	68	300	41	0	0	148	40	149	39	8	100	83	53	160	40	476	31	156	41	59	58	121	43	4947	9
pine	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	0	0	.	0	.	19	42	0	0	0	0	0	.	0	.	73	30	8	73	0	0	3	71	0	0	14	93	2	100	0	.	10	59	4	100	0	.	2	100	0	.	2	100	104	23	0	.	8	71	248	15
	21-30 cm	0	0	0	.	0	.	27	62	10	100	16	100	0	.	0	.	104	36	33	72	0	0	0	.	0	.	0	0	12	72	0	0	19	77	0	0	0	0	7	100	5	100	26	100	112	28	0	.	17	71	388	18
	31-40 cm	0	0	0	.	0	.	67	49	33	60	0	0	0	0	0	.	85	38	0	0	0	0	11	100	0	.	0	0	0	0	29	58	32	76	19	81	0	0	26	71	0	0	25	58	127	31	0	.	26	73	480	16
	41-50 cm	0	.	0	.	0	.	56	51	10	100	0	0	14	100	0	.	34	58	18	100	0	0	11	100	0	.	0	0	10	100	0	0	22	100	0	0	16	100	0	0	0	0	0	0	51	53	0	.	38	58	280	23
	51-60 cm	0	0	0	.	0	.	54	58	0	0	0	0	0	.	0	.	46	58	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	0	0	.	0	0	11	100	0	0	0	.	21	100	0	.	21	100	153	34
	61-70 cm	0	.	0	.	0	.	0	0	0	0	0	0	0	.	0	.	29	100	0	.	0	0	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	0	0	.	0	.	0	0	0	.	0	.	29	100
	71-80 cm	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	0	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	0
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	0
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0
	>100 cm	0	.	0	.	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	0	0	0	.	0	.	224	30	53	51	16	100	14	100	0	.	370	25	58	55	0	0	25	93	0	0	14	93	23	73	29	58	83	58	23	69	16	100	45	57	5	100	53	57	414	22	0	.	110	47	1577	11
larch	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	0	0	.	0	.	4	100	0	.	0	0	0	.	0	.	71	26	0	.	0	0	0	.	0	.	2	100	10	63	0	.	0	.	0	.	0	0	27	31	0	.	10	62	104	23	0	.	0	0	227	15
	21-30 cm	0	0	0	.	0	.	0	0	0	.	0	0	0	.	0	.	165	28	0	.	0	0	0	.	0	.	0	0	0	0	0	0	0	.	0	.	7	100	28	39	0	.	0	0	198	27	0	.	0	0	398	18
	31-40 cm	0	0	0	.	0	.	29	100	0	.	8	100	0	.	0	.	158	28	0	.	0	.	0	.	0	.	0	.	0	0	0	0	0	.	0	.	0	.	19	100	0	.	12	100	153	30	0	.	0	0	379	19
	41-50 cm	0	0	0	.	0	.	0	0	0	0	0	.	0	.	0	.	159	38	0	.	0	0	0	.	0	.	0	.	9	100	0	0	0	.	0	.	0	0	41	50	0	.	13	100	177	30	0	.	0	0	399	21
	51-60 cm	0	0	0	.	0	.	0	0	0	.	0	.	0	.	0	.	128	39	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	0	0	0	0	.	49	58	0	.	0	0	90	46	0	.	0	0	267	26
	61-70 cm	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	98	50	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	12	100	0	.	0	0	71	58	0	.	0	0	181	36
	71-80 cm	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	0	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	0	0	0	0	0	0	.	0	0
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	76	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	100	0	.	0	.	0	0	0	.	0	.	115	58
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	.	0	0
	>100 cm	0	.	0	.	0	.	0	.	0	.	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	0	0	0	.	0	.	33	88	0	0	8	100	0	.	0	0	855	20	0	0	0	0	0	0	0	.	2	100	19	68	0	0	0	0	0	0	7	100	215	27	0	.	34	54	793	17	0	0	0	0	1966	12
Arolla pine	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	7	52	0	.	0	.	20	38
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	25	52	0	.	0	.	31	46
	31-40 cm	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	6	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	58	0	.	0	.	28	50
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	100	0	.	0	.	16	71
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	100	0	.	0	.	39	58
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	0
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	0
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	100	0	.	0	.	29	100
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	100	0	.	0	.	26	100
	>100 cm	0	.	0	.	0	.	0	.	0	.	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	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	61	47	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	127	41	0	.	0	.	188	32
other conifers	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	0	0	.	0	0	6	68	0	0	0	.	0	.	0	0	13	49	0	0	0	0	0	.	0	.	0	0	0	0	0	.	0	0	0	0	0	0	0	0	3	100	3	74	1	100	0	.	0	0	26	32
	21-30 cm	0	0	0	.	0	0	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	0	5	100	0	.	0	0	0	.	0	.	0	.	0	.	0	0	0	0	0	.	0	0	5	100
	31-40 cm	0	0	0	.	0	.	0	0	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	.	0	.	0	0	11	100	0	.	0	0	11	100
	41-50 cm	0	0	0	.	0	.	0	0	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	.	0	0
	51-60 cm	0	0	0	.	0	.	0	0	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	0	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	0
	61-70 cm	0	0	0	.	0	.	0	0	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	0
	71-80 cm	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0
	81-90 cm	0	.	0	.	0	.	0	0	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	>100 cm	0	.	0	.	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	0	0	0	.	0	0	6	68	0	0	0	.	0	.	0	0	13	49	0	0	0	0	0	0	0	.	0	0	5	100	0	0	0	0	0	0	0	0	0	0	3	100	3	74	12	92	0	.	0	0	41	35
beech	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	10	56	2	78	2	100	42	27	14	63	26	43	0	.	32	50	11	43	42	54	20	36	8	67	2	100	19	63	23	35	21	48	23	47	5	61	2	100	56	30	3	72	61	23	16	48	0	0	10	62	451	10
	21-30 cm	22	58	0	0	0	0	53	52	15	71	17	78	0	.	21	60	19	70	22	100	39	68	6	100	8	100	14	75	65	33	10	100	91	44	22	65	0	0	53	39	0	0	86	46	18	73	0	0	28	51	611	14
	31-40 cm	23	100	0	0	26	71	100	49	62	48	57	47	0	.	10	71	10	71	17	71	62	51	11	100	7	100	0	0	96	46	9	100	35	81	24	71	0	0	57	43	0	0	65	54	11	100	0	0	14	71	697	15
	41-50 cm	41	59	0	0	11	100	93	34	33	71	21	71	0	.	7	100	8	100	24	71	48	59	14	100	0	0	26	75	43	52	0	0	58	46	30	72	0	0	43	51	6	100	24	71	0	0	12	100	34	71	575	15
	51-60 cm	125	49	0	.	0	0	20	100	83	71	0	0	0	.	0	0	32	72	0	0	0	0	20	100	0	0	0	0	66	63	16	100	40	71	0	0	0	0	12	100	0	0	41	74	0	0	0	0	0	0	454	24
	61-70 cm	81	100	0	0	0	0	80	77	29	100	22	100	0	.	0	0	0	0	0	0	0	0	0	.	0	.	0	0	28	100	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	240	47
	71-80 cm	26	100	0	.	0	0	64	71	40	100	0	0	0	.	0	.	20	100	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	.	0	0	150	46
	81-90 cm	0	0	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	0	0	0	0	0	37	100	0	.	0	.	37	100
	91-100 cm	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	0
	>100 cm	0	.	0	.	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	329	37	2	78	39	58	453	25	275	38	143	37	0	.	71	42	99	46	106	39	169	41	59	63	17	63	59	46	320	27	56	44	247	30	82	56	2	100	222	29	9	74	277	28	82	53	12	100	86	35	3215	9
maple	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	2	100	0	0	5	100	21	55	13	54	2	100	0	0	5	77	0	0	12	64	9	61	12	76	0	0	0	0	6	100	2	100	1	100	4	78	5	100	9	56	1	100	4	75	19	51	0	0	8	84	140	18
	21-30 cm	0	0	0	.	0	0	32	58	7	100	0	0	0	.	10	71	0	0	15	72	0	0	0	0	13	100	0	0	23	71	0	0	0	0	0	0	12	100	12	100	0	0	0	0	0	0	0	0	12	71	135	27
	31-40 cm	0	0	0	0	16	100	16	100	0	0	0	0	0	.	0	0	0	0	14	71	9	100	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	12	100	0	0	0	0	0	0	67	43
	41-50 cm	12	100	0	.	0	0	0	0	0	0	0	0	0	.	9	100	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	21	71
	51-60 cm	0	0	0	.	0	.	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	0	0	.	0	.	0	.	0	0	0	.	0	0	0	0	0	0	0	.	0	.	0	0	0	.	0	0	0	0	0	0
	61-70 cm	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	.	0	0	0	0	0	.	0	.	0	0	0	0
	71-80 cm	0	0	0	.	0	.	0	.	0	0	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	0	0	0
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0
	>100 cm	0	.	0	.	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	14	87	0	0	21	80	68	39	20	49	2	100	0	0	25	56	0	0	41	52	18	59	12	76	13	100	0	0	29	60	2	100	1	100	4	78	17	100	21	78	1	100	16	77	19	51	0	0	20	71	363	16
ash	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	32	52	0	.	5	100	25	45	4	100	18	47	1	100	6	79	8	63	41	43	36	42	0	0	5	76	0	0	8	62	4	71	15	58	20	48	4	83	23	54	3	100	18	51	16	65	0	0	19	57	310	14
	21-30 cm	0	0	0	.	25	75	35	76	19	100	17	100	0	0	17	79	23	79	23	73	40	62	0	0	14	100	6	100	34	66	7	100	5	100	35	65	0	0	19	79	0	0	27	51	19	71	0	0	63	48	427	18
	31-40 cm	0	0	0	.	32	71	68	51	0	0	0	0	0	.	24	77	0	0	139	74	0	0	0	.	39	80	0	0	39	50	0	0	10	100	0	0	0	0	16	100	0	0	0	0	0	0	0	0	23	71	390	31
	41-50 cm	33	100	0	.	0	0	28	71	12	100	0	0	0	.	32	72	11	100	53	58	14	100	0	0	0	0	0	0	48	58	0	0	0	0	0	0	36	71	29	71	0	0	10	100	8	100	0	0	31	71	346	22
	51-60 cm	21	100	0	.	0	.	0	0	0	0	28	100	0	.	18	100	0	.	0	0	0	0	0	.	0	0	0	.	0	0	0	0	0	0	0	0	21	100	0	0	0	.	0	0	0	0	0	.	0	0	88	51
	61-70 cm	33	100	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	0	0	.	0	0	0	0	0	0	0	0	0	0	0	0	0	.	0	0	0	.	0	0	0	0	33	100
	71-80 cm	0	0	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	0	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	0
	81-90 cm	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	0
	91-100 cm	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	0
	>100 cm	0	.	0	.	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	118	60	0	.	62	60	156	39	36	65	64	58	1	100	98	55	42	59	255	48	90	44	0	0	58	83	6	100	129	32	11	68	29	47	55	55	61	70	86	47	3	100	55	35	43	43	0	0	136	39	1594	13
oak	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	3	100	0	.	0	.	6	60	0	0	2	100	4	59	0	.	1	100	2	100	5	100	6	82	0	.	0	.	0	0	3	100	5	70	0	.	0	0	33	41	0	0	24	47	6	49	0	.	2	100	103	20
	21-30 cm	0	0	0	.	0	.	0	0	13	100	0	0	12	100	0	.	0	0	15	74	0	0	5	100	0	0	0	.	22	100	0	0	13	78	0	.	0	0	29	51	9	100	14	73	0	0	0	.	0	0	131	29
	31-40 cm	0	0	0	.	0	.	0	0	0	0	8	100	0	0	0	.	0	0	8	100	0	.	0	0	0	.	0	.	0	0	0	0	6	100	0	.	0	0	10	100	0	0	14	100	5	100	0	.	11	100	62	40
	41-50 cm	0	0	0	.	0	.	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	0	0	.	0	.	0	.	0	0	8	100	0	.	0	0	24	73	0	0	0	0	0	0	0	0	0	0	33	60
	51-60 cm	0	0	0	.	0	.	0	0	0	0	0	.	0	0	0	.	0	0	0	0	0	0	0	0	0	.	0	.	0	0	0	.	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	.	0	0	0	0
	61-70 cm	0	0	0	.	0	.	21	100	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	0	21	100	0	.	0	0	0	.	0	.	0	0	42	71
	71-80 cm	0	0	0	.	0	.	0	.	0	.	0	0	0	0	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	0
	81-90 cm	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	.	0	0	0	0
	91-100 cm	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	0
	>100 cm	0	.	0	.	0	.	0	.	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	3	100	0	.	0	.	27	78	13	100	10	84	16	75	0	.	1	100	25	55	5	100	11	89	0	0	0	.	22	100	3	100	32	50	0	0	0	0	118	34	9	100	51	47	11	63	0	0	13	84	370	18
sweet chestnut	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	69	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	476	17	0	.	0	.	7	79	0	.	0	.	511	16
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	226	24	0	.	0	.	0	0	0	.	0	.	230	24
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	23	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	114	38	0	.	0	.	0	0	0	.	0	.	137	35
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	100	32	0	.	0	0	9	100	0	.	0	.	109	30
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	52	46	0	.	0	.	0	0	0	.	0	.	52	46
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	41	58	0	.	0	.	16	100	0	.	0	.	57	50
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	84	53	0	.	0	.	0	0	0	.	0	.	84	53
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	19	100
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	23	100	0	.	0	.	0	0	0	.	0	.	23	100
	>100 cm	0	.	0	.	0	.	0	.	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	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	55	56	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1137	14	0	.	0	0	31	85	0	.	0	.	1223	13
other broadleaves	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	11	54	0	.	0	0	53	27	9	47	46	49	5	100	17	70	134	22	25	42	18	44	13	55	0	0	8	65	26	31	0	0	8	55	40	57	8	58	192	17	36	55	72	29	109	22	4	100	13	39	847	8
	21-30 cm	34	46	0	.	7	71	57	41	23	100	12	76	0	.	0	0	169	30	19	75	8	100	0	0	0	0	10	100	63	52	0	0	26	81	24	51	0	0	204	29	13	73	44	44	42	34	0	.	12	71	767	13
	31-40 cm	7	100	0	.	0	0	0	0	8	100	0	0	0	.	8	100	82	45	47	85	0	0	16	100	0	0	0	0	26	75	0	.	0	0	0	0	0	0	114	43	0	0	57	46	20	58	0	.	0	0	386	22
	41-50 cm	0	0	0	.	0	.	22	100	0	0	12	100	0	.	21	71	27	59	0	0	0	0	0	.	0	0	0	.	0	0	0	0	10	100	0	0	11	100	40	50	0	.	12	100	17	72	0	.	0	0	173	26
	51-60 cm	0	0	0	.	0	0	19	100	0	0	39	100	0	.	16	100	0	0	0	0	0	0	0	.	0	.	0	.	0	0	0	.	0	0	0	0	0	0	0	0	0	.	38	71	0	0	0	.	0	0	112	48
	61-70 cm	0	0	0	.	0	.	19	100	0	.	0	0	0	.	0	0	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	0	0	0	0	0	0	0	0	.	0	.	19	100
	71-80 cm	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	0	0	0
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	0
	>100 cm	0	.	0	.	0	.	0	0	0	.	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	52	39	0	.	7	71	169	32	40	65	110	59	5	100	61	62	413	23	91	50	27	44	28	64	0	0	18	61	115	36	0	0	44	55	64	46	19	77	549	19	49	52	224	27	188	20	4	100	26	43	2303	9
indeterminable	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	1	100	4	53	4	100	1	100	0	.	0	.	19	35	2	100	5	58	0	.	0	.	1	100	13	48	0	.	5	100	0	.	1	100	7	51	0	.	13	45	8	46	0	.	1	100	84	17
	21-30 cm	0	.	0	.	0	.	9	72	0	.	7	100	0	.	0	.	39	56	13	100	13	71	8	100	0	.	0	.	0	.	0	.	11	100	0	.	0	.	0	.	0	.	7	100	19	76	0	.	7	100	134	27
	31-40 cm	0	.	0	.	10	100	81	40	0	.	0	.	0	.	0	.	51	52	0	.	0	.	15	100	0	.	9	100	15	71	0	.	15	100	0	.	0	.	0	.	0	.	0	.	6	100	0	.	21	100	221	24
	41-50 cm	0	.	0	.	0	.	54	59	13	100	0	.	0	.	0	.	33	60	0	.	0	.	0	.	0	.	0	.	9	100	0	.	0	.	0	.	0	.	0	.	22	100	24	73	9	100	0	.	0	.	163	31
	51-60 cm	0	.	0	.	0	.	17	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	71	0	.	0	.	87	45
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	19	100
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	>100 cm	0	.	0	.	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	0	.	0	.	11	93	165	32	16	81	8	88	0	.	0	.	141	30	14	89	18	55	22	74	35	72	10	87	37	51	0	.	31	86	0	.	1	100	7	51	22	100	44	45	95	39	0	.	29	76	708	14
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	87	26	28	41	31	35	515	11	65	28	193	21	10	56	86	31	640	10	189	23	218	20	92	23	23	52	87	32	201	18	35	34	91	26	144	24	50	36	860	11	85	30	360	13	656	11	24	49	115	32	4887	4
	21-30 cm	108	29	5	100	132	29	954	13	113	37	226	25	12	100	119	34	1180	12	201	27	383	29	30	53	79	40	84	32	328	22	41	55	225	27	261	33	67	47	659	14	174	26	468	21	729	14	27	82	248	29	6853	5
	31-40 cm	76	48	14	100	155	44	1558	12	141	32	267	32	0	0	136	37	1216	14	444	39	363	21	148	32	90	42	150	45	394	24	57	41	140	41	156	38	54	82	480	18	124	43	556	20	1045	13	44	77	161	28	7969	5
	41-50 cm	194	34	28	71	67	51	1258	15	109	40	292	26	14	100	109	43	1086	16	180	33	366	25	71	45	52	77	183	37	443	22	139	81	141	37	234	36	103	41	451	17	98	46	488	23	771	15	12	100	169	36	7060	6
	51-60 cm	217	39	20	100	103	82	1081	16	83	71	314	38	0	0	103	56	1159	16	84	50	150	46	67	58	35	72	66	59	220	33	61	78	40	71	208	41	43	71	332	38	118	41	374	28	677	21	43	100	231	40	5830	7
	61-70 cm	182	55	0	0	31	100	349	30	29	100	152	54	0	0	32	100	425	25	71	72	521	37	0	0	0	0	109	51	104	50	39	100	96	58	0	0	34	100	211	48	139	45	154	46	307	28	0	0	68	100	3051	11
	71-80 cm	26	100	0	0	0	0	379	37	40	100	170	58	0	0	0	0	85	59	87	71	137	58	0	0	0	0	0	0	163	51	0	0	0	0	47	100	0	0	190	41	0	0	72	71	90	58	0	0	75	71	1560	17
	81-90 cm	0	0	0	0	0	.	92	71	0	0	0	0	0	.	0	0	104	58	0	0	0	0	0	0	0	.	0	0	44	100	0	.	0	0	0	0	0	0	84	60	0	0	55	100	66	71	0	0	0	0	444	30
	91-100 cm	0	0	0	.	0	.	53	100	0	.	0	0	0	.	49	100	0	0	0	0	0	.	0	0	0	.	0	.	0	0	0	.	0	0	0	0	0	0	23	100	0	.	0	0	26	100	0	.	0	0	152	53
	>100 cm	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	0	0	0	0	0	0	0	106	100	0	.	0	.	0	0	0	.	0	.	0	0	0	0	0	0	0	.	0	0	0	0	0	.	0	.	106	100
	total	891	21	95	39	519	35	6238	9	579	26	1613	21	36	57	635	25	5895	9	1256	20	2138	18	514	31	279	34	679	28	1897	15	372	50	733	21	1049	21	351	35	3291	10	738	23	2526	14	4368	9	149	49	1067	21	37911	3

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. 1306741. Birmensdorf, Swiss Federal Research Institute WSL

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