NFI Results

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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NFI4
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 NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
state 2009/17
		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	16	68	11	52	15	45	236	16	9	54	97	28	0	.	34	44	188	16	15	58	130	28	31	37	10	55	28	39	60	30	9	52	16	64	48	51	14	43	30	37	36	50	107	21	196	20	5	63	31	33	1373	7
	21-30 cm	22	72	13	71	39	52	529	18	41	59	173	32	0	.	74	46	422	20	9	100	299	42	11	100	34	53	29	53	122	33	15	71	47	46	110	71	24	60	46	44	110	33	191	35	298	24	7	100	6	100	2670	9
	31-40 cm	33	58	0	0	60	52	765	19	0	0	147	40	0	.	62	64	532	23	52	64	174	37	0	0	7	100	57	58	132	42	22	71	40	62	101	48	16	100	18	71	97	43	136	32	466	21	32	100	72	51	3021	9
	41-50 cm	74	45	28	71	15	100	801	17	16	100	229	35	0	.	12	100	472	22	32	71	112	50	0	0	47	81	175	43	112	41	35	71	27	71	83	45	0	0	82	47	12	100	286	31	347	21	0	0	132	40	3132	8
	51-60 cm	46	71	0	0	23	100	532	21	0	0	394	44	0	.	116	53	559	23	0	0	90	61	27	100	0	0	50	72	86	52	0	0	0	0	118	45	0	0	30	100	94	50	195	46	236	30	18	100	54	71	2670	11
	61-70 cm	28	100	24	100	0	0	217	39	0	0	87	75	0	.	0	0	221	34	0	0	161	46	0	0	0	0	23	100	130	51	0	0	0	0	29	100	0	0	20	100	24	100	0	0	23	100	0	0	0	0	988	18
	71-80 cm	0	0	0	0	0	.	41	100	0	0	258	77	0	.	0	0	24	100	0	0	90	71	0	0	0	.	0	0	0	0	0	0	0	0	0	0	0	0	61	71	40	100	67	71	0	0	0	.	0	0	580	39
	81-90 cm	0	0	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	27	100	0	.	0	0	34	100	0	.	0	0	89	58
	91-100 cm	0	.	0	.	0	.	0	0	0	.	0	.	0	.	48	100	0	0	0	.	0	0	0	.	0	.	0	.	45	100	0	.	0	.	0	.	0	.	0	0	0	0	0	0	40	100	0	.	0	.	133	58
	>100 cm	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	0	0	0	0	0	0	.	0	.	0	.	0	.	48	100	0	.	0	.	0	0	0	.	0	0	0	.	0	0	0	0	0	.	0	.	48	100
	total	218	32	76	45	152	42	3120	13	66	46	1385	33	0	.	347	34	2446	13	108	47	1056	26	69	49	98	53	363	37	735	23	81	40	129	39	490	32	55	54	315	27	412	29	982	23	1640	14	63	66	295	28	14703	6
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	8	66	0	0	8	51	88	26	2	100	22	43	0	.	6	100	3	73	30	33	15	45	17	51	0	0	16	55	9	64	0	0	19	53	19	55	0	0	4	75	13	60	41	28	9	48	3	100	7	71	339	11
	21-30 cm	0	0	0	0	34	82	148	27	0	0	0	0	0	.	5	100	31	58	64	60	68	41	14	100	7	100	0	0	44	53	0	0	31	59	11	100	0	0	0	0	15	71	17	73	19	72	0	0	26	71	535	16
	31-40 cm	18	100	0	0	20	71	130	42	20	100	37	100	0	.	0	0	26	76	63	48	58	53	0	0	12	100	9	100	15	100	0	0	29	75	51	68	0	0	0	0	28	73	94	44	0	0	0	0	22	100	630	17
	41-50 cm	66	78	0	0	54	71	134	41	31	71	17	100	0	.	0	0	57	50	64	65	148	43	27	71	15	100	0	0	31	72	0	0	29	72	22	100	0	0	33	70	12	100	54	61	0	0	0	0	0	0	794	17
	51-60 cm	25	100	0	0	0	0	154	42	0	0	56	72	0	.	0	0	0	0	0	0	75	59	0	0	0	0	25	100	81	50	0	0	0	0	0	0	0	0	0	0	18	100	25	100	72	75	26	100	22	100	580	22
	61-70 cm	0	0	0	0	0	0	46	100	0	0	37	100	0	.	0	.	65	71	39	100	110	58	0	0	0	0	0	0	0	0	0	.	61	100	0	0	0	0	0	0	0	0	63	100	0	0	0	.	0	0	421	32
	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	54	100	0	.	0	0	0	0	0	0	0	0	0	0	0	0	39	100	0	.	39	100	132	58
	81-90 cm	0	0	0	.	0	.	46	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	.	55	100	0	0	0	.	0	.	101	71
	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	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
	total	117	51	0	0	116	64	798	20	52	58	170	47	0	.	11	71	182	37	261	39	474	29	58	44	34	100	51	55	235	38	0	0	169	47	102	47	0	0	36	64	87	42	349	38	139	49	29	90	116	46	3586	10
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	.	15	54	0	0	2	100	0	.	0	.	41	36	4	100	0	.	5	73	0	.	7	100	0	.	0	0	3	100	0	0	4	100	2	100	0	0	4	73	59	30	0	.	5	100	150	18
	21-30 cm	0	0	0	.	0	.	10	100	8	100	21	71	0	0	0	.	71	36	46	66	0	0	0	0	0	.	0	0	0	.	6	100	26	82	0	0	0	0	6	100	0	0	9	100	87	32	0	.	10	100	300	19
	31-40 cm	19	100	0	.	0	.	52	76	35	70	59	62	0	0	0	.	18	71	10	100	0	0	11	100	0	.	0	0	0	.	0	0	12	100	14	100	0	0	25	71	0	0	9	100	115	33	0	.	30	58	409	20
	41-50 cm	0	0	0	.	0	0	51	58	0	0	0	0	19	100	0	.	22	73	18	100	0	0	12	100	0	.	0	0	0	.	0	0	42	75	0	0	0	0	0	0	0	0	10	100	45	78	0	.	17	100	236	29
	51-60 cm	0	0	0	.	0	.	42	74	0	0	0	0	0	.	0	.	18	100	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	.	13	100	0	.	0	0	73	52
	61-70 cm	0	.	0	.	0	.	0	0	0	.	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	20	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
	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
	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	19	100	0	.	0	0	170	42	44	60	82	63	19	100	0	.	189	30	78	55	0	0	28	93	0	.	7	100	0	0	6	100	83	69	14	100	4	100	33	68	0	0	32	58	319	22	0	.	62	43	1188	13
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	.	25	30	0	.	0	0	0	.	0	.	1	100	6	71	0	.	0	.	0	.	0	0	17	41	0	.	10	62	83	29	0	.	0	0	146	19
	21-30 cm	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	.	75	37	0	.	0	0	0	.	0	.	0	.	0	0	0	0	0	.	0	.	0	0	15	63	0	.	8	100	147	27	0	.	0	.	245	20
	31-40 cm	0	0	0	.	0	.	30	100	0	0	11	100	0	.	0	0	54	48	0	.	0	0	0	.	0	.	0	.	0	0	0	0	0	.	0	.	0	0	8	100	0	.	0	0	117	35	0	.	0	0	219	26
	41-50 cm	0	0	0	.	0	.	0	0	0	0	0	.	0	.	0	.	127	36	0	.	0	.	0	.	0	.	0	.	11	100	0	.	0	0	0	.	0	0	43	64	0	.	18	100	100	40	0	.	0	0	298	23
	51-60 cm	0	0	0	.	0	.	0	0	0	.	0	0	0	.	0	.	51	58	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	0	0	.	0	0	138	39	0	0	0	0	189	32
	61-70 cm	0	0	0	.	0	.	0	0	0	.	28	100	0	.	0	.	69	58	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	0	63	73	0	.	0	0	160	42
	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
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	75	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	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
	>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	.	34	89	0	0	39	77	0	.	0	0	475	25	0	0	0	0	0	0	0	.	1	100	16	85	0	0	0	0	0	0	0	0	123	41	0	.	37	65	648	21	0	0	0	0	1372	14
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	.	10	56	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	3	100	0	.	0	.	13	49
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	6	100	0	.	0	.	10	74
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	71	0	.	0	.	22	58
	41-50 cm	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	9	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	100	0	.	0	.	16	71
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	14	100
	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	.	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	.	32	100	0	.	0	.	32	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	.	43	57	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	64	59	0	.	0	.	107	42
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	0	0	0	.	0	.	0	.	0	0	8	52	0	0	0	0	0	.	0	.	0	.	0	0	0	.	0	0	0	0	0	0	0	.	0	0	5	51	1	100	0	.	0	0	15	35
	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	.	0	.	0	.	0	.	0	0	8	100	0	.	0	0	8	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	.	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	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
	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
	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	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	8	52	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5	51	9	88	0	.	0	0	23	42
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	17	60	1	100	2	100	33	27	14	52	2	71	0	.	5	55	7	51	9	62	14	45	7	71	3	100	15	55	25	31	6	60	19	57	5	71	2	100	30	46	1	72	29	34	5	59	0	0	9	48	261	12
	21-30 cm	14	73	0	0	0	0	58	36	23	71	0	0	0	.	20	54	2	100	10	100	24	59	5	100	0	0	8	71	33	48	0	0	34	58	5	100	5	100	57	46	0	0	69	42	7	71	0	0	41	44	415	15
	31-40 cm	20	71	0	0	13	100	66	48	38	50	34	71	0	.	0	0	6	100	8	100	58	81	0	0	7	100	0	0	21	79	0	0	83	76	17	75	0	0	38	63	0	0	18	71	0	0	0	0	7	100	434	23
	41-50 cm	21	100	0	0	0	0	100	39	29	71	38	58	0	.	0	0	8	100	27	72	72	77	0	0	0	0	21	100	37	59	0	0	23	71	0	0	0	0	29	58	0	0	0	0	0	0	0	0	11	100	417	21
	51-60 cm	85	64	0	0	0	.	14	100	23	100	17	100	0	.	0	0	0	0	24	100	20	100	0	0	0	0	0	0	25	100	20	100	0	0	0	0	0	0	49	60	0	0	17	100	0	0	16	100	22	100	332	27
	61-70 cm	0	0	0	0	0	0	72	58	0	0	0	0	0	.	0	0	0	0	0	0	0	0	0	0	0	.	0	0	30	100	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	102	51
	71-80 cm	0	0	0	.	0	.	43	100	0	0	28	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	71	72
	81-90 cm	0	0	0	.	0	.	0	0	45	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	45	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
	>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	158	49	1	100	16	86	387	23	172	51	119	39	0	.	25	50	23	71	78	43	188	63	12	59	9	77	44	56	171	34	26	85	160	50	27	56	7	78	204	32	1	72	133	31	12	54	16	100	89	37	2078	11
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	5	58	0	0	6	100	19	56	3	100	0	0	0	.	5	100	2	100	2	100	6	71	6	75	2	100	0	0	2	100	2	100	0	0	3	100	0	0	4	71	0	0	9	50	11	52	0	0	11	65	97	20
	21-30 cm	0	0	0	.	0	0	16	58	0	0	0	0	0	.	10	100	0	0	17	72	0	0	0	0	0	0	0	0	14	100	0	0	0	0	0	0	0	0	0	0	0	0	0	0	7	100	0	0	24	58	88	32
	31-40 cm	0	0	0	0	0	0	0	0	0	0	10	100	0	.	0	0	0	0	0	0	0	0	0	0	0	0	0	0	24	75	0	0	0	0	0	0	0	0	0	0	0	0	6	100	0	0	0	0	6	100	47	48
	41-50 cm	12	100	0	.	0	.	0	0	0	0	0	0	0	.	9	100	0	0	0	0	0	0	0	0	0	0	0	0	9	100	0	.	0	0	0	0	0	0	0	.	0	0	0	0	12	100	0	0	0	0	42	50
	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
	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
	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	17	72	0	0	6	100	35	40	3	100	10	100	0	.	24	60	2	100	18	67	6	71	6	75	2	100	0	0	50	50	2	100	0	0	3	100	0	0	4	71	0	0	16	50	29	60	0	0	41	56	274	18
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	3	73	0	.	0	0	4	71	0	0	1	100	0	0	0	0	21	53	6	100	9	51	2	100	3	100	0	0	4	100	0	0	7	71	5	76	5	100	19	60	0	0	7	64	8	60	0	0	6	73	110	20
	21-30 cm	8	100	0	.	11	100	8	100	0	0	5	100	0	0	8	100	6	100	17	71	14	73	0	0	0	0	0	0	10	100	0	0	6	100	0	0	0	0	16	75	0	0	16	72	21	75	0	0	20	73	166	23
	31-40 cm	11	100	0	.	15	100	10	100	0	0	0	0	0	0	7	100	0	0	0	0	0	0	0	0	17	100	0	0	0	0	0	0	0	0	0	0	0	0	7	100	0	0	15	100	0	0	0	0	39	100	121	42
	41-50 cm	0	0	0	.	0	0	26	73	0	0	0	0	0	.	0	0	0	0	0	0	15	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	39	71	80	46
	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	14	100	0	0	0	.	0	.	0	0	0	0	0	0	0	0	14	100
	61-70 cm	32	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	32	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
	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
	>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	53	84	0	.	26	71	48	48	0	0	6	81	0	0	14	100	27	59	24	58	37	52	2	100	21	100	0	0	14	78	0	0	13	61	20	83	5	100	42	47	0	0	39	51	30	64	0	0	104	57	523	19
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	0	0	0	.	0	.	4	100	2	100	3	100	4	71	0	.	1	100	4	100	0	0	3	100	0	.	0	.	0	0	6	73	4	73	0	.	0	0	29	42	0	0	15	48	6	60	0	.	0	0	81	22
	21-30 cm	0	0	0	.	0	.	0	0	15	100	0	0	17	75	0	.	0	0	0	0	0	0	0	0	0	0	0	.	20	100	0	0	0	0	0	.	0	0	14	74	0	0	26	73	0	0	0	.	0	0	92	38
	31-40 cm	0	0	0	.	0	.	0	0	0	0	8	100	0	0	0	.	0	0	27	100	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	47	65
	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	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	26	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	26	100
	61-70 cm	0	0	0	.	0	.	0	0	0	0	0	0	0	0	0	.	0	.	0	.	26	100	0	.	0	.	0	.	0	.	0	0	0	0	0	.	0	0	0	0	0	.	0	0	0	.	0	.	0	0	26	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
	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	.	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	.	4	100	17	89	12	77	47	82	0	.	1	100	31	88	26	100	3	100	0	0	0	.	20	100	6	73	4	73	0	0	0	0	43	43	0	0	42	49	6	60	0	.	11	100	272	25
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	.	20	69	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	323	19	0	.	2	100	6	100	0	.	0	.	351	17
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	134	29	0	.	0	.	0	0	0	.	0	.	143	28
	31-40 cm	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	84	36	0	.	0	.	0	0	0	.	0	.	93	34
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	84	45	0	.	0	0	0	0	0	.	0	.	84	45
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	75	0	.	0	.	0	.	0	.	0	.	22	75
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	71	0	.	0	.	0	0	0	.	0	.	28	71
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	33	70	0	.	0	.	0	.	0	.	0	.	33	70
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	100	0	.	0	.	0	0	0	.	0	.	31	100
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	100	0	.	0	.	0	.	0	.	0	.	25	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	.	0	.	38	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	763	17	0	.	2	100	6	100	0	.	0	.	808	16
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	3	73	1	100	0	0	46	30	9	53	46	42	1	100	10	65	104	22	25	39	28	36	7	61	4	100	21	78	17	48	3	100	4	77	14	62	5	80	119	17	16	70	67	33	71	26	5	100	19	39	649	9
	21-30 cm	25	58	0	.	4	100	20	59	0	0	9	100	0	.	4	100	96	36	28	59	0	0	0	0	0	0	13	100	19	59	0	0	0	0	33	53	0	0	224	26	5	100	19	61	42	38	0	.	10	71	551	14
	31-40 cm	23	71	0	.	0	0	0	0	0	0	0	0	0	.	0	0	70	55	14	71	0	0	0	0	0	0	0	.	19	73	0	0	0	0	0	0	0	0	77	51	6	100	13	100	21	73	0	0	9	100	252	25
	41-50 cm	8	100	0	.	0	.	0	0	0	0	0	0	0	.	11	100	20	71	0	0	0	0	0	.	0	.	0	.	0	0	0	.	12	100	0	0	0	0	20	71	0	.	34	60	9	100	0	.	12	100	126	29
	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	.	18	100	0	0	0	.	0	.	18	100
	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	.	31	100	0	.	0	.	0	.	0	0	0	.	0	.	0	0	31	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
	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	57	45	1	100	4	100	67	31	9	53	55	39	1	100	25	52	290	25	68	36	28	36	7	61	4	100	35	61	55	41	3	100	16	78	78	51	5	80	441	19	27	51	151	27	142	24	5	100	51	42	1626	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	4	100	0	.	2	71	10	47	4	100	3	77	0	.	0	.	14	48	2	100	8	62	0	.	0	.	0	.	2	100	0	.	5	100	0	.	1	100	13	64	2	100	11	50	7	47	0	.	2	100	89	19
	21-30 cm	0	.	0	.	0	.	13	71	0	.	10	100	0	.	9	100	12	73	0	.	13	76	9	100	0	.	0	.	6	100	0	.	0	.	0	.	0	.	7	100	0	.	8	100	10	74	0	.	0	.	98	28
	31-40 cm	0	.	0	.	10	100	47	52	0	.	0	.	0	.	0	.	14	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	122	38
	41-50 cm	0	.	0	.	0	.	62	52	13	100	0	.	0	.	0	.	22	71	0	.	13	100	0	.	0	.	13	100	0	.	0	.	0	.	13	100	0	.	0	.	22	100	30	75	9	100	0	.	0	.	198	28
	51-60 cm	0	.	0	.	0	.	15	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	71	0	.	0	.	62	50
	61-70 cm	0	.	0	.	0	.	17	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	36	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	.
	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	4	100	0	.	11	85	164	31	17	80	13	79	0	.	9	100	62	40	2	100	35	69	9	100	0	.	13	100	21	69	0	.	37	87	13	100	1	100	20	66	24	92	49	50	78	42	0	.	22	93	606	15
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	56	30	13	55	34	31	460	11	42	30	177	24	5	58	61	32	444	11	97	23	209	19	79	23	22	51	89	29	125	19	25	36	77	29	95	32	30	37	589	12	69	33	309	14	464	13	13	55	90	21	3673	4
	21-30 cm	68	43	13	71	87	41	802	14	88	43	218	27	17	75	130	35	727	14	191	29	419	31	40	52	41	47	50	42	268	22	21	59	144	32	158	51	29	53	520	15	130	29	363	24	652	16	7	100	136	27	5321	6
	31-40 cm	124	33	0	0	118	43	1099	15	93	40	307	27	0	0	69	58	735	18	175	32	289	31	11	100	43	53	66	52	211	31	22	71	196	41	183	37	16	100	258	23	131	36	291	22	734	16	32	100	217	32	5419	6
	41-50 cm	181	36	28	71	68	60	1174	14	89	48	285	30	19	100	32	58	736	17	141	38	361	33	39	58	63	66	210	38	200	28	35	71	133	35	118	38	0	0	290	27	46	79	433	26	529	18	0	0	211	31	5422	6
	51-60 cm	157	44	0	0	23	100	757	19	23	100	467	40	26	100	116	53	642	21	24	100	185	39	27	100	0	0	75	58	206	34	20	100	0	0	132	41	0	0	101	45	113	45	255	37	493	25	60	100	98	50	3999	9
	61-70 cm	59	71	24	100	0	0	352	30	0	0	152	52	0	0	0	0	375	26	39	100	296	34	0	0	0	0	23	100	160	46	0	0	61	100	60	71	0	0	49	59	24	100	63	100	106	52	0	0	0	0	1844	13
	71-80 cm	0	0	0	0	0	0	84	71	0	0	285	70	0	.	0	0	24	100	0	0	90	71	0	0	0	.	0	0	54	100	0	0	0	0	0	0	0	0	94	52	40	100	67	71	39	100	0	0	39	100	816	30
	81-90 cm	0	0	0	.	0	.	46	100	45	100	0	0	0	.	0	0	103	59	0	0	0	.	0	0	0	.	0	.	0	0	0	.	0	0	0	0	0	0	98	59	0	0	55	100	34	100	0	.	0	0	380	32
	91-100 cm	0	0	0	.	0	.	53	100	0	.	0	.	0	.	48	100	0	0	0	0	0	0	0	0	0	.	0	.	45	100	0	.	0	.	0	0	0	0	25	100	0	0	0	0	72	71	0	.	0	0	243	42
	>100 cm	0	0	0	.	0	.	0	0	0	.	0	0	0	.	0	0	0	0	0	0	0	.	0	.	0	.	0	.	48	100	0	.	0	.	0	0	0	.	0	0	0	.	0	0	0	0	0	.	0	.	48	100
	total	645	23	78	44	330	36	4828	10	380	30	1891	26	67	66	456	29	3787	10	667	22	1850	20	196	27	168	40	514	28	1317	17	123	35	611	24	747	25	76	42	2024	10	551	25	1836	17	3122	11	113	67	791	19	27167	4

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. 1306706. Birmensdorf, Swiss Federal Research Institute WSL

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