Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

ownership (2 categories)	volume of deadwood Jura NFI5
	estimated value	standard error		confidence interval
		relative	absolute	68%	95%
	m³/ha	±%	±m³/ha	m³/ha	m³/ha
public	30	10	3	27-33	24-36
private	27	17	5	22-32	17-37
total	29	9	3	26-32calculated with the standard error, i.e. 29 ± 3	23-35calculated with twice the standard error, i.e. 29 ± 2 × 3

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI1
number of stems
diameter at breast height (in 4 cm classes) · main tree species
regional demarcation: production region
unit: 1000 n
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
state 1983/85
		production region
		Jura		Plateau		Pre-Alps		Alps		Southern Alps		Switzerland
diameter at breast height (in 4 cm classes)	main tree species	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
12-15 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	5374	15	8325	13	9880	9	12606	7	1342	17	37526	5
	fir	3469	11	2811	14	3285	10	1507	18	234	41	11305	6
	pine	507	52	360	51	208	65	3087	18	49	100	4211	16
	larch	34	100	71	71	0	.	1590	17	720	26	2415	14
	Arolla pine	0	.	0	.	0	.	652	24	0	.	652	24
	other conifers	245	39	256	46	36	71	250	45	0	.	787	24
	beech	6850	9	5724	8	4767	11	3262	14	3586	16	24189	5
	maple	1183	16	916	20	1166	16	1356	20	93	45	4714	9
	ash	931	21	1114	18	1485	21	937	24	561	28	5027	10
	oak	672	38	1117	35	166	58	336	28	829	46	3120	20
	sweet chestnut	0	.	0	.	0	.	19	100	4159	17	4178	17
	other broadleaves	1888	20	2530	17	2413	16	3902	13	4907	14	15640	7
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	21154	6	23224	6	23405	6	29505	5	16478	7	113765	3
16-19 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3777	15	4380	11	7520	9	10905	7	970	21	27552	5
	fir	2775	12	2075	16	2748	12	1011	18	234	45	8843	7
	pine	149	44	189	41	177	89	2684	17	18	100	3218	15
	larch	35	70	69	61	0	.	1249	16	765	23	2118	13
	Arolla pine	0	.	0	.	0	.	441	27	0	.	441	27
	other conifers	173	72	153	43	39	71	50	58	0	.	415	35
	beech	5611	9	4026	9	3482	10	2287	14	2524	19	17930	5
	maple	1073	16	745	20	816	18	759	22	189	40	3582	9
	ash	669	30	1082	16	1319	21	710	27	288	34	4068	11
	oak	466	39	841	32	93	51	229	43	445	37	2075	18
	sweet chestnut	0	.	0	.	0	.	55	74	3381	16	3436	16
	other broadleaves	993	20	1615	16	1568	20	1958	14	3372	12	9507	7
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	15722	6	15176	6	17763	6	22339	5	12185	7	83184	3
20-23 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2161	13	3044	11	6001	9	9270	7	1167	19	21644	4
	fir	1789	12	1849	15	1914	12	777	22	108	46	6437	7
	pine	177	47	137	35	55	73	1512	17	0	.	1881	15
	larch	0	.	122	51	0	.	1478	16	443	24	2043	13
	Arolla pine	0	.	0	.	0	.	475	25	0	.	475	25
	other conifers	52	58	100	47	22	100	0	.	0	.	174	34
	beech	4277	10	3273	10	2611	13	1674	14	1542	18	13377	5
	maple	839	18	772	20	836	18	671	21	0	.	3118	10
	ash	690	20	1140	17	881	23	408	31	18	100	3138	11
	oak	543	26	610	21	21	100	108	47	266	36	1547	14
	sweet chestnut	0	.	0	.	0	.	34	71	1933	18	1967	17
	other broadleaves	598	19	979	18	457	31	924	18	1506	14	4464	8
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	11125	5	12027	5	12798	6	17331	5	6983	7	60264	3
24-27 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2116	11	3308	12	5710	9	7574	7	1033	19	19742	4
	fir	1735	14	1452	14	1525	14	596	21	111	52	5419	8
	pine	406	32	299	34	55	73	1338	15	50	74	2149	13
	larch	0	.	119	47	0	.	1131	17	483	24	1734	13
	Arolla pine	0	.	0	.	0	.	312	30	0	.	312	30
	other conifers	0	.	17	100	0	.	15	100	0	.	32	71
	beech	3170	9	2838	10	2217	12	1055	16	1027	17	10307	5
	maple	646	18	485	22	577	20	591	20	37	71	2336	10
	ash	411	27	724	17	599	23	492	30	57	57	2282	12
	oak	262	32	594	22	56	73	61	58	126	46	1100	16
	sweet chestnut	0	.	0	.	0	.	19	100	828	21	847	21
	other broadleaves	507	23	531	19	282	33	455	21	1070	20	2846	10
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	9253	6	10369	6	11022	6	13639	5	4823	8	49106	3
28-31 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2069	13	3188	10	4753	9	6703	7	950	24	17664	4
	fir	1664	15	1029	18	1675	14	485	21	18	100	4870	8
	pine	305	29	273	35	79	62	1039	17	69	62	1766	13
	larch	70	61	52	74	0	.	939	18	432	31	1492	15
	Arolla pine	0	.	0	.	0	.	391	28	0	.	391	28
	other conifers	0	.	50	58	0	.	0	.	0	.	50	58
	beech	3454	9	1690	13	1762	13	997	17	542	24	8444	6
	maple	564	19	302	26	476	22	461	23	19	100	1820	11
	ash	443	26	530	21	199	35	105	41	0	.	1277	14
	oak	299	28	323	25	18	100	15	100	135	43	791	17
	sweet chestnut	0	.	0	.	0	.	19	100	550	23	568	22
	other broadleaves	177	31	573	25	119	52	281	33	445	29	1596	14
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	9044	6	8010	6	9081	6	11433	5	3160	11	40729	3
32-35 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1650	13	3037	10	4041	9	5655	8	663	22	15045	5
	fir	1268	15	1312	13	1133	15	378	24	92	44	4183	8
	pine	480	26	471	27	38	71	631	21	34	71	1654	14
	larch	0	.	152	40	0	.	1052	17	322	30	1525	14
	Arolla pine	0	.	0	.	0	.	298	24	0	.	298	24
	other conifers	0	.	66	61	0	.	17	100	0	.	84	53
	beech	2162	11	1719	12	1608	13	544	21	356	26	6389	6
	maple	285	26	154	37	275	30	149	37	19	100	883	16
	ash	187	32	519	21	204	30	109	42	23	100	1042	14
	oak	200	33	277	25	0	.	0	.	128	41	605	18
	sweet chestnut	0	.	0	.	0	.	23	100	267	26	290	25
	other broadleaves	303	26	295	27	69	50	316	27	247	37	1230	14
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	6535	6	8001	5	7370	6	9171	5	2149	11	33227	3
36-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1399	10	2988	7	3345	7	4379	6	592	17	12702	4
	fir	907	12	1123	11	1150	11	422	20	62	40	3665	6
	pine	354	18	528	19	38	46	564	16	63	72	1548	10
	larch	7	100	72	41	0	.	905	12	266	22	1250	10
	Arolla pine	0	.	0	.	0	.	248	24	0	.	248	24
	other conifers	0	.	20	58	0	.	0	.	0	.	20	58
	beech	1566	8	1436	10	948	13	462	15	292	21	4703	5
	maple	219	21	131	25	188	24	130	25	0	.	669	12
	ash	157	36	374	18	96	36	103	36	18	72	748	14
	oak	119	29	189	21	21	74	30	61	48	71	407	16
	sweet chestnut	0	.	0	.	0	.	6	100	200	32	206	31
	other broadleaves	140	27	182	23	24	58	73	36	134	28	553	13
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	4869	5	7042	4	5810	5	7323	4	1674	9	26719	2
40-43 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1322	10	2382	8	3160	7	3771	6	463	18	11098	4
	fir	707	12	821	12	1027	11	382	19	83	39	3021	6
	pine	232	22	467	18	93	45	383	19	14	70	1189	11
	larch	0	.	35	45	0	.	688	12	197	22	919	10
	Arolla pine	0	.	0	.	0	.	154	28	0	.	154	28
	other conifers	0	.	55	43	0	.	0	.	0	.	55	43
	beech	1278	10	1029	10	672	15	390	19	149	25	3518	6
	maple	85	29	50	38	109	27	54	35	7	100	304	15
	ash	92	33	290	17	68	36	39	56	0	.	490	14
	oak	35	53	197	22	0	.	13	71	60	78	304	22
	sweet chestnut	0	.	0	.	0	.	0	.	126	26	126	26
	other broadleaves	42	41	98	30	43	41	43	41	57	37	283	17
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	3793	5	5424	5	5173	5	5917	5	1155	10	21461	2
44-47 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1100	10	1733	9	2294	8	3145	6	413	19	8684	4
	fir	452	16	623	13	767	11	278	18	91	37	2211	7
	pine	166	25	313	20	80	58	206	26	0	.	764	14
	larch	14	70	76	35	7	100	710	12	202	22	1010	10
	Arolla pine	0	.	0	.	0	.	92	35	0	.	92	35
	other conifers	0	.	45	76	0	.	0	.	0	.	45	76
	beech	769	12	838	12	548	15	289	19	143	24	2586	7
	maple	64	33	66	37	46	41	76	33	0	.	251	18
	ash	53	38	78	32	36	53	12	100	7	100	186	21
	oak	72	34	172	24	0	.	0	.	7	100	252	19
	sweet chestnut	0	.	0	.	0	.	7	100	123	28	130	27
	other broadleaves	43	47	36	45	8	100	43	41	8	100	139	24
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	2734	6	3979	5	3785	6	4859	5	994	11	16350	3
48-51 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	945	11	1391	9	1652	8	2189	7	406	18	6583	4
	fir	303	17	437	15	593	13	206	22	45	40	1583	8
	pine	42	41	273	22	31	58	168	26	14	71	528	15
	larch	14	100	14	71	22	75	533	14	148	24	730	12
	Arolla pine	0	.	0	.	0	.	57	35	0	.	57	35
	other conifers	0	.	43	62	0	.	0	.	0	.	43	62
	beech	503	15	424	16	359	19	188	22	74	33	1549	8
	maple	31	51	35	45	20	58	21	58	0	.	107	26
	ash	35	59	115	29	43	45	15	72	11	100	220	21
	oak	39	45	87	37	0	.	13	71	20	72	159	25
	sweet chestnut	0	.	0	.	0	.	6	100	104	32	110	31
	other broadleaves	28	61	23	58	14	71	74	39	17	71	156	25
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	1940	7	2841	6	2736	6	3469	6	838	11	11825	3
52-55 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	598	14	813	12	1129	10	1524	8	224	20	4288	5
	fir	180	20	251	20	312	17	210	21	7	100	959	10
	pine	62	40	139	25	12	100	107	29	7	100	328	17
	larch	14	71	33	45	7	100	498	15	123	25	675	12
	Arolla pine	0	.	0	.	0	.	21	58	0	.	21	58
	other conifers	0	.	15	71	0	.	0	.	0	.	15	71
	beech	276	20	298	17	295	22	132	25	43	47	1045	10
	maple	14	71	29	50	18	74	0	.	0	.	60	36
	ash	14	71	73	34	22	57	0	.	0	.	110	27
	oak	21	57	57	35	0	.	0	.	0	.	78	30
	sweet chestnut	0	.	0	.	0	.	7	100	42	45	50	41
	other broadleaves	7	100	22	58	0	.	45	52	8	100	82	35
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	1186	9	1731	8	1794	8	2544	6	454	13	7710	4
56-59 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	431	15	641	11	987	11	1184	9	222	21	3465	5
	fir	167	27	169	22	257	21	139	27	15	71	747	12
	pine	15	71	43	41	23	71	36	53	0	.	116	28
	larch	0	.	15	71	9	100	264	20	79	35	367	16
	Arolla pine	0	.	0	.	0	.	64	37	0	.	64	37
	other conifers	0	.	7	100	0	.	0	.	0	.	7	100
	beech	203	20	215	21	130	26	101	31	59	34	708	11
	maple	22	58	7	100	0	.	13	71	0	.	41	41
	ash	0	.	35	45	0	.	14	71	0	.	48	38
	oak	49	46	62	36	0	.	0	.	0	.	111	29
	sweet chestnut	0	.	0	.	0	.	0	.	47	47	47	47
	other broadleaves	7	100	23	58	0	.	8	100	8	100	46	41
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	892	11	1216	8	1407	9	1824	7	429	14	5767	4
60-63 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	154	22	223	19	426	15	595	12	79	32	1479	8
	fir	106	27	135	27	200	21	33	45	15	70	489	13
	pine	28	61	34	53	11	100	28	50	0	.	101	30
	larch	0	.	0	.	0	.	182	22	57	35	239	19
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	57	35	129	24	58	40	44	41	39	45	327	15
	maple	15	71	8	100	6	100	0	.	0	.	29	50
	ash	14	71	24	59	0	.	6	100	0	.	44	42
	oak	9	100	27	50	12	100	0	.	0	.	48	42
	sweet chestnut	0	.	0	.	0	.	0	.	45	41	45	41
	other broadleaves	8	100	8	100	0	.	14	71	0	.	29	50
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	391	14	588	12	714	12	902	10	236	18	2831	5
64-67 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	147	22	243	19	369	15	331	18	90	42	1181	9
	fir	43	41	35	45	142	28	13	71	16	71	248	19
	pine	0	.	7	100	7	100	7	100	0	.	21	58
	larch	0	.	14	71	7	100	129	23	28	61	178	21
	Arolla pine	0	.	0	.	0	.	21	58	0	.	21	58
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	63	37	89	29	32	59	22	58	22	58	228	19
	maple	14	71	0	.	0	.	0	.	0	.	14	71
	ash	7	100	7	100	7	100	0	.	0	.	21	58
	oak	0	.	14	71	0	.	0	.	0	.	14	71
	sweet chestnut	0	.	0	.	0	.	0	.	15	71	15	71
	other broadleaves	0	.	8	100	10	100	0	.	7	100	24	58
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	274	16	415	14	574	13	524	13	179	26	1965	7
68-71 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	59	35	148	22	137	25	390	14	85	36	820	10
	fir	44	41	43	41	45	41	32	44	0	.	164	21
	pine	0	.	7	100	0	.	7	100	0	.	14	71
	larch	0	.	0	.	10	100	148	25	35	44	193	21
	Arolla pine	0	.	0	.	0	.	21	58	0	.	21	58
	other conifers	0	.	7	100	7	100	0	.	0	.	14	71
	beech	28	50	96	30	18	71	21	58	15	71	179	21
	maple	0	.	0	.	6	100	0	.	0	.	6	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	24	59	0	.	0	.	0	.	24	59
	sweet chestnut	0	.	0	.	0	.	0	.	18	71	18	71
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	132	25	324	15	224	22	620	11	153	25	1452	8
72-75 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	67	33	48	42	137	26	217	21	23	56	493	13
	fir	51	43	30	62	83	30	21	58	30	60	215	20
	pine	0	.	7	100	0	.	0	.	0	.	7	100
	larch	7	100	7	100	0	.	79	30	14	71	107	26
	Arolla pine	0	.	0	.	0	.	35	53	0	.	35	53
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	8	100	14	71	17	72	0	.	0	.	38	45
	maple	0	.	0	.	0	.	17	73	0	.	17	73
	ash	0	.	7	100	0	.	0	.	0	.	7	100
	oak	0	.	30	50	0	.	6	100	0	.	36	45
	sweet chestnut	0	.	0	.	0	.	7	100	20	72	27	59
	other broadleaves	0	.	8	100	0	.	0	.	0	.	8	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	133	25	150	24	238	19	382	15	87	32	989	9
76-79 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	16	70	21	58	91	37	115	25	61	48	303	18
	fir	15	71	13	71	15	72	7	100	0	.	50	38
	pine	0	.	0	.	0	.	7	100	0	.	7	100
	larch	0	.	0	.	0	.	64	37	8	100	71	35
	Arolla pine	0	.	0	.	0	.	7	100	0	.	7	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	21	58	7	100	16	71	0	.	44	41
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	10	100	0	.	0	.	0	.	10	100
	oak	0	.	7	100	0	.	0	.	0	.	7	100
	sweet chestnut	0	.	0	.	0	.	0	.	45	56	45	56
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	30	50	72	32	114	32	215	19	113	35	545	13
80-83 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	29	50	43	41	30	50	48	38	6	100	156	21
	fir	15	71	7	100	16	71	13	71	0	.	51	38
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	14	71	7	100	21	58
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	36	52	0	.	14	71	7	100	56	39
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	7	100	0	.	0	.	0	.	7	100
	oak	7	100	22	58	0	.	0	.	0	.	28	50
	sweet chestnut	0	.	0	.	0	.	0	.	36	65	36	65
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	51	38	114	28	46	41	89	28	57	46	355	15
84-87 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	8	100	14	72	51	38	0	.	73	32
	fir	0	.	0	.	31	50	0	.	18	72	49	42
	pine	0	.	8	100	0	.	0	.	0	.	8	100
	larch	0	.	0	.	0	.	22	58	0	.	22	58
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	6	100	0	.	6	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	8	100	0	.	0	.	0	.	8	100
	sweet chestnut	0	.	0	.	0	.	0	.	8	100	8	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	24	58	45	41	79	30	26	59	174	21
88-91 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	8	100	0	.	7	100	15	71	7	100	37	45
	fir	7	100	0	.	14	71	7	100	0	.	28	50
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	7	100	0	.	7	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	8	100	13	71	0	.	0	.	0	.	21	58
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	7	100	0	.	0	.	0	.	7	100
	sweet chestnut	0	.	0	.	0	.	0	.	23	58	23	58
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	22	58	20	58	21	57	29	50	30	50	122	24
92-95 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	7	100	7	100	7	100	7	100	0	.	28	50
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	7	100	0	.	7	100
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	8	100	0	.	0	.	0	.	8	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	12	100	12	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	7	100	15	71	7	100	14	71	12	100	55	39
96-99 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	7	100	0	.	44	41	0	.	51	38
	fir	7	100	0	.	0	.	0	.	0	.	7	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	7	100	7	100	14	71
	Arolla pine	0	.	0	.	0	.	7	100	0	.	7	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	7	100	7	100	0	.	59	35	7	100	79	30
100-103 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	6	100	0	0	0	.	6	100
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	7	100	0	.	7	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	25	58	25	58
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	6	100	7	100	25	58	39	45
104-107 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	9	100	7	100	0	.	16	71
	fir	7	100	0	.	0	.	0	.	11	100	18	73
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	7	100	7	100
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	7	100	0	.	9	100	7	100	18	72	41	46
108-111 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	7	100	0	.	7	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	7	100	0	.	7	100
112-115 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	7	100	0	.	7	100
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	7	100	0	.	7	100
116-119 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
120-123 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
124-127 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	6	100	6	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	6	100	6	100
128-131 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	7	100	7	100
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	7	100	7	100
132-135 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
136-139 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
140-143 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
144-147 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	7	100	7	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	7	100	7	100
148-151 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	8	100	8	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	8	100	8	100
152-155 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	6	100	6	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	6	100	6	100
156-159 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
160-163 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
164-167 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
168-171 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
172-175 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
176-179 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
180-183 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
184-187 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
188-191 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
192-195 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
196-199 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	6	100	6	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	6	100	6	100
=200 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	23429	8	35978	6	51708	5	70724	4	8805	12	190643	3
	fir	15709	8	14215	9	16933	7	6516	12	1189	28	54562	4
	pine	2922	16	3556	14	909	50	11803	12	317	52	19508	9
	larch	194	33	850	24	62	45	11697	8	4342	14	17144	7
	Arolla pine	0	.	0	.	0	.	3318	15	0	.	3318	15
	other conifers	470	48	834	28	103	42	333	39	0	.	1740	20
	beech	30282	5	23916	5	19533	8	11504	10	10419	14	95653	3
	maple	5053	10	3698	12	4539	10	4298	13	365	32	17953	6
	ash	3704	15	6130	10	4959	15	2952	20	983	25	18728	7
	oak	2794	22	4663	16	388	34	812	28	2063	27	10720	11
	sweet chestnut	0	.	0	.	0	.	203	54	12039	13	12242	13
	other broadleaves	4742	13	6931	12	5007	15	8137	11	11785	10	36602	5
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	89299	3	100769	3	104141	3	132296	3	52308	5	478813	1

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. 1350026. Birmensdorf, Swiss Federal Research Institute WSL

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