Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI4
number of stems
diameter at breast height (in 4 cm classes) · main tree species
regional demarcation: biogeographical region
unit: 1000 n
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
state 2009/17
		biogeographical region
		Jura		Plateau		Northern Alps		Western Central-Alps		Eastern Central-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	±%	1000 n	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
12-15 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3991	10	6265	9	11857	5	3660	10	8100	8	2796	12	36670	3
	fir	3647	8	3109	11	3800	8	267	26	158	32	457	28	11437	5
	pine	112	52	117	55	502	32	888	26	1461	19	49	65	3129	13
	larch	11	100	284	60	212	37	1433	16	1280	24	1669	14	4888	10
	Arolla pine	0	.	0	.	42	71	339	25	555	20	48	53	984	15
	other conifers	308	34	197	23	515	29	40	62	537	27	40	79	1637	15
	beech	4714	7	4829	7	4911	8	425	30	451	21	3460	12	18791	4
	maple	1565	13	1724	12	2686	10	341	27	276	30	607	23	7199	6
	ash	663	16	1690	12	1429	14	207	28	261	28	913	19	5163	7
	oak	436	45	378	28	137	50	609	29	10	100	410	25	1980	16
	sweet chestnut	10	100	10	100	55	84	0	.	0	.	2115	18	2190	18
	other broadleaves	1921	11	2557	11	4262	9	2099	13	2104	16	6177	9	19121	4
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	17377	4	21160	4	30409	4	10308	7	15194	6	18741	5	113189	2
16-19 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3315	11	4118	9	9514	5	2594	11	6160	8	1921	12	27623	3
	fir	2458	8	2620	11	2654	9	179	30	140	28	203	32	8254	5
	pine	99	55	111	61	308	35	788	23	1082	18	30	58	2420	12
	larch	10	100	108	43	156	40	1363	13	760	21	1181	14	3578	8
	Arolla pine	0	.	0	.	33	75	306	24	663	20	10	100	1012	15
	other conifers	168	38	148	32	221	40	31	74	182	37	0	.	751	18
	beech	3401	8	3278	7	3708	8	293	32	494	21	2850	12	14024	4
	maple	1241	12	1317	12	2167	10	226	28	137	30	545	22	5632	6
	ash	510	19	1421	14	1050	15	243	37	248	27	585	20	4056	8
	oak	352	31	379	25	86	58	237	36	0	.	416	29	1470	14
	sweet chestnut	0	.	19	71	53	73	0	0	0	.	2134	14	2207	13
	other broadleaves	861	14	1587	12	2560	11	1339	16	1347	18	4142	9	11836	5
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	12415	4	15106	4	22511	4	7599	7	11214	6	14018	5	82863	2
20-23 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2282	11	3560	9	7031	6	2324	10	4664	8	1563	12	21425	3
	fir	1770	10	1672	11	1871	9	189	29	117	42	270	27	5888	6
	pine	125	35	85	42	218	33	894	20	802	19	51	68	2175	12
	larch	0	0	95	39	91	45	1161	14	672	20	1114	14	3133	8
	Arolla pine	0	.	0	.	11	100	260	22	288	24	20	71	578	16
	other conifers	99	42	140	27	114	39	0	.	90	40	21	100	464	18
	beech	2622	9	2695	7	3025	8	211	40	261	26	2056	12	10869	4
	maple	859	14	1103	14	1612	11	120	34	89	51	181	27	3963	7
	ash	387	18	848	13	846	15	158	37	160	42	445	22	2844	8
	oak	220	33	311	23	166	35	187	31	43	60	310	25	1237	12
	sweet chestnut	0	.	10	100	19	100	0	0	0	.	2007	14	2036	14
	other broadleaves	574	17	1173	13	1245	14	676	17	738	23	2584	10	6990	6
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	8937	5	11692	4	16249	4	6181	7	7924	6	10620	5	61602	2
24-27 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1861	11	2890	10	6710	6	1702	11	3630	8	1119	12	17910	3
	fir	1391	11	1136	12	1599	10	108	35	99	32	143	37	4477	6
	pine	151	35	144	37	203	42	621	18	416	23	0	0	1535	12
	larch	20	100	85	40	40	79	737	15	468	17	1120	13	2470	8
	Arolla pine	0	.	0	.	21	71	324	23	458	22	0	.	803	15
	other conifers	38	50	79	35	53	53	0	.	31	58	0	.	201	24
	beech	2505	8	2168	8	2533	9	134	39	322	26	1458	13	9119	5
	maple	639	14	819	14	1464	11	66	50	150	35	104	37	3242	7
	ash	276	27	724	15	780	16	125	38	98	49	520	25	2523	9
	oak	261	23	469	23	51	53	63	41	0	0	292	24	1136	13
	sweet chestnut	0	.	0	.	11	100	0	.	0	.	1141	14	1152	14
	other broadleaves	358	18	717	14	708	16	367	20	267	30	1656	11	4072	7
	indeterminable	0	0	0	.	0	0	0	0	0	0	0	.	0	0
	total	7500	5	9231	5	14171	4	4249	7	5938	6	7552	5	48640	2
28-31 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1525	10	2284	9	5844	6	1657	12	3081	9	1109	13	15500	4
	fir	885	14	872	13	1307	11	119	43	100	32	98	35	3381	7
	pine	261	30	146	37	249	30	395	22	405	19	78	43	1535	11
	larch	10	100	133	30	56	61	719	14	570	17	740	16	2227	8
	Arolla pine	0	.	0	.	42	80	353	22	357	22	0	.	751	15
	other conifers	68	43	78	39	20	71	0	0	0	.	0	.	166	27
	beech	2528	10	1725	8	2370	8	74	56	242	23	1050	15	7987	5
	maple	573	16	590	17	1281	13	0	.	129	40	113	35	2687	8
	ash	389	21	581	15	511	18	67	87	72	43	157	44	1777	10
	oak	330	28	385	19	44	51	49	53	0	0	206	28	1014	13
	sweet chestnut	0	.	19	100	0	.	20	100	0	.	1045	15	1084	15
	other broadleaves	250	22	472	25	425	19	202	29	53	52	999	13	2401	9
	indeterminable	0	.	0	0	0	0	0	0	0	0	0	.	0	0
	total	6819	5	7286	5	12148	4	3654	8	5008	7	5594	6	40510	2
32-35 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1358	11	2054	10	4782	6	1177	12	2332	8	902	15	12605	4
	fir	1071	11	855	12	1240	11	49	53	51	53	97	37	3362	6
	pine	272	24	185	24	124	39	279	23	351	23	107	59	1318	12
	larch	10	100	115	37	41	50	717	17	481	17	585	16	1949	9
	Arolla pine	0	.	0	.	33	75	173	27	202	28	30	75	438	18
	other conifers	9	100	100	43	0	.	0	.	0	.	0	.	109	40
	beech	2240	9	1347	10	1561	11	69	43	177	27	604	17	5999	5
	maple	358	18	371	17	500	16	20	71	59	47	75	44	1384	9
	ash	253	22	571	16	508	19	97	62	26	72	183	32	1637	10
	oak	217	24	179	26	19	71	0	.	10	100	131	31	555	15
	sweet chestnut	0	.	0	.	23	100	10	100	0	.	576	19	609	18
	other broadleaves	191	25	318	21	251	22	56	57	58	41	751	14	1626	9
	indeterminable	0	0	0	0	0	0	0	.	0	0	0	0	0	0
	total	5979	5	6094	5	9082	4	2648	9	3748	7	4041	6	31591	2
36-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1075	9	1726	7	4025	5	1058	10	1984	7	704	12	10573	3
	fir	900	10	624	10	842	8	64	39	58	32	88	34	2575	5
	pine	270	21	229	17	162	27	197	19	265	19	58	50	1180	9
	larch	20	45	79	23	18	51	532	13	417	15	495	12	1561	7
	Arolla pine	0	.	0	.	18	60	122	23	171	22	0	.	310	15
	other conifers	19	66	52	38	4	100	0	.	0	.	0	.	75	32
	beech	1912	6	1313	7	1243	8	64	39	174	24	447	13	5153	4
	maple	316	13	297	14	454	12	12	100	59	55	31	38	1169	7
	ash	183	19	547	12	250	17	29	55	17	50	62	36	1088	8
	oak	109	27	222	18	51	34	21	45	8	71	122	25	532	11
	sweet chestnut	0	.	12	74	0	.	6	100	0	.	339	15	356	14
	other broadleaves	93	34	292	15	130	22	55	38	104	37	428	13	1104	8
	indeterminable	0	.	0	0	0	0	0	.	0	0	0	0	0	0
	total	4897	4	5392	4	7198	3	2158	7	3257	5	2773	5	25675	2
40-43 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1145	8	1338	8	3801	5	720	11	1743	7	644	12	9392	3
	fir	793	9	618	10	897	9	60	37	55	31	81	27	2504	5
	pine	230	21	197	18	137	24	187	21	191	19	42	39	984	9
	larch	8	71	58	33	30	38	525	13	372	15	425	13	1417	7
	Arolla pine	0	.	0	.	14	73	69	27	120	23	0	.	202	17
	other conifers	11	58	40	48	0	.	0	.	0	.	0	.	52	39
	beech	1568	6	1182	8	1248	8	21	65	93	25	391	14	4503	4
	maple	215	16	155	17	260	14	16	79	17	50	38	37	701	8
	ash	132	20	418	12	222	18	17	61	12	58	60	34	861	9
	oak	91	31	231	17	28	51	16	61	12	100	57	33	436	13
	sweet chestnut	0	.	4	100	8	71	0	.	0	.	306	17	317	16
	other broadleaves	125	31	159	17	89	27	50	41	15	60	227	16	665	10
	indeterminable	0	0	0	0	0	0	0	.	0	0	0	0	0	0
	total	4321	4	4400	4	6733	4	1679	7	2630	6	2273	6	22035	2
44-47 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	922	8	1149	8	3004	5	680	11	1408	8	537	13	7699	3
	fir	794	9	529	11	860	9	48	33	75	27	58	27	2364	5
	pine	156	19	185	17	48	33	112	23	147	22	27	62	674	9
	larch	8	71	42	35	41	50	430	13	381	13	307	14	1209	7
	Arolla pine	0	.	0	.	14	58	55	32	81	26	0	.	151	19
	other conifers	15	79	24	47	0	.	0	.	0	.	4	100	43	39
	beech	1212	7	1063	7	818	9	22	69	102	27	213	18	3430	4
	maple	161	18	102	22	163	17	4	100	4	100	13	76	448	11
	ash	132	22	286	14	178	18	0	.	4	100	32	42	632	10
	oak	84	23	189	18	19	50	0	.	9	71	69	33	370	12
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	202	17	202	17
	other broadleaves	45	32	101	26	75	31	4	100	8	70	169	18	402	12
	indeterminable	0	0	0	.	0	0	0	0	0	0	0	.	0	0
	total	3529	4	3669	4	5220	4	1355	8	2219	6	1631	6	17624	2
48-51 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	843	8	909	9	2600	5	430	12	1170	8	406	12	6357	3
	fir	522	11	564	10	680	9	24	47	50	28	45	32	1884	5
	pine	106	27	137	19	70	41	27	43	111	24	11	58	462	12
	larch	12	58	34	40	27	51	375	13	327	15	281	14	1057	8
	Arolla pine	0	.	0	.	0	.	59	32	103	25	0	.	163	20
	other conifers	4	100	51	39	0	.	0	.	0	.	0	.	54	37
	beech	906	7	944	8	660	10	4	100	54	28	231	16	2799	4
	maple	57	29	91	22	152	23	0	.	20	53	4	100	324	14
	ash	79	24	304	14	94	21	0	.	10	71	22	62	509	10
	oak	57	34	155	21	14	58	0	.	16	61	25	46	268	16
	sweet chestnut	0	.	8	100	4	100	0	.	0	.	133	20	145	19
	other broadleaves	4	100	136	26	40	37	0	.	4	100	47	35	231	18
	indeterminable	0	.	0	0	0	0	0	.	0	0	0	0	0	0
	total	2589	5	3331	4	4342	4	920	9	1867	6	1206	7	14254	2
52-55 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	600	10	656	10	2186	6	346	13	838	9	340	15	4965	4
	fir	489	11	535	12	624	9	37	45	59	29	68	31	1812	6
	pine	63	30	106	20	19	52	61	33	118	23	11	74	379	12
	larch	0	.	68	27	24	48	401	14	282	21	274	14	1049	9
	Arolla pine	0	.	0	.	0	0	39	34	36	33	0	.	74	24
	other conifers	0	.	28	43	0	.	0	.	0	.	0	.	28	43
	beech	553	10	707	9	545	10	4	100	30	39	117	21	1956	5
	maple	47	31	33	35	55	30	0	.	13	58	4	100	152	17
	ash	54	28	190	16	47	31	8	71	4	100	0	.	303	12
	oak	81	33	128	22	13	58	4	100	12	74	24	45	261	16
	sweet chestnut	0	.	4	100	0	.	0	.	0	.	106	24	109	23
	other broadleaves	8	71	63	35	58	31	13	74	4	100	19	51	165	20
	indeterminable	0	.	0	0	0	0	0	0	0	0	0	.	0	0
	total	1894	6	2517	5	3572	4	913	9	1396	8	963	8	11254	2
56-59 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	620	10	718	9	1851	6	234	16	654	10	301	15	4377	4
	fir	388	12	415	11	484	11	27	43	49	33	36	40	1399	6
	pine	58	36	87	24	23	45	54	41	49	31	8	71	278	15
	larch	8	71	46	33	28	43	302	14	258	17	199	14	841	8
	Arolla pine	0	.	0	.	0	0	14	59	36	37	4	100	54	30
	other conifers	0	.	4	100	0	.	0	.	0	.	4	100	8	71
	beech	420	11	506	10	422	13	4	100	31	39	117	24	1500	6
	maple	31	35	46	30	28	38	0	.	5	100	0	.	111	19
	ash	31	38	133	22	36	40	0	.	4	100	16	60	220	16
	oak	13	77	73	24	12	58	0	.	4	100	7	100	109	21
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	126	23	126	23
	other broadleaves	8	71	44	41	40	57	8	71	6	100	20	45	126	25
	indeterminable	0	.	0	.	0	.	0	0	0	.	0	.	0	0
	total	1576	6	2071	5	2925	5	643	10	1095	9	839	9	9148	2
60-63 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	341	12	397	12	1134	8	150	18	401	12	144	19	2567	5
	fir	266	15	287	13	407	12	15	78	30	39	20	45	1025	7
	pine	12	58	40	32	8	71	16	50	39	34	4	100	118	19
	larch	0	.	22	46	14	59	125	20	160	18	117	21	438	11
	Arolla pine	0	.	0	.	0	.	0	.	20	53	0	.	20	53
	other conifers	0	.	12	58	0	.	0	.	0	.	0	.	12	58
	beech	195	16	352	12	174	18	0	.	12	58	53	30	786	8
	maple	15	59	20	52	33	47	0	.	8	71	4	100	80	27
	ash	17	50	73	23	24	46	0	.	0	.	4	100	119	19
	oak	11	73	103	22	4	100	0	.	0	.	8	71	126	20
	sweet chestnut	0	.	4	100	14	77	0	.	0	.	64	29	82	27
	other broadleaves	8	71	23	54	18	60	8	70	10	72	14	57	81	26
	indeterminable	0	.	0	.	0	0	0	0	0	0	0	.	0	0
	total	865	8	1333	6	1829	6	314	13	680	9	433	11	5453	3
64-67 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	245	15	273	15	817	8	99	27	308	13	124	19	1865	5
	fir	189	19	294	13	304	14	16	61	20	45	11	57	834	8
	pine	25	46	43	32	6	100	4	100	28	42	0	.	106	21
	larch	0	.	23	46	22	63	186	21	65	25	98	20	394	13
	Arolla pine	0	.	0	.	14	59	11	58	32	35	0	.	57	27
	other conifers	0	.	16	50	0	.	0	.	0	.	0	.	16	50
	beech	90	23	285	12	157	19	4	100	15	50	36	36	587	9
	maple	0	.	12	58	4	100	0	.	0	.	0	.	16	50
	ash	4	100	39	41	13	58	0	.	0	.	6	100	61	31
	oak	19	59	45	32	10	71	0	.	0	.	8	71	82	25
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	26	47	26	47
	other broadleaves	4	100	13	58	0	.	0	.	0	.	9	72	26	41
	indeterminable	0	.	0	0	0	.	0	.	0	.	0	.	0	0
	total	575	10	1043	7	1346	7	320	16	468	11	317	12	4070	4
68-71 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	184	17	207	15	644	10	89	26	303	20	133	21	1561	7
	fir	114	19	183	16	212	16	8	71	20	45	20	52	557	9
	pine	5	100	24	41	8	71	0	.	22	56	0	.	59	30
	larch	0	.	12	58	18	51	118	19	60	27	87	22	295	12
	Arolla pine	0	.	0	.	0	0	8	71	19	45	0	.	27	38
	other conifers	4	100	12	58	0	.	0	.	0	.	0	.	16	50
	beech	89	30	188	16	104	22	0	.	0	.	43	34	424	11
	maple	4	100	4	100	7	71	0	.	0	.	0	.	16	50
	ash	22	52	33	38	12	58	0	.	4	100	0	.	71	27
	oak	8	71	59	28	0	.	0	.	8	71	0	.	75	25
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	54	31	54	31
	other broadleaves	8	71	37	36	11	58	0	.	0	.	6	100	62	27
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	437	11	759	8	1018	8	223	15	436	15	343	12	3217	4
72-75 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	61	27	162	17	515	11	49	39	156	19	101	23	1045	7
	fir	94	21	93	21	131	20	4	100	11	58	17	50	351	12
	pine	4	100	4	100	0	.	0	.	0	.	0	.	8	71
	larch	4	100	5	100	12	58	68	28	43	32	57	29	189	16
	Arolla pine	0	.	0	.	0	.	11	58	4	100	0	.	15	50
	other conifers	0	.	24	58	0	.	0	.	0	.	0	.	24	58
	beech	60	27	118	19	63	29	0	.	4	100	11	58	256	13
	maple	5	100	0	.	4	100	0	.	0	.	0	.	9	71
	ash	8	71	18	50	6	100	0	.	0	.	0	.	32	38
	oak	8	71	23	46	0	.	0	.	0	.	0	.	32	38
	sweet chestnut	0	.	0	.	5	100	0	.	0	.	42	34	47	32
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	244	14	447	10	737	9	133	21	218	16	227	14	2008	5
76-79 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	76	26	66	26	312	13	44	30	136	20	57	29	692	8
	fir	45	35	108	22	119	20	12	58	20	45	16	50	320	12
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	55	31	31	38	37	37	123	20
	Arolla pine	0	.	0	.	0	.	15	50	11	58	0	.	27	38
	other conifers	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	beech	4	100	73	24	18	51	0	.	12	58	26	60	134	20
	maple	0	.	0	.	4	100	0	.	0	.	0	.	4	100
	ash	0	.	32	38	4	100	0	.	0	.	0	.	36	36
	oak	0	.	31	49	0	.	0	.	0	.	4	100	36	45
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	32	42	32	42
	other broadleaves	0	.	4	100	4	100	0	.	0	.	0	.	8	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	125	21	319	13	461	11	126	19	210	15	174	18	1415	6
80-83 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	24	41	68	25	163	18	16	50	85	22	58	26	414	10
	fir	15	60	43	32	24	41	0	.	0	.	4	100	85	23
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	4	100	4	100	30	38	13	77	35	33	87	23
	Arolla pine	0	.	0	.	0	.	4	100	8	71	4	100	16	50
	other conifers	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	beech	10	72	50	34	8	71	0	.	0	.	20	45	88	24
	maple	0	.	6	100	0	.	0	.	5	100	0	.	10	71
	ash	0	.	12	58	0	.	0	.	0	.	0	.	12	58
	oak	4	100	18	50	5	100	0	.	0	.	0	.	26	41
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	15	78	15	78
	other broadleaves	0	.	10	72	0	.	0	.	0	.	8	71	19	51
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	57	28	212	15	203	16	50	29	111	20	145	18	777	8
84-87 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	12	74	28	43	110	20	31	55	34	36	33	36	248	14
	fir	20	45	38	33	58	30	4	100	8	71	0	.	128	19
	pine	0	.	4	100	0	.	0	.	4	100	0	.	8	71
	larch	0	.	0	.	0	.	20	45	12	58	34	36	66	25
	Arolla pine	0	.	0	.	0	.	8	71	4	100	0	.	12	58
	other conifers	4	100	8	71	0	.	0	.	0	.	0	.	12	58
	beech	9	71	45	32	8	71	0	.	0	.	4	100	66	26
	maple	0	.	0	.	4	100	0	.	0	.	0	.	4	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	16	50	10	72	0	.	0	.	0	.	26	41
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	42	37	42	37
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	45	33	139	18	189	16	62	32	62	26	113	21	611	9
88-91 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	12	58	8	71	84	28	12	58	36	37	16	50	168	18
	fir	12	58	4	100	33	36	0	.	4	100	8	71	62	26
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	18	51	14	59	13	58	46	32
	Arolla pine	0	.	0	.	0	.	4	100	4	100	0	.	8	71
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	4	100	4	100	4	100	0	.	0	.	12	58
	maple	0	.	0	.	4	100	0	.	0	.	4	100	8	71
	ash	0	.	9	72	0	.	0	.	0	.	0	.	9	72
	oak	10	72	4	100	0	.	0	.	0	.	0	.	14	59
	sweet chestnut	0	.	0	.	0	.	4	100	0	.	12	58	17	50
	other broadleaves	0	.	8	71	0	.	0	.	0	.	0	.	8	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	35	36	37	33	125	22	43	32	58	29	53	28	351	12
92-95 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4	100	8	71	23	57	0	0	7	71	11	58	54	32
	fir	20	53	13	58	4	100	0	.	4	100	6	100	46	33
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	13	58	5	100	8	71	25	41
	Arolla pine	0	.	0	.	0	.	4	100	4	100	0	.	8	71
	other conifers	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	beech	0	.	0	.	4	100	0	.	0	.	0	.	4	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	oak	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	8	71	8	71
	other broadleaves	0	.	6	100	4	100	0	.	0	.	0	.	10	73
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	24	47	38	34	35	43	16	50	20	45	33	36	167	17
96-99 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	4	100	37	34	0	.	0	.	4	100	45	30
	fir	4	100	0	.	8	71	0	.	0	.	0	.	12	58
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	8	71	4	100	10	100	22	56
	Arolla pine	0	.	0	.	0	.	0	0	0	.	0	.	0	0
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	4	100	9	71	0	.	0	.	0	.	8	71	21	45
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	6	100	9	100	0	.	0	.	0	.	0	.	16	72
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	6	100	0	.	0	.	0	.	0	.	6	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	14	60	29	47	45	30	8	71	4	100	26	50	127	20
100-103 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	4	100	20	45	0	.	39	63	19	50	82	34
	fir	0	.	8	71	0	.	0	.	0	.	4	100	12	58
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	4	100	0	.	4	100	8	71
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	4	100	0	.	0	.	0	.	4	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	8	71	0	.	0	.	0	.	0	.	8	71
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	20	45	24	41	4	100	39	63	35	36	122	25
104-107 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4	100	8	71	9	71	4	100	8	71	9	71	42	32
	fir	0	.	0	.	8	71	0	.	0	.	0	.	8	71
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	4	100	4	100	4	100	12	58
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4	100	8	71	17	50	8	71	12	58	13	58	62	26
108-111 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	12	58	0	.	9	71	0	.	21	45
	fir	0	.	0	.	4	100	0	.	4	100	0	.	8	71
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	16	50	0	.	13	58	4	100	33	35
112-115 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	4	100	0	.	0	.	0	.	4	100
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	4	100	4	100	8	71
	Arolla pine	0	.	0	.	0	.	4	100	4	100	0	.	8	71
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	11	100	0	.	0	.	0	.	0	.	11	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	15	80	4	100	4	100	8	71	8	71	38	40
116-119 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	4	100	0	.	0	.	4	100	8	71
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	4	100	0	.	0	.	12	58	16	50
120-123 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	4	100	0	.	0	.	0	.	4	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	11	100	11	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	4	100	0	.	0	.	11	100	15	78
124-127 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	10	71	0	.	0	.	0	.	0	.	0	.	10	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	10	71	0	.	0	.	0	.	0	.	0	.	10	71
128-131 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	5	100	11	100	0	.	0	.	0	.	0	.	16	76
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	5	100	11	100	0	.	0	.	0	.	0	.	16	76
132-135 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	fir	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	4	100	0	.	0	.	0	.	4	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	4	100	0	.	0	.	12	58	16	50
136-139 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	8	100	0	.	0	.	0	.	8	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	8	100	0	.	0	.	0	.	8	100
140-143 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	4	100	4	100
144-147 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
148-151 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	4	100	4	100
152-155 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	4	100	4	100
156-159 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	4	100	4	100
160-163 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
164-167 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
168-171 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	13	75	13	75
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	13	75	13	75
172-175 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	11	100	11	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	11	100	11	100
176-179 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
180-183 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
184-187 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
188-191 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
192-195 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	11	100	11	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	11	100	11	100
196-199 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
=200 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	9	71	9	71
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	9	71	9	71
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	20500	6	28899	5	67094	3	17075	7	37288	5	13058	8	183914	2
	fir	15883	5	14620	6	18173	5	1228	22	1134	16	1755	19	52794	3
	pine	1949	15	1843	13	2085	22	4523	15	5491	13	476	40	16367	7
	larch	120	36	1214	20	834	24	9345	8	6682	10	8905	8	27100	5
	Arolla pine	0	.	0	.	241	54	2182	15	3180	14	116	55	5720	10
	other conifers	752	27	1022	17	927	28	71	63	840	27	69	56	3680	12
	beech	25040	5	22879	4	23590	5	1332	28	2474	16	13209	9	88523	3
	maple	6087	7	6690	8	10894	7	805	21	970	24	1724	17	27171	4
	ash	3140	10	7934	7	6009	9	952	27	920	25	3003	14	21958	4
	oak	2318	18	3422	11	669	29	1185	25	131	54	2090	17	9815	8
	sweet chestnut	10	100	89	86	193	72	40	77	0	.	10604	10	10937	10
	other broadleaves	4473	9	7750	9	9921	8	4877	12	4718	15	17261	7	49001	4
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	80272	3	96360	2	140630	2	43617	5	63829	4	72270	3	496978	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. 1350106. Birmensdorf, Swiss Federal Research Institute WSL

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