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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NFI2
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 1993/95
		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	4716	11	9978	9	13173	6	3223	11	6266	8	1805	14	39161	4
	fir	3419	8	2962	10	4140	8	329	34	219	25	300	27	11369	5
	pine	172	32	300	29	304	36	1334	21	1387	21	59	74	3556	12
	larch	10	100	207	34	85	58	1302	16	651	20	981	16	3236	9
	Arolla pine	0	.	0	.	0	.	256	29	296	27	10	100	562	19
	other conifers	300	34	296	28	249	34	31	58	321	30	62	100	1259	16
	beech	4681	7	5657	6	6064	8	403	32	465	24	3643	12	20913	4
	maple	1429	12	1360	13	1993	12	225	32	204	36	327	26	5538	7
	ash	824	17	1303	17	1335	15	289	28	246	38	887	18	4885	8
	oak	588	29	787	24	83	40	296	28	0	0	688	28	2442	13
	sweet chestnut	10	100	10	100	40	77	0	.	0	.	3435	13	3495	13
	other broadleaves	2045	11	2515	12	4628	9	1802	16	1495	17	6053	10	18538	5
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	18193	4	25376	4	32094	4	9493	7	11550	6	18248	5	114954	2
16-19 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2749	11	7217	8	10326	6	2585	10	4435	8	1411	13	28722	3
	fir	2301	9	2156	10	2776	8	249	32	139	30	261	31	7881	5
	pine	249	31	343	36	257	33	1365	18	1015	19	60	62	3289	11
	larch	20	71	149	37	48	51	1045	15	501	18	799	18	2561	9
	Arolla pine	0	.	0	.	33	74	227	26	398	27	10	100	667	19
	other conifers	176	41	164	38	100	42	0	.	171	52	62	100	673	22
	beech	3949	8	4253	7	4170	8	269	36	459	22	2721	12	15821	4
	maple	990	13	916	17	1939	10	107	41	151	40	118	36	4220	7
	ash	729	20	926	14	1207	15	114	42	192	39	525	23	3692	8
	oak	322	29	805	22	170	38	232	31	10	100	489	25	2027	13
	sweet chestnut	0	.	20	71	23	100	10	100	0	.	2758	13	2811	12
	other broadleaves	1094	14	1429	12	2360	10	960	17	711	20	3956	10	10510	5
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	12578	5	18379	4	23407	4	7161	7	8182	6	13168	5	82875	2
20-23 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2260	11	4574	8	8467	6	2016	11	3699	9	1259	13	22275	3
	fir	1477	10	1514	12	2073	9	192	33	188	34	125	33	5571	6
	pine	208	29	154	33	300	36	952	19	797	19	9	100	2420	11
	larch	50	59	126	54	30	58	894	15	454	18	767	17	2321	9
	Arolla pine	0	.	0	.	21	71	293	23	351	26	0	.	665	17
	other conifers	49	45	141	37	54	45	0	.	50	52	10	100	304	22
	beech	3712	8	3320	7	3215	8	139	35	423	26	1627	13	12436	4
	maple	687	14	786	17	1421	11	20	71	58	57	129	35	3101	7
	ash	526	20	1061	15	1039	16	41	61	120	46	234	29	3020	9
	oak	379	25	716	23	158	37	78	46	30	74	321	25	1683	13
	sweet chestnut	0	.	10	100	34	100	10	100	0	.	1760	13	1814	12
	other broadleaves	545	18	1016	13	1284	13	414	20	227	24	2109	10	5596	6
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	9894	5	13417	4	18098	4	5050	7	6397	7	8350	5	61206	2
24-27 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2038	10	3069	9	7594	6	1733	12	3212	8	1016	14	18661	4
	fir	1335	10	1147	12	1626	10	140	39	107	32	93	37	4449	6
	pine	220	33	191	26	238	30	554	19	413	21	39	50	1655	11
	larch	10	100	205	28	39	61	971	15	464	19	585	18	2274	9
	Arolla pine	0	.	0	.	64	63	312	26	259	27	10	100	646	18
	other conifers	49	60	99	49	9	100	0	.	10	100	0	.	168	35
	beech	3203	8	2793	8	2831	9	92	52	280	28	1017	14	10217	4
	maple	736	13	739	14	1100	12	10	100	78	35	147	28	2809	7
	ash	439	20	965	12	656	19	43	50	70	55	148	33	2321	9
	oak	386	25	471	19	101	53	49	53	10	100	228	28	1245	13
	sweet chestnut	0	.	0	.	21	71	30	74	0	.	1248	15	1299	14
	other broadleaves	350	18	712	15	741	15	173	29	216	30	1165	14	3356	7
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	8765	5	10392	4	15020	4	4107	8	5120	7	5697	6	49101	2
28-31 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1609	11	2790	9	6246	6	1624	11	2828	9	802	15	15899	3
	fir	1200	11	1315	11	1339	11	31	58	100	35	91	47	4076	6
	pine	278	25	172	27	208	27	469	21	459	20	136	51	1721	11
	larch	10	100	80	39	9	100	676	18	386	19	591	18	1752	10
	Arolla pine	0	.	0	.	11	100	159	29	283	29	0	.	453	21
	other conifers	0	.	120	47	0	.	0	.	10	100	0	.	130	44
	beech	3121	7	2338	8	2093	10	101	42	192	29	745	14	8589	5
	maple	505	16	547	15	673	15	22	71	87	48	54	45	1889	8
	ash	313	26	833	14	486	17	41	60	41	61	99	38	1812	10
	oak	317	21	388	22	106	42	0	.	31	75	225	28	1066	13
	sweet chestnut	0	.	10	100	0	.	10	100	0	.	604	17	624	17
	other broadleaves	171	26	470	20	432	21	97	42	82	44	682	16	1933	9
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	7521	5	9062	4	11602	4	3230	8	4500	7	4030	6	39945	2
32-35 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1778	10	3001	8	5478	6	1299	12	2498	9	926	15	14980	4
	fir	1257	12	1073	13	1337	10	69	52	19	71	68	61	3822	7
	pine	323	23	281	22	158	33	271	23	369	25	86	65	1489	11
	larch	49	53	79	39	33	72	641	15	453	17	440	20	1695	9
	Arolla pine	0	.	0	.	11	100	146	27	259	23	0	.	416	17
	other conifers	0	.	40	50	0	.	0	.	0	.	0	.	40	50
	beech	2640	8	1992	8	1878	9	59	47	178	30	421	19	7168	5
	maple	343	20	305	21	391	18	10	100	50	52	21	71	1120	11
	ash	318	19	587	17	310	21	20	70	10	100	74	47	1320	10
	oak	138	34	423	18	54	100	0	.	20	100	94	33	729	15
	sweet chestnut	0	.	10	100	9	100	23	71	0	.	384	19	425	18
	other broadleaves	143	50	460	17	262	24	60	47	50	52	553	17	1527	10
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	6989	5	8250	5	9920	4	2597	8	3908	7	3067	7	34730	2
36-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1375	8	2625	6	4933	4	865	10	1687	8	681	12	12166	3
	fir	1043	8	975	9	1187	8	64	36	51	33	74	31	3395	5
	pine	374	18	455	16	136	25	255	18	277	18	42	47	1540	8
	larch	0	.	76	29	47	53	513	14	381	13	303	16	1320	8
	Arolla pine	0	.	0	.	21	67	78	25	148	24	0	.	247	17
	other conifers	0	.	12	58	0	.	0	.	0	.	4	100	16	50
	beech	1856	7	1707	7	1238	8	27	55	122	24	320	14	5270	4
	maple	243	15	212	16	342	13	12	100	21	45	20	60	850	8
	ash	160	25	500	12	167	18	4	100	19	51	19	50	868	9
	oak	116	25	307	13	48	37	11	100	13	75	59	44	553	11
	sweet chestnut	0	.	4	100	0	.	0	.	0	.	192	17	196	17
	other broadleaves	119	25	225	19	126	25	28	46	36	36	161	18	693	10
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	5284	4	7097	4	8245	3	1859	7	2755	6	1874	6	27114	2
40-43 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1264	7	2453	6	4009	5	659	11	1683	8	565	13	10633	3
	fir	864	8	922	9	933	9	45	41	54	29	55	37	2874	5
	pine	248	18	378	14	90	32	149	25	220	19	53	46	1138	8
	larch	20	60	61	36	43	38	471	13	408	13	365	14	1368	7
	Arolla pine	0	.	0	.	5	100	43	37	112	23	0	.	160	19
	other conifers	0	.	37	50	0	.	0	.	0	.	0	.	37	50
	beech	1407	7	1393	7	1104	9	26	73	84	36	231	15	4245	4
	maple	123	20	129	22	163	17	0	.	8	71	4	100	427	11
	ash	142	19	402	13	162	19	4	100	6	100	12	58	729	9
	oak	72	25	267	16	8	70	4	100	8	71	49	38	409	12
	sweet chestnut	0	.	4	100	0	.	0	.	0	.	184	24	188	23
	other broadleaves	53	30	170	17	62	38	0	0	4	100	129	24	419	12
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4194	4	6217	4	6579	4	1401	8	2588	6	1648	7	22626	2
44-47 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1143	8	2155	6	3525	5	520	11	1323	8	376	13	9042	3
	fir	677	9	805	9	901	9	16	61	67	28	60	25	2525	5
	pine	155	20	301	15	93	35	79	32	161	19	8	100	797	9
	larch	4	100	63	29	38	37	411	13	330	14	254	14	1101	7
	Arolla pine	0	.	0	.	0	.	103	32	99	24	0	.	203	20
	other conifers	0	.	8	71	0	.	0	.	0	.	0	.	8	71
	beech	1069	8	1049	8	772	11	0	.	105	25	190	19	3186	5
	maple	58	27	84	27	107	24	0	.	9	72	9	71	267	14
	ash	51	31	256	15	68	27	8	71	4	100	14	59	400	12
	oak	32	40	231	18	9	71	4	100	17	80	24	57	317	15
	sweet chestnut	0	.	4	100	4	100	0	.	0	.	162	26	170	25
	other broadleaves	8	71	95	30	78	32	21	60	6	100	44	33	252	17
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	3197	4	5050	4	5595	4	1162	8	2121	6	1141	7	18267	2
48-51 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	902	8	1700	7	2860	5	344	13	1024	8	393	14	7223	3
	fir	464	12	642	10	712	9	47	41	62	33	69	32	1996	6
	pine	106	24	179	17	51	31	47	36	117	22	4	100	503	10
	larch	4	100	62	34	25	47	360	14	254	16	194	15	899	8
	Arolla pine	0	.	0	.	0	.	20	45	68	28	4	100	91	23
	other conifers	4	100	32	43	0	.	0	.	0	.	0	.	37	40
	beech	655	12	791	8	610	11	9	71	39	37	99	20	2204	6
	maple	62	26	42	36	85	26	0	.	12	58	0	.	201	16
	ash	39	36	152	21	28	38	0	.	8	71	0	.	227	16
	oak	86	37	169	20	0	.	0	.	12	73	24	46	291	17
	sweet chestnut	0	.	4	100	5	100	0	.	0	.	100	23	109	22
	other broadleaves	20	53	50	36	43	39	4	100	4	100	16	50	136	21
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	2343	5	3824	4	4418	4	831	9	1600	7	903	8	13919	2
52-55 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	625	10	1198	7	2121	6	247	18	739	9	289	14	5219	4
	fir	410	16	552	11	562	10	28	47	49	29	37	40	1637	7
	pine	64	32	147	18	20	52	73	36	81	27	15	50	400	12
	larch	8	71	25	47	41	37	293	15	206	16	171	17	743	9
	Arolla pine	0	.	0	.	0	0	15	60	32	35	0	.	47	31
	other conifers	0	.	16	61	0	.	0	.	0	.	0	.	16	61
	beech	407	11	605	10	500	14	8	71	27	51	72	28	1619	7
	maple	8	71	46	35	37	36	0	.	4	100	0	.	94	23
	ash	15	60	124	22	29	42	0	.	0	.	0	.	168	18
	oak	15	59	129	23	23	45	4	100	4	100	10	72	184	18
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	96	23	96	23
	other broadleaves	17	60	31	43	36	41	8	70	0	.	12	58	105	23
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	1569	7	2872	5	3368	5	676	11	1141	7	702	9	10329	2
56-59 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	516	10	884	8	1528	7	242	17	626	9	209	16	4005	4
	fir	303	13	385	12	424	12	23	52	19	52	16	50	1171	7
	pine	47	31	97	24	13	71	24	47	57	29	4	100	243	14
	larch	0	.	49	36	49	40	185	20	159	17	148	19	590	10
	Arolla pine	0	.	0	.	0	.	4	100	52	30	0	.	56	29
	other conifers	4	100	16	80	0	.	0	.	0	.	0	.	21	67
	beech	267	14	395	12	240	15	4	100	32	35	74	26	1011	7
	maple	14	58	26	41	11	74	0	.	4	100	0	.	54	29
	ash	13	58	58	35	22	45	0	.	0	.	6	100	99	25
	oak	28	54	158	19	16	58	0	.	0	.	9	71	210	17
	sweet chestnut	0	.	0	.	14	77	0	.	0	.	88	26	102	25
	other broadleaves	0	.	17	50	25	53	4	100	0	.	6	100	52	33
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	1192	7	2086	5	2342	5	486	13	948	8	559	9	7613	3
60-63 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	263	14	539	10	818	9	107	21	377	12	143	21	2247	5
	fir	156	17	168	16	241	14	20	45	21	45	16	50	621	9
	pine	32	51	49	31	0	.	4	100	17	50	4	100	106	23
	larch	0	.	4	100	28	55	161	18	64	25	88	23	345	12
	Arolla pine	0	.	0	.	4	100	9	72	24	41	0	.	37	34
	other conifers	0	.	12	74	0	.	0	.	0	.	0	.	12	74
	beech	93	23	223	16	188	21	0	.	4	100	42	32	551	11
	maple	8	71	4	100	22	46	0	.	0	.	0	.	34	36
	ash	4	100	33	39	7	100	0	.	4	100	0	.	48	33
	oak	15	61	41	35	0	.	0	.	4	100	9	71	69	27
	sweet chestnut	0	.	0	.	0	0	0	.	0	.	45	33	45	33
	other broadleaves	4	100	18	51	5	100	0	.	0	.	14	59	41	34
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	575	10	1091	7	1312	7	301	13	514	10	360	12	4153	4
64-67 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	163	17	344	12	748	9	102	23	234	15	107	22	1698	6
	fir	124	19	113	20	169	17	16	50	22	47	28	50	471	10
	pine	4	100	31	39	15	59	0	.	17	50	0	.	66	27
	larch	0	.	12	58	8	71	63	25	42	35	43	33	168	16
	Arolla pine	0	.	0	.	0	.	8	71	20	45	0	.	28	38
	other conifers	0	.	5	100	0	.	0	.	0	.	0	.	5	100
	beech	79	29	145	20	46	33	0	.	0	.	8	71	278	15
	maple	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	ash	9	71	47	36	0	.	0	.	4	100	0	.	60	31
	oak	17	63	24	46	0	.	0	.	0	.	0	.	41	37
	sweet chestnut	0	.	0	.	5	100	0	.	0	.	35	40	40	37
	other broadleaves	0	.	11	73	4	100	0	.	0	.	5	100	20	51
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	399	12	732	8	995	7	188	17	339	12	226	15	2879	4
68-71 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	130	19	222	15	520	10	35	45	154	17	95	26	1156	7
	fir	55	29	75	25	147	18	0	.	4	100	4	100	284	13
	pine	0	.	4	100	0	.	0	.	9	71	0	.	13	58
	larch	0	.	25	56	8	71	77	26	40	32	60	27	211	15
	Arolla pine	0	.	0	.	0	.	8	71	20	45	0	.	27	38
	other conifers	4	100	8	71	0	.	0	.	0	.	0	.	12	58
	beech	50	29	132	19	0	.	0	.	11	74	11	57	205	15
	maple	0	.	6	100	4	100	0	.	0	.	0	.	9	73
	ash	0	.	8	100	4	100	0	.	0	.	0	.	12	74
	oak	0	.	55	31	0	.	0	.	0	.	0	.	55	31
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	44	32	44	32
	other broadleaves	0	.	12	58	0	.	0	.	0	.	4	100	16	50
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	240	14	547	10	683	9	120	22	238	14	218	16	2045	5
72-75 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	58	27	83	27	270	14	31	35	128	20	60	29	629	9
	fir	47	30	76	26	62	26	0	.	11	58	4	100	200	15
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	4	100	4	100	4	100	39	34	24	47	24	41	99	22
	Arolla pine	0	.	0	.	0	.	19	45	4	100	0	.	23	41
	other conifers	0	.	12	58	0	.	0	.	0	.	0	.	12	58
	beech	19	45	81	27	12	58	0	.	0	.	17	50	129	20
	maple	0	.	0	.	0	.	0	.	6	100	0	.	6	100
	ash	0	.	12	58	0	.	0	.	0	.	0	.	12	58
	oak	0	.	29	42	10	72	0	.	0	.	0	.	39	36
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	23	46	23	46
	other broadleaves	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	127	18	297	14	359	12	90	22	173	17	131	19	1177	7
76-79 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	37	37	33	39	165	17	21	45	60	26	51	30	367	11
	fir	29	42	30	38	12	58	0	.	8	71	9	70	87	23
	pine	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	larch	0	.	0	.	0	.	55	29	28	38	24	41	108	20
	Arolla pine	0	.	0	.	0	.	0	.	8	71	4	100	12	58
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	4	100	63	32	14	58	0	.	0	.	8	71	88	26
	maple	0	.	6	100	7	71	0	.	0	.	4	100	17	51
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	10	73	5	100	0	.	0	.	0	.	15	59
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	21	45	21	45
	other broadleaves	0	.	10	72	0	.	0	.	0	.	0	.	10	72
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	70	31	155	21	202	15	76	25	104	20	121	20	728	9
80-83 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	43	30	70	31	12	58	23	41	25	41	173	17
	fir	20	45	29	43	41	34	0	.	0	.	0	.	89	23
	pine	0	.	0	.	0	.	0	.	4	100	0	.	4	100
	larch	0	.	0	.	0	.	12	58	8	71	13	58	32	35
	Arolla pine	0	.	0	.	0	.	0	.	4	100	0	.	4	100
	other conifers	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	beech	4	100	23	45	13	58	4	100	4	100	17	78	64	31
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	6	100	0	.	0	.	0	.	0	.	6	100
	oak	0	.	20	45	0	.	0	.	0	.	0	.	20	45
	sweet chestnut	0	.	0	.	0	.	4	100	0	.	42	47	46	43
	other broadleaves	0	.	9	71	0	.	0	.	0	.	0	.	9	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	23	41	134	19	124	21	32	35	42	30	97	28	452	11
84-87 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	13	58	12	58	70	28	8	71	17	50	8	71	127	19
	fir	0	.	8	71	26	41	0	.	4	100	4	100	42	32
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	13	58	4	100	18	50	35	36
	Arolla pine	0	.	0	.	0	.	0	.	4	100	0	.	4	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	4	100	16	50	8	71	0	.	0	.	4	100	32	35
	maple	0	.	0	.	12	76	0	.	0	.	0	.	12	76
	ash	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	oak	0	.	8	71	0	.	0	.	0	.	0	.	8	71
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	27	42	27	42
	other broadleaves	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	16	50	53	28	116	22	21	45	29	38	61	27	296	13
88-91 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	8	71	16	50	37	33	4	100	8	71	12	58	85	22
	fir	0	.	17	50	23	46	0	.	0	.	6	100	46	32
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	8	71	8	71	5	100	21	45
	Arolla pine	0	.	0	.	0	.	4	100	0	.	0	.	4	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	18	50	0	.	0	.	0	.	0	.	18	50
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	12	58	0	.	0	.	0	.	0	.	12	58
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	14	58	14	58
	other broadleaves	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	8	71	63	26	60	27	16	50	16	50	41	34	204	14
92-95 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	4	100	12	58	0	0	0	.	6	100	22	45
	fir	4	100	4	100	0	.	0	.	0	.	0	.	8	71
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	4	100	0	.	4	100	0	.	5	100	13	59
	Arolla pine	0	.	0	.	0	.	0	0	4	100	0	.	4	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	9	71	0	.	0	.	0	.	0	.	9	71
	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	.	8	71	8	71
	other broadleaves	0	.	5	100	0	.	0	.	0	.	0	.	5	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4	100	29	38	12	58	4	100	4	100	20	51	72	24
96-99 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4	100	9	71	12	58	4	100	8	71	9	71	46	30
	fir	0	.	0	.	12	58	0	.	0	.	0	.	12	58
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	4	100	0	.	8	71	12	58
	Arolla pine	0	.	0	.	0	.	4	100	0	.	0	.	4	100
	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	.	19	60	19	60
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4	100	9	71	24	41	12	58	8	71	36	39	92	22
100-103 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	5	100	12	58	0	.	14	59	4	100	34	36
	fir	0	.	0	.	0	.	0	.	4	100	0	.	4	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	4	100	4	100	0	.	8	71
	Arolla pine	0	.	0	.	0	.	4	100	0	.	0	.	4	100
	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	.	17	60	17	60
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	8	71	12	58	8	71	22	45	20	53	71	26
104-107 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	11	58	0	.	0	.	4	100	15	50
	fir	0	.	4	100	4	100	0	.	0	.	6	100	14	59
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	4	100	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	.	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	.	10	72	10	72
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	4	100	15	50	0	.	4	100	23	45	46	30
108-111 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	4	100	0	.	4	100	4	100	12	58
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	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	.	4	100	0	.	4	100
	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	0	0
	other broadleaves	5	100	0	.	0	.	0	.	0	.	0	.	5	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	5	100	0	.	4	100	4	100	8	71	8	71	29	38
112-115 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	.	4	100	0	.	0	.	4	100
	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	100	9	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	4	100	0	.	9	100	13	77
116-119 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	5	100	0	.	0	.	0	.	5	100
	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	.	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	.	5	100	0	.	0	.	4	100	9	71
120-123 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	.
124-127 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	.	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	.	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	.	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
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	.	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	.	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	.	4	100	4	100
132-135 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
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	.	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	.
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	.	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	.
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	.	18	62	18	62
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	18	62	18	62
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	.	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	.
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	.	8	100	8	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	8	100	8	100
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	.	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
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	.	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	.
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	.	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
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	.	19	100	19	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	.	19	100	19	100
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	.	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	.
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	.	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
=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	.	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	.
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	21651	5	42953	5	73013	3	15680	8	31045	5	10263	8	194606	2
	fir	15183	5	14969	6	18747	5	1269	26	1150	16	1329	19	52647	3
	pine	2479	13	3087	11	1883	21	5575	15	5401	13	519	39	18945	7
	larch	189	37	1230	19	535	26	8207	9	4872	9	5903	9	20936	5
	Arolla pine	0	.	0	.	168	64	1717	18	2449	16	37	70	4371	12
	other conifers	587	32	1023	22	413	31	31	58	562	35	138	97	2754	14
	beech	27219	4	27004	4	24996	6	1142	30	2426	18	11285	10	94072	2
	maple	5209	7	5207	9	8309	7	407	26	693	27	832	21	20658	4
	ash	3581	12	7278	8	5519	10	564	25	724	34	2018	16	19683	5
	oak	2510	17	5057	12	790	25	678	24	159	60	2228	18	11422	8
	sweet chestnut	10	100	74	78	156	68	88	66	0	.	11373	9	11702	9
	other broadleaves	4573	9	7259	8	10085	8	3570	15	2830	14	14917	8	43235	4
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	83192	2	115143	2	144615	3	38928	5	52310	4	60843	3	495030	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. 1350055. Birmensdorf, Swiss Federal Research Institute WSL

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