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: protection forest region
unit: 1000 n
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
state 1993/95
		protection forest region
		Jura + Plateau		Northwestern Alps		Northeastern Alps		Southwestern Alps		Southeastern 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	14207	7	8437	7	5126	10	3473	10	6211	8	1707	14	39161	4
	fir	5658	7	3192	9	1553	12	498	26	169	28	300	27	11369	5
	pine	461	22	254	42	74	47	1355	21	1374	21	38	100	3556	12
	larch	217	33	10	100	104	51	1391	15	637	21	876	17	3236	9
	Arolla pine	0	.	0	.	0	.	256	29	296	27	10	100	562	19
	other conifers	661	22	52	45	133	43	93	69	321	30	0	.	1259	16
	beech	9834	5	3741	11	2671	11	653	27	370	26	3643	12	20913	4
	maple	2689	9	1223	15	811	20	313	26	196	36	306	27	5538	7
	ash	2119	12	516	20	808	21	328	26	227	40	887	18	4885	8
	oak	1351	18	96	37	20	70	286	29	0	0	688	28	2442	13
	sweet chestnut	20	71	0	.	0	.	40	77	0	.	3435	13	3495	13
	other broadleaves	4450	8	2320	12	2007	15	2346	14	1746	17	5668	10	18538	5
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	41667	3	19842	5	13306	7	11032	7	11548	6	17559	5	114954	2
16-19 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	9309	7	6792	7	4153	10	2763	10	4382	8	1324	13	28722	3
	fir	4090	7	2125	10	1014	13	277	30	116	33	261	31	7881	5
	pine	581	25	148	42	159	44	1385	18	977	19	39	79	3289	11
	larch	169	34	20	71	44	60	1133	14	501	18	694	19	2561	9
	Arolla pine	0	.	21	100	11	100	227	26	408	26	0	.	667	19
	other conifers	359	28	19	71	62	47	62	100	171	52	0	.	673	22
	beech	7897	5	2469	10	1886	11	505	26	344	23	2721	12	15821	4
	maple	1837	10	1092	13	798	17	244	28	132	44	118	36	4220	7
	ash	1530	12	653	21	615	20	199	34	171	42	525	23	3692	8
	oak	1100	18	155	43	22	71	251	29	19	71	480	25	2027	13
	sweet chestnut	20	71	0	.	0	.	33	76	0	.	2758	13	2811	12
	other broadleaves	2563	9	1284	14	855	19	1151	15	1050	26	3606	8	10510	5
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	29454	3	14778	5	9619	6	8229	6	8271	7	12525	5	82875	2
20-23 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	6270	7	5703	7	3290	10	2144	11	3648	9	1220	13	22275	3
	fir	2721	8	1570	11	794	15	242	29	119	39	125	33	5571	6
	pine	361	22	167	55	158	40	952	19	771	20	9	100	2420	11
	larch	176	42	30	58	20	71	894	15	463	18	738	17	2321	9
	Arolla pine	0	.	11	100	10	100	293	23	351	26	0	.	665	17
	other conifers	212	28	21	71	11	100	10	100	50	52	0	.	304	22
	beech	6750	5	1917	10	1515	13	307	28	321	30	1627	13	12436	4
	maple	1381	12	779	14	703	16	79	43	30	58	129	35	3101	7
	ash	1521	12	399	22	657	21	99	44	111	49	234	29	3020	9
	oak	1078	18	157	39	10	100	88	43	39	62	311	25	1683	13
	sweet chestnut	10	100	0	.	0	.	44	80	0	.	1760	13	1814	12
	other broadleaves	1510	10	617	18	651	21	492	19	294	25	2031	10	5596	6
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	21990	3	11369	5	7819	7	5648	7	6196	7	8184	5	61206	2
24-27 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4787	7	5059	7	2791	12	1880	11	3166	8	978	14	18661	4
	fir	2335	8	1139	12	642	15	171	34	69	38	93	37	4449	6
	pine	411	21	102	45	162	35	564	19	387	22	29	58	1655	11
	larch	215	27	20	71	48	53	1037	15	444	19	509	19	2274	9
	Arolla pine	0	.	32	100	32	76	312	26	270	26	0	.	646	18
	other conifers	138	41	0	.	20	71	0	.	10	100	0	.	168	35
	beech	5622	6	1802	13	1368	12	199	32	209	31	1017	14	10217	4
	maple	1485	9	530	17	559	16	30	58	59	41	147	28	2809	7
	ash	1244	11	347	27	445	23	77	38	60	62	148	33	2321	9
	oak	867	15	78	66	24	71	49	53	0	.	228	28	1245	13
	sweet chestnut	0	.	0	.	0	.	51	53	9	100	1238	15	1299	14
	other broadleaves	1009	12	372	21	416	19	217	26	220	30	1122	15	3356	7
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	18113	3	9481	5	6507	7	4588	7	4903	7	5509	6	49101	2
28-31 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3932	7	4232	7	2349	9	1774	11	2847	9	764	15	15899	3
	fir	2224	8	1068	12	533	16	59	56	100	35	91	47	4076	6
	pine	438	19	97	37	161	33	479	21	421	21	125	54	1721	11
	larch	90	37	0	.	19	71	695	18	407	20	541	18	1752	10
	Arolla pine	0	.	11	100	0	.	159	29	283	29	0	.	453	21
	other conifers	120	47	0	.	0	.	0	.	10	100	0	.	130	44
	beech	5295	6	1299	14	1031	13	110	37	109	33	745	14	8589	5
	maple	962	11	378	19	422	20	43	50	30	74	54	45	1889	8
	ash	1096	13	209	26	318	23	69	43	21	71	99	38	1812	10
	oak	682	16	86	49	54	52	10	100	10	100	225	28	1066	13
	sweet chestnut	10	100	0	.	0	.	10	100	0	.	604	17	624	17
	other broadleaves	619	16	224	33	177	27	149	35	101	40	663	16	1933	9
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	15469	3	7603	6	5064	6	3557	8	4340	7	3912	6	39945	2
32-35 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4340	6	3505	7	2341	11	1426	11	2499	9	868	16	14980	4
	fir	2073	9	1058	12	535	16	78	47	10	100	68	61	3822	7
	pine	581	16	55	54	140	36	271	23	357	26	86	65	1489	11
	larch	128	32	20	100	42	50	654	14	441	17	410	21	1695	9
	Arolla pine	0	.	11	100	0	.	146	27	259	23	0	.	416	17
	other conifers	40	50	0	.	0	.	0	.	0	.	0	.	40	50
	beech	4339	6	1165	12	1053	12	103	35	88	43	421	19	7168	5
	maple	636	14	226	25	207	24	19	71	11	100	21	71	1120	11
	ash	869	13	168	26	170	31	29	58	10	100	74	47	1320	10
	oak	561	16	54	100	0	.	0	.	20	100	94	33	729	15
	sweet chestnut	10	100	0	.	0	.	32	58	0	.	384	19	425	18
	other broadleaves	613	17	119	41	109	32	84	39	50	52	553	17	1527	10
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	14188	3	6380	6	4596	7	2842	8	3744	7	2979	8	34730	2
36-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3618	5	3409	5	1835	8	944	9	1715	8	646	12	12166	3
	fir	1821	6	912	10	465	13	84	30	38	39	74	31	3395	5
	pine	841	12	50	33	79	35	255	18	272	18	42	47	1540	8
	larch	72	30	12	58	50	41	552	13	360	14	276	17	1320	8
	Arolla pine	0	.	21	67	0	.	78	25	148	24	0	.	247	17
	other conifers	12	58	0	.	0	.	0	.	0	.	4	100	16	50
	beech	3355	5	681	10	803	11	31	50	79	27	320	14	5270	4
	maple	416	11	157	18	220	16	20	67	17	50	20	60	850	8
	ash	629	12	75	28	123	21	8	71	15	59	19	50	868	9
	oak	423	12	39	42	13	58	11	100	16	71	51	48	553	11
	sweet chestnut	4	100	0	.	0	.	0	.	4	100	188	17	196	17
	other broadleaves	345	15	71	38	49	31	36	42	31	39	161	18	693	10
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	11536	3	5427	4	3636	6	2020	7	2695	6	1801	6	27114	2
40-43 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3424	5	2800	6	1419	8	757	11	1704	8	528	13	10633	3
	fir	1644	6	671	10	392	15	72	38	39	32	55	37	2874	5
	pine	608	11	60	41	54	34	149	25	215	19	53	46	1138	8
	larch	86	30	24	47	21	54	501	13	416	12	321	15	1368	7
	Arolla pine	0	.	0	.	5	100	43	37	112	23	0	.	160	19
	other conifers	37	50	0	.	0	.	0	.	0	.	0	.	37	50
	beech	2625	5	702	11	603	13	16	50	69	43	231	15	4245	4
	maple	239	16	72	26	104	21	4	100	4	100	4	100	427	11
	ash	536	11	75	28	95	26	4	100	6	100	12	58	729	9
	oak	332	14	8	100	8	70	4	100	12	58	45	40	409	12
	sweet chestnut	4	100	0	.	0	.	0	.	0	.	184	24	188	23
	other broadleaves	214	15	46	47	15	50	10	73	8	71	125	25	419	12
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	9748	3	4458	5	2715	6	1560	8	2584	6	1560	7	22626	2
44-47 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3021	5	2389	6	1371	8	592	10	1312	8	357	13	9042	3
	fir	1317	7	672	11	382	14	39	44	54	32	60	25	2525	5
	pine	456	12	68	44	30	43	75	33	161	19	8	100	797	9
	larch	67	28	24	47	28	52	437	12	326	14	218	15	1101	7
	Arolla pine	0	.	0	.	0	.	103	32	99	24	0	.	203	20
	other conifers	8	71	0	.	0	.	0	.	0	.	0	.	8	71
	beech	2020	5	448	14	461	13	4	100	62	29	190	19	3186	5
	maple	118	20	43	32	98	27	0	.	0	.	9	71	267	14
	ash	267	14	39	47	68	27	8	71	4	100	14	59	400	12
	oak	263	17	9	71	0	.	4	100	17	80	24	57	317	15
	sweet chestnut	4	100	0	.	0	.	4	100	0	.	162	26	170	25
	other broadleaves	98	29	23	47	43	44	37	49	6	100	44	33	252	17
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	7640	3	3715	5	2481	6	1303	8	2042	6	1086	7	18267	2
48-51 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2385	5	1942	7	1083	9	416	12	1045	8	353	15	7223	3
	fir	1022	8	581	10	222	16	47	41	55	36	69	32	1996	6
	pine	281	14	26	46	35	39	47	36	111	22	4	100	503	10
	larch	66	32	19	53	4	100	382	14	259	15	170	16	899	8
	Arolla pine	0	.	0	.	0	.	20	45	68	28	4	100	91	23
	other conifers	37	40	0	.	0	.	0	.	0	.	0	.	37	40
	beech	1401	7	353	13	303	17	25	56	23	47	99	20	2204	6
	maple	105	21	53	33	36	39	0	.	8	71	0	.	201	16
	ash	182	19	8	71	32	35	0	.	4	100	0	.	227	16
	oak	255	18	0	.	0	.	0	.	16	61	21	51	291	17
	sweet chestnut	4	100	0	.	0	.	5	100	4	100	96	24	109	22
	other broadleaves	59	33	28	50	18	50	10	73	4	100	16	50	136	21
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	5796	3	3010	5	1734	7	952	9	1596	7	831	8	13919	2
52-55 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1678	6	1391	8	810	10	326	16	744	9	272	14	5219	4
	fir	841	10	469	11	220	17	33	43	38	34	37	40	1637	7
	pine	206	16	11	73	24	56	73	36	70	27	15	50	400	12
	larch	33	39	28	42	21	53	308	15	215	16	138	17	743	9
	Arolla pine	0	.	0	0	0	.	15	60	32	35	0	.	47	31
	other conifers	16	61	0	.	0	.	0	.	0	.	0	.	16	61
	beech	953	8	330	19	233	18	8	71	23	57	72	28	1619	7
	maple	49	33	19	51	22	45	0	.	4	100	0	.	94	23
	ash	139	20	18	50	12	74	0	.	0	.	0	.	168	18
	oak	144	21	13	58	4	100	10	72	4	100	10	72	184	18
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	96	23	96	23
	other broadleaves	52	33	20	63	12	58	8	70	0	.	12	58	105	23
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4110	4	2300	6	1357	8	780	10	1130	7	652	9	10329	2
56-59 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1262	7	1007	8	619	10	293	16	627	9	196	16	4005	4
	fir	628	10	357	14	127	22	23	52	19	52	16	50	1171	7
	pine	145	19	13	71	0	.	24	47	57	29	4	100	243	14
	larch	45	39	24	53	25	47	212	19	151	18	133	19	590	10
	Arolla pine	0	.	0	.	0	.	4	100	52	30	0	.	56	29
	other conifers	21	67	0	.	0	.	0	.	0	.	0	.	21	67
	beech	612	9	166	18	136	19	4	100	20	45	74	26	1011	7
	maple	40	34	4	100	7	100	0	.	4	100	0	.	54	29
	ash	76	29	9	71	8	71	0	.	0	.	6	100	99	25
	oak	181	18	11	71	9	71	0	.	0	.	9	71	210	17
	sweet chestnut	0	.	0	.	0	.	14	77	0	.	88	26	102	25
	other broadleaves	21	45	12	75	9	100	4	100	0	.	6	100	52	33
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	3031	4	1603	7	939	9	579	12	930	8	531	10	7613	3
60-63 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	685	9	535	11	365	14	157	20	387	12	118	22	2247	5
	fir	279	13	187	16	98	22	20	45	21	45	16	50	621	9
	pine	77	28	0	.	4	100	4	100	17	50	4	100	106	23
	larch	4	100	17	61	4	100	182	18	68	24	71	25	345	12
	Arolla pine	0	.	0	.	4	100	9	72	24	41	0	.	37	34
	other conifers	12	74	0	.	0	.	0	.	0	.	0	.	12	74
	beech	295	13	123	27	86	28	0	.	4	100	42	32	551	11
	maple	12	58	12	58	10	74	0	.	0	.	0	.	34	36
	ash	33	39	0	.	11	72	0	.	4	100	0	.	48	33
	oak	56	30	0	.	0	.	0	.	4	100	9	71	69	27
	sweet chestnut	0	.	0	.	0	.	0	0	0	.	45	33	45	33
	other broadleaves	22	45	5	100	0	.	0	.	0	.	14	59	41	34
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	1475	6	879	8	581	11	373	13	528	10	317	12	4153	4
64-67 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	454	10	482	11	295	14	134	20	238	15	96	23	1698	6
	fir	197	15	143	19	73	25	16	50	15	50	28	50	471	10
	pine	31	40	15	59	4	100	0	.	17	50	0	.	66	27
	larch	8	71	4	100	9	71	75	24	42	35	31	35	168	16
	Arolla pine	0	.	0	.	0	.	8	71	20	45	0	.	28	38
	other conifers	5	100	0	.	0	.	0	.	0	.	0	.	5	100
	beech	187	18	40	37	43	37	0	.	0	.	8	71	278	15
	maple	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	ash	52	34	0	.	4	100	0	.	4	100	0	.	60	31
	oak	36	40	0	.	5	100	0	.	0	.	0	.	41	37
	sweet chestnut	0	.	0	.	0	.	5	100	0	.	35	40	40	37
	other broadleaves	11	73	4	100	0	.	0	.	0	.	5	100	20	51
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	984	7	687	9	432	12	237	15	335	12	203	16	2879	4
68-71 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	318	13	287	12	252	16	54	38	159	17	86	27	1156	7
	fir	117	20	108	21	48	33	4	100	4	100	4	100	284	13
	pine	4	100	0	.	0	.	0	.	9	71	0	.	13	58
	larch	23	58	0	.	10	72	89	24	45	30	43	32	211	15
	Arolla pine	0	.	0	.	0	.	8	71	20	45	0	.	27	38
	other conifers	12	58	0	.	0	.	0	.	0	.	0	.	12	58
	beech	182	16	0	.	0	.	0	.	11	74	11	57	205	15
	maple	6	100	4	100	0	.	0	.	0	.	0	.	9	73
	ash	8	100	4	100	0	.	0	.	0	.	0	.	12	74
	oak	41	34	7	100	7	100	0	.	0	.	0	.	55	31
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	44	32	44	32
	other broadleaves	12	58	0	.	0	.	0	.	0	.	4	100	16	50
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	723	8	409	10	318	14	155	19	248	14	192	16	2045	5
72-75 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	110	20	142	19	146	20	47	31	128	20	56	30	629	9
	fir	104	21	65	28	15	50	0	.	11	58	4	100	200	15
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	8	71	4	100	0	.	47	31	28	43	12	58	99	22
	Arolla pine	0	.	0	.	0	.	19	45	4	100	0	.	23	41
	other conifers	8	71	4	100	0	.	0	.	0	.	0	.	12	58
	beech	88	25	21	53	4	100	0	.	0	.	17	50	129	20
	maple	0	.	0	.	6	100	0	.	0	.	0	.	6	100
	ash	8	71	0	.	4	100	0	.	0	.	0	.	12	58
	oak	29	42	0	.	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	355	12	236	16	185	17	113	20	172	18	115	20	1177	7
76-79 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	66	28	87	23	73	26	30	44	60	26	51	30	367	11
	fir	41	34	22	45	7	71	0	.	8	71	9	70	87	23
	pine	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	larch	0	.	0	.	0	.	64	27	28	38	16	50	108	20
	Arolla pine	0	.	0	.	0	.	0	.	12	58	0	.	12	58
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	65	31	10	71	6	100	0	.	0	.	8	71	88	26
	maple	6	100	4	100	4	100	0	.	0	.	4	100	17	51
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	10	73	0	.	5	100	0	.	0	.	0	.	15	59
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	21	45	21	45
	other broadleaves	10	72	0	.	0	.	0	.	0	.	0	.	10	72
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	201	19	122	20	95	23	94	23	108	19	108	21	728	9
80-83 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	35	33	28	42	43	42	20	45	27	38	21	45	173	17
	fir	32	35	43	35	10	72	4	100	0	.	0	.	89	23
	pine	0	.	0	.	0	.	0	.	4	100	0	.	4	100
	larch	0	.	0	.	0	.	12	58	13	58	8	71	32	35
	Arolla pine	0	.	0	.	0	.	0	.	4	100	0	.	4	100
	other conifers	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	beech	23	46	8	71	8	71	4	100	4	100	17	78	64	31
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	6	100	0	.	0	.	0	.	0	.	0	.	6	100
	oak	20	45	0	.	0	.	0	.	0	.	0	.	20	45
	sweet chestnut	0	.	0	.	0	.	4	100	0	.	42	47	46	43
	other broadleaves	9	71	0	.	0	.	0	.	0	.	0	.	9	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	128	19	79	25	61	33	45	30	51	28	88	30	452	11
84-87 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	16	50	54	33	25	41	8	71	17	50	8	71	127	19
	fir	8	71	22	45	4	100	0	.	4	100	4	100	42	32
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	17	50	9	71	9	71	35	36
	Arolla pine	0	.	0	.	0	.	0	.	4	100	0	.	4	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	20	45	4	100	4	100	0	.	0	.	4	100	32	35
	maple	0	.	8	100	4	100	0	.	0	.	0	.	12	76
	ash	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	oak	8	71	0	.	0	.	0	.	0	.	0	.	8	71
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	27	42	27	42
	other broadleaves	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	61	26	88	25	37	36	25	41	34	36	52	29	296	13
88-91 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	25	41	12	58	20	45	8	71	8	71	12	58	85	22
	fir	14	60	21	45	4	100	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	18	50	0	.	0	.	0	.	0	.	0	.	18	50
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	12	58	0	.	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	69	25	34	35	25	41	19	45	16	50	41	34	204	14
92-95 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4	100	4	100	8	71	0	0	0	.	6	100	22	45
	fir	8	71	0	.	0	.	0	.	0	.	0	.	8	71
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	4	100	0	.	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	9	71	0	.	0	.	0	.	0	.	0	.	9	71
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	8	71	8	71
	other broadleaves	5	100	0	.	0	.	0	.	0	.	0	.	5	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	33	36	4	100	8	71	4	100	4	100	20	51	72	24
96-99 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	8	71	4	100	13	58	4	100	8	71	9	71	46	30
	fir	0	.	8	71	4	100	0	.	0	.	0	.	12	58
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	8	71	0	.	4	100	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	.	4	100	14	71	19	60
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	8	71	12	58	17	50	16	50	12	58	27	46	92	22
100-103 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	8	71	8	71	0	.	18	51	0	.	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	4	100	0	.	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	4	100	8	71	8	71	8	71	26	41	17	60	71	26
104-107 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	8	71	4	100	0	.	0	.	4	100	15	50
	fir	4	100	4	100	0	.	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	4	100	12	58	4	100	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	.	5	100	0	.	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	.	4	100	0	.	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	.	5	100	0	0	0	.	4	100	0	.	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	59954	4	48319	4	28443	6	17251	7	30953	5	9686	8	194606	2
	fir	27178	4	14439	6	7141	8	1667	21	893	18	1329	19	52647	3
	pine	5486	8	1066	30	1084	25	5633	14	5219	13	457	42	18945	7
	larch	1408	17	257	25	447	29	8710	9	4875	9	5239	10	20936	5
	Arolla pine	0	.	106	92	62	73	1717	18	2473	16	13	77	4371	12
	other conifers	1701	18	96	42	226	31	165	82	562	35	4	100	2754	14
	beech	51588	3	15280	8	12214	8	1969	22	1735	19	11285	10	94072	2
	maple	9984	6	4603	9	4014	11	752	21	493	27	812	21	20658	4
	ash	10319	6	2520	13	3370	13	821	21	636	37	2018	16	19683	5
	oak	7455	10	712	28	191	30	713	23	157	60	2194	18	11422	8
	sweet chestnut	84	70	0	.	0	.	244	50	21	83	11352	10	11702	9
	other broadleaves	11633	6	5144	10	4362	13	4546	13	3510	17	14039	7	43235	4
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	186792	1	92541	3	61552	5	44187	5	51528	4	58430	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. 1350054. Birmensdorf, Swiss Federal Research Institute WSL

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