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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NFI3
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 2004/07
		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	4712	11	7272	8	11728	6	3591	11	8189	9	2445	12	37936	3
	fir	3733	8	2882	11	3765	8	318	30	179	32	380	24	11256	5
	pine	148	53	176	63	463	33	957	21	1458	18	40	71	3242	12
	larch	10	100	99	41	133	42	1624	17	829	20	1718	13	4413	9
	Arolla pine	0	.	0	.	11	100	314	26	452	22	20	71	797	16
	other conifers	257	37	292	38	336	31	23	71	517	30	10	100	1435	17
	beech	4499	7	5080	7	5174	9	427	30	479	21	3375	12	19035	4
	maple	1467	14	1589	12	2487	12	239	29	206	34	532	21	6520	6
	ash	772	16	1601	14	1483	14	201	36	294	32	1031	18	5381	7
	oak	442	34	486	26	97	56	392	32	0	0	528	24	1945	14
	sweet chestnut	20	100	29	100	55	84	0	.	0	.	2761	16	2865	16
	other broadleaves	1970	11	2383	11	4209	9	2184	17	1971	18	6582	9	19299	5
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	18030	5	21887	4	29942	4	10270	7	14573	6	19420	5	114123	2
16-19 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3396	11	5681	8	9258	6	2628	11	5725	8	1701	12	28389	3
	fir	2301	9	1995	11	2246	9	221	31	159	28	283	27	7204	5
	pine	189	33	118	37	319	38	1027	19	1047	19	19	71	2720	11
	larch	0	0	162	30	140	37	1442	13	748	18	985	15	3477	8
	Arolla pine	0	.	0	.	22	71	225	28	369	21	10	100	626	16
	other conifers	118	37	173	34	246	35	23	71	183	39	0	.	743	18
	beech	3302	8	3497	7	4047	8	283	33	496	20	2839	11	14463	4
	maple	1240	13	1209	14	2225	10	203	31	169	34	381	24	5428	6
	ash	579	20	1375	14	978	15	178	35	213	31	627	21	3951	8
	oak	357	33	475	23	165	35	258	29	12	100	496	32	1764	14
	sweet chestnut	20	100	10	100	29	100	0	0	0	.	2424	13	2483	13
	other broadleaves	916	15	1605	13	2344	12	1148	17	1192	19	4037	9	11243	5
	indeterminable	0	.	0	0	0	0	0	0	0	0	0	0	0	0
	total	12419	5	16298	4	22019	4	7636	7	10311	6	13804	5	82488	2
20-23 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2366	11	4511	9	6988	6	2521	11	4396	8	1250	12	22033	4
	fir	1838	11	1397	11	2266	9	190	27	135	36	202	29	6028	5
	pine	136	31	202	30	165	39	985	19	716	18	50	67	2255	11
	larch	0	0	102	43	107	52	966	19	499	18	1075	15	2748	10
	Arolla pine	0	.	0	.	21	100	277	21	380	27	10	100	688	18
	other conifers	136	43	149	37	114	43	0	.	80	46	10	100	489	21
	beech	3075	8	3161	7	3132	8	221	33	270	29	2048	13	11908	4
	maple	892	13	1017	16	1493	11	123	46	109	41	113	44	3746	7
	ash	470	18	947	13	1113	20	149	43	166	39	495	25	3340	9
	oak	239	30	428	22	166	41	118	37	30	74	449	21	1430	12
	sweet chestnut	0	.	10	100	11	100	0	.	0	.	1890	12	1911	12
	other broadleaves	603	16	903	15	1093	14	680	17	591	22	2721	10	6592	6
	indeterminable	0	0	0	.	0	0	0	0	0	0	0	0	0	0
	total	9755	5	12827	4	16671	4	6230	8	7371	6	10314	5	63167	2
24-27 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1787	11	3261	9	6859	6	1765	12	3069	9	1213	13	17955	4
	fir	1000	12	1095	12	1540	11	148	38	120	29	135	35	4038	6
	pine	239	27	163	38	162	36	644	20	448	21	19	71	1676	11
	larch	30	100	134	38	50	45	814	15	533	16	926	14	2487	8
	Arolla pine	0	.	0	.	30	74	338	23	399	22	0	.	768	16
	other conifers	76	55	117	33	21	71	0	.	21	71	10	100	244	25
	beech	2944	8	2480	8	2672	9	91	46	392	24	1346	13	9925	4
	maple	670	13	608	16	1459	10	20	71	68	47	167	30	2992	7
	ash	491	22	695	15	867	17	20	71	96	42	244	31	2412	9
	oak	363	23	604	20	91	45	62	41	0	0	330	27	1450	12
	sweet chestnut	0	.	10	100	0	0	0	.	0	.	1230	14	1240	14
	other broadleaves	418	17	818	14	881	14	317	20	244	28	1719	10	4396	6
	indeterminable	0	.	0	.	0	0	0	0	0	0	0	.	0	0
	total	8018	5	9985	4	14631	4	4219	8	5389	7	7341	5	49584	2
28-31 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1760	10	2531	9	6069	6	1504	12	2801	9	1095	13	15759	4
	fir	1246	11	1041	12	1354	11	40	61	90	37	116	33	3887	6
	pine	225	33	205	25	209	30	428	21	429	21	106	44	1602	11
	larch	10	100	146	32	54	56	763	15	369	18	560	15	1901	9
	Arolla pine	0	.	0	.	54	60	188	25	252	26	20	71	514	17
	other conifers	57	47	70	43	9	100	13	100	0	.	0	.	150	29
	beech	2646	8	1871	10	2438	9	83	50	237	26	814	16	8089	5
	maple	496	17	576	16	842	13	10	100	117	37	104	42	2146	8
	ash	371	25	718	14	712	18	79	75	60	47	137	29	2077	10
	oak	294	27	334	25	70	60	49	53	21	100	202	30	969	14
	sweet chestnut	0	.	10	100	23	100	20	100	0	.	842	17	895	17
	other broadleaves	259	27	427	20	560	19	89	46	128	34	983	14	2446	9
	indeterminable	0	.	0	.	0	0	0	.	0	0	0	0	0	0
	total	7364	5	7930	5	12395	4	3265	8	4503	7	4979	6	40436	2
32-35 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1333	12	2114	10	5022	6	1360	12	2445	9	653	17	12928	4
	fir	1051	12	760	15	1017	11	71	51	81	35	155	34	3135	7
	pine	269	25	278	28	177	29	300	24	405	20	116	60	1545	11
	larch	20	71	88	37	26	71	606	19	493	18	502	18	1734	10
	Arolla pine	0	.	0	.	21	100	160	28	200	30	10	100	391	20
	other conifers	0	.	59	47	10	100	0	.	0	.	0	.	69	43
	beech	2396	8	1857	9	1499	12	60	47	171	35	553	16	6535	5
	maple	462	17	402	18	464	18	34	58	29	58	57	45	1447	10
	ash	262	23	650	15	429	22	87	71	61	59	83	35	1572	11
	oak	190	24	337	24	67	46	0	.	10	100	224	26	827	14
	sweet chestnut	0	.	0	.	0	.	10	100	0	.	564	16	574	16
	other broadleaves	192	39	320	20	200	26	78	44	68	63	678	15	1536	10
	indeterminable	0	.	0	.	0	0	0	0	0	.	0	.	0	0
	total	6175	5	6864	5	8932	5	2767	9	3963	7	3594	6	32294	2
36-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1186	8	1700	8	4068	5	980	10	1859	7	748	11	10542	3
	fir	884	9	808	9	969	8	68	28	71	36	67	40	2868	5
	pine	323	19	276	17	118	27	253	19	222	20	34	59	1226	9
	larch	16	61	56	31	18	51	476	12	389	14	461	14	1416	7
	Arolla pine	0	.	0	.	4	100	128	23	141	24	0	.	273	16
	other conifers	0	.	35	54	0	.	0	.	0	.	0	.	35	54
	beech	1902	6	1454	7	1393	8	36	40	157	24	450	15	5392	4
	maple	224	14	210	14	321	13	8	71	21	52	51	33	835	8
	ash	201	19	513	16	237	17	12	74	21	44	68	32	1052	10
	oak	139	26	286	19	17	60	19	66	16	79	81	25	558	13
	sweet chestnut	0	.	12	100	4	100	6	100	0	.	330	17	351	17
	other broadleaves	120	30	277	17	140	24	64	37	28	43	343	14	972	9
	indeterminable	0	.	0	.	0	0	0	.	0	0	0	.	0	0
	total	4995	4	5627	4	7289	3	2049	7	2925	6	2635	5	25521	2
40-43 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1126	8	1663	7	3694	5	707	10	1693	8	573	13	9457	3
	fir	773	9	675	10	939	8	66	32	63	26	73	31	2589	5
	pine	219	20	293	17	119	25	142	23	224	19	57	48	1055	9
	larch	8	100	62	31	38	52	531	14	406	13	328	14	1373	8
	Arolla pine	0	.	0	.	26	57	43	41	139	21	0	.	208	18
	other conifers	0	.	24	57	0	.	0	.	0	.	4	100	29	51
	beech	1590	6	1327	7	1107	9	25	57	121	25	318	15	4488	4
	maple	224	16	157	17	216	15	12	75	8	71	13	76	630	9
	ash	131	23	389	12	235	24	8	70	4	100	30	43	797	10
	oak	99	26	262	17	38	43	16	78	8	100	49	46	472	13
	sweet chestnut	0	.	4	100	4	100	0	.	0	.	248	16	256	16
	other broadleaves	109	30	141	22	74	30	27	46	16	50	219	17	586	11
	indeterminable	0	.	0	0	0	0	0	0	0	0	0	0	0	0
	total	4280	4	4998	4	6490	4	1576	8	2682	6	1913	6	21940	2
44-47 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1030	8	1375	8	3174	5	602	11	1401	7	533	13	8115	3
	fir	781	9	612	10	755	9	51	37	51	30	54	33	2304	5
	pine	164	19	259	16	74	29	100	25	163	21	31	68	791	9
	larch	8	71	72	35	35	46	396	15	323	13	328	14	1163	8
	Arolla pine	0	.	0	.	0	.	68	27	76	25	0	.	144	18
	other conifers	0	.	56	39	0	.	0	.	0	.	0	.	56	39
	beech	1137	7	1165	8	863	9	22	69	89	28	217	17	3493	4
	maple	141	18	126	21	164	17	0	.	14	72	0	.	444	11
	ash	107	22	319	15	145	24	0	.	21	51	19	60	611	11
	oak	51	32	181	18	34	46	0	0	16	61	66	32	349	13
	sweet chestnut	0	.	8	100	0	0	0	.	0	.	161	18	168	18
	other broadleaves	12	58	166	22	61	34	8	71	4	100	64	26	316	15
	indeterminable	0	.	0	.	0	0	0	0	0	.	0	.	0	0
	total	3431	4	4339	4	5305	4	1248	8	2157	6	1473	7	17954	2
48-51 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	880	9	1177	8	2632	5	471	13	1040	8	368	14	6566	3
	fir	614	10	616	10	753	9	16	62	51	30	52	34	2101	5
	pine	110	26	193	18	59	38	43	34	134	21	4	100	543	11
	larch	8	71	56	32	30	43	401	13	304	14	303	14	1104	7
	Arolla pine	0	.	0	.	0	.	64	28	87	26	0	.	151	19
	other conifers	0	.	12	58	0	.	0	.	0	.	0	.	12	58
	beech	854	10	864	8	689	11	0	.	46	33	178	18	2631	5
	maple	74	30	58	30	90	27	0	.	16	50	9	71	246	16
	ash	56	28	298	14	82	26	4	100	4	100	14	59	458	11
	oak	55	30	241	17	8	70	0	.	12	58	16	78	333	14
	sweet chestnut	0	.	0	0	4	100	0	.	0	.	154	26	158	26
	other broadleaves	20	45	82	32	63	38	0	.	4	100	39	41	208	19
	indeterminable	0	.	0	.	0	0	0	.	0	0	0	.	0	0
	total	2671	5	3597	4	4410	4	999	9	1699	6	1137	8	14513	2
52-55 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	715	9	990	9	2223	6	289	14	759	9	308	15	5284	3
	fir	400	12	588	10	531	10	47	41	54	28	60	31	1680	6
	pine	74	30	108	21	33	39	43	39	101	25	12	58	370	12
	larch	0	.	51	31	32	44	396	15	217	15	193	16	888	8
	Arolla pine	0	.	0	.	0	0	12	58	28	38	4	100	44	30
	other conifers	0	.	12	58	0	.	0	.	0	.	4	100	16	50
	beech	487	11	680	9	444	12	10	72	51	32	122	20	1793	6
	maple	33	36	44	37	50	29	0	.	4	100	4	100	136	19
	ash	47	30	126	25	26	42	4	100	14	59	8	71	226	17
	oak	39	46	121	23	5	100	4	100	8	71	37	38	214	17
	sweet chestnut	0	.	4	100	0	.	0	.	0	.	87	22	91	22
	other broadleaves	13	58	31	41	49	42	23	52	6	100	25	41	147	21
	indeterminable	0	.	0	.	0	0	0	.	0	0	0	.	0	0
	total	1808	6	2755	5	3392	4	828	10	1241	7	865	8	10889	2
56-59 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	604	11	678	10	1762	7	211	16	681	9	265	15	4200	4
	fir	389	17	420	11	584	11	16	50	50	29	37	36	1496	7
	pine	67	35	105	21	10	72	48	37	42	32	4	100	276	14
	larch	8	71	48	35	33	39	222	15	233	16	198	16	742	8
	Arolla pine	0	.	0	.	0	0	0	.	44	33	0	.	44	33
	other conifers	4	100	28	43	0	.	0	.	0	.	0	.	32	39
	beech	328	13	528	10	429	12	4	100	19	45	80	28	1389	6
	maple	16	50	33	35	23	51	0	.	8	71	0	.	80	24
	ash	14	58	149	18	33	43	0	.	0	.	4	100	200	16
	oak	11	73	130	20	17	50	0	.	0	.	14	59	171	17
	sweet chestnut	0	.	0	.	5	100	0	.	0	.	130	24	135	23
	other broadleaves	8	71	52	41	54	45	16	61	4	100	13	58	147	24
	indeterminable	0	.	0	.	0	0	0	0	0	0	0	.	0	0
	total	1449	7	2171	5	2950	5	517	10	1081	7	744	9	8913	3
60-63 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	342	13	524	11	1134	8	162	22	351	12	158	18	2670	5
	fir	222	15	329	13	338	13	31	49	20	45	11	58	951	7
	pine	29	38	75	26	4	100	12	58	29	38	0	0	148	18
	larch	0	.	20	45	20	51	169	23	115	21	114	22	438	12
	Arolla pine	0	.	0	.	4	100	8	71	36	33	0	.	48	29
	other conifers	0	.	12	58	0	.	0	.	0	.	0	.	12	58
	beech	198	16	321	12	157	19	0	.	20	45	50	31	746	8
	maple	9	71	17	50	26	47	0	.	0	.	0	.	53	31
	ash	19	52	45	34	11	72	0	.	0	.	10	72	86	25
	oak	30	62	82	29	10	72	0	.	0	.	4	100	126	25
	sweet chestnut	0	.	0	.	9	71	0	.	0	.	51	33	60	30
	other broadleaves	16	50	15	59	30	76	0	.	0	.	0	0	61	42
	indeterminable	0	.	0	.	0	0	0	0	0	0	0	.	0	0
	total	865	8	1441	6	1743	6	381	15	570	9	399	11	5399	3
64-67 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	234	18	346	12	649	9	89	27	322	12	103	20	1743	6
	fir	151	17	199	16	240	15	12	58	15	50	8	71	625	9
	pine	10	72	20	45	6	100	4	100	20	45	4	100	64	26
	larch	0	.	15	60	10	72	125	19	69	26	79	24	297	12
	Arolla pine	0	.	0	.	8	71	11	58	12	58	0	.	31	35
	other conifers	0	.	25	59	0	.	0	.	0	.	0	.	25	59
	beech	68	25	199	16	126	24	4	100	4	100	47	32	448	11
	maple	4	100	4	100	4	100	0	.	0	.	0	.	12	58
	ash	10	72	43	34	12	58	0	.	0	.	0	.	65	28
	oak	8	71	63	36	6	100	0	.	4	100	6	100	87	29
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	29	37	29	37
	other broadleaves	0	.	13	58	8	71	0	.	0	.	12	58	33	35
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	484	11	927	8	1068	7	245	15	447	10	288	12	3458	4
68-71 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	139	20	267	14	597	10	96	28	240	16	142	20	1482	6
	fir	163	19	128	20	152	18	12	58	19	45	32	43	506	10
	pine	4	100	12	58	8	71	0	.	18	64	0	.	42	36
	larch	0	.	13	58	26	46	86	23	44	35	73	27	243	14
	Arolla pine	0	.	0	.	0	.	8	71	19	45	0	.	27	38
	other conifers	4	100	8	71	0	.	0	.	0	.	0	.	12	58
	beech	91	36	143	21	95	23	0	.	4	100	24	41	357	14
	maple	6	100	0	.	8	71	0	.	0	.	0	.	13	59
	ash	16	61	33	38	6	100	0	.	4	100	0	.	59	30
	oak	12	58	29	56	0	.	0	.	4	100	4	100	49	38
	sweet chestnut	0	.	0	.	5	100	0	.	0	.	41	34	47	32
	other broadleaves	0	.	4	100	8	71	0	.	0	.	0	.	12	58
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	433	13	638	9	905	8	202	17	353	13	318	13	2849	4
72-75 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	95	24	124	19	436	11	44	37	95	20	77	27	871	8
	fir	71	27	84	22	126	19	8	71	19	52	4	100	313	12
	pine	0	.	8	71	0	.	0	.	0	.	0	.	8	71
	larch	4	100	0	.	8	71	67	34	28	38	38	32	146	20
	Arolla pine	0	.	0	.	0	.	8	71	8	71	0	.	16	50
	other conifers	0	.	5	100	0	.	0	.	0	.	0	.	5	100
	beech	16	50	90	26	17	50	0	.	12	58	4	100	139	19
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	36	39	4	100	0	.	0	.	0	.	40	36
	oak	4	100	34	39	0	.	0	.	0	.	0	.	38	36
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	30	37	30	37
	other broadleaves	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	189	17	384	11	591	9	127	23	162	16	153	18	1608	6
76-79 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	62	26	99	21	240	15	27	38	116	21	64	26	607	9
	fir	29	43	52	29	76	25	0	.	4	100	12	58	172	16
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	4	100	0	.	37	37	20	45	40	32	101	21
	Arolla pine	0	.	0	.	0	.	19	53	12	58	0	.	31	39
	other conifers	4	100	4	100	0	.	0	.	0	.	0	.	8	71
	beech	25	45	72	26	7	71	0	.	0	.	24	41	129	19
	maple	0	.	6	100	8	71	0	.	0	.	0	.	14	59
	ash	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	oak	0	.	36	39	9	71	0	.	0	.	0	.	45	34
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	34	44	34	44
	other broadleaves	0	.	10	72	0	.	0	.	0	.	4	100	14	59
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	119	20	287	13	339	12	83	25	152	18	178	16	1158	6
80-83 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	70	53	12	58	132	20	31	55	59	31	61	30	365	15
	fir	21	53	29	43	26	41	0	.	8	71	4	100	88	24
	pine	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	larch	0	.	0	.	0	.	49	35	16	50	41	34	107	22
	Arolla pine	0	.	0	.	0	.	4	100	4	100	4	100	12	58
	other conifers	0	.	8	71	0	.	0	.	0	.	0	.	8	71
	beech	0	.	42	37	12	58	0	.	0	0	4	100	58	30
	maple	0	.	0	.	4	100	0	.	5	100	0	.	9	72
	ash	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	oak	0	.	5	100	11	71	0	.	0	.	0	.	15	58
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	12	75	12	75
	other broadleaves	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	91	42	104	22	184	17	84	30	92	23	132	20	686	10
84-87 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4	100	20	45	88	23	12	58	29	42	20	45	173	16
	fir	29	38	16	50	25	42	0	.	4	100	4	100	79	23
	pine	0	.	0	.	0	.	0	.	4	100	0	.	4	100
	larch	0	.	0	.	0	.	21	45	16	62	13	58	50	31
	Arolla pine	0	.	0	.	0	.	0	.	8	71	0	.	8	71
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	25	46	12	58	4	100	0	.	0	.	41	34
	maple	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	ash	0	.	6	100	0	.	0	.	0	.	0	.	6	100
	oak	0	.	23	46	0	.	0	.	0	.	0	.	23	46
	sweet chestnut	0	.	0	.	0	.	4	100	0	.	49	31	54	30
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	33	35	89	24	126	19	42	32	60	29	91	22	440	10
88-91 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	16	50	28	38	64	28	12	58	12	58	15	50	148	17
	fir	16	60	25	41	12	58	0	.	4	100	15	78	72	28
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	13	58	4	100	16	50	33	35
	Arolla pine	0	.	0	.	0	.	4	100	0	.	0	.	4	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	4	100	6	100	4	100	0	.	0	.	0	.	14	59
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	oak	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	12	58	12	58
	other broadleaves	0	.	10	72	0	.	0	.	0	.	0	.	10	72
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	36	36	77	25	81	24	29	38	20	45	58	30	300	13
92-95 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	8	71	42	39	0	0	16	50	12	58	78	26
	fir	4	100	8	71	4	100	0	.	0	.	0	.	16	50
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	8	71	8	71	0	.	16	50
	Arolla pine	0	.	0	.	0	.	0	0	4	100	0	.	4	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	12	58	0	.	0	.	0	.	8	71	21	45
	maple	0	.	0	.	4	100	0	.	0	.	0	.	4	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	13	76	0	.	0	.	0	.	0	.	13	76
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	11	71	4	100	0	.	0	.	0	.	15	58
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4	100	52	31	54	34	8	71	29	38	24	41	171	17
96-99 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4	100	0	.	33	39	0	.	8	71	6	100	51	31
	fir	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	8	71	0	.	5	100	13	58
	Arolla pine	0	.	0	.	0	.	4	100	0	.	0	.	4	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	6	100	0	.	0	.	0	.	0	.	6	100
	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	100	8	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4	100	10	72	33	39	12	58	8	71	27	46	93	23
100-103 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4	100	4	100	8	71	0	.	4	100	9	71	29	38
	fir	0	.	0	.	10	73	0	.	0	.	0	.	10	73
	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	.	4	100	0	.	0	.	0	.	0	.	4	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	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4	100	8	71	18	52	0	.	4	100	17	50	52	29
104-107 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	4	100	4	100	4	100	4	100	8	71	25	41
	fir	0	.	0	.	4	100	0	.	4	100	0	.	8	71
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	4	100	4	100	4	100	12	58
	Arolla pine	0	.	0	.	0	.	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	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	8	71	8	71	12	58	12	58	12	58	52	28
108-111 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	5	100	8	71	0	.	9	71	0	.	21	45
	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	.	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	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	5	100	8	71	0	.	17	50	4	100	34	36
112-115 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	4	100	0	.	0	.	4	100	8	71
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	8	71	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	.	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	4	100	0	.	16	50	24	41
116-119 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	4	100	0	.	4	100
	fir	0	.	0	.	4	100	0	.	0	.	0	.	4	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	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	0	.	4	100	0	.	13	58
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	.	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	.	0	.	0	.	9	100	9	100
124-127 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
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	.	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	.	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	.	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	.	12	75	0	.	0	.	0	.	12	75
	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	.	12	75	0	.	0	.	8	71	20	53
136-139 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	.	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	.	4	100	4	100
140-143 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	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	.
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	.	9	71	9	71
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	9	71	9	71
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	.	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	.
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	.	14	76	14	76
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	14	76	14	76
160-163 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
164-167 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	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	.	0	.	0	.	9	100	9	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	.	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
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	.	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	.
176-179 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
180-183 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
184-187 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	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
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	.	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
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	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
=200 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	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
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	21865	6	34395	5	66913	4	17106	8	35325	5	11837	8	187441	2
	fir	15714	5	13760	6	17735	5	1313	24	1202	16	1714	18	51437	3
	pine	2205	14	2495	11	1928	21	4985	14	5461	13	497	39	17570	7
	larch	121	36	1128	17	761	24	9225	9	5670	9	8017	8	24922	5
	Arolla pine	0	.	0	.	202	58	1891	16	2672	15	77	64	4843	11
	other conifers	657	28	1090	22	736	30	59	70	800	30	39	62	3381	13
	beech	25562	4	24885	4	24319	6	1269	28	2567	16	12521	9	91123	3
	maple	5959	7	6055	8	9898	7	649	22	774	24	1434	18	24770	4
	ash	3545	11	7956	7	6374	10	741	31	959	26	2772	15	22346	5
	oak	2333	18	4179	11	810	26	918	24	142	51	2507	18	10889	8
	sweet chestnut	40	100	95	90	149	69	40	77	0	.	11161	10	11487	9
	other broadleaves	4661	9	7273	8	9778	8	4635	14	4254	17	17449	7	48050	4
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	82663	3	103309	2	139603	3	42832	5	59827	4	70025	3	498258	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. 1350077. Birmensdorf, Swiss Federal Research Institute WSL

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