Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI4
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 NFI4/NFI5
grid: 1.4 km grid, subgrids 1-5
state 2009/17
		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	9993	9	7917	10	4006	12	3943	13	7918	10	2240	16	36016	4
	fir	6051	9	3244	13	1428	18	290	35	139	66	305	33	11457	6
	pine	233	54	179	59	180	65	1056	32	1127	27	49	100	2824	17
	larch	349	84	202	50	164	56	1264	17	780	22	1433	20	4193	12
	Arolla pine	0	.	0	.	0	.	273	40	575	27	32	100	880	22
	other conifers	678	29	102	58	158	59	70	61	501	36	0	.	1508	19
	beech	8863	6	2836	13	2396	16	579	33	236	37	3102	15	18011	5
	maple	2907	12	1582	18	830	23	619	27	319	38	573	33	6831	8
	ash	2354	14	838	25	750	23	238	32	255	41	891	25	5326	9
	oak	874	40	89	66	57	58	499	37	0	.	513	34	2032	21
	sweet chestnut	17	100	0	.	0	.	84	100	0	.	2813	21	2914	21
	other broadleaves	4084	11	2748	15	1865	20	2213	16	2218	22	6016	13	19144	6
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	36403	4	19737	6	11835	8	11128	8	14066	8	17967	7	111136	2
16-19 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	6923	9	6414	9	3747	12	2825	15	5559	10	1551	17	27019	4
	fir	4445	9	2215	14	980	21	214	33	180	37	160	48	8195	7
	pine	239	55	121	77	71	61	1106	28	904	28	16	100	2457	17
	larch	106	53	171	50	61	72	1292	16	542	26	1134	19	3305	10
	Arolla pine	0	.	0	.	0	.	268	36	898	25	0	.	1167	21
	other conifers	334	28	69	100	52	58	52	74	158	45	0	.	666	22
	beech	6892	7	2363	14	1888	16	579	32	310	34	2605	16	14636	5
	maple	2368	11	1285	18	819	20	411	28	124	43	422	33	5429	8
	ash	1635	15	411	26	676	26	410	40	219	39	443	32	3795	10
	oak	794	28	71	79	0	.	127	43	15	100	489	41	1497	21
	sweet chestnut	0	.	0	.	0	.	63	100	0	.	2490	18	2553	18
	other broadleaves	1985	13	1163	21	1373	25	1366	19	1594	25	3843	14	11324	8
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	25722	4	14284	6	9666	9	8713	8	10504	8	13152	7	82041	2
20-23 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	5402	9	4110	10	3194	13	2518	15	4347	11	1485	15	21057	5
	fir	3021	11	1612	14	576	21	141	40	121	47	213	35	5685	7
	pine	258	31	139	63	141	59	1101	25	619	28	16	100	2275	16
	larch	138	46	53	58	121	55	1021	21	635	30	1111	20	3080	12
	Arolla pine	0	.	0	.	0	.	266	29	284	34	16	100	566	22
	other conifers	188	33	35	71	57	58	35	100	35	71	0	.	350	24
	beech	5165	8	2061	13	1490	15	246	38	177	43	2040	17	11178	6
	maple	1862	15	811	19	523	23	177	34	36	71	160	37	3568	10
	ash	1042	15	436	25	767	23	237	44	186	60	318	36	2986	11
	oak	504	24	102	54	21	100	250	39	0	.	311	30	1188	16
	sweet chestnut	0	.	0	.	0	.	0	0	0	.	2474	18	2474	18
	other broadleaves	1612	13	559	23	774	27	662	21	927	28	2496	14	7030	8
	indeterminable	0	.	0	0	0	0	0	0	0	0	0	0	0	0
	total	19192	4	9917	7	7665	9	6654	9	7368	9	10640	7	61436	3
24-27 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4459	10	4373	11	2734	13	1754	14	3296	11	1099	17	17715	5
	fir	2280	12	1393	15	658	20	181	42	52	58	88	66	4653	8
	pine	411	29	139	88	66	59	729	23	395	33	0	0	1739	16
	larch	51	74	73	80	18	100	657	21	302	27	1100	18	2200	12
	Arolla pine	0	.	0	.	0	.	244	33	554	25	0	.	799	20
	other conifers	102	41	52	74	0	.	0	.	17	100	0	.	172	35
	beech	4825	7	1595	14	1181	17	363	40	278	39	1570	18	9813	6
	maple	1334	14	872	21	671	20	73	50	181	43	39	70	3169	10
	ash	803	19	442	26	645	27	161	43	91	83	305	32	2447	12
	oak	777	24	45	72	18	100	76	50	15	100	344	29	1275	17
	sweet chestnut	0	.	0	.	0	.	21	100	15	100	1331	19	1367	19
	other broadleaves	905	15	411	24	308	36	309	28	252	32	1696	15	3883	9
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	.	0	0
	total	15947	4	9396	7	6300	9	4568	10	5450	9	7572	7	49233	3
28-31 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3674	10	3796	10	2297	14	1819	15	2671	12	1073	16	15330	5
	fir	1654	14	942	16	414	29	91	45	37	71	126	43	3265	9
	pine	365	36	122	71	171	42	353	29	325	27	68	60	1404	16
	larch	103	47	54	75	18	100	712	19	488	23	875	21	2249	12
	Arolla pine	0	.	0	.	0	.	228	33	322	29	0	.	550	22
	other conifers	138	39	17	100	15	100	0	0	0	.	0	.	170	35
	beech	4122	9	1255	13	1386	15	239	39	197	37	1067	21	8267	6
	maple	1049	15	728	18	624	21	66	50	92	67	116	48	2675	10
	ash	878	16	338	32	395	26	152	72	130	43	80	81	1973	12
	oak	627	20	38	71	0	0	70	61	0	.	225	39	961	17
	sweet chestnut	0	.	0	.	0	.	37	100	0	.	1153	21	1190	20
	other broadleaves	506	22	140	48	267	29	146	39	80	60	995	15	2135	11
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	13117	5	7431	7	5587	9	3914	10	4343	9	5778	7	40170	3
32-35 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3185	10	3183	10	1997	12	1145	17	2400	11	845	21	12755	5
	fir	1774	12	951	17	373	24	90	53	21	100	109	47	3317	9
	pine	467	23	35	70	70	100	320	30	362	30	16	100	1270	15
	larch	120	38	23	100	18	100	659	23	473	22	510	23	1803	12
	Arolla pine	0	.	0	.	0	.	103	47	268	32	0	.	371	26
	other conifers	68	61	0	.	0	.	0	.	0	.	0	.	68	61
	beech	3406	9	1145	19	555	20	87	53	104	41	550	24	5846	7
	maple	708	16	291	31	333	25	36	71	37	71	36	70	1441	12
	ash	813	17	350	33	272	28	143	76	0	.	38	71	1615	14
	oak	432	22	21	100	0	.	0	.	0	.	125	41	577	19
	sweet chestnut	0	.	0	.	0	.	61	76	0	.	618	24	679	22
	other broadleaves	540	21	61	60	166	34	35	71	38	71	684	22	1524	13
	indeterminable	0	0	0	0	0	.	0	.	0	.	0	0	0	0
	total	11513	5	6059	7	3783	9	2678	11	3702	9	3531	9	31267	3
36-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2581	8	2665	8	1658	11	1163	13	1934	9	750	16	10752	4
	fir	1265	10	620	12	379	18	87	44	56	47	81	41	2487	7
	pine	531	19	77	47	46	47	204	22	228	24	27	60	1113	12
	larch	62	37	7	100	44	53	470	19	388	22	489	18	1460	10
	Arolla pine	0	.	0	.	0	.	99	35	141	34	0	.	240	25
	other conifers	34	53	7	100	0	.	0	.	0	.	0	.	41	47
	beech	2972	6	686	15	733	14	63	57	132	37	390	19	4975	5
	maple	508	13	259	22	271	25	26	60	59	79	23	58	1146	11
	ash	757	15	166	31	186	24	29	80	23	58	39	44	1200	11
	oak	317	19	17	71	32	60	21	58	7	100	74	33	468	15
	sweet chestnut	7	100	0	.	0	.	10	100	0	.	357	21	374	20
	other broadleaves	320	18	86	32	39	41	64	51	83	40	415	19	1008	11
	indeterminable	0	.	0	0	0	0	0	.	0	0	0	0	0	0
	total	9354	4	4590	6	3388	8	2237	9	3051	8	2644	7	25264	2
40-43 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2287	7	2410	8	1527	11	648	15	1792	9	680	16	9343	4
	fir	1420	9	559	14	474	19	66	43	14	71	73	37	2607	7
	pine	419	17	73	51	45	53	194	29	154	27	28	62	913	12
	larch	41	47	15	71	21	77	551	18	353	20	396	17	1376	10
	Arolla pine	0	.	10	100	0	.	50	43	149	27	0	.	209	22
	other conifers	41	58	0	.	0	.	0	.	0	.	0	.	41	58
	beech	2494	7	599	17	815	15	36	68	97	34	298	20	4338	5
	maple	302	16	131	26	181	22	22	100	15	71	22	58	674	11
	ash	531	15	73	31	181	27	15	100	0	.	27	70	827	12
	oak	325	19	22	58	9	100	21	75	0	.	70	43	448	16
	sweet chestnut	0	.	7	100	0	.	0	.	6	100	351	22	364	22
	other broadleaves	303	24	60	51	19	58	81	44	7	100	196	25	667	15
	indeterminable	0	0	0	0	0	0	0	.	0	0	0	.	0	0
	total	8164	4	3959	6	3272	8	1684	10	2586	8	2141	8	21808	2
44-47 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1792	8	1957	9	1241	11	733	13	1236	10	481	17	7439	4
	fir	1207	9	505	14	423	16	83	38	41	49	51	37	2310	7
	pine	316	17	18	72	32	50	105	33	130	35	7	100	607	13
	larch	62	36	14	71	8	100	418	19	363	17	221	22	1085	11
	Arolla pine	0	.	0	.	0	.	55	47	67	34	0	.	123	28
	other conifers	34	53	0	.	0	.	0	.	0	.	8	100	42	47
	beech	2057	7	600	14	487	16	15	71	104	40	143	27	3406	6
	maple	260	18	59	37	110	27	6	100	7	100	0	.	443	14
	ash	413	16	64	36	120	32	12	100	7	100	8	100	624	13
	oak	247	19	21	71	7	100	0	.	12	100	72	46	360	17
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	193	25	193	25
	other broadleaves	139	29	50	55	26	80	16	71	15	70	146	26	392	17
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	.	0	0
	total	6526	4	3287	7	2454	8	1444	10	1983	8	1329	9	17022	2
48-51 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1633	8	1742	9	1025	11	533	15	1278	10	391	16	6602	4
	fir	1083	10	487	14	295	20	58	47	49	38	74	33	2046	7
	pine	243	20	70	65	23	58	21	74	108	32	0	.	465	17
	larch	35	45	14	71	6	100	362	18	307	20	233	21	957	11
	Arolla pine	0	.	0	.	0	.	49	43	78	33	0	.	127	26
	other conifers	55	53	0	.	0	.	0	.	0	.	0	.	55	53
	beech	1763	7	427	19	335	18	16	72	40	48	238	22	2818	6
	maple	111	25	129	41	102	29	0	.	30	61	0	.	373	18
	ash	376	17	33	51	95	26	0	.	0	.	41	62	544	13
	oak	246	23	0	.	8	100	0	.	13	71	18	71	286	21
	sweet chestnut	0	.	0	.	0	.	7	100	0	.	104	28	111	27
	other broadleaves	178	30	18	75	35	52	8	100	7	100	41	53	287	22
	indeterminable	0	.	0	0	0	0	0	.	0	0	0	.	0	0
	total	5722	4	2921	8	1925	8	1054	11	1911	8	1139	9	14671	3
52-55 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1089	9	1356	10	955	12	414	16	734	12	338	20	4886	5
	fir	850	11	455	14	216	22	40	52	36	53	74	39	1670	8
	pine	166	21	19	73	0	.	41	57	98	35	14	100	338	17
	larch	36	45	14	71	8	100	406	19	246	20	244	19	954	11
	Arolla pine	0	.	0	.	0	.	14	71	29	50	0	.	43	41
	other conifers	41	47	0	.	0	.	0	.	0	.	0	.	41	47
	beech	1117	9	302	19	284	19	7	100	26	50	124	29	1860	7
	maple	56	35	23	59	59	39	0	.	14	71	8	100	159	22
	ash	235	18	20	58	47	41	7	100	0	.	0	.	309	15
	oak	134	24	0	.	0	.	8	100	14	100	18	72	174	22
	sweet chestnut	0	.	0	.	0	.	0	.	6	100	113	33	119	32
	other broadleaves	74	46	51	49	29	50	8	100	7	100	24	58	192	25
	indeterminable	0	.	0	.	0	.	0	0	0	.	0	.	0	0
	total	3796	5	2241	7	1597	9	945	12	1209	9	956	10	10745	3
56-59 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1279	9	1009	11	747	13	354	18	612	13	354	19	4356	5
	fir	684	11	319	17	200	20	42	46	38	46	51	47	1334	8
	pine	102	30	11	100	16	71	24	59	43	41	0	.	195	21
	larch	47	43	22	58	28	62	283	19	273	20	157	23	809	11
	Arolla pine	0	.	0	.	0	.	0	.	43	41	0	.	43	41
	other conifers	7	100	0	.	0	.	0	.	0	.	8	100	15	71
	beech	933	10	218	21	197	24	26	77	33	52	54	38	1461	8
	maple	69	32	15	72	24	58	0	.	0	.	0	.	108	26
	ash	211	23	21	74	13	71	0	.	0	.	13	100	259	21
	oak	41	41	0	.	6	100	0	.	0	.	0	.	47	38
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	106	32	106	32
	other broadleaves	34	67	63	63	15	72	7	100	12	100	15	71	146	34
	indeterminable	0	.	0	.	0	.	0	0	0	.	0	.	0	0
	total	3407	5	1677	8	1245	10	736	13	1055	10	758	13	8879	3
60-63 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	714	11	682	12	542	18	184	22	387	16	142	24	2650	6
	fir	486	13	297	18	127	36	7	100	19	58	8	100	945	10
	pine	35	45	13	71	0	.	7	100	36	45	7	100	99	27
	larch	7	100	7	100	0	.	125	29	170	25	93	33	401	16
	Arolla pine	0	.	0	.	0	.	0	.	29	61	0	.	29	61
	other conifers	20	58	0	.	0	.	0	.	0	.	0	.	20	58
	beech	476	13	79	30	64	37	6	100	14	71	74	34	714	11
	maple	35	53	30	60	18	100	0	.	14	71	0	.	96	34
	ash	113	25	15	71	19	73	0	.	0	.	0	.	148	23
	oak	97	30	0	.	0	.	0	.	6	100	8	100	111	28
	sweet chestnut	0	.	0	.	0	.	27	77	0	.	30	50	57	45
	other broadleaves	28	50	24	71	15	72	7	100	19	72	8	100	102	30
	indeterminable	0	.	0	0	0	.	0	0	0	.	0	.	0	0
	total	2011	7	1148	9	786	16	363	16	693	12	370	15	5371	4
64-67 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	442	15	514	14	430	16	138	30	267	19	135	22	1927	7
	fir	392	16	282	22	66	33	15	100	28	50	14	70	797	12
	pine	34	45	11	100	0	.	0	.	36	53	0	.	81	33
	larch	14	71	0	.	6	100	207	31	74	32	72	34	372	20
	Arolla pine	0	.	0	.	0	.	7	100	7	100	0	.	14	71
	other conifers	20	58	0	.	0	.	0	.	0	.	0	.	20	58
	beech	308	15	101	28	90	32	0	.	14	71	52	42	564	12
	maple	21	58	0	.	7	100	0	.	0	.	0	.	28	50
	ash	32	65	15	71	7	100	0	.	0	.	10	100	65	41
	oak	59	39	0	.	0	.	0	.	0	.	7	100	67	36
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	16	71	16	71
	other broadleaves	14	71	0	.	0	.	0	.	0	.	0	.	14	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	1336	8	924	11	605	13	367	22	426	15	306	16	3964	5
68-71 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	349	15	343	15	264	18	132	29	195	23	140	28	1422	8
	fir	343	15	135	26	91	34	0	.	6	100	15	71	591	12
	pine	14	71	0	.	7	100	0	.	14	71	0	.	35	45
	larch	7	100	14	71	7	100	98	27	58	40	80	32	263	17
	Arolla pine	0	.	0	.	0	.	7	100	7	100	0	.	14	71
	other conifers	21	58	0	.	0	.	0	.	0	.	0	.	21	58
	beech	234	23	62	33	20	58	0	.	0	.	32	50	349	18
	maple	7	100	13	71	0	.	0	.	0	.	0	.	20	58
	ash	40	45	7	100	6	100	0	.	6	100	0	.	60	36
	oak	55	38	0	.	0	.	0	.	7	100	0	.	62	36
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	44	46	44	46
	other broadleaves	30	50	12	70	9	100	0	.	0	.	0	.	51	38
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	1099	9	587	12	405	15	236	20	293	18	311	17	2931	5
72-75 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	197	20	323	18	214	20	45	50	119	26	98	30	997	10
	fir	114	25	67	35	86	32	7	100	14	71	8	100	296	16
	pine	14	71	0	.	0	.	0	.	0	.	0	.	14	71
	larch	7	100	0	.	16	71	75	34	64	36	34	45	195	20
	Arolla pine	0	.	0	.	0	.	14	71	7	100	0	.	21	58
	other conifers	34	66	0	.	0	.	0	.	0	.	0	.	34	66
	beech	117	25	48	42	50	46	0	.	6	100	7	100	228	19
	maple	9	100	0	.	0	.	0	.	0	.	0	.	9	100
	ash	16	71	0	.	11	100	0	.	0	.	0	.	27	58
	oak	16	71	0	.	0	.	0	.	0	.	0	.	16	71
	sweet chestnut	0	.	0	.	0	.	10	100	0	.	39	44	48	41
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	523	12	438	15	377	16	151	25	210	19	186	20	1885	7
76-79 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	123	28	110	27	163	26	51	38	82	36	68	37	596	13
	fir	103	32	93	30	47	43	7	100	21	58	15	71	287	18
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	78	35	40	46	23	76	142	26
	Arolla pine	0	.	0	.	0	.	21	58	7	100	0	.	28	50
	other conifers	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	beech	59	36	0	0	7	100	6	100	12	70	22	58	107	26
	maple	0	.	7	100	0	.	0	.	0	.	0	.	7	100
	ash	15	71	7	100	7	100	0	.	0	.	0	.	30	50
	oak	15	71	0	.	8	100	0	.	0	.	0	.	23	58
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	16	71	16	71
	other broadleaves	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	329	17	218	20	233	21	164	23	163	24	144	25	1250	9
80-83 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	94	28	97	33	84	33	14	71	77	30	44	41	410	14
	fir	40	41	23	58	17	73	0	.	0	.	0	.	79	30
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	39	45	22	77	36	45	96	30
	Arolla pine	0	.	0	.	0	.	7	100	7	100	0	.	14	71
	other conifers	8	100	0	.	0	.	0	.	0	.	0	.	8	100
	beech	32	51	7	100	0	.	0	.	0	.	22	58	62	36
	maple	0	.	0	.	8	100	0	.	0	.	0	.	8	100
	ash	14	71	0	.	7	100	0	.	0	.	0	.	21	58
	oak	22	58	0	.	8	100	0	.	0	.	0	.	30	50
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	0	0	0
	other broadleaves	7	100	0	.	0	.	0	.	0	.	7	100	14	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	217	19	127	28	124	27	59	36	107	28	109	25	743	10
84-87 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	21	58	52	42	45	41	47	63	30	51	39	46	234	21
	fir	42	41	29	61	14	71	7	100	7	100	0	.	101	29
	pine	7	100	0	.	0	.	0	.	7	100	0	.	14	71
	larch	0	.	0	.	0	.	14	71	21	58	31	51	66	34
	Arolla pine	0	.	0	.	0	.	7	100	7	100	0	.	15	71
	other conifers	8	100	7	100	0	.	0	.	0	.	0	.	15	71
	beech	42	46	7	100	16	71	0	.	0	.	7	100	72	34
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	20	58	0	.	0	.	0	.	0	.	0	.	20	58
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	45	46	45	46
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	140	23	95	31	76	32	76	43	73	32	121	26	582	12
88-91 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	21	58	56	38	51	61	15	71	44	47	15	71	202	23
	fir	29	50	6	100	14	71	0	.	0	.	15	71	63	33
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	15	71	18	73	7	100	40	46
	Arolla pine	0	.	0	.	0	.	7	100	0	.	0	.	7	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	7	100	7	100	0	.	0	.	15	71
	maple	0	.	0	.	6	100	0	.	0	.	0	.	6	100
	ash	10	100	0	.	0	.	0	.	0	.	0	.	10	100
	oak	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	sweet chestnut	0	.	0	.	0	.	8	100	0	.	15	71	23	58
	other broadleaves	14	71	0	.	0	.	0	.	0	.	0	.	14	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	80	30	62	36	78	43	52	38	63	39	52	38	387	15
92-95 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	15	71	0	.	0	0	0	0	6	100	6	100	27	50
	fir	28	50	8	100	0	.	0	.	0	.	10	100	47	41
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	7	100	8	100	0	.	15	71
	Arolla pine	0	.	0	.	0	.	7	100	0	.	0	.	7	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	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	7	100	7	100
	other broadleaves	12	100	0	.	0	.	0	.	0	.	0	.	12	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	61	36	8	100	0	0	14	71	14	71	24	59	122	25
96-99 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	20	58	15	71	0	.	0	.	0	.	35	45
	fir	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	14	71	0	.	0	.	14	71
	Arolla pine	0	.	0	.	0	.	0	0	0	.	0	.	0	0
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	16	100	0	.	0	.	0	.	0	.	0	.	16	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	7	100	7	100
	other broadleaves	12	100	0	.	0	.	0	.	0	.	0	.	12	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	42	54	20	58	15	71	14	71	0	.	7	100	98	30
100-103 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	14	71	14	71	0	.	14	71	11	100	54	38
	fir	14	71	0	.	0	.	0	.	0	.	0	.	14	71
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	7	100	7	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	.	8	100	8	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	14	71	14	71	14	71	0	.	14	71	26	59	83	30
104-107 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	21	58	0	.	7	100	7	100	0	.	0	.	35	45
	fir	0	.	7	100	0	.	0	.	0	.	0	.	7	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	21	58	7	100	7	100	7	100	0	.	0	.	42	41
108-111 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	7	100	7	100	0	.	15	71	0	.	30	50
	fir	7	100	0	.	0	.	0	.	0	.	0	.	7	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	.	7	100	7	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	7	100	7	100	7	100	0	.	15	71	7	100	44	41
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	.	8	100	7	100	15	71
	Arolla pine	0	.	0	.	0	.	7	100	7	100	0	.	14	71
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	6	100	6	100
	other broadleaves	18	100	0	.	0	.	0	.	0	.	0	.	18	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	18	100	0	.	0	.	7	100	15	71	14	71	54	45
116-119 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	.	7	100	0	.	7	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	.	7	100	0	.	7	100
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	.	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	.	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	18	100	0	.	0	.	0	.	0	.	0	.	18	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	18	100	0	.	0	.	0	.	0	.	0	.	18	100
132-135 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	8	100	8	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	.	8	100	8	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	.	6	100	6	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	6	100	6	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	.	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
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	.	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
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	.	6	100	6	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	6	100	6	100
160-163 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
164-167 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
168-171 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	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	.	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	.	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	.	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	.	6	100	6	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	6	100	6	100
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	46293	5	43152	6	26966	8	18481	10	35015	7	11990	10	181897	3
	fir	27341	6	14250	8	6880	11	1426	25	878	27	1491	25	52265	4
	pine	3852	13	1026	51	867	39	5261	20	4586	19	249	63	15841	10
	larch	1183	32	682	34	542	44	8767	11	5641	12	8293	11	25108	6
	Arolla pine	0	.	10	100	0	.	1734	22	3488	18	49	100	5280	14
	other conifers	1838	18	289	70	282	39	156	53	712	34	16	100	3293	15
	beech	45885	4	14392	9	12001	10	2274	28	1779	24	12396	13	88727	3
	maple	11606	7	6235	12	4586	13	1437	22	929	33	1398	26	26191	5
	ash	10295	8	3239	16	4206	15	1405	31	918	41	2211	24	22274	6
	oak	5626	14	426	37	174	35	1073	31	91	72	2274	23	9664	11
	sweet chestnut	23	76	7	100	0	.	328	75	28	100	12379	13	12765	13
	other broadleaves	10839	8	5445	13	4943	18	4924	15	5258	21	16583	10	47992	5
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	164782	2	89155	4	61445	6	47265	6	59321	5	69328	4	491296	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. 1350094. Birmensdorf, Swiss Federal Research Institute WSL

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