Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI4
number of stems
diameter at breast height (in 4 cm classes) · main tree species
regional demarcation: protection forest region
unit: 1000 n
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
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	9843	6	7721	7	4480	9	3992	9	8078	8	2555	12	36670	3
	fir	5938	7	3074	9	1461	14	418	28	141	46	405	29	11437	5
	pine	229	38	343	42	153	46	924	25	1442	19	38	79	3129	13
	larch	252	65	189	41	121	46	1632	15	1252	24	1443	14	4888	10
	Arolla pine	0	.	0	.	42	71	339	25	565	20	38	61	984	15
	other conifers	631	24	101	47	257	40	71	55	537	27	40	79	1637	15
	beech	9128	5	3051	11	2282	12	550	26	368	24	3412	12	18791	4
	maple	3265	9	1492	13	1040	19	528	21	266	31	607	23	7199	6
	ash	2316	10	827	18	636	20	229	26	243	29	913	19	5163	7
	oak	802	27	107	62	42	50	609	29	10	100	410	25	1980	16
	sweet chestnut	20	71	0	.	0	.	55	84	0	.	2115	18	2190	18
	other broadleaves	4368	8	2544	12	1657	15	2474	12	2157	16	5919	9	19121	4
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	36792	3	19450	5	12171	6	11821	6	15059	6	17897	5	113189	2
16-19 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	6970	7	6196	7	3652	9	2857	10	6255	8	1694	12	27623	3
	fir	4430	7	2087	11	1087	14	326	24	141	30	183	34	8254	5
	pine	210	41	257	41	71	47	799	23	1063	18	19	71	2420	12
	larch	86	40	136	42	44	59	1472	12	791	21	1049	15	3578	8
	Arolla pine	0	.	11	100	22	100	306	24	673	20	0	.	1012	15
	other conifers	416	26	52	82	81	35	31	74	172	39	0	.	751	18
	beech	6477	5	2104	11	1772	12	486	25	363	24	2821	12	14024	4
	maple	2497	9	1193	13	887	15	383	21	127	32	545	22	5632	6
	ash	1919	11	456	19	566	22	293	32	238	28	585	20	4056	8
	oak	731	20	76	64	0	.	246	35	9	100	407	29	1470	14
	sweet chestnut	19	71	0	.	0	.	53	73	0	.	2134	14	2207	13
	other broadleaves	2439	9	1164	14	1236	18	1612	14	1422	18	3963	9	11836	5
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	26194	3	13732	5	9417	6	8865	6	11255	6	13400	5	82863	2
20-23 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	5540	7	4205	8	2964	10	2609	10	4672	8	1436	12	21425	3
	fir	2966	8	1652	10	654	16	267	25	100	38	249	28	5888	6
	pine	209	27	157	43	124	44	926	19	739	20	19	71	2175	12
	larch	95	39	31	58	87	48	1256	13	662	20	1002	15	3133	8
	Arolla pine	0	.	11	100	0	.	260	22	298	23	10	100	578	16
	other conifers	258	24	31	58	63	47	21	100	90	40	0	.	464	18
	beech	5062	6	1929	10	1293	12	328	30	201	30	2056	12	10869	4
	maple	1922	10	935	14	668	17	187	27	70	62	181	27	3963	7
	ash	1151	11	361	22	565	20	182	34	141	47	445	22	2844	8
	oak	531	19	134	41	12	100	208	28	43	60	310	25	1237	12
	sweet chestnut	10	100	0	.	0	.	19	100	0	.	2007	14	2036	14
	other broadleaves	1725	10	550	19	647	21	758	15	821	22	2490	10	6990	6
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	19469	3	9995	5	7075	6	7021	6	7836	6	10205	5	61602	2
24-27 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4511	7	4324	8	2580	10	1845	10	3589	8	1061	13	17910	3
	fir	2219	9	1226	12	664	16	157	32	68	38	143	37	4477	6
	pine	295	25	105	72	98	40	621	18	416	23	0	0	1535	12
	larch	105	37	40	79	10	100	799	14	478	17	1038	14	2470	8
	Arolla pine	0	.	11	100	10	100	324	23	458	22	0	.	803	15
	other conifers	107	30	53	53	10	100	0	.	31	58	0	.	201	24
	beech	4574	6	1504	13	1060	13	272	32	251	28	1458	13	9119	5
	maple	1435	10	799	15	657	17	117	36	130	37	104	37	3242	7
	ash	935	13	379	21	429	24	163	34	98	49	520	25	2523	9
	oak	716	17	55	52	10	100	63	41	9	100	283	24	1136	13
	sweet chestnut	0	.	0	.	0	.	11	100	9	100	1131	15	1152	14
	other broadleaves	1064	11	400	21	269	27	437	18	258	31	1645	11	4072	7
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	.	0	0
	total	15961	3	8895	5	5796	7	4810	7	5796	6	7383	5	48640	2
28-31 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3565	7	3717	7	2267	10	1837	11	3053	9	1061	13	15500	4
	fir	1568	10	999	12	436	20	199	31	80	35	98	35	3381	7
	pine	407	23	111	49	182	32	405	22	361	19	67	47	1535	11
	larch	132	30	30	74	40	61	765	13	560	17	699	17	2227	8
	Arolla pine	0	.	32	100	10	100	353	22	357	22	0	.	751	15
	other conifers	146	29	10	100	9	100	0	0	0	.	0	.	166	27
	beech	4062	7	1254	11	1250	12	192	30	180	27	1050	15	7987	5
	maple	1163	12	650	15	621	21	69	43	71	52	113	35	2687	8
	ash	886	13	239	28	319	22	105	58	72	43	157	44	1777	10
	oak	703	17	47	51	0	0	58	47	0	.	206	28	1014	13
	sweet chestnut	19	100	0	.	0	.	20	100	0	.	1045	15	1084	15
	other broadleaves	702	19	183	30	248	23	246	26	53	52	969	13	2401	9
	indeterminable	0	0	0	.	0	0	0	0	0	0	0	.	0	0
	total	13354	4	7273	5	5382	7	4250	7	4786	7	5465	6	40510	2
32-35 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3147	8	3064	8	1905	10	1285	12	2362	8	842	16	12605	4
	fir	1803	9	859	13	472	17	79	40	51	53	97	37	3362	6
	pine	457	17	83	47	79	61	290	23	312	22	96	65	1318	12
	larch	125	35	23	71	38	61	736	17	463	17	565	16	1949	9
	Arolla pine	0	.	11	100	22	100	173	27	222	27	10	100	438	18
	other conifers	98	43	0	.	10	100	0	.	0	.	0	.	109	40
	beech	3485	7	1105	14	629	14	78	39	98	35	604	17	5999	5
	maple	727	12	267	22	245	23	20	71	50	53	75	44	1384	9
	ash	831	13	263	28	213	24	122	52	26	72	183	32	1637	10
	oak	372	18	31	58	10	100	0	.	10	100	131	31	555	15
	sweet chestnut	0	.	0	.	0	.	33	76	0	.	576	19	609	18
	other broadleaves	498	16	129	31	125	29	84	45	68	43	722	15	1626	9
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	11544	4	5835	6	3748	7	2900	8	3662	7	3901	6	31591	2
36-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2533	6	2669	6	1537	8	1176	9	1985	7	673	12	10573	3
	fir	1397	8	633	9	311	15	99	29	46	37	88	34	2575	5
	pine	501	14	77	36	83	41	197	19	265	19	58	50	1180	9
	larch	90	22	4	100	59	34	562	12	390	15	455	13	1561	7
	Arolla pine	0	.	14	72	4	100	122	23	171	22	0	.	310	15
	other conifers	71	33	4	100	0	.	0	.	0	.	0	.	75	32
	beech	3092	5	739	11	665	11	93	31	117	29	447	13	5153	4
	maple	587	10	248	16	226	19	39	42	37	71	31	38	1169	7
	ash	676	11	130	25	167	19	40	43	13	58	62	36	1088	8
	oak	331	15	27	46	24	51	21	45	8	71	122	25	532	11
	sweet chestnut	12	74	0	.	0	.	6	100	0	.	339	15	356	14
	other broadleaves	384	14	70	31	39	39	78	31	116	34	417	13	1104	8
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	9675	3	4615	4	3115	6	2433	6	3147	5	2691	5	25675	2
40-43 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2256	6	2513	6	1475	8	800	10	1735	7	613	12	9392	3
	fir	1293	7	597	10	410	14	76	32	47	35	81	27	2504	5
	pine	426	14	77	35	59	32	194	21	185	20	42	39	984	9
	larch	66	30	16	50	43	53	555	12	345	15	393	14	1417	7
	Arolla pine	0	.	14	73	0	.	69	27	120	23	0	.	202	17
	other conifers	52	39	0	.	0	.	0	.	0	.	0	.	52	39
	beech	2595	5	616	12	785	11	43	40	77	29	387	14	4503	4
	maple	345	12	140	18	146	19	20	66	12	58	38	37	701	8
	ash	529	11	83	23	168	21	17	61	4	100	60	34	861	9
	oak	317	15	25	57	5	100	20	53	12	100	57	33	436	13
	sweet chestnut	4	100	4	100	0	.	4	100	4	100	302	17	317	16
	other broadleaves	280	17	66	34	27	38	50	41	15	60	227	16	665	10
	indeterminable	0	0	0	0	0	0	0	.	0	0	0	0	0	0
	total	8163	3	4151	5	3117	6	1846	7	2556	6	2202	6	22035	2
44-47 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1879	6	1948	6	1211	8	739	10	1409	8	513	13	7699	3
	fir	1174	7	641	11	369	14	71	30	51	35	58	27	2364	5
	pine	331	13	19	51	44	34	112	23	141	23	27	62	674	9
	larch	50	31	16	50	25	47	459	13	364	14	295	15	1209	7
	Arolla pine	0	.	10	71	4	100	55	32	81	26	0	.	151	19
	other conifers	39	42	0	.	0	.	0	.	0	.	4	100	43	39
	beech	2112	5	517	11	496	12	16	50	76	34	213	18	3430	4
	maple	263	14	52	30	104	22	11	58	4	100	13	76	448	11
	ash	414	12	61	27	110	24	11	74	4	100	32	42	632	10
	oak	267	14	22	50	9	70	0	.	12	74	61	34	370	12
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	202	17	202	17
	other broadleaves	146	21	29	54	34	45	16	50	8	70	169	18	402	12
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	.	0	0
	total	6676	3	3314	5	2406	6	1492	7	2150	6	1588	6	17624	2
48-51 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1592	6	1716	7	996	9	500	11	1166	8	387	12	6357	3
	fir	963	8	474	11	313	14	47	37	42	30	45	32	1884	5
	pine	237	16	54	51	21	45	27	43	111	24	11	58	462	12
	larch	46	33	12	58	23	56	414	13	320	15	241	14	1057	8
	Arolla pine	0	.	0	.	0	.	59	32	103	25	0	.	163	20
	other conifers	54	37	0	.	0	.	0	.	0	.	0	.	54	37
	beech	1750	5	433	14	331	13	23	45	31	39	231	16	2799	4
	maple	129	19	89	34	85	23	0	.	17	62	4	100	324	14
	ash	349	13	34	39	94	21	4	100	6	100	22	62	509	10
	oak	213	18	5	100	4	100	4	100	20	53	21	51	268	16
	sweet chestnut	8	100	0	.	0	.	4	100	0	.	133	20	145	19
	other broadleaves	140	26	15	61	21	52	4	100	4	100	47	35	231	18
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	.	0	0
	total	5481	3	2832	5	1888	6	1088	8	1821	6	1144	7	14254	2
52-55 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1156	7	1368	7	890	9	385	13	853	9	313	15	4965	4
	fir	906	8	519	10	219	16	45	39	56	30	68	31	1812	6
	pine	170	17	11	73	19	65	61	33	107	23	11	74	379	12
	larch	68	27	24	48	8	71	413	13	282	21	254	14	1049	9
	Arolla pine	0	.	0	0	0	.	39	34	36	33	0	.	74	24
	other conifers	28	43	0	.	0	.	0	.	0	.	0	.	28	43
	beech	1218	7	301	14	297	15	8	71	15	50	117	21	1956	5
	maple	72	25	26	41	43	34	0	.	8	71	4	100	152	17
	ash	231	14	20	45	44	32	8	71	0	.	0	.	303	12
	oak	208	19	9	71	0	.	8	71	12	74	24	45	261	16
	sweet chestnut	4	100	0	.	0	.	0	.	4	100	102	25	109	23
	other broadleaves	66	34	34	45	25	41	17	61	4	100	19	51	165	20
	indeterminable	0	0	0	0	0	.	0	0	0	0	0	.	0	0
	total	4126	4	2311	5	1544	7	985	9	1376	8	912	8	11254	2
56-59 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1233	7	1137	8	752	10	308	14	658	10	289	15	4377	4
	fir	727	9	361	12	187	18	43	35	45	35	36	40	1399	6
	pine	145	20	6	100	17	50	54	41	49	31	8	71	278	15
	larch	50	31	20	45	16	62	325	13	262	17	167	16	841	8
	Arolla pine	0	.	0	0	0	.	14	59	36	37	4	100	54	30
	other conifers	4	100	0	.	0	.	0	.	0	.	4	100	8	71
	beech	902	7	240	18	194	17	20	65	27	42	117	24	1500	6
	maple	69	24	12	58	30	38	0	.	0	.	0	.	111	19
	ash	155	20	29	43	16	61	0	.	4	100	16	60	220	16
	oak	86	23	9	71	4	100	0	.	4	100	7	100	109	21
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	126	23	126	23
	other broadleaves	47	39	36	62	9	72	8	71	10	73	16	50	126	25
	indeterminable	0	.	0	.	0	.	0	0	0	.	0	.	0	0
	total	3417	4	1849	6	1224	8	772	9	1094	9	792	9	9148	2
60-63 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	677	9	699	9	460	13	197	16	397	12	136	20	2567	5
	fir	518	10	304	13	148	23	15	78	19	44	20	45	1025	7
	pine	48	29	8	71	10	72	16	50	33	35	4	100	118	19
	larch	22	46	4	100	8	71	135	20	164	18	105	22	438	11
	Arolla pine	0	.	0	.	0	.	0	.	20	53	0	.	20	53
	other conifers	12	58	0	.	0	.	0	.	0	.	0	.	12	58
	beech	512	10	103	23	102	24	4	100	12	58	53	30	786	8
	maple	35	39	17	60	16	72	0	.	8	71	4	100	80	27
	ash	90	21	13	58	12	74	0	.	0	.	4	100	119	19
	oak	113	21	0	.	4	100	0	.	4	100	4	100	126	20
	sweet chestnut	4	100	0	.	0	.	14	77	0	.	64	29	82	27
	other broadleaves	26	49	14	71	9	72	8	70	10	72	14	57	81	26
	indeterminable	0	.	0	0	0	.	0	0	0	0	0	.	0	0
	total	2058	5	1161	7	769	11	389	11	667	9	410	11	5453	3
64-67 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	459	11	465	11	388	12	133	23	308	13	112	20	1865	5
	fir	417	12	264	16	105	22	16	61	20	45	11	57	834	8
	pine	63	27	6	100	4	100	4	100	28	42	0	.	106	21
	larch	23	46	4	100	10	73	214	20	65	25	78	23	394	13
	Arolla pine	0	.	10	72	4	100	11	58	32	35	0	.	57	27
	other conifers	16	50	0	.	0	.	0	.	0	.	0	.	16	50
	beech	333	12	107	24	95	23	4	100	12	58	36	36	587	9
	maple	12	58	0	.	4	100	0	.	0	.	0	.	16	50
	ash	39	41	9	71	8	71	0	.	0	.	6	100	61	31
	oak	64	29	5	100	0	.	5	100	0	.	8	71	82	25
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	26	47	26	47
	other broadleaves	17	50	0	.	0	.	0	.	0	.	9	72	26	41
	indeterminable	0	0	0	.	0	.	0	.	0	.	0	.	0	0
	total	1443	6	870	8	619	10	387	14	465	11	286	13	4070	4
68-71 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	353	12	371	13	291	15	128	22	295	20	122	22	1561	7
	fir	276	13	153	19	79	27	8	71	20	45	20	52	557	9
	pine	25	41	8	71	4	100	0	.	22	56	0	.	59	30
	larch	8	71	12	58	4	100	140	17	64	26	67	25	295	12
	Arolla pine	0	.	0	.	0	0	8	71	19	45	0	.	27	38
	other conifers	16	50	0	.	0	.	0	.	0	.	0	.	16	50
	beech	264	15	69	27	49	33	0	.	0	.	43	34	424	11
	maple	8	71	7	71	0	.	0	.	0	.	0	.	16	50
	ash	55	31	4	100	8	71	0	.	4	100	0	.	71	27
	oak	62	27	0	.	5	100	0	.	8	71	0	.	75	25
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	54	31	54	31
	other broadleaves	43	32	7	71	5	100	0	.	0	.	6	100	62	27
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	1112	7	632	10	445	12	284	13	433	15	312	13	3217	4
72-75 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	193	16	317	13	205	16	73	32	160	19	97	23	1045	7
	fir	151	17	94	24	77	26	4	100	8	71	17	50	351	12
	pine	8	71	0	.	0	.	0	.	0	.	0	.	8	71
	larch	4	100	4	100	13	58	88	25	47	31	33	36	189	16
	Arolla pine	0	.	0	.	0	.	11	58	4	100	0	.	15	50
	other conifers	24	58	0	.	0	.	0	.	0	.	0	.	24	58
	beech	157	17	47	33	36	39	0	.	4	100	11	58	256	13
	maple	5	100	4	100	0	.	0	.	0	.	0	.	9	71
	ash	26	41	0	.	6	100	0	.	0	.	0	.	32	38
	oak	32	38	0	.	0	.	0	.	0	.	0	.	32	38
	sweet chestnut	0	.	0	.	0	.	5	100	0	.	42	34	47	32
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	599	9	466	11	338	13	182	18	223	15	200	15	2008	5
76-79 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	125	20	142	18	162	19	73	25	136	20	53	30	692	8
	fir	136	20	87	23	54	30	12	58	16	50	16	50	320	12
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	68	28	35	36	21	54	123	20
	Arolla pine	0	.	0	.	0	.	15	50	11	58	0	.	27	38
	other conifers	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	beech	73	24	4	100	19	51	4	100	7	71	26	60	134	20
	maple	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	ash	24	45	4	100	8	71	0	.	0	.	0	.	36	36
	oak	27	55	0	.	5	100	0	.	0	.	4	100	36	45
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	32	42	32	42
	other broadleaves	4	100	0	.	0	.	4	100	0	.	0	.	8	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	392	12	241	14	248	15	176	16	206	16	153	19	1415	6
80-83 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	84	23	86	24	84	25	23	41	81	22	54	27	414	10
	fir	48	30	21	45	13	59	0	.	0	.	4	100	85	23
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	4	100	4	100	0	.	35	36	13	77	31	35	87	23
	Arolla pine	0	.	0	.	0	.	4	100	12	58	0	.	16	50
	other conifers	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	beech	52	32	8	71	8	100	0	.	0	.	20	45	88	24
	maple	6	100	0	.	5	100	0	.	0	.	0	.	10	71
	ash	8	71	0	.	4	100	0	.	0	.	0	.	12	58
	oak	22	45	0	.	5	100	0	.	0	.	0	.	26	41
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	15	78	15	78
	other broadleaves	10	72	0	.	0	.	0	.	0	.	8	71	19	51
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	238	14	119	20	119	21	62	26	106	21	133	19	777	8
84-87 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	41	37	71	25	34	36	34	50	34	36	33	36	248	14
	fir	48	29	48	32	20	51	4	100	8	71	0	.	128	19
	pine	4	100	0	.	0	.	0	.	4	100	0	.	8	71
	larch	0	.	0	.	0	.	24	41	16	50	26	41	66	25
	Arolla pine	0	.	0	.	0	.	8	71	4	100	0	.	12	58
	other conifers	8	71	4	100	0	.	0	.	0	.	0	.	12	58
	beech	45	32	4	100	13	58	0	.	0	.	4	100	66	26
	maple	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	12	58	4	100	10	72	0	.	0	.	0	.	26	41
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	42	37	42	37
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	158	17	135	19	77	24	70	30	65	25	105	21	611	9
88-91 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	20	45	39	34	41	47	16	50	40	34	12	58	168	18
	fir	16	50	8	71	21	46	4	100	4	100	8	71	62	26
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	18	51	14	59	13	58	46	32
	Arolla pine	0	.	0	.	0	.	4	100	4	100	0	.	8	71
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	4	100	0	.	4	100	4	100	0	.	0	.	12	58
	maple	0	.	0	.	4	100	0	.	0	.	4	100	8	71
	ash	9	72	0	.	0	.	0	.	0	.	0	.	9	72
	oak	14	59	0	.	0	.	0	.	0	.	0	.	14	59
	sweet chestnut	0	.	0	.	0	.	4	100	0	.	12	58	17	50
	other broadleaves	8	71	0	.	0	.	0	.	0	.	0	.	8	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	72	24	47	31	70	32	51	29	62	27	49	29	351	12
92-95 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	12	58	12	58	15	79	0	0	4	100	11	58	54	32
	fir	28	43	5	100	4	100	0	.	4	100	6	100	46	33
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	17	50	9	71	0	.	25	41
	Arolla pine	0	.	0	.	0	.	4	100	4	100	0	.	8	71
	other conifers	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	beech	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	oak	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	8	71	8	71
	other broadleaves	6	100	0	.	0	.	4	100	0	.	0	.	10	73
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	58	29	20	45	19	66	25	41	21	45	25	41	167	17
96-99 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	23	41	18	51	0	.	0	.	4	100	45	30
	fir	4	100	8	71	0	.	0	.	0	.	0	.	12	58
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	8	71	4	100	10	100	22	56
	Arolla pine	0	.	0	.	0	.	0	0	0	.	0	.	0	0
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	13	58	0	.	0	.	0	.	0	.	8	71	21	45
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	16	72	0	.	0	.	0	.	0	.	0	.	16	72
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	6	100	0	.	0	.	0	.	0	.	0	.	6	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	39	40	32	35	18	51	8	71	4	100	26	50	127	20
100-103 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	12	58	8	71	4	100	39	63	19	50	82	34
	fir	8	71	0	.	0	.	0	.	0	.	4	100	12	58
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	4	100	0	.	4	100	8	71
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	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	8	71	0	.	0	.	0	.	0	.	0	.	8	71
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	16	50	16	50	8	71	8	71	39	63	35	36	122	25
104-107 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	12	58	5	100	4	100	4	100	12	58	5	100	42	32
	fir	0	.	4	100	4	100	0	.	0	.	0	.	8	71
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	4	100	4	100	4	100	12	58
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	12	58	9	71	8	71	8	71	16	50	9	71	62	26
108-111 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	4	100	8	71	0	.	9	71	0	.	21	45
	fir	4	100	0	.	0	.	0	.	4	100	0	.	8	71
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4	100	4	100	8	71	0	.	13	58	4	100	33	35
112-115 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	4	100	0	.	0	.	0	.	4	100
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	4	100	4	100	8	71
	Arolla pine	0	.	0	.	0	.	4	100	4	100	0	.	8	71
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	4	100	0	.	0	.	0	.	0	.	0	.	4	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	11	100	0	.	0	.	0	.	0	.	0	.	11	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	15	80	0	.	4	100	4	100	8	71	8	71	38	40
116-119 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	4	100	0	.	0	.	4	100	8	71
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	4	100	0	.	4	100
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	4	100	0	.	4	100	8	71	16	50
120-123 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	4	100	0	.	0	.	0	.	0	.	4	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	11	100	11	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	4	100	0	.	0	.	0	.	11	100	15	78
124-127 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	10	71	0	.	0	.	0	.	0	.	0	.	10	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	10	71	0	.	0	.	0	.	0	.	0	.	10	71
128-131 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	16	76	0	.	0	.	0	.	0	.	0	.	16	76
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	16	76	0	.	0	.	0	.	0	.	0	.	16	76
132-135 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	fir	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	4	100	0	.	0	.	0	.	4	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	4	100	0	.	0	.	12	58	16	50
136-139 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	8	100	0	.	0	.	0	.	0	.	8	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	8	100	0	.	0	.	0	.	0	.	8	100
140-143 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	4	100	4	100
144-147 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
148-151 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	4	100	4	100
152-155 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	4	100	4	100
156-159 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	4	100	4	100
160-163 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
164-167 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
168-171 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	13	75	13	75
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	13	75	13	75
172-175 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	11	100	11	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	11	100	11	100
176-179 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
180-183 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
184-187 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
188-191 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
192-195 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	11	100	11	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	11	100	11	100
196-199 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
=200 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	9	71	9	71
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	9	71	9	71
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	46201	4	42826	4	26433	6	19020	7	37330	5	12103	8	183914	2
	fir	27038	4	14122	6	7111	8	1890	18	971	19	1662	19	52794	3
	pine	3766	10	1322	32	970	26	4630	15	5277	13	402	43	16367	7
	larch	1227	19	569	28	547	29	10142	8	6613	10	8002	8	27100	5
	Arolla pine	0	.	122	80	119	72	2182	15	3235	14	62	56	5720	10
	other conifers	1993	16	255	50	431	28	122	47	830	27	49	68	3680	12
	beech	45910	3	14142	7	11378	7	2125	21	1839	17	13128	9	88523	3
	maple	12541	5	5948	9	4784	11	1376	16	799	27	1724	17	27171	4
	ash	10649	6	2911	12	3372	12	1173	22	850	27	3003	14	21958	4
	oak	5653	10	555	34	148	27	1242	24	161	49	2056	17	9815	8
	sweet chestnut	99	78	4	100	0	.	229	62	17	100	10587	10	10937	10
	other broadleaves	12016	6	5242	10	4350	13	5800	11	4947	15	16645	7	49001	4
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	167092	2	88018	3	59643	4	49933	5	62869	4	69424	3	496978	1

Table citation

Abegg, M.; Ahles, P.; Allgaier Leuch, B.; Cioldi, F.; Didion, M.; Düggelin, C.; Fischer, C.; Herold, A.; Meile, R.; Rohner, B.; Rösler, E.; Speich, S.; Temperli, C.; Traub, B.,
2023: Swiss national forest inventory - Result table No. 1350104. Birmensdorf, Swiss Federal Research Institute WSL

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