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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NFI5
number of stems
diameter at breast height (in 4 cm classes) · main tree species
regional demarcation: biogeographical region
unit: 1000 n
evaluation area: accessible forest without shrub forest
grid: 1.4 km grid, subgrids 1-5
state 2018/26
		biogeographical region
		Jura		Plateau		Northern Alps		Western Central-Alps		Eastern Central-Alps		Southern Alps		Switzerland
diameter at breast height (in 4 cm classes)	main tree species	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
12-15 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3041	17	5077	12	11486	8	3896	13	7412	10	3186	19	34099	5
	fir	3663	11	3171	12	3782	12	221	37	68	50	428	30	11333	7
	pine	56	58	78	61	304	45	635	38	1452	28	116	65	2642	19
	larch	17	100	411	43	211	46	1284	21	916	24	1430	19	4269	11
	Arolla pine	0	.	0	.	0	.	401	37	776	40	32	70	1210	29
	other conifers	225	52	214	29	391	42	121	74	449	34	20	100	1420	19
	beech	4853	11	5912	11	4272	10	681	31	317	29	2981	14	19015	6
	maple	1924	17	1827	15	2626	12	791	41	249	41	723	32	8141	8
	ash	702	29	955	17	1152	20	470	38	175	54	949	27	4402	11
	oak	572	59	386	28	109	52	454	41	0	.	472	39	1994	22
	sweet chestnut	0	.	0	.	19	100	0	0	0	.	2018	25	2037	25
	other broadleaves	1664	14	3305	13	4349	12	2326	17	1827	21	6121	11	19592	6
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	16718	7	21337	6	28702	5	11280	9	13641	8	18477	7	110154	3
16-19 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2229	13	4797	12	8682	8	2952	12	5942	10	2038	15	26640	4
	fir	2866	12	2105	14	2569	13	199	33	108	41	161	36	8009	7
	pine	127	52	55	58	215	47	910	34	916	27	102	71	2323	18
	larch	0	.	385	52	153	52	1287	19	631	21	1304	18	3761	11
	Arolla pine	0	.	0	.	0	.	266	36	575	27	35	71	876	21
	other conifers	211	37	159	33	386	36	17	100	213	35	17	100	1004	18
	beech	3140	11	3241	9	3783	11	344	38	474	32	2560	15	13543	6
	maple	1192	16	1533	16	2119	13	262	30	86	45	454	33	5646	8
	ash	375	25	678	22	1155	16	242	35	218	37	526	30	3195	10
	oak	376	41	206	48	71	79	229	46	0	.	341	43	1222	22
	sweet chestnut	0	.	0	.	56	100	0	0	0	.	1581	20	1638	20
	other broadleaves	848	21	1721	14	2316	15	952	20	1043	23	4076	13	10956	7
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	11364	6	14879	6	21505	5	7660	9	10208	8	13195	6	78812	2
20-23 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1636	14	2762	13	7230	8	2170	15	4898	11	1526	17	20221	5
	fir	1920	13	1771	14	2122	12	94	45	157	44	178	42	6242	7
	pine	73	50	145	51	174	55	935	25	686	26	18	100	2032	16
	larch	0	.	253	57	70	61	1137	17	743	26	1291	18	3494	11
	Arolla pine	0	.	0	.	0	.	199	35	630	26	0	.	830	22
	other conifers	86	53	106	41	71	61	0	.	35	71	17	100	315	26
	beech	2342	12	2835	10	2786	11	185	45	232	44	1983	16	10363	6
	maple	1138	16	818	17	2026	12	157	56	71	61	296	37	4507	8
	ash	399	24	695	21	686	20	244	40	163	63	331	43	2516	12
	oak	122	75	372	28	39	71	194	52	0	0	348	33	1075	19
	sweet chestnut	0	.	0	.	0	.	0	.	18	100	1873	19	1891	19
	other broadleaves	484	26	1317	15	1535	20	834	20	1054	27	2648	14	7872	8
	indeterminable	0	.	0	0	0	0	0	.	0	.	0	.	0	0
	total	8201	6	11074	6	16740	5	6148	9	8687	8	10508	7	61358	3
24-27 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1333	15	2359	13	6056	9	1706	15	3737	10	1250	16	16441	5
	fir	1521	13	1235	15	1267	14	72	50	34	71	107	40	4235	8
	pine	88	45	153	50	134	62	673	25	341	29	52	75	1440	16
	larch	0	.	84	66	59	59	725	24	559	29	1106	18	2534	12
	Arolla pine	0	.	0	.	0	.	260	33	570	29	35	71	865	22
	other conifers	51	74	73	50	52	75	0	.	17	100	0	.	193	35
	beech	2203	11	1829	12	2456	12	142	44	272	31	1743	18	8645	6
	maple	647	18	763	22	1336	14	152	44	157	43	54	58	3109	9
	ash	196	33	327	27	617	19	247	44	38	71	207	40	1632	13
	oak	157	37	340	35	84	63	54	58	0	0	300	30	934	18
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	1439	18	1439	18
	other broadleaves	316	27	681	18	831	18	419	24	265	30	2011	15	4523	9
	indeterminable	0	0	0	.	0	0	0	.	0	0	0	.	0	0
	total	6512	6	7842	7	12892	5	4450	10	5992	8	8303	7	45990	3
28-31 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1360	15	2257	13	5430	8	1585	15	3011	12	1056	26	14700	5
	fir	1175	16	1138	16	1483	14	74	61	67	50	71	50	4008	8
	pine	176	49	119	43	255	44	456	29	327	28	52	58	1385	16
	larch	0	.	105	47	131	54	776	22	346	37	918	18	2275	13
	Arolla pine	0	.	0	.	0	.	158	40	411	28	18	100	587	23
	other conifers	0	.	51	58	35	71	0	.	0	.	0	.	86	45
	beech	1997	13	1821	11	2020	12	161	65	342	35	1162	17	7503	6
	maple	492	19	593	19	1360	15	18	100	103	46	111	41	2678	10
	ash	190	33	431	22	561	29	36	71	127	66	218	38	1563	15
	oak	180	38	383	28	83	51	110	47	0	0	310	31	1067	16
	sweet chestnut	0	.	0	.	19	100	18	100	0	.	1154	20	1192	19
	other broadleaves	220	29	493	23	360	26	196	40	200	39	1266	22	2734	12
	indeterminable	0	0	0	.	0	.	0	0	0	.	0	0	0	0
	total	5791	7	7392	6	11736	6	3589	11	4934	9	6337	9	39778	3
32-35 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1257	15	1504	13	4823	8	1320	16	2508	11	1021	19	12434	5
	fir	848	17	740	20	1283	15	91	45	72	50	143	43	3177	9
	pine	227	39	85	45	160	45	299	30	258	35	32	100	1060	17
	larch	0	.	34	71	17	100	836	23	551	21	790	21	2229	13
	Arolla pine	0	.	0	.	0	.	157	40	251	33	0	.	408	25
	other conifers	17	100	52	74	15	100	0	0	0	.	0	.	84	53
	beech	1755	12	1418	12	1964	12	73	50	140	35	816	21	6167	6
	maple	450	24	401	22	927	17	0	.	109	41	132	47	2019	11
	ash	159	40	514	22	419	25	59	58	56	58	49	73	1255	14
	oak	141	40	230	28	29	100	18	100	0	.	123	41	539	19
	sweet chestnut	0	.	0	.	38	100	37	100	0	.	814	24	888	22
	other broadleaves	176	35	275	26	222	29	17	100	35	71	677	17	1404	12
	indeterminable	0	0	0	0	0	0	0	.	0	0	0	0	0	0
	total	5029	7	5253	7	9897	6	2908	12	3981	9	4596	8	31665	3
36-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	914	12	1308	11	4001	6	912	13	1804	9	852	14	9790	4
	fir	668	14	579	14	933	12	59	61	27	50	89	37	2354	7
	pine	281	29	171	26	149	35	230	24	230	26	14	71	1074	12
	larch	7	100	48	43	29	59	509	20	416	19	533	18	1543	11
	Arolla pine	0	.	0	.	0	.	104	36	173	24	15	100	291	20
	other conifers	20	58	42	47	7	100	0	.	0	.	0	.	69	35
	beech	1791	9	1193	10	1205	11	102	43	209	27	427	17	4928	5
	maple	233	20	310	17	427	15	7	100	73	51	22	74	1071	10
	ash	136	25	383	16	372	23	52	62	30	50	46	40	1020	11
	oak	84	37	146	30	8	100	14	100	14	71	67	43	333	19
	sweet chestnut	0	.	0	.	0	.	12	100	0	.	367	19	380	18
	other broadleaves	84	32	196	23	136	24	69	46	46	41	436	18	969	11
	indeterminable	0	.	0	0	0	0	0	0	0	.	0	0	0	0
	total	4217	6	4375	5	7267	5	2071	9	3023	7	2869	7	23822	2
40-43 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	882	12	1242	11	3772	7	697	15	1733	9	634	16	8960	4
	fir	631	14	736	13	906	12	44	62	77	40	81	44	2476	7
	pine	206	26	194	24	52	43	191	26	223	26	56	49	921	12
	larch	21	58	41	41	7	100	528	17	402	18	482	18	1481	10
	Arolla pine	0	.	0	.	10	100	80	41	156	27	0	.	246	22
	other conifers	0	.	48	52	0	.	0	.	0	.	8	100	56	47
	beech	1215	9	1080	10	1086	11	53	56	126	30	384	19	3943	5
	maple	278	16	142	25	342	15	7	100	33	64	29	50	832	10
	ash	144	24	392	19	206	24	7	100	7	100	23	57	780	12
	oak	56	39	197	22	42	52	23	58	0	.	76	31	393	15
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	282	21	282	21
	other broadleaves	101	42	190	24	94	36	40	52	13	71	226	21	665	13
	indeterminable	0	0	0	.	0	0	0	.	0	0	0	0	0	0
	total	3533	6	4262	5	6517	5	1672	10	2770	7	2282	7	21035	2
44-47 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	783	11	1097	11	3027	7	587	15	1563	10	586	17	7643	4
	fir	647	13	540	14	680	12	44	53	26	60	51	43	1989	7
	pine	106	27	142	22	71	45	110	31	116	37	7	100	551	14
	larch	14	71	27	50	15	71	456	20	379	20	358	17	1248	11
	Arolla pine	0	.	0	.	0	.	45	47	99	28	0	.	144	24
	other conifers	14	71	14	71	0	.	0	.	0	.	0	.	27	50
	beech	1085	9	971	11	1091	12	64	65	135	35	244	20	3589	6
	maple	215	21	104	27	209	20	22	100	16	71	0	.	566	13
	ash	119	26	274	17	131	27	0	.	0	.	27	70	551	12
	oak	121	40	249	20	29	50	14	71	0	.	76	43	490	16
	sweet chestnut	0	.	0	.	7	100	0	.	0	.	272	26	280	25
	other broadleaves	113	43	114	26	27	50	23	58	36	82	180	25	494	16
	indeterminable	0	.	0	.	0	0	0	0	0	0	0	.	0	0
	total	3216	6	3534	6	5287	5	1365	11	2370	8	1802	8	17574	3
48-51 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	714	13	767	12	2580	7	519	16	1125	11	502	22	6207	4
	fir	671	12	494	14	770	12	51	43	36	45	52	37	2074	7
	pine	72	37	135	27	65	54	24	58	138	33	0	.	433	17
	larch	0	.	29	61	15	100	367	19	320	17	179	21	909	11
	Arolla pine	0	.	0	.	0	.	48	48	50	38	0	.	98	30
	other conifers	0	.	20	58	0	.	0	.	0	.	0	.	20	58
	beech	785	11	882	12	727	12	0	.	80	31	216	22	2690	6
	maple	113	26	110	29	126	25	0	.	21	58	14	71	385	14
	ash	54	45	183	22	155	30	0	.	0	0	10	100	402	16
	oak	30	60	156	23	16	71	0	.	0	.	53	46	255	19
	sweet chestnut	0	.	0	.	7	100	0	.	0	.	120	29	127	28
	other broadleaves	33	51	79	33	53	35	0	.	0	0	154	26	318	17
	indeterminable	0	.	0	.	0	0	0	.	0	.	0	.	0	0
	total	2471	6	2854	6	4514	5	1009	12	1769	8	1300	10	13918	3
52-55 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	600	13	642	13	2214	7	420	15	864	12	302	19	5042	5
	fir	414	15	444	16	730	13	36	68	56	44	87	44	1766	8
	pine	64	36	124	26	48	42	45	41	79	39	14	100	375	16
	larch	15	71	42	41	0	.	435	19	256	21	246	21	994	11
	Arolla pine	0	.	0	.	0	.	42	58	71	32	0	.	113	29
	other conifers	14	71	41	53	0	.	0	.	0	.	8	100	63	40
	beech	642	12	781	10	505	15	7	100	58	39	153	25	2146	6
	maple	60	36	36	45	177	24	0	.	39	45	0	.	311	17
	ash	44	47	154	23	71	32	0	.	7	100	23	71	299	17
	oak	28	61	164	25	0	.	0	.	14	100	42	45	248	20
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	87	38	87	38
	other broadleaves	7	100	74	38	63	40	0	.	14	100	14	100	172	25
	indeterminable	0	.	0	.	0	0	0	.	0	.	0	.	0	0
	total	1888	7	2502	6	3809	5	985	12	1457	9	976	11	11616	3
56-59 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	371	17	401	16	1695	8	290	18	650	12	457	31	3863	6
	fir	434	15	451	15	558	12	40	52	56	43	95	31	1635	7
	pine	27	50	81	33	24	59	17	71	83	33	0	.	233	19
	larch	0	.	35	45	50	47	259	21	273	19	250	18	867	10
	Arolla pine	0	.	0	.	0	.	14	71	50	38	0	.	64	33
	other conifers	0	.	48	43	0	.	0	.	0	.	0	.	48	43
	beech	352	20	610	12	475	15	0	.	33	45	83	32	1554	8
	maple	56	35	42	41	22	59	0	.	14	71	0	.	135	23
	ash	44	40	187	26	36	53	7	100	0	.	6	100	281	20
	oak	7	100	132	24	6	100	0	.	7	100	13	100	165	22
	sweet chestnut	0	.	0	.	8	100	0	.	0	.	171	35	180	33
	other broadleaves	14	71	80	37	21	58	8	100	11	100	24	58	158	24
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	1306	9	2067	7	2896	6	635	13	1178	9	1100	18	9182	4
60-63 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	390	16	310	15	1143	10	221	20	448	15	158	23	2669	6
	fir	239	19	357	16	380	16	0	.	37	47	8	100	1021	9
	pine	0	.	34	45	7	100	14	71	21	58	0	.	76	30
	larch	7	100	7	100	7	100	153	21	140	25	100	28	413	14
	Arolla pine	0	.	0	.	0	.	0	.	14	71	0	.	14	71
	other conifers	0	.	27	50	0	.	0	.	0	.	0	.	27	50
	beech	198	19	328	16	194	22	7	100	13	71	80	30	820	10
	maple	14	71	28	50	23	58	0	.	6	100	0	.	71	32
	ash	39	45	82	28	16	72	0	.	0	.	0	.	136	23
	oak	0	.	53	42	8	100	0	.	0	.	0	.	61	39
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	28	60	28	60
	other broadleaves	0	.	27	50	35	52	15	71	7	100	0	.	84	31
	indeterminable	0	.	0	.	0	0	0	0	0	.	0	.	0	0
	total	886	10	1253	8	1812	8	409	15	687	12	375	15	5422	4
64-67 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	280	20	306	16	829	10	92	33	288	18	103	28	1898	7
	fir	171	24	182	23	341	18	7	100	6	100	0	0	708	12
	pine	15	71	20	58	10	100	0	.	37	45	7	100	89	29
	larch	0	.	14	71	0	.	196	29	144	27	80	32	433	17
	Arolla pine	0	.	0	.	0	.	0	.	7	100	0	.	7	100
	other conifers	0	.	14	71	0	.	0	.	0	.	8	100	22	58
	beech	128	28	193	20	163	25	0	.	27	50	59	39	571	12
	maple	8	100	7	100	28	60	0	.	0	.	0	.	43	46
	ash	15	71	70	35	19	73	0	.	0	.	0	.	104	29
	oak	0	.	67	34	7	100	0	.	0	.	6	100	81	31
	sweet chestnut	0	.	0	.	7	100	0	.	0	.	52	38	60	35
	other broadleaves	7	100	16	71	18	74	0	.	11	100	15	71	67	36
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	624	13	889	10	1424	8	295	22	519	14	332	15	4082	5
68-71 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	182	22	177	24	788	12	77	35	207	19	191	20	1622	8
	fir	115	26	191	20	260	23	15	100	22	58	22	58	625	13
	pine	0	.	28	50	0	.	0	.	14	71	0	.	42	41
	larch	0	.	14	71	0	.	115	29	90	31	94	31	313	17
	Arolla pine	0	.	0	.	0	.	14	71	7	100	0	.	21	58
	other conifers	0	.	40	41	0	.	0	.	0	.	0	.	40	41
	beech	56	35	251	18	130	26	0	.	14	71	48	41	499	13
	maple	7	100	14	71	35	64	0	.	0	.	0	.	55	45
	ash	15	71	15	71	14	71	0	.	0	.	10	100	55	38
	oak	20	73	32	62	0	.	0	.	0	.	8	100	60	43
	sweet chestnut	0	.	0	.	0	0	0	.	0	.	23	57	23	57
	other broadleaves	7	100	7	100	12	70	0	.	0	.	0	.	26	50
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	402	14	770	10	1240	9	221	21	353	15	396	14	3382	5
72-75 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	104	28	188	22	474	13	47	46	140	22	97	33	1049	9
	fir	123	24	149	24	188	22	7	100	20	58	7	100	495	13
	pine	7	100	14	71	0	.	0	.	7	100	0	.	27	50
	larch	7	100	15	71	21	58	88	31	63	36	58	35	252	18
	Arolla pine	0	.	0	.	0	.	7	100	14	71	0	.	21	58
	other conifers	0	.	7	100	0	.	0	.	0	.	0	.	7	100
	beech	31	51	108	28	88	29	0	.	6	100	30	50	264	17
	maple	0	.	7	100	6	100	0	.	0	.	0	.	13	71
	ash	0	.	7	100	14	71	0	.	6	100	6	100	33	45
	oak	0	.	40	46	0	.	0	.	7	100	0	.	47	42
	sweet chestnut	0	.	0	.	8	100	0	.	0	.	28	60	37	51
	other broadleaves	0	.	29	50	0	.	0	.	0	.	0	.	29	50
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	272	17	563	12	799	10	149	26	264	16	227	19	2274	6
76-79 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	78	32	96	28	392	18	49	42	71	35	55	42	741	12
	fir	45	40	90	28	101	27	7	100	20	58	8	100	271	16
	pine	0	.	7	100	0	.	0	.	0	.	0	.	7	100
	larch	0	.	0	.	0	.	56	40	46	41	42	47	145	24
	Arolla pine	0	.	0	.	0	.	21	58	7	100	0	.	28	50
	other conifers	0	.	21	75	0	.	0	.	0	.	0	.	21	75
	beech	21	58	66	36	31	60	0	.	0	.	7	100	125	27
	maple	9	100	0	.	7	100	0	.	0	.	0	.	16	71
	ash	7	100	10	100	0	.	0	.	0	.	0	.	17	71
	oak	0	.	30	50	0	.	0	.	0	.	0	.	30	50
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	30	50	30	50
	other broadleaves	0	.	7	100	0	.	0	.	0	.	7	100	14	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	160	22	326	16	531	15	134	25	144	23	149	24	1444	8
80-83 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	7	100	65	36	160	21	29	50	110	31	38	53	409	14
	fir	22	58	95	28	109	28	7	100	6	100	22	57	263	17
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	46	46	21	58	37	45	103	28
	Arolla pine	0	.	0	.	0	.	0	.	0	.	7	100	7	100
	other conifers	0	.	7	100	0	.	0	.	0	.	0	.	7	100
	beech	0	.	30	51	22	58	0	.	12	70	15	71	79	30
	maple	0	.	0	.	0	.	0	.	8	100	0	.	8	100
	ash	0	.	23	58	10	100	0	.	0	.	0	.	33	51
	oak	0	.	16	71	10	100	0	.	0	.	0	.	26	58
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	7	100	7	100
	other broadleaves	0	.	7	100	6	100	0	.	0	.	0	.	13	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	29	50	243	18	317	16	82	33	157	24	126	25	955	9
84-87 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	24	58	34	45	98	30	0	.	30	51	46	46	232	19
	fir	29	61	54	35	22	57	0	.	8	100	0	.	113	26
	pine	0	.	7	100	0	.	0	.	0	.	0	.	7	100
	larch	0	.	0	.	0	.	22	75	14	71	51	38	86	31
	Arolla pine	0	.	0	.	0	.	21	75	0	.	0	.	21	75
	other conifers	0	.	21	58	0	.	0	.	0	.	0	.	21	58
	beech	0	.	15	71	7	100	0	.	0	.	22	58	44	41
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	14	71	0	.	0	.	0	.	0	.	14	71
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	30	50	30	50
	other broadleaves	0	.	8	100	0	.	0	.	0	.	0	.	8	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	53	42	152	21	127	25	43	53	52	38	150	23	576	12
88-91 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	16	100	33	53	88	31	7	100	42	41	14	71	201	21
	fir	14	71	45	41	15	71	0	.	7	100	0	.	81	30
	pine	0	.	0	.	0	.	0	.	7	100	0	.	7	100
	larch	0	.	0	.	0	.	14	71	28	61	28	50	70	35
	Arolla pine	0	.	0	.	0	.	7	100	7	100	0	.	15	71
	other conifers	0	.	14	71	0	.	0	.	0	.	0	.	14	71
	beech	0	.	13	71	7	100	0	0	0	.	0	.	21	58
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	7	100	0	.	0	.	0	.	0	.	7	100
	oak	0	.	21	57	0	.	0	.	0	.	0	.	21	57
	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	29	63	133	24	111	27	29	50	92	30	49	38	443	13
92-95 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	7	100	7	100	62	36	22	58	21	58	11	100	130	25
	fir	22	58	0	.	28	50	0	.	0	.	25	58	75	32
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	7	100	18	72	0	.	25	59
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	31	59	7	100	0	.	0	.	0	.	38	52
	maple	0	.	0	.	6	100	0	.	0	.	0	.	6	100
	ash	0	.	17	71	0	.	0	.	0	.	0	.	17	71
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	7	100	0	.	22	74	30	61
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	29	50	55	42	104	27	37	45	39	45	59	42	322	16
96-99 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	8	100	0	.	7	100	0	.	7	100	7	100	29	50
	fir	0	.	14	71	6	100	0	.	0	.	0	.	20	58
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	14	71	0	.	7	100	22	58
	Arolla pine	0	.	0	.	0	.	7	100	0	.	0	.	7	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	7	100	0	.	0	.	0	.	0	.	7	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	.	15	71	15	71
	other broadleaves	0	.	7	100	0	.	0	.	0	.	0	.	7	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	8	100	27	50	14	71	21	58	7	100	30	50	107	26
100-103 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	38	45	0	.	0	.	6	100	44	41
	fir	19	72	0	.	0	.	0	.	0	.	0	.	19	72
	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	.	16	100	0	.	0	.	0	.	0	.	16	100
	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	19	72	16	100	38	45	0	.	0	.	21	58	94	32
104-107 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	7	100	7	100	0	.	14	71	0	.	29	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	.	0	.	0	.
	other broadleaves	0	.	14	71	0	.	0	.	0	.	0	.	14	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	7	100	21	58	7	100	0	.	14	71	0	.	50	38
108-111 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	14	71	7	100	0	.	0	.	22	58
	fir	0	.	0	.	7	100	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	.	6	100	6	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	21	58	7	100	0	.	6	100	35	45
112-115 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	7	100	7	100	14	71	0	.	15	71	11	100	55	38
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	7	100	7	100	14	71
	Arolla pine	0	.	0	.	0	.	0	.	7	100	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	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	7	100	7	100	14	71	0	.	30	50	18	72	76	32
116-119 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	7	100	0	.	0	.	0	.	0	.	7	100
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	7	100	7	100
	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	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	0	.	7	100	0	.	7	100	0	.	15	71	28	50
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	.	7	100	0	.	0	.	0	.	0	.	7	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	7	100	0	.	0	.	0	.	0	.	7	100
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	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
132-135 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	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	.
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	.	7	100	0	.	0	.	0	.	0	.	7	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	7	100	0	.	0	.	0	.	0	.	7	100
140-143 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	7	100	7	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	.	7	100	7	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	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
156-159 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
160-163 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	14	71	14	71
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	14	71	14	71
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	.	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	.	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	.	7	100	7	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	7	100	7	100
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	16222	8	25450	7	65111	5	17607	10	36640	7	14152	12	175182	3
	fir	16265	7	14581	8	18542	7	1069	29	910	22	1637	24	53003	4
	pine	1523	20	1590	16	1668	34	4538	22	4935	18	470	47	14724	10
	larch	88	37	1543	32	786	31	9310	12	6365	12	9406	11	27496	6
	Arolla pine	0	.	0	.	10	100	1860	22	3877	20	142	65	5889	15
	other conifers	637	31	1017	19	957	36	138	66	714	31	78	59	3543	14
	beech	22594	6	23616	6	23021	7	1819	32	2490	21	13012	12	86553	3
	maple	6836	10	6735	10	11800	8	1418	31	986	27	1836	26	29611	5
	ash	2638	14	5403	9	5634	12	1365	29	828	41	2433	22	18301	6
	oak	1892	31	3251	15	541	29	1109	33	42	85	2235	23	9071	11
	sweet chestnut	0	.	0	.	171	88	75	76	18	100	10476	13	10739	13
	other broadleaves	4074	13	8660	9	10080	10	4899	15	4562	19	17857	10	50132	5
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	72770	3	91846	3	138321	3	45207	7	62366	5	73733	4	484244	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. 1350127. Birmensdorf, Swiss Federal Research Institute WSL

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