Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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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 NFI4/NFI5
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	11319	8	3896	13	7228	10	3186	19	33748	5
	fir	3663	11	3154	12	3782	12	221	37	68	50	428	30	11315	7
	pine	56	58	78	61	304	45	635	38	1452	28	116	65	2642	19
	larch	17	100	411	43	175	52	971	19	766	21	1269	21	3610	11
	Arolla pine	0	.	0	.	0	.	380	39	776	40	32	70	1189	29
	other conifers	225	52	214	29	345	45	121	74	432	35	20	100	1357	20
	beech	4822	11	5912	11	4165	10	681	31	317	29	2908	15	18804	6
	maple	1924	17	1801	15	2609	12	773	42	249	41	706	33	8062	8
	ash	702	29	955	17	1096	20	408	41	175	54	949	27	4285	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	3057	13	3899	11	2287	17	1718	22	5970	12	18595	6
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	16687	7	21045	6	27823	5	10828	9	13180	8	18075	7	107637	3
16-19 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2229	13	4797	12	8593	8	2935	12	5791	10	2038	15	26383	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	135	58	962	19	550	23	1178	20	3209	12
	Arolla pine	0	.	0	.	0	.	266	36	575	27	35	71	876	21
	other conifers	211	37	159	33	318	37	17	100	196	37	17	100	918	19
	beech	3140	11	3241	9	3748	12	344	38	474	32	2476	15	13423	6
	maple	1192	16	1533	16	2100	13	262	30	86	45	454	33	5628	8
	ash	375	25	678	22	1099	16	242	35	218	37	526	30	3139	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	1696	14	2254	16	913	21	1043	23	4055	14	10808	7
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	11364	6	14854	6	21158	5	7279	9	9957	8	12963	6	77575	2
20-23 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1636	14	2762	13	7175	8	2146	15	4898	11	1526	17	20143	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	988	18	544	25	1275	18	3130	11
	Arolla pine	0	.	0	.	0	.	178	37	630	26	0	.	808	22
	other conifers	86	53	106	41	71	61	0	.	17	100	17	100	298	27
	beech	2342	12	2835	10	2768	11	185	45	232	44	1941	17	10302	6
	maple	1138	16	818	17	1925	13	137	63	71	61	296	37	4386	8
	ash	399	24	695	21	667	21	203	44	163	63	331	43	2457	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	1386	22	794	20	1054	27	2552	14	7587	8
	indeterminable	0	.	0	0	0	0	0	.	0	.	0	.	0	0
	total	8201	6	11074	6	16399	5	5853	9	8471	8	10354	7	60351	3
24-27 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1333	15	2359	13	6019	9	1659	15	3672	10	1250	16	16293	5
	fir	1521	13	1217	15	1250	14	72	50	34	71	107	40	4201	8
	pine	88	45	153	50	134	62	673	25	324	30	52	75	1422	16
	larch	0	.	84	66	59	59	653	25	541	30	1050	19	2388	13
	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	1811	12	2438	12	142	44	272	31	1704	18	8570	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	401	25	265	30	2011	15	4505	9
	indeterminable	0	0	0	.	0	0	0	.	0	0	0	.	0	0
	total	6512	6	7806	7	12821	5	4313	10	5890	8	8209	7	45551	3
28-31 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1360	15	2257	13	5375	8	1568	15	2773	11	1056	26	14390	5
	fir	1175	16	1121	16	1483	14	74	61	67	50	71	50	3990	8
	pine	176	49	119	43	255	44	456	29	327	28	52	58	1385	16
	larch	0	.	105	47	131	54	625	21	237	28	862	19	1959	12
	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	1901	12	161	65	342	35	1162	17	7385	6
	maple	492	19	593	19	1341	15	18	100	103	46	93	45	2642	10
	ash	190	33	431	22	561	29	36	71	127	66	218	38	1563	15
	oak	180	38	383	28	54	58	110	47	0	0	310	31	1038	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	1249	22	2718	12
	indeterminable	0	0	0	.	0	.	0	0	0	.	0	0	0	0
	total	5791	7	7375	6	11516	6	3421	11	4586	9	6247	9	38935	3
32-35 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1257	15	1504	13	4805	8	1320	16	2508	11	1021	19	12415	5
	fir	848	17	704	20	1283	15	91	45	72	50	143	43	3142	9
	pine	227	39	85	45	160	45	299	30	241	37	32	100	1043	17
	larch	0	.	34	71	17	100	709	22	534	22	790	21	2085	12
	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	1914	12	73	50	140	35	798	22	6099	7
	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	0	.	18	100	0	.	123	41	511	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	660	18	1386	12
	indeterminable	0	0	0	0	0	0	0	.	0	0	0	0	0	0
	total	5029	7	5218	7	9800	6	2781	12	3946	9	4561	8	31335	3
36-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	897	12	1308	11	3885	6	894	13	1804	9	852	14	9640	4
	fir	668	14	579	14	885	11	59	61	27	50	89	37	2307	7
	pine	281	29	171	26	149	35	230	24	230	26	14	71	1074	12
	larch	7	100	48	43	29	59	458	20	395	20	504	18	1442	11
	Arolla pine	0	.	0	.	0	.	104	36	166	25	15	100	284	20
	other conifers	20	58	42	47	7	100	0	.	0	.	0	.	69	35
	beech	1791	9	1193	10	1154	11	102	43	209	27	427	17	4877	5
	maple	233	20	310	17	413	16	7	100	73	51	22	74	1058	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	125	24	51	52	46	41	436	18	939	11
	indeterminable	0	.	0	0	0	0	0	0	0	.	0	0	0	0
	total	4200	6	4375	5	7028	5	1984	9	2995	7	2840	7	23422	2
40-43 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	875	12	1221	11	3661	7	697	15	1733	9	625	16	8813	4
	fir	631	14	736	13	831	11	44	62	77	40	81	44	2401	7
	pine	206	26	194	24	52	43	191	26	215	26	56	49	914	12
	larch	21	58	41	41	7	100	506	17	388	19	482	18	1445	10
	Arolla pine	0	.	0	.	10	100	71	45	156	27	0	.	237	23
	other conifers	0	.	48	52	0	.	0	.	0	.	8	100	56	47
	beech	1215	9	1080	10	1036	11	53	56	126	30	384	19	3893	5
	maple	278	16	142	25	342	15	7	100	33	64	29	50	832	10
	ash	132	24	392	19	198	25	7	100	7	100	23	57	760	13
	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	86	38	40	52	13	71	226	21	657	13
	indeterminable	0	0	0	.	0	0	0	.	0	0	0	0	0	0
	total	3514	6	4241	5	6265	5	1641	10	2748	7	2273	7	20682	2
44-47 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	768	11	1056	11	2943	7	587	15	1542	10	578	17	7473	4
	fir	647	13	540	14	673	12	44	53	26	60	51	43	1982	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	348	17	1239	11
	Arolla pine	0	.	0	.	0	.	35	53	99	28	0	.	134	25
	other conifers	14	71	14	71	0	.	0	.	0	.	0	.	27	50
	beech	1085	9	971	11	1027	13	64	65	135	35	219	21	3501	6
	maple	215	21	104	27	209	20	22	100	16	71	0	.	566	13
	ash	107	27	274	17	131	27	0	.	0	.	27	70	540	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	102	46	114	26	27	50	23	58	36	82	180	25	482	17
	indeterminable	0	.	0	.	0	0	0	0	0	0	0	.	0	0
	total	3179	6	3492	6	5131	5	1356	11	2349	8	1759	8	17266	3
48-51 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	698	13	746	12	2509	7	519	16	1111	11	494	22	6076	5
	fir	671	12	494	14	764	12	51	43	36	45	52	37	2068	7
	pine	72	37	135	27	65	54	24	58	130	34	0	.	425	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	870	12	700	12	0	.	80	31	216	22	2651	6
	maple	113	26	110	29	126	25	0	.	21	58	14	71	385	14
	ash	54	45	183	22	147	31	0	.	0	0	10	100	395	17
	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	21	58	79	33	53	35	0	.	0	0	154	26	306	17
	indeterminable	0	.	0	.	0	0	0	.	0	.	0	.	0	0
	total	2443	6	2821	6	4402	5	1009	12	1748	8	1292	10	13715	3
52-55 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	584	13	633	13	2169	7	409	15	856	12	302	19	4953	5
	fir	414	15	444	16	716	13	36	68	56	44	87	44	1752	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	491	15	7	100	58	39	146	26	2124	7
	maple	60	36	36	45	169	25	0	.	39	45	0	.	304	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	1871	7	2493	6	3728	5	974	12	1450	9	969	11	11484	3
56-59 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	363	18	401	16	1666	8	290	18	650	12	457	31	3827	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	252	21	273	19	250	18	860	10
	Arolla pine	0	.	0	.	0	.	7	100	50	38	0	.	57	35
	other conifers	0	.	48	43	0	.	0	.	0	.	0	.	48	43
	beech	352	20	586	12	475	15	0	.	33	45	83	32	1530	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	123	24	6	100	0	.	7	100	13	100	156	22
	sweet chestnut	0	.	0	.	8	100	0	.	0	.	171	35	180	33
	other broadleaves	14	71	80	37	12	70	8	100	11	100	24	58	150	25
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	1299	9	2034	7	2859	6	621	13	1178	9	1100	18	9090	4
60-63 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	390	16	301	15	1135	10	221	20	434	15	158	23	2639	6
	fir	239	19	357	16	365	16	0	.	37	47	8	100	1006	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	1244	8	1790	8	409	15	673	12	375	15	5377	4
64-67 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	280	20	306	16	815	10	92	33	288	18	103	28	1884	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	1410	8	295	22	519	14	332	15	4068	5
68-71 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	182	22	177	24	788	12	77	35	207	19	176	21	1607	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	239	18	130	26	0	.	14	71	48	41	487	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	758	10	1240	9	221	21	353	15	381	14	3355	5
72-75 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	104	28	176	22	467	13	47	46	140	22	89	35	1022	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	551	12	792	10	149	26	264	16	220	20	2247	6
76-79 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	78	32	96	28	369	18	49	42	71	35	55	42	717	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	507	15	134	25	144	23	149	24	1420	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	82	32	0	.	30	51	46	46	216	20
	fir	21	74	54	35	22	57	0	.	8	100	0	.	105	27
	pine	0	.	7	100	0	.	0	.	0	.	0	.	7	100
	larch	0	.	0	.	0	.	22	75	14	71	45	41	80	33
	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	45	47	152	21	111	27	43	53	52	38	143	24	546	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	.	20	58	0	.	0	.	25	58	68	34
	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	.	19	73	7	100	0	.	0	.	0	.	26	60
	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	43	46	96	28	37	45	39	45	59	42	302	17
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	8	100	0	.	0	.	0	.	0	.	0	.	8	100
	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	8	100	16	100	38	45	0	.	0	.	21	58	82	33
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	16143	8	25337	7	64167	5	17474	10	35944	7	14105	12	173170	3
	fir	16246	7	14493	8	18353	7	1069	29	910	22	1637	24	52707	4
	pine	1523	20	1590	16	1668	34	4538	22	4885	19	470	47	14674	10
	larch	88	37	1543	32	731	32	8094	11	5755	11	8945	11	25155	6
	Arolla pine	0	.	0	.	10	100	1791	22	3870	20	142	65	5813	15
	other conifers	637	31	1017	19	842	39	138	66	662	33	78	59	3376	15
	beech	22563	6	23538	6	22467	7	1819	32	2490	21	12725	12	85602	3
	maple	6836	10	6709	10	11625	8	1379	32	986	27	1800	26	29336	5
	ash	2615	14	5403	9	5489	12	1262	30	828	41	2433	22	18030	6
	oak	1892	31	3242	15	483	30	1109	33	42	85	2235	23	9004	11
	sweet chestnut	0	.	0	.	171	88	75	76	18	100	10476	13	10739	13
	other broadleaves	4051	13	8386	10	9389	10	4745	15	4453	20	17555	10	48580	5
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	total	72595	3	91259	3	135395	3	43493	7	60843	5	72602	4	476187	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. 1350121. Birmensdorf, Swiss Federal Research Institute WSL

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