Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI4
number of stems
diameter at breast height (in 4 cm classes) · main tree species
regional demarcation: production region
unit: 1000 n
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
state 2009/17
		production region
		Jura		Plateau		Pre-Alps		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	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
12-15 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3918	10	5925	8	7343	7	16929	5	2555	12	36670	3
	fir	3603	8	2335	12	3701	8	1393	13	405	29	11437	5
	pine	122	48	107	60	105	56	2757	14	38	79	3129	13
	larch	32	74	220	74	127	52	3067	13	1443	14	4888	10
	Arolla pine	0	.	0	.	20	100	926	15	38	61	984	15
	other conifers	287	37	344	31	123	40	843	21	40	79	1637	15
	beech	4811	7	4316	7	3615	9	2636	12	3412	12	18791	4
	maple	1642	13	1624	12	1307	15	2020	12	607	23	7199	6
	ash	766	17	1551	12	828	16	1105	15	913	19	5163	7
	oak	486	41	317	29	32	58	735	25	410	25	1980	16
	sweet chestnut	0	.	20	71	0	.	55	84	2115	18	2190	18
	other broadleaves	2024	11	2344	11	1914	12	6919	8	5919	9	19121	4
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0
	total	17689	4	19103	4	19115	4	39385	3	17897	5	113189	2
16-19 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3251	11	3718	10	6070	7	12890	5	1694	12	27623	3
	fir	2438	8	1992	13	2576	9	1066	14	183	34	8254	5
	pine	112	51	99	67	174	47	2015	14	19	71	2420	12
	larch	10	100	77	44	99	52	2343	10	1049	15	3578	8
	Arolla pine	0	.	0	.	11	100	1001	15	0	.	1012	15
	other conifers	168	38	248	35	61	41	274	30	0	.	751	18
	beech	3406	8	3071	8	2527	10	2198	11	2821	12	14024	4
	maple	1254	13	1244	12	1191	14	1400	11	545	22	5632	6
	ash	657	19	1262	14	579	20	974	15	585	20	4056	8
	oak	311	26	419	29	0	0	332	30	407	29	1470	14
	sweet chestnut	0	.	19	71	0	.	53	73	2134	14	2207	13
	other broadleaves	995	15	1444	11	1161	16	4274	9	3963	9	11836	5
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0
	total	12603	4	13591	4	14448	4	28820	3	13400	5	82863	2
20-23 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2160	11	3379	9	4597	7	9852	5	1436	12	21425	3
	fir	1757	10	1209	13	1867	10	807	14	249	28	5888	6
	pine	117	35	92	42	126	50	1820	13	19	71	2175	12
	larch	9	100	86	42	39	78	1997	11	1002	15	3133	8
	Arolla pine	0	.	0	.	11	100	558	16	10	100	578	16
	other conifers	80	47	179	28	74	42	132	33	0	.	464	18
	beech	2634	8	2429	8	2236	9	1515	12	2056	12	10869	4
	maple	892	13	1030	15	947	14	913	14	181	27	3963	7
	ash	395	17	756	14	599	19	650	18	445	22	2844	8
	oak	291	28	240	25	57	54	339	23	310	25	1237	12
	sweet chestnut	0	.	10	100	0	.	19	100	2007	14	2036	14
	other broadleaves	634	17	1091	13	669	19	2107	11	2490	10	6990	6
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0
	total	8970	4	10499	4	11220	4	20708	3	10205	5	61602	2
24-27 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1837	11	2674	10	4283	7	8056	5	1061	13	17910	3
	fir	1361	11	858	13	1488	11	627	15	143	37	4477	6
	pine	200	34	95	35	94	79	1145	13	0	0	1535	12
	larch	20	100	85	40	0	.	1327	11	1038	14	2470	8
	Arolla pine	0	.	0	.	21	71	783	16	0	.	803	15
	other conifers	48	45	58	41	19	71	75	43	0	.	201	24
	beech	2553	8	2021	8	1701	10	1386	13	1458	13	9119	5
	maple	720	14	715	15	1003	14	700	15	104	37	3242	7
	ash	332	25	603	15	661	18	408	21	520	25	2523	9
	oak	357	29	358	19	26	71	112	33	283	24	1136	13
	sweet chestnut	0	.	0	.	0	.	21	71	1131	15	1152	14
	other broadleaves	400	18	665	14	367	23	996	13	1645	11	4072	7
	indeterminable	0	0	0	.	0	0	0	0	0	.	0	0
	total	7828	5	8133	5	9662	5	15634	3	7383	5	48640	2
28-31 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1562	10	2004	10	3818	7	7055	6	1061	13	15500	4
	fir	855	14	713	14	1131	12	584	16	98	35	3381	7
	pine	280	29	127	40	93	51	967	13	67	47	1535	11
	larch	29	58	104	35	11	100	1385	10	699	17	2227	8
	Arolla pine	0	.	0	.	42	80	710	15	0	.	751	15
	other conifers	59	47	87	37	0	.	20	71	0	.	166	27
	beech	2515	10	1547	9	1728	9	1147	11	1050	15	7987	5
	maple	543	17	620	16	707	14	703	20	113	35	2687	8
	ash	379	21	507	16	383	21	351	25	157	44	1777	10
	oak	445	23	258	22	27	71	78	39	206	28	1014	13
	sweet chestnut	0	.	19	100	0	.	20	100	1045	15	1084	15
	other broadleaves	346	32	355	20	192	25	538	17	969	13	2401	9
	indeterminable	0	.	0	0	0	.	0	0	0	.	0	0
	total	7013	5	6341	5	8133	4	13558	4	5465	6	40510	2
32-35 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1331	11	1816	10	3078	7	5537	5	842	16	12605	4
	fir	1097	11	706	13	1157	11	305	20	97	37	3362	6
	pine	245	26	212	23	83	47	681	16	96	65	1318	12
	larch	19	71	106	39	0	.	1260	12	565	16	1949	9
	Arolla pine	0	.	0	.	11	100	417	19	10	100	438	18
	other conifers	28	58	70	55	10	100	0	.	0	.	109	40
	beech	2185	9	1299	10	1376	12	535	15	604	17	5999	5
	maple	387	17	340	18	330	19	252	23	75	44	1384	9
	ash	276	23	555	17	329	24	294	26	183	32	1637	10
	oak	202	24	170	27	32	58	20	71	131	31	555	15
	sweet chestnut	0	.	0	.	0	.	33	76	576	19	609	18
	other broadleaves	214	25	284	21	110	32	297	21	722	15	1626	9
	indeterminable	0	0	0	0	0	.	0	0	0	0	0	0
	total	5986	5	5558	5	6517	5	9629	4	3901	6	31591	2
36-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1122	9	1411	8	2732	5	4635	4	673	12	10573	3
	fir	878	10	520	11	768	9	321	14	88	34	2575	5
	pine	284	20	217	17	76	36	545	13	58	50	1180	9
	larch	27	38	63	26	16	50	999	9	455	13	1561	7
	Arolla pine	0	.	0	.	12	75	298	16	0	.	310	15
	other conifers	34	53	37	41	0	.	4	100	0	.	75	32
	beech	1910	6	1182	7	1051	9	563	12	447	13	5153	4
	maple	336	12	252	15	265	16	286	17	31	38	1169	7
	ash	219	17	458	14	232	18	117	23	62	36	1088	8
	oak	147	22	184	20	20	50	60	30	122	25	532	11
	sweet chestnut	0	.	12	74	0	.	6	100	339	15	356	14
	other broadleaves	153	25	231	15	52	40	251	20	417	13	1104	8
	indeterminable	0	.	0	0	0	0	0	0	0	0	0	0
	total	5108	4	4566	4	5225	4	8085	3	2691	5	25675	2
40-43 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1152	8	1105	8	2504	6	4018	4	613	12	9392	3
	fir	779	9	514	11	800	9	331	16	81	27	2504	5
	pine	242	20	185	19	65	39	451	13	42	39	984	9
	larch	15	78	50	31	8	71	950	9	393	14	1417	7
	Arolla pine	0	.	0	.	9	100	194	17	0	.	202	17
	other conifers	19	66	33	49	0	.	0	.	0	.	52	39
	beech	1602	6	993	8	1016	9	505	13	387	14	4503	4
	maple	223	15	122	19	156	18	162	18	38	37	701	8
	ash	161	18	369	13	180	19	92	27	60	34	861	9
	oak	121	26	196	19	13	58	48	42	57	33	436	13
	sweet chestnut	0	.	4	100	0	.	11	58	302	17	317	16
	other broadleaves	149	27	130	18	49	32	108	27	227	16	665	10
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0
	total	4464	4	3699	4	4800	4	6870	3	2202	6	22035	2
44-47 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	971	8	908	9	2091	6	3215	5	513	13	7699	3
	fir	783	9	392	12	817	9	314	14	58	27	2364	5
	pine	172	18	159	18	32	38	283	15	27	62	674	9
	larch	15	61	35	36	12	74	852	9	295	15	1209	7
	Arolla pine	0	.	0	.	4	100	147	19	0	.	151	19
	other conifers	11	100	28	43	0	.	0	.	4	100	43	39
	beech	1214	7	899	8	737	9	367	14	213	18	3430	4
	maple	169	18	94	23	71	26	100	21	13	76	448	11
	ash	163	19	251	15	106	23	80	27	32	42	632	10
	oak	73	25	194	17	16	58	25	46	61	34	370	12
	sweet chestnut	0	.	0	.	0	.	0	.	202	17	202	17
	other broadleaves	55	29	90	28	31	46	57	34	169	18	402	12
	indeterminable	0	0	0	.	0	.	0	0	0	.	0	0
	total	3625	4	3051	4	3920	4	5441	3	1588	6	17624	2
48-51 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	795	9	798	9	1829	6	2549	5	387	12	6357	3
	fir	515	10	448	11	670	9	206	15	45	32	1884	5
	pine	122	24	115	21	58	48	155	19	11	58	462	12
	larch	12	58	34	40	12	58	757	10	241	14	1057	8
	Arolla pine	0	.	0	.	0	.	163	20	0	.	163	20
	other conifers	27	56	28	48	0	.	0	.	0	.	54	37
	beech	941	7	810	8	572	11	245	18	231	16	2799	4
	maple	61	28	68	25	94	23	97	32	4	100	324	14
	ash	79	24	271	15	84	24	53	28	22	62	509	10
	oak	77	29	135	23	0	.	34	39	21	51	268	16
	sweet chestnut	0	.	8	100	0	.	4	100	133	20	145	19
	other broadleaves	35	57	104	28	17	50	27	47	47	35	231	18
	indeterminable	0	.	0	0	0	0	0	0	0	.	0	0
	total	2663	4	2818	4	3337	4	4292	4	1144	7	14254	2
52-55 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	582	10	575	10	1509	7	1987	5	313	15	4965	4
	fir	467	11	438	13	628	9	211	16	68	31	1812	6
	pine	63	30	106	20	15	60	182	19	11	74	379	12
	larch	4	100	64	28	12	76	715	11	254	14	1049	9
	Arolla pine	0	.	0	.	0	.	74	24	0	.	74	24
	other conifers	4	100	24	47	0	.	0	.	0	.	28	43
	beech	597	10	621	9	415	12	206	16	117	21	1956	5
	maple	39	35	32	35	56	30	20	45	4	100	152	17
	ash	79	24	152	17	43	32	30	38	0	.	303	12
	oak	78	32	131	23	5	100	24	47	24	45	261	16
	sweet chestnut	0	.	4	100	0	.	4	100	102	25	109	23
	other broadleaves	33	52	33	43	13	58	66	30	19	51	165	20
	indeterminable	0	.	0	0	0	0	0	0	0	.	0	0
	total	1946	5	2180	5	2697	5	3520	4	912	8	11254	2
56-59 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	592	10	641	10	1250	7	1605	6	289	15	4377	4
	fir	378	12	349	12	453	11	183	17	36	40	1399	6
	pine	62	34	83	25	15	59	110	25	8	71	278	15
	larch	12	58	38	37	21	53	603	10	167	16	841	8
	Arolla pine	0	.	0	.	0	.	50	31	4	100	54	30
	other conifers	0	.	4	100	0	.	0	.	4	100	8	71
	beech	442	11	460	10	288	14	193	21	117	24	1500	6
	maple	35	33	34	35	33	35	8	71	0	.	111	19
	ash	34	35	121	23	37	40	11	58	16	60	220	16
	oak	21	54	64	25	5	100	12	58	7	100	109	21
	sweet chestnut	0	.	0	.	0	.	0	.	126	23	126	23
	other broadleaves	14	59	33	49	9	71	54	45	16	50	126	25
	indeterminable	0	.	0	.	0	.	0	0	0	.	0	0
	total	1590	6	1826	5	2112	5	2828	5	792	9	9148	2
60-63 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	337	12	340	13	815	9	939	7	136	20	2567	5
	fir	260	15	258	14	374	13	112	22	20	45	1025	7
	pine	12	58	36	33	8	71	58	27	4	100	118	19
	larch	4	100	18	51	4	100	306	13	105	22	438	11
	Arolla pine	0	.	0	.	0	.	20	53	0	.	20	53
	other conifers	0	.	12	58	0	.	0	.	0	.	12	58
	beech	203	16	309	13	165	18	55	32	53	30	786	8
	maple	11	72	24	47	13	78	27	46	4	100	80	27
	ash	21	45	69	24	8	71	16	60	4	100	119	19
	oak	18	52	95	23	4	100	4	100	4	100	126	20
	sweet chestnut	0	.	4	100	0	.	14	77	64	29	82	27
	other broadleaves	8	71	18	64	5	100	36	39	14	57	81	26
	indeterminable	0	.	0	.	0	0	0	0	0	.	0	0
	total	874	8	1184	6	1397	7	1589	5	410	11	5453	3
64-67 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	253	15	205	17	577	10	717	8	112	20	1865	5
	fir	196	18	220	15	315	14	91	23	11	57	834	8
	pine	28	42	35	36	10	72	32	39	0	.	106	21
	larch	0	.	23	46	10	72	283	16	78	23	394	13
	Arolla pine	0	.	0	.	4	100	53	28	0	.	57	27
	other conifers	0	.	16	50	0	.	0	.	0	.	16	50
	beech	115	20	218	14	129	19	90	27	36	36	587	9
	maple	0	.	12	58	0	.	4	100	0	.	16	50
	ash	12	58	27	54	17	50	0	.	6	100	61	31
	oak	23	52	42	34	5	100	5	100	8	71	82	25
	sweet chestnut	0	.	0	.	0	.	0	.	26	47	26	47
	other broadleaves	4	100	13	58	0	.	0	.	9	72	26	41
	indeterminable	0	.	0	0	0	.	0	.	0	.	0	0
	total	631	9	811	8	1067	7	1274	7	286	13	4070	4
68-71 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	192	17	161	16	437	12	649	11	122	22	1561	7
	fir	105	19	171	17	169	18	91	25	20	52	557	9
	pine	5	100	20	45	8	71	26	50	0	.	59	30
	larch	0	.	8	71	8	71	212	14	67	25	295	12
	Arolla pine	0	.	0	.	0	.	27	38	0	.	27	38
	other conifers	0	.	16	50	0	.	0	.	0	.	16	50
	beech	109	26	155	18	99	22	18	52	43	34	424	11
	maple	4	100	4	100	4	100	4	100	0	.	16	50
	ash	22	52	33	38	4	100	11	58	0	.	71	27
	oak	21	45	41	34	5	100	8	71	0	.	75	25
	sweet chestnut	0	.	0	.	0	.	0	.	54	31	54	31
	other broadleaves	23	46	21	45	5	100	7	71	6	100	62	27
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	482	11	630	9	740	9	1053	8	312	13	3217	4
72-75 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	61	27	131	19	304	13	451	12	97	23	1045	7
	fir	98	21	53	28	133	20	51	29	17	50	351	12
	pine	4	100	4	100	0	.	0	.	0	.	8	71
	larch	4	100	0	.	13	58	139	19	33	36	189	16
	Arolla pine	0	.	0	.	0	.	15	50	0	.	15	50
	other conifers	4	100	20	67	0	.	0	.	0	.	24	58
	beech	68	25	89	22	71	28	16	50	11	58	256	13
	maple	5	100	0	.	0	.	4	100	0	.	9	71
	ash	4	100	22	45	6	100	0	.	0	.	32	38
	oak	17	50	14	59	0	.	0	.	0	.	32	38
	sweet chestnut	0	.	0	.	0	.	5	100	42	34	47	32
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	265	13	334	12	528	10	681	9	200	15	2008	5
76-79 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	76	26	49	31	191	16	323	13	53	30	692	8
	fir	45	35	90	25	118	20	50	28	16	50	320	12
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	102	22	21	54	123	20
	Arolla pine	0	.	0	.	0	.	27	38	0	.	27	38
	other conifers	0	.	4	100	0	.	0	.	0	.	4	100
	beech	11	58	62	27	14	58	20	45	26	60	134	20
	maple	0	.	0	.	0	.	4	100	0	.	4	100
	ash	0	.	24	45	8	71	4	100	0	.	36	36
	oak	0	.	27	55	5	100	0	.	4	100	36	45
	sweet chestnut	0	.	0	.	0	.	0	.	32	42	32	42
	other broadleaves	0	.	4	100	0	.	4	100	0	.	8	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	133	20	259	14	336	12	534	10	153	19	1415	6
80-83 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	28	38	56	28	105	22	170	16	54	27	414	10
	fir	11	73	37	33	27	41	7	71	4	100	85	23
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	4	100	0	.	52	32	31	35	87	23
	Arolla pine	0	.	0	.	0	.	16	50	0	.	16	50
	other conifers	0	.	4	100	0	.	0	.	0	.	4	100
	beech	18	51	34	41	12	74	4	100	20	45	88	24
	maple	0	.	6	100	0	.	5	100	0	.	10	71
	ash	4	100	4	100	4	100	0	.	0	.	12	58
	oak	4	100	18	50	0	.	5	100	0	.	26	41
	sweet chestnut	0	.	0	.	0	.	0	.	15	78	15	78
	other broadleaves	6	100	4	100	0	.	0	.	8	71	19	51
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	71	25	167	17	148	18	258	13	133	19	777	8
84-87 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	12	74	29	43	53	29	121	22	33	36	248	14
	fir	20	45	28	38	59	29	20	45	0	.	128	19
	pine	0	.	4	100	0	.	4	100	0	.	8	71
	larch	0	.	0	.	0	.	39	32	26	41	66	25
	Arolla pine	0	.	0	.	0	.	12	58	0	.	12	58
	other conifers	4	100	4	100	4	100	0	.	0	.	12	58
	beech	13	58	32	39	9	71	8	71	4	100	66	26
	maple	0	.	0	.	4	100	0	.	0	.	4	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	12	58	14	58	0	.	0	.	26	41
	sweet chestnut	0	.	0	.	0	.	0	.	42	37	42	37
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	48	31	109	20	144	18	205	15	105	21	611	9
88-91 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	12	58	8	71	33	55	102	21	12	58	168	18
	fir	12	58	4	100	21	46	16	50	8	71	62	26
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	33	38	13	58	46	32
	Arolla pine	0	.	0	.	0	.	8	71	0	.	8	71
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	4	100	4	100	4	100	0	.	12	58
	maple	0	.	0	.	0	.	4	100	4	100	8	71
	ash	0	.	9	72	0	.	0	.	0	.	9	72
	oak	10	72	4	100	0	.	0	.	0	.	14	59
	sweet chestnut	0	.	0	.	0	.	4	100	12	58	17	50
	other broadleaves	4	100	4	100	0	.	0	.	0	.	8	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	39	34	33	35	59	36	171	16	49	29	351	12
92-95 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4	100	8	71	4	100	26	52	11	58	54	32
	fir	20	53	8	71	5	100	8	71	6	100	46	33
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	25	41	0	.	25	41
	Arolla pine	0	.	0	.	0	.	8	71	0	.	8	71
	other conifers	0	.	4	100	0	.	0	.	0	.	4	100
	beech	0	.	0	.	4	100	0	.	0	.	4	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	4	100	0	.	0	.	0	.	4	100
	oak	4	100	0	.	0	.	0	.	0	.	4	100
	sweet chestnut	0	.	0	.	0	.	0	.	8	71	8	71
	other broadleaves	0	.	6	100	0	.	4	100	0	.	10	73
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	28	43	30	38	12	58	72	27	25	41	167	17
96-99 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	22	45	19	45	4	100	45	30
	fir	4	100	0	.	8	71	0	.	0	.	12	58
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	12	58	10	100	22	56
	Arolla pine	0	.	0	.	0	.	0	0	0	.	0	0
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	4	100	9	71	0	.	0	.	8	71	21	45
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	6	100	9	100	0	.	0	.	0	.	16	72
	sweet chestnut	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	6	100	0	.	0	.	0	.	6	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	14	60	25	52	30	38	31	35	26	50	127	20
100-103 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	17	50	46	54	19	50	82	34
	fir	0	.	8	71	0	.	0	.	4	100	12	58
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	4	100	4	100	8	71
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	4	100	0	.	0	.	4	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	4	100	4	100	0	.	0	.	0	.	8	71
	sweet chestnut	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	4	100	4	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	4	100	12	58	21	45	50	50	35	36	122	25
104-107 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4	100	8	71	5	100	20	45	5	100	42	32
	fir	0	.	0	.	4	100	4	100	0	.	8	71
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	8	71	4	100	12	58
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	4	100	8	71	9	71	32	35	9	71	62	26
108-111 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	21	45	0	.	21	45
	fir	0	.	4	100	0	.	4	100	0	.	8	71
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	4	100	0	.	25	41	4	100	33	35
112-115 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	4	100	0	.	0	.	4	100
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	4	100	4	100	8	71
	Arolla pine	0	.	0	.	0	.	8	71	0	.	8	71
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	4	100	0	.	0	.	0	.	4	100
	sweet chestnut	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	11	100	0	.	0	.	0	.	11	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	15	80	4	100	12	58	8	71	38	40
116-119 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	4	100	4	100	8	71
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	4	100	0	.	4	100
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	8	71	8	71	16	50
120-123 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	4	100	0	.	0	.	4	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	11	100	11	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	4	100	0	.	11	100	15	78
124-127 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	10	71	0	.	0	.	0	.	0	.	10	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	10	71	0	.	0	.	0	.	0	.	10	71
128-131 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	5	100	11	100	0	.	0	.	0	.	16	76
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	5	100	11	100	0	.	0	.	0	.	16	76
132-135 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	4	100	4	100
	fir	0	.	0	.	0	.	0	.	4	100	4	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	4	100	4	100
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	4	100	0	.	4	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	4	100	12	58	16	50
136-139 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	8	100	0	.	8	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	8	100	0	.	8	100
140-143 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	4	100	4	100
144-147 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
148-151 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	4	100	4	100
152-155 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	4	100	4	100
156-159 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	4	100	4	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	4	100	4	100
160-163 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
164-167 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
168-171 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	13	75	13	75
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	13	75	13	75
172-175 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	11	100	11	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	11	100	11	100
176-179 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
180-183 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
184-187 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
188-191 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
192-195 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	11	100	11	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	11	100	11	100
196-199 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
=200 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	9	71	9	71
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	9	71	9	71
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	20252	6	25949	5	43672	4	81937	3	12103	8	183914	2
	fir	15683	5	11354	7	17294	5	6801	8	1662	19	52794	3
	pine	2069	15	1696	13	965	37	11234	9	402	43	16367	7
	larch	211	31	1015	22	392	35	17479	6	8002	8	27100	5
	Arolla pine	0	.	0	.	143	75	5515	10	62	56	5720	10
	other conifers	773	27	1220	21	292	27	1346	21	49	68	3680	12
	beech	25351	4	20559	4	17776	5	11709	8	13128	9	88523	3
	maple	6319	7	6221	8	6181	9	6725	8	1724	17	27171	4
	ash	3604	10	7046	7	4109	11	4197	11	3003	14	21958	4
	oak	2717	17	2936	11	265	22	1840	20	2056	17	9815	8
	sweet chestnut	0	.	99	78	0	.	250	57	10587	10	10937	10
	other broadleaves	5114	11	6902	8	4595	10	15745	7	16645	7	49001	4
	indeterminable	0	0	0	0	0	0	0	0	0	0	0	0
	total	82094	2	84998	2	95684	2	164778	2	69424	3	496978	1

Table citation

Abegg, M.; Ahles, P.; Allgaier Leuch, B.; Cioldi, F.; Didion, M.; Düggelin, C.; Fischer, C.; Herold, A.; Meile, R.; Rohner, B.; Rösler, E.; Speich, S.; Temperli, C.; Traub, B.,
2023: Swiss national forest inventory - Result table No. 1350107. Birmensdorf, Swiss Federal Research Institute WSL

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