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 (“±”).

top

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).

top

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).

top

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.

top

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.

top

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

top

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.

top

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.

top

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.

top

NFI2
number of stems
diameter at breast height (in 4 cm classes) · main tree species
regional demarcation: protection forest region
unit: 1000 n
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
state 1993/95
		protection forest region
		Jura + Plateau		Northwestern Alps		Northeastern Alps		Southwestern Alps		Southeastern Alps		Southern Alps		Switzerland
diameter at breast height (in 4 cm classes)	main tree species	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
12-15 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	14751	9	8395	9	4862	15	3655	15	5421	11	1329	18	38414	5
	fir	5480	9	2920	12	1534	16	307	39	163	40	235	35	10638	6
	pine	503	28	165	76	17	100	1484	29	1114	28	65	100	3348	17
	larch	137	56	18	100	147	62	1431	21	532	36	734	27	2999	14
	Arolla pine	0	.	0	.	0	.	216	37	369	34	16	100	601	25
	other conifers	553	27	53	58	140	47	156	69	142	56	0	.	1044	21
	beech	10161	6	3870	15	2601	15	584	36	287	40	3116	16	20619	5
	maple	2257	12	1129	22	571	21	384	31	193	53	274	37	4807	9
	ash	1764	17	462	23	745	30	296	39	199	69	571	32	4035	12
	oak	1670	23	109	41	0	.	191	41	0	.	885	35	2855	18
	sweet chestnut	17	100	0	.	0	.	0	.	0	.	3815	17	3831	17
	other broadleaves	3894	11	2026	15	1956	18	1985	18	1679	24	5385	15	16924	7
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	41187	4	19146	7	12574	9	10689	9	10097	9	16424	8	110116	3
16-19 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	9609	9	6710	10	4013	13	2781	14	4000	11	990	18	28103	5
	fir	3999	10	2273	13	1017	19	193	37	106	41	320	43	7908	7
	pine	663	32	90	65	36	100	1399	24	853	27	16	100	3057	15
	larch	141	50	36	71	79	60	811	19	299	34	770	25	2136	13
	Arolla pine	0	.	0	.	0	.	229	33	404	34	0	.	633	25
	other conifers	223	41	0	.	54	58	104	100	35	71	0	.	416	35
	beech	7907	7	2552	13	1882	15	527	37	358	29	2717	16	15942	5
	maple	1767	13	1073	18	785	23	215	43	96	44	55	58	3992	9
	ash	1497	15	787	27	692	22	176	43	146	73	429	30	3727	11
	oak	1213	24	135	55	39	71	267	36	15	100	433	36	2102	17
	sweet chestnut	0	.	0	.	0	.	19	100	0	.	2682	18	2700	17
	other broadleaves	2181	13	1142	20	685	28	1006	21	906	29	3301	12	9222	7
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	29197	4	14798	7	9283	9	7727	9	7220	9	11713	7	79939	3
20-23 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	6239	10	5711	9	3038	14	2210	14	3698	11	1145	18	22041	5
	fir	2970	11	1542	15	677	19	167	43	71	62	124	51	5551	8
	pine	445	27	156	89	127	66	973	27	693	28	0	.	2394	16
	larch	123	43	18	100	36	71	841	21	336	26	625	22	1979	12
	Arolla pine	0	.	0	.	0	.	261	32	283	25	0	.	544	20
	other conifers	120	43	17	100	0	.	17	100	17	100	0	.	172	35
	beech	6770	7	1934	14	1404	17	319	40	490	34	1695	19	12612	5
	maple	1150	15	782	19	657	23	71	62	18	100	57	58	2734	10
	ash	1271	17	456	28	706	27	76	61	110	71	168	37	2787	12
	oak	1101	25	93	51	0	.	89	66	15	100	197	51	1495	20
	sweet chestnut	0	.	0	.	0	.	19	100	0	.	1911	17	1930	17
	other broadleaves	1448	14	512	25	609	30	360	32	273	30	1956	13	5160	8
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	21636	4	11222	7	7255	9	5402	10	6004	9	7879	7	59397	3
24-27 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	5075	9	5039	9	2904	16	1832	15	2925	12	1005	19	18780	5
	fir	2532	11	1128	16	446	23	90	65	37	71	35	70	4268	8
	pine	415	29	87	72	100	69	537	26	306	31	34	71	1480	15
	larch	155	43	37	71	36	71	943	23	332	28	450	24	1953	14
	Arolla pine	0	.	0	.	0	.	178	42	281	30	0	.	459	25
	other conifers	103	47	0	.	15	100	0	.	0	.	0	.	119	43
	beech	5318	7	1779	17	1382	16	265	39	196	38	1010	20	9950	6
	maple	1538	12	563	22	515	24	18	100	52	58	113	40	2800	9
	ash	1346	13	432	34	495	30	55	58	108	63	55	74	2492	12
	oak	859	19	36	71	18	100	35	100	0	.	271	36	1220	16
	sweet chestnut	0	.	0	.	0	.	55	74	15	100	1385	20	1456	19
	other broadleaves	748	17	207	31	391	26	152	40	222	46	968	20	2688	11
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	18089	4	9309	7	6303	10	4161	11	4476	9	5326	8	47664	3
28-31 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3968	9	3778	10	2434	12	1548	16	2446	12	822	20	14996	5
	fir	2176	11	1166	17	410	22	67	76	112	47	95	66	4025	8
	pine	362	26	79	50	53	74	405	28	434	28	85	60	1419	14
	larch	85	53	0	.	18	100	516	25	320	28	507	26	1445	14
	Arolla pine	0	.	0	.	0	.	70	61	250	38	0	.	320	33
	other conifers	153	58	0	.	0	.	0	.	0	.	0	.	153	58
	beech	5201	7	1317	20	1088	17	126	52	142	40	678	20	8553	6
	maple	805	16	453	22	560	24	60	58	18	100	0	.	1896	11
	ash	1079	17	264	32	442	27	69	50	21	100	37	71	1913	12
	oak	634	18	21	100	76	60	18	100	0	.	138	47	887	16
	sweet chestnut	0	.	0	.	0	.	19	100	0	.	554	25	572	25
	other broadleaves	702	20	152	37	188	38	91	51	60	76	590	22	1781	12
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	15163	4	7230	8	5268	8	2989	11	3803	10	3506	9	37959	3
32-35 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4238	9	3218	10	2264	14	1146	18	2529	12	794	22	14188	5
	fir	2308	12	1029	17	453	23	71	81	18	100	55	58	3933	9
	pine	631	21	59	76	83	52	302	30	359	26	0	.	1434	14
	larch	138	43	37	100	18	100	531	22	348	26	319	35	1390	14
	Arolla pine	0	.	0	.	0	.	121	38	195	35	0	.	316	26
	other conifers	51	58	0	.	0	.	0	.	0	.	0	.	51	58
	beech	4009	8	1133	16	1036	17	85	54	96	53	404	27	6764	6
	maple	527	19	278	30	279	27	15	100	20	100	18	100	1136	13
	ash	989	17	113	40	155	40	18	100	18	100	0	.	1294	14
	oak	504	21	96	100	0	.	0	.	0	.	64	58	665	22
	sweet chestnut	0	.	0	.	0	.	42	70	0	.	364	26	405	24
	other broadleaves	515	21	72	50	118	42	105	47	52	72	441	27	1303	14
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	13909	4	6035	8	4405	9	2437	12	3635	10	2459	12	32880	3
36-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3796	7	3334	7	1627	11	932	13	1651	11	688	15	12028	4
	fir	1823	9	832	12	413	17	59	56	25	79	73	39	3225	6
	pine	760	15	38	46	13	71	227	24	260	25	48	66	1345	11
	larch	84	39	7	100	7	100	449	21	361	19	302	22	1210	11
	Arolla pine	0	.	15	71	0	.	69	40	162	31	0	.	246	23
	other conifers	7	100	0	.	0	.	0	.	0	.	8	100	15	71
	beech	3169	6	655	14	771	15	42	63	98	34	293	21	5027	5
	maple	382	15	135	26	274	20	28	81	25	58	7	100	851	11
	ash	688	15	86	33	117	29	14	71	15	72	19	72	938	12
	oak	360	17	28	81	7	100	19	100	12	100	59	71	486	17
	sweet chestnut	0	.	0	.	0	.	0	.	6	100	158	27	164	26
	other broadleaves	346	19	63	51	41	46	33	60	49	42	154	25	686	13
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	11413	3	5193	6	3272	8	1872	10	2663	8	1809	9	26222	2
40-43 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3513	6	2495	8	1336	11	743	14	1619	10	538	17	10244	4
	fir	1660	8	696	13	389	21	88	50	35	45	52	42	2921	6
	pine	682	15	75	51	41	60	129	36	207	28	35	67	1168	12
	larch	63	41	28	63	0	.	470	20	395	18	235	23	1192	11
	Arolla pine	0	.	0	.	0	.	49	47	113	29	0	.	162	25
	other conifers	47	62	0	.	0	.	0	.	0	.	0	.	47	62
	beech	2490	7	683	15	512	19	21	58	103	47	222	20	4030	6
	maple	238	19	95	31	116	26	6	100	6	100	0	.	462	13
	ash	550	15	80	34	102	34	7	100	0	.	14	70	754	13
	oak	314	17	14	100	7	100	0	.	13	71	46	56	394	16
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	227	31	227	31
	other broadleaves	232	20	54	62	19	58	0	.	7	100	107	26	419	16
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	9789	3	4220	6	2523	9	1514	11	2498	8	1476	9	22021	2
44-47 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2898	7	2344	9	1400	11	606	13	1245	11	397	17	8890	4
	fir	1266	10	659	15	377	19	55	52	48	47	66	33	2471	7
	pine	458	16	81	59	16	71	58	35	144	27	0	0	757	13
	larch	29	50	28	50	6	100	337	18	314	19	225	20	939	10
	Arolla pine	0	.	0	.	0	.	112	47	63	33	0	.	175	32
	other conifers	14	71	0	.	0	.	0	.	0	.	0	.	14	71
	beech	2166	7	442	19	445	19	6	100	88	33	166	29	3314	6
	maple	122	24	60	36	110	35	0	.	0	.	8	100	300	18
	ash	320	16	37	52	53	35	0	.	6	100	11	100	428	14
	oak	244	24	0	.	0	.	0	.	7	100	37	66	288	22
	sweet chestnut	0	.	0	.	0	.	7	100	0	.	132	32	139	30
	other broadleaves	78	52	32	52	60	52	23	75	0	.	36	45	229	26
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	7595	4	3684	7	2468	9	1204	11	1915	8	1078	10	17943	3
48-51 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2436	7	1756	9	1022	12	346	18	912	12	404	19	6876	4
	fir	972	11	541	14	227	21	44	58	41	46	104	34	1930	7
	pine	267	18	37	51	8	100	47	54	116	30	7	100	483	14
	larch	76	35	14	100	6	100	373	19	261	19	161	23	891	11
	Arolla pine	0	.	0	.	0	.	7	100	64	40	0	.	71	37
	other conifers	62	40	0	.	0	.	0	.	0	.	0	.	62	40
	beech	1269	9	296	18	275	19	36	62	28	62	71	31	1974	7
	maple	78	33	38	45	48	47	0	.	14	71	0	.	178	22
	ash	226	24	7	100	41	41	0	.	0	.	0	.	274	21
	oak	190	25	0	.	0	.	0	.	20	76	7	100	217	24
	sweet chestnut	0	.	0	.	0	.	0	.	6	100	76	38	83	36
	other broadleaves	56	50	48	49	25	58	7	100	7	100	8	100	151	27
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	5632	4	2737	7	1652	9	859	12	1470	9	838	12	13189	3
52-55 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1840	8	1290	10	710	12	341	19	658	13	264	19	5103	4
	fir	713	11	465	15	213	20	39	52	32	52	15	71	1476	8
	pine	183	23	19	73	8	100	45	47	58	40	14	71	327	17
	larch	34	53	36	53	22	75	224	22	232	21	95	29	642	12
	Arolla pine	0	.	0	0	0	.	12	100	21	58	0	.	33	51
	other conifers	27	61	0	.	0	.	0	.	0	.	0	.	27	61
	beech	885	10	285	22	240	24	7	100	31	66	77	34	1525	8
	maple	56	39	15	72	15	71	0	.	7	100	0	.	94	30
	ash	120	26	15	71	19	73	0	.	0	.	0	.	154	24
	oak	98	30	0	.	6	100	0	.	0	.	11	100	115	28
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	76	36	76	36
	other broadleaves	29	61	26	75	14	71	7	100	0	.	0	.	76	38
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	3984	5	2151	8	1248	10	676	14	1039	10	552	12	9649	3
56-59 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1289	9	850	11	615	13	219	21	520	13	227	20	3719	5
	fir	544	14	344	18	116	31	22	74	20	73	8	100	1054	10
	pine	127	26	23	71	0	.	14	71	72	34	0	.	235	19
	larch	21	58	35	60	26	61	215	28	186	22	144	26	626	14
	Arolla pine	0	.	0	.	0	.	0	.	56	39	0	.	56	39
	other conifers	29	78	0	.	0	.	0	.	0	.	0	.	29	78
	beech	603	12	138	26	119	28	0	.	20	58	81	35	961	10
	maple	48	41	6	100	0	.	0	.	6	100	0	.	61	36
	ash	75	42	15	71	6	100	0	.	0	.	11	100	107	33
	oak	160	23	0	.	0	.	0	.	0	.	0	.	160	23
	sweet chestnut	0	.	0	.	0	.	7	100	0	.	38	44	45	41
	other broadleaves	24	58	21	76	15	100	7	100	0	.	0	.	67	40
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	2920	6	1431	9	896	12	485	17	879	10	508	13	7120	4
60-63 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	715	11	511	14	358	19	130	25	359	17	143	27	2216	7
	fir	246	18	164	23	99	29	7	100	24	58	14	70	555	12
	pine	35	53	0	.	0	.	0	.	22	58	0	.	57	39
	larch	7	100	16	71	6	100	140	26	58	35	64	32	290	17
	Arolla pine	0	.	0	.	0	.	10	100	22	58	0	.	32	51
	other conifers	20	75	0	.	0	.	0	.	0	.	0	.	20	75
	beech	286	17	112	31	58	52	0	.	7	100	55	38	520	13
	maple	14	71	7	100	18	74	0	.	0	.	0	.	38	46
	ash	37	45	0	.	12	100	0	.	6	100	0	.	55	39
	oak	41	41	0	.	0	.	0	.	0	.	0	.	41	41
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	45	45	45	45
	other broadleaves	30	50	8	100	0	.	0	.	0	.	8	100	46	41
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	1430	8	819	11	551	15	288	18	498	14	329	16	3916	5
64-67 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	438	13	425	15	293	18	121	29	148	26	124	27	1549	7
	fir	175	21	140	26	69	34	7	100	12	70	23	57	426	14
	pine	34	45	11	100	7	100	0	.	14	71	0	.	66	34
	larch	7	100	0	.	7	100	48	38	47	41	21	58	129	24
	Arolla pine	0	.	0	.	0	.	0	.	15	71	0	.	15	71
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	122	24	59	40	39	52	0	.	0	.	7	100	227	19
	maple	8	100	0	.	0	.	0	.	0	.	0	.	8	100
	ash	47	41	0	.	7	100	0	.	6	100	0	.	60	36
	oak	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	30	50	30	50
	other broadleaves	8	100	6	100	0	.	0	.	0	.	9	100	23	58
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	844	10	641	12	422	16	176	24	242	19	214	19	2540	6
68-71 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	301	17	242	18	238	20	51	46	112	25	72	42	1017	9
	fir	94	28	112	27	21	58	6	100	0	.	7	100	239	18
	pine	0	.	0	.	0	.	0	.	7	100	0	.	7	100
	larch	7	100	0	.	17	72	104	30	57	35	43	41	227	19
	Arolla pine	0	.	0	.	0	.	7	100	14	71	0	.	21	58
	other conifers	8	100	0	.	0	.	0	.	0	.	0	.	8	100
	beech	196	21	0	.	0	.	0	.	18	74	21	57	236	19
	maple	0	.	6	100	0	.	0	.	0	.	0	.	6	100
	ash	14	100	7	100	0	.	0	.	0	.	0	.	21	74
	oak	44	41	0	.	12	100	0	.	0	.	0	.	56	39
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	38	44	38	44
	other broadleaves	15	71	0	.	0	.	0	.	0	.	0	.	15	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	678	11	368	14	288	18	169	24	209	19	181	22	1893	7
72-75 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	62	33	78	30	159	23	20	58	104	31	60	39	483	13
	fir	111	27	67	37	13	71	0	.	14	71	0	.	205	20
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	14	71	7	100	0	.	55	40	43	47	14	70	133	25
	Arolla pine	0	.	0	.	0	.	28	50	7	100	0	.	35	44
	other conifers	0	.	7	100	0	.	0	.	0	.	0	.	7	100
	beech	90	32	23	73	0	.	0	.	0	.	15	71	128	27
	maple	0	.	0	.	10	100	0	.	0	.	0	.	10	100
	ash	7	100	0	.	7	100	0	.	0	.	0	.	14	71
	oak	15	71	0	.	0	.	0	.	0	.	0	.	15	71
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	12	100	12	100
	other broadleaves	0	.	0	.	0	.	0	.	0	.	7	100	7	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	299	16	182	21	189	21	104	29	168	24	108	28	1051	9
76-79 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	70	34	59	36	78	33	38	45	69	32	50	42	364	15
	fir	37	45	26	57	12	71	0	.	7	100	8	100	90	29
	pine	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	larch	0	.	0	.	0	.	58	39	28	50	22	58	107	27
	Arolla pine	0	.	0	.	0	.	0	.	7	100	0	.	7	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	53	38	16	71	10	100	0	.	0	.	7	100	87	30
	maple	0	.	0	.	6	100	0	.	0	.	0	.	6	100
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	17	72	0	.	8	100	0	.	0	.	0	.	25	59
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	24	57	24	57
	other broadleaves	8	100	0	.	0	.	0	.	0	.	0	.	8	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	192	20	101	28	114	27	96	30	111	25	111	28	726	10
80-83 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	48	38	14	71	39	70	21	58	20	58	18	72	160	25
	fir	44	41	36	45	7	100	0	.	0	.	0	.	88	29
	pine	0	.	0	.	0	.	0	.	7	100	0	.	7	100
	larch	0	.	0	.	0	.	22	58	14	71	7	100	43	41
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	14	71	8	100	7	100	7	100	6	100	0	.	44	41
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	10	100	0	.	0	.	0	.	0	.	0	.	10	100
	oak	20	58	0	.	0	.	0	.	0	.	0	.	20	58
	sweet chestnut	0	.	0	.	0	.	8	100	0	.	61	56	69	51
	other broadleaves	16	71	0	.	0	.	0	.	0	.	0	.	16	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	154	22	59	36	53	54	58	35	47	38	87	43	458	15
84-87 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	22	58	23	58	22	58	0	0	14	71	0	0	82	30
	fir	7	100	32	50	0	.	0	.	0	.	7	100	47	41
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	7	100	0	.	0	.	7	100
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	21	58	0	.	7	100	0	.	0	.	0	.	29	50
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	oak	8	100	0	.	0	.	0	.	0	.	0	.	8	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	20	72	20	72
	other broadleaves	8	100	0	.	0	.	0	.	0	.	0	.	8	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	73	32	56	38	29	50	7	100	14	71	27	59	206	19
88-91 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	23	58	21	58	15	71	7	100	13	71	0	.	79	30
	fir	0	.	7	100	9	100	0	.	0	.	10	100	26	58
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	7	100	7	100	0	.	14	71
	Arolla pine	0	.	0	.	0	.	7	100	0	.	0	.	7	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	8	100	0	.	0	.	0	.	0	.	0	.	8	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	18	71	18	71
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	37	45	28	50	23	58	22	58	20	58	28	58	159	22
92-95 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	7	100	0	.	7	100	0	0	0	.	11	100	25	59
	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	15	71	0	.	0	.	0	.	0	.	0	.	15	71
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	15	71	15	71
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	36	45	0	.	7	100	0	0	0	.	26	59	69	34
96-99 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	15	71	0	.	23	58	7	100	7	100	0	.	52	38
	fir	0	.	7	100	0	.	0	.	0	.	0	.	7	100
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	14	71	0	.	7	100	21	58
	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	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	15	71	7	100	23	58	29	50	7	100	7	100	88	29
100-103 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	14	71	0	.	17	72	0	.	31	51
	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	.	14	71	0	.	17	72	8	100	39	45
104-107 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	13	71	0	.	0	.	0	.	0	.	13	71
	fir	0	.	0	.	0	.	0	.	0	.	10	100	10	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	.	17	72	17	72
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	13	71	0	.	0	.	0	.	28	58	41	45
108-111 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	.	7	100	7	100
	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	0	.	0	.	0	.	0	.	7	100	7	100	14	71
112-115 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	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	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	7	100	0	.	0	.	7	100
116-119 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	7	100	0	.	7	100
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	7	100	0	.	7	100
120-123 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
124-127 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	8	100	8	100
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	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	.	15	71	15	71
128-131 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	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	.	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
136-139 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
140-143 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	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
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	.	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	.
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	.	15	71	15	71
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	15	71	15	71
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	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
164-167 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
168-171 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
172-175 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
176-179 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
180-183 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
184-187 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
188-191 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
192-195 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
196-199 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	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
=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	.	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	.
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	61351	5	46309	6	27471	9	16756	11	28487	7	9090	11	189464	3
	fir	27163	6	14188	8	6502	11	1223	28	763	25	1261	27	51100	4
	pine	5572	11	920	49	511	45	5618	20	4665	18	305	55	17590	9
	larch	1119	20	316	31	431	42	7596	13	4175	13	4753	14	18391	7
	Arolla pine	0	.	15	71	0	.	1390	24	2335	20	16	100	3755	15
	other conifers	1415	22	78	47	209	40	277	82	195	55	8	100	2182	19
	beech	50753	4	15302	10	11877	10	2026	30	1969	25	10636	14	92563	3
	maple	8990	7	4640	13	3964	14	798	30	455	35	532	29	19379	5
	ash	10047	9	2761	18	3601	17	711	30	637	62	1315	25	19072	7
	oak	7514	14	532	34	174	44	620	33	84	74	2147	26	11071	11
	sweet chestnut	17	100	0	.	0	.	176	61	28	100	11748	13	11969	13
	other broadleaves	10335	9	4368	12	4121	17	3778	17	3255	22	12971	11	38829	5
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	184276	2	89430	4	58861	6	40969	7	47048	6	54781	5	475365	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. 1350044. Birmensdorf, Swiss Federal Research Institute WSL

zurück