Selection from the list of topics

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volume of deadwood (stemwood) #24
Volume of stemwood of all dead trees and shrubs (standing and lying) with a diameter at breast height (dbh) ≥12 cm with bark.

main tree species #90
Type of trees and shrubs ≥12 cm in diameter at breast height (dbh) with the ten most common species or species groups in Switzerland ('main tree species') categorised, and the classes 'other conifers' and 'other broadleaves' for the remaining species. The main tree species are: spruce (Picea spp.), fir (Abies spp.), pine (Pinus sylvestris, P. nigra, P. strobus, P. mugo subsp. uncinata), larch (Larix spp.), Arolla pine (Pinus cembra), beech (Fagus sylvatica), maple (Acer spp.), ash (Fraxinus spp.), oak (Quercus spp.) and chestnut (Castanea sativa). Reference: Field Survey (MID 50: Baumart)

higher/lower altitude zone #2635
Areas in higher and lower altitude zones classified according to the system used for altitudinal vegetation belts in the guidelines for monitoring the sustainability and performance of protection forests (NaiS; Frehner et al. 2005). The boundary between the higher and lower altitudes runs between the «upper montane» and «lower montane» levels on the Northern Alps and between the «high montane» and «upper/lower montane» levels to the Southern Alps. The information is based on the altitudinal vegetation belts determined by experts (accessible forest sample plots of NFI4 on the 1.4-km network; Arge Frehner et al. 2020), as well as on the altitudinal vegetation belts modelled for the period 1981-2010 (other sample plots; Zischg et al. 2021).

forest district (2024) #2777
Regional demarcation with the forest districts as a unit. This variable was implemented in the year 2024 and is based on a survey with the cantonal forest services in the years 2022/2023.

accessible forest without shrub forest #434
Forest of which less than two-thirds is covered with shrubs that can be accessed on foot.

1.4-km grid #410
NFI's sampling grid with a mesh size of 1.4 km. The 1.4-km grid is the grid size covering all the previous terrestrial Inventories, which is why it is also called the base grid.

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
volume of deadwood (stemwood)
main tree species · higher/lower altitude zone
regional demarcation: forest district (2024)
unit: 1000 m³
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
state 2009/17
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
main tree species	higher/lower altitude zone	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	higher altitude zone	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
spruce	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	45	58	56	42	33	74	41	42	4	86	28	53	100	41	184	33	120	31	63	40	11	84	16	68	47	52	0	.	40	77	81	52	81	55	58	52	0	0	58	40	0	0	32	61	0	.	37	72	0	.	96	35	110	47	99	43	31	54	2	100	0	0	15	69	0	0	3	72	11	100	25	100	1	100	52	51	41	88	125	64	32	68	3	79	54	34	7	79	16	74	18	62	32	54	27	73	0	.	19	79	16	63	40	61	7	54	0	0	42	61	0	0	0	.	15	80	0	0	1	100	1	100	12	75	9	100	0	0	0	0	9	74	5	100	0	0	71	56	20	91	14	84	22	100	13	75	0	0	10	74	1	100	13	68	13	100	36	94	0	0	34	64	17	79	21	81	101	46	2	74	61	56	65	38	64	51	36	57	29	58	6	79	41	45	0	.	2803	8
	higher altitude zone	0	.	0	.	0	.	0	.	68	41	155	45	2090	13	266	26	2	100	140	31	0	.	0	.	0	.	0	.	24	67	113	40	633	41	59	37	0	.	322	30	345	24	361	25	775	20	1038	17	376	19	43	41	58	50	16	81	579	30	14	71	17	94	5	100	0	0	38	50	69	45	215	35	173	35	7	.	59	48	321	28	74	59	166	48	0	.	21	100	15	74	0	.	5	100	83	43	292	36	110	49	0	.	0	.	0	.	76	54	142	32	101	38	0	0	0	.	0	.	45	52	11	100	55	98	73	55	90	51	219	32	101	46	127	34	221	32	36	64	0	.	164	53	0	.	4	73	82	41	38	72	43	50	126	52	0	0	0	.	29	100	0	.	735	17	370	22	761	19	58	51	3	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	12859	5
	total	45	58	56	42	33	74	41	42	73	39	184	39	2189	13	451	21	122	31	203	25	11	84	16	68	47	52	0	.	64	54	194	32	714	37	118	32	0	0	380	26	345	24	393	23	775	20	1075	17	376	19	138	27	168	35	115	38	610	28	16	64	17	94	20	57	0	0	41	47	81	41	240	33	173	34	59	47	100	46	445	27	107	46	169	47	54	34	27	78	32	52	18	62	37	48	110	37	292	36	129	43	16	63	40	61	7	54	76	54	184	28	101	38	0	0	15	80	0	0	46	51	12	93	66	82	83	50	90	51	219	32	110	43	132	33	221	32	107	43	20	91	178	49	22	100	17	61	82	41	47	59	44	49	139	48	13	100	36	94	29	100	34	64	753	17	392	22	862	18	61	49	64	54	65	38	64	51	36	57	29	58	6	79	41	45	0	.	15662	4
fir	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	35	65	0	0	0	0	69	50	6	100	66	65	30	73	126	36	152	31	48	62	11	100	0	0	19	67	0	.	0	0	2	100	43	56	21	71	0	.	11	58	0	0	26	74	0	.	28	71	0	.	205	31	14	72	101	39	134	48	9	100	0	0	12	87	0	0	11	70	0	0	0	.	6	100	80	55	0	0	1	100	16	100	4	100	0	0	0	0	8	84	0	0	86	48	13	84	0	.	1	100	12	87	0	0	0	0	0	.	9	100	0	.	0	.	0	.	0	0	11	100	92	99	13	90	0	0	0	0	0	0	26	68	0	0	0	0	49	63	0	0	29	79	17	93	6	67	0	.	2	100	17	80	0	0	9	76	0	0	9	87	6	100	0	0	0	0	52	64	4	100	0	0	7	100	55	51	41	65	2	100	0	0	0	0	0	.	1862	10
	higher altitude zone	0	.	0	.	0	.	0	.	0	0	12	65	88	34	157	34	5	100	97	46	0	.	0	.	0	.	0	.	3	72	2	100	52	63	35	67	0	.	29	91	37	57	13	75	34	74	21	59	10	100	49	41	2	71	3	76	64	52	10	79	12	74	0	0	0	0	3	100	21	95	35	59	9	62	0	.	13	92	28	64	8	100	11	87	0	.	17	94	10	92	0	.	0	0	26	56	29	54	27	77	0	.	0	.	0	.	0	0	21	77	9	100	0	.	0	.	0	.	0	0	0	0	0	0	24	49	0	0	29	58	0	100	56	81	90	61	35	100	0	.	2	100	0	.	16	100	20	63	18	70	5	61	1	100	0	0	0	.	0	0	0	.	12	56	34	54	74	47	46	54	0	.	0	.	13	100	0	.	0	.	0	.	0	.	0	.	1480	10
	total	35	65	0	0	0	0	69	50	6	100	78	56	119	31	283	25	157	30	146	37	11	100	0	0	19	67	0	.	3	72	5	71	95	43	56	50	0	.	40	68	37	57	39	55	34	74	49	48	10	100	254	27	16	64	104	38	198	36	18	63	12	74	12	87	0	0	14	59	21	95	35	59	15	54	80	55	13	92	29	62	24	74	15	70	0	0	17	94	18	63	0	0	86	48	39	47	29	54	29	73	12	87	0	0	0	0	0	0	29	62	9	100	0	.	0	.	0	0	11	100	92	99	13	90	24	49	0	0	29	58	27	67	56	81	90	61	84	55	0	0	30	75	17	93	22	75	20	63	20	63	22	62	1	100	9	76	0	0	9	87	6	100	12	56	34	54	126	38	50	50	0	0	7	100	68	46	41	65	2	100	0	0	0	0	0	.	3342	7
pine	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	18	66	1	100	5	100	10	100	0	0	0	.	14	72	5	100	76	53	15	63	25	100	0	0	25	57	0	.	0	0	52	71	0	.	32	66	11	100	0	.	16	67	30	55	0	.	0	.	0	.	65	41	0	0	0	0	0	.	15	100	1	100	17	100	0	.	15	100	0	.	0	.	0	.	0	0	0	.	9	83	0	.	0	0	3	100	0	0	4	100	26	100	41	54	25	77	0	.	0	.	0	0	0	0	2	100	0	.	0	.	0	.	0	.	0	.	2	100	0	.	0	.	5	100	0	0	0	0	0	0	7	100	0	.	0	.	0	.	5	100	0	0	0	0	5	100	0	.	0	0	0	.	0	0	0	.	0	.	0	0	0	.	65	40	40	43	51	40	0	.	5	100	23	59	9	75	2	100	0	0	6	100	0	0	0	.	783	13
	higher altitude zone	0	.	0	.	0	.	0	.	0	0	0	0	44	46	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	100	39	60	0	0	94	35	153	33	0	0	0	.	0	.	15	78	0	.	0	0	0	.	0	.	0	.	0	.	4	100	4	100	0	.	0	.	10	100	0	.	2	100	0	.	0	.	6	71	0	.	7	100	13	71	0	0	1	100	0	.	0	.	0	.	0	.	20	60	9	90	0	.	0	.	0	.	0	.	0	.	0	0	2	100	0	.	6	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	123	28	68	44	95	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	715	13
	total	18	66	1	100	5	100	10	100	0	0	0	0	57	39	5	100	76	53	15	63	25	100	0	0	25	57	0	.	0	0	52	71	0	.	32	66	11	100	0	.	17	64	69	42	0	0	94	35	153	33	65	41	0	0	0	0	15	78	15	100	1	100	17	100	0	.	15	100	0	.	4	100	4	100	0	0	0	.	19	66	0	.	2	100	3	100	0	0	10	58	26	100	47	48	37	56	0	0	1	100	0	0	0	0	2	100	0	.	20	60	9	90	0	.	0	.	2	100	0	.	0	.	5	100	2	100	0	0	6	100	7	100	0	.	0	.	0	.	5	100	0	0	0	0	5	100	0	.	0	0	0	.	0	0	0	.	0	.	0	0	0	.	188	23	108	32	146	25	0	.	5	100	23	59	9	75	2	100	0	0	6	100	0	0	0	.	1498	9
larch	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	0	0	2	100	0	0	0	0	0	0	0	0	2	100	0	0	1	100	0	.	0	.	0	.	0	0	0	.	1	100	15	100	0	.	6	100	0	.	0	0	0	0	15	100	0	.	0	0	0	0	0	0	0	0	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	1	100	0	0	0	0	5	88	0	0	0	0	0	0	0	0	0	0	0	0	0	.	0	.	0	.	0	0	0	0	0	0	0	0	0	.	0	0	0	.	0	0	36	75	0	0	11	86	9	82	5	86	0	.	0	.	0	.	2	100	0	.	0	0	0	0	0	0	0	.	0	0	0	.	0	.	7	100	0	.	11	100	0	.	0	0	0	.	0	0	2	100	0	0	34	64	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	.	168	27
	higher altitude zone	0	.	0	.	0	.	0	.	0	0	0	.	16	100	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	20	76	5	75	17	58	250	25	209	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	9	85	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	12	68	52	41	26	55	31	73	0	.	0	.	52	41	0	100	7	87	0	.	0	.	0	.	10	100	0	0	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	436	20	116	28	146	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1417	10
	total	0	0	2	100	0	0	0	0	0	0	0	0	19	88	0	0	1	100	4	100	0	.	0	.	0	0	0	.	1	100	15	100	0	.	6	100	0	.	0	0	20	76	20	78	17	58	250	25	209	24	0	0	0	0	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	1	100	0	0	0	0	14	62	0	0	0	0	0	0	0	0	0	0	0	0	0	.	0	.	0	0	0	0	0	0	0	0	0	0	12	68	52	41	26	55	31	73	36	75	0	0	62	37	10	79	12	62	0	.	0	.	0	.	12	83	0	0	0	0	0	0	0	0	0	.	0	0	0	.	0	.	7	100	0	.	11	100	0	.	0	0	0	.	0	0	438	20	116	28	180	24	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	.	1585	9
Arolla pine	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	higher altitude zone	0	.	0	.	0	.	0	.	0	.	0	.	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	0	0	0	1	100	79	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	54	38	73	17	69	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	199	23
	total	0	.	0	.	0	.	0	.	0	.	0	.	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	0	0	0	1	100	79	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	54	38	73	17	69	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	199	23
other conifers	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	0	0	0	0	0	0	1	100	0	.	0	0	0	0	0	.	0	0	0	0	0	0	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	0	1	100	0	.	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	.	0	0	0	.	0	0	0	0	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	1	100	3	51	0	0	0	0	0	.	0	.	0	.	0	0	0	0	0	0	0	.	0	.	0	.	0	.	0	0	0	0	0	0	0	0	0	0	0	0	0	.	0	.	0	.	0	.	6	39
	higher altitude zone	0	.	0	.	0	.	0	.	1	100	0	.	2	71	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	79	0	.	0	.	1	100	10	53	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	3	100	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	5	100	1	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	34
	total	0	0	0	0	0	0	1	100	1	100	0	0	2	71	0	.	0	0	0	0	0	0	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	0	2	79	0	.	0	.	1	100	10	53	0	0	0	0	1	100	0	0	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	0	0	0	0	0	3	100	0	0	0	0	0	0	0	0	0	0	0	0	0	.	0	0	0	.	0	0	0	0	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	0	0	.	0	0	0	0	0	.	1	100	3	51	0	0	0	0	0	.	0	.	0	.	0	0	0	0	0	0	0	.	0	.	0	0	5	100	1	100	0	0	0	0	0	0	0	0	0	0	0	.	0	.	0	.	0	.	30	28
beech	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	63	67	43	47	46	96	19	61	0	0	18	59	35	37	69	44	128	34	70	71	37	100	55	58	65	38	0	.	21	60	23	69	0	0	30	52	0	.	15	52	0	0	18	60	0	.	4	74	0	.	67	34	31	50	0	0	30	53	2	100	0	0	1	100	0	0	1	100	6	77	1	100	38	46	21	100	30	56	61	49	20	67	45	60	20	66	8	100	53	80	24	59	41	48	42	78	0	.	0	0	5	83	0	0	5	73	0	.	12	100	0	.	25	48	25	50	20	52	44	39	20	68	63	50	0	100	0	0	0	0	11	64	1	100	0	0	2	76	7	92	32	52	6	77	0	0	0	0	0	0	10	64	2	72	12	82	0	0	0	0	36	71	0	0	1	100	13	51	0	0	12	100	8	91	11	59	17	60	5	78	23	100	14	63	0	.	1740	9
	higher altitude zone	0	.	0	.	0	.	0	.	0	100	1	100	26	61	31	46	0	0	56	45	0	.	0	.	1	100	0	.	0	0	0	0	19	71	0	0	0	.	4	67	8	51	0	0	0	0	0	0	0	.	13	68	0	0	1	71	62	89	0	0	4	81	0	0	0	0	4	59	19	63	0	0	1	100	0	.	5	87	8	61	4	77	9	66	0	.	6	100	3	79	0	.	3	100	9	100	10	71	5	76	0	.	0	.	0	.	0	.	0	0	0	.	8	100	0	.	0	.	0	0	0	0	0	.	0	100	0	.	0	0	0	0	0	0	8	80	15	100	0	.	5	100	0	.	0	0	1	100	13	73	2	100	10	100	0	0	0	.	0	0	0	.	0	.	0	0	9	81	10	93	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	397	19
	total	63	67	43	47	46	96	19	61	0	100	19	55	61	33	101	34	128	34	126	44	37	100	55	58	67	38	0	.	21	60	23	69	19	71	30	52	0	.	19	44	8	51	18	60	0	0	4	74	0	.	80	30	31	50	1	71	91	63	2	100	4	81	1	100	0	0	6	51	25	52	1	100	39	45	21	100	35	49	68	44	24	57	54	52	20	66	14	71	56	76	24	59	44	45	51	66	10	71	5	76	5	83	0	0	5	73	0	.	12	100	0	.	33	44	25	50	20	52	44	39	20	68	63	50	1	72	0	0	0	0	11	64	1	100	8	80	17	90	7	92	37	47	6	77	0	0	1	100	13	73	11	56	13	83	12	82	0	0	0	0	36	71	0	0	1	100	22	45	10	93	12	100	8	91	11	59	17	60	5	78	23	100	14	63	0	.	2136	8
maple	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	9	80	1	100	0	0	9	80	0	0	0	0	5	73	0	0	16	55	1	100	0	0	2	100	3	100	0	.	5	100	9	100	0	0	1	100	0	0	0	0	0	0	0	0	0	.	0	0	0	.	15	49	3	100	0	0	2	100	1	100	0	0	4	75	0	0	0	0	1	100	0	0	0	0	0	0	8	100	1	100	7	100	9	100	11	85	0	0	0	0	0	0	11	76	2	100	0	.	9	100	0	0	0	0	0	0	0	.	0	0	0	0	0	0	1	100	2	71	1	100	0	0	0	0	0	0	0	0	0	0	1	100	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	100	5	73	0	.	2	100	0	.	1	100	0	.	0	0	9	88	0	0	0	0	3	74	17	75	12	72	1	100	0	0	0	0	0	.	201	17
	higher altitude zone	0	.	0	.	0	.	0	.	0	0	3	100	11	54	0	0	3	100	0	0	0	.	0	.	0	0	0	.	0	0	0	0	4	100	6	100	0	.	15	55	0	0	0	0	1	100	0	0	0	0	4	100	2	100	0	0	1	100	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	.	5	100	5	85	0	0	1	100	0	.	0	0	0	0	0	.	0	0	2	100	0	0	0	0	0	.	0	.	0	.	1	100	1	100	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	0	0	0	0	0	0	0	2	100	6	65	0	0	0	.	0	0	0	.	0	.	0	0	0	0	0	0	1	100	0	0	0	.	0	0	0	.	0	0	0	0	7	77	0	0	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	81	21
	total	9	80	1	100	0	0	9	80	0	0	3	100	15	44	0	0	18	49	1	100	0	0	2	100	3	100	0	.	5	100	9	100	4	100	7	86	0	0	15	55	0	0	0	0	1	100	0	0	0	0	19	44	5	72	0	0	3	72	1	100	0	0	4	75	0	0	0	0	1	100	0	0	0	0	0	0	14	73	7	71	7	100	11	88	11	85	0	0	0	0	0	0	11	76	4	71	0	0	9	100	0	0	0	0	0	0	1	100	1	100	0	0	0	0	1	100	2	71	1	100	0	0	0	0	0	0	0	0	0	0	1	100	2	100	6	65	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	100	7	62	0	0	2	100	0	0	1	100	0	0	0	0	16	60	0	0	0	0	3	74	17	75	12	72	1	100	0	0	0	0	0	.	282	13
ash	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	22	64	29	93	0	0	1	100	0	0	11	72	10	71	6	86	26	57	4	72	12	92	8	100	0	0	0	.	0	0	0	0	3	100	1	100	0	0	0	0	0	0	0	0	0	.	7	100	0	.	29	42	8	100	23	52	5	50	1	100	0	0	0	0	0	0	0	0	12	100	10	73	0	0	19	83	6	100	5	73	2	100	2	100	0	0	0	0	0	0	4	71	10	60	20	58	0	.	0	0	3	100	13	100	2	100	0	.	0	0	0	.	2	71	6	100	22	42	4	100	1	100	5	100	0	0	0	0	0	0	8	100	3	100	0	0	2	100	0	0	0	0	5	82	0	0	0	0	3	100	24	77	4	100	0	0	6	100	0	.	0	0	1	100	0	0	17	63	8	87	0	0	0	100	46	68	9	87	6	93	0	0	12	100	0	.	508	14
	higher altitude zone	0	.	0	.	0	.	0	.	3	100	9	100	21	100	1	100	0	0	0	0	0	.	0	.	0	0	0	.	0	.	0	.	0	0	0	0	0	.	11	83	0	0	0	.	7	61	0	0	0	0	4	100	0	0	0	.	0	0	0	0	0	0	0	.	0	.	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	.	0	.	0	0	0	0	0	0	0	.	0	.	0	.	9	75	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	0	0	.	1	100	0	0	2	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	100	4	71	0	0	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	73	36
	total	22	64	29	93	0	0	1	100	3	100	19	60	30	72	7	77	26	57	4	72	12	92	8	100	0	0	0	.	0	0	0	0	3	100	1	100	0	0	11	83	0	0	0	0	7	61	7	100	0	0	33	38	8	100	23	52	5	50	1	100	0	0	0	0	0	0	0	0	12	100	10	73	0	0	19	83	6	100	5	73	2	100	2	100	0	0	0	0	0	0	4	71	10	60	20	58	0	0	0	0	3	100	13	100	2	100	9	75	0	0	0	0	2	71	6	100	22	42	4	100	1	100	5	100	0	0	0	0	0	0	9	92	3	100	2	72	2	100	0	0	0	0	5	82	0	0	0	0	3	100	24	77	4	100	0	0	6	100	0	.	0	0	2	75	4	71	17	63	8	87	0	0	0	100	46	68	9	87	6	93	0	0	12	100	0	.	581	13
oak	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	20	89	1	100	0	0	15	75	0	.	0	0	0	0	0	0	4	73	0	0	13	100	4	100	9	89	0	.	9	71	0	0	2	100	20	71	32	69	0	.	0	0	3	100	0	.	1	100	0	0	18	88	16	100	1	100	0	0	4	59	0	.	0	0	0	0	0	.	0	0	0	.	0	0	0	0	11	100	0	0	0	0	0	.	4	62	0	0	1	100	8	100	1	100	0	0	0	.	0	0	0	0	0	0	13	100	0	.	0	0	0	.	2	100	10	69	27	39	8	88	7	73	2	100	0	0	0	0	0	0	3	79	1	100	0	.	0	0	0	.	0	0	5	100	14	68	0	.	35	85	0	0	9	100	9	81	15	100	0	0	4	100	0	0	1	100	5	61	0	0	0	0	21	71	0	0	5	100	0	0	0	0	7	100	0	.	399	16
	higher altitude zone	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	0	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0
	total	20	89	1	100	0	0	15	75	0	.	0	0	0	0	0	0	4	73	0	0	13	100	4	100	9	89	0	.	9	71	0	0	2	100	20	71	32	69	0	.	0	0	3	100	0	0	1	100	0	0	18	88	16	100	1	100	0	0	4	59	0	.	0	0	0	0	0	.	0	0	0	.	0	0	0	0	11	100	0	0	0	0	0	.	4	62	0	0	1	100	8	100	1	100	0	0	0	.	0	0	0	0	0	0	13	100	0	.	0	0	0	.	2	100	10	69	27	39	8	88	7	73	2	100	0	0	0	0	0	0	3	79	1	100	0	.	0	0	0	.	0	0	5	100	14	68	0	.	35	85	0	0	9	100	9	81	15	100	0	0	4	100	0	0	1	100	5	61	0	0	0	0	21	71	0	0	5	100	0	0	0	0	7	100	0	.	399	16
sweet chestnut	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	61	38	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	100	51	45	19	100	42	41	166	44	237	26	45	59	90	41	147	30	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	91	0	.	0	.	0	.	0	.	3	100	0	.	17	86	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	891	13
	higher altitude zone	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	21	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	58
	total	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	61	38	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	100	51	45	40	57	42	41	166	44	237	26	45	59	90	41	147	30	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	91	0	.	0	.	0	.	0	.	3	100	0	.	17	86	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	912	13
other broadleaves	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	23	64	16	70	6	89	11	72	6	76	0	0	28	45	10	87	13	58	8	54	4	80	2	100	7	47	0	.	6	83	0	0	3	71	0	0	7	90	0	0	13	64	8	75	0	.	64	42	0	0	73	28	15	67	4	71	3	72	0	0	0	0	0	0	0	0	0	0	2	100	2	100	2	71	0	0	7	62	26	54	14	57	0	0	13	88	3	100	0	0	8	92	2	73	28	69	0	.	20	60	9	60	5	52	0	0	0	0	23	41	12	86	46	52	70	28	124	30	103	31	19	60	52	35	0	0	0	0	1	100	13	68	15	75	4	100	1	100	10	83	2	100	10	100	2	73	0	0	0	0	2	100	7	79	1	100	10	91	1	100	1	100	38	69	1	100	49	31	3	100	5	100	24	57	9	70	3	100	1	100	9	100	2	100	0	.	1145	8
	higher altitude zone	0	.	0	.	0	.	0	.	4	84	2	100	74	33	8	63	3	100	3	100	0	.	0	.	1	100	0	.	8	100	4	71	2	71	14	58	0	.	24	43	11	44	14	73	77	37	33	32	19	53	0	0	1	100	0	.	40	52	1	100	3	72	0	.	1	100	5	100	2	100	13	78	12	73	0	.	2	72	11	58	0	0	8	60	0	.	0	0	0	0	0	.	0	0	18	95	4	100	15	81	0	.	0	.	0	.	62	58	2	74	23	42	1	100	0	.	0	.	38	69	0	.	8	64	7	63	7	82	3	78	6	72	18	52	12	46	7	100	0	.	11	86	0	.	0	.	3	76	0	0	0	0	0	0	0	0	0	.	0	.	0	.	43	34	54	47	31	40	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	0	.	781	10
	total	23	64	16	70	6	89	11	72	10	57	2	100	102	27	19	56	17	51	11	48	4	80	2	100	8	42	0	.	14	67	4	71	5	52	14	58	7	90	24	43	24	40	21	54	77	37	97	30	19	53	73	28	16	63	4	71	43	49	1	100	3	72	0	0	1	100	5	100	4	73	15	68	14	64	0	0	9	51	37	42	14	57	8	60	13	88	3	100	0	0	8	92	2	73	46	56	4	100	34	49	9	60	5	52	0	0	62	58	25	39	35	40	47	51	70	28	124	30	141	29	19	60	60	31	7	63	7	82	5	62	19	52	33	44	15	42	9	86	10	83	12	74	10	100	2	73	3	76	0	0	2	100	7	79	1	100	10	91	1	100	1	100	82	37	55	46	80	24	3	100	5	100	24	57	19	63	3	100	1	100	9	100	2	100	0	.	1927	6
indeterminable	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	9	52	0	.	0	.	0	.	0	.	0	.	26	65	1	100	59	46	1	72	2	100	0	.	7	100	0	.	0	.	0	.	0	.	0	.	0	.	6	100	0	.	18	86	0	.	12	91	0	.	12	88	2	100	2	100	0	.	5	100	0	.	0	.	0	.	0	.	0	.	0	.	4	100	6	100	0	.	12	100	0	.	3	100	0	.	0	.	20	86	0	.	8	73	13	72	0	.	0	.	0	.	1	100	0	.	0	.	0	.	0	.	0	100	2	100	9	71	9	66	7	94	0	.	0	.	0	.	0	.	18	67	0	.	1	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	100	3	100	0	.	8	100	1	100	0	.	7	88	0	.	0	.	0	.	0	.	7	100	11	100	0	.	1	100	0	.	314	17
	higher altitude zone	0	.	0	.	0	.	0	.	0	.	7	85	87	32	4	100	0	.	5	68	0	.	0	.	0	.	0	.	1	100	0	100	0	.	5	100	0	.	3	100	20	52	9	96	65	62	12	47	20	69	0	.	0	.	0	.	20	64	0	.	0	.	0	.	0	.	5	100	0	.	9	87	0	.	0	.	2	73	21	72	0	.	0	.	0	.	1	100	0	.	0	.	0	.	6	100	0	.	0	.	0	.	0	.	0	.	3	100	0	.	0	.	0	.	0	.	0	.	1	100	1	100	0	100	12	100	0	.	10	80	8	89	2	84	1	76	2	100	0	.	5	100	0	.	1	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	46	29	52	17	49	4	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	438	15
	total	9	52	0	.	0	.	0	.	0	.	7	85	113	29	4	84	59	46	6	55	2	100	0	.	7	100	0	.	1	100	0	100	0	.	5	100	0	.	9	74	20	52	27	65	65	62	25	51	20	69	12	88	2	100	2	100	20	64	5	100	0	.	0	.	0	.	5	100	0	.	9	87	4	100	6	100	2	73	32	59	0	.	3	100	0	.	1	100	20	86	0	.	8	73	19	59	0	.	0	.	0	.	1	100	0	.	3	100	0	.	0	.	0	100	2	100	9	71	10	62	7	85	0	100	12	100	0	.	10	80	26	54	2	84	2	61	2	100	0	.	5	100	0	.	1	100	0	.	0	.	0	.	0	.	1	100	3	100	0	.	8	100	40	46	29	52	23	43	4	100	0	.	0	.	0	.	7	100	11	100	0	.	1	100	0	.	752	11
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lower altitude zone	244	28	149	34	90	57	175	25	17	52	123	46	250	25	403	22	594	16	210	34	115	44	85	41	184	30	0	.	82	57	182	41	132	42	170	32	50	52	89	36	29	47	150	40	0	.	214	26	0	0	580	17	198	30	230	29	204	43	39	51	1	100	48	51	0	0	30	62	32	61	38	86	52	47	177	35	104	46	244	41	90	42	67	48	105	28	17	57	103	48	88	44	232	26	171	45	0	.	49	52	45	43	58	49	29	57	4	100	136	34	31	70	118	29	331	29	443	18	237	22	246	41	302	21	10	95	0	0	1	100	100	36	25	55	4	83	124	41	43	50	79	41	66	52	40	43	0	0	57	57	55	47	62	43	44	45	71	56	10	89	90	46	128	34	64	39	355	24	17	50	84	46	152	26	210	33	132	33	55	43	45	59	76	41	0	.	10819	4
	higher altitude zone	0	.	0	.	0	.	0	.	77	37	189	40	2471	12	467	22	13	79	306	26	0	.	0	.	3	72	0	.	35	57	119	39	710	37	119	40	0	.	407	26	446	21	442	21	975	17	1450	14	875	14	113	31	63	48	20	66	780	25	25	69	36	51	5	100	1	100	55	38	111	35	276	31	199	31	7	.	86	37	415	25	87	52	197	41	0	.	45	60	35	53	0	.	15	74	156	36	336	32	158	38	0	.	0	.	0	.	164	35	238	25	188	27	40	60	0	.	0	.	135	35	12	92	70	80	119	40	97	48	281	29	127	46	204	39	341	31	95	76	0	.	187	48	0	.	20	89	106	38	69	52	51	45	140	48	0	0	0	.	29	100	0	.	1426	13	718	16	1157	15	118	44	3	.	0	.	23	71	0	.	0	.	0	.	0	.	0	.	18485	4
	total	244	28	149	34	90	57	175	25	93	32	312	30	2721	11	870	15	607	16	516	21	115	44	85	41	187	29	0	.	118	44	302	29	842	32	289	25	50	52	496	22	475	20	591	19	975	17	1664	12	875	14	693	15	261	26	251	27	984	22	64	41	37	50	53	47	1	100	86	33	143	30	315	29	251	27	185	34	190	30	659	22	177	34	264	33	105	28	63	46	138	38	88	44	247	25	327	29	336	32	207	31	45	43	58	49	29	57	168	34	374	20	219	25	157	26	331	29	443	18	373	19	258	39	373	23	129	37	97	48	282	29	226	30	229	35	345	31	219	40	43	50	266	36	66	52	60	41	106	38	126	38	105	32	202	36	44	45	71	56	39	77	90	46	1554	12	782	15	1512	13	135	39	87	45	152	26	233	31	132	33	55	43	45	59	76	41	0	.	29304	3

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. 2296722. Birmensdorf, Swiss Federal Research Institute WSL

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