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growing stock (stemwood) #21
Stemwood volume of living trees and shrubs (standing and lying) with a diameter at breast height (dbh) ≥12 cm with bark.

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).

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)

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 NFI1-NFI5 #2382
Forest that was less than two-thirds covered with shrubs in the five inventories NFI1 (1983-1985), NFI2 (1993-1995), NFI3 (2004-2006), NFI4 (2009-2017) and NFI5 (2018-2026) and was accessible on foot.

1.4 km grid, subgrids 1-5 #1746
Sub-grids 1, 2, 3, 4 and 5 of the field surveys on the sampling grid with a mesh size of 1.4 km (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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NFI3—NFI5
change: growing stock (stemwood)
higher/lower altitude zone · main tree species
regional demarcation: forest district (2024)
unit: 1000 m³
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
change 2004/07–2018/26
		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
higher/lower altitude zone	main tree species	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	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	fir	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	pine	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	larch	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	other conifers	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	beech	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	maple	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	ash	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	oak	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	other broadleaves	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	indeterminable	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
lower altitude zone	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	-189	109	80	187	123	124	-759	53	-56	.	-357	62	-232	167	-1163	43	-1778	46	-499	46	44	83	-38	190	-291	100	0	.	-266	95	-346	72	-298	114	146	217	4	75	-285	58	46	104	96	68	.	.	97	80	.	.	-756	48	-136	109	-543	85	-1182	54	45	135	3	100	-87	77	43	167	-21	351	246	96	.	.	84	152	-91	332	168	110	-243	122	-76	207	-30	552	-514	55	-205	103	-195	96	19	536	22	214	18	253	.	.	-16	181	59	255	-394	61	-647	64	8	.	1021	82	4	100	.	.	22	79	13	100	42	95	2	100	87	54	50	71	18	.	-16	72	-59	132	23	127	.	.	-390	122	4	2388	-26	177	-172	139	-198	102	-4	647	57	72	-70	101	-220	75	-21	135	-352	76	-136	71	-28	291	13	80	-50	107	-13	186	98	64	-302	93	-58	314	-40	277	154	181	-906	47	-291	96	25	529	.	.	-12063	18
	fir	-113	83	-65	95	49	76	-244	107	0	.	160	71	177	54	-48	818	29	1789	-114	266	16	68	78	66	72	58	.	.	39	73	51	74	8	800	-65	150	4	100	2	2523	45	100	20	65	.	.	93	85	.	.	147	196	175	168	225	125	186	64	-80	84	0	100	86	103	5	1174	-124	89	9	296	.	.	139	64	183	77	.	.	-5	806	185	99	-160	92	58	81	-80	209	-70	164	-24	157	56	170	10	100	.	.	22	57	6	1920	-42	391	74	86	.	.	1	100	.	.	.	.	.	.	3	100	73	76	-14	90	103	79	48	81	.	.	-3	100	5	1705	0	100	3	.	89	86	43	100	48	235	-43	428	-63	283	.	.	33	84	78	55	146	71	-72	79	-18	556	73	73	86	77	-3	100	2	100	28	58	13	355	-21	358	-93	160	240	53	-51	152	10	85	15	100	-60	175	.	.	1877	61
	pine	-153	71	-385	62	-20	98	9	236	.	.	.	.	-37	103	19	243	-107	86	14	549	-2	774	2	2322	13	72	.	.	5	100	-138	96	.	.	-80	93	-48	62	.	.	-35	82	-69	99	.	.	.	.	.	.	-49	100	3	100	32	80	.	.	-64	100	2	100	.	.	.	.	18	100	.	.	.	.	.	.	5	100	.	.	.	.	.	.	14	100	-20	359	-19	89	5	632	-35	85	-47	94	.	.	.	.	.	.	-5	390	-15	242	-47	63	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	13	100	0	0	.	.	.	.	.	.	13	89	0	100	.	.	-16	100	.	.	1	94	.	.	-64	73	.	.	.	.	39	100	.	.	-14	415	-40	110	-35	61	.	.	-43	100	-38	129	3	654	-142	54	-11	307	-159	58	-42	101	.	.	-1763	23
	larch	8	221	-8	115	41	114	-132	58	.	.	.	.	35	72	-15	100	-45	118	.	.	.	.	.	.	-9	130	.	.	.	.	23	100	.	.	-5	378	.	.	.	.	-9	116	-108	76	.	.	8	100	9	100	2	100	3	100	1	746	.	.	.	.	.	.	.	.	0	100	.	.	.	.	.	.	10	100	2	100	16	100	-38	65	1	100	.	.	-8	222	.	.	.	.	6	100	.	.	.	.	.	.	6	100	3	100	-11	100	27	100	.	.	29	100	.	.	-7	117	.	.	0	4709	122	53	48	94	49	62	.	.	.	.	.	.	-8	232	.	.	.	.	.	.	51	100	.	.	10	100	.	.	.	.	-11	100	.	.	-1	2059	.	.	21	100	.	.	68	100	2	768	-8	100	-6	170	-15	100	8	100	-1	100	20	89	.	.	-24	94	6	100	-52	79	.	.	112	185
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	other conifers	13	73	.	.	24	100	67	72	.	.	8	71	.	.	.	.	104	162	1	100	.	.	.	.	.	.	99	.	.	.	.	.	.	.	.	.	.	.	0	100	.	.	.	.	.	.	.	.	.	.	6	74	32	97	90	77	.	.	.	.	.	.	1	100	.	.	.	.	.	.	.	.	5	100	105	94	5	100	-4	100	1	190	.	.	-4	100	4	100	2	100	22	77	.	.	.	.	.	.	1	100	.	.	.	.	-3	128	.	.	.	.	.	.	.	.	.	.	.	.	39	100	1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	26	100	15	63	.	.	3	100	.	.	.	.	.	.	-141	100	.	.	6	100	.	.	.	.	.	.	.	.	1	100	.	.	.	.	10	61	32	91	4	71	.	.	.	.	.	.	.	.	573	49
	beech	-625	54	-101	157	105	79	-344	73	23	.	-114	75	-486	81	107	277	-641	76	250	61	-227	57	-127	158	-177	87	.	.	70	107	-6	1686	194	57	91	171	.	.	-383	59	12	173	16	190	.	.	146	50	.	.	-79	379	382	45	-9	1266	-18	320	5	683	-5	100	35	185	9	459	7	553	108	63	14	.	32	321	131	58	-341	78	134	105	-61	303	0	2014351	96	132	-79	103	-273	54	-33	549	-102	162	23	175	.	.	134	58	132	65	20	253	-100	136	.	.	20	78	.	.	222	49	354	34	216	45	167	64	171	56	165	66	174	82	.	.	46	103	93	70	-32	234	47	.	176	60	40	59	2	2088	39	79	-10	210	11	90	-16	456	-86	109	126	50	-13	323	16	403	86	60	9	610	.	.	.	.	52	157	100	64	51	87	32	272	-153	110	-109	132	114	55	-24	231	48	191	.	.	78	1613
	maple	78	83	30	161	17	163	-43	71	.	.	67	79	-17	292	143	59	135	47	-11	745	9	494	13	217	-5	319	.	.	10	100	21	65	12	52	55	54	.	.	13	169	60	59	46	72	.	.	9	73	.	.	19	375	100	42	8	247	-19	277	30	157	14	71	21	96	12	59	5	76	-39	116	.	.	-9	134	-97	72	132	62	43	82	48	69	144	49	35	58	60	50	35	123	-28	123	-18	260	18	242	.	.	13	92	43	99	4	997	-1	8805	.	.	23	100	0	100	-5	151	-20	79	25	79	7	53	16	87	8	60	-15	100	3	.	.	.	-1	1666	-11	155	-12	.	-31	101	9	78	31	84	10	100	19	72	4	100	14	138	3	232	29	97	13	135	-2	100	.	.	41	96	.	.	.	.	75	77	18	127	27	94	-15	198	45	81	-4	1277	102	56	-48	95	111	54	.	.	1685	20
	ash	-18	417	-49	105	-108	72	1	2975	.	.	-67	162	-34	104	-158	64	54	165	-14	257	-149	56	8	219	20	70	.	.	43	58	85	136	111	42	-54	274	-34	100	-439	86	23	71	-7	122	.	.	5	223	.	.	-212	72	-261	88	-59	106	-29	100	15	141	-20	100	4	100	2	203	.	.	48	119	.	.	-5	100	-74	182	-48	152	-27	127	-53	97	38	76	58	73	64	55	3	142	-4	1594	-93	96	-14	597	.	.	19	92	-124	105	-221	54	-48	160	.	.	115	100	2	100	9	112	-10	307	79	56	69	57	25	133	32	72	3	100	1	.	.	.	-89	94	0	6081	.	.	149	65	92	92	-33	138	-60	100	9	77	5	100	9	72	-24	108	82	70	12	197	-163	79	.	.	-137	117	11	79	5	100	96	62	-64	148	62	105	-161	67	-26	170	15	421	71	59	-104	84	-96	76	.	.	-1835	41
	oak	-133	147	19	84	.	.	2	2120	.	.	.	.	4	104	18	127	-19	459	.	.	-44	77	1	100	14	82	.	.	-27	139	4	100	20	103	42	52	-213	76	.	.	.	.	14	100	.	.	-1	100	29	100	6	612	-39	77	-33	201	-12	100	-13	107	.	.	2	100	.	.	.	.	1	100	.	.	.	.	10	100	-15	179	.	.	1	1577	-11	100	-10	187	13	100	-9	121	14	95	2	2306	4	100	.	.	.	.	2	1460	74	189	30	191	.	.	.	.	.	.	14	181	12	225	32	275	-22	93	13	232	38	53	5	338	.	.	3	100	9	98	11	100	.	.	3	448	2	100	-10	127	-4	982	18	117	.	.	-14	554	9	100	-34	66	-37	124	-19	100	9	100	19	87	16	69	2	1103	28	73	.	.	-7	433	18	63	-9	100	-53	121	53	54	-70	102	11	334	.	.	-210	186
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	103	55	0	341	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-10	.	115	97	67	99	-7	915	-93	111	160	87	92	54	32	251	43	264	.	.	.	.	.	.	.	.	1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-8	100	.	.	.	.	.	.	.	.	3	100	.	.	15	66	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	519	53
	other broadleaves	9	726	82	52	23	206	-8	308	.	.	10	73	-119	66	20	301	26	401	-10	220	-60	81	-3	326	-15	142	.	.	7	100	10	649	25	80	109	55	3	72	-181	88	30	81	-15	190	.	.	-37	215	24	100	30	119	24	168	23	69	-4	621	.	.	1	100	6	100	-15	74	2	100	21	66	.	.	8	116	1	342	-14	173	-20	84	-86	81	21	126	-60	103	55	104	-49	72	58	65	-102	77	28	124	.	.	0	0	48	222	44	89	-12	220	.	.	285	58	24	96	42	88	58	121	292	49	41	122	-59	200	59	87	-6	118	.	.	5	100	-133	73	52	97	0	.	20	72	106	101	18	72	2	144	2	134	0	100	52	101	1	616	0	1809	-55	95	-5	797	-1	100	7	100	5	174	16	99	37	149	-19	104	19	64	80	64	0	53530	21	59	20	49	-64	90	48	74	.	.	908	53
	indeterminable	.	.	.	.	.	.	.	.	.	.	0	0	0	0	.	.	0	0	0	0	0	0	.	.	0	0	.	.	.	.	.	.	.	.	0	0	.	.	0	0	.	.	0	0	.	.	.	.	.	.	0	0	0	0	0	0	0	0	.	.	.	.	.	.	0	0	.	.	.	.	.	.	0	0	0	0	0	0	.	.	0	0	.	.	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	.	.	0	0	.	.	.	.	0	0	.	.	.	.	.	.	0	0	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	-1125	62	-399	90	253	75	-1453	41	-33	.	-294	127	-709	86	-1077	82	-2241	53	-383	134	-412	51	-64	363	-380	84	99	.	-118	263	-297	139	73	571	239	164	-284	63	-1273	57	179	66	-7	1682	.	.	422	34	62	72	-885	72	283	178	-264	245	-1077	66	-62	198	-5	234	67	200	55	205	-112	114	395	67	14	.	264	73	175	220	-98	398	-161	233	-39	932	14	2755	-367	94	-188	187	-550	57	-4	6814	-282	125	88	154	.	.	178	63	166	188	-542	79	-725	65	-2	.	1608	63	97	73	269	48	323	49	821	34	630	31	234	79	584	38	260	72	21	.	47	125	-184	100	44	245	39	.	16	3291	386	58	45	281	-218	151	-237	127	17	239	125	71	-90	158	-86	291	-174	65	-516	83	71	175	66	394	34	192	-72	83	277	54	130	105	-205	161	-226	138	112	285	-165	234	-571	76	-739	58	-6	4412	.	.	-10118	34
higher altitude zone	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	.	.	.	.	.	.	.	.	272	83	-400	84	826	86	-527	54	1	.	-251	95	.	.	.	.	.	.	.	.	156	54	104	155	492	35	299	62	.	.	-460	146	953	56	479	83	358	138	-207	317	292	124	154	38	-235	76	-136	67	-896	35	65	109	142	72	-215	69	-23	477	-182	112	203	46	291	48	92	216	.	.	108	78	510	49	145	92	-365	94	.	.	-10	86	-8	704	.	.	.	.	-150	181	-437	76	-147	122	.	.	.	.	.	.	195	96	320	44	-320	97	.	.	.	.	.	.	53	60	32	71	75	85	122	64	340	46	-107	307	-50	246	299	36	159	114	98	65	.	.	23	919	.	.	-26	116	47	256	167	51	-32	369	-18	508	-95	.	.	.	-15	.	.	.	720	37	175	158	725	43	-1	7165	0	.	.	.	22	331	.	.	.	.	.	.	.	.	.	.	4202	48
	fir	.	.	.	.	.	.	.	.	120	79	13	1423	374	39	442	74	28	.	8	1366	.	.	.	.	.	.	.	.	75	74	2	3442	-160	128	28	382	.	.	43	90	77	87	-35	117	55	68	142	71	-6	100	283	45	19	297	49	65	43	477	109	52	186	60	15	79	65	72	597	39	76	75	22	207	131	55	.	.	-53	80	13	387	47	59	-34	356	.	.	94	61	-22	180	.	.	.	.	310	56	-25	596	89	128	.	.	.	.	.	.	18	100	84	60	21	100	.	.	.	.	.	.	-73	100	21	100	.	.	16	605	.	.	64	106	65	91	114	79	252	58	53	84	.	.	251	48	.	.	23	75	96	71	82	62	110	53	61	65	-38	.	.	.	-227	.	.	.	48	94	75	91	391	39	41	170	.	.	.	.	28	100	.	.	.	.	.	.	.	.	.	.	4795	17
	pine	.	.	.	.	.	.	.	.	.	.	-14	100	-54	135	.	.	.	.	-8	117	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	9	135	-3	550	5	100	-66	119	-119	91	0	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	4	100	92	100	22	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	0	.	.	.	.	-9	100	1	100	.	.	.	.	.	.	.	.	.	.	-44	75	9	100	.	.	.	.	.	.	.	.	.	.	4	100	.	.	.	.	23	68	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	76	84	20	142	-28	225	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-79	264
	larch	.	.	.	.	.	.	.	.	.	.	.	.	-2	272	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	100	.	.	2	100	-51	156	38	105	67	72	86	106	382	62	.	.	.	.	.	.	1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	24	97	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	57	48	19	301	118	59	36	103	.	.	.	.	299	38	-16	146	54	172	.	.	.	.	-22	100	-35	269	.	.	20	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	494	50	325	56	32	245	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1931	24
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	0	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	8	100	.	.	.	.	61	49	128	102	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	82	64	-2	2284	-14	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	269	56
	other conifers	.	.	.	.	.	.	.	.	.	.	.	.	1	100	.	.	.	.	0	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-1	100	.	.	.	.	-1	100	4	78	.	.	.	.	.	.	2	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	3	100	1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	2	100	.	.	4	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-1	100	-9	100	0	108	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	200
	beech	.	.	.	.	.	.	.	.	73	67	42	139	133	49	116	74	-23	.	0	34157	.	.	.	.	22	.	.	.	2	100	14	95	-26	539	.	.	.	.	98	83	39	143	-5	1314	-19	94	-2	100	.	.	57	75	6	222	3	76	59	91	-2	532	-77	74	13	155	58	72	-55	119	0	10514	19	71	-30	321	.	.	21	79	179	50	73	75	-102	246	.	.	47	133	65	62	.	.	.	.	65	69	27	200	97	82	.	.	.	.	.	.	.	.	.	.	.	.	6	100	.	.	.	.	19	76	4	106	.	.	72	87	.	.	50	76	-10	233	15	129	57	70	12	100	.	.	62	37	.	.	-82	104	30	170	-89	73	-6	558	21	86	34	.	.	.	-105	.	.	.	.	.	20	89	45	101	-35	147	.	.	.	.	25	169	.	.	.	.	.	.	.	.	.	.	1132	43
	maple	.	.	.	.	.	.	.	.	-22	156	22	173	112	52	29	108	3	.	77	52	.	.	.	.	8	.	.	.	-11	100	17	79	101	47	-12	89	.	.	3	1892	9	88	1	100	32	64	18	106	3	100	12	128	21	85	-11	64	32	80	14	58	45	60	11	100	28	71	14	64	48	47	-26	100	19	141	.	.	6	72	37	49	48	66	-16	454	.	.	9	91	29	60	.	.	.	.	15	55	-24	96	43	92	.	.	.	.	.	.	23	100	.	.	.	.	1	100	.	.	.	.	.	.	.	.	.	.	48	76	3	100	1	100	13	53	22	52	45	104	20	83	.	.	13	65	.	.	.	.	-1	349	14	54	-6	194	-49	131	20	.	.	.	.	.	.	.	9	100	29	72	26	51	.	.	.	.	.	.	38	100	.	.	.	.	.	.	.	.	.	.	1014	20
	ash	.	.	.	.	.	.	.	.	.	.	19	100	22	77	17	57	.	.	-24	88	.	.	.	.	11	.	.	.	.	.	.	.	29	56	3	100	.	.	20	199	.	.	.	.	-40	100	13	80	.	.	27	94	.	.	1	100	1	291	6	100	-7	222	.	.	.	.	3	100	20	105	.	.	87	73	.	.	2	100	13	73	.	.	-60	66	.	.	3	100	5	100	.	.	.	.	6	199	8	84	-29	79	.	.	.	.	.	.	7	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	49	75	13	84	.	.	33	78	9	87	22	137	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-27	259	18	63	0	100	.	.	.	.	.	.	-7	100	.	.	.	.	.	.	.	.	.	.	276	52
	oak	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	8	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	13	73
	other broadleaves	.	.	.	.	.	.	.	.	-3	71	9	97	24	132	-16	195	1	.	1	489	.	.	.	.	0	.	.	.	-17	71	-3	213	23	71	-15	103	.	.	-5	349	-6	270	-16	76	81	103	-68	61	136	123	12	86	-2	195	1	100	40	67	.	.	-1	845	.	.	-5	100	-22	106	11	49	-13	85	-20	132	.	.	13	87	33	133	.	.	-72	73	.	.	1	100	1	100	.	.	.	.	-14	154	-1	538	-8	122	.	.	.	.	.	.	-16	121	-2	131	0	607	-2	100	.	.	.	.	-3	125	.	.	5	100	8	164	-29	100	4	73	-3	148	3	192	9	53	3	72	.	.	-7	264	.	.	.	.	10	62	.	.	3	145	.	.	-7	.	.	.	.	.	.	.	-28	226	49	80	-18	207	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	60	396
	indeterminable	.	.	.	.	.	.	.	.	.	.	0	0	0	0	0	0	.	.	0	0	.	.	.	.	.	.	.	.	0	0	0	0	.	.	0	0	.	.	.	.	0	0	.	.	0	0	0	0	0	0	.	.	0	0	.	.	0	0	.	.	.	.	.	.	.	.	0	0	0	0	0	0	.	.	.	.	0	0	0	0	0	0	0	0	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	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	.	.	.	.	.	.	.	.	440	67	-310	152	1435	54	60	678	11	.	-196	159	.	.	.	.	41	.	.	.	206	50	133	139	458	74	309	70	.	.	-298	234	1037	54	458	91	538	95	-24	2962	820	66	546	36	-192	109	-93	85	-719	57	192	54	288	57	-175	74	122	65	356	100	362	42	385	48	301	81	.	.	102	104	811	34	313	59	-649	86	.	.	146	55	69	143	.	.	.	.	224	148	-452	83	45	617	.	.	.	.	.	.	285	75	382	41	-159	202	40	90	.	.	.	.	295	44	41	99	138	83	316	58	328	48	15	2293	13	1707	467	33	562	51	187	60	.	.	342	63	.	.	-85	80	183	86	174	82	69	206	14	784	-85	.	.	.	-348	.	.	.	1374	32	706	55	1160	32	5	3116	0	.	.	.	106	98	.	.	.	.	.	.	.	.	.	.	13624	18
total	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	-189	109	80	187	123	124	-759	53	216	107	-758	53	594	137	-1690	34	-1777	46	-750	44	44	83	-38	190	-291	100	0	.	-109	243	-242	123	194	195	445	82	4	75	-744	93	1000	54	575	70	358	138	-110	603	292	124	-602	61	-371	62	-679	69	-2078	34	110	85	145	71	-302	54	20	667	-203	107	450	57	291	48	176	134	-91	332	276	74	267	146	68	304	-395	97	-514	55	-215	99	-202	96	19	536	22	214	-132	208	-437	76	-163	111	59	255	-394	61	-647	64	203	92	1341	63	-316	98	.	.	22	79	13	100	95	54	35	66	163	49	173	50	358	44	-124	267	-109	134	322	35	159	114	-292	164	4	2388	-4	6064	-172	139	-224	91	43	285	224	42	-102	136	-238	79	-117	85	-352	76	-151	64	-28	291	733	36	125	225	712	44	97	114	-302	93	-58	314	-18	751	154	181	-906	47	-291	96	25	529	.	.	-7861	38
	fir	-113	83	-65	95	49	76	-244	107	120	79	174	126	551	32	394	130	57	912	-106	305	16	68	78	66	72	58	.	.	113	55	52	132	-152	142	-37	393	4	100	45	134	122	66	-16	278	55	68	235	54	-6	100	431	73	194	154	274	103	229	103	29	299	185	61	101	89	70	113	473	54	86	75	22	207	271	43	183	77	-53	80	8	751	232	80	-194	98	58	81	15	1197	-92	131	-24	157	56	170	320	55	-25	596	111	103	6	1920	-42	391	74	86	18	100	85	59	21	100	.	.	.	.	3	100	1	13872	6	389	103	79	64	160	.	.	61	111	71	156	115	79	255	58	143	62	43	100	299	55	-43	428	-40	444	96	71	115	50	188	38	207	54	-110	62	-18	556	-154	152	86	77	45	100	77	89	419	36	54	155	-21	358	-93	160	268	49	-51	152	10	85	15	100	-60	175	.	.	6672	21
	pine	-153	71	-385	62	-20	98	9	236	.	.	-14	100	-91	90	19	243	-107	86	7	1191	-2	774	2	2322	13	72	.	.	5	100	-138	96	.	.	-80	93	-48	62	.	.	-26	119	-72	97	5	100	-66	119	-119	91	-49	100	3	100	32	80	.	.	-64	100	2	100	.	.	.	.	18	100	4	100	92	100	22	100	5	100	.	.	.	.	.	.	14	100	-20	359	-19	89	5	632	-35	85	-47	94	-9	100	1	100	.	.	-5	390	-15	242	-47	63	.	.	-44	75	9	100	.	.	.	.	.	.	.	.	.	.	4	100	.	.	.	.	36	56	0	0	.	.	.	.	.	.	13	89	0	100	.	.	-16	100	.	.	1	94	.	.	-64	73	.	.	.	.	39	100	.	.	62	138	-19	273	-63	105	.	.	-43	100	-38	129	3	654	-142	54	-11	307	-159	58	-42	101	.	.	-1842	25
	larch	8	221	-8	115	41	114	-132	58	.	.	.	.	33	81	-15	100	-45	118	.	.	.	.	.	.	-9	130	.	.	.	.	23	100	.	.	0	17625	.	.	2	100	-60	135	-70	132	67	72	93	98	391	61	2	100	3	100	1	746	1	100	.	.	.	.	.	.	0	100	.	.	.	.	.	.	10	100	2	100	16	100	-14	239	1	100	.	.	-8	222	.	.	.	.	6	100	.	.	.	.	.	.	6	100	3	100	-11	100	27	100	57	48	48	135	118	59	29	129	.	.	0	4709	421	31	31	162	103	95	.	.	.	.	-22	100	-43	221	.	.	20	100	.	.	51	100	.	.	10	100	.	.	.	.	-11	100	.	.	-1	2059	.	.	21	100	.	.	68	100	497	50	316	57	26	306	-15	100	8	100	-1	100	20	89	.	.	-24	94	6	100	-52	79	.	.	2043	25
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	0	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	8	100	.	.	.	.	61	49	128	102	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	82	64	-2	2284	-14	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	269	56
	other conifers	13	73	.	.	24	100	67	72	.	.	8	71	1	100	.	.	104	162	1	71	.	.	.	.	.	.	99	.	.	.	.	.	.	.	.	.	.	.	0	100	-1	100	.	.	.	.	-1	100	4	78	6	74	32	97	90	77	2	100	.	.	.	.	1	100	.	.	.	.	.	.	.	.	5	100	105	94	8	72	-3	124	1	190	.	.	-4	100	4	100	2	100	22	77	.	.	.	.	.	.	1	100	.	.	.	.	-3	128	.	.	.	.	.	.	.	.	.	.	.	.	39	100	1	100	.	.	.	.	.	.	2	100	.	.	4	100	.	.	.	.	26	100	15	63	.	.	3	100	.	.	.	.	.	.	-141	100	.	.	6	100	.	.	.	.	-1	100	-9	100	0	140	.	.	.	.	10	61	32	91	4	71	.	.	.	.	.	.	.	.	579	49
	beech	-625	54	-101	157	105	79	-344	73	96	56	-72	143	-353	113	223	139	-664	73	250	89	-227	57	-127	158	-156	100	.	.	72	104	8	1249	168	105	91	171	.	.	-285	85	51	117	11	700	-19	94	144	51	.	.	-21	1429	388	45	-6	1827	41	196	3	1350	-82	70	48	141	67	88	-47	162	109	68	32	59	2	7589	131	58	-319	84	313	53	12	1618	-102	279	96	132	-31	324	-209	73	-33	549	-102	162	88	69	27	200	231	48	132	65	20	253	-100	136	.	.	20	78	.	.	227	48	354	34	216	45	186	58	175	55	165	66	247	63	.	.	96	63	83	84	-17	449	104	59	188	57	40	59	64	72	39	79	-92	95	41	127	-104	92	-92	108	147	44	21	264	16	403	-19	615	9	610	.	.	20	89	97	96	65	127	51	87	32	272	-128	135	-109	132	114	55	-24	231	48	191	.	.	1209	111
	maple	78	83	30	161	17	163	-43	71	-22	156	88	74	95	81	172	52	139	46	66	134	9	494	13	217	3	714	.	.	-1	2372	37	51	113	42	44	72	.	.	16	343	70	52	47	72	32	64	27	76	3	100	31	232	121	38	-3	713	13	458	44	110	59	49	33	72	40	53	19	51	9	571	-26	100	10	295	-97	72	138	59	80	49	97	48	128	81	35	58	69	45	63	73	-28	123	-18	260	33	133	-24	96	56	73	43	99	4	997	-1	8805	23	100	23	100	0	100	-4	182	-20	79	25	79	7	53	16	87	8	60	34	119	5	71	1	100	12	169	11	197	34	144	-11	337	9	78	44	62	10	100	19	72	3	136	28	76	-3	406	-21	339	33	81	-2	100	.	.	41	96	9	100	29	72	101	59	18	127	27	94	-15	198	83	63	-4	1277	102	56	-48	95	111	54	.	.	2699	14
	ash	-18	417	-49	105	-108	72	1	2975	.	.	-49	227	-12	320	-141	72	54	165	-38	109	-149	56	8	219	31	58	.	.	43	58	85	136	140	35	-51	292	-34	100	-419	91	23	71	-7	122	-40	100	18	86	.	.	-185	84	-261	88	-58	108	-28	103	21	102	-27	94	4	100	2	203	3	100	68	90	.	.	81	78	-74	182	-45	160	-14	260	-53	97	-22	227	58	73	67	52	8	82	-4	1594	-93	96	-7	1155	8	84	-10	278	-124	105	-221	54	-48	160	7	100	115	100	2	100	9	112	-10	307	79	56	69	57	25	133	32	72	52	71	14	79	.	.	-56	155	9	266	22	137	149	65	92	92	-33	138	-60	100	9	77	5	100	9	72	-24	108	82	70	12	197	-163	79	.	.	-137	117	-16	430	23	54	96	62	-64	148	62	105	-161	67	-33	136	15	421	71	59	-104	84	-96	76	.	.	-1559	49
	oak	-133	147	19	84	.	.	2	2120	.	.	.	.	4	104	18	127	-19	459	.	.	-44	77	1	100	14	82	.	.	-27	139	4	100	20	103	42	52	-213	76	.	.	.	.	14	100	.	.	-1	100	29	100	6	612	-39	77	-33	201	-12	100	-13	107	.	.	2	100	.	.	.	.	1	100	.	.	.	.	10	100	-15	179	.	.	1	1577	-11	100	-10	187	13	100	-9	121	14	95	2	2306	4	100	.	.	.	.	2	1460	74	189	30	191	.	.	.	.	.	.	14	181	12	225	32	275	-22	93	13	232	38	53	5	338	.	.	3	100	9	98	11	100	.	.	3	448	2	100	-10	127	-4	982	18	117	.	.	-14	554	9	100	-34	66	-37	124	-19	100	9	100	19	87	16	69	8	364	28	73	.	.	-7	433	18	63	-9	100	-53	121	53	54	-70	102	11	334	.	.	-205	190
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	103	55	0	341	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-10	100	120	93	75	89	-7	915	-93	111	160	87	92	54	32	251	43	264	.	.	.	.	.	.	.	.	1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-8	100	.	.	.	.	.	.	.	.	3	100	.	.	15	66	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	531	51
	other broadleaves	9	726	82	52	23	206	-8	308	-3	71	18	60	-95	89	4	1774	27	381	-9	246	-60	81	-3	326	-15	142	.	.	-9	150	7	965	48	53	93	67	3	72	-186	86	25	116	-31	101	81	103	-106	85	160	106	42	89	22	183	25	66	36	96	.	.	0	16230	6	100	-20	61	-20	118	32	47	-13	85	-12	223	1	342	-1	4075	13	364	-86	81	-52	114	-60	103	56	102	-48	73	58	65	-102	77	14	287	-1	538	-8	122	48	222	44	89	-12	220	-16	121	283	58	24	95	40	92	58	121	292	49	38	131	-59	200	64	80	2	669	-29	100	9	62	-137	71	55	92	9	53	22	64	106	101	11	209	2	144	2	134	11	60	52	101	4	158	0	1809	-62	85	-5	797	-1	100	7	100	-23	279	66	65	19	355	-19	104	19	64	80	64	0	53530	21	59	20	49	-64	90	48	74	.	.	968	56
	indeterminable	.	.	.	.	.	.	.	.	.	.	0	0	0	0	0	0	0	0	0	0	0	0	.	.	0	0	.	.	0	0	0	0	.	.	0	0	.	.	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	.	.	.	.	.	.	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	.	.	0	0	.	.	.	.	0	0	.	.	.	.	.	.	0	0	0	0	.	.	0	0	0	0	.	.	0	0	0	0	0	0	0	0	0	0	.	.	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	-1125	62	-399	90	253	75	-1453	41	407	73	-605	99	727	136	-1017	95	-2229	54	-579	103	-412	51	-64	363	-340	95	99	.	87	376	-164	276	531	101	547	82	-284	63	-1571	64	1217	47	451	96	538	95	399	179	882	61	-340	196	91	599	-357	183	-1796	46	129	125	283	58	-108	173	178	78	244	156	757	40	398	46	565	55	175	220	4	9597	651	71	273	150	-635	107	-367	94	-42	851	-481	68	-4	6814	-282	125	311	115	-452	83	223	135	166	188	-542	79	-725	65	283	75	1990	51	-62	529	309	43	323	49	821	34	925	25	275	68	722	35	576	46	350	46	62	567	-171	169	511	37	601	49	203	271	386	58	387	64	-218	151	-322	95	200	81	299	56	-21	932	-71	383	-259	54	-516	83	-277	133	66	394	1408	31	634	62	1437	28	135	148	-205	161	-226	138	218	154	-165	234	-571	76	-739	58	-6	4412	.	.	3506	120

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. 2285894. Birmensdorf, Swiss Federal Research Institute WSL

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