Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI4—NFI5
change: growing stock (stemwood)
protection forest against hillslope debris flows/landslides (2022) · main tree species
regional demarcation: forest district (2024)
unit: 1000 m³
evaluation area: accessible forest without shrub forest NFI4/NFI5
grid: 1.4 km grid, subgrids 1-5
change 2009/17–2018/26
		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
protection forest against hillslope debris flows/landslides (2022)	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	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
inside	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	.	.	.	.	.	.	.	.	13	.	-62	210	35	387	-187	75	1	100	52	117	.	.	3	100	.	.	.	.	.	.	.	.	34	86	.	.	.	.	-188	94	93	62	43	400	-307	89	-76	357	-54	276	-255	78	.	.	.	.	.	.	-8	.	61	75	.	.	-9	182	-16	110	120	96	.	.	256	95	69	67	-106	113	85	66	0	.	5	437	-99	89	.	.	.	.	.	.	.	.	-1	4639	.	.	.	.	-12	109	.	.	.	.	99	53	39	105	-83	89	.	.	0	100	6	100	59	77	1	100	.	.	-46	.	46	.	-273	110	9	83	16	100	87	100	15	100	.	.	-4	100	.	.	.	.	.	.	.	.	.	.	24	.	.	.	.	.	-85	.	.	.	163	110	-141	161	185	62	.	.	.	.	.	.	6	.	3	.	.	.	.	.	.	.	.	.	-387	209
	fir	.	.	.	.	.	.	.	.	.	.	121	78	29	138	-22	182	-31	220	-87	155	.	.	.	.	.	.	.	.	.	.	.	.	0	100	.	.	.	.	15	103	.	.	-19	100	.	.	48	100	0	0	-155	89	4	100	.	.	.	.	.	.	33	63	.	.	-10	100	3	554	6	100	.	.	39	100	4	100	-36	100	4	137	-2	.	70	68	.	.	.	.	.	.	.	.	.	.	78	85	.	.	-32	87	-31	83	.	.	.	.	.	.	46	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	4	.	.	.	-18	199	25	149	77	96	15	100	.	.	.	.	-14	272	41	.	.	.	.	.	.	.	.	.	9	.	.	.	.	.	10	.	.	.	-5	100	-3	219	68	82	.	.	.	.	.	.	6	.	.	.	.	.	.	.	.	.	.	.	293	100
	pine	.	.	.	.	.	.	.	.	.	.	.	.	-4	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	257	.	.	-39	125	19	362	9	67	.	.	.	.	.	.	.	.	2	100	.	.	.	.	.	.	.	.	.	.	26	100	.	.	.	.	.	.	.	.	.	.	-9	100	.	.	.	.	-11	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	14	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	32	66	0	0	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-11	354	3	611	-5	128	.	.	.	.	.	.	-5	.	.	.	.	.	.	.	.	.	.	.	27	385
	larch	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	677	31	102	9	78	3	610	81	47	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	7	100	-3	100	.	.	-10	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	3	100	7	95	2	100	1	100	.	.	-4	100	149	71	0	0	.	.	.	.	.	.	.	.	6	100	.	.	10	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	59	82	89	91	1	5891	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	441	35
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	19	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	100	-6	123	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	-31	75	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-13	245
	other conifers	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	4	100	.	.	.	.	.	.	1	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	100	.	.	.	.	.	.	1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	7	59
	beech	.	.	.	.	.	.	.	.	.	.	-5	337	107	62	6	498	15	97	-108	69	-5	.	-112	129	30	.	.	.	.	.	.	.	64	78	.	.	.	.	10	130	-8	173	8	140	-2	100	-3	100	.	.	22	146	28	118	.	.	.	.	-22	.	-8	146	.	.	1	100	-11	160	35	100	.	.	2	161	27	86	-111	176	82	71	-38	.	-46	93	-24	79	.	.	.	.	-30	.	-70	.	28	82	.	.	29	116	13	74	.	.	.	.	.	.	0	573	.	.	-1	2133	70	63	-26	97	.	.	-23	100	4	100	.	.	.	.	26	168	-1	1944	-1	228	3	100	85	71	.	.	10	88	30	.	.	.	.	.	.	.	.	.	3	.	.	.	.	.	24	.	.	.	.	.	.	.	-63	116	22	.	.	.	.	.	-9	.	10	.	.	.	.	.	.	.	.	.	68	487
	maple	.	.	.	.	.	.	.	.	.	.	10	83	2	2141	.	.	31	100	18	87	.	.	-16	100	.	.	.	.	.	.	.	.	2	88	.	.	.	.	36	154	-13	100	10	101	17	100	1	100	.	.	15	76	1	100	.	.	.	.	.	.	4	120	.	.	5	84	2	100	5	100	.	.	2	100	-14	116	153	98	-1	368	3	.	30	90	.	.	.	.	.	.	.	.	1	.	4	96	.	.	1	100	-22	71	.	.	.	.	1	100	.	.	.	.	1	100	.	.	4	95	.	.	2	100	.	.	.	.	.	.	1	100	-4	210	-2	318	-3	100	.	.	.	.	2	803	10	.	.	.	.	.	.	.	.	.	0	.	.	.	.	.	.	.	.	.	.	.	0	100	31	93	-3	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	328	55
	ash	.	.	.	.	.	.	.	.	.	.	-23	100	-29	79	.	.	-14	188	-5	100	-45	.	.	.	.	.	.	.	.	.	.	.	12	135	.	.	.	.	-42	70	10	100	-7	100	46	92	.	.	.	.	-20	174	.	.	.	.	.	.	.	.	-28	71	.	.	-2	100	.	.	-21	100	.	.	1	100	1	436	-11	219	7	100	.	.	-26	82	.	.	.	.	.	.	.	.	0	.	-11	100	.	.	.	.	-26	100	.	.	.	.	.	.	.	.	.	.	1	76	.	.	-5	100	.	.	-8	100	3	156	.	.	0	.	.	.	-68	100	0	100	.	.	18	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	13	85	1	100	5	401	3	.	.	.	.	.	.	.	2	.	.	.	.	.	.	.	.	.	-272	47
	oak	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	0	18	92	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-11	100	.	.	.	.	.	.	.	.	.	.	.	.	-2	100	.	.	.	.	.	.	.	.	.	.	6	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-3	100	.	.	7	79	-13	113	29	103	-1	226	-22	85	.	.	.	.	.	.	5	100	0	73	-1	100	.	.	2	100	.	.	3	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	18	89	11	68	-10	78	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	34	142
	sweet chestnut	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	4	100	-1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	100	73	65	3	100	-49	75	-32	180	-8	911	17	230	-45	72	33	157	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	2	140	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-3	4341
	other broadleaves	.	.	.	.	.	.	.	.	.	.	1	100	-209	98	.	.	11	100	11	78	.	.	1	100	.	.	.	.	.	.	.	.	1	100	.	.	.	.	1	100	-22	74	73	96	-55	93	-6	271	8	132	17	78	1	362	.	.	.	.	.	.	2	100	.	.	-12	100	.	.	.	.	.	.	7	70	0	0	9	77	3	77	.	.	-5	197	0	0	.	.	.	.	0	.	.	.	18	99	.	.	.	.	.	.	.	.	.	.	3	76	18	111	0	242	23	61	19	75	66	69	6	100	39	71	70	70	.	.	.	.	6	74	-29	102	2	100	-8	100	2	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	2	.	.	.	5	189	-2	1407	75	68	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	151	163
	indeterminable	.	.	.	.	.	.	.	.	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	0	0	0	.	.	0	0	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	0	0	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	0	.	.	.	.	.	.	0	.	.	.	.	.	0	0	0	0	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	0
	total	.	.	.	.	.	.	.	.	13	.	42	456	-51	564	-203	90	30	114	-120	144	-50	.	-124	130	30	.	.	.	.	.	.	.	113	58	.	.	.	.	-168	106	60	106	145	129	-291	96	-67	428	47	342	-379	69	33	107	.	.	.	.	-30	.	66	72	.	.	-31	83	-22	192	145	82	.	.	338	82	87	62	-89	348	176	48	-36	.	19	326	-132	82	.	.	.	.	-41	.	-69	.	116	91	.	.	-3	364	-77	71	.	.	.	.	108	53	194	47	-78	94	-16	209	44	156	63	154	230	54	-56	95	109	72	-42	.	46	.	-222	138	-62	186	91	97	104	108	122	71	.	.	-2	2623	81	.	.	.	.	.	.	.	.	.	37	.	.	.	.	.	-50	.	.	.	247	76	-71	360	289	64	21	.	.	.	.	.	-2	.	14	.	.	.	.	.	.	.	.	.	676	157
outside	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	-32	341	-13	1392	65	155	-631	59	256	68	-717	52	-759	109	-940	49	-1084	60	-701	42	43	84	-25	189	4	1121	.	.	-40	183	-189	159	-38	1061	507	41	4	75	-507	75	675	51	409	61	505	85	551	80	276	109	-279	103	-307	64	-138	128	-1160	58	-63	75	154	62	-152	72	27	232	-133	83	147	53	122	75	258	54	264	40	383	53	-29	1298	-127	151	-486	87	-401	59	-64	223	-272	83	-43	255	41	58	-446	66	279	70	-74	223	149	51	-205	73	-535	52	-13	1095	1123	77	-494	69	43	100	18	100	.	.	58	57	13	73	213	35	120	57	222	67	160	78	171	54	271	38	-6	2986	-28	319	-51	135	83	119	42	178	-88	94	-145	91	43	111	-165	64	-420	54	-159	74	-126	103	-15	100	65	64	249	77	244	55	412	64	223	46	-366	87	45	376	135	111	18	1095	-685	59	-270	80	-8	830	.	.	-4540	54
	fir	-139	77	-62	109	25	140	-313	90	52	158	-111	180	434	31	353	118	200	141	-220	162	14	80	16	53	62	52	.	.	84	53	41	197	-221	147	-88	177	4	100	-39	189	85	73	-38	103	9	269	46	138	-17	100	476	40	51	431	223	89	167	120	-7	840	-13	695	44	181	20	160	397	37	31	151	23	158	129	51	153	63	-3	268	44	85	220	66	-147	142	45	72	26	416	-98	120	-68	71	140	47	156	75	-49	273	44	179	32	277	38	113	40	96	10	100	35	55	5	100	.	.	.	.	7	100	40	76	16	271	80	88	-57	163	1	100	-19	85	-5	2026	33	89	160	72	115	58	10	205	130	101	-74	132	-18	607	28	255	79	48	143	41	72	84	-102	77	90	69	-228	104	34	100	42	94	57	61	171	43	27	215	-34	202	-37	234	42	202	8	891	38	89	-5	100	-99	128	.	.	3085	37
	pine	-50	73	-14	72	-8	110	3	558	.	.	-17	100	-48	136	47	100	-48	105	-18	253	-2	688	58	68	24	58	.	.	3	100	-123	106	.	.	-43	114	-43	59	.	.	53	57	1	2661	4	100	73	85	-19	432	5	1621	1	100	59	77	.	.	-57	100	.	.	.	.	.	.	20	100	4	100	28	100	.	.	10	100	.	.	-48	102	.	.	11	100	-21	225	1	229	-6	165	9	84	-3	515	23	88	1	100	.	.	-4	402	-41	91	9	299	.	.	-32	100	3	310	.	.	4	100	.	.	.	.	.	.	-3	100	.	.	-14	100	9	100	.	.	.	.	.	.	.	.	4	79	0	100	.	.	-8	100	.	.	1	94	.	.	4	100	.	.	.	.	-26	100	.	.	-33	92	32	141	-87	78	.	.	-6	100	16	249	1	298	-59	95	-16	231	-99	76	11	100	.	.	-470	64
	larch	16	160	-21	91	39	115	-50	76	.	.	.	.	37	78	-16	100	-60	107	.	.	.	.	.	.	2	94	.	.	.	.	11	100	.	.	14	73	.	.	-16	72	-31	243	-21	177	66	75	364	33	273	101	2	100	1	100	8	71	1	100	.	.	.	.	.	.	-2	100	.	.	.	.	.	.	4	100	2	100	.	.	19	142	0	100	.	.	-3	381	.	.	.	.	3	100	.	.	.	.	.	.	6	100	5	100	-17	100	27	100	-29	144	48	114	123	51	57	145	.	.	4	73	302	26	44	72	41	142	.	.	.	.	.	.	56	77	.	.	.	.	.	.	20	100	.	.	10	100	.	.	.	.	-12	100	.	.	8	113	.	.	11	100	.	.	39	100	324	47	126	109	-46	127	-15	100	8	100	-6	100	19	88	.	.	-28	71	5	100	1	1636	.	.	1772	25
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	71	.	.	7	100	39	93	189	48	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	3	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	88	46	30	91	-3	377	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	360	31
	other conifers	6	72	.	.	28	100	43	75	.	.	5	71	-2	182	.	.	159	42	0	100	.	.	.	.	.	.	75	.	.	.	.	.	.	.	.	.	.	.	.	.	-1	99	.	.	.	.	-1	112	-2	124	16	90	16	94	77	79	1	100	.	.	.	.	0	100	.	.	.	.	.	.	1	100	.	.	50	92	24	88	-3	124	-1	100	.	.	9	100	2	100	25	100	18	85	.	.	5	100	.	.	1	100	.	.	.	.	0	86	.	.	.	.	.	.	.	.	.	.	.	.	31	100	.	.	.	.	.	.	.	.	.	.	.	.	3	100	.	.	.	.	-47	100	10	62	.	.	1	100	.	.	.	.	.	.	-185	100	.	.	4	100	.	.	.	.	-2	73	-1	100	1	77	.	.	.	.	5	55	14	123	3	72	.	.	.	.	.	.	.	.	391	61
	beech	-225	92	2	4858	37	209	-238	66	64	98	-58	119	-92	311	385	60	-176	163	134	140	-89	74	13	687	-608	53	.	.	24	153	-8	1524	-15	824	-2	7437	.	.	-36	299	3	1893	12	546	-7	123	106	58	.	.	-200	106	42	314	29	323	100	59	-124	112	-40	80	62	96	-7	817	-83	138	14	400	18	64	-192	52	195	58	36	175	165	63	-90	202	195	108	75	131	80	140	-265	60	-139	122	3	2564	-24	217	57	71	89	65	21	346	-54	89	31	378	.	.	51	71	.	.	92	43	56	145	152	37	310	44	204	37	79	105	125	77	7	100	1	100	38	122	-55	108	41	133	71	72	-3	529	17	289	7	196	-29	104	27	162	-27	265	-169	78	35	251	15	255	58	53	-38	238	-54	85	.	.	10	75	16	259	20	180	84	37	97	58	-1	6610	-36	305	39	191	-97	69	25	183	.	.	386	263
	maple	94	44	51	57	-55	63	-37	68	7	99	11	391	-20	450	139	42	159	32	102	53	12	253	32	51	-31	116	.	.	-14	146	29	57	29	125	35	67	3	100	30	141	38	77	-31	226	5	58	2	727	3	100	48	148	44	70	-17	134	-5	750	23	93	35	89	37	96	53	80	10	68	2	1491	11	84	-27	186	2	2056	44	68	50	97	18	174	90	63	15	94	52	47	28	84	24	86	70	118	-20	267	12	176	34	82	72	47	-47	156	31	113	23	100	31	71	-8	100	12	79	-26	71	-7	204	11	43	54	71	26	73	5	391	25	61	.	.	-2	1395	-11	136	53	111	10	126	9	78	21	52	.	.	16	82	10	87	35	96	-6	439	29	71	25	76	-6	100	.	.	64	69	8	100	18	59	97	45	-8	275	36	96	35	96	69	80	9	270	42	120	-62	77	13	227	.	.	1934	17
	ash	-16	311	-35	117	-138	64	-85	99	.	.	-58	153	-20	137	-60	161	-5	1407	-25	140	-97	66	-10	200	-16	194	.	.	-32	136	48	236	137	55	-111	80	-19	100	7	701	4	100	10	93	-36	131	15	41	.	.	-133	65	-195	92	-99	56	-60	64	-5	184	2	100	2	100	1	100	2	100	94	97	.	.	42	103	61	197	-29	316	-11	77	-60	161	13	424	16	158	36	57	3	398	-78	72	-2	622	7	448	-56	113	-30	111	-111	108	-167	59	18	317	6	100	88	100	11	82	-8	104	-3	581	52	70	28	122	-36	75	24	53	28	128	9	107	.	.	-35	131	22	63	10	243	131	90	45	93	-17	87	-69	101	7	90	3	100	10	84	-24	128	-21	148	17	61	-165	77	.	.	-167	109	5	343	34	63	-31	242	-59	124	46	89	-74	74	-56	92	-24	270	27	151	-43	68	-51	68	.	.	-1562	36
	oak	61	64	17	66	.	.	45	61	.	.	.	.	5	87	8	106	-59	155	.	.	0	100	1	100	-9	91	.	.	1	100	6	100	18	89	46	54	-88	155	.	.	.	.	5	100	.	.	16	100	14	100	44	128	-4	126	-3	260	4	100	2	295	.	.	2	100	.	.	.	.	0	100	.	.	.	.	-4	100	19	100	1	100	-6	282	.	.	-31	122	13	100	-9	112	13	77	-6	645	3	100	.	.	.	.	-10	187	66	105	13	282	.	.	.	.	.	.	-4	352	18	81	0	11028	-16	72	32	75	19	83	6	330	-19	100	.	.	.	.	.	.	.	.	36	100	2	100	2	100	-47	112	-13	157	.	.	-2	987	5	100	-16	76	-22	138	-25	100	17	100	17	85	1	100	8	68	42	53	2	100	-35	116	9	64	11	71	-28	194	21	83	-72	87	11	84	.	.	149	172
	sweet chestnut	.	.	.	.	-6	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	58	62	0	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	65	79	41	71	36	138	-105	64	71	132	26	168	-28	153	-90	136	.	.	.	.	.	.	.	.	-1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-2	100	.	.	.	.	.	.	.	.	5	100	.	.	-36	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	39	513
	other broadleaves	-11	312	78	41	0	21799	10	151	-3	100	11	97	-45	123	60	78	-94	124	0	16378	8	344	13	171	-23	107	.	.	5	121	-130	122	43	56	59	49	-8	261	-32	127	42	84	-3	503	76	59	-144	58	93	138	78	81	1	4943	-2	541	38	70	-2	100	2	235	0	100	-12	72	-24	108	12	228	-9	78	13	75	-3	100	-8	139	-16	135	-101	114	30	94	3	216	52	112	-57	70	49	60	6	60	10	170	44	92	1	2792	25	349	19	189	-326	99	-27	78	242	61	7	217	-2	629	20	217	208	51	-54	159	-103	79	68	103	0	2209	-16	225	1	82	-89	90	28	116	4	119	6	272	70	95	31	232	0	1273	-2	160	-2	412	30	76	-104	99	-6	80	-5	137	0	3813	.	.	1	100	-5	887	108	68	6	499	0	3512	9	207	56	78	8	219	13	62	11	109	-12	238	40	81	.	.	368	154
	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
	total	-296	102	4	6099	-13	1124	-1253	42	377	62	-933	57	-512	185	-23	3389	-1008	84	-727	72	-112	127	98	137	-594	60	75	.	32	403	-315	159	-47	1339	418	74	-147	100	-594	74	879	44	345	92	628	70	1126	44	810	61	59	846	-352	120	135	255	-913	80	-233	76	140	100	-4	3319	80	154	188	141	304	54	194	59	227	87	730	39	466	67	174	233	-147	266	-294	216	-294	93	199	125	-651	54	-212	113	248	61	-287	116	288	99	70	351	178	120	-409	66	-692	69	-30	548	1651	62	-309	113	226	61	-18	700	488	34	735	27	196	71	456	47	226	89	215	70	152	83	134	143	289	44	263	94	340	50	59	219	275	74	-133	157	-134	139	-79	208	155	78	-319	68	-502	65	-232	78	-159	148	-290	116	-1	31776	683	42	664	38	540	56	190	68	-257	146	145	176	241	110	-96	299	-550	78	-654	47	-57	295	.	.	1913	176
total	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	spruce	-32	341	-13	1392	65	155	-631	59	269	65	-780	51	-725	116	-1127	43	-1083	60	-650	46	43	84	-23	211	4	1121	.	.	-40	183	-189	159	-4	9089	507	41	4	75	-695	60	767	45	453	67	197	258	475	109	222	152	-534	65	-307	64	-138	128	-1160	58	-71	67	215	49	-152	72	18	364	-149	75	267	52	122	75	514	54	333	35	277	85	56	668	-127	151	-481	88	-500	50	-64	223	-272	83	-43	255	41	58	-447	66	279	70	-74	223	137	56	-205	73	-535	52	86	174	1161	75	-577	61	43	100	18	100	6	100	117	48	14	67	213	35	74	112	268	58	-113	288	179	51	287	36	82	228	-13	699	-51	135	79	124	42	178	-88	94	-145	91	43	111	-165	64	-395	58	-159	74	-126	103	-101	86	65	64	412	64	103	256	597	48	223	46	-366	87	45	376	141	107	20	949	-685	59	-270	80	-8	830	.	.	-4927	52
	fir	-139	77	-62	109	25	140	-313	90	52	158	10	2124	463	30	331	126	169	172	-307	125	14	80	16	53	62	52	.	.	84	53	41	197	-220	148	-88	177	4	100	-25	310	85	73	-57	76	9	269	94	85	-17	100	321	73	54	404	223	89	167	120	-7	840	20	452	44	181	10	345	400	37	37	127	23	158	168	45	157	61	-39	95	48	79	218	66	-77	280	45	72	26	416	-98	120	-68	71	140	47	234	57	-49	273	12	708	1	6631	38	113	40	96	10	100	81	61	5	100	.	.	.	.	7	100	40	76	16	271	80	88	-53	176	1	100	-37	106	20	564	110	72	175	66	115	58	10	205	117	117	-33	319	-18	607	28	255	79	48	143	41	82	76	-102	77	90	69	-218	109	34	100	37	108	54	66	239	39	27	215	-34	202	-37	234	48	176	8	891	38	89	-5	100	-99	128	.	.	3377	35
	pine	-50	73	-14	72	-8	110	3	558	.	.	-17	100	-52	127	47	100	-48	105	-18	253	-2	688	58	68	24	58	.	.	3	100	-123	106	.	.	-43	114	-43	59	.	.	53	57	8	442	4	100	34	233	0	131978	14	562	1	100	59	77	.	.	-57	100	2	100	.	.	.	.	20	100	4	100	28	100	26	100	10	100	.	.	-48	102	.	.	11	100	-30	163	1	229	-6	165	-2	716	-3	515	23	88	1	100	.	.	-4	402	-41	91	9	299	.	.	-18	194	3	310	.	.	4	100	.	.	.	.	.	.	-3	100	.	.	-14	100	41	56	0	0	.	.	.	.	.	.	4	79	0	100	.	.	-8	100	.	.	1	94	.	.	4	100	.	.	.	.	-26	100	.	.	-44	114	35	139	-92	74	.	.	-6	100	16	249	-5	119	-59	95	-16	231	-99	76	11	100	.	.	-443	72
	larch	16	160	-21	91	39	115	-50	76	.	.	.	.	37	78	-16	100	-60	107	.	.	.	.	.	.	2	94	.	.	.	.	11	100	.	.	14	73	.	.	-16	72	-30	248	10	479	75	66	368	34	354	79	2	100	1	100	8	71	1	100	.	.	.	.	.	.	-2	100	.	.	.	.	.	.	4	100	2	100	7	100	16	172	0	100	-10	100	-3	381	.	.	.	.	3	100	.	.	.	.	.	.	6	100	5	100	-17	100	27	100	-25	164	55	100	125	50	59	143	.	.	0	1944	451	29	44	72	41	142	.	.	.	.	.	.	62	70	.	.	10	100	.	.	20	100	.	.	10	100	.	.	.	.	-12	100	.	.	8	113	.	.	11	100	.	.	39	100	383	42	215	74	-46	144	-15	100	8	100	-6	100	19	88	.	.	-28	71	5	100	1	1636	.	.	2213	21
	Arolla pine	.	.	.	.	.	.	.	.	.	.	.	.	19	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	71	.	.	7	100	39	94	184	50	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	3	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	93	44	-1	3298	-3	377	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	347	33
	other conifers	6	72	.	.	28	100	43	75	.	.	5	71	-2	182	.	.	159	42	1	71	.	.	.	.	.	.	75	.	.	.	.	.	.	.	.	.	.	.	0	100	-1	99	.	.	.	.	-1	112	-2	124	16	90	16	94	77	79	1	100	.	.	.	.	0	100	.	.	.	.	.	.	1	100	4	100	50	92	24	88	-3	124	0	838	.	.	9	100	2	100	25	100	18	85	.	.	5	100	.	.	1	100	.	.	.	.	0	86	.	.	.	.	.	.	.	.	.	.	.	.	31	100	1	100	.	.	.	.	.	.	1	100	.	.	3	100	.	.	.	.	-47	100	10	62	.	.	1	100	.	.	.	.	.	.	-185	100	.	.	4	100	.	.	.	.	-2	73	-1	100	1	77	.	.	.	.	5	55	14	123	3	72	.	.	.	.	.	.	.	.	398	60
	beech	-225	92	2	4858	37	209	-238	66	64	98	-63	113	14	2037	391	60	-161	179	26	786	-94	70	-99	173	-577	56	.	.	24	153	-8	1524	49	279	-2	7437	.	.	-26	421	-5	1074	20	326	-9	96	103	59	.	.	-178	120	70	194	29	323	100	59	-146	96	-48	71	62	96	-7	884	-94	124	50	135	18	64	-190	52	223	52	-74	276	247	48	-128	144	149	144	51	195	80	140	-265	60	-169	102	-67	155	4	1390	57	71	117	57	34	216	-54	89	31	378	.	.	51	70	.	.	91	45	125	73	126	49	310	44	181	44	83	101	125	77	7	100	27	162	37	134	-56	106	44	124	156	51	-3	529	27	184	37	89	-29	104	27	162	-27	265	-169	78	38	229	15	255	58	53	-14	667	-54	85	.	.	10	75	-47	178	41	101	84	37	97	58	-10	807	-26	426	39	191	-97	69	25	183	.	.	454	235
	maple	94	44	51	57	-55	63	-37	68	7	99	22	210	-18	539	139	42	190	31	120	47	12	253	16	142	-31	116	.	.	-14	146	29	57	32	116	35	67	3	100	66	106	25	128	-21	332	22	80	3	443	3	100	62	114	45	69	-17	134	-5	750	23	93	39	81	37	96	58	73	11	59	8	456	11	84	-25	198	-13	305	197	78	49	99	22	148	120	52	15	94	52	47	28	84	24	86	70	117	-16	334	12	176	35	80	50	76	-47	156	31	113	24	94	31	71	-8	100	13	74	-26	71	-3	547	11	43	57	68	26	73	5	391	25	61	1	100	-5	441	-12	126	50	118	10	126	9	78	23	94	10	100	16	82	10	87	35	96	-6	439	29	71	25	76	-6	100	.	.	64	69	8	100	18	58	128	41	-12	196	36	96	35	96	69	80	9	270	42	120	-62	77	13	227	.	.	2262	17
	ash	-16	311	-35	117	-138	64	-85	99	.	.	-81	113	-50	73	-60	161	-19	370	-30	117	-142	55	-10	200	-16	194	.	.	-32	136	48	236	149	52	-111	80	-19	100	-35	159	14	76	3	440	10	666	15	41	.	.	-152	60	-195	92	-99	56	-60	64	-5	184	-26	77	2	100	-2	141	2	100	72	129	.	.	43	99	63	193	-41	236	-5	241	-60	161	-13	451	16	158	36	57	3	398	-78	72	-2	622	-4	885	-56	113	-30	111	-137	89	-167	59	18	317	6	100	88	100	11	82	-7	115	-3	581	47	78	28	122	-45	64	26	50	28	128	9	105	.	.	-103	80	22	63	10	243	149	80	45	93	-17	87	-69	101	7	90	3	100	10	84	-24	128	-21	148	17	61	-165	77	.	.	-167	109	17	114	35	61	-27	291	-56	131	46	89	-74	74	-56	92	-23	289	27	151	-43	68	-51	68	.	.	-1834	32
	oak	61	64	17	66	.	.	45	61	.	.	.	.	5	87	8	106	-41	225	.	.	0	100	1	100	-9	91	.	.	1	100	6	100	18	89	46	54	-88	155	.	.	.	.	5	100	.	.	16	100	14	100	33	175	-4	126	-3	260	4	100	2	295	.	.	2	100	-2	100	.	.	0	100	.	.	.	.	-4	100	25	79	1	100	-6	282	.	.	-31	122	13	100	-9	112	13	77	-6	645	3	100	.	.	.	.	-10	187	66	105	13	282	.	.	-3	100	.	.	3	563	4	466	29	196	-17	69	10	321	19	83	6	330	-19	100	5	100	0	73	-1	100	.	.	37	95	2	100	5	71	-47	112	-13	157	.	.	-2	987	5	100	-16	76	-22	138	-25	100	17	100	17	85	19	84	19	49	32	75	2	100	-35	116	9	64	11	71	-28	194	21	83	-72	87	11	84	.	.	184	142
	sweet chestnut	.	.	.	.	-6	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	63	58	-1	163	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	100	138	51	43	67	-12	503	-137	64	63	193	43	136	-73	73	-57	233	.	.	.	.	.	.	.	.	-1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-2	100	.	.	.	.	.	.	.	.	5	100	.	.	-34	106	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	36	667
	other broadleaves	-11	312	78	41	0	21799	10	151	-3	100	12	87	-255	83	60	78	-83	142	11	119	8	344	14	156	-23	107	.	.	5	121	-130	122	44	55	59	49	-8	261	-32	129	20	192	70	102	22	316	-150	57	101	128	94	68	1	2573	-2	541	38	70	-2	100	4	129	0	100	-25	62	-24	108	12	228	-9	78	20	54	-3	100	1	1600	-13	167	-101	114	25	119	3	216	52	112	-57	70	49	60	6	60	27	88	44	92	1	2792	25	349	19	189	-326	99	-24	88	260	57	6	235	21	92	39	116	275	42	-48	181	-65	134	138	62	0	2209	-16	225	8	62	-118	72	30	108	-4	226	8	193	70	95	31	232	0	1273	-2	160	-2	412	30	76	-104	99	-6	80	-5	137	0	3813	2	100	1	100	1	7027	106	73	82	74	0	3512	9	207	56	78	8	219	13	62	11	109	-12	238	40	81	.	.	520	119
	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	.	.	0	0
	total	-296	102	4	6099	-13	1124	-1253	42	389	60	-891	64	-563	176	-226	353	-977	87	-847	65	-162	93	-26	789	-564	64	75	.	32	403	-315	159	67	940	418	74	-147	100	-762	62	939	42	490	75	337	155	1059	54	857	61	-321	174	-319	133	135	255	-913	80	-263	69	206	72	-4	3319	50	255	166	162	449	45	194	59	564	60	818	35	377	117	349	118	-183	214	-275	232	-426	69	199	125	-651	54	-253	96	178	94	-172	204	288	99	67	365	101	219	-409	66	-692	69	78	223	1845	55	-387	92	209	68	25	573	551	34	965	24	140	106	565	40	184	111	261	60	-69	480	72	312	380	41	367	74	463	41	59	219	273	79	-51	435	-134	139	-79	208	155	78	-319	68	-465	71	-232	78	-159	148	-340	100	-1	31776	930	37	593	61	829	43	211	62	-257	146	145	176	238	112	-81	352	-550	78	-654	47	-57	295	.	.	2588	136

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. 2283009. Birmensdorf, Swiss Federal Research Institute WSL

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