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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NFI2
total number of stems
main tree species · tree state (living/dead)
regional demarcation: forest district (2024)
unit: 1000 n
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
state 1993/95
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
main tree species	tree state (living/dead)	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	dead	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
spruce	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	814	28	1252	34	1559	31	1472	23	1576	25	2592	22	17660	8	6138	10	7021	13	3356	15	161	46	299	64	412	37	10	.	1529	31	3104	21	4038	17	2457	21	15	78	3421	21	5833	14	4549	15	6016	12	11768	9	7245	11	4047	16	2209	23	2394	20	5043	15	403	58	1283	26	530	33	425	32	1374	22	1619	30	2520	22	2587	21	2178	23	1639	30	2910	18	1091	33	2666	19	1544	24	916	25	925	38	909	41	429	45	1752	25	3456	19	950	23	1576	26	1167	31	1357	37	736	29	1957	20	1489	24	0	.	90	65	4	100	404	42	109	49	440	34	847	29	1029	31	1882	27	744	29	876	24	2138	23	1065	28	403	44	1285	24	634	39	342	37	2518	17	772	31	996	34	1186	27	215	61	472	44	96	44	958	33	5033	13	5724	14	6494	12	1262	30	854	34	1108	27	1448	32	1681	26	1065	32	600	32	1452	31	0	.	194606	2
	dead	30	58	81	52	40	79	15	77	144	53	165	35	1397	16	217	38	95	57	151	40	0	.	0	.	29	58	0	.	19	71	206	55	68	45	43	47	0	.	483	28	306	27	423	38	628	24	1069	18	273	26	179	29	53	42	15	79	299	31	0	.	15	77	9	100	0	.	43	55	154	36	243	34	176	32	37	59	44	51	617	38	131	55	224	36	40	50	36	61	19	65	20	100	24	61	79	57	339	39	102	36	30	58	10	100	0	.	66	47	143	35	69	54	0	.	19	100	4	100	13	77	0	.	23	85	67	47	44	80	224	33	48	52	65	55	117	55	84	66	16	100	79	44	41	62	58	71	32	57	11	100	0	.	131	41	40	100	31	100	4	100	96	63	843	22	511	30	814	18	47	61	14	77	16	100	44	46	58	47	20	71	0	.	29	58	0	.	12740	5
	total	844	27	1333	33	1599	31	1487	23	1720	26	2757	21	19058	8	6355	10	7115	13	3507	15	161	46	299	64	442	37	10	.	1549	31	3310	22	4106	17	2500	21	15	78	3904	21	6138	14	4972	15	6644	13	12837	9	7518	11	4225	16	2262	23	2410	20	5342	15	403	58	1298	26	540	33	425	32	1418	22	1773	29	2763	21	2763	21	2215	23	1682	30	3527	18	1222	31	2890	19	1584	24	952	24	944	37	929	41	453	45	1830	24	3794	19	1051	23	1606	26	1177	31	1357	37	803	28	2100	19	1558	24	0	.	109	66	9	70	417	42	109	49	463	33	914	29	1074	31	2107	26	792	28	941	25	2255	23	1148	29	418	44	1364	24	675	39	400	37	2550	17	783	31	996	34	1316	26	255	56	504	47	100	45	1054	33	5876	12	6235	14	7307	12	1309	30	867	33	1125	27	1492	31	1739	25	1086	31	600	32	1482	31	0	.	207347	2
fir	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	512	36	111	40	269	53	880	23	411	32	720	27	1300	18	5865	10	3582	13	2825	14	49	72	138	42	388	31	0	.	191	53	184	36	1194	24	735	32	0	.	413	37	233	38	383	26	147	43	418	29	10	100	3359	13	1189	23	2113	17	1606	22	417	38	794	25	430	33	408	32	1376	26	297	31	289	44	535	33	547	24	234	40	482	27	420	32	1143	23	101	42	505	39	471	33	171	43	596	26	482	31	680	25	405	35	570	31	205	39	207	69	0	.	197	38	104	100	0	.	0	.	4	100	212	44	281	39	232	60	623	29	105	100	284	50	448	35	150	47	1076	28	164	38	23	100	601	36	338	42	496	31	288	36	336	31	569	25	319	35	157	41	448	51	228	48	251	69	404	45	258	46	1005	28	539	33	81	46	236	40	683	24	365	35	49	64	30	100	71	60	0	.	52647	3
	dead	67	52	0	.	10	100	52	52	32	71	30	54	69	42	164	29	200	36	235	27	25	61	0	.	79	43	0	.	0	.	9	100	50	55	45	60	0	.	66	67	0	.	42	51	30	100	109	48	0	.	397	28	24	85	28	73	42	63	20	100	11	100	34	76	9	100	9	100	67	53	13	75	56	56	16	100	49	54	28	74	0	.	88	38	0	.	39	60	81	72	14	77	106	50	53	47	18	71	54	48	0	.	0	.	0	.	10	100	32	72	4	100	0	.	0	.	0	.	29	82	24	73	49	81	68	47	0	.	18	63	55	59	31	59	34	59	18	71	0	.	92	60	10	100	49	67	10	100	0	.	20	71	24	61	10	100	0	.	0	.	30	75	29	58	4	100	232	37	0	.	0	.	10	100	37	74	27	58	0	.	0	.	0	.	0	.	3523	8
	total	579	33	111	40	279	51	932	23	443	33	750	27	1369	18	6028	10	3782	13	3060	14	74	56	138	42	467	30	0	.	191	53	193	35	1244	24	780	32	0	.	480	35	233	38	425	26	177	46	527	29	10	100	3757	13	1213	22	2141	17	1649	21	437	39	805	25	463	32	417	32	1385	26	364	32	302	43	591	33	564	24	283	39	510	27	420	32	1231	22	101	42	544	37	552	31	185	44	702	26	534	31	697	25	458	34	570	31	205	39	207	69	10	100	229	37	107	100	0	.	0	.	4	100	241	43	305	38	281	62	691	29	105	100	302	49	503	34	182	45	1110	28	182	37	23	100	693	33	348	42	545	32	298	36	336	31	589	25	343	34	166	41	448	51	228	48	280	66	433	43	262	46	1237	27	539	33	81	46	247	41	720	23	393	35	49	64	30	100	71	60	0	.	56170	3
pine	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	231	44	205	37	164	63	89	40	8	100	5	100	494	32	27	53	246	28	387	41	91	58	180	49	236	39	0	.	43	59	82	61	0	.	163	52	134	87	0	.	595	39	582	33	16	100	1108	25	2951	19	465	33	0	.	116	65	167	72	56	71	63	90	45	100	0	.	44	100	0	.	270	90	51	71	42	57	0	.	321	54	24	84	39	54	343	41	48	55	133	40	91	79	290	47	218	51	12	77	11	100	94	43	52	57	276	40	4	100	170	68	96	92	0	.	0	.	122	100	0	.	0	.	33	76	165	77	18	100	235	53	5	100	0	.	0	.	0	.	23	85	4	100	76	95	20	83	0	.	55	65	0	.	59	51	4	100	0	.	47	100	0	.	3127	22	1408	25	1097	27	0	.	39	82	167	37	60	52	229	32	132	44	186	38	59	46	0	.	18945	7
	dead	39	79	45	70	0	.	0	.	0	.	0	.	122	60	4	100	0	.	4	100	13	75	0	.	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	87	55	52	70	0	.	197	38	496	33	59	52	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	0	.	10	100	27	100	0	.	0	.	13	100	0	.	0	.	4	100	0	.	9	100	32	76	24	72	28	63	0	.	43	100	0	.	0	.	0	.	19	100	32	89	4	100	0	.	0	.	0	.	0	.	0	.	0	.	10	100	0	.	10	100	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	71	0	.	10	100	0	.	0	.	0	.	0	.	550	30	233	34	207	29	0	.	10	100	0	.	14	77	0	.	4	100	0	.	0	.	0	.	2470	12
	total	271	40	249	39	164	63	89	40	8	100	5	100	616	31	31	48	246	28	391	40	104	58	180	49	236	39	0	.	43	59	92	64	0	.	163	52	134	87	0	.	682	39	634	33	16	100	1304	25	3447	19	524	33	0	.	116	65	167	72	56	71	63	90	64	100	0	.	44	100	0	.	281	88	78	76	42	57	0	.	334	54	24	84	39	54	347	41	48	55	142	38	123	64	314	44	247	52	12	77	53	100	94	43	52	57	276	40	23	85	202	71	100	89	0	.	0	.	122	100	0	.	0	.	33	76	175	75	18	100	245	52	15	100	0	.	0	.	0	.	23	85	4	100	76	95	20	83	0	.	75	63	0	.	68	53	4	100	0	.	47	100	0	.	3678	21	1641	25	1304	25	0	.	49	85	167	37	74	48	229	32	136	43	186	38	59	46	0	.	21415	6
larch	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	64	56	214	65	48	82	60	68	4	100	26	100	89	39	13	74	186	55	50	100	0	.	0	.	13	76	0	.	90	100	49	80	0	.	39	90	0	.	4	100	423	34	492	27	257	52	1779	16	3488	11	8	71	29	78	10	100	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	7	100	8	71	61	93	314	35	6	100	0	.	108	47	4	100	20	100	4	100	0	.	0	.	0	.	15	72	31	88	69	73	10	100	192	32	671	27	329	38	278	41	35	74	16	60	1293	20	555	38	308	44	0	.	0	.	4	100	92	46	18	81	17	100	12	100	33	100	0	.	9	100	0	.	0	.	30	100	0	.	78	55	0	.	0	.	0	.	0	.	4838	12	2528	16	1344	18	8	100	4	100	22	71	19	79	0	.	45	62	20	82	45	60	0	.	20936	5
	dead	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	74	71	70	28	71	351	25	190	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	80	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	100	0	.	0	.	61	54	60	46	29	74	11	100	77	59	0	.	80	55	39	80	48	53	0	.	0	.	0	.	10	100	0	.	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	100	0	.	0	.	0	.	0	.	581	26	153	32	223	44	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	0	.	2159	11
	total	64	56	214	65	48	82	60	68	4	100	26	100	89	39	13	74	186	55	79	100	0	.	0	.	13	76	0	.	90	100	49	80	0	.	39	90	0	.	4	100	453	35	563	26	285	48	2129	16	3679	11	8	71	29	78	10	100	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	7	100	8	71	61	93	354	38	6	100	0	.	108	47	4	100	20	100	4	100	0	.	0	.	0	.	15	72	35	80	69	73	10	100	252	32	731	27	359	36	289	40	112	58	16	60	1374	21	594	40	356	43	0	.	0	.	4	100	102	42	18	81	27	100	12	100	33	100	0	.	9	100	0	.	0	.	30	100	0	.	99	56	0	.	0	.	0	.	0	.	5419	12	2681	16	1567	19	8	100	4	100	22	71	19	79	0	.	45	62	20	82	55	53	0	.	23094	5
Arolla pine	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	0	.	0	.	0	.	0	.	0	.	0	.	8	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	100	4	100	0	.	189	38	2280	17	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	98	100	0	.	24	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	930	25	518	28	268	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4371	12
	dead	0	.	0	.	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	145	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	33	52	39	82	24	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	256	26
	total	0	.	0	.	0	.	0	.	0	.	0	.	12	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	100	4	100	0	.	199	38	2425	17	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	98	100	0	.	24	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	964	25	557	28	293	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4628	12
other conifers	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	19	71	8	71	30	100	91	86	20	100	10	100	9	100	0	.	229	33	109	100	75	100	0	.	0	.	87	.	22	72	0	.	0	.	0	.	0	.	10	100	121	51	21	100	0	.	0	.	420	44	10	100	59	63	49	81	0	.	0	.	0	.	9	100	0	.	0	.	31	100	0	.	10	100	44	80	10	100	28	100	12	100	38	100	22	85	20	100	59	85	40	61	0	.	0	.	0	.	10	100	20	100	0	.	68	77	0	.	0	.	0	.	0	.	0	.	0	.	4	100	0	.	0	.	10	100	0	.	94	57	0	.	10	100	0	.	0	.	68	100	163	67	18	100	20	71	0	.	0	.	0	.	17	80	0	.	141	100	0	.	0	.	134	100	10	100	21	71	0	.	10	100	62	59	137	68	14	77	0	.	0	.	0	.	0	.	2754	14
	dead	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	79	63	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	100	52
	total	19	71	8	71	30	100	91	86	20	100	10	100	9	100	0	.	229	33	109	100	75	100	0	.	0	.	87	.	22	72	0	.	0	.	0	.	0	.	10	100	121	51	21	100	0	.	0	.	499	43	10	100	59	63	49	81	0	.	0	.	0	.	9	100	0	.	0	.	31	100	0	.	10	100	44	80	10	100	28	100	12	100	38	100	22	85	20	100	59	85	50	60	0	.	0	.	0	.	10	100	20	100	0	.	68	77	0	.	0	.	0	.	0	.	0	.	0	.	4	100	0	.	0	.	10	100	0	.	94	57	0	.	10	100	0	.	0	.	68	100	173	64	18	100	20	71	0	.	0	.	0	.	17	80	0	.	141	100	0	.	0	.	134	100	10	100	21	71	0	.	10	100	62	59	137	68	14	77	0	.	0	.	0	.	0	.	2854	15
beech	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	2278	16	1101	22	896	25	2085	21	358	34	846	27	3535	20	3311	13	5377	11	4773	13	367	33	1022	24	1900	21	0	.	629	34	977	26	1376	30	1414	24	0	.	1552	26	728	31	930	26	77	66	795	32	0	.	4315	12	1412	25	954	23	1573	21	302	32	583	30	421	33	324	31	617	26	911	34	182	53	1590	28	545	32	1103	34	1260	24	1482	25	1854	21	2530	18	1318	22	1628	22	745	26	1929	20	1189	24	277	38	629	26	432	25	362	32	923	22	0	.	267	41	0	.	1658	29	1486	27	1237	28	2264	24	1976	27	1602	28	547	34	4	100	177	66	635	36	291	45	597	33	530	32	88	70	1195	25	354	41	311	36	567	28	526	28	1251	25	576	28	614	32	324	35	172	45	513	34	0	.	131	85	1838	23	306	32	574	36	439	30	913	25	1051	23	573	32	420	29	348	28	0	.	94072	2
	dead	34	59	20	71	0	.	40	61	28	58	21	100	148	37	14	77	44	46	92	37	0	.	59	53	51	46	0	.	39	100	31	75	22	71	30	74	0	.	87	37	49	53	29	74	0	.	9	100	0	.	149	32	20	100	10	100	10	100	0	.	0	.	0	.	0	.	0	.	13	75	0	.	37	59	0	.	48	56	38	79	95	45	40	64	40	50	20	71	19	71	39	80	99	55	61	71	0	.	12	100	0	.	0	.	14	77	0	.	19	71	0	.	69	63	19	100	73	72	29	87	51	52	34	59	19	71	0	.	0	.	0	.	0	.	0	.	11	100	0	.	41	50	30	100	0	.	10	100	9	100	9	100	10	100	0	.	0	.	0	.	0	.	0	.	0	.	58	62	21	71	21	71	0	.	0	.	34	89	14	78	10	100	9	100	0	.	2209	9
	total	2311	16	1121	22	896	25	2125	21	386	34	867	28	3683	19	3325	13	5421	11	4865	13	367	33	1081	24	1950	21	0	.	668	34	1008	26	1398	30	1444	24	0	.	1639	25	777	30	959	26	77	66	804	32	0	.	4464	12	1432	25	964	23	1583	21	302	32	583	30	421	33	324	31	617	26	924	34	182	53	1628	28	545	32	1151	33	1298	24	1577	25	1894	21	2570	18	1338	22	1647	22	785	27	2028	20	1249	25	277	38	642	26	432	25	362	32	937	22	0	.	286	40	0	.	1726	29	1505	28	1310	28	2292	23	2028	27	1636	28	565	34	4	100	177	66	635	36	291	45	597	33	541	32	88	70	1236	25	384	41	311	36	577	28	536	27	1260	25	585	29	614	32	324	35	172	45	513	34	0	.	131	85	1896	23	327	32	595	37	439	30	913	25	1085	23	586	31	430	29	357	28	0	.	96281	2
maple	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	546	22	199	32	165	35	288	45	283	59	245	38	1273	17	480	21	439	23	926	19	83	47	298	31	214	31	0	.	107	59	106	53	385	26	140	39	20	71	626	29	135	44	67	47	271	43	193	39	21	100	927	16	288	35	112	39	260	28	86	42	119	35	154	57	145	75	67	38	271	28	102	52	315	46	200	29	170	38	486	34	262	36	653	26	190	46	158	56	256	30	190	34	417	28	339	37	233	36	161	54	445	49	126	38	124	51	83	89	49	100	10	100	57	47	75	58	151	43	131	68	62	53	0	.	215	42	47	69	21	100	303	44	473	38	529	27	296	64	0	.	225	34	111	88	61	63	61	47	114	34	199	25	232	50	19	100	30	58	11	100	62	73	70	71	124	44	558	25	147	45	121	51	204	36	385	34	172	31	270	53	142	53	71	63	0	.	20658	4
	dead	4	100	0	.	0	.	20	71	0	.	0	.	47	66	0	.	0	.	19	71	0	.	0	.	10	100	0	.	0	.	0	.	0	.	0	.	0	.	50	66	0	.	0	.	0	.	0	.	0	.	50	53	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	100	0	.	0	.	0	.	0	.	19	71	0	.	14	100	0	.	0	.	11	100	0	.	24	61	14	100	9	100	0	.	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	58	0	.	10	100	0	.	0	.	0	.	0	.	0	.	9	100	0	.	10	100	4	100	10	100	0	.	0	.	0	.	0	.	29	58	0	.	0	.	0	.	4	100	20	71	0	.	0	.	0	.	0	.	445	17
	total	550	22	199	32	165	35	307	43	283	59	245	38	1320	17	480	21	439	23	945	19	83	47	298	31	224	31	0	.	107	59	106	53	385	26	140	39	20	71	676	27	135	44	67	47	271	43	193	39	21	100	977	16	288	35	112	39	260	28	86	42	119	35	154	57	145	75	67	38	280	28	102	52	315	46	200	29	170	38	504	34	262	36	667	26	190	46	158	56	267	30	190	34	441	27	354	36	242	35	161	54	455	48	126	38	124	51	83	89	49	100	10	100	57	47	75	58	162	43	131	68	62	53	0	.	215	42	47	69	21	100	303	44	502	37	529	27	306	62	0	.	225	34	111	88	61	63	61	47	124	32	199	25	242	49	23	86	40	61	11	100	62	73	70	71	124	44	587	26	147	45	121	51	204	36	389	34	192	31	270	53	142	53	71	63	0	.	21103	4
ash	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	487	25	291	37	187	35	143	43	76	60	414	36	374	32	513	24	540	23	292	40	286	47	168	71	181	56	0	.	45	60	185	57	472	34	310	38	39	79	426	50	126	46	40	66	393	57	306	35	208	87	1251	21	355	54	280	38	234	45	76	83	97	79	14	77	0	.	14	100	299	51	116	68	105	50	572	30	401	38	205	44	223	43	425	34	166	46	31	57	99	51	179	50	287	47	419	42	198	86	88	55	296	35	226	34	245	34	90	76	81	89	38	79	102	50	203	40	625	32	206	44	57	52	180	54	94	73	82	59	33	100	146	39	82	55	124	52	324	37	62	59	73	60	90	42	0	.	21	100	62	58	279	57	249	46	42	51	157	45	0	.	366	52	197	36	218	48	406	30	284	44	154	31	221	48	298	33	297	39	106	57	163	43	68	49	0	.	19683	5
	dead	0	.	10	100	0	.	0	.	0	.	42	61	10	100	0	.	10	100	20	100	0	.	0	.	0	.	0	.	0	.	10	100	26	72	20	71	0	.	58	70	0	.	0	.	10	100	0	.	0	.	49	45	0	.	10	100	16	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	71	0	.	0	.	10	100	0	.	0	.	0	.	0	.	0	.	28	74	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	52	68	0	.	0	.	0	.	0	.	0	.	0	.	10	100	9	100	9	100	11	100	0	.	0	.	10	100	0	.	0	.	0	.	38	78	19	71	10	100	0	.	0	.	0	.	0	.	0	.	15	100	21	100	0	.	0	.	0	.	20	100	19	100	0	.	0	.	0	.	623	16
	total	487	25	301	38	187	35	143	43	76	60	455	36	384	32	513	24	549	23	313	42	286	47	168	71	181	56	0	.	45	60	195	56	498	34	331	37	39	79	484	51	126	46	40	66	403	56	306	35	208	87	1300	20	355	54	291	38	249	46	76	83	97	79	14	77	0	.	14	100	299	51	116	68	105	50	592	31	401	38	205	44	234	42	425	34	166	46	31	57	99	51	179	50	315	44	429	41	198	86	88	55	296	35	226	34	245	34	90	76	81	89	38	79	122	48	203	40	677	32	206	44	57	52	180	54	94	73	82	59	33	100	156	39	91	51	133	50	335	37	62	59	73	60	100	41	0	.	21	100	62	58	317	58	268	44	52	45	157	45	0	.	366	52	197	36	218	48	420	30	305	41	154	31	221	48	298	33	318	37	125	53	163	43	68	49	0	.	20306	5
oak	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	301	36	286	47	48	60	325	37	0	.	4	100	65	53	28	87	572	22	15	100	79	39	184	92	158	57	0	.	41	49	9	100	90	50	120	47	889	42	0	.	4	100	101	86	4	100	241	58	34	100	252	33	82	45	71	79	82	81	286	62	0	.	21	71	0	.	0	.	11	100	0	.	5	100	127	89	57	66	0	.	29	61	10	100	273	27	27	64	70	51	54	65	234	58	24	61	0	.	19	100	92	48	205	47	129	35	0	.	0	.	0	.	126	45	289	34	673	27	370	68	361	54	148	48	15	75	23	100	14	100	212	62	153	70	0	.	82	78	0	.	131	74	172	38	481	50	0	.	597	47	28	87	90	42	418	48	64	78	0	.	206	56	149	45	260	46	304	31	5	100	8	71	22	69	18	80	63	46	60	40	72	45	51	57	0	.	11422	8
	dead	9	100	20	71	0	.	10	100	0	.	0	.	12	100	10	100	10	100	0	.	11	100	20	100	0	.	0	.	0	.	0	.	13	100	0	.	59	62	0	.	0	.	20	100	0	.	19	71	0	.	29	75	0	.	0	.	0	.	11	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	100	0	.	10	100	0	.	0	.	19	71	0	.	50	100	10	100	11	100	0	.	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	0	.	10	100	130	57	10	100	19	71	0	.	0	.	0	.	0	.	10	100	10	100	0	.	0	.	0	.	11	100	11	100	28	58	0	.	28	100	0	.	0	.	27	100	0	.	0	.	24	62	0	.	20	71	0	.	0	.	0	.	0	.	10	100	0	.	10	100	0	.	10	100	0	.	745	17
	total	311	35	307	47	48	60	335	38	0	.	4	100	77	47	38	73	582	22	15	100	89	36	204	93	158	57	0	.	41	49	9	100	103	55	120	47	948	43	0	.	4	100	121	88	4	100	261	57	34	100	281	32	82	45	71	79	82	81	297	63	0	.	21	71	0	.	0	.	11	100	0	.	5	100	144	90	57	66	10	100	29	61	10	100	292	27	27	64	120	63	64	70	245	60	24	61	0	.	19	100	92	48	215	46	129	35	0	.	0	.	0	.	126	45	299	35	803	29	380	69	380	52	148	48	15	75	23	100	14	100	222	63	163	69	0	.	82	78	0	.	142	69	182	38	509	50	0	.	625	47	28	87	90	42	444	49	64	78	0	.	230	52	149	45	280	46	304	31	5	100	8	71	22	69	28	86	63	46	70	41	72	45	61	59	0	.	12168	8
sweet chestnut	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	915	42	29	66	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	70	100	532	30	440	48	1167	36	1252	25	3141	21	466	31	828	35	2533	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	64	86	0	.	20	100	0	.	0	.	51	100	0	.	193	57	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11702	9
	dead	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	96	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	100	89	100	45	55	139	67	266	42	666	26	47	56	108	49	352	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	0	.	0	.	5	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1831	15
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1011	41	29	66	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	79	100	621	36	485	47	1306	36	1518	26	3808	20	513	31	935	35	2886	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	74	87	0	.	20	100	0	.	0	.	51	100	0	.	198	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13533	9
other broadleaves	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	569	33	741	28	287	39	203	42	91	55	157	50	1431	19	565	32	839	28	525	24	318	37	172	52	312	35	0	.	208	53	210	34	221	33	320	41	110	56	481	31	489	31	271	43	1021	25	2537	19	1377	37	1244	19	215	31	100	47	609	40	70	54	133	50	79	89	106	76	131	43	182	45	244	50	195	34	98	90	558	43	654	32	377	45	388	31	97	39	169	54	139	40	443	39	262	35	252	32	198	34	375	60	431	39	371	40	253	48	770	37	679	27	377	32	1206	27	1597	24	3099	19	2079	23	689	29	1360	22	169	42	413	60	176	41	407	36	514	36	363	36	75	47	188	58	302	46	245	58	48	52	74	47	191	62	109	40	182	59	190	60	93	53	21	100	48	69	1520	22	1098	29	1929	19	71	51	143	45	187	34	186	36	32	58	350	37	135	67	95	42	0	.	43235	4
	dead	62	63	39	62	0	.	0	.	45	60	0	.	308	30	96	64	20	71	61	48	20	71	11	100	19	71	0	.	45	81	47	52	31	100	45	46	10	100	29	74	19	71	60	71	240	39	306	28	45	61	131	37	77	57	26	71	97	46	25	100	0	.	0	.	0	.	0	.	0	.	89	67	41	71	10	100	50	60	63	54	0	.	10	100	0	.	21	71	19	71	0	.	40	50	0	.	53	82	23	100	80	71	10	100	10	100	43	51	83	48	11	100	172	60	102	34	267	33	251	29	89	53	125	39	0	.	10	100	20	71	64	67	9	100	83	55	54	54	87	100	23	61	0	.	19	71	10	100	20	71	19	71	29	100	0	.	20	71	0	.	58	100	271	40	135	39	78	40	0	.	0	.	0	.	30	58	39	61	24	84	29	100	140	84	0	.	4846	8
	total	630	34	780	27	287	39	203	42	135	50	157	50	1739	18	661	29	859	28	586	23	338	37	183	51	331	34	0	.	253	53	257	32	252	32	365	38	120	56	510	32	507	31	331	47	1261	25	2843	18	1422	37	1375	19	292	31	126	43	706	38	95	50	133	50	79	89	106	76	131	43	182	45	334	52	236	36	108	82	608	42	717	32	377	45	398	30	97	39	190	49	158	36	443	39	302	33	252	32	251	34	398	62	512	36	380	41	262	47	812	36	762	27	388	33	1378	27	1699	23	3366	19	2330	22	777	29	1485	21	169	42	423	60	196	43	471	35	524	36	446	32	129	42	275	68	325	43	245	58	67	51	84	43	210	57	128	38	211	63	190	60	113	47	21	100	106	84	1791	23	1233	29	2007	18	71	51	143	45	187	34	216	37	72	42	374	36	164	61	235	61	0	.	48081	4
indeterminable	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	dead	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	living	5821	13	4409	17	3653	19	5636	14	2826	22	5020	18	26238	7	16939	8	19031	8	13258	10	1508	25	2461	23	3815	18	97	.	2906	23	4906	17	7774	14	5699	15	1206	38	6933	16	8690	12	7439	12	8201	11	20250	8	18062	8	15879	8	5837	16	6198	14	9574	12	1696	25	3073	18	1702	25	1411	26	3623	17	3622	21	3723	20	5499	16	4361	17	4258	20	6659	15	3927	20	7216	15	5374	15	3196	17	3801	18	2828	21	4445	16	4675	18	5054	17	2663	19	3987	18	2784	21	3591	19	1944	22	4603	14	2891	18	4593	17	5027	16	9073	13	7430	13	4917	17	6837	14	2684	22	1721	27	2959	22	2991	20	2568	22	4843	19	2547	22	888	34	3979	17	2046	24	1778	24	3530	16	2684	20	3431	19	3051	19	1658	27	1750	29	575	39	2402	24	16453	8	12278	10	15456	9	2623	22	1988	23	2668	18	4148	18	3905	17	2650	21	1766	23	2261	25	0	.	495030	1
	dead	245	30	216	31	50	67	136	34	249	37	258	28	2118	13	505	23	378	32	613	20	68	42	90	43	187	29	0	.	103	64	312	39	210	34	183	32	69	55	773	22	491	21	697	28	936	20	2166	12	1230	17	1042	16	174	34	90	49	465	24	55	61	26	61	62	54	9	100	53	49	242	30	356	29	338	27	100	43	190	29	827	30	236	37	376	25	103	30	115	37	207	40	124	42	355	31	245	32	419	41	234	33	124	49	30	58	23	61	208	29	457	27	162	38	411	37	492	27	1203	19	459	21	330	29	632	23	164	31	54	68	273	30	207	35	154	33	254	35	187	44	103	86	257	34	102	49	154	51	62	47	97	53	87	50	264	32	90	56	62	63	4	100	208	50	2308	15	1095	19	1686	15	89	43	44	56	26	73	138	33	199	35	91	42	39	79	198	61	0	.	31948	3
	total	6066	13	4624	17	3703	19	5772	14	3075	22	5278	18	28356	7	17444	8	19408	8	13871	10	1576	25	2551	23	4002	18	97	.	3009	23	5218	17	7985	14	5882	15	1275	38	7707	16	9181	12	8136	12	9137	11	22417	8	19292	8	16921	8	6011	16	6289	14	10039	12	1751	25	3099	18	1764	25	1421	26	3675	17	3864	20	4079	20	5837	16	4461	17	4448	20	7486	14	4164	19	7592	15	5477	14	3311	17	4008	18	2952	21	4800	17	4919	17	5472	17	2897	19	4112	18	2814	21	3614	19	2152	21	5060	14	3053	18	5004	17	5519	16	10276	13	7888	13	5247	18	7469	14	2848	22	1775	27	3231	22	3198	20	2722	22	5097	19	2734	22	991	34	4236	17	2148	24	1933	25	3591	16	2781	20	3518	19	3315	19	1749	27	1811	30	579	39	2610	24	18761	8	13373	10	17142	9	2712	21	2032	23	2694	18	4285	18	4104	16	2741	21	1805	23	2458	24	0	.	526978	1

Table citation

Abegg, M.; Ahles, P.; Allgaier Leuch, B.; Cioldi, F.; Didion, M.; Düggelin, C.; Fischer, C.; Herold, A.; Meile, R.; Rohner, B.; Rösler, E.; Speich, S.; Temperli, C.; Traub, B.,
2023: Swiss national forest inventory - Result table No. 2282077. Birmensdorf, Swiss Federal Research Institute WSL

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