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
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 2009/17
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
main tree species	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	543	39	1465	27	1025	30	689	23	1664	24	1995	22	15915	8	4813	11	4567	13	2749	16	83	51	429	52	234	33	0	.	493	36	2821	22	2929	19	1762	25	4	100	3251	17	6800	12	4527	14	9605	13	13013	9	8118	10	2774	17	1577	23	1738	21	3588	15	489	44	1295	25	423	34	516	34	1627	32	1555	34	2630	21	3317	21	1435	24	1767	30	3077	18	944	26	2125	17	1441	26	678	27	619	36	330	42	308	35	1869	21	2395	18	1066	23	1082	26	811	32	1269	39	1063	25	2591	19	2065	22	57	100	68	88	4	100	655	30	158	48	710	38	919	30	1219	29	1698	25	922	27	1315	23	2360	23	763	34	185	50	1634	27	250	50	219	36	2505	17	1107	35	944	35	841	26	473	53	432	38	52	45	384	38	5989	11	6036	14	6995	11	1124	29	1012	40	654	27	1055	30	1227	27	501	36	696	38	792	31	0	.	183914	2
	dead	42	46	69	43	28	58	44	42	168	33	286	26	3279	12	512	20	221	26	345	23	23	60	70	62	76	44	0	.	85	45	356	38	721	26	164	30	0	.	618	25	683	19	483	24	1147	19	1792	17	644	19	316	25	320	35	165	29	987	30	39	68	14	76	27	54	0	.	146	36	184	36	355	31	316	28	146	43	152	41	582	24	164	48	259	36	141	30	48	61	84	54	42	55	42	49	105	34	459	41	165	39	41	55	64	67	68	55	110	52	316	30	165	32	0	.	19	72	0	.	77	64	13	76	55	55	85	44	73	50	434	30	124	37	136	36	377	29	111	41	19	81	187	32	43	100	51	53	204	31	122	50	107	44	142	42	24	100	74	76	9	100	51	42	1220	16	812	23	1278	18	115	37	99	48	68	34	49	40	34	52	42	46	20	71	80	42	0	.	24226	4
	total	585	37	1534	26	1053	29	733	22	1831	23	2281	21	19194	8	5325	11	4789	13	3093	15	106	49	499	52	310	29	0	.	578	35	3176	23	3649	17	1926	24	4	100	3868	17	7484	12	5010	14	10751	12	14805	9	8762	10	3090	17	1896	22	1903	20	4575	16	528	42	1309	25	450	34	516	34	1773	30	1739	32	2985	21	3633	21	1581	23	1920	30	3658	17	1108	27	2384	18	1582	26	726	28	703	36	371	42	350	32	1974	20	2855	19	1231	23	1123	27	875	32	1337	39	1173	24	2907	19	2229	21	57	100	87	82	4	100	732	32	172	48	765	37	1003	29	1292	29	2132	24	1046	26	1451	23	2737	22	874	32	204	51	1820	26	293	48	270	35	2709	17	1229	36	1051	33	983	26	498	51	506	39	61	44	436	35	7209	11	6849	14	8273	11	1240	28	1111	40	722	26	1104	30	1261	26	543	36	716	37	871	31	0	.	208140	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	478	43	76	61	266	38	747	39	350	30	722	30	1420	18	5180	10	3477	14	2904	15	70	63	155	43	512	29	0	.	240	43	176	45	1218	27	645	27	0	.	368	40	205	42	406	26	124	47	451	26	93	100	3863	12	1324	23	2115	20	1620	20	309	35	870	24	395	31	365	33	1256	24	224	32	233	47	621	32	482	27	231	40	440	29	457	32	912	23	102	49	686	38	396	37	79	42	632	29	727	32	575	27	512	33	479	35	395	44	288	79	16	80	261	39	108	96	0	.	0	.	4	100	309	41	429	51	228	55	620	33	42	77	338	41	507	31	137	51	1027	28	215	32	66	76	549	27	294	42	578	31	446	32	445	33	501	24	302	33	223	70	162	43	250	48	96	47	385	46	312	37	1193	23	642	31	93	46	200	42	430	24	370	32	31	59	11	100	105	57	0	.	52794	3
	dead	47	53	0	.	0	.	69	42	10	100	109	48	161	31	421	22	271	26	250	30	10	100	0	.	28	63	0	.	19	71	20	71	108	37	56	51	0	.	71	45	15	50	41	44	35	67	59	46	10	100	421	23	36	52	89	35	158	29	28	74	21	70	19	71	0	.	67	57	30	73	57	48	52	44	88	43	15	77	43	56	15	77	24	62	0	.	41	71	27	54	0	.	109	39	84	47	51	56	51	60	14	77	0	.	0	.	0	.	11	58	4	100	0	.	0	.	0	.	8	100	31	73	32	76	70	53	0	.	75	67	51	62	25	72	81	40	64	50	0	.	83	47	15	74	43	57	25	61	56	52	83	38	10	100	27	74	0	.	14	76	4	100	60	48	16	50	278	48	50	43	0	.	11	100	87	42	15	60	10	100	0	.	0	.	0	.	4689	6
	total	524	40	76	61	266	38	816	36	360	31	830	30	1581	18	5601	10	3748	13	3155	15	80	58	155	43	539	29	0	.	259	44	197	42	1327	26	701	27	0	.	439	39	221	40	447	26	159	48	510	26	103	91	4284	12	1360	23	2204	19	1777	19	337	36	891	24	414	30	365	33	1324	25	255	33	290	43	672	31	570	25	245	40	483	29	471	32	936	23	102	49	727	37	424	35	79	42	741	28	811	31	626	26	562	31	493	34	395	44	288	79	16	80	273	38	111	97	0	.	0	.	4	100	316	41	460	48	260	57	690	31	42	77	413	44	558	30	162	49	1108	27	279	32	66	76	632	26	309	44	622	30	471	31	500	31	584	23	312	33	250	64	162	43	264	47	100	46	445	44	328	36	1471	24	692	31	93	46	211	42	517	23	385	32	41	64	11	100	105	57	0	.	57483	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	111	51	57	55	88	59	70	40	18	71	5	100	542	35	106	80	253	58	342	44	69	54	85	42	146	35	0	.	14	77	42	71	0	.	84	48	64	80	0	.	613	34	469	32	146	92	1089	27	2988	19	444	43	4	100	66	60	155	83	51	76	33	87	26	100	0	.	28	100	0	.	318	91	15	100	37	60	0	.	325	56	0	.	38	59	245	40	40	56	138	42	56	81	210	51	261	48	4	100	21	100	44	41	36	59	160	46	0	.	152	75	96	92	0	.	0	.	93	100	0	.	0	.	33	72	68	86	18	100	207	50	175	100	0	.	0	.	0	.	14	77	4	100	8	100	16	80	0	.	45	60	0	.	25	58	0	.	0	.	63	100	0	.	2612	23	1056	25	962	28	0	.	35	80	102	41	31	50	175	33	86	43	103	43	27	62	0	.	16367	7
	dead	30	58	10	100	18	100	4	100	0	.	0	.	180	40	4	100	52	53	27	63	28	100	0	.	36	50	0	.	0	.	45	80	0	.	38	65	4	100	0	.	47	45	78	45	0	.	244	30	878	32	113	42	0	.	0	.	40	83	8	100	9	100	28	100	0	.	24	100	0	.	10	100	31	100	0	.	0	.	62	68	0	.	9	100	10	100	0	.	29	58	26	100	80	50	77	48	0	.	11	100	0	.	0	.	10	100	0	.	57	52	14	76	0	.	0	.	10	100	0	.	0	.	4	100	10	100	0	.	4	100	15	100	0	.	0	.	0	.	18	100	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	708	24	441	31	410	27	0	.	4	100	18	63	14	77	10	100	0	.	10	100	0	.	0	.	4053	10
	total	141	47	67	58	105	56	75	40	18	71	5	100	723	32	111	77	305	50	369	43	97	63	85	42	182	34	0	.	14	77	87	74	0	.	122	51	68	76	0	.	661	33	547	32	146	92	1333	25	3866	19	558	38	4	100	66	60	195	69	59	72	42	89	54	100	0	.	52	100	0	.	329	88	46	100	37	60	0	.	387	56	0	.	47	51	255	39	40	56	167	39	82	66	291	49	337	48	4	100	32	100	44	41	36	59	170	45	0	.	209	66	109	90	0	.	0	.	102	100	0	.	0	.	37	73	78	88	18	100	212	50	190	92	0	.	0	.	0	.	31	66	4	100	8	100	20	83	0	.	45	60	0	.	25	58	0	.	0	.	63	100	0	.	3320	21	1497	24	1373	24	0	.	39	82	121	38	45	50	185	33	86	43	113	43	27	62	0	.	20420	7
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	74	58	91	65	52	74	32	56	15	77	24	100	119	37	4	100	101	43	34	100	0	.	0	.	8	71	0	.	74	100	38	80	0	.	4	100	0	.	8	71	276	31	709	38	313	40	2481	16	4952	11	19	65	39	71	14	77	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	59	89	4	100	89	95	366	36	5	100	4	100	50	56	24	85	12	100	12	75	0	.	0	.	10	100	14	72	31	88	54	72	10	100	492	33	1103	26	779	32	536	36	30	62	25	71	2026	18	546	32	345	43	0	.	0	.	0	.	214	50	18	81	59	77	21	72	92	73	0	.	13	75	0	.	0	.	24	72	0	.	45	58	0	.	4	100	0	.	200	91	5939	11	2690	15	1513	17	8	100	4	100	43	61	27	61	0	.	35	54	8	71	32	56	0	.	27100	5
	dead	0	.	10	100	0	.	0	.	0	.	0	.	30	74	0	.	10	100	30	100	0	.	0	.	0	.	0	.	11	100	4	100	0	.	4	100	0	.	0	.	44	56	43	66	33	52	457	23	380	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	0	.	0	.	54	55	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	81	41	108	35	94	56	21	69	100	59	0	.	131	34	90	62	27	54	0	.	0	.	0	.	28	77	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	15	100	0	.	0	.	0	.	0	.	750	17	303	25	464	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3350	8
	total	74	58	100	59	52	74	32	56	15	77	24	100	149	35	4	100	111	45	63	100	0	.	0	.	8	71	0	.	85	88	42	74	0	.	8	71	0	.	8	71	320	32	753	37	346	38	2939	16	5332	11	19	65	39	71	14	77	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	70	90	4	100	89	95	420	33	5	100	4	100	50	56	24	85	12	100	12	75	0	.	0	.	10	100	14	72	31	88	54	72	10	100	573	31	1211	25	873	31	557	36	130	53	25	71	2158	18	636	33	372	43	0	.	0	.	0	.	242	47	18	81	59	77	21	72	92	73	0	.	13	75	0	.	0	.	44	75	0	.	60	54	0	.	4	100	0	.	200	91	6689	11	2992	15	1977	16	8	100	4	100	43	61	27	61	0	.	35	54	8	71	32	56	0	.	30450	4
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	.	26	70	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	41	83	4	100	20	100	360	30	2824	16	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	96	100	0	.	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	0	.	38	79	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	72	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1019	21	674	25	489	42	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5720	10
	dead	0	.	0	.	0	.	0	.	0	.	0	.	8	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	255	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	90	50	48	68	49	60	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	465	20
	total	0	.	0	.	0	.	0	.	0	.	0	.	34	63	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	41	83	4	100	20	100	370	30	3079	16	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	96	100	0	.	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	0	.	38	79	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	76	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1109	21	722	25	538	43	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6184	10
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	54	53	13	58	12	100	96	47	30	100	21	71	177	69	0	.	233	28	148	87	36	100	0	.	0	.	42	.	8	100	0	.	0	.	0	.	0	.	10	100	100	91	0	.	0	.	122	54	639	31	50	53	79	78	33	68	9	100	0	.	0	.	9	100	0	.	0	.	21	100	0	.	10	100	86	50	22	71	38	78	72	72	152	100	24	86	20	100	99	91	79	68	0	.	10	100	0	.	10	100	20	100	0	.	120	84	0	.	0	.	0	.	0	.	0	.	0	.	9	100	0	.	10	100	0	.	0	.	155	59	0	.	10	100	13	100	0	.	50	100	173	57	4	100	40	79	0	.	0	.	0	.	40	59	11	100	35	76	0	.	0	.	30	75	41	100	51	66	21	100	10	100	99	49	147	76	28	75	0	.	0	.	0	.	0	.	3680	12
	dead	0	.	0	.	0	.	10	100	10	100	0	.	21	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	60	85	0	.	0	.	21	100	140	50	0	.	0	.	10	100	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	.	0	.	0	.	0	.	0	.	0	.	10	100	39	50	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	351	27
	total	54	53	13	58	12	100	106	45	40	100	21	71	198	68	0	.	233	28	148	87	36	100	0	.	0	.	42	.	8	100	0	.	0	.	0	.	0	.	10	100	160	88	0	.	0	.	142	58	778	32	50	53	79	78	43	57	9	100	0	.	0	.	9	100	0	.	0	.	21	100	0	.	10	100	86	50	22	71	48	65	72	72	152	100	24	86	20	100	99	91	79	68	0	.	10	100	0	.	10	100	20	100	0	.	120	84	0	.	0	.	0	.	0	.	0	.	0	.	9	100	0	.	10	100	0	.	0	.	155	59	0	.	10	100	13	100	0	.	60	100	212	55	4	100	40	79	0	.	0	.	0	.	40	59	11	100	35	76	0	.	0	.	30	75	51	100	61	62	21	100	10	100	99	49	147	76	28	75	0	.	0	.	0	.	0	.	4031	12
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	1475	16	1008	23	585	25	1935	22	290	35	729	27	3546	19	3340	12	3941	10	4529	13	254	41	895	24	1832	21	0	.	566	31	771	27	1318	26	1077	26	0	.	1394	22	795	27	943	24	91	66	945	32	0	.	4234	13	1252	23	937	27	1471	23	433	28	586	32	357	26	368	30	535	27	666	34	166	46	1212	26	604	25	922	31	1391	24	1435	25	1611	21	2138	17	1207	21	1285	23	875	30	1537	20	1033	22	318	44	695	29	645	24	217	37	1032	23	0	.	367	37	0	.	1799	26	1540	27	1355	26	2980	20	2597	26	1555	29	587	36	4	100	186	61	553	34	184	43	562	33	478	29	131	75	1451	28	283	39	256	36	636	29	417	29	1058	24	728	26	360	36	215	42	167	46	274	40	80	100	211	60	1834	23	366	33	507	31	492	26	821	25	813	21	476	31	352	27	425	26	0	.	88523	3
	dead	50	69	37	50	29	74	80	36	9	100	36	52	176	26	194	30	167	26	179	33	11	100	85	48	105	34	0	.	21	57	28	75	14	71	58	53	0	.	123	36	79	47	78	39	0	.	19	71	0	.	147	29	94	53	22	71	177	45	9	100	21	70	10	100	0	.	41	50	63	61	10	100	132	48	5	100	126	62	133	37	112	37	112	40	62	41	8	71	90	51	63	80	77	46	90	46	22	83	24	87	13	76	0	.	20	71	0	.	4	100	0	.	70	44	63	50	75	56	115	42	58	71	116	58	19	71	0	.	0	.	80	50	10	100	33	65	26	62	14	76	76	51	14	78	0	.	11	100	44	91	51	61	23	61	25	86	0	.	0	.	44	66	0	.	20	100	132	42	13	75	4	100	15	78	32	58	54	52	30	58	4	100	38	62	0	.	4574	6
	total	1526	16	1045	22	614	24	2015	22	299	34	765	26	3723	19	3535	12	4108	10	4708	13	265	40	980	24	1937	21	0	.	587	30	799	27	1332	26	1135	26	0	.	1517	22	874	27	1021	24	91	66	963	32	0	.	4381	13	1346	24	959	27	1648	22	443	28	607	32	367	26	368	30	576	26	728	34	176	48	1345	27	609	25	1048	31	1524	24	1547	25	1723	21	2200	17	1215	21	1375	23	939	29	1615	20	1123	22	340	41	720	28	658	24	217	37	1052	23	0	.	371	37	0	.	1869	26	1603	27	1430	26	3095	20	2655	26	1672	29	606	36	4	100	186	61	633	35	194	42	595	34	504	28	145	75	1527	27	297	39	256	36	646	29	461	28	1110	24	750	27	386	34	215	42	167	46	318	40	80	100	231	63	1966	22	379	33	511	31	506	26	853	24	866	21	506	30	356	27	463	26	0	.	93098	3
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	587	31	250	27	495	30	198	34	396	68	301	51	1612	17	589	19	828	24	1100	19	152	46	271	28	303	30	0	.	115	53	121	40	559	27	226	41	39	79	814	24	159	34	261	52	301	46	342	37	15	74	1126	19	332	27	166	35	350	25	282	59	216	32	233	52	149	65	68	41	259	28	86	42	591	43	280	29	244	44	492	31	337	34	491	24	191	41	223	33	341	30	100	38	381	28	548	31	219	33	261	42	481	36	236	40	140	39	178	71	289	56	10	100	165	50	97	51	348	34	235	39	98	56	23	61	261	40	23	67	40	80	353	39	657	32	683	26	273	40	19	100	206	31	136	80	79	39	102	42	155	34	241	31	298	35	9	100	32	67	4	100	72	50	151	49	275	40	950	19	110	44	184	47	219	41	305	29	190	31	358	46	155	53	331	62	0	.	27171	4
	dead	13	76	10	100	0	.	23	61	0	.	32	100	62	44	0	.	84	52	10	100	0	.	13	100	10	100	0	.	4	100	20	100	11	100	19	71	0	.	53	56	0	.	0	.	10	100	0	.	0	.	81	39	20	71	0	.	21	71	10	100	0	.	20	71	0	.	0	.	10	100	0	.	0	.	0	.	14	79	24	60	10	100	23	71	38	61	0	.	0	.	0	.	57	70	19	71	0	.	21	100	0	.	0	.	0	.	12	100	10	100	0	.	0	.	11	100	21	71	10	100	0	.	0	.	0	.	0	.	0	.	10	100	10	100	39	60	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	100	24	61	0	.	10	100	0	.	11	100	0	.	0	.	64	52	0	.	0	.	27	74	44	80	14	77	10	100	0	.	0	.	0	.	1077	12
	total	600	31	260	26	495	30	221	32	396	68	333	49	1674	16	589	19	912	23	1109	19	152	46	284	27	313	29	0	.	119	52	141	45	570	26	244	39	39	79	867	23	159	34	261	52	311	46	342	37	15	74	1207	19	353	28	166	35	371	24	292	60	216	32	252	52	149	65	68	41	269	29	86	42	591	43	280	29	258	43	515	31	347	34	514	25	229	42	223	33	341	30	100	38	438	29	567	30	219	33	282	41	481	36	236	40	140	39	190	71	299	57	10	100	165	50	108	51	369	33	245	38	98	56	23	61	261	40	23	67	40	80	363	38	667	32	721	25	273	40	19	100	206	31	136	80	79	39	102	42	155	34	250	30	323	36	9	100	42	60	4	100	83	52	151	49	275	40	1015	20	110	44	184	47	247	41	349	29	204	31	368	47	155	53	331	62	0	.	28248	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	602	28	292	33	274	39	81	53	76	46	271	40	521	31	429	24	729	20	324	47	192	40	116	43	166	39	0	.	134	55	258	52	395	33	542	32	48	100	419	32	137	45	70	55	522	40	415	29	211	90	1020	19	276	42	326	35	316	34	75	59	62	78	14	77	20	71	25	71	274	57	67	47	135	35	544	30	409	42	178	39	290	41	320	33	273	52	86	40	101	41	190	42	180	42	513	36	232	80	116	50	359	31	228	33	223	35	113	50	195	100	189	54	180	41	281	38	543	29	708	30	56	52	233	45	147	55	129	55	21	100	120	42	228	41	318	44	269	44	137	43	53	50	153	39	11	100	21	100	48	67	137	62	235	39	46	47	125	53	0	.	209	44	505	41	295	44	373	25	177	38	150	33	268	46	471	34	365	35	129	49	159	58	82	43	0	.	21958	4
	dead	49	53	29	73	0	.	10	100	18	100	44	62	52	75	24	62	37	48	22	71	14	77	11	100	0	.	0	.	0	.	0	.	10	100	10	100	0	.	23	71	0	.	0	.	51	60	32	100	0	.	82	44	10	100	55	56	43	50	9	100	0	.	0	.	0	.	0	.	21	100	36	89	0	.	69	65	12	100	28	74	10	100	12	100	0	.	0	.	0	.	20	71	29	58	48	56	0	.	0	.	11	100	4	100	10	100	57	75	0	.	0	.	21	71	11	100	110	41	4	100	11	100	22	100	0	.	0	.	0	.	20	71	20	100	19	71	12	100	0	.	0	.	20	71	0	.	0	.	10	100	27	58	10	100	0	.	10	100	0	.	0	.	19	71	20	71	59	62	14	77	0	.	10	100	50	63	14	76	20	71	0	.	4	100	0	.	1534	10
	total	651	26	321	34	274	39	91	51	94	51	315	37	573	31	454	25	765	20	345	45	206	39	127	44	166	39	0	.	134	55	258	52	405	33	552	32	48	100	442	31	137	45	70	55	574	41	448	29	211	90	1102	20	286	42	381	33	359	34	85	60	62	78	14	77	20	71	25	71	295	55	102	51	135	35	613	30	421	41	206	40	300	41	332	34	273	52	86	40	101	41	210	43	209	42	561	35	232	80	116	50	370	31	232	32	233	34	170	52	195	100	189	54	200	41	292	37	652	28	712	30	67	47	255	46	147	55	129	55	21	100	140	44	248	44	337	43	281	43	137	43	53	50	173	40	11	100	21	100	58	58	164	59	245	38	46	47	135	52	0	.	209	44	524	41	315	43	432	26	191	38	150	33	278	44	521	33	380	34	148	46	159	58	86	42	0	.	23492	4
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	220	39	146	55	27	54	284	32	0	.	4	100	76	47	18	82	390	22	35	74	37	59	174	77	123	48	0	.	14	79	9	100	61	50	69	42	336	42	0	.	4	100	95	71	4	100	162	47	34	100	149	34	46	54	66	62	19	70	276	64	0	.	11	100	20	100	0	.	11	100	0	.	5	100	81	78	19	63	15	76	28	61	0	.	224	28	57	93	92	47	85	61	215	61	14	78	0	.	12	100	70	47	101	45	86	39	0	.	21	100	0	.	146	42	291	32	560	31	346	64	398	39	157	48	19	71	4	100	22	100	112	81	220	72	0	.	69	83	0	.	110	77	96	47	535	48	0	.	457	51	27	87	126	79	335	52	66	89	7	100	59	52	238	44	401	46	604	36	10	71	8	71	16	50	18	81	102	71	74	45	70	45	66	43	0	.	9815	8
	dead	21	71	21	100	0	.	29	74	0	.	0	.	0	.	0	.	20	71	0	.	9	100	40	100	28	74	0	.	14	78	0	.	10	100	29	88	53	52	0	.	0	.	10	100	0	.	10	100	0	.	24	72	4	100	9	100	0	.	31	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	100	0	.	0	.	0	.	29	58	0	.	20	100	20	100	11	100	0	.	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	20	100	41	61	151	45	80	88	52	73	11	100	0	.	0	.	0	.	31	74	10	100	0	.	0	.	0	.	0	.	11	100	65	62	0	.	68	58	0	.	19	100	22	60	4	100	0	.	19	100	0	.	10	100	24	61	0	.	0	.	8	71	0	.	36	100	0	.	0	.	4	100	0	.	1150	14
	total	242	36	168	60	27	54	313	33	0	.	4	100	76	47	18	82	410	22	35	74	46	51	214	80	151	51	0	.	28	59	9	100	71	45	98	46	389	41	0	.	4	100	105	73	4	100	172	45	34	100	172	37	50	51	74	58	19	70	306	63	0	.	11	100	20	100	0	.	11	100	0	.	5	100	81	78	40	60	15	76	28	61	0	.	253	28	57	93	112	46	105	60	226	63	14	78	0	.	12	100	70	47	101	45	90	37	0	.	21	100	0	.	166	41	332	31	711	30	425	67	450	42	167	46	19	71	4	100	22	100	143	78	230	71	0	.	69	83	0	.	110	77	106	47	600	47	0	.	525	49	27	87	145	70	357	52	70	84	7	100	78	59	238	44	410	46	627	34	10	71	8	71	24	47	18	81	138	78	74	45	70	45	70	41	0	.	10965	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	.	4	100	0	.	0	.	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	673	42	25	75	0	.	0	.	0	.	0	.	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	769	33	461	46	1578	34	1052	28	2153	22	707	29	797	31	2320	27	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	86	89	0	.	0	.	0	.	0	.	30	100	0	.	199	70	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10937	10
	dead	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	306	39	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	100	239	62	96	51	297	43	450	42	1352	26	119	56	420	42	668	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	73	0	.	0	.	0	.	0	.	20	100	0	.	49	83	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4072	12
	total	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	979	39	25	75	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	98	100	1008	33	557	43	1875	33	1501	27	3504	21	826	30	1217	34	2988	26	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	114	83	0	.	0	.	0	.	0	.	50	100	0	.	248	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15008	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	834	49	566	28	269	31	280	32	47	60	187	46	1814	18	653	23	1081	19	622	21	149	38	154	42	299	31	0	.	194	50	185	47	192	34	352	63	189	47	460	30	522	29	343	37	2259	24	2595	21	1261	33	1063	20	266	35	94	46	266	37	87	51	115	46	48	73	104	48	107	51	203	36	175	40	333	44	123	46	209	37	611	31	377	46	312	32	175	40	322	54	149	43	297	47	117	49	431	36	269	35	406	57	334	50	393	34	265	39	1077	39	1060	23	779	31	1360	25	2068	22	3497	18	2077	22	1105	21	1589	19	155	45	495	62	265	44	453	39	361	34	669	42	267	53	173	53	279	41	204	41	49	52	106	55	193	53	144	39	132	57	171	57	69	49	11	100	58	49	1652	19	1762	21	2386	17	31	58	159	46	248	39	172	44	109	43	145	38	160	41	156	37	0	.	49001	4
	dead	65	73	34	59	13	78	23	83	44	56	9	100	524	25	47	46	73	58	82	46	20	71	11	100	57	41	0	.	64	73	19	71	37	50	102	59	40	80	124	44	155	36	83	66	444	30	537	26	112	50	245	27	55	49	22	71	280	46	11	100	30	74	0	.	12	100	19	100	19	71	122	69	65	59	0	.	59	42	142	46	52	47	36	53	14	78	11	100	0	.	14	77	28	74	92	44	21	100	135	55	48	53	63	51	0	.	238	49	127	30	265	37	226	30	268	26	462	22	664	32	130	45	250	31	23	61	59	75	53	65	128	52	149	40	104	39	19	71	77	78	35	52	19	100	19	71	21	71	0	.	11	100	19	71	10	100	24	72	11	100	11	100	392	27	306	41	503	24	21	100	19	100	52	49	49	55	10	100	10	100	14	100	10	100	0	.	9121	6
	total	899	47	599	27	282	30	303	33	91	52	196	45	2338	17	700	22	1154	19	704	21	169	36	165	41	356	29	0	.	258	43	204	43	229	29	454	52	229	46	584	27	677	28	427	36	2703	23	3132	19	1373	32	1308	19	321	31	116	40	546	36	97	51	145	48	48	73	116	49	126	45	222	36	296	46	397	45	123	46	268	33	752	33	429	42	348	30	188	38	332	53	149	43	310	46	145	42	523	32	290	35	541	52	382	45	456	35	265	39	1316	36	1188	23	1044	30	1586	24	2336	21	3959	18	2740	20	1235	21	1838	19	177	42	554	61	318	42	582	35	510	30	773	39	286	50	250	51	314	37	223	42	67	42	127	49	193	53	155	37	152	58	181	55	93	49	21	100	68	49	2044	19	2068	22	2889	17	52	53	178	46	301	35	221	40	119	42	154	37	174	44	165	36	0	.	58122	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	40	50	0	.	0	.	0	.	0	.	23	61	177	27	20	71	37	44	60	47	21	100	0	.	4	100	0	.	21	100	9	100	0	.	11	100	0	.	19	71	16	50	28	54	105	46	87	38	64	51	30	58	10	100	21	100	37	64	10	100	0	.	0	.	0	.	11	100	0	.	13	75	12	100	4	100	21	70	41	65	0	.	10	100	0	.	10	100	39	71	0	.	30	74	17	64	0	.	0	.	0	.	10	100	0	.	4	100	0	.	0	.	9	100	20	100	51	73	35	53	41	62	10	100	8	100	0	.	36	59	68	39	20	71	30	58	9	100	0	.	4	100	0	.	10	100	0	.	0	.	0	.	0	.	9	100	9	100	0	.	4	100	87	34	50	41	71	37	10	100	0	.	0	.	0	.	4	100	9	100	0	.	9	100	0	.	1681	9
	total	40	50	0	.	0	.	0	.	0	.	23	61	177	27	20	71	37	44	60	47	21	100	0	.	4	100	0	.	21	100	9	100	0	.	11	100	0	.	19	71	16	50	28	54	105	46	87	38	64	51	30	58	10	100	21	100	37	64	10	100	0	.	0	.	0	.	11	100	0	.	13	75	12	100	4	100	21	70	41	65	0	.	10	100	0	.	10	100	39	71	0	.	30	74	17	64	0	.	0	.	0	.	10	100	0	.	4	100	0	.	0	.	9	100	20	100	51	73	35	53	41	62	10	100	8	100	0	.	36	59	68	39	20	71	30	58	9	100	0	.	4	100	0	.	10	100	0	.	0	.	0	.	0	.	9	100	9	100	0	.	4	100	87	34	50	41	71	37	10	100	0	.	0	.	0	.	4	100	9	100	0	.	9	100	0	.	1681	9
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	4978	16	3964	17	3096	17	4412	16	2886	21	4259	17	25770	7	15134	8	15610	8	12787	10	1041	26	2280	21	3621	17	42	.	1853	22	4420	18	6671	14	4761	17	681	36	6724	13	9652	10	7828	12	13386	11	22647	7	21158	7	14742	8	5195	16	5554	15	7793	12	2002	22	3175	18	1516	25	1546	23	3646	19	3212	22	3675	20	6393	16	3675	17	3962	21	6932	14	3945	19	5965	16	4863	15	3343	18	3233	19	2103	22	3581	17	5406	16	4022	16	3114	19	3547	18	2471	21	3594	20	3019	21	6808	13	4524	15	5822	15	5427	15	8582	13	10052	11	6184	16	7204	14	2775	23	1935	27	3006	20	3409	18	3134	20	5691	17	2354	22	868	35	4458	19	1440	26	1782	27	3817	16	2890	21	3052	20	2858	18	1628	31	1140	29	556	42	1352	28	18630	8	13753	9	17549	8	2489	21	2161	24	2343	19	3478	19	3379	16	1835	22	1715	23	2016	22	0	.	496978	1
	dead	357	26	219	30	88	38	291	22	258	30	539	24	4670	10	1223	15	971	16	1005	17	136	41	230	37	344	26	0	.	239	40	500	32	912	23	491	25	97	47	1030	19	1101	15	843	18	1824	15	3575	11	2484	14	1459	13	549	27	393	23	1742	20	154	33	97	41	105	39	12	100	307	28	327	28	604	26	618	22	311	32	419	29	1118	18	364	29	485	23	294	25	118	37	289	32	185	45	463	24	531	26	553	35	406	29	126	39	140	40	111	43	531	28	872	23	637	23	664	24	982	24	2231	18	1242	21	845	25	1195	19	214	31	132	43	606	25	555	27	380	25	682	22	240	32	137	49	424	24	121	50	192	35	260	31	320	37	289	28	290	28	118	42	131	49	33	59	144	39	3346	11	2036	15	3391	12	224	28	126	41	209	25	324	29	190	32	130	31	48	47	144	32	0	.	60343	2
	total	5335	15	4183	17	3184	17	4703	16	3144	21	4798	17	30440	7	16357	8	16581	8	13792	10	1177	25	2510	22	3965	17	42	.	2092	22	4921	18	7583	14	5252	16	778	35	7754	13	10753	10	8672	11	15210	10	26222	7	23642	7	16201	8	5744	16	5947	14	9535	12	2157	22	3272	18	1620	25	1557	24	3953	19	3540	21	4278	19	7011	16	3987	17	4381	20	8049	14	4309	18	6450	16	5156	15	3461	18	3521	19	2287	22	4044	17	5937	15	4575	16	3520	19	3673	18	2611	21	3704	20	3550	20	7680	13	5162	15	6486	15	6409	15	10814	13	11293	11	7029	16	8398	14	2989	23	2067	27	3613	20	3964	18	3514	20	6373	17	2595	22	1005	35	4883	18	1561	26	1974	27	4076	16	3210	21	3341	19	3149	18	1746	30	1271	30	589	41	1496	27	21976	7	15789	9	20940	8	2713	21	2287	24	2552	18	3802	18	3570	16	1965	22	1762	23	2160	21	0	.	557321	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. 2280871. Birmensdorf, Swiss Federal Research Institute WSL

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