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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NFI3
total number of stems
main tree species · tree state (living/dead)
regional demarcation: forest district (2024)
unit: n/ha
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
state 2004/06
		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)	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%
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	34	29	118	26	144	26	74	22	323	16	252	16	259	7	128	9	119	11	122	14	27	54	48	39	39	33	0	.	159	30	304	16	194	15	171	21	2	95	199	17	255	9	245	11	304	10	234	7	154	9	103	14	136	19	149	17	248	11	79	42	160	19	136	22	165	39	176	25	201	30	322	15	240	18	193	19	217	27	182	15	107	24	156	12	156	27	96	23	102	33	98	37	35	31	159	16	254	12	145	16	166	23	168	27	194	33	105	22	145	16	146	18	0	.	5	85	0	99	29	30	10	48	49	36	151	26	249	21	253	20	128	21	152	17	209	18	167	30	50	39	157	21	101	31	63	33	239	11	135	32	131	28	153	21	93	66	145	31	57	25	116	37	117	10	201	12	196	10	168	20	225	30	86	26	148	29	117	24	151	29	107	32	211	26	0	.	159	2
	dead	3	51	6	52	4	48	8	46	24	42	28	27	50	12	12	22	4	30	12	21	3	72	5	72	7	47	50	.	23	33	41	35	47	28	17	29	0	.	34	22	24	18	26	24	33	18	27	18	12	20	9	25	21	40	9	36	47	31	2	98	4	56	2	98	0	.	9	45	31	29	41	30	21	34	29	44	10	34	35	28	18	50	22	33	9	32	11	38	12	55	3	68	5	50	9	45	52	39	20	38	4	56	30	60	8	81	11	58	14	33	8	37	0	.	3	75	1	99	2	55	2	60	2	73	11	43	10	70	60	29	12	39	15	38	28	28	18	38	35	73	17	27	7	97	9	68	9	33	7	50	6	63	17	43	10	85	3	97	5	93	7	48	22	18	21	26	28	17	8	41	12	53	13	40	8	38	8	42	4	51	4	98	12	38	0	.	18	4
	total	37	27	123	25	148	26	82	21	347	16	280	15	309	6	140	9	123	11	133	14	30	49	53	38	47	30	50	.	182	29	345	17	241	14	187	20	2	95	233	17	279	9	271	11	337	10	262	7	165	9	113	14	157	19	158	16	294	11	81	41	163	19	139	22	165	39	185	24	231	27	363	15	261	18	222	18	226	26	218	14	125	24	178	12	165	26	108	22	114	34	101	37	40	32	168	16	306	13	165	17	170	23	198	25	202	33	116	21	159	16	155	18	0	.	8	69	1	76	31	31	12	49	51	34	162	25	259	21	313	19	140	20	167	17	238	17	185	29	85	51	174	20	108	31	72	33	248	11	143	33	137	27	171	20	103	60	148	31	63	20	123	34	139	10	222	12	224	10	176	20	238	31	99	25	156	27	125	24	155	29	111	31	222	26	0	.	177	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	35	40	9	50	37	45	55	22	66	27	85	23	23	17	129	8	72	12	114	12	12	73	24	40	54	26	0	.	36	46	16	37	82	24	62	27	0	.	25	37	9	41	20	23	6	38	9	26	1	100	100	10	111	18	125	14	96	18	63	29	129	21	104	21	80	28	150	19	30	27	25	41	45	32	53	20	28	36	31	27	54	28	69	20	12	47	76	36	57	30	15	36	73	24	50	29	44	23	57	31	68	27	42	28	35	77	0	.	15	34	9	96	0	.	0	.	0	99	15	35	29	42	20	57	111	26	17	70	47	47	64	28	19	45	99	26	40	26	20	96	52	25	83	40	120	19	33	31	60	22	68	19	35	31	78	61	74	50	144	33	30	56	8	46	10	43	29	22	99	29	17	42	24	47	55	21	33	35	9	63	2	98	12	54	0	.	44	3
	dead	4	58	0	.	1	99	6	48	0	.	10	46	2	32	11	22	6	24	10	24	5	67	0	.	5	53	0	.	4	68	3	56	8	37	5	43	0	.	3	48	1	60	5	51	1	79	2	48	0	100	9	27	4	45	3	38	10	32	5	82	3	69	5	67	0	.	2	69	6	56	6	52	3	58	4	77	4	73	2	57	2	75	5	54	0	.	6	60	4	64	0	.	15	48	7	51	2	84	8	57	2	75	0	.	0	.	0	.	1	71	0	99	0	.	0	.	0	.	1	78	0	99	1	99	12	56	3	98	5	87	5	51	4	63	8	41	3	78	0	.	9	38	2	98	5	58	0	99	3	68	7	39	0	.	0	.	6	81	3	93	0	.	1	57	0	100	6	37	4	69	0	.	4	70	7	52	2	70	0	.	0	.	0	.	0	.	4	7
	total	38	36	9	50	38	43	62	22	66	27	95	22	25	17	140	8	78	12	124	11	17	59	24	40	60	26	0	.	40	47	19	33	90	24	68	27	0	.	28	35	10	38	25	24	7	40	10	26	1	91	110	10	116	18	128	13	106	18	68	30	132	21	110	20	80	28	152	19	36	30	31	37	48	31	57	19	32	35	34	26	56	27	73	20	12	47	82	34	61	29	15	36	88	23	57	28	46	22	65	30	70	27	42	28	35	77	0	.	17	34	10	96	0	.	0	.	0	99	16	35	29	42	20	58	123	25	21	73	52	46	69	28	23	43	106	26	43	27	20	96	61	24	85	41	125	19	34	31	63	22	75	18	35	31	78	61	80	52	146	32	30	56	9	46	10	42	35	23	103	28	17	42	28	47	62	20	35	33	9	63	2	98	12	54	0	.	47	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	14	44	13	37	11	54	5	42	3	68	1	99	9	33	2	78	7	46	13	43	18	52	17	37	20	40	0	.	7	64	6	63	0	.	11	45	46	80	0	.	24	33	27	29	3	86	21	25	60	18	15	35	0	99	7	60	9	81	12	71	8	78	10	98	0	.	4	99	0	.	38	90	3	73	5	54	0	.	18	56	5	99	3	58	24	37	5	53	13	36	12	90	30	42	17	52	0	99	3	98	6	42	6	51	24	40	0	.	11	68	7	90	0	.	0	.	7	99	0	.	0	.	2	76	9	98	3	98	33	47	11	99	0	.	0	.	0	.	6	71	0	99	12	90	4	81	0	.	13	75	0	.	8	53	0	.	0	.	25	95	0	.	56	20	47	23	28	25	0	.	9	66	18	34	5	55	19	30	18	34	30	38	8	46	0	.	15	7
	dead	7	60	2	69	3	99	0	.	0	.	0	.	3	42	0	100	1	52	1	63	3	98	0	.	4	50	0	.	0	.	4	82	0	.	2	77	2	95	0	.	2	55	5	48	0	.	3	36	17	33	2	44	0	.	1	99	2	89	1	98	0	.	5	98	0	.	0	99	0	.	1	99	5	99	0	.	0	.	2	99	0	.	1	99	1	99	0	.	4	56	3	99	5	53	7	46	0	.	3	98	1	99	1	99	2	99	0	.	2	88	1	75	0	.	0	.	1	99	0	.	0	.	0	.	2	98	0	.	2	98	2	99	0	.	0	.	0	.	8	96	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	28	6	37	8	27	0	.	1	98	2	74	2	53	1	99	0	.	2	98	1	99	0	.	3	12
	total	21	44	15	37	14	56	5	42	3	68	1	99	12	30	2	75	8	44	14	41	22	57	17	37	23	37	0	.	7	64	9	69	0	.	12	47	48	77	0	.	26	34	32	29	3	86	24	25	77	19	18	34	0	99	8	63	11	67	12	69	8	78	15	98	0	.	5	99	0	.	40	87	8	88	5	54	0	.	20	57	5	99	3	50	25	36	5	53	17	35	16	75	35	42	24	47	0	99	6	98	8	45	7	48	26	39	0	.	13	71	9	88	0	.	0	.	8	99	0	.	0	.	2	76	11	98	3	98	35	46	12	84	0	.	0	.	0	.	13	60	0	99	12	90	4	81	0	.	13	75	0	.	8	53	0	.	0	.	25	95	0	.	69	20	52	23	35	24	0	.	10	63	20	34	8	46	20	30	18	34	32	40	8	47	0	.	18	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	4	70	12	66	6	81	3	62	3	74	3	99	2	47	0	100	3	50	1	100	0	.	0	.	1	69	0	.	12	98	3	99	0	.	1	69	0	.	0	99	10	31	31	34	12	40	40	14	86	9	0	70	3	70	1	70	0	.	0	.	0	.	0	.	1	98	0	.	0	.	0	.	4	86	0	99	9	93	24	35	1	99	0	.	5	48	0	99	2	99	1	68	0	.	0	.	0	.	2	70	6	91	14	71	1	99	48	28	57	27	48	29	33	33	3	61	1	59	89	16	44	32	23	44	0	.	0	.	1	98	27	39	2	79	2	99	2	98	40	68	0	.	3	72	0	.	0	.	3	69	0	.	11	59	0	.	7	97	0	.	4	68	117	10	85	13	49	19	1	98	1	98	3	70	1	72	0	.	5	57	2	68	8	51	0	.	21	5
	dead	0	.	0	.	0	.	0	.	0	.	0	.	0	84	0	.	0	70	2	100	0	.	0	.	0	.	0	.	2	97	0	99	0	.	0	.	0	.	0	.	2	61	2	76	2	50	6	26	7	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	68	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	38	6	35	7	49	2	68	8	59	0	.	5	43	6	57	2	58	0	.	0	.	0	.	1	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	99	0	.	1	98	0	.	0	.	0	.	0	.	12	20	8	27	7	37	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	9
	total	4	70	12	66	6	81	3	62	3	74	3	99	2	41	0	100	4	50	3	100	0	.	0	.	1	69	0	.	14	98	3	89	0	.	1	69	0	.	0	99	12	34	33	33	13	37	46	14	93	9	0	70	3	70	1	70	0	.	0	.	0	.	0	.	1	98	0	.	0	.	0	.	4	86	0	99	9	93	27	32	1	99	0	.	5	48	0	99	2	99	1	68	0	.	0	.	0	.	2	70	6	91	14	71	1	99	56	27	63	26	55	28	35	33	10	53	1	59	94	16	50	31	25	44	0	.	0	.	1	98	28	38	2	79	2	99	2	98	40	68	0	.	3	72	0	.	0	.	6	77	0	.	12	55	0	.	7	97	0	.	4	68	130	10	93	13	56	18	1	98	1	98	3	70	1	72	0	.	5	57	2	68	8	51	0	.	23	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	.	0	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	84	0	100	0	.	4	33	49	15	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	99	0	.	3	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	99	0	.	2	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	98	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	20	19	25	9	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	11
	dead	0	.	0	.	0	.	0	.	0	.	0	.	0	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100	4	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	71	1	81	1	70	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	25
	total	0	.	0	.	0	.	0	.	0	.	0	.	1	57	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	84	0	100	0	.	5	33	54	15	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	99	0	.	3	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	99	0	.	2	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	98	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	20	20	24	9	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	11
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	3	51	1	69	2	99	6	50	5	98	2	69	3	59	0	.	5	27	5	85	13	98	0	.	0	.	310	.	1	98	0	.	0	.	0	.	0	.	1	99	6	67	0	.	0	.	2	64	11	38	1	61	4	84	6	67	0	.	0	.	0	.	2	98	0	.	0	.	3	99	0	.	1	99	6	71	1	99	2	78	1	99	8	99	3	88	2	99	11	88	6	59	0	.	5	81	0	.	1	99	2	99	0	.	24	85	0	.	0	.	0	.	0	.	0	.	0	.	0	99	0	.	1	99	0	.	0	.	9	72	0	.	1	99	0	.	0	.	17	96	19	58	1	98	6	72	0	.	0	.	0	.	3	69	0	.	11	97	0	.	0	.	0	100	1	100	1	57	0	.	2	98	12	51	15	73	2	84	0	.	0	.	0	.	0	.	3	13
	dead	0	.	0	.	0	.	1	99	0	.	0	.	0	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	100	0	.	0	.	0	100	2	50	0	.	0	.	1	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	96	5	80	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	31
	total	3	51	1	69	2	99	7	50	5	98	2	69	4	60	0	.	5	27	5	85	13	98	0	.	0	.	310	.	1	98	0	.	0	.	0	.	0	.	1	99	8	74	0	.	0	.	2	69	13	37	1	61	4	84	7	60	0	.	0	.	0	.	2	98	0	.	0	.	3	99	0	.	1	99	6	71	1	99	2	78	1	99	8	99	3	88	2	99	11	88	6	59	0	.	6	84	0	.	1	99	2	99	0	.	24	85	0	.	0	.	0	.	0	.	0	.	0	.	0	99	0	.	1	99	0	.	0	.	9	72	0	.	1	99	0	.	0	.	21	96	25	61	1	98	6	72	0	.	0	.	0	.	3	69	0	.	11	97	0	.	0	.	0	100	1	100	1	57	0	.	2	98	12	51	15	73	2	84	0	.	0	.	0	.	0	.	3	13
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	120	14	84	20	89	19	163	19	57	29	83	23	56	20	86	11	108	9	186	10	64	33	139	19	216	14	0	.	111	24	85	22	92	27	116	21	0	.	98	21	32	25	45	24	3	63	19	29	0	.	127	10	114	21	79	21	90	20	69	23	83	25	91	18	68	22	75	20	94	31	16	43	123	24	69	23	142	27	98	21	173	20	122	18	199	13	125	17	173	17	116	17	178	13	79	19	28	37	91	21	72	19	40	26	127	17	0	.	21	37	0	.	143	24	128	24	88	24	126	20	169	22	112	26	107	31	1	98	29	56	89	28	31	42	53	29	89	23	65	66	117	21	72	34	58	35	54	26	77	22	140	18	89	26	184	22	62	29	143	24	78	29	0	100	6	71	50	21	56	26	84	28	65	23	94	18	85	16	97	25	69	20	63	23	0	.	77	3
	dead	2	71	5	39	2	99	7	32	5	55	3	56	2	34	4	32	3	31	4	42	3	98	13	41	17	44	0	.	4	68	5	44	2	59	7	57	0	.	9	33	2	59	3	45	0	100	0	100	0	.	4	35	2	64	2	70	7	51	0	.	0	.	3	97	0	.	1	99	5	44	0	.	5	44	0	.	12	54	2	59	20	39	7	45	3	51	2	62	8	42	5	98	6	66	5	57	2	99	8	73	0	.	0	.	2	75	0	.	1	100	0	.	3	46	8	46	5	60	3	48	3	49	6	64	2	98	0	.	0	.	7	50	1	99	2	59	6	50	0	.	4	48	8	98	0	.	2	70	3	69	5	59	0	.	0	.	0	.	0	.	6	72	0	.	0	.	3	53	5	72	1	98	0	.	2	75	8	49	2	76	0	.	4	59	0	.	3	7
	total	122	14	88	19	91	19	171	19	62	30	86	23	59	20	90	11	110	9	190	10	67	32	152	17	232	15	0	.	115	24	90	22	94	27	123	21	0	.	107	20	34	24	48	24	3	61	19	29	0	.	131	10	116	21	81	21	97	19	69	23	83	25	93	20	68	22	76	20	99	30	16	43	128	24	69	23	154	28	100	21	193	19	129	19	202	13	127	17	181	17	121	18	184	13	84	19	29	35	99	23	72	19	40	26	128	17	0	.	21	37	0	.	146	24	136	23	92	24	129	20	173	22	118	27	109	31	1	98	29	56	96	28	32	43	55	29	95	23	65	66	122	21	80	33	58	35	56	25	80	21	145	18	89	26	184	22	62	29	143	24	84	29	0	100	6	71	52	21	61	26	85	28	65	23	95	18	93	16	99	25	69	20	68	22	0	.	80	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	24	21	18	26	36	28	17	40	63	66	23	40	25	18	14	19	16	22	40	17	31	37	46	29	40	23	0	.	20	59	11	36	33	23	24	41	15	68	47	23	6	36	5	38	11	43	6	33	0	100	34	18	25	29	14	32	20	25	28	35	22	30	57	44	32	65	9	35	33	23	12	42	43	53	31	23	33	38	27	30	41	28	41	25	17	42	25	40	38	27	17	33	43	22	37	26	23	32	26	44	73	35	26	37	15	42	20	72	15	57	1	99	8	40	9	48	14	39	10	47	7	57	1	76	42	36	28	64	0	.	40	37	78	30	61	24	45	36	0	.	23	29	48	86	15	52	9	39	23	27	27	20	34	33	6	97	7	72	7	93	10	52	1	66	8	39	22	18	23	43	27	47	25	38	33	28	16	24	69	45	29	51	52	55	0	.	21	4
	dead	2	60	2	69	0	.	1	99	0	.	0	.	0	57	0	.	0	100	1	70	0	.	0	.	2	69	0	.	2	98	2	99	0	.	1	99	0	.	4	62	1	100	0	.	0	.	0	100	0	.	2	46	0	.	0	.	1	70	0	.	0	.	2	98	0	.	0	.	0	.	0	.	0	.	0	.	3	60	2	51	0	.	1	99	1	99	0	.	0	.	2	98	3	73	1	99	3	56	3	99	1	99	0	.	0	.	0	.	0	.	0	.	0	.	1	99	1	70	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	69	6	55	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	75	0	.	3	97	0	.	0	.	0	.	0	.	2	51	0	.	0	.	1	99	5	59	1	99	2	99	0	.	0	.	0	.	1	13
	total	26	20	20	24	36	28	18	39	63	66	23	40	25	18	14	19	16	21	41	17	31	37	46	29	43	22	0	.	21	56	13	43	33	23	25	42	15	68	50	23	7	39	5	38	11	43	6	33	0	100	36	17	25	29	14	32	22	24	28	35	22	30	59	45	32	65	9	35	33	23	12	42	43	53	31	23	36	35	29	30	41	28	42	24	17	41	25	40	38	27	19	30	46	24	37	26	26	31	28	41	75	35	26	37	15	42	20	72	15	57	1	99	8	40	10	48	16	38	10	47	7	57	1	76	42	36	28	64	0	.	40	37	80	28	68	22	45	36	0	.	23	29	48	86	15	52	9	39	23	27	27	20	36	33	6	97	10	57	7	93	10	52	1	66	8	39	23	19	23	43	27	47	27	36	37	27	17	25	70	44	29	51	52	55	0	.	22	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	42	23	22	35	32	32	7	46	15	49	41	33	7	32	14	29	14	19	13	35	58	48	32	59	31	53	0	.	15	45	23	50	27	33	49	32	20	95	37	53	8	44	3	58	17	44	8	31	4	88	33	20	27	43	30	52	21	34	15	55	13	60	1	97	2	98	3	70	53	62	8	61	9	58	70	26	72	30	16	34	34	35	27	32	20	48	8	38	15	37	25	45	31	39	45	35	21	79	13	54	64	31	34	34	32	29	12	52	13	86	16	45	12	48	21	35	37	30	20	35	14	65	13	48	22	65	33	55	3	98	22	36	28	41	18	37	49	36	38	34	8	57	26	35	0	.	2	99	5	57	20	59	25	42	14	41	28	47	0	.	40	40	7	53	8	48	10	28	35	34	26	27	37	49	41	30	33	43	15	64	37	58	16	40	0	.	19	5
	dead	1	99	2	99	0	.	1	99	2	99	3	59	0	75	0	100	0	100	2	79	0	.	0	.	0	.	0	.	2	98	1	99	1	70	1	99	0	.	4	83	0	.	0	100	1	78	0	.	0	.	1	51	0	.	0	99	1	99	0	.	1	99	0	.	0	.	0	.	1	99	6	99	2	99	3	73	0	.	0	.	1	99	1	99	0	.	0	.	0	.	0	.	0	.	3	56	0	.	0	.	1	99	2	75	2	99	4	99	0	.	0	.	1	99	0	.	3	45	0	100	0	.	2	99	0	.	0	.	0	.	3	59	0	.	5	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	99	3	69	0	.	5	67	0	.	0	.	0	.	0	100	1	79	3	98	0	.	1	99	4	79	1	99	2	74	0	.	0	.	0	.	1	14
	total	43	22	24	36	32	32	7	44	16	52	44	32	7	32	14	29	14	19	14	38	58	48	32	59	31	53	0	.	17	41	24	48	28	33	50	31	20	95	41	55	8	44	3	54	19	45	8	31	4	88	35	20	27	43	30	52	22	35	15	55	15	57	1	97	2	98	3	70	54	61	13	74	10	65	73	27	72	30	16	34	35	34	28	33	20	48	8	38	15	37	25	45	31	39	48	35	21	79	13	54	65	31	36	32	34	31	16	55	13	86	16	45	13	45	21	35	40	29	20	34	14	65	15	48	22	65	33	55	3	98	25	35	28	41	23	37	49	36	38	34	8	57	26	35	0	.	2	99	5	57	21	60	27	41	14	41	33	47	0	.	40	40	7	53	9	46	11	27	38	31	26	27	38	48	44	29	34	42	18	57	37	58	16	40	0	.	20	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	23	42	19	49	3	73	23	30	0	.	0	99	1	48	1	87	9	20	1	70	12	42	29	90	14	53	0	.	5	58	1	99	5	56	8	43	249	24	0	.	0	100	5	72	0	100	6	56	1	100	5	32	5	50	6	65	2	66	62	59	0	.	3	98	0	.	0	.	1	99	0	.	0	99	16	89	6	61	0	99	3	61	1	99	20	26	0	99	9	44	14	53	29	52	1	77	0	.	3	99	10	40	25	45	11	33	0	.	0	.	0	.	12	39	27	28	45	26	19	68	33	40	12	42	4	68	3	98	2	98	27	63	26	71	0	.	13	74	0	.	14	73	31	35	101	43	0	.	77	47	4	87	6	42	120	43	19	81	4	95	44	53	4	47	10	42	13	32	1	98	1	98	4	51	2	80	13	63	16	37	14	40	8	52	0	.	9	8
	dead	0	.	2	99	0	.	1	99	0	.	0	.	0	.	0	.	1	52	0	.	2	97	7	98	4	75	0	.	1	99	0	.	0	99	1	99	57	59	0	.	0	.	1	99	0	.	0	100	0	.	2	48	1	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	99	0	.	0	.	0	.	3	56	0	.	2	99	2	98	1	99	0	.	0	.	0	.	0	.	2	75	0	99	0	.	0	.	0	.	0	.	3	72	7	55	0	.	1	99	1	99	0	.	2	98	0	.	3	69	1	99	0	.	0	.	0	.	2	69	5	67	12	59	0	.	1	99	0	.	3	99	0	.	1	97	0	.	0	.	0	.	0	100	1	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	98	0	.	1	16
	total	23	42	21	53	3	73	24	30	0	.	0	99	1	48	1	87	10	20	1	70	14	37	36	92	18	54	0	.	6	51	1	99	5	53	9	46	306	28	0	.	0	100	6	78	0	100	7	55	1	100	7	33	6	44	6	65	2	66	62	59	0	.	3	98	0	.	0	.	1	99	0	.	0	99	16	89	7	66	0	99	3	61	1	99	22	25	0	99	12	45	16	55	30	54	1	77	0	.	3	99	10	40	27	45	11	32	0	.	0	.	0	.	12	39	29	29	52	26	19	68	34	41	13	41	4	68	5	98	2	98	30	61	28	69	0	.	13	74	0	.	16	69	36	35	113	44	0	.	79	47	4	87	9	45	120	43	20	77	4	95	44	53	4	47	10	43	13	31	1	98	1	98	4	51	2	80	13	63	16	37	14	40	9	49	0	.	10	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	.	13	41	0	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	.	11	99	45	30	35	44	115	31	108	24	176	19	29	29	54	31	186	23	0	.	0	.	0	.	0	.	1	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	73	0	.	3	97	0	.	0	.	1	100	0	.	4	66	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	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	.	4	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	.	1	99	14	73	10	62	12	55	27	40	70	21	5	59	14	50	44	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	99	0	.	0	.	0	.	0	.	0	100	0	.	1	84	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	13
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	37	0	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	.	12	99	59	32	45	43	128	31	135	23	247	17	34	28	68	33	230	22	0	.	0	.	0	.	0	.	1	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	75	0	.	3	97	0	.	0	.	1	100	0	.	5	69	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	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	50	37	49	29	33	28	26	36	12	44	16	53	28	16	11	21	23	23	22	21	61	35	27	41	35	29	0	.	34	49	20	46	7	35	36	54	93	39	41	37	31	44	10	39	68	26	52	18	23	35	34	18	21	32	8	43	25	38	12	65	18	50	8	71	12	53	15	42	32	39	17	49	15	28	13	66	50	35	36	34	52	38	22	30	13	36	26	45	17	37	65	35	23	30	25	30	19	31	41	55	48	38	55	37	27	42	154	33	68	21	83	27	101	23	148	21	242	15	107	21	65	21	106	16	29	40	130	51	30	43	68	35	54	36	46	36	21	46	65	49	45	43	30	52	8	58	9	44	30	54	12	40	17	64	89	45	18	52	13	93	8	62	39	21	51	24	59	16	7	43	34	42	32	33	19	36	8	75	38	40	33	50	24	34	0	.	41	4
	dead	3	52	5	39	3	83	0	.	5	73	3	71	7	27	1	57	1	59	4	36	5	68	3	77	6	51	0	.	13	62	2	70	3	59	8	50	25	76	4	39	9	33	6	76	8	33	8	28	1	45	3	34	2	70	3	48	13	40	0	.	3	99	0	.	8	98	1	99	0	.	15	59	3	56	3	99	17	55	11	54	3	69	5	61	1	99	1	99	0	.	5	49	2	99	5	53	3	57	15	64	0	.	6	58	2	76	13	50	5	48	8	60	19	31	29	21	24	22	29	26	6	48	18	39	6	49	5	81	5	73	12	60	15	46	12	39	5	74	37	75	2	69	0	.	2	98	2	69	0	.	3	69	6	64	6	66	5	67	0	.	2	98	6	30	7	37	8	26	2	98	2	98	1	69	4	51	1	99	7	52	0	.	2	98	0	.	6	6
	total	53	36	54	27	36	27	26	36	17	44	20	46	34	16	11	21	24	23	26	20	65	36	30	44	41	26	0	.	46	44	21	43	10	30	44	48	118	35	45	34	40	39	16	48	77	24	60	17	25	34	37	18	23	32	11	36	38	34	12	65	21	50	8	71	20	65	16	42	32	39	32	51	18	28	16	72	67	35	47	38	55	37	27	28	14	34	27	43	17	37	70	35	25	31	30	28	22	29	57	56	48	38	61	37	29	40	167	33	73	21	91	27	120	22	177	18	265	14	135	20	71	20	124	17	35	36	135	49	34	40	81	33	69	33	58	30	26	38	102	49	47	41	30	52	10	49	11	37	30	54	14	37	23	59	95	41	23	52	13	93	10	65	45	20	57	24	68	16	8	47	35	42	33	32	24	34	9	67	45	36	33	50	25	32	0	.	47	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	1	99	0	.	0	.	1	99	0	.	3	56	3	24	0	100	0	100	1	70	0	.	0	.	0	.	0	.	4	98	2	99	0	.	2	69	0	.	1	70	2	43	1	76	5	40	1	42	2	38	0	100	0	.	0	.	1	72	0	.	0	.	0	.	0	.	0	.	0	.	2	69	1	99	0	.	3	69	1	72	1	99	0	.	0	.	0	.	0	.	0	.	2	69	1	99	0	.	0	.	0	.	2	99	0	.	0	.	2	99	0	.	1	99	1	99	4	51	2	49	0	.	3	49	0	.	0	.	2	98	18	54	3	69	1	99	2	99	0	.	0	.	2	98	0	.	0	.	0	.	0	.	0	.	3	98	0	.	0	.	0	.	2	36	2	49	2	37	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	10
	total	1	99	0	.	0	.	1	99	0	.	3	56	3	24	0	100	0	100	1	70	0	.	0	.	0	.	0	.	4	98	2	99	0	.	2	69	0	.	1	70	2	43	1	76	5	40	1	42	2	38	0	100	0	.	0	.	1	72	0	.	0	.	0	.	0	.	0	.	0	.	2	69	1	99	0	.	3	69	1	72	1	99	0	.	0	.	0	.	0	.	0	.	2	69	1	99	0	.	0	.	0	.	2	99	0	.	0	.	2	99	0	.	1	99	1	99	4	51	2	49	0	.	3	49	0	.	0	.	2	98	18	54	3	69	1	99	2	99	0	.	0	.	2	98	0	.	0	.	0	.	0	.	0	.	3	98	0	.	0	.	0	.	2	36	2	49	2	37	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	10
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	349	10	344	11	393	10	380	10	546	10	506	9	414	5	385	4	375	5	517	6	297	19	361	14	451	9	310	.	399	12	469	10	440	9	477	9	424	18	447	12	383	7	391	7	424	8	414	5	389	4	455	5	447	9	427	9	512	6	338	11	433	9	413	11	361	18	431	10	446	16	438	13	491	10	456	9	561	11	435	9	471	11	449	11	468	9	365	11	437	10	369	11	440	8	418	9	389	9	383	10	516	10	410	12	490	13	353	15	390	9	348	9	426	10	447	9	610	7	446	7	425	10	524	8	475	15	464	16	414	13	478	11	392	14	488	12	425	13	300	29	436	10	405	17	376	14	346	9	423	12	401	11	396	11	584	17	372	17	392	11	329	18	373	5	445	6	468	6	391	10	427	14	307	12	413	12	326	10	417	12	323	15	401	13	0	.	423	1
	dead	21	26	23	24	14	37	26	20	36	33	50	20	68	10	28	15	16	16	35	14	21	27	28	41	45	22	50	.	53	28	59	26	61	22	44	22	84	42	59	16	44	13	49	18	51	14	53	11	46	14	33	13	29	31	19	23	83	18	8	56	10	43	18	50	8	98	14	32	44	22	72	23	41	32	40	33	50	26	59	19	44	28	41	20	17	27	20	29	30	28	19	43	41	25	38	24	62	34	57	24	9	33	43	43	17	56	36	26	45	26	35	26	38	22	80	19	116	14	46	18	32	25	79	17	32	29	21	47	73	24	62	28	42	23	62	21	33	32	83	41	40	18	24	49	28	41	13	30	18	37	21	25	35	30	19	62	24	37	8	65	16	40	58	11	46	15	68	11	21	36	15	46	21	28	30	25	22	28	18	37	6	73	19	30	0	.	43	3
	total	370	10	367	11	407	9	405	10	582	10	557	9	482	5	413	4	391	5	552	5	318	18	388	14	496	10	360	.	453	13	529	11	501	9	520	9	508	17	507	12	427	7	440	7	475	7	467	4	435	5	488	5	476	9	446	8	594	6	346	10	443	9	431	12	368	18	446	10	490	14	510	13	531	10	495	9	611	11	494	9	515	10	490	11	486	9	385	11	467	11	389	12	481	9	456	8	451	10	439	10	525	10	453	11	507	13	389	15	434	8	383	9	463	10	527	8	726	7	492	7	457	10	603	8	507	14	485	16	487	12	539	10	434	13	550	11	458	13	384	26	476	10	430	18	404	15	359	9	441	13	422	11	431	10	603	17	396	17	400	11	345	17	430	5	491	6	536	6	412	10	442	14	329	11	443	11	348	9	435	12	330	15	420	13	0	.	466	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. 2282100. Birmensdorf, Swiss Federal Research Institute WSL

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